{"pageNumber":"262","pageRowStart":"6525","pageSize":"25","recordCount":46679,"records":[{"id":70211941,"text":"70211941 - 2020 - Geophysical characterization of a Proterozoic REE terrane at Mountain Pass, eastern Mojave Desert, California","interactions":[],"lastModifiedDate":"2020-08-12T20:06:20.547455","indexId":"70211941","displayToPublicDate":"2019-12-19T15:00:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Geophysical characterization of a Proterozoic REE terrane at Mountain Pass, eastern Mojave Desert, California","docAbstract":"

Mountain Pass, California (USA), located in the eastern Mojave Desert, hosts one of the world’s richest rare earth element (REE) deposits. The REE-rich terrane occurs in a 2.5-km-wide, northwest-trending belt of Mesoproterozoic (1.4 Ga) stocks and dikes, which intrude a larger Paleoproterozoic (1.7 Ga) metamorphic block that extends ∼10 km southward from Clark Mountain to the eastern Mescal Range. To characterize the REE terrane, gravity, magnetic, magnetotelluric, and whole-rock physical property data were analyzed. Geophysical data reveal that the Mountain Pass carbonatite body is associated with an ∼5 mGal local gravity high that is superimposed on a gravity terrace (∼4 km wide) caused by granitic Paleoproterozoic host rocks. Physical rock property data indicate that the Mountain Pass REE suite is essentially nonmagnetic at the surface with a magnetic susceptibility of 2.0 × 10−3 SI (n = 57), and lower-than-expected magnetizations may be the result of alteration. However, aeromagnetic data indicate that the intrusive suite occurs along the eastern edge of a distinct northwest-trending aeromagnetic high along the eastern Mescal Range. The source of this magnetic anomaly is ∼1.5–2 km below the surface and coincides with an electrical conductivity zone that is several orders of magnitude more conductive than the surrounding rock. The source of the magnetic anomaly is likely a moderately magnetic pluton. Combined geophysical data and models suggest that the carbonatite and its associated REE-enriched ultrapotassic suite were preferentially emplaced along a northwest-trending zone of weakness, which has potential implications for regional mineral exploration.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02066.1","usgsCitation":"Denton, K., Ponce, D.A., Peacock, J., and Miller, D., 2020, Geophysical characterization of a Proterozoic REE terrane at Mountain Pass, eastern Mojave Desert, California: Geosphere, v. 16, no. 1, p. 456-471, https://doi.org/10.1130/GES02066.1.","productDescription":"16 p.","startPage":"456","endPage":"471","ipdsId":"IP-097916","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":458330,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02066.1","text":"Publisher Index Page"},{"id":377423,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mountain Pass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.04583740234374,\n 35.0254981588326\n ],\n [\n -115.103759765625,\n 35.0254981588326\n ],\n [\n -115.103759765625,\n 35.628279555648845\n ],\n [\n -116.04583740234374,\n 35.628279555648845\n ],\n [\n -116.04583740234374,\n 35.0254981588326\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Denton, Kevin 0000-0001-9604-4021","orcid":"https://orcid.org/0000-0001-9604-4021","contributorId":207718,"corporation":false,"usgs":true,"family":"Denton","given":"Kevin","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":795899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ponce, David A. 0000-0003-4785-7354 ponce@usgs.gov","orcid":"https://orcid.org/0000-0003-4785-7354","contributorId":1049,"corporation":false,"usgs":true,"family":"Ponce","given":"David","email":"ponce@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":795900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":795901,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":140769,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":795902,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210758,"text":"70210758 - 2020 - Postmortem evaluation of reintroduced migratory whooping cranes (Grus americana) in eastern North America","interactions":[],"lastModifiedDate":"2023-06-21T16:54:08.35167","indexId":"70210758","displayToPublicDate":"2019-12-19T10:17:53","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3768,"text":"Wildlife Disease","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Postmortem evaluation of reintroduced migratory whooping cranes (Grus americana) in eastern North America","title":"Postmortem evaluation of reintroduced migratory whooping cranes (Grus americana) in eastern North America","docAbstract":"

We reviewed necropsy records of 124 Whooping Cranes (Grus americana) recovered following reintroduction of 268 individuals from 2001 to 2016 in the eastern US. Causes of death were determined in 62% (77/124) of cases facilitated by active monitoring that limited decomposition and scavenging artifact. The greatest proportions of mortality were caused by predation (0.468; 95% confidence interval 0.356–0.580; 36/77), collision with power lines or vehicles (0.260; 0.162–0.358; 20/77), and gunshot (0.169; 0.085–0.253; 13/77). Six deaths were attributed to infection (0.078; 0.018–0.138; 6/77), including bacterial and fungal etiologies. Lead analysis of 50 liver samples yielded two results with elevated concentrations (3.65 and 10.97 ppm wet weight), and 10 bone samples from partial carcasses lacking suitable liver tissue resulted in one elevated result (48.82 ppm dry weight). These data indicate that underlying subclinical or clinical lead toxicosis may be a factor in up to 5% of deaths attributed to predation or impact trauma. Brain cholinesterase activity testing indicated no exposure to organophosphate or carbamate pesticides (mean±SD=17.32±2.90 µmol/min/g, 31/71). The causes of death and potential underlying factors summarized in this study constitute the first definitive mortality survey of migratory Whooping Cranes based on a high carcass recovery rate. Causes of death by infectious etiologies remained comparatively rare in this study, and occurred as single cases with no evidence of sustained transmission among reintroduced Whooping Cranes.

","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2019-05-124","usgsCitation":"Yaw, T.J., Miller, K.J., Lankton, J.S., and Hartup, B.K., 2020, Postmortem evaluation of reintroduced migratory whooping cranes (Grus americana) in eastern North America: Wildlife Disease, v. 56, no. 3, p. 673-678, https://doi.org/10.7589/2019-05-124.","productDescription":"6 p.; Data Release","startPage":"673","endPage":"678","ipdsId":"IP-104967","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":375814,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418310,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MR4XN4"}],"country":"Canada, United States","otherGeospatial":"Eastern North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.5517578125,\n 25.3241665257384\n ],\n [\n -79.8046875,\n 27.449790329784214\n ],\n [\n -80.947265625,\n 31.353636941500987\n ],\n [\n -75.1025390625,\n 35.88905007936091\n ],\n [\n -76.2451171875,\n 38.95940879245423\n ],\n [\n -76.11328125,\n 39.70718665682654\n ],\n [\n -80.68359375,\n 39.774769485295465\n ],\n [\n -80.37597656249999,\n 41.96765920367816\n ],\n [\n -78.662109375,\n 47.66538735632654\n ],\n [\n -81.1669921875,\n 52.26815737376817\n ],\n [\n -92.59277343749999,\n 52.16045455774706\n ],\n [\n -96.94335937499999,\n 52.696361078274485\n ],\n [\n -97.20703125,\n 49.009050809382046\n ],\n [\n -96.6357421875,\n 43.54854811091286\n ],\n [\n -95.97656249999999,\n 41.376808565702355\n ],\n [\n -97.3828125,\n 31.653381399664\n ],\n [\n -96.8994140625,\n 27.68352808378776\n ],\n [\n -92.8125,\n 28.844673680771795\n ],\n [\n -88.06640625,\n 29.305561325527698\n ],\n [\n -84.814453125,\n 29.267232865200878\n ],\n [\n -82.529296875,\n 27.01998400798257\n ],\n [\n -80.5517578125,\n 25.3241665257384\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Yaw, Taylor J.","contributorId":225414,"corporation":false,"usgs":false,"family":"Yaw","given":"Taylor","email":"","middleInitial":"J.","affiliations":[{"id":41101,"text":"School of Veterinary Medicine, Department of Surgical Sciences, University of Wisconsin, Madison, Wisconsin 53706, USA","active":true,"usgs":false}],"preferred":false,"id":791304,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Kimberli J.G. 0000-0002-7947-0894","orcid":"https://orcid.org/0000-0002-7947-0894","contributorId":81447,"corporation":false,"usgs":true,"family":"Miller","given":"Kimberli","email":"","middleInitial":"J.G.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":791305,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lankton, Julia S. 0000-0002-6843-4388 jlankton@usgs.gov","orcid":"https://orcid.org/0000-0002-6843-4388","contributorId":5888,"corporation":false,"usgs":true,"family":"Lankton","given":"Julia","email":"jlankton@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":791306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hartup, Barry K.","contributorId":209630,"corporation":false,"usgs":false,"family":"Hartup","given":"Barry","email":"","middleInitial":"K.","affiliations":[{"id":16606,"text":"International Crane Foundation","active":true,"usgs":false}],"preferred":false,"id":791307,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227481,"text":"70227481 - 2020 - Future losses of playa wetlands decrease network structure and connectivity of the Rainwater Basin, Nebraska","interactions":[],"lastModifiedDate":"2022-01-19T12:50:27.021336","indexId":"70227481","displayToPublicDate":"2019-12-19T06:45:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Future losses of playa wetlands decrease network structure and connectivity of the Rainwater Basin, Nebraska","docAbstract":"

Context

The Rainwater Basin in south-central Nebraska once supported a complex network of ~ 12,000 spatially-isolated playa wetlands, but ~ 90% have been lost since European settlement. Future losses are likely and expected reductions in connectivity could further isolate populations, increasing local extinction rates of many wetland species. However, to what extent future losses will affect wildlife likely depends on the role of lost wetlands in maintaining connectivity.

Objectives

We compared the current Rainwater Basin network to future wetland loss scenarios to assess minimum, mean, and maximum effects of losses on network connectivity for a range of wildlife taxa.

Methods

We used network models to rank wetlands by their functionality and relative importance in maintaining connectivity. We then removed 10–50% of high-ranked, low-ranked, or random subsets of wetlands and assessed connectivity of the remaining network.

Results

A 10% loss of highly-ranked wetlands substantially decreased connectivity for species with dispersal capabilities < 5.5 km, while a 40–50% loss reduced connectivity for all tested dispersal distances (0.5–12.0 km). When large proportions of highly-ranked wetlands were lost, the eastern and western halves of the Rainwater Basin network were no longer connected for any dispersal distance. Loss of low-ranked wetlands had minimal effects on network connectivity, until at least the lowest-ranked 50% were removed.

Conclusions

Many highly-ranked playa wetlands in the Rainwater Basin are currently unprotected and might disappear from the landscape. Protecting wetlands that are key in maintaining connectivity especially benefits species with limited dispersal capabilities (< 5.5 km) for which consequences of future habitat losses might be worst.

","language":"English","publisher":"Springer","doi":"10.1007/s10980-019-00958-w","usgsCitation":"Verheijen, B.H., Varner, D.M., and Haukos, D.A., 2020, Future losses of playa wetlands decrease network structure and connectivity of the Rainwater Basin, Nebraska: Landscape Ecology, v. 35, p. 453-467, https://doi.org/10.1007/s10980-019-00958-w.","productDescription":"15 p.","startPage":"453","endPage":"467","ipdsId":"IP-108305","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":394501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.4482421875,\n 40.07807142745009\n ],\n [\n -96.0205078125,\n 40.07807142745009\n ],\n [\n -96.0205078125,\n 41.409775832009565\n ],\n [\n -99.4482421875,\n 41.409775832009565\n ],\n [\n -99.4482421875,\n 40.07807142745009\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","noUsgsAuthors":false,"publicationDate":"2019-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Verheijen, Bram H.F.","contributorId":271195,"corporation":false,"usgs":false,"family":"Verheijen","given":"Bram","email":"","middleInitial":"H.F.","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":831140,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Varner, Dana M.","contributorId":271196,"corporation":false,"usgs":false,"family":"Varner","given":"Dana","email":"","middleInitial":"M.","affiliations":[{"id":40582,"text":"Rainwater Basin Joint Venture","active":true,"usgs":false}],"preferred":false,"id":831141,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":831142,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70207990,"text":"70207990 - 2020 - Variation of annual apparent survival and detection rates with age, year, and individual identity in male Weddell seals (Leptonychotes weddellii) from long-term mark-recapture data","interactions":[],"lastModifiedDate":"2020-01-23T06:35:11","indexId":"70207990","displayToPublicDate":"2019-12-19T06:33:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3103,"text":"Population Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Variation of annual apparent survival and detection rates with age, year, and individual identity in male Weddell seals (Leptonychotes weddellii) from long-term mark-recapture data","docAbstract":"Exploring age- and sex-specific survival rates provides insight regarding population behavior and life-history trait evolution, but many population studies exclude males. Accordingly, our understanding of how age-specific patterns of survival, including actuarial senescence, compare between the sexes remains inadequate. Using 35 years of mark-recapture data for 7,516 male Weddell seals (Leptonychotes weddellii) born in Erebus Bay, Antarctica, we estimated age- specific annual survival rates using a hierarchical model for mark-recapture data in a Bayesian framework. Our male survival estimates were moderate for pups and yearlings, highest for 2- year-olds, and gradually declined with age thereafter such that the oldest animals observed had the lowest rates of any age. Reports of senescence in other wildlife populations of species with similar longevity occurred at older ages than those presented here. When compared to recently published estimates for reproductive Weddell seal females, we found that peak survival rates were similar (males: 0.94, 95% CI = 0.92-0.96; females: 0.92, 95% CI = 0.93-0.95), but rates declined more rapidly in males. Costs of reproduction for males seem to exceed costs incurred by females, but age-specific reproductive data for males are necessary to fully evaluate survival- reproduction tradeoffs in males. Similar studies on a broad range of species are needed to contextualize these results for a better understanding of the variation in senescence patterns between the sexes of the same species, but our study adds information for a marine mammal species to a research topic dominated by avian and ungulate species.","language":"English","publisher":"Wiley","doi":"10.1002/1438-390X.12036","usgsCitation":"Brusa, J.L., Rotella, J.J., Garrott, R.A., Paterson, J.T., and Link, W., 2020, Variation of annual apparent survival and detection rates with age, year, and individual identity in male Weddell seals (Leptonychotes weddellii) from long-term mark-recapture data: Population Ecology, v. 62, no. 1, p. 134-150, https://doi.org/10.1002/1438-390X.12036.","productDescription":"17 p.","startPage":"134","endPage":"150","ipdsId":"IP-111162","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":371490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Brusa, Jamie L.","contributorId":221719,"corporation":false,"usgs":false,"family":"Brusa","given":"Jamie","email":"","middleInitial":"L.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":780052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rotella, Jay J.","contributorId":37271,"corporation":false,"usgs":false,"family":"Rotella","given":"Jay","email":"","middleInitial":"J.","affiliations":[{"id":5098,"text":"Department of Ecology, Montana State University","active":true,"usgs":false}],"preferred":false,"id":780053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garrott, Robert A.","contributorId":171537,"corporation":false,"usgs":false,"family":"Garrott","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":780054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paterson, J. Terrill","contributorId":206296,"corporation":false,"usgs":false,"family":"Paterson","given":"J.","email":"","middleInitial":"Terrill","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":780055,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Link, William 0000-0002-9913-0256","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":221718,"corporation":false,"usgs":true,"family":"Link","given":"William","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":780051,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70207455,"text":"70207455 - 2020 - Caribou use of habitat near energy development in Arctic Alaska","interactions":[],"lastModifiedDate":"2020-04-06T21:16:30.68736","indexId":"70207455","displayToPublicDate":"2019-12-18T14:44:55","publicationYear":"2020","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":"Caribou use of habitat near energy development in Arctic Alaska","docAbstract":"Increasing demands for energy have generated interest in expanding oil and gas production on the North Slope of Alaska, raising questions about the resilience of barren-ground caribou populations to new development. Although the amount of habitat lost directly to energy development in the Arctic will likely be relatively small, there are significant concerns about habitat that may be indirectly impacted due to caribou avoidance behaviors. Behavioral responses to energy development for wildlife have been well-documented, but such responses are often assumed to dissipate over time, despite scant information on the ability of animals to habituate. To understand the long-term effects of energy development on barren-ground caribou we investigated the behavior of the Central Arctic Herd in northern Alaska, which has been exposed to oil development on its summer range for approximately 40 years. Using recent (2015-2017) location data from GPS collared females, we conducted a zone of influence analysis to assess whether caribou reduced their use of habitat near energy development, and if so, the distance the effects attenuated. We conducted this analysis for the calving, post-calving and mosquito harassment periods when caribou exhibit distinct resource selection patterns, and contrasted our results to past research that investigated the responses of the Central Arctic Caribou Herd immediately following the construction of the oil fields. Despite the long-term presence of energy development within the Central Arctic Herd summer range, we found that female caribou exhibited avoidance responses to infrastructure during all time periods, although the effects waned across the summer. Caribou reduced their use of habitat within 5 km of development during the calving period, within 2 km during the post-calving period, and within 1 km during the mosquito harassment period, areas which were predicted to overlap 12%, 15% and 17% of important calving, post-calving, and mosquito habitat areas, respectively. During the calving period, the indirect effects we observed were similar to those observed in past research, whereas during the post-calving and mosquito periods, we detected avoidance responses which had not been previously reported. These findings corroborate a growing body of evidence suggesting that habituation to industrial development in Arctic caribou is likely to be weak or absent, and emphasizes the value of minimizing the footprint of infrastructure within important seasonal habitat areas to reduce behavioral impacts to barren-ground caribou.","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21809","usgsCitation":"Johnson, H.E., Golden, T., Adams, L., Gustine, D., and Lenart, E.A., 2020, Caribou use of habitat near energy development in Arctic Alaska: Journal of Wildlife Management, v. 84, no. 3, p. 401-412, https://doi.org/10.1002/jwmg.21809.","productDescription":"12 p.","startPage":"401","endPage":"412","ipdsId":"IP-108741","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":458345,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21809","text":"Publisher Index Page"},{"id":370513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"North Slope","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -164.53125,\n 67.33986082559095\n ],\n [\n -140.9765625,\n 67.33986082559095\n ],\n [\n -140.9765625,\n 71.35706654962706\n ],\n [\n -164.53125,\n 71.35706654962706\n ],\n [\n -164.53125,\n 67.33986082559095\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"84","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Heather E. 0000-0001-5392-7676 hejohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5392-7676","contributorId":205919,"corporation":false,"usgs":true,"family":"Johnson","given":"Heather","email":"hejohnson@usgs.gov","middleInitial":"E.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"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":778113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Golden, Trevor","contributorId":221421,"corporation":false,"usgs":false,"family":"Golden","given":"Trevor","affiliations":[{"id":40372,"text":"Axiom Data Science (formerly with USGS)","active":true,"usgs":false}],"preferred":false,"id":778114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":778115,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gustine, David","contributorId":200449,"corporation":false,"usgs":false,"family":"Gustine","given":"David","affiliations":[],"preferred":false,"id":778116,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lenart, Elizabeth A.","contributorId":209732,"corporation":false,"usgs":false,"family":"Lenart","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":778117,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70218766,"text":"70218766 - 2020 - Testing reproducibility of vitrinite and solid bitumen reflectance measurements in North American unconventional source-rock reservoir petroleum systems","interactions":[],"lastModifiedDate":"2021-03-12T14:30:22.076149","indexId":"70218766","displayToPublicDate":"2019-12-18T08:10:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Testing reproducibility of vitrinite and solid bitumen reflectance measurements in North American unconventional source-rock reservoir petroleum systems","docAbstract":"

An interlaboratory study (ILS) was conducted to test reproducibility of vitrinite and solid bitumen reflectance measurements in six mudrock samples from United States unconventional source-rock reservoir petroleum systems. Samples selected from the Marcellus, Haynesville, Eagle Ford, Barnett, Bakken and Woodford are representative of resource plays currently under exploitation in North America. All samples are from marine depositional environments, are thermally mature (Tmax >445 °C) and have moderate to high organic matter content (2.9–11.6 wt% TOC). Their organic matter is dominated by solid bitumen, which contains intraparticle nano-porosity. Visual evaluation of organic nano-porosity (pore sizes < 100 nm) via SEM suggests that intraparticle organic nano-pores are most abundant in dry gas maturity samples and less abundant at lower wet gas/condensate and peak oil maturities. Samples were distributed to ILS participants in forty laboratories in the Americas, Europe, Africa and Australia; thirty-seven independent sets of results were received. Mean vitrinite reflectance (VRo) values from all ILS participants range from 0.90 to 1.83% whereas mean solid bitumen reflectance (BRo) values range from 0.85 to 2.04% (no outlying values excluded), confirming the thermally mature nature of all six samples. Using multiple statistical approaches to eliminate outlying values, we evaluated reproducibility limit R, the maximum difference between valid mean reflectance results obtained on the same sample by different operators in different laboratories using different instruments. Removal of outlying values where the individual signed multiple of standard deviation was >1.0 produced lowest R values, generally ≤0.5% (absolute reflectance), similar to a prior ILS for similar samples. Other traditional approaches to outlier removal (outside mean ± 1.5*interquartile range and outside F10 to F90 percentile range) also produced similar R values. Standard deviation values < 0.15*(VRo or BRo) reduce R and should be a requirement of dispersed organic matter reflectance analysis. After outlier removal, R values were 0.1%–0.2% for peak oil thermal maturity, about 0.3% for wet gas/condensate maturity and 0.4%–0.5% for dry gas maturity. That is, these R values represent the uncertainty (in absolute reflectance) that users of vitrinite and solid bitumen reflectance data should assign to any one individual reported mean reflectance value from a similar thermal maturity mudrock sample. R values of this magnitude indicate a need for further standardization of reflectance measurement of dispersed organic matter. Furthermore, these R values quantify realistic interlaboratory measurement dispersion for a difficult but critically important analytical technique necessary for thermal maturity determination in the source-rock reservoirs of unconventional petroleum systems.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2019.104172","usgsCitation":"Hackley, P.C., Araujo, C., Borrego, A.G., Bouzinos, A., Cardott, B.J., Carvajal-Ortiz, H., Rocio Lopez Cely, M., Chabalala, V., Crosdale, P.J., Demchuk, T.D., Eble, C.F., Flores, D., Furmann, A., Gentzis, T., Goncalves, P., Guvad, C., Hamor-Vido, M., Jelonek, I., Johnston, M., Juliao-Lemus, T., Kalaitzidis, S., Knowles, W., Kus, J., Li, Z., Macleod, G., Mastalerz, M., Rego Menezes, T., Ocubalidet, S., Orban, R., Pickel, W., Ranasinghe, P., Ribeiro, J., Gomez Rojas, O.P., Ruiz-Monroy, R., Schmidt, J., Seyedolali, A., Siavalas, G., Suarez-Ruiz, I., Vargas, C.V., Valentine, B.J., Wagner, N., Wrolson, B., and Jaramillo Zapata, J.E., 2020, Testing reproducibility of vitrinite and solid bitumen reflectance measurements in North American unconventional source-rock reservoir petroleum systems: Marine and Petroleum Geology, v. 114, 104172, 17 p., 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architecture","interactions":[],"lastModifiedDate":"2021-03-24T12:30:48.087213","indexId":"70219115","displayToPublicDate":"2019-12-16T07:29:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5279,"text":"Special Publications","onlineIssn":"0149-1768","active":true,"publicationSubtype":{"id":10}},"title":"Fault fictions: Systematic biases in the conceptualization of fault-zone architecture","docAbstract":"

Mental models are a human's internal representation of the real world and have an important role in the way we understand and reason about uncertainties, explore potential options and make decisions. Mental models have not yet received much attention in geosciences, yet systematic biases can affect any geological investigation: from how the problem is conceived, through selection of appropriate hypotheses and data collection/processing methods, to the conceptualization and communication of results. We draw on findings from cognitive science and system dynamics, with knowledge and experiences of field geology, to consider the limitations and biases presented by mental models in geoscience, and their effect on predictions of the physical properties of faults in particular. We highlight biases specific to geological investigations and propose strategies for debiasing. Doing so will enhance how multiple data sources can be brought together, and minimize controllable geological uncertainty to develop more robust geological models. Critically, there is a need for standardized procedures that guard against biases, permitting data from multiple studies to be combined and communication of assumptions to be made. While we use faults to illustrate potential biases in mental models and the implications of these biases, our findings can be applied across the geosciences.

","language":"English","publisher":"Geological Society of London","doi":"10.1144/SP496-2018-161","usgsCitation":"Shipton, Z.K., Roberts, J.J., L, C.E., Kremer, Y., Lunn, R.J., and Caine, J., 2020, Fault fictions: Systematic biases in the conceptualization of fault-zone architecture: Special Publications, v. 496, p. 125-143, https://doi.org/10.1144/SP496-2018-161.","productDescription":"19 p.","startPage":"125","endPage":"143","ipdsId":"IP-101941","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":458358,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://strathprints.strath.ac.uk/view/author/742207.html>","text":"External Repository"},{"id":384631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"496","noUsgsAuthors":false,"publicationDate":"2019-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Shipton, Zoe K 0000-0002-2268-7750","orcid":"https://orcid.org/0000-0002-2268-7750","contributorId":255721,"corporation":false,"usgs":false,"family":"Shipton","given":"Zoe","email":"","middleInitial":"K","affiliations":[{"id":51656,"text":"University of Strathclyde","active":true,"usgs":false}],"preferred":false,"id":812827,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberts, Jennifer J","contributorId":255722,"corporation":false,"usgs":false,"family":"Roberts","given":"Jennifer","email":"","middleInitial":"J","affiliations":[{"id":51656,"text":"University of Strathclyde","active":true,"usgs":false}],"preferred":false,"id":812828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"L, Comrie Emma","contributorId":255723,"corporation":false,"usgs":false,"family":"L","given":"Comrie","email":"","middleInitial":"Emma","affiliations":[{"id":51656,"text":"University of Strathclyde","active":true,"usgs":false}],"preferred":false,"id":812829,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kremer, Yannick","contributorId":255724,"corporation":false,"usgs":false,"family":"Kremer","given":"Yannick","affiliations":[{"id":51656,"text":"University of Strathclyde","active":true,"usgs":false}],"preferred":false,"id":812830,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lunn, Rebecca J","contributorId":255725,"corporation":false,"usgs":false,"family":"Lunn","given":"Rebecca","email":"","middleInitial":"J","affiliations":[{"id":51656,"text":"University of Strathclyde","active":true,"usgs":false}],"preferred":false,"id":812831,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caine, Jonathan Saul 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":199295,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan Saul","email":"jscaine@usgs.gov","affiliations":[],"preferred":true,"id":812832,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208560,"text":"70208560 - 2020 - UAV-derived estimates of forest structure to inform ponderosa pine forest restoration","interactions":[],"lastModifiedDate":"2020-06-19T16:23:52.408024","indexId":"70208560","displayToPublicDate":"2019-12-16T06:54:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5347,"text":"Remote Sensing in Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"UAV-derived estimates of forest structure to inform ponderosa pine forest restoration","docAbstract":"

Restoring forest ecosystems has become an increasingly high priority for land managers across the American West. Millions of hectares of forest are in need of drastic yet strategic reductions in density (e.g., basal area). Meeting the restoration and management goals requires quantifying metrics of vertical and horizontal forest structure, which has relied upon field‐based measurements, manned airborne or satellite remote sensing datasets. We used unmanned aerial vehicle (UAV ) image‐derived Structure‐from‐Motion (SfM) models and high‐resolution multispectral orthoimagery in this study to quantify vertical and horizontal forest structure at both the fine‐ (<4 ha) and mid‐scales (4–400 ha) across a forest density gradient. We then used these forest structure estimates to assess specific objectives of a forest restoration treatment. At the fine‐scale, we found that estimates of individual tree height and canopy diameter were most accurate in low‐density conditions, with accuracies degrading significantly in high‐density conditions. Mid‐scale estimates of canopy cover and forest density followed a similar pattern across the density gradient, demonstrating the effectiveness of UAV image‐derived estimates in low‐ to medium‐density conditions as well as the challenges associated with high‐density conditions. We found that post‐treatment conditions met a majority of the prescription objectives and demonstrate the UAV image application in quantifying changes from a mechanical thinning treatment. We provide a novel approach to forest restoration monitoring using UAV ‐derived data, one that considers varying density conditions and spatial scales. Future research should consider a more spatially extensive sampling design, including different restoration treatments, as well as experimenting with different combinations of equipment, flight parameters, and data processing workflows.

","language":"English","publisher":"Wiley","doi":"10.1002/rse2.137","usgsCitation":"Belmonte, A., Sankey, T.T., Biederman, J.A., Bradford, J.B., Goetz, S.J., Kolb, T., and Woolley, T., 2020, UAV-derived estimates of forest structure to inform ponderosa pine forest restoration: Remote Sensing in Ecology and Conservation, v. 6, no. 2, p. 181-197, https://doi.org/10.1002/rse2.137.","productDescription":"17 p.","startPage":"181","endPage":"197","ipdsId":"IP-113835","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":458361,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.137","text":"Publisher Index Page"},{"id":372377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.150390625,\n 48.8936153614802\n ],\n [\n -123.48632812499999,\n 49.1242192485914\n ],\n [\n -123.22265625000001,\n 48.31242790407178\n ],\n [\n -125.595703125,\n 48.42920055556841\n ],\n [\n -124.76074218749999,\n 46.800059446787316\n ],\n [\n -125.33203125,\n 41.77131167976407\n ],\n [\n -124.4091796875,\n 38.238180119798635\n ],\n [\n -120.58593749999999,\n 34.05265942137599\n ],\n [\n -117.59765625,\n 32.84267363195431\n ],\n [\n -116.103515625,\n 32.69486597787505\n ],\n [\n -108.9404296875,\n 31.316101383495624\n ],\n [\n -106.2158203125,\n 31.914867503276223\n ],\n [\n -103.3154296875,\n 31.952162238024975\n ],\n [\n -102.216796875,\n 37.16031654673677\n ],\n [\n -101.953125,\n 40.78054143186033\n ],\n [\n -103.84277343749999,\n 41.0130657870063\n ],\n [\n -104.150390625,\n 48.8936153614802\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Belmonte, Adam","contributorId":222546,"corporation":false,"usgs":false,"family":"Belmonte","given":"Adam","email":"","affiliations":[{"id":40559,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":782489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankey, Temuulen T.","contributorId":173297,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"T.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":782490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biederman, Joel A.","contributorId":201939,"corporation":false,"usgs":false,"family":"Biederman","given":"Joel","email":"","middleInitial":"A.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":782491,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":782488,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goetz, Scott J.","contributorId":222547,"corporation":false,"usgs":false,"family":"Goetz","given":"Scott","email":"","middleInitial":"J.","affiliations":[{"id":40559,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":782492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kolb, Thomas","contributorId":174381,"corporation":false,"usgs":false,"family":"Kolb","given":"Thomas","affiliations":[],"preferred":false,"id":782493,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Woolley, Travis","contributorId":222548,"corporation":false,"usgs":false,"family":"Woolley","given":"Travis","affiliations":[{"id":40560,"text":"The Nature Conservancy Northern Arizona Program, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":782494,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70209440,"text":"70209440 - 2020 - Time scales of arsenic variability and the role of high-frequency monitoring at three water-supply wells in New Hampshire, USA","interactions":[],"lastModifiedDate":"2020-05-05T12:11:42.664539","indexId":"70209440","displayToPublicDate":"2019-12-14T19:51:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Time scales of arsenic variability and the role of high-frequency monitoring at three water-supply wells in New Hampshire, USA","docAbstract":"

Groundwater geochemistry, redox process classification, high-frequency physicochemical and hydrologic measurements, and climate data were analyzed to identify controls on arsenic (As) concentration changes. Groundwater was monitored in two public-supply wells (one glacial aquifer and one bedrock aquifer), and one bedrock-aquifer domestic well in New Hampshire, USA, from 2014 to 2018 to identify time scales of and controls on As concentration changes. Concentrations of As and other geochemical constituents were measured bimonthly. Specific conductance (SC), pH, dissolved oxygen, and pumping rate/water level were measured at high frequency (every 5 to 15 min). Median (and 95% confidence interval) As concentrations at the three wells were 4.1 (3.7–4.6), 18.9 (17.2–23.6), and 37.5 (30.4–42.9) μg/L. Arsenic variability in each of the three wells, in relative standard deviation, ranged from 9 to 12%. Median quarterly As concentrations were highest in all wells in the spring. The bedrock-aquifer public-supply well As concentration increased over the period of study while pumping rate decreased. In the public-supply wells, As variability was correlated with SC and pH, and As species were related to SC, pH, pumping, precipitation, and changes in redox process. Specific conductance also had a seasonal pattern in the two public-supply wells and was correlated with Na and Cl. Excess Na in water samples suggests possible ion exchange with dissolved Ca, creating more capacity to dissolve CaCO3 from calcareous rocks, which can increase pH and in turn, As concentrations in wells. High-frequency monitoring data are cost effective to collect, which could be advantageous in other parts of the United States and in the many parts of the world where glacial aquifers are in direct contact with other water supply aquifers or where water from different aquifers have potential to mix.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.135946","usgsCitation":"Degnan, J.R., Levitt, J.P., Erickson, M., Jurgens, B.C., Lindsey, B.D., and Ayotte, J.D., 2020, Time scales of arsenic variability and the role of high-frequency monitoring at three water-supply wells in New Hampshire, USA: Science of the Total Environment, v. 709, Report: 135946, 13 p.; Data Release, https://doi.org/10.1016/j.scitotenv.2019.135946.","productDescription":"Report: 135946, 13 p.; Data Release","ipdsId":"IP-107690","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":458363,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2019.135946","text":"Publisher Index Page"},{"id":437187,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C2H7F4","text":"USGS data release","linkHelpText":"Data for Time Scales of Arsenic Variability and the Role of High-Frequency Monitoring at Three Water-Supply Wells in New Hampshire, USA"},{"id":373803,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":373804,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5d0a2c07e4b0e3d3115de4cb","text":"USGS data release","description":"USGS data release","linkHelpText":"Data for Time Scales of Arsenic Variability and the Role of High-Frequency Monitoring at Three Water-Supply Wells in New Hampshire, USA"}],"country":"United States","state":"New Hampshire","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.35595703125,\n 42.73087427928485\n ],\n [\n -71.19140625,\n 42.71473218539458\n ],\n [\n -70.94970703125,\n 42.76314586689492\n ],\n [\n -70.72998046875,\n 43.068887774169625\n ],\n [\n -70.94970703125,\n 43.45291889355465\n ],\n [\n -71.08154296875,\n 45.259422036351694\n ],\n [\n -71.34521484375,\n 45.22848059584359\n ],\n [\n -71.54296874999999,\n 44.91813929958515\n ],\n [\n -71.7626953125,\n 44.38669150215206\n ],\n [\n -72.0703125,\n 44.10336537791152\n ],\n [\n -72.3779296875,\n 43.43696596521823\n ],\n [\n -72.4658203125,\n 42.74701217318067\n ],\n [\n -72.35595703125,\n 42.73087427928485\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"709","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Degnan, James R. 0000-0002-5665-9010 jrdegnan@usgs.gov","orcid":"https://orcid.org/0000-0002-5665-9010","contributorId":498,"corporation":false,"usgs":true,"family":"Degnan","given":"James","email":"jrdegnan@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Levitt, Joseph P. 0000-0002-2058-9516 jlevitt@usgs.gov","orcid":"https://orcid.org/0000-0002-2058-9516","contributorId":198353,"corporation":false,"usgs":false,"family":"Levitt","given":"Joseph","email":"jlevitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erickson, Melinda L. 0000-0002-1117-2866 merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":206446,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda","email":"merickso@usgs.gov","middleInitial":"L.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786487,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - 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Characterizing the state of the volcanic vent is key for interpreting observational datasets and accurately assessing volcanic hazards. This is particularly true for remote, complex eruptions such as the 2016–2017 Bogoslof volcano, Alaska eruption sequence. Bogoslof’s eruptions in this period were either shallow submarine or subaerial, or some combination of both. Our results demonstrate how low-frequency sound waves (infrasound), integrated with seismic and satellite data, can provide unique insight into shallow vent processes, otherwise not available. We use simple metrics, such as the infrasound frequency index (FI), event duration, and acoustic-seismic amplitude ratio, to look at changes in the elastic energy radiation and infer changes in seawater access to the vent. Satellite imagery before and after selected eruptions is used to ground-truth inferences on vent conditions. High FI and gradual increases in infrasound frequency content at Bogoslof correspond with transitions from submarine to subaerial vent conditions and a diminished or absent role of water, likely resulting in a drying out of the vent region. Event durations generally correlate with high FI and the range of FI values for each event, suggesting long duration events were more effective at drying out the vent region. A trend from low to high acoustic-seismic amplitude ratios for some long duration events also suggests an increase in acoustic efficiency as the vent dried out. We demonstrate that infrasound can serve as a robust indicator of seawater involvement for Bogoslof and other shallow submarine eruptions that may not be inferable from other datasets, particularly in near-real-time.

","language":"English","publisher":"Springer","doi":"10.1007/s00445-019-1326-5","usgsCitation":"Fee, D., Lyons, J.J., Haney, M.M., Wech, A., Waythomas, C.F., Diefenbach, A., Lopez, T., Van Eaton, A.R., and Schneider, D.J., 2020, Seismo-acoustic evidence for vent drying during shallow submarine eruptions at Bogoslof volcano, Alaska: Bulletin of Volcanology Special Issue on the Bogoslof Eruption, v. 82, 2, 14 p., https://doi.org/10.1007/s00445-019-1326-5.","productDescription":"2, 14 p.","ipdsId":"IP-107901","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":458366,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-019-1326-5","text":"Publisher Index Page"},{"id":383378,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168.28582763671875,\n 53.21096737507053\n ],\n [\n -166.81915283203125,\n 53.21096737507053\n ],\n [\n -166.81915283203125,\n 53.99485396562768\n ],\n [\n -168.28582763671875,\n 53.99485396562768\n ],\n [\n -168.28582763671875,\n 53.21096737507053\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2019-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Fee, David","contributorId":199660,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[],"preferred":false,"id":810536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, John J. 0000-0001-5409-1698 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0000-0003-4983-1991","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":202561,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waythomas, Christopher F. 0000-0002-3898-272X cwaythomas@usgs.gov","orcid":"https://orcid.org/0000-0002-3898-272X","contributorId":640,"corporation":false,"usgs":true,"family":"Waythomas","given":"Christopher","email":"cwaythomas@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810540,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diefenbach, Angela K. 0000-0003-0214-7818","orcid":"https://orcid.org/0000-0003-0214-7818","contributorId":204743,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Angela K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810541,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lopez, Taryn","contributorId":237830,"corporation":false,"usgs":false,"family":"Lopez","given":"Taryn","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":810542,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810543,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schneider, David J. 0000-0001-9092-1054 djschneider@usgs.gov","orcid":"https://orcid.org/0000-0001-9092-1054","contributorId":198601,"corporation":false,"usgs":true,"family":"Schneider","given":"David","email":"djschneider@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":810544,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70217068,"text":"70217068 - 2020 - Not all fuel‐reduction treatments degrade biocrusts: Herbicides cause mostly neutral to positive effects on cover of biocrusts","interactions":[],"lastModifiedDate":"2021-01-04T13:26:49.305257","indexId":"70217068","displayToPublicDate":"2019-12-13T07:24:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7487,"text":"Land Degradation & Development","active":true,"publicationSubtype":{"id":10}},"title":"Not all fuel‐reduction treatments degrade biocrusts: Herbicides cause mostly neutral to positive effects on cover of biocrusts","docAbstract":"

In response to increasing fire, fuel‐reduction treatments are being used to minimize large fire risk. Although biocrusts are associated with reduced cover of fire‐promoting, invasive grasses, the impact of fuel‐reduction treatments on biocrusts is poorly understood. We use data from a long‐term experiment, the Sagebrush Steppe Treatment Evaluation Project, testing the following fuel‐reduction treatments: mowing, prescribed fire, and the use of two herbicides: one commonly used to reduce shrub cover, tebuthiuron, and one commonly used to combat cheatgrass, imazapic. Looking at sites with high cover of biocrusts prior to treatments, we demonstrate positive effects of the herbicide, tebuthiuron on lichens with an increase in cover of 10% and trending towards slightly negative effects on moss cover. Across plots, imazapic trended towards a decrease in lichen and moss cover without being statistically significant. Mowing and prescribed fire reduced cover of mosses, with the latter leading to greater declines across sites (declines of 18% vs. 32%). Reductions in moss cover mirrored gains in cover of bare soil, which is associated with increased risk of invasion by grasses responsible for increasing fire risk. We demonstrate that the use of herbicides simultaneously reduces fuels and maintains greater cover of lichens and mosses compared with other fuel‐reduction treatments, possibly reducing risk of invasion by annual grasses that are responsible for increasing fire risk.

","language":"English","publisher":"Wiley","doi":"10.1002/ldr.3516","usgsCitation":"Condon, L.A., and Gray, M.L., 2020, Not all fuel‐reduction treatments degrade biocrusts: Herbicides cause mostly neutral to positive effects on cover of biocrusts: Land Degradation & Development, v. 31, no. 13, p. 1727-1734, https://doi.org/10.1002/ldr.3516.","productDescription":"8 p.","startPage":"1727","endPage":"1734","ipdsId":"IP-108427","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":458372,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ldr.3516","text":"Publisher Index Page"},{"id":437189,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P972F9LN","text":"USGS data release","linkHelpText":"10 Year Data for biocrust cover after fire management treatments"},{"id":381838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"13","noUsgsAuthors":false,"publicationDate":"2020-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Condon, Lea A. 0000-0002-9357-3881","orcid":"https://orcid.org/0000-0002-9357-3881","contributorId":202908,"corporation":false,"usgs":true,"family":"Condon","given":"Lea","email":"","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":807472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, Margaret L 0000-0002-4810-8876","orcid":"https://orcid.org/0000-0002-4810-8876","contributorId":221166,"corporation":false,"usgs":false,"family":"Gray","given":"Margaret","email":"","middleInitial":"L","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":807473,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70207192,"text":"70207192 - 2020 - USGS near-real-time products-and their use-for the 2018 Anchorage earthquake","interactions":[],"lastModifiedDate":"2020-01-08T14:20:33","indexId":"70207192","displayToPublicDate":"2019-12-11T14:59:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"USGS near-real-time products-and their use-for the 2018 Anchorage earthquake","docAbstract":"

In the minutes to hours after a major earthquake, such as the recent 2018 Mw\">Mw 7.1 Anchorage event, the U.S. Geological Survey (USGS) produces a suite of interconnected earthquake products that provides diverse information ranging from basic earthquake source parameters to loss estimates. The 2018 Anchorage earthquake is the first major domestic earthquake to occur since several new USGS products have been developed, thus providing an opportunity to discuss the newly expanded USGS earthquake product suite, its timeliness, performance, and reception. Overall, the products were relatively timely, accurate, well received, and widely used, including by the media, who used information and visualizations from many products to frame their early reporting. One downside of the codependence of multiple products is that reasonable updates to upstream products (e.g., magnitude and source characterization) can result in significant changes to downstream products; this was the case for the Anchorage earthquake. However, the coverage of strong‐motion stations and felt reports was so dense that the ShakeMap and downstream products were relatively insensitive to changes in magnitude or fault‐plane orientation once the ground‐motion data were available. Shaking and loss indicators initially fluctuated in the first hour or two after the earthquake, but they stabilized quickly. To understand how the products are being used and how effectively they are being communicated, we analyze the media coverage of USGS earthquake products. Most references to USGS products occurred within the first 48 hr after the event. The lack of coverage after 48 hr could indicate that longer‐term products addressing what actions the USGS is taking or what early reconnaissance has revealed might be useful for those people wanting additional information about the earthquake.

","language":"English","publisher":"GeoScienceWorld","doi":"10.1785/0220190207","usgsCitation":"Thompson, E.M., McBride, S., Hayes, G.P., Allstadt, K.E., Wald, L., Wald, D.J., Knudsen, K.L., Worden, C., Marano, K., Jibson, R.W., and Grant, A.R., 2020, USGS near-real-time products-and their use-for the 2018 Anchorage earthquake: Seismological Research Letters, v. 91, no. 1, p. 94-113, https://doi.org/10.1785/0220190207.","productDescription":"20 p.","startPage":"94","endPage":"113","ipdsId":"IP-112025","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":370183,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Anchorage ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -151.5234375,\n 60.74842446462361\n ],\n [\n -147.91992187499997,\n 60.74842446462361\n ],\n [\n -147.91992187499997,\n 61.48075950007598\n ],\n [\n -151.5234375,\n 61.48075950007598\n ],\n [\n -151.5234375,\n 60.74842446462361\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"91","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":146592,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":777220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McBride, Sara K. 0000-0002-8062-6542","orcid":"https://orcid.org/0000-0002-8062-6542","contributorId":206933,"corporation":false,"usgs":true,"family":"McBride","given":"Sara K.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":777221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Gavin P. 0000-0003-3323-0112 ghayes@usgs.gov","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":147556,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin","email":"ghayes@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777223,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wald, Lisa 0000-0002-5467-0523","orcid":"https://orcid.org/0000-0002-5467-0523","contributorId":204456,"corporation":false,"usgs":true,"family":"Wald","given":"Lisa","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":777224,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777225,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Knudsen, Keith L. 0000-0003-2826-5812 kknudsen@usgs.gov","orcid":"https://orcid.org/0000-0003-2826-5812","contributorId":3758,"corporation":false,"usgs":true,"family":"Knudsen","given":"Keith","email":"kknudsen@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":777226,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Worden, Charles 0000-0003-1181-685X cbworden@usgs.gov","orcid":"https://orcid.org/0000-0003-1181-685X","contributorId":152042,"corporation":false,"usgs":true,"family":"Worden","given":"Charles","email":"cbworden@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777227,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Marano, Kristin 0000-0002-0420-2748 kmarano@usgs.gov","orcid":"https://orcid.org/0000-0002-0420-2748","contributorId":207906,"corporation":false,"usgs":true,"family":"Marano","given":"Kristin","email":"kmarano@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777228,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jibson, Randall W. 0000-0003-3399-0875 jibson@usgs.gov","orcid":"https://orcid.org/0000-0003-3399-0875","contributorId":2985,"corporation":false,"usgs":true,"family":"Jibson","given":"Randall","email":"jibson@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777229,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Grant, Alex R. 0000-0002-5096-4305","orcid":"https://orcid.org/0000-0002-5096-4305","contributorId":219066,"corporation":false,"usgs":true,"family":"Grant","given":"Alex","middleInitial":"R.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":777230,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70212646,"text":"70212646 - 2020 - Evaluation of ground‐motion models for U.S. Geological Survey seismic hazard models: 2018 Anchorage, Alaska, Mw 7.1 subduction zone earthquake sequence","interactions":[],"lastModifiedDate":"2020-08-25T14:46:14.53336","indexId":"70212646","displayToPublicDate":"2019-12-11T09:39:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evaluation of ground‐motion models for U.S. Geological Survey seismic hazard models: 2018 Anchorage, Alaska, Mw 7.1 subduction zone earthquake sequence","title":"Evaluation of ground‐motion models for U.S. Geological Survey seismic hazard models: 2018 Anchorage, Alaska, Mw 7.1 subduction zone earthquake sequence","docAbstract":"

Instrumental ground‐motion recordings from the 2018 Anchorage, Alaska (⁠Mw\">Mw 7.1), earthquake sequence provide an independent data set allowing us to evaluate the predictive power of ground‐motion models (GMMs) for intraslab earthquakes associated with the Alaska subduction zone. In this study, we evaluate 15 candidate GMMs using instrumental ground‐motion observations of peak ground acceleration and 5% damped pseudospectral acceleration (0.02–10 s) to inform logic‐tree weights for the update of the U.S. Geological Survey seismic hazard model for Alaska. GMMs are evaluated using two methods. The first is a total residual visualization approach that compares the probability density function, mean, and standard deviations &#x3C3;\">σ of the observed and predicted ground motion. The second GMM evaluation method we use is the common total residual probabilistic scoring method (log likelihood [LLH]). The LLH method provides a single score that can be used to weight GMMs in the Alaska seismic hazard model logic trees. To test logic branches in previous seismic hazard models, we evaluate GMM performance as a function of depth and we demonstrate that some GMMs show improved performance for earthquakes with focal depths greater than 50 km. Ten of the initial 15 candidate GMMs fit the observed ground motions and meet established criteria for inclusion in the next update of the Alaska seismic hazard model.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190188","usgsCitation":"McNamara, D.E., Wolin, E., Powers, P.M., Shumway, A., Moschetti, M.P., Rekoske, J., Thompson, E.M., Mueller, C., and Petersen, M.D., 2020, Evaluation of ground‐motion models for U.S. Geological Survey seismic hazard models: 2018 Anchorage, Alaska, Mw 7.1 subduction zone earthquake sequence: Seismological Research Letters, v. 91, no. 1, p. 183-194, https://doi.org/10.1785/0220190188.","productDescription":"12 p.","startPage":"183","endPage":"194","ipdsId":"IP-113669","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":377821,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Anchorage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.88623046875,\n 60.67855911666429\n ],\n [\n -149.007568359375,\n 60.67855911666429\n ],\n [\n -149.007568359375,\n 61.66120280305204\n ],\n [\n -150.88623046875,\n 61.66120280305204\n ],\n [\n -150.88623046875,\n 60.67855911666429\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"91","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"McNamara, Daniel E. 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":402,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":797201,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolin, Emily 0000-0003-1610-1191","orcid":"https://orcid.org/0000-0003-1610-1191","contributorId":221834,"corporation":false,"usgs":true,"family":"Wolin","given":"Emily","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":797202,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powers, Peter M. 0000-0003-2124-6184 pmpowers@usgs.gov","orcid":"https://orcid.org/0000-0003-2124-6184","contributorId":176814,"corporation":false,"usgs":true,"family":"Powers","given":"Peter","email":"pmpowers@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":797203,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shumway, Allison 0000-0003-1142-7141 ashumway@usgs.gov","orcid":"https://orcid.org/0000-0003-1142-7141","contributorId":147862,"corporation":false,"usgs":true,"family":"Shumway","given":"Allison","email":"ashumway@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":797204,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":797205,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rekoske, John 0000-0003-0539-2069","orcid":"https://orcid.org/0000-0003-0539-2069","contributorId":220108,"corporation":false,"usgs":true,"family":"Rekoske","given":"John","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":797206,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":797207,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mueller, Charles 0000-0002-1868-9710 cmueller@usgs.gov","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":140380,"corporation":false,"usgs":true,"family":"Mueller","given":"Charles","email":"cmueller@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":797208,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":797209,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70217004,"text":"70217004 - 2020 - Geochronology of the Oliverian Plutonic Suite and the Ammonoosuc Volcanics in the Bronson Hill arc: Western New Hampshire, USA","interactions":[],"lastModifiedDate":"2020-12-23T13:31:09.51661","indexId":"70217004","displayToPublicDate":"2019-12-11T07:28:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Geochronology of the Oliverian Plutonic Suite and the Ammonoosuc Volcanics in the Bronson Hill arc: Western New Hampshire, USA","docAbstract":"

U-Pb zircon geochronology by sensitive high-resolution ion microprobe–reverse geometry (SHRIMP-RG) on 11 plutonic rocks and two volcanic rocks from the Bronson Hill arc in western New Hampshire yielded Early to Late Ordovician ages ranging from 475 to 445 Ma. Ages from Oliverian Plutonic Suite rocks that intrude a largely mafic lower section of the Ammonoosuc Volcanics ranged from 474.8 ± 5.2 to 460.2 ± 3.4 Ma. Metamorphosed felsic volcanic rocks from within the Ammonoosuc Volcanics yielded ages of 460.1 ± 2.4 and 455.0 ± 11 Ma. Younger Oliverian Plutonic Suite rocks that either intrude both the upper and lower Ammonoosuc Volcanics or Partridge Formation ranged in age from 456.1 ± 6.7 Ma to 445.2 ± 6.7 Ma.

These new data and previously published results document extended magmatism for >30 m.y. The ages, along with the lack of mappable structural discontinuities between the plutons and their volcanic cover, suggest that the Bronson Hill arc was part of a relatively long-lived composite arc. The Early to Late Ordovician ages presented here overlap with previously determined igneous U-Pb zircon ages in the Shelburne Falls arc to the west, suggesting that the Bronson Hill arc and the Shelburne Falls arc could be part of one, long-lived composite arc system, in agreement with the interpretation that the Iapetus suture (Red Indian Line) lies to the west of the Shelburne Falls–Bronson Hill arc system.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02170.1","usgsCitation":"Valley, P.M., Walsh, G.J., Merschat, A.J., and McAleer, R.J., 2020, Geochronology of the Oliverian Plutonic Suite and the Ammonoosuc Volcanics in the Bronson Hill arc: Western New Hampshire, USA: Geosphere, v. 16, no. 1, p. 229-257, https://doi.org/10.1130/GES02170.1.","productDescription":"29 p.","startPage":"229","endPage":"257","ipdsId":"IP-102995","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":458395,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02170.1","text":"Publisher Index Page"},{"id":381609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Hampshire","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.5537109375,\n 42.94033923363181\n ],\n [\n -71.312255859375,\n 42.94033923363181\n ],\n [\n -71.312255859375,\n 43.723474896114794\n ],\n [\n -72.5537109375,\n 43.723474896114794\n ],\n [\n -72.5537109375,\n 42.94033923363181\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Valley, Peter M. 0000-0002-9957-0403 pvalley@usgs.gov","orcid":"https://orcid.org/0000-0002-9957-0403","contributorId":4809,"corporation":false,"usgs":true,"family":"Valley","given":"Peter","email":"pvalley@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":807236,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsh, Gregory J. 0000-0003-4264-8836 gwalsh@usgs.gov","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":873,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory","email":"gwalsh@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":807237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merschat, Arthur J. 0000-0002-9314-4067 amerschat@usgs.gov","orcid":"https://orcid.org/0000-0002-9314-4067","contributorId":4556,"corporation":false,"usgs":true,"family":"Merschat","given":"Arthur","email":"amerschat@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":807238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":807239,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208438,"text":"70208438 - 2020 - Successful molecular detection studies require clear communication among diverse research partners","interactions":[],"lastModifiedDate":"2020-02-10T18:12:55","indexId":"70208438","displayToPublicDate":"2019-12-09T18:05:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Successful molecular detection studies require clear communication among diverse research partners","docAbstract":"

Molecular detection techniques are powerful tools used in ecological applications ranging from diet analyses to pathogen surveillance. Research partnerships that use these tools often involve collaboration among professionals with expertise in field biology, laboratory techniques, quantitative modeling, wildlife disease, and natural resource management. However, in many cases, each of these collaborators lacks specific knowledge about the approaches, decisions, methods, and terminology used by their research partners, which can impede effective communication and act as a barrier to the efficient use of molecular data for ecological inferences and subsequent conservation decision making. We outline a collaborative framework to assist colleagues with diverse types of expertise to effectively translate their scientific and management needs to research partners from other specialties. The molecular techniques used to detect organisms will continue to advance both in sophistication and in the breadth of ecological applications. Our objective is to enable ecologists to harness the full utility of these methods by developing effective collaborative partnerships.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/fee.2141","usgsCitation":"Mosher, B.A., Bernard, R.F., Lorch, J.M., Miller, D., Richgels, K.L., White, C.L., and Campbell Grant, E.H., 2020, Successful molecular detection studies require clear communication among diverse research partners: Frontiers in Ecology and the Environment, v. 18, no. 1, p. 43-51, https://doi.org/10.1002/fee.2141.","productDescription":"9 p.","startPage":"43","endPage":"51","ipdsId":"IP-104082","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":372203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Mosher, B. A.","contributorId":216927,"corporation":false,"usgs":false,"family":"Mosher","given":"B.","email":"","middleInitial":"A.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":781881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernard, R. F.","contributorId":216081,"corporation":false,"usgs":false,"family":"Bernard","given":"R.","email":"","middleInitial":"F.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":781882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252 jlorch@usgs.gov","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":5565,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey","email":"jlorch@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":781883,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, D. A. W.","contributorId":201361,"corporation":false,"usgs":false,"family":"Miller","given":"D. A. W.","affiliations":[],"preferred":false,"id":781988,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richgels, Katherine L. D. 0000-0003-2834-9477 krichgels@usgs.gov","orcid":"https://orcid.org/0000-0003-2834-9477","contributorId":151205,"corporation":false,"usgs":true,"family":"Richgels","given":"Katherine","email":"krichgels@usgs.gov","middleInitial":"L. D.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":781885,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"White, C. LeAnn 0000-0002-5004-5165 clwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-5004-5165","contributorId":4315,"corporation":false,"usgs":true,"family":"White","given":"C.","email":"clwhite@usgs.gov","middleInitial":"LeAnn","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":781886,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":781880,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70207821,"text":"70207821 - 2020 - Dimensional effects of inter-phase mass transfer on attenuation of structurally trapped gaseous carbon dioxide in shallow aquifers","interactions":[],"lastModifiedDate":"2020-12-14T13:14:53.68955","indexId":"70207821","displayToPublicDate":"2019-12-09T15:50:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2228,"text":"Journal of Computational Physics","active":true,"publicationSubtype":{"id":10}},"title":"Dimensional effects of inter-phase mass transfer on attenuation of structurally trapped gaseous carbon dioxide in shallow aquifers","docAbstract":"

Based on experimental evidence and using mathematical modeling, inter-phase mass transfer processes of CO2 exsolving from and dissolving into water in heterogeneous porous media are investigated under two fundamentally different flow conditions: in a quasi one dimensional vertical column and in a two-dimensional tank with a lateral background water flow, both at laboratory scale. In both cases, the CO2 dissolved in water under a given overpressure is injected for a certain period at the bottom of the tank, exsolves, and migrates upwards. A layer of fine sand is present in the tanks designed to mimic geological scenarios of accumulation and trapping of exsolved CO2 in shallow aquifers. Then, clean water is injected and the accumulated CO2 is dissolved back into the flowing water. The study aims to point out the differences in the mass transfer processes between the quasi-1D and 2D cases using a mathematical model of two-phase compositional flow in heterogeneous porous media calibrated to the experimental datasets, and expose strategies that should be explored in future research. Additionally, temperature variations observed during the 2D experiments allow for analysis of isothermal versus non-isothermal effects on the processes of multiphase CO2 evolution. The mathematical model is discretized and solved using the mixed hybrid finite element method in 2D that allows for the simulation of both advection- and diffusion-dominated processes accurately.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jcp.2019.109178","usgsCitation":"Jakub Solovsky, Radek Fucik, Plampin, M.R., Illangasekare, T.H., and Jiri Mikyska, 2020, Dimensional effects of inter-phase mass transfer on attenuation of structurally trapped gaseous carbon dioxide in shallow aquifers: Journal of Computational Physics, v. 405, 109178, https://doi.org/10.1016/j.jcp.2019.109178.","productDescription":"109178","ipdsId":"IP-104741","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":458403,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1580146","text":"Publisher Index Page"},{"id":371236,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"405","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jakub Solovsky","contributorId":217696,"corporation":false,"usgs":false,"family":"Jakub Solovsky","affiliations":[{"id":39686,"text":"Czech Technical University in Prague","active":true,"usgs":false}],"preferred":false,"id":779439,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Radek Fucik","contributorId":217697,"corporation":false,"usgs":false,"family":"Radek Fucik","affiliations":[{"id":39686,"text":"Czech Technical University in Prague","active":true,"usgs":false}],"preferred":false,"id":779440,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plampin, Michelle R. 0000-0003-4068-5801 mplampin@usgs.gov","orcid":"https://orcid.org/0000-0003-4068-5801","contributorId":204983,"corporation":false,"usgs":true,"family":"Plampin","given":"Michelle","email":"mplampin@usgs.gov","middleInitial":"R.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":779441,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Illangasekare, Tissa H.","contributorId":194933,"corporation":false,"usgs":false,"family":"Illangasekare","given":"Tissa","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":779442,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jiri Mikyska","contributorId":217700,"corporation":false,"usgs":false,"family":"Jiri Mikyska","affiliations":[{"id":39686,"text":"Czech Technical University in Prague","active":true,"usgs":false}],"preferred":false,"id":779443,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208802,"text":"70208802 - 2020 - Toward ecosystem accounts for Rwanda: Tracking 25 years of change in potential supply and flows of ecosystem services","interactions":[],"lastModifiedDate":"2021-10-22T19:44:22.967675","indexId":"70208802","displayToPublicDate":"2019-12-09T12:36:59","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5936,"text":"People and Nature","active":true,"publicationSubtype":{"id":10}},"title":"Toward ecosystem accounts for Rwanda: Tracking 25 years of change in potential supply and flows of ecosystem services","docAbstract":"

1. Rwanda, a small but rapidly developing central African nation, has undertaken development of natural capital accounts to better inform its economic development through the World Bank’s Wealth Accounting and Valuation of Ecosystem Services (WAVES) Partnership. In this paper, we develop ecosystem service (ES) models to quantify the physical supply components of ecosystem accounts in Rwanda from 1990 to 2015.

2. We applied the InVEST carbon storage, sediment delivery ratio, and annual and seasonal water yield models to map changes in potential ES supply nationwide. We also quantified flows of sediment and water to 96 hydroelectric dam, irrigation dam, and water treatment plant sites.

3. Over a 25-year period, we found declines in all ES, which were most strongly driven by conversion of forests to cropland. Declines were most pronounced from 1990 to 2000 and 2010 to 2015; ES were relatively stable from 2000 to 2010. From 2010 to 2015, over 42% of Rwanda’s water-use sites (representing 17% of the nation’s hydroelectric generation capacity and 69% of its water treatment capacity) had increases in sediment export and quick flow greater than the national average.

4. Our results quantify nationwide ES trends, their implications for key water-dependent industries, and the importance of protected areas in safeguarding ES potential supply and flows in Rwanda. They also provide data that can be integrated with existing land, water, and economic accounts for Rwanda, as well as a baseline to inform development strategies that better link economic and environmental goals.

","language":"English","publisher":"British Ecological Society","doi":"10.1002/pan3.10062","usgsCitation":"Bagstad, K.J., Ingram, J.C., Lange, G., Masozera, M.K., Ancona, Z.H., Bana, M., Kabogo, D., Musana, B., Nabahungu, N.L., Rukundo, E., Rutebuka, E., Polasky, S., Rugege, D., and Uwera, C., 2020, Toward ecosystem accounts for Rwanda: Tracking 25 years of change in potential supply and flows of ecosystem services: People and Nature, v. 1, no. 2, p. 163-188, https://doi.org/10.1002/pan3.10062.","productDescription":"26 p.","startPage":"163","endPage":"188","ipdsId":"IP-090139","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":458407,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/pan3.10062","text":"Publisher Index Page"},{"id":437190,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72806JN","text":"USGS data 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Minnesota","active":true,"usgs":false}],"preferred":false,"id":783447,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rugege, Denis","contributorId":222900,"corporation":false,"usgs":false,"family":"Rugege","given":"Denis","email":"","affiliations":[],"preferred":false,"id":783450,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Uwera, Claudine 0000-0002-9490-3969","orcid":"https://orcid.org/0000-0002-9490-3969","contributorId":222901,"corporation":false,"usgs":false,"family":"Uwera","given":"Claudine","email":"","affiliations":[{"id":40624,"text":"University of Rwanda","active":true,"usgs":false}],"preferred":false,"id":783451,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70211969,"text":"70211969 - 2020 - Roosting habitat use by sandhill cranes and waterfowl on the North and South Platte Rivers in Nebraska","interactions":[],"lastModifiedDate":"2025-07-10T21:19:05.547791","indexId":"70211969","displayToPublicDate":"2019-12-03T15:41:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Roosting habitat use by sandhill cranes and waterfowl on the North and South Platte Rivers in Nebraska","docAbstract":"

Migration ecology and habitat use of spring migrating birds using the Central Platte River is a well-explored topic, yet less is known about use of the North and South Platte rivers (NSPR) in western Nebraska. The efficiency and effectiveness of conservation efforts in the NSPR could be greatly improved with access to information about where and when birds roost and landscape prioritization tools. We used aerial surveys to determine population distribution and migration phenology of sandhill cranes Antigone canadensis, Canada geese Branta canadensis, and ducks using the NSPR for roosting during the mid-February to mid-April spring migration. We used these data and geospatial information to identify important river reaches for these species and habitat covariates that discriminate between those used at lower and higher densities. We found that sandhill cranes and waterfowl generally roosted in different segments of the NSPR and, subsequently, different factors were associated with high densities. Sandhill crane density was positively correlated with distance from obstructions greater than 1 m high and negatively correlated with area of unvegetated sandbar within 1 km. Density of Canada geese and ducks was high in segments positively associated with wetland and sand pit habitats. Human disturbance variables such as roads and bridges in this rural region had little effect on identification of roosting areas used by high densities of all groups. On the basis of our results, habitat conservation efforts that specifically target sandhill cranes will not have similar positive effects on waterfowl use and distribution in the NSPR. Our identification of the most important river segments should allow managers to better target land acquisition or management resources to areas that will have the greatest effect on either waterfowl or sandhill cranes during spring migration.

","language":"English","publisher":"U.S. Fish & Wildlife Service","doi":"10.3996/042019-JFWM-030","usgsCitation":"Varner, D.M., Pearse, A.T., Bishop, A., Davis, J., Denton, J., Grosse, R., Johnson, H., Munter, E., Schroeder, K.D., Spangler, R.E., Vrtiska, M., and Wright, A., 2020, Roosting habitat use by sandhill cranes and waterfowl on the North and South Platte Rivers in Nebraska: Journal of Fish and Wildlife Management, v. 11, p. 56-67, https://doi.org/10.3996/042019-JFWM-030.","productDescription":"12 p.","startPage":"56","endPage":"67","ipdsId":"IP-092984","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":458419,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/042019-jfwm-030","text":"Publisher Index Page"},{"id":377439,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"North and South Platte Rivers","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.699951171875,\n 40.718119379753446\n ],\n [\n -100.4150390625,\n 40.718119379753446\n ],\n [\n -100.4150390625,\n 41.90636538970964\n ],\n [\n -103.699951171875,\n 41.90636538970964\n ],\n [\n -103.699951171875,\n 40.718119379753446\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2019-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Varner, Dana M","contributorId":238096,"corporation":false,"usgs":false,"family":"Varner","given":"Dana","email":"","middleInitial":"M","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":796008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":796009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bishop, Andrew","contributorId":198583,"corporation":false,"usgs":false,"family":"Bishop","given":"Andrew","affiliations":[],"preferred":false,"id":796010,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Jonas","contributorId":238097,"corporation":false,"usgs":false,"family":"Davis","given":"Jonas","email":"","affiliations":[{"id":36215,"text":"Ducks Unlimited","active":true,"usgs":false}],"preferred":false,"id":796011,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Denton, John","contributorId":238098,"corporation":false,"usgs":false,"family":"Denton","given":"John","email":"","affiliations":[{"id":36215,"text":"Ducks Unlimited","active":true,"usgs":false}],"preferred":false,"id":796012,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grosse, Roger","contributorId":166720,"corporation":false,"usgs":false,"family":"Grosse","given":"Roger","email":"","affiliations":[],"preferred":false,"id":796013,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Heather M.","contributorId":357800,"corporation":false,"usgs":false,"family":"Johnson","given":"Heather M.","affiliations":[{"id":17640,"text":"Nebraska Game and Parks Commission","active":true,"usgs":false}],"preferred":false,"id":796014,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Munter, Emily","contributorId":238099,"corporation":false,"usgs":false,"family":"Munter","given":"Emily","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796015,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schroeder, Kirk D","contributorId":222655,"corporation":false,"usgs":false,"family":"Schroeder","given":"Kirk","email":"","middleInitial":"D","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796016,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Spangler, Robert E.","contributorId":200420,"corporation":false,"usgs":false,"family":"Spangler","given":"Robert","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":796017,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Vrtiska, Mark P.","contributorId":201604,"corporation":false,"usgs":false,"family":"Vrtiska","given":"Mark","middleInitial":"P.","affiliations":[{"id":36216,"text":"NE Game & Parks","active":true,"usgs":false}],"preferred":false,"id":796018,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wright, Angelina","contributorId":238100,"corporation":false,"usgs":false,"family":"Wright","given":"Angelina","email":"","affiliations":[{"id":36215,"text":"Ducks Unlimited","active":true,"usgs":false}],"preferred":false,"id":796019,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70218301,"text":"70218301 - 2020 - Controls on debris‐flow initiation on burned and unburned hillslopes during an exceptional rainstorm in southern New Mexico, USA","interactions":[],"lastModifiedDate":"2021-03-08T12:38:06.42036","indexId":"70218301","displayToPublicDate":"2019-12-02T07:15:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Controls on debris‐flow initiation on burned and unburned hillslopes during an exceptional rainstorm in southern New Mexico, USA","docAbstract":"

AbstractUsing observations from 688 debris flows, we analyse the hydrologic and landscape characteristics that influenced debris‐flow initiation mechanisms and locations in a watershed that had been partially burned by the 2012 Whitewater‐Baldy Complex Fire in the Gila Mountains, southern New Mexico. Debris flows can initiate due to different processes. Slopes can fail as discrete landslides and then become fluidized and move downstream as debris flows (landslide initiated) or progressive bulking of sediment from a distributed area can become channelized and concentrated as it moves downslope (runoff generated). In this study, we have an unusual opportunity to investigate both types of debris‐flow initiation mechanisms in our observations of debris flows, triggered by an exceptional rainstorm in the autumn of 2013. Additionally, we compare our observations with those of a dataset of 1138 debris flows in the Colorado Front Range, triggered during the same weather system. We found that runoff‐generated debris flows dominated in burn areas, and runoff required to start these flows could be well characterized by the Shields stress. Landslide‐initiated debris flows were dominant in unburned areas. Debris‐flow densities were tied to total rainfall and precipitation intensities. Like the observations in the Colorado Front Range, debris‐flow initiation locations were found primarily in areas of relatively sparse vegetation on south‐facing slopes between 25 and 40°, and with upslope contributing areas less than 1000 m2. In terms of preferential locations for debris‐flow initiations, 2013 vegetation coverage, approximated by Green–Red Vegetation Index metrics, proved to be more influential than the 2012 burn‐severity designation. The uniformity of observations between our study area and those in the Colorado Front Range indicate that the underlying hydrologic and landscape patterns of the debris‐flow initiation locations documented in these studies could be applicable to the wider southwest and Rocky Mountain regions.

","language":"English","publisher":"Wiley","doi":"10.1002/esp.4761","usgsCitation":"Tillery, A.C., and Rengers, F.K., 2020, Controls on debris‐flow initiation on burned and unburned hillslopes during an exceptional rainstorm in southern New Mexico, USA: Earth Surface Processes and Landforms, v. 45, no. 4, p. 1051-1066, https://doi.org/10.1002/esp.4761.","productDescription":"16 p.","startPage":"1051","endPage":"1066","ipdsId":"IP-102711","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":383616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.984375,\n 32.97180377635759\n ],\n [\n -107.7978515625,\n 32.97180377635759\n ],\n [\n -107.7978515625,\n 33.916013113401696\n ],\n [\n -108.984375,\n 33.916013113401696\n ],\n [\n -108.984375,\n 32.97180377635759\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Tillery, Anne C. 0000-0002-9508-7908 atillery@usgs.gov","orcid":"https://orcid.org/0000-0002-9508-7908","contributorId":2549,"corporation":false,"usgs":true,"family":"Tillery","given":"Anne","email":"atillery@usgs.gov","middleInitial":"C.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":810919,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70209788,"text":"70209788 - 2020 - Parsing the effects of demography, climate, and management on recurrent brucellosis outbreaks in elk","interactions":[],"lastModifiedDate":"2020-05-04T18:18:52.416224","indexId":"70209788","displayToPublicDate":"2019-12-01T07:27:54","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Parsing the effects of demography, climate, and management on recurrent brucellosis outbreaks in elk","docAbstract":"1. Zoonotic pathogens can harm human health and well-being directly or by impacting livestock. Pathogens that spillover from wildlife can also impair conservation efforts if humans perceive wildlife as pests. Brucellosis, caused by the bacterium Brucella abortus, circulates in elk and bison herds of the Greater Yellowstone Ecosystem and poses a risk to cattle and humans. Our goal was to understand the relative effects of climatic drivers, host demography, and management control programs on disease dynamics. \n2. Using >20 years of serologic, demographic, and environmental data on brucellosis in elk, we built stochastic compartmental models to assess the influences of climate forcing, herd immunity, population turnover, and management interventions on pathogen transmission. Data were collected at feedgrounds visited in winter by free-ranging elk in Wyoming, USA.\n3. Snowpack, hypothesized as a driver of elk aggregation and thus brucellosis transmission, was strongly correlated across feedgrounds. We expected this variable to drive synchronized disease dynamics across herds. Instead, we demonstrate asynchronous epizootics driven by variation in demographic rates.\n4. We evaluated the effectiveness of test-and-slaughter of seropositive female elk at two feedgrounds. Test-and-slaughter temporarily reduced herd-level seroprevalence but likely reduced herd immunity while removing few infectious individuals, resulting in subsequent outbreaks once the intervention ceased. We simulated an alternative strategy of removing seronegative female elk and found it would increase herd immunity, yielding fewer infections. We evaluated a second experimental treatment wherein feeding density was reduced at one feedground, but we found no evidence for an effect despite a decade of implementation.\n5. Synthesis and applications: Positive serostatus is often weakly correlated with infectiousness but is nevertheless used to make management decisions including lethal removal in wildlife disease systems. We show how this can have adverse consequences whereas efforts that maintain herd immunity can have longer-term protective effects. Climatic drivers may not result in synchronous disease dynamics across populations unless vital rates are also similar because demographic factors have a large influence on disease patterns.","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13553","collaboration":"","usgsCitation":"Cotterill, G., Cross, P., Merkle, J., Rogerson, J., Scurlock, B., and Du Toit, J.T., 2020, Parsing the effects of demography, climate, and management on recurrent brucellosis outbreaks in elk: Journal of Applied Ecology, v. 2, no. 57, p. 379-389, https://doi.org/10.1111/1365-2664.13553.","productDescription":"11 p.","startPage":"379","endPage":"389","ipdsId":"IP-106553","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":458423,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13553","text":"Publisher Index Page"},{"id":374346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.3134765625,\n 42.98857645832184\n ],\n [\n -108.19335937499999,\n 42.98857645832184\n ],\n [\n -108.19335937499999,\n 45.27488643704891\n ],\n [\n -111.3134765625,\n 45.27488643704891\n ],\n [\n -111.3134765625,\n 42.98857645832184\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","issue":"57","noUsgsAuthors":false,"publicationDate":"2020-01-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Cotterill, Gavin G.","contributorId":203301,"corporation":false,"usgs":false,"family":"Cotterill","given":"Gavin G.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":788017,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":218820,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":788018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merkle, Jerod 0000-0003-0100-1833","orcid":"https://orcid.org/0000-0003-0100-1833","contributorId":224370,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":788019,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rogerson, JD","contributorId":224371,"corporation":false,"usgs":false,"family":"Rogerson","given":"JD","email":"","affiliations":[{"id":40869,"text":"WYGFD","active":true,"usgs":false}],"preferred":false,"id":788020,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scurlock, BM","contributorId":199582,"corporation":false,"usgs":false,"family":"Scurlock","given":"BM","email":"","affiliations":[],"preferred":false,"id":788021,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Du Toit, Johan T. 0000-0003-0705-7117","orcid":"https://orcid.org/0000-0003-0705-7117","contributorId":210266,"corporation":false,"usgs":false,"family":"Du Toit","given":"Johan","email":"","middleInitial":"T.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":788022,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228287,"text":"70228287 - 2020 - Predicting wildlife distribution patterns in New England USA with expert elicitation techniques","interactions":[],"lastModifiedDate":"2022-02-09T12:04:24.462319","indexId":"70228287","displayToPublicDate":"2019-11-30T15:56:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Predicting wildlife distribution patterns in New England USA with expert elicitation techniques","docAbstract":"

Understanding the impacts of landscape change on species distributions can help inform decision-making and conservation planning. Unfortunately, empirical data that span large spatial extents across multiple taxa are limited. In this study, we used expert elicitation techniques to develop species distribution models (SDMs) for harvested wildlife species (n = 10) in the New England region of the northeastern United States. We administered an online survey that elicited opinions from wildlife experts on the probability of species occurrence throughout the study region. We collected 3396 probability of occurrence estimates from 46 experts, and used linear mixed-effects methods and landcover variables at multiple spatial extents to develop SDMs. The models were in general agreement with the literature and provided effect sizes for variables that shape species occurrence. With the exception of gray fox, models performed well when validated against crowdsourced empirical data. We applied models to rasters (30 × 30 m cells) of the New England region to map each species’ distribution. Average regional occurrence probability was highest for coyote (0.92) and white-tailed deer (0.89) and lowest for gray fox (0.42) and moose (0.52). We then stacked distribution maps of each species to estimate and map focal species richness. Species richness (s) varied across New England, with highest average richness in the least developed states of Vermont (s = 7.47) and Maine (s = 7.32), and lowest average richness in the most developed states of Rhode Island (s = 6.13) and Massachusetts (s = 6.61). Our expert-based approach provided relatively inexpensive, comprehensive information that would have otherwise been difficult to obtain given the spatial extent and range of species being assessed. The results provide valuable information about the current distribution of wildlife species and offer a means of exploring how climate and land-use change may impact wildlife in the future.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2019.e00853","usgsCitation":"Pearman-Gillman, S.B., Katz, J.E., Mickey, R., Murdoch, J.D., and Donovan, T.M., 2020, Predicting wildlife distribution patterns in New England USA with expert elicitation techniques: Global Ecology and Conservation, v. 21, e00853, 19 p., https://doi.org/10.1016/j.gecco.2019.e00853.","productDescription":"e00853, 19 p.","ipdsId":"IP-110199","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":458424,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2019.e00853","text":"Publisher Index Page"},{"id":395658,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, 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\"}}]}","volume":"21","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pearman-Gillman, Schuyler B. spearman-gillman@usgs.gov","contributorId":275070,"corporation":false,"usgs":false,"family":"Pearman-Gillman","given":"Schuyler","email":"spearman-gillman@usgs.gov","middleInitial":"B.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":833613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katz, Jonathan E.","contributorId":275072,"corporation":false,"usgs":false,"family":"Katz","given":"Jonathan","email":"","middleInitial":"E.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":833614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mickey, Ruth M.","contributorId":275073,"corporation":false,"usgs":false,"family":"Mickey","given":"Ruth M.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":833615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murdoch, James D.","contributorId":275075,"corporation":false,"usgs":false,"family":"Murdoch","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":833616,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833612,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206902,"text":"70206902 - 2020 - Antibiotic resistant bacteria in wildlife: Perspectives on trends, acquisitions and dissemination, data gaps, and future directions","interactions":[],"lastModifiedDate":"2020-01-08T14:15:59","indexId":"70206902","displayToPublicDate":"2019-11-25T08:43:54","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Antibiotic resistant bacteria in wildlife: Perspectives on trends, acquisitions and dissemination, data gaps, and future directions","docAbstract":"The proliferation of antibiotic resistant bacteria in the environment has potential negative economic and health consequences. Thus, previous investigations have targeted wild animals to understand the occurrence of antibiotic resistance in diverse environmental sources. In this critical review and synthesis, we summarize important concepts learned through the sampling of wildlife for antibiotic resistant indicator bacteria. These concepts are helpful for understanding dissemination of resistance through environmental pathways and helping to guide future research efforts. \nOur review is comprised of six sections. The first section briefly introduces antibiotic resistance as it pertains to bacteria harbored in environmental sources such as wild animals. Next, we differentiate wildlife from other animals in the context of how diverse taxa provide different information on antibiotic resistance in the environment. In the third section, we identify representative research and seminal works that illustrate important associations between the occurrence of antibiotic resistant bacteria in wildlife and anthropogenic inputs into the environment. For example, we highlight numerous investigations that support the premise that anthropogenic inputs into the environment drive the occurrence of antibiotic resistance in bacteria harbored by free-ranging wildlife. Additionally, we summarize previous research demonstrating foraging as a mechanism by which wildlife may be exposed to anthropogenic antibiotic resistance contamination in the environment. In the fourth section of our review, we summarize molecular evidence for the acquisition and dissemination of resistance among bacteria harbored by wildlife. In the fifth section, we identify what we believe to be important data gaps and potential future directions that other researchers may find useful towards the development of efficient, informative, and impactful investigations of antibiotic resistant bacteria in wildlife. Finally, we conclude our review by highlighting the need to move from surveys that simply identify antibiotic resistant bacteria in wildlife towards hypothesis-driven investigations that: (1) identify point sources of antibiotic resistance; (2) provide information on risk to human and animal health; (3) identify interventions that may interrupt environmentally mediated pathways of antibiotic resistance acquisition/transmission; and (4) evaluate whether management practices are leading to desirable outcomes.","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2019-04-099","usgsCitation":"Ramey, A.M., and Ahlstrom, C., 2020, Antibiotic resistant bacteria in wildlife: Perspectives on trends, acquisitions and dissemination, data gaps, and future directions: Journal of Wildlife Diseases, v. 56, no. 1, p. 1-15, https://doi.org/10.7589/2019-04-099.","productDescription":"15 p.","startPage":"1","endPage":"15","ipdsId":"IP-107397","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":369698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":776194,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":776195,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70206881,"text":"70206881 - 2020 - Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud","interactions":[],"lastModifiedDate":"2020-04-06T21:07:55.202827","indexId":"70206881","displayToPublicDate":"2019-11-22T06:58:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1722,"text":"GIScience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud","docAbstract":"The South Asia (India, Pakistan, Bangladesh, Nepal, Sri Lanka and Bhutan) has a staggering 900 million people (~43% of the population) who face food insecurity or severe food insecurity as per United Nations, Food and Agriculture Organization’s (FAO) the Food Insecurity Experience Scale (FIES). The existing coarse-resolution (>250-m) cropland maps lack precision in geo-location of individual farms and have low map accuracies. This also results in uncertainties in cropland areas calculated from such products. Thereby, the overarching goal of this study was to develop high spatial resolution (30-m or better) baseline cropland extent product of South Asia for the year 2015 using Landsat satellite time-series big-data and machine learning algorithms (MLAs) on the Google Earth Engine (GEE) cloud computing platform. To eliminate the impact of clouds, ten time-composited Landsat bands (blue, green, red, NIR, SWIR1, SWIR2, Thermal, EVI, NDVI, NDWI) were derived for each of the 3 time-periods over 12 months (monsoon: Julian days 151-300; winter: Julian days 301-365 plus 1-60; and summer: Julian days 61-150), taking the every 8-day data from Landsat-8 and 7 for the years 2013-2015, for a total of 30-bands plus global digital elevation model (GDEM) derived slope band. This 31-band mega-file big data-cube was composed for each of the 5 agro-ecological zones (AEZ’s) of South Asia and formed a baseline data for image classification and analysis. Knowledge-base for the Random Forest (RF) MLAs were developed using spatially well spread-out reference training data (N=2179) in 5 AEZs. Classification was performed on GEE for each of the 5 AEZs using well-established knowledge-based and RF MLAs on the cloud. Map accuracies were measured using independent validation data (N=1185). The survey showed that the South Asia cropland product had a producer’s accuracy of 89.9% (errors of omissions of 10.1%), user’s accuracy of 95.3% (errors of commission of 4.7%) and an overall accuracy of 88.7%. The National and sub-national (districts) areas computed from this cropland extent product explained 80-96% variability when compared with the National statistics of the South Asian Countries. The full resolution imagery can be viewed at full-resolution, by zooming-in to any location in South Asia or the world, at www.croplands.org and the cropland products of South Asia downloaded from The Land Processes Distributed Active Archive Center (LP DAAC) of National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS): https://lpdaac.usgs.gov/products/gfsad30saafgircev001/","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15481603.2019.1690780","usgsCitation":"Gumma, M.K., Thenkabail, P., Pardhasaradhi Teluguntla, and Oliphant, A., 2020, Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud: GIScience and Remote Sensing, v. 57, no. 3, p. 302-322, https://doi.org/10.1080/15481603.2019.1690780.","productDescription":"21 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Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Gumma, Murali Krishna","contributorId":127590,"corporation":false,"usgs":false,"family":"Gumma","given":"Murali","email":"","middleInitial":"Krishna","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":776137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad 0000-0002-2182-8822","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":220239,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":776136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pardhasaradhi Teluguntla 0000-0001-8060-9841","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":214457,"corporation":false,"usgs":false,"family":"Pardhasaradhi Teluguntla","affiliations":[{"id":39046,"text":"Bay Area Environmental Research Institute at USGS","active":true,"usgs":false}],"preferred":false,"id":776138,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliphant, Adam 0000-0001-8622-7932 aoliphant@usgs.gov","orcid":"https://orcid.org/0000-0001-8622-7932","contributorId":192325,"corporation":false,"usgs":true,"family":"Oliphant","given":"Adam","email":"aoliphant@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":776139,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208919,"text":"70208919 - 2020 - The ecology of chronic wasting disease in wildlife","interactions":[],"lastModifiedDate":"2020-03-05T10:26:47","indexId":"70208919","displayToPublicDate":"2019-11-21T10:26:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1023,"text":"Biological Reviews","active":true,"publicationSubtype":{"id":10}},"title":"The ecology of chronic wasting disease in wildlife","docAbstract":"

Prions are misfolded infectious proteins responsible for a group of fatal neurodegenerative diseases termed transmissible spongiform encephalopathy or prion diseases. Chronic Wasting Disease (CWD) is the prion disease with the highest spillover potential, affecting at least seven Cervidae (deer) species. The zoonotic potential of CWD is inconclusive and cannot be ruled out. A risk of infection for other domestic and wildlife species is also plausible. Here, we review the current status of the knowledge with respect to CWD ecology in wildlife. Our current understanding of the geographic distribution of CWD lacks spatial and temporal detail, does not consider the biogeography of infectious diseases, and is largely biased by sampling based on hunters' cooperation and funding available for each region. Limitations of the methods used for data collection suggest that the extent and prevalence of CWD in wildlife is underestimated. If the zoonotic potential of CWD is confirmed in the short term, as suggested by recent results obtained in experimental animal models, there will be limited accurate epidemiological data to inform public health. Research gaps in CWD prion ecology include the need to identify specific biological characteristics of potential CWD reservoir species that better explain susceptibility to spillover, landscape and climate configurations that are suitable for CWD transmission, and the magnitude of sampling bias in our current understanding of CWD distribution and risk. Addressing these research gaps will help anticipate novel areas and species where CWD spillover is expected, which will inform control strategies. From an ecological perspective, control strategies could include assessing restoration of natural predators of CWD reservoirs, ultrasensitive CWD detection in biotic and abiotic reservoirs, and deer density and landscape modification to reduce CWD spread and prevalence.

","language":"English","publisher":"Wiley","doi":"10.1111/brv.12568","usgsCitation":"Escobar, L.E., Pritzkow, S., Winter, S.N., Grear, D.A., Kirchgessner, M.S., Dominguez-Villegas, E., Machado, G., Peterson, A.T., and Soto, C., 2020, The ecology of chronic wasting disease in wildlife: Biological Reviews, v. 95, no. 2, p. 393-408, https://doi.org/10.1111/brv.12568.","productDescription":"16 p.","startPage":"393","endPage":"408","ipdsId":"IP-107301","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":458473,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/brv.12568","text":"External Repository"},{"id":372946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Finland, Norway, South Korea, Sweden, United States","volume":"95","issue":"2","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Escobar, Luis E.","contributorId":178962,"corporation":false,"usgs":false,"family":"Escobar","given":"Luis","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":784013,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pritzkow, Sandra","contributorId":223075,"corporation":false,"usgs":false,"family":"Pritzkow","given":"Sandra","email":"","affiliations":[{"id":40666,"text":"University of Texas Medical School at Houston","active":true,"usgs":false}],"preferred":false,"id":784014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winter, Steven N","contributorId":223076,"corporation":false,"usgs":false,"family":"Winter","given":"Steven","email":"","middleInitial":"N","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":784015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":784012,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kirchgessner, Megan S.","contributorId":173866,"corporation":false,"usgs":false,"family":"Kirchgessner","given":"Megan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":784016,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dominguez-Villegas, Ernesto","contributorId":223077,"corporation":false,"usgs":false,"family":"Dominguez-Villegas","given":"Ernesto","email":"","affiliations":[{"id":37079,"text":"Wildlife Center of Virginia","active":true,"usgs":false}],"preferred":false,"id":784017,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Machado, Gustavo","contributorId":223078,"corporation":false,"usgs":false,"family":"Machado","given":"Gustavo","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":784018,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Peterson, A Townsend","contributorId":223079,"corporation":false,"usgs":false,"family":"Peterson","given":"A","email":"","middleInitial":"Townsend","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":784019,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Soto, Claudio","contributorId":223080,"corporation":false,"usgs":false,"family":"Soto","given":"Claudio","email":"","affiliations":[{"id":40666,"text":"University of Texas Medical School at Houston","active":true,"usgs":false}],"preferred":false,"id":784020,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70223511,"text":"70223511 - 2020 - Nonlinear patterns in mercury bioaccumulation in American alligators are a function of predicted age","interactions":[],"lastModifiedDate":"2021-08-31T13:00:27.640555","indexId":"70223511","displayToPublicDate":"2019-11-21T07:53:45","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Nonlinear patterns in mercury bioaccumulation in American alligators are a function of predicted age","docAbstract":"

Mercury is a widespread, naturally occurring contaminant that biomagnifies in wetlands due to the methylation of this element by sulfate-reducing bacteria. Species that feed at the top trophic level within wetlands are predicted to have higher mercury loads compared to species feeding at lower trophic levels and are therefore often used for mercury biomonitoring. However, mechanisms for mercury bioaccumulation in sentinel species are often poorly understood, due to a lack of long-term studies or an inability to differentiate between confounding variables. We examined mercury bioaccumulation patterns in the whole blood of American alligators (Alligator mississippiensis) from a long-term mark-recapture study (1979–2017) in South Carolina, USA. Using a growth model and auxiliary information on predicted age at first capture, we differentiated between age- and size-related variation in mercury bioaccumulation, which are often confounded in alligators due to their determinate growth pattern. Contrary to predictions that the oldest or largest individuals were likely to have the highest mercury concentrations, our best-supported model indicated a peak in mercury concentration at 30–40 years of age, depending on the sex, and lower concentrations in the youngest and oldest animals. To evaluate the robustness of our findings, we re-analyzed data from a previously published study of mercury in alligators sampled at Merritt Island National Wildlife Refuge in Florida. Unlike the South Carolina data, the data from Florida contained minimal auxiliary information regarding age, yet the best supported model similarly indicated a peaked rather than increasing relationship between mercury and body size, a less-precise indicator of age. These findings highlight how long-term monitoring can differentiate between confounding variables (e.g., age and size) to better elucidate complex relationships between contaminant exposure and demographic factors in sentinel species.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.135103","usgsCitation":"Lawson, A., Moore, C.T., Rainwater, T., Nilsen, F., Wilkinson, P., Lowers, R., Guillett, L., McFadden, K., and Jodice, P.G., 2020, Nonlinear patterns in mercury bioaccumulation in American alligators are a function of predicted age: Science of the Total Environment, v. 707, 135103, 15 p., https://doi.org/10.1016/j.scitotenv.2019.135103.","productDescription":"135103, 15 p.","ipdsId":"IP-104151","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":458476,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2019.135103","text":"Publisher Index Page"},{"id":437198,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98XHBCY","text":"USGS data release","linkHelpText":"Mercury concentrations in American alligators in South Carolina, 2010-2017"},{"id":388683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, South Carolina","otherGeospatial":"Merritt Island National Wildlife Refuge, Tom Yawkey Wildlife Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.82366943359375,\n 28.401064827220896\n ],\n [\n -80.69183349609375,\n 28.270520445825415\n ],\n [\n -80.52291870117188,\n 28.38173504322308\n ],\n [\n -80.52429199218749,\n 28.642389157900553\n ],\n [\n -80.6396484375,\n 28.8975881579445\n ],\n [\n -80.9307861328125,\n 28.936054482136672\n ],\n [\n -80.82366943359375,\n 28.401064827220896\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.43801879882812,\n 33.06737684108429\n ],\n [\n -79.1455078125,\n 33.06737684108429\n ],\n [\n -79.1455078125,\n 33.38099943104024\n ],\n [\n -79.43801879882812,\n 33.38099943104024\n ],\n [\n -79.43801879882812,\n 33.06737684108429\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"707","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lawson, A.J.","contributorId":264958,"corporation":false,"usgs":false,"family":"Lawson","given":"A.J.","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":822237,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":822238,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rainwater, T.R.","contributorId":264959,"corporation":false,"usgs":false,"family":"Rainwater","given":"T.R.","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":822239,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nilsen, F.M.","contributorId":264960,"corporation":false,"usgs":false,"family":"Nilsen","given":"F.M.","email":"","affiliations":[{"id":38740,"text":"Medical University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":822240,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilkinson, P.M.","contributorId":264961,"corporation":false,"usgs":false,"family":"Wilkinson","given":"P.M.","email":"","affiliations":[{"id":54598,"text":"Tom Yawkey Wildlife Center","active":true,"usgs":false}],"preferred":false,"id":822241,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lowers, R.H.","contributorId":264962,"corporation":false,"usgs":false,"family":"Lowers","given":"R.H.","email":"","affiliations":[{"id":54599,"text":"Integrated Mission Support Services","active":true,"usgs":false}],"preferred":false,"id":822242,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Guillett, L.J. 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