Endangered Sonoran (Antilocapra americana sonoriensis) and Peninsular (A. a. peninsularis) pronghorn persist largely because of captive breeding and reintroduction efforts. Recovery team managers want to re-establish pronghorn in their native range, but there is currently uncertainty regarding the subspecies status of extinct pronghorn populations that historically inhabited southern California, USA, and northern Baja California, Mexico. To address this uncertainty, we genotyped museum specimens and conducted phylogenetic and population genetic analyses of historical data in the context of 3 contemporary pronghorn populations. The historical northern Baja California pronghorn share the most ancestry with contemporary Peninsular pronghorn, whereas pronghorn in southern California share more ancestry with contemporary American (A. a. americana) pronghorn. For reintroductions into northern Baja California, the Peninsular subspecies is more appropriate based on museum genetic data. For reintroductions into Southern California, ecological and genetic factors are both important, as the subspecies most genetically related to historical populations (American) may not be well-adapted to the hot, low-elevation deserts of the reintroduction area. © 2019 The Wildlife Society.
Atmospheric rivers (ARs) significantly influence precipitation and hydrologic variability in many areas of the world, including the western United States. As ARs are increasingly recognized by the research community and the public, there is a need to more precisely quantify and communicate their hydrologic impacts, which can vary from hazardous to beneficial depending on location and on the atmospheric and land surface conditions prior to and during the AR. This study leverages 33 years of atmospheric and hydrologic data for the western United States to 1) identify how water vapor amount, wind direction and speed, temperature, and antecedent soil moisture conditions influence precipitation and hydrologic responses (runoff, recharge, and snowpack) using quantile regression and 2) identify differences in hydrologic response types and magnitudes across the study region. Results indicate that water vapor amount serves as a primary control on precipitation amounts. Holding water vapor constant, precipitation amounts vary with wind direction, depending on location, and are consistently greater at colder temperatures. Runoff efficiencies further covary with temperature and antecedent soil moisture, with precipitation falling as snow and greater available water storage in the soil column mitigating flood impacts of large AR events. This study identifies the coastal and maritime mountain ranges as areas with the greatest potential for hazardous flooding and snowfall impacts. This spatially explicit information can lead to better understanding of the conditions under which ARs of different precipitation amounts are likely to be hazardous at a given location.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-19-0119.1","usgsCitation":"Albano, C.M., Dettinger, M.D., and Harpold, A., 2020, Patterns and drivers of atmospheric river precipitation and hydrologic impacts across the western United States: Journal of Hydrometeorology, v. 21, p. 143-159, https://doi.org/10.1175/JHM-D-19-0119.1.","productDescription":"17 p.","startPage":"143","endPage":"159","ipdsId":"IP-108504","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":458275,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-19-0119.1","text":"Publisher Index Page"},{"id":387290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -127.3095703125,\n 31.541089879585808\n ],\n [\n -108.9404296875,\n 31.541089879585808\n ],\n [\n -108.9404296875,\n 49.26780455063753\n ],\n [\n -127.3095703125,\n 49.26780455063753\n ],\n [\n -127.3095703125,\n 31.541089879585808\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Albano, Christine M.","contributorId":169455,"corporation":false,"usgs":false,"family":"Albano","given":"Christine","email":"","middleInitial":"M.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":819519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dettinger, Michael D. 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":149896,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael","email":"mddettin@usgs.gov","middleInitial":"D.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":819520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harpold, Adrian","contributorId":184147,"corporation":false,"usgs":false,"family":"Harpold","given":"Adrian","affiliations":[],"preferred":false,"id":819521,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208152,"text":"70208152 - 2020 - Benthic infaunal communities of Baltimore and Norfolk Canyons","interactions":[],"lastModifiedDate":"2020-01-31T07:06:34","indexId":"70208152","displayToPublicDate":"2020-01-01T07:02:18","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Benthic infaunal communities of Baltimore and Norfolk Canyons","docAbstract":"The imperative for finding, cataloging, and understanding continental margin diversity derives\nfrom the many key functions, goods and services provided by margin ecosystems and by an\nincreasingly deleterious human footprint on our continental slopes (Levin and Dayton 2009). Progress in seafloor mapping technology and direct observation has revealed unexpected heterogeneity, with a mosaic of habitats and ecosystems linked to geomorphological, geochemical, and hydrographic features that are capable of influencing biotic diversity (Levin and Sibuet 2012).\n\nSubmarine canyons are dramatic and widespread topographic features crossing continental and\nisland margins in oceans, connecting shelf-margins to deep ocean basins (Harris and Whiteway 2011). Their importance as biodiversity hotspots has continued to emerge over the last two decades as research efforts have increased. Understanding the physical parameters within a canyon system is a primary factor for understanding habitat variability and ecological patterns within the confines of canyon systems (Levin et al. 2001). Margin sediments exhibit ubiquitous depth zonation (Carney et al. 2005), with a diverse suite of species that occupy restricted bathymetric ranges along any given section of the margin. Major shifts in composition among taxa are observed at the shelf-slope transition zone (canyons <500 m), along the upper slope (1,000 m), and at the lower slope transition zone (<3,000 m) (Gibson et al. 2005).\n\nIn the deep sea, macrofaunal assemblages are generally limited by the availability of allochthonous organic material (Rowe et al. 1982, Billet et al. 1983, Rex et al. 2005, Smith et al. 2008) where macrofaunal densities usually decline with depth and distance from the shore (Rowe et al. 1982, Houston and Haedrich 1984, Rex et al. 2005). However, canyon fauna can experience enhanced food supply through the resuspension and deposition of organic-rich sediments, delivered by increased current velocities within the confines of the canyon (Rowe 1971, Shepard et al. 1974). As a result, canyons are often reported as sustaining enhanced abundances and biomass compared with nearby open slope habitats at similar depths (Vetter and Dayton 1998, Duineveld et al. 2001, De Leo et al. 2010) as well as enhancing regional (γ) and local (α) biodiversity (Hecker et al. 1983, Vetter and Dayton 1998, De Leo et al. 2010, Vetter et al. 2010). Furthermore, enhanced habitat heterogeneity can also be a major structuring agent of ecological assemblages, promoting beta (β) diversity (McClain and\nBarry 2010) in canyon environments.\n\nCanyon systems have often been described as biodiversity hotspots, especially at mid-slope depths (Levin and Sibuet 2012) where physical processes, characterized by complex patterns in hydrography, promote topographically induced upwelling, enhanced mixing via internal tides, and the focusing of tidal bores (Vetter and Dayton 1998, Cacchione et al. 2002). Additionally, sediment transport and accumulation (García et al. 2008) represent important influential ecological drivers. Factors such as substrata heterogeneity (Levin and Sibuet 2012) and concentration of organic matter (De Leo et al. 2010) have been suggested to explain higher faunal diversity, abundance, and benthic productivity found in canyon systems compared with surrounding areas. Bathymetric patterns of species diversity have been attributed to changes in sediment characteristics (Etter and Grassle 1992), productivity, currents, oxygen, disturbance, and the interplay of biotic effects with depth and latitude (Levin et al. 2001, Carney et al. 2005).\n\nRecent studies report on the uniqueness of canyon benthic communities and habitats and the view that no two canyons are alike (Cunha et al. 2011). Certain submarine canyons may maintain 436 characteristic and unique faunas, but more often canyon macrofaunal assemblages show high dominance and locally reduced biodiversity (Rowe 1971, Gage 1997, Curdia et al. 2004, Cun","language":"English","publisher":"Bureau of Ocean Energy Management","usgsCitation":"Robertson, C.M., Bourque, J.R., and Demopoulos, A., 2020, Benthic infaunal communities of Baltimore and Norfolk Canyons, 76 p.","productDescription":"76 p.","startPage":"435","endPage":"510","ipdsId":"IP-090160","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":371787,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":371697,"type":{"id":11,"text":"Document"},"url":"https://espis.boem.gov/final%20reports/5655.pdf"}],"country":"United States","otherGeospatial":"Baltimore Canyon, Norfolk Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.267333984375,\n 35.209721645221386\n ],\n [\n -74.99267578125,\n 34.66032236481892\n ],\n [\n -74.24560546875,\n 35.074964853989556\n ],\n [\n -73.5205078125,\n 36.31512514748051\n ],\n [\n -72.61962890625,\n 37.61423141542417\n ],\n [\n -71.663818359375,\n 38.94232097947902\n ],\n [\n -71.89453125,\n 39.52946653645165\n ],\n [\n -72.685546875,\n 39.41922073655956\n ],\n [\n -73.65234375,\n 38.71123253895224\n ],\n [\n -74.59716796875,\n 37.22158045838649\n ],\n [\n -75.267333984375,\n 35.209721645221386\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robertson, Craig M.","contributorId":169050,"corporation":false,"usgs":false,"family":"Robertson","given":"Craig","email":"","middleInitial":"M.","affiliations":[{"id":25399,"text":"Bangor University, Wales, UK","active":true,"usgs":false}],"preferred":false,"id":780728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bourque, Jill R. 0000-0003-3809-2601","orcid":"https://orcid.org/0000-0003-3809-2601","contributorId":215719,"corporation":false,"usgs":true,"family":"Bourque","given":"Jill","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":780729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":215717,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":780727,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70212124,"text":"70212124 - 2020 - Semiautomated process for enumeration of fishes from recreational-grade side-scan sonar imagery","interactions":[],"lastModifiedDate":"2020-08-14T13:40:27.721905","indexId":"70212124","displayToPublicDate":"2020-01-01T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Semiautomated process for enumeration of fishes from recreational-grade side-scan sonar imagery","docAbstract":"The use of hydroacoustic techniques is increasing as scientists search for less invasive ways to monitor fish populations, and using recreational side‐scan sonar (SSS) imagery for monitoring has become more common in aquatic resource management over the last 15 years due in part to its low cost and user‐friendly interface. The time‐consuming nature of manually counting fish targets has limited the use of the data that is collected by these systems in research or management contexts. To reduce the time and effort that is required to enumerate acoustic targets that are presumed to be fish, we developed a semiautomated process that rapidly quantifies targets from recreational SSS imagery by using an open‐source image processing software. Perceived fish targets were enumerated using a set of macroinstructions that performed similarly to manual enumeration by three experienced assessors. This method reduced variation that arises from individual assessors and eliminated the prohibitive time constraints that are associated with manual processing. Herein, we describe how our semiautomated process could be used in fisheries management contexts after further research and development of sampling methods. Future research will focus on field validation, quantifying relative abundance, testing across a broader range of environmental conditions, and exploring other applications for fisheries management.N","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10373","usgsCitation":"Lawson, K.M., Ridgway, J.L., Mueller, A.T., Faulkner, J., and Calfee, R.D., 2020, Semiautomated process for enumeration of fishes from recreational-grade side-scan sonar imagery: North American Journal of Fisheries Management, v. 40, no. 1, p. 75-83, https://doi.org/10.1002/nafm.10373.","productDescription":"9 p.","startPage":"75","endPage":"83","ipdsId":"IP-104107","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":458278,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10373","text":"Publisher Index Page"},{"id":437181,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AKBIK9","text":"USGS data release","linkHelpText":"Semi-automated and manual enumeration of bigheaded carps from recreational-grade side-scan sonar imagery, Perche Creek, MO, 2018"},{"id":377504,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Lawson, Katelyn M 0000-0002-8017-3352","orcid":"https://orcid.org/0000-0002-8017-3352","contributorId":238276,"corporation":false,"usgs":true,"family":"Lawson","given":"Katelyn","email":"","middleInitial":"M","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":796232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ridgway, Josey Lee 0000-0003-4157-7255","orcid":"https://orcid.org/0000-0003-4157-7255","contributorId":238277,"corporation":false,"usgs":true,"family":"Ridgway","given":"Josey","email":"","middleInitial":"Lee","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":796233,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueller, Andrew T. 0000-0001-8566-8023","orcid":"https://orcid.org/0000-0001-8566-8023","contributorId":238278,"corporation":false,"usgs":true,"family":"Mueller","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":796234,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Faulkner, Jacob 0000-0002-8109-9107","orcid":"https://orcid.org/0000-0002-8109-9107","contributorId":238279,"corporation":false,"usgs":true,"family":"Faulkner","given":"Jacob","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":796235,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":796236,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208625,"text":"70208625 - 2020 - Temporospatial shifts in Sandhill Crane staging in the Central Platte River Valley in response to climatic variation and habitat change","interactions":[],"lastModifiedDate":"2020-12-15T20:16:16.059853","indexId":"70208625","displayToPublicDate":"2019-12-31T14:44:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2785,"text":"Monographs of the Western North American Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Temporospatial shifts in Sandhill Crane staging in the Central Platte River Valley in response to climatic variation and habitat change","docAbstract":"Over 80% of the Mid-Continent Sandhill Crane (Antigone canadensis) Population (MCP), estimated at over 660,000 individuals, stops in the Central Platte River Valley (CPRV) during spring migration from mid-February through mid-April. Research suggests that the MCP may be shifting its distribution spatially and temporally within the CPRV. From 2002 to 2017, we conducted weekly aerial surveys of Sandhill Cranes staging in the CPRV to examine temporal and spatial trends in their abundance and distribution. Then, we used winter temperature and drought severity measures from key wintering and early migratory stopover locations to assess the impacts of weather patterns on annual migration chronology in the CPRV. We also evaluated channel width and land cover characteristics using aerial imagery from 1938, 1998, and 2016 to assess the relationship between habitat change and the spatial distribution of the MCP in the CPRV. We used generalized linear models, cumulative link models, and Akaike’s information criterion corrected for small sample sizes (AICc) to compare temporal and spatial models. Temperatures and drought conditions at wintering and migration locations that are heavily used by Greater Sandhill Cranes (A. c. tabida) best predicted migration chronology of the MCP to the CPRV. The spatial distribution of roosting Sandhill Cranes from 2015 to 2017 was best predicted by the proportion of width reduction in the main channel since 1938 (rather than its width in 2016) and the proportion of land cover as prairie-meadow habitat within 800 m of the Platte River. Our data suggest that Sandhill Cranes advanced their migration by an average of just over 1 day per year from 2002 to 2017, and that they continued to shift eastward, concentrating at eastern reaches of the CPRV. Climate change, land use change, and habitat loss have all likely contributed to Sandhill Cranes coming earlier and staying longer in fewer reaches of the CPRV, increasing their site use intensity. These historically unprecedented densities may present a disease risk to Sandhill Cranes and other waterbirds, including Whooping Cranes (Grus americana). Our models suggest that conservation actions may be maintaining Sandhill Crane densities in areas that would otherwise be declining in use. We suggest that management actions intended to mitigate trends in the distribution of Sandhill Cranes, including wet meadow restoration, may similarly benefit prairie- and braided river–endemic species of concern.
","language":"English","publisher":"BioOne","doi":"10.3398/042.011.0104","usgsCitation":"Caven, A.J., Brinley Buckley, E.M., King, K.C., Wiese, J.D., Baasch, D.M., Wright, G.D., Harner, M.J., Pearse, A.T., Rabbe, M., Varner, D., Krohn, B., Arcilla, N., Schroeder, K.D., and Dinan, K.F., 2020, Temporospatial shifts in Sandhill Crane staging in the Central Platte River Valley in response to climatic variation and habitat change: Monographs of the Western North American Naturalist, v. 11, p. 33-76, https://doi.org/10.3398/042.011.0104.","productDescription":"44 p.","startPage":"33","endPage":"76","ipdsId":"IP-102357","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":458279,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3398/042.011.0104","text":"Publisher Index Page"},{"id":372957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Platte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.03237915039062,\n 41.024981358869915\n ],\n [\n -98.06465148925781,\n 41.055537533528636\n ],\n [\n -98.27957153320312,\n 40.954492756949186\n ],\n [\n -98.40934753417967,\n 40.88029480552824\n ],\n [\n -98.81515502929688,\n 40.73112880602221\n ],\n [\n -98.99642944335938,\n 40.69938133866613\n ],\n [\n -99.55535888671874,\n 40.73321007823572\n ],\n [\n -99.60548400878906,\n 40.66293116628907\n ],\n [\n -99.1845703125,\n 40.63740418690266\n ],\n [\n -98.86459350585938,\n 40.64469860601899\n ],\n [\n -98.55491638183594,\n 40.72540497175607\n ],\n [\n -98.28781127929688,\n 40.805493843894155\n ],\n [\n -98.16970825195312,\n 40.91039911873504\n ],\n [\n -98.03237915039062,\n 41.024981358869915\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Caven, Andrew J.","contributorId":177586,"corporation":false,"usgs":false,"family":"Caven","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":782798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brinley Buckley, Emma M.","contributorId":198370,"corporation":false,"usgs":false,"family":"Brinley Buckley","given":"Emma","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":782799,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"King, Kelsey C","contributorId":222650,"corporation":false,"usgs":false,"family":"King","given":"Kelsey","email":"","middleInitial":"C","affiliations":[{"id":40581,"text":"Platte River Whooping Crane Maintenance Trust","active":true,"usgs":false}],"preferred":false,"id":782800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiese, Joshua D","contributorId":222651,"corporation":false,"usgs":false,"family":"Wiese","given":"Joshua","email":"","middleInitial":"D","affiliations":[{"id":40581,"text":"Platte River Whooping Crane Maintenance Trust","active":true,"usgs":false}],"preferred":false,"id":782801,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baasch, David M.","contributorId":147145,"corporation":false,"usgs":false,"family":"Baasch","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":16795,"text":"Headwaters Corp, Kearney, NE","active":true,"usgs":false}],"preferred":false,"id":782802,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wright, Greg D.","contributorId":177585,"corporation":false,"usgs":false,"family":"Wright","given":"Greg","email":"","middleInitial":"D.","affiliations":[{"id":12957,"text":"Chippewa Ottawa Resource Authority","active":true,"usgs":false}],"preferred":false,"id":782803,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harner, Mary J.","contributorId":177584,"corporation":false,"usgs":false,"family":"Harner","given":"Mary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":782804,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":782797,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rabbe, Matt","contributorId":202597,"corporation":false,"usgs":false,"family":"Rabbe","given":"Matt","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":782805,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Varner, Dana","contributorId":222652,"corporation":false,"usgs":false,"family":"Varner","given":"Dana","affiliations":[{"id":40582,"text":"Rainwater Basin Joint Venture","active":true,"usgs":false}],"preferred":false,"id":782806,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Krohn, Brice","contributorId":222653,"corporation":false,"usgs":false,"family":"Krohn","given":"Brice","email":"","affiliations":[{"id":40581,"text":"Platte River Whooping Crane Maintenance Trust","active":true,"usgs":false}],"preferred":false,"id":782807,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Arcilla, Nicole","contributorId":223085,"corporation":false,"usgs":false,"family":"Arcilla","given":"Nicole","email":"","affiliations":[],"preferred":false,"id":782808,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"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":782809,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Dinan, Kenneth F","contributorId":222656,"corporation":false,"usgs":false,"family":"Dinan","given":"Kenneth","email":"","middleInitial":"F","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":782810,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70209290,"text":"70209290 - 2020 - Envisioning a national invasive species information framework","interactions":[],"lastModifiedDate":"2020-03-31T12:51:15","indexId":"70209290","displayToPublicDate":"2019-12-31T12:48:40","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Envisioning a national invasive species information framework","docAbstract":"With a view toward creating a national Early Detection and Rapid Response Program (EDRR) program, the United States National Invasive Species Council Management Plan for 2016–2018 calls for a series of assessments of federal EDRR capacities, including the evaluation of “relevant federal information systems to provide the data and other information necessary for risk analyses/horizon scanning, rapid specimen identification, and rapid response planning.” This paper is a response to that directive. We provide an overview of information management needs for enacting EDRR and discuss challenges to meeting these needs. We then review the history of relevant US policy directives for advancing invasive species information systems and provide an overview of federal invasive species information system capacities, including current gaps and inconsistencies. We conclude with a summary of key principles and needs for establishing a national invasive species information framework. Our findings are consistent with earlier studies and, thus, emphasize the need to act on long-recognized needs. As a supplement to this paper, we have cataloged federal invasive species databases and information tools identified through this work.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-019-02141-3","usgsCitation":"Reaser, J.K., Simpson, A., Guala, G., Morisette, J., and Fuller, P., 2020, Envisioning a national invasive species information framework: Biological Invasions, v. 22, no. 1, p. 21-36, https://doi.org/10.1007/s10530-019-02141-3.","productDescription":"16 p.","startPage":"21","endPage":"36","ipdsId":"IP-103628","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":458280,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10530-019-02141-3","text":"Publisher Index Page"},{"id":373661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Reaser, Jamie K","contributorId":223683,"corporation":false,"usgs":false,"family":"Reaser","given":"Jamie","email":"","middleInitial":"K","affiliations":[{"id":39207,"text":"Department of the Interior","active":true,"usgs":false}],"preferred":false,"id":785903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simpson, Annie 0000-0001-8338-5134","orcid":"https://orcid.org/0000-0001-8338-5134","contributorId":206062,"corporation":false,"usgs":true,"family":"Simpson","given":"Annie","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":785902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guala, Gerald","contributorId":223684,"corporation":false,"usgs":true,"family":"Guala","given":"Gerald","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":785904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morisette, Jeffrey 0000-0002-0483-0082","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":212187,"corporation":false,"usgs":false,"family":"Morisette","given":"Jeffrey","affiliations":[{"id":38451,"text":"U.S. Department of the Interior, National Invasive Species Council Secretariat","active":true,"usgs":false}],"preferred":false,"id":785905,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuller, Pam 0000-0002-9389-9144 pfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9389-9144","contributorId":223685,"corporation":false,"usgs":true,"family":"Fuller","given":"Pam","email":"pfuller@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":785906,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215618,"text":"70215618 - 2020 - Scale-specific metrics for adaptive generalization and geomorphic classification of stream features","interactions":[],"lastModifiedDate":"2020-10-27T12:18:02.666651","indexId":"70215618","displayToPublicDate":"2019-12-31T11:25:30","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Scale-specific metrics for adaptive generalization and geomorphic classification of stream features","docAbstract":"The Richardson plot has been used to illustrate fractal dimension of naturally occurring landscape features that are sensitive to changes in scale or resolution, such as coastlines and river channels. The Richardson method estimates the length of a path by traversing (i.e., “walking”) the path with a specific stride length. Fractal dimension is determined as the slope of the Richardson plot, which shows path length over a range of stride lengths graphed on log-log axes. This paper describes a variant of the Richardson plot referred to as the Scale-Specific Sinuosity (S3) plot. S3 is defined as negative one times the slope of the Richardson plot for a given stride length. A plot of S3 against stride length offers a frequency distribution whose area under the curve reflects total sinuosity, and whose points mark the amount of sinuosity contributed to the total sinuosity at each stride length. Mathematical relations of S3 with fractal dimension and sinuosity for linear features are described. The S3 metric is demonstrated and discussed for several linear stream features distributed over the conterminous United States. The S3 metric can help guide the preservation of stream feature sinuosity during cartographic generalization and may assist automated geomorphic classification of river systems.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Program and papers","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Abstractions, Scales, and Perception, 22nd ICA Workshop","conferenceDate":"July 15, 2019","conferenceLocation":"Tokyo, Japan","language":"English","publisher":"International Cartographic Association","usgsCitation":"Stanislawski, L., Buttenfield, B.P., Kronenfeld, B.J., and Shavers, E.J., 2020, Scale-specific metrics for adaptive generalization and geomorphic classification of stream features, in Program and papers, Tokyo, Japan, July 15, 2019, 9 p.","productDescription":"9 p.","ipdsId":"IP-109076","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":379765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":379746,"type":{"id":15,"text":"Index Page"},"url":"https://generalisation.icaci.org/prevevents/workshop2019.html"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stanislawski, Larry 0000-0002-9437-0576","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":217849,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":803002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buttenfield, Barbara P. 0000-0001-5961-5809","orcid":"https://orcid.org/0000-0001-5961-5809","contributorId":206887,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara","email":"","middleInitial":"P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":803003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kronenfeld, Barry J. 0000-0002-9518-2462","orcid":"https://orcid.org/0000-0002-9518-2462","contributorId":207104,"corporation":false,"usgs":false,"family":"Kronenfeld","given":"Barry","email":"","middleInitial":"J.","affiliations":[{"id":5043,"text":"Eastern Illinois University","active":true,"usgs":false}],"preferred":false,"id":803004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shavers, Ethan J. 0000-0001-9470-5199 eshavers@usgs.gov","orcid":"https://orcid.org/0000-0001-9470-5199","contributorId":206890,"corporation":false,"usgs":true,"family":"Shavers","given":"Ethan","email":"eshavers@usgs.gov","middleInitial":"J.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":803005,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209255,"text":"70209255 - 2020 - Event and decadal-scale modeling of barrier island restoration designs for decision support","interactions":[],"lastModifiedDate":"2020-03-26T11:18:40","indexId":"70209255","displayToPublicDate":"2019-12-31T11:18:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3385,"text":"Shore & Beach","printIssn":"0037-4237","active":true,"publicationSubtype":{"id":10}},"title":"Event and decadal-scale modeling of barrier island restoration designs for decision support","docAbstract":"An interdisciplinary project team was convened to develop a modeling framework that simulates the potential impacts of storms and sea level-rise to habitat availability at Breton Island, Louisiana (Breton) for existing conditions and potential future restoration designs. The model framework was iteratively developed through evaluation of model results at multiple checkpoints. A methodology was developed for characterizing regional wave and water levels, and the numerical model XBeach was used to simulate the potential impacts from a wide range of storm events. Simulations quantified the potential for erosion, overwash, and inundation of the pre- and post-restoration beach and dune system and were used as a preliminary screening of restoration designs. The model framework also incorporated a computationally efficient method to evaluate the impacts of storms, long-term shoreline changes, and relative sea level rise over a 15-year time period in order to evaluate the effect of the preferred restoration alternative on habitat distribution. Results directly informed engineering design decisions and expedited later project stages including the construction permitting process.","language":"English","publisher":"American Shore and Beach Preservation Association","usgsCitation":"Long, J.W., Dalyander, P., Poff, M., Spears, B., Borne, B., Thompson, D.M., Mickey, R.C., Dartez, S., and Gandy, G., 2020, Event and decadal-scale modeling of barrier island restoration designs for decision support: Shore & Beach, v. 88, no. 1, p. 49-57.","productDescription":"9 p.","startPage":"49","endPage":"57","ipdsId":"IP-115503","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":373548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":373522,"type":{"id":15,"text":"Index Page"},"url":"https://asbpa.org/publications/shore-and-beach/shore-beach-in-2020-vol-88/"}],"volume":"88","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Long, Joseph W. 0000-0003-2912-1992","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":219235,"corporation":false,"usgs":false,"family":"Long","given":"Joseph","email":"","middleInitial":"W.","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":785594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dalyander, P. Soupy 0000-0001-9583-0872","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":221891,"corporation":false,"usgs":false,"family":"Dalyander","given":"P. Soupy","affiliations":[{"id":40456,"text":"St. Petersburg Coastal and Marine Science Center (Former Employee)","active":true,"usgs":false}],"preferred":false,"id":785595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poff, Michael","contributorId":223601,"corporation":false,"usgs":false,"family":"Poff","given":"Michael","email":"","affiliations":[{"id":40745,"text":"Coastal Engineering Consultants, Inc.","active":true,"usgs":false}],"preferred":false,"id":785596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spears, Brian","contributorId":223602,"corporation":false,"usgs":false,"family":"Spears","given":"Brian","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":785597,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Borne, Brett","contributorId":223603,"corporation":false,"usgs":false,"family":"Borne","given":"Brett","email":"","affiliations":[{"id":40745,"text":"Coastal Engineering Consultants, Inc.","active":true,"usgs":false}],"preferred":false,"id":785598,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thompson, David M. 0000-0002-7103-5740 dthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-7103-5740","contributorId":3502,"corporation":false,"usgs":true,"family":"Thompson","given":"David","email":"dthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":785593,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mickey, Rangley C. 0000-0001-5989-1432 rmickey@usgs.gov","orcid":"https://orcid.org/0000-0001-5989-1432","contributorId":141016,"corporation":false,"usgs":true,"family":"Mickey","given":"Rangley","email":"rmickey@usgs.gov","middleInitial":"C.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":785599,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dartez, Steve","contributorId":223604,"corporation":false,"usgs":false,"family":"Dartez","given":"Steve","email":"","affiliations":[{"id":40745,"text":"Coastal Engineering Consultants, Inc.","active":true,"usgs":false}],"preferred":false,"id":785600,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gandy, Gregory","contributorId":223605,"corporation":false,"usgs":false,"family":"Gandy","given":"Gregory","email":"","affiliations":[{"id":13608,"text":"Louisiana Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":785601,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70216997,"text":"70216997 - 2020 - A transect through Vermont's most famous volcano - Mount Ascutney","interactions":[],"lastModifiedDate":"2023-03-23T16:18:22.745397","indexId":"70216997","displayToPublicDate":"2019-12-31T09:57:15","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A transect through Vermont's most famous volcano - Mount Ascutney","docAbstract":"The Cretaceous Ascutney Mountain igneous complex affords a classic exposure of the White Mountain Igneous Suite. Often called Vermont’s most famous volcano, Mount Ascutney (elev. 3,144 feet, 958 m) stands as a prominent monadnock in the Connecticut River Valley. The mountain often serves as an inspirational landmark, as it does when viewed from locations throughout the valley including the Saint-Gaudens National Historic Site (Walsh, 2017). The Ascutney Mountain igneous complex (Ratcliffe and others, 2011) consists of several mafic to felsic nested plutons including gabbro-diorite exposed at Little Ascutney to the west, and the Ascutney Mountain stock composed of syenite, granite, and related volcanic rocks underlying the main summit to the east (Fig. 1) (Schneiderman, 1989, 1991). Foland and Faul (1977) and Foland and others (1985) dated the gabbro-diorite complex at 125.5 to 122.2 Ma by K-Ar on biotite and by whole rock Rb/Sr, and dated the syenite-granite complex at 123.2 to 121.4 Ma by K-Ar on biotite. During the field trip we will visit the host rocks south of the mountain and the main rocks types of the Ascutney Mountain stock exposed near the summit and along the Mount Ascutney toll road. \n \n Mount Ascutney is the classic location where Daly (1903) discussed the evidence for piecemeal stoping as a pluton emplacement mechanism. This theory was later modified to favor cauldron subsidence, or ring-fracture stoping, as an alternative mode of emplacement (Chapman and Chapman, 1940). Our new mapping (Walsh and others, in press), which supersedes an earlier provisional study (Walsh and others, 1996a, b), supports the cauldron subsidence model, and shows that the main Ascutney Mountain stock is a funnel shaped composite pluton in agreement with geophysical data (Daniels, 1990). This field guide will primarily highlight the results of the new geologic mapping.\n\n This field guide is modified from a field trip presented in 2017 (Walsh, 2017). Additional stops have been added to examine the host rocks in the region south of the Ascutney Mountain stock. Two hikes are planned as part of this trip. Other NEIGC field trip guides to Mount Ascutney include Stoiber (1954) and Schneiderman (1988).","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"111th New England Intercollegiate Geological Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"111th New England Intercollegiate Geological Conference","conferenceDate":"October 1-13, 2019","conferenceLocation":"Barre, VT","language":"English","publisher":"New England Intercollegiate Geological Conference","usgsCitation":"Walsh, G.J., Proctor, B., Sicard, K.R., and Valley, P.M., 2020, A transect through Vermont's most famous volcano - Mount Ascutney, in 111th New England Intercollegiate Geological Conference, v. 111, Barre, VT, October 1-13, 2019, p. 1-6.","productDescription":"6 p.","startPage":"1","endPage":"6","ipdsId":"IP-109653","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":381650,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":414625,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://neigc.info/guidebooks/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Vermont","otherGeospatial":"Mount Ascutney","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.48590469360352,\n 43.4175176458317\n ],\n [\n -72.40299224853516,\n 43.4175176458317\n ],\n [\n -72.40299224853516,\n 43.466002139041116\n ],\n [\n -72.48590469360352,\n 43.466002139041116\n ],\n [\n -72.48590469360352,\n 43.4175176458317\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"111","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":807199,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Proctor, Brooks P. 0000-0002-4878-8728 bproctor@usgs.gov","orcid":"https://orcid.org/0000-0002-4878-8728","contributorId":178527,"corporation":false,"usgs":true,"family":"Proctor","given":"Brooks P.","email":"bproctor@usgs.gov","affiliations":[],"preferred":true,"id":807200,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sicard, Karri R. 0000-0003-4062-8030","orcid":"https://orcid.org/0000-0003-4062-8030","contributorId":219210,"corporation":false,"usgs":false,"family":"Sicard","given":"Karri","email":"","middleInitial":"R.","affiliations":[],"preferred":true,"id":807201,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":807202,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216799,"text":"70216799 - 2020 - Micrometer-scale characterization of solid mine waste aids in closure due diligence","interactions":[],"lastModifiedDate":"2020-12-09T12:59:49.381577","indexId":"70216799","displayToPublicDate":"2019-12-31T09:54:10","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Micrometer-scale characterization of solid mine waste aids in closure due diligence","docAbstract":"Precious- and base-metal mining often occurs in deposits with high acid-generating potential, resulting in mine waste that contains metals in forms of varying bioavailability, and therefore toxicity. The solids that host these metals are often noncrystalline, nanometer to micrometer in size, or undetectable by readily available analytical techniques (e.g., X-ray diffraction). This analytical shortcoming can pose a challenge when attempting to characterize sources and natural attenuation of metals at a given site, which is a best practice to satisfy closure due diligence. Numerous case studies have shown that efforts to characterize mine waste at multiple scales, particularly the micrometer scale, often lead to a better understanding of metal distribution and potential contamination risks.
This paper presents a case study that compares the use of both traditional and non-traditional techniques to identify and quantify metal hosts in sediments downstream of the abandoned mine waste piles at the Ely Copper Mine Superfund site in Vermont (USA). The contaminant present in the highest concentration in the sediments is copper, yet not all copper-bearing solids were detected with bulk X-ray diffraction (XRD). At the micrometer scale, a combination of synchrotron-based X-ray absorption spectroscopy (XAS) and an automated mineralogy (AM) system were used to identify the most abundant copper-bearing solids. Bulk XAS and AM also provided semi-quantitative abundances of these solids in the sediment.
At the Ely Copper Mine, copper in stream sediments was found to be predominantly hosted in sulphide minerals downstream of a major mine waste pile, whereas upstream copper was predominantly hosted in secondary iron and manganese (oxyhydr)oxides. These copper-bearing hosts were consistent with the expected bioavailability of copper in the sediments based on laboratory toxicity tests with aquatic organisms. When the bulk of copper was present in sulphides, aquatic organisms experienced greater survival than when copper was mostly associated with secondary iron and manganese (oxyhydr)oxides. The information gained from probing the sediments at multiple scales can now be used to prioritize containment and remediation strategies.
While synchrotron-based analytical techniques have proven to be invaluable in many studies of mine waste, access to these techniques is limited. In contrast, access to a scanning electron microscope that can perform AM is becoming more common, primarily for the application in mining design and mineral processing operations. More recently, the successful use of AM to characterize mine waste suggests that this technique can be equally as valuable for mine closure plans. The resolution of information obtained may go beyond what is required from a regulatory perspective, but given that the results have the potential to be more conclusive than many traditional techniques, this level of characterization may save time and money in the long run.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of tailings and mine waste 2019","largerWorkSubtype":{"id":15,"text":"Monograph"},"conferenceTitle":"Tailings and Mine Waste 2019","conferenceDate":"November 17-20, 2019","conferenceLocation":"Vancouver, BC","language":"English","publisher":"University of British Columbia","usgsCitation":"Bryn E. Kimball, Jamieson, H., Seal,, R., Dobosz, A., and Piatak, N.M., 2020, Micrometer-scale characterization of solid mine waste aids in closure due diligence, in Proceedings of tailings and mine waste 2019, Vancouver, BC, November 17-20, 2019, p. 569-580.","productDescription":"12 p.","startPage":"569","endPage":"580","ipdsId":"IP-111822","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":381106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381105,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://tailingsandminewaste.com/2019-program-proceedings/"}],"country":"United States","state":"Vermont","otherGeospatial":"Ely Brook","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.29246377944946,\n 43.91788126751183\n ],\n [\n -72.2829794883728,\n 43.91788126751183\n ],\n [\n -72.2829794883728,\n 43.9283136288617\n ],\n [\n -72.29246377944946,\n 43.9283136288617\n ],\n [\n -72.29246377944946,\n 43.91788126751183\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bryn E. Kimball","contributorId":245507,"corporation":false,"usgs":false,"family":"Bryn E. Kimball","affiliations":[{"id":49206,"text":"INTERA Incorporated","active":true,"usgs":false}],"preferred":false,"id":806318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jamieson, Heather E.","contributorId":245508,"corporation":false,"usgs":false,"family":"Jamieson","given":"Heather E.","affiliations":[{"id":49208,"text":"Queen’s University, Canada","active":true,"usgs":false}],"preferred":false,"id":806319,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seal,, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":141204,"corporation":false,"usgs":true,"family":"Seal,","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":806320,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dobosz, Agatha","contributorId":245509,"corporation":false,"usgs":false,"family":"Dobosz","given":"Agatha","email":"","affiliations":[{"id":49208,"text":"Queen’s University, Canada","active":true,"usgs":false}],"preferred":false,"id":806321,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Piatak, Nadine M. 0000-0002-1973-8537 npiatak@usgs.gov","orcid":"https://orcid.org/0000-0002-1973-8537","contributorId":193010,"corporation":false,"usgs":true,"family":"Piatak","given":"Nadine","email":"npiatak@usgs.gov","middleInitial":"M.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":806322,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208091,"text":"70208091 - 2020 - Establishing high-frequency noise baselines to 100 Hz based on millions of power spectra from IRIS MUSTANG","interactions":[],"lastModifiedDate":"2020-02-06T11:42:11","indexId":"70208091","displayToPublicDate":"2019-12-31T07:16:23","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Establishing high-frequency noise baselines to 100 Hz based on millions of power spectra from IRIS MUSTANG","docAbstract":"Advances in seismic instrumentation have enabled data to be recorded at increasing sample rates. This has in turn created a need to establish higher-frequency baselines for assessing data quality, as the widely-used New High (NHNM) and Low Noise Models (NLNM) of Peterson (1993) do not extend to frequencies above 10 Hz. To provide a baseline for higher frequencies (10-100 Hz), we examine power spectral density probability density functions (PSDPDFs) for high-sample-rate stations available from the Incorporated Research Institutions for Seismology Data Services (IRIS DS) MUSTANG quality control system. We compute high-frequency high and low noise baselines by matching the appropriate composite PSDPDF percentile points to NHNM and NLNM power levels at overlapping frequencies (1-10 Hz) and then extending to higher frequencies (10-100 Hz) with piecewise linear fits to the matching PSDPDF percentile.\n\nWe find that the Peterson NLNM remains an accurate representation of the lower bound of global ambient Earth noise since it is matched by only 0.1% of Global Seismographic Network (GSN) PSDs. We present high-frequency high and low noise baselines intended primarily for use by temporary networks targeting high-frequency signals (e.g. monitoring of aftershocks or induced seismicity) based on statistics of PSDPDFs from all publicly available high-sample-rate data. \n\nMost publicly-available high-sample-rate data is recorded by temporary deployments, and the experiment design and scientific targets of these deployments strongly influence the observed statistical distribution of high-frequency noise. We anticipate that the noise baselines presented here will be useful in automated quality control of high-sample-rate seismic data. However, we note that establishing a low noise model that accurately represents the lowest possible ambient Earth noise at frequencies up to 100 Hz will require additional continuous high-sample-rate data from high-quality permanent stations in low-noise environments.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120190123","usgsCitation":"Wolin, E., and McNamara, D., 2020, Establishing high-frequency noise baselines to 100 Hz based on millions of power spectra from IRIS MUSTANG: Bulletin of the Seismological Society of America, v. 110, no. 1, p. 270-278, https://doi.org/10.1785/0120190123.","productDescription":"9 p.","startPage":"270","endPage":"278","ipdsId":"IP-107994","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":371634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"110","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-31","publicationStatus":"PW","contributors":{"authors":[{"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":780442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McNamara, Daniel 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":221835,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":780443,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70208092,"text":"70208092 - 2020 - Integrating multiple data sources and multi-scale land-cover data to model the distribution of a declining amphibian","interactions":[],"lastModifiedDate":"2020-01-27T19:59:37","indexId":"70208092","displayToPublicDate":"2019-12-30T19:58:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Integrating multiple data sources and multi-scale land-cover data to model the distribution of a declining amphibian","docAbstract":"Determining the spatial scale at which landscape features influence population persistence is an important task for conservation planning. One challenge is that sampling biases confound factors that influence species occurrence and survey effort. Recent developments in Point Process Models (PPMs) enable researchers to disentangle the sampling process from ecological drivers of species' distributions. Land-cover change is a driver of decline for the western spadefoot (Spea hammondii), which has been extirpated from much of its range in California. Assessing this species' status requires information on the current distribution of suitable habitat within its historical range, but little is known about the effect of the landscape surrounding breeding ponds on spadefoot occurrence. Critically, surveys for western spadefoots often occur along roads, potentially biasing data used to fit species distribution models. We created PPMs integrating historical presence/non-detection and presence-only data for western spadefoots and land-cover data at multiple spatial scales to model the distribution of this species while removing the influence of sampling bias. There was spatial sampling bias in presence-only data; records were more likely to be reported near roads and urban centers and PPMs that removed sampling bias outperformed models that ignored sampling bias. The occurrence of western spadefoots was positively related to the proportion of grassland within a 2000 m buffer. The remaining habitat for western spadefoots is largely found in the foothills surrounding California's Central Valley. Our study illustrates how PPMs can improve projections of habitat suitability and our understanding of the drivers of species' distributions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2019.108374","usgsCitation":"Rose, J.P., Halstead, B., and Fisher, R.N., 2020, Integrating multiple data sources and multi-scale land-cover data to model the distribution of a declining amphibian: Biological Conservation, v. 241, 108374, https://doi.org/10.1016/j.biocon.2019.108374.","productDescription":"108374","ipdsId":"IP-108816","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458282,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2019.108374","text":"Publisher Index Page"},{"id":371628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.14599609375001,\n 40.96330795307353\n ],\n [\n -123.06884765625,\n 41.062786068733026\n ],\n [\n -123.15673828124999,\n 39.13006024213511\n ],\n [\n -120.21240234375001,\n 35.06597313798418\n ],\n [\n -117.83935546874999,\n 34.17999758688084\n ],\n [\n -117.00439453125,\n 34.994003757575776\n ],\n [\n -117.97119140625,\n 36.06686213257888\n ],\n [\n -119.2236328125,\n 37.77071473849609\n ],\n [\n -122.14599609375001,\n 40.96330795307353\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"241","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780446,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211621,"text":"70211621 - 2020 - Assessment of leachable elements in volcanic ashfall: A review and evaluation of a standardized protocol for ash hazard characterization","interactions":[],"lastModifiedDate":"2020-08-10T17:01:51.255152","indexId":"70211621","displayToPublicDate":"2019-12-28T09:47:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of leachable elements in volcanic ashfall: A review and evaluation of a standardized protocol for ash hazard characterization","docAbstract":"Volcanic ash presents a widespread and common hazard during and after eruptions. Complex interactions between solid ash surfaces and volcanic gases lead to the formation of soluble salts that may be mobilized in aqueous environments. A variety of stakeholders may be concerned about the effects of ash on human and animal health, drinking water supplies, crops, soils and surface runoff. As part of the immediate emergency response, rapid dissemination of information regarding potentially hazardous concentrations of soluble species is critical. However, substantial variability in the methods used to characterize leachable elements makes it challenging to compare datasets and eruption impacts. To address these challenges, the International Volcanic Health Hazard Network (www.ivhhn.org) organized a two-day workshop to define appropriate methods for hazard assessment. The outcome of this workshop was a ‘consensus protocol’ for analysis of volcanic ash samples for rapid assessment of hazards from leachable elements, which was subsequently ratified by leading volcanological organizations. The purpose of this protocol is to recommend clear, standard and reliable methods applicable to a range of purposes during eruption response, such as assessing impacts on drinking-water supplies and ingestion hazards to livestock, and also applicable to research purposes. Where possible, it is intended that the methods make use of commonly available equipment and require little training. To evaluate method transferability, an interlaboratory comparison exercise was organized among six laboratories worldwide. Each laboratory received a split of pristine ash, and independently analyzed it according to the protocol for a wide range of elements. Collated results indicate good repeatability and reproducibility for most elements, thus indicating that the development of this protocol is a useful step towards providing standardized and reliable methods for ash hazard characterization. In this article, we review recent ash leachate studies, report the outcomes of the comparison exercise and present a revised and updated protocol based on the experiences and recommendations of the exercise participants. The adoption of standardized methods will improve and facilitate the comparability of results among studies and enable the ongoing development of a global database of leachate information relevant for informing volcanic health hazards assessment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2019.106756","usgsCitation":"Stewart, C., Damby, D., Tomasek, I., Horwell, C.J., Plumlee, G.S., Armienta, M.A., Hinojosa, M.G., Appleby, M., Delmelle, P., Cronin, S., Ottley, C.J., Oppenheimer, C., and Morman, S.A., 2020, Assessment of leachable elements in volcanic ashfall: A review and evaluation of a standardized protocol for ash hazard characterization: Journal of Volcanology and Geothermal Research, v. 392, 106756, 22 p., https://doi.org/10.1016/j.jvolgeores.2019.106756.","productDescription":"106756, 22 p.","ipdsId":"IP-112086","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":458284,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://dro.dur.ac.uk/29919/","text":"External Repository"},{"id":377039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"392","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stewart, Carol","contributorId":236960,"corporation":false,"usgs":false,"family":"Stewart","given":"Carol","email":"","affiliations":[{"id":47573,"text":"Massey University, NZ","active":true,"usgs":false}],"preferred":false,"id":794824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Damby, David 0000-0002-3238-3961","orcid":"https://orcid.org/0000-0002-3238-3961","contributorId":206614,"corporation":false,"usgs":true,"family":"Damby","given":"David","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":794825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tomasek, Ines","contributorId":205741,"corporation":false,"usgs":false,"family":"Tomasek","given":"Ines","email":"","affiliations":[{"id":37158,"text":"Institute of Hazard, Risk & Resilience, Department of Earth Sciences, Durham University, UK","active":true,"usgs":false}],"preferred":false,"id":794826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horwell, Claire J.","contributorId":177455,"corporation":false,"usgs":false,"family":"Horwell","given":"Claire","email":"","middleInitial":"J.","affiliations":[{"id":16770,"text":"Dept. Earth Sciences, Durham University, UK","active":true,"usgs":false}],"preferred":false,"id":794827,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plumlee, Geoffrey S. 0000-0002-9607-5626","orcid":"https://orcid.org/0000-0002-9607-5626","contributorId":204552,"corporation":false,"usgs":true,"family":"Plumlee","given":"Geoffrey","email":"","middleInitial":"S.","affiliations":[],"preferred":true,"id":794828,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Armienta, Maria Aurora","contributorId":236961,"corporation":false,"usgs":false,"family":"Armienta","given":"Maria","email":"","middleInitial":"Aurora","affiliations":[{"id":47574,"text":"Universidad Nacional Autónoma de México, Mexico","active":true,"usgs":false}],"preferred":false,"id":794829,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hinojosa, Maria Gabriela Ruiz","contributorId":236962,"corporation":false,"usgs":false,"family":"Hinojosa","given":"Maria","email":"","middleInitial":"Gabriela Ruiz","affiliations":[{"id":47575,"text":"UCLouvain, Belgium","active":true,"usgs":false}],"preferred":false,"id":794830,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Appleby, Moya","contributorId":236963,"corporation":false,"usgs":false,"family":"Appleby","given":"Moya","email":"","affiliations":[{"id":5111,"text":"GNS Science, New Zealand","active":true,"usgs":false}],"preferred":false,"id":794831,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Delmelle, Pierre","contributorId":236964,"corporation":false,"usgs":false,"family":"Delmelle","given":"Pierre","email":"","affiliations":[{"id":47575,"text":"UCLouvain, Belgium","active":true,"usgs":false}],"preferred":false,"id":794832,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cronin, Shane","contributorId":236965,"corporation":false,"usgs":false,"family":"Cronin","given":"Shane","affiliations":[{"id":26898,"text":"University of Auckland, New Zealand","active":true,"usgs":false}],"preferred":false,"id":794833,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ottley, Christopher J","contributorId":236967,"corporation":false,"usgs":false,"family":"Ottley","given":"Christopher","email":"","middleInitial":"J","affiliations":[{"id":40359,"text":"Durham University, UK","active":true,"usgs":false}],"preferred":false,"id":794834,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Oppenheimer, Clive","contributorId":174445,"corporation":false,"usgs":false,"family":"Oppenheimer","given":"Clive","email":"","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":794835,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Morman, Suzette A. 0000-0002-2532-1033 smorman@usgs.gov","orcid":"https://orcid.org/0000-0002-2532-1033","contributorId":996,"corporation":false,"usgs":true,"family":"Morman","given":"Suzette","email":"smorman@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":794836,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70228175,"text":"70228175 - 2020 - Increasing accuracy of lake nutrient predictions in thousands of lakes by leveraging water clarity data","interactions":[],"lastModifiedDate":"2022-02-07T17:50:09.933226","indexId":"70228175","displayToPublicDate":"2019-12-27T11:39:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5456,"text":"Limnology and Oceanography Letters","active":true,"publicationSubtype":{"id":10}},"title":"Increasing accuracy of lake nutrient predictions in thousands of lakes by leveraging water clarity data","docAbstract":"Aquatic scientists require robust, accurate information about nutrient concentrations and indicators of algal biomass in unsampled lakes in order to understand and predict the effects of global climate and land-use change. Historically, lake and landscape characteristics have been used as predictor variables in regression models to generate nutrient predictions, but often with significant uncertainty. An alternative approach to improve predictions is to leverage the observed relationship between water clarity and nutrients, which is possible because water clarity is more commonly measured than lake nutrients. We used a joint-nutrient model that conditioned predictions of total phosphorus, nitrogen, and chlorophyll a on observed water clarity. Our results demonstrated substantial reductions (8–27%; median = 23%) in prediction error when conditioning on water clarity. These models will provide new opportunities for predicting nutrient concentrations of unsampled lakes across broad spatial scales with reduced uncertainty.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lol2.10134","usgsCitation":"Wagner, T., Noah R., O.L., Bartley, M.L., Hanks, E., Schliep, E.M., Wikle, N.B., King, K.B., McCullough, I., Stachelek, J., Cheruvelil, K.S., Filstrup, C.T., Lapierre, J., Liu, B., Sorrano, P., Tan, P., Wang, Q., Webster, K., and Zhou, J., 2020, Increasing accuracy of lake nutrient predictions in thousands of lakes by leveraging water clarity data: Limnology and Oceanography Letters, v. 5, no. 2, p. 228-235, https://doi.org/10.1002/lol2.10134.","productDescription":"8 p.","startPage":"228","endPage":"235","ipdsId":"IP-109351","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":488957,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lol2.10134","text":"Publisher Index Page"},{"id":395550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noah R., oa Lottig Lottig","contributorId":274769,"corporation":false,"usgs":false,"family":"Noah R.","given":"oa","suffix":"Lottig","email":"","middleInitial":"Lottig","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":833308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartley, Meridith L.","contributorId":274772,"corporation":false,"usgs":false,"family":"Bartley","given":"Meridith","email":"","middleInitial":"L.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":833309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanks, Ephraim M.","contributorId":274775,"corporation":false,"usgs":false,"family":"Hanks","given":"Ephraim M.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":833310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schliep, Erin M.","contributorId":274778,"corporation":false,"usgs":false,"family":"Schliep","given":"Erin","email":"","middleInitial":"M.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":833311,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wikle, Nathan B.","contributorId":274780,"corporation":false,"usgs":false,"family":"Wikle","given":"Nathan","email":"","middleInitial":"B.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":833312,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"King, Katelyn B. 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S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833313,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCullough, Ian","contributorId":274784,"corporation":false,"usgs":false,"family":"McCullough","given":"Ian","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833314,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stachelek, Jemma","contributorId":274864,"corporation":false,"usgs":false,"family":"Stachelek","given":"Jemma","email":"","affiliations":[],"preferred":false,"id":833315,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cheruvelil, Kendra S.","contributorId":172029,"corporation":false,"usgs":false,"family":"Cheruvelil","given":"Kendra","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":833316,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Filstrup, Christopher T.","contributorId":169032,"corporation":false,"usgs":false,"family":"Filstrup","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":833440,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lapierre, Jean-Francois","contributorId":264522,"corporation":false,"usgs":false,"family":"Lapierre","given":"Jean-Francois","affiliations":[{"id":54487,"text":"University of Montreal","active":true,"usgs":false}],"preferred":false,"id":833441,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Liu, Boyang","contributorId":274865,"corporation":false,"usgs":false,"family":"Liu","given":"Boyang","email":"","affiliations":[],"preferred":false,"id":833442,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sorrano, Patricia","contributorId":204929,"corporation":false,"usgs":false,"family":"Sorrano","given":"Patricia","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833443,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tan, Pang-Ning","contributorId":172193,"corporation":false,"usgs":false,"family":"Tan","given":"Pang-Ning","affiliations":[],"preferred":false,"id":833444,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wang, Q.","contributorId":83761,"corporation":false,"usgs":true,"family":"Wang","given":"Q.","affiliations":[],"preferred":false,"id":833445,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Webster, Katherine","contributorId":274866,"corporation":false,"usgs":false,"family":"Webster","given":"Katherine","affiliations":[],"preferred":false,"id":833446,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Zhou, Jiayu","contributorId":204926,"corporation":false,"usgs":false,"family":"Zhou","given":"Jiayu","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833447,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70222540,"text":"70222540 - 2020 - Metal bioavailability models: Current status, lessons learned, considerations for regulatory use, and the path forward","interactions":[],"lastModifiedDate":"2021-08-03T13:47:20.331188","indexId":"70222540","displayToPublicDate":"2019-12-27T08:45:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Metal bioavailability models: Current status, lessons learned, considerations for regulatory use, and the path forward","docAbstract":"Since the early 2000s, biotic ligand models and related constructs have been a dominant paradigm for risk assessment of aqueous metals in the environment. We critically review 1) the evidence for the mechanistic approach underlying metal bioavailability models; 2) considerations for the use and refinement of bioavailability-based toxicity models; 3) considerations for the incorporation of metal bioavailability models into environmental quality standards; and 4) some consensus recommendations for developing or applying metal bioavailability models. We note that models developed to date have been particularly challenged to accurately incorporate pH effects because they are unique with multiple possible mechanisms. As such, we doubt it is ever appropriate to lump algae/plant and animal bioavailability models; however, it is often reasonable to lump bioavailability models for animals, although aquatic insects may be an exception. Other recommendations include that data generated for model development should consider equilibrium conditions in exposure designs, including food items in combined waterborne–dietary matched chronic exposures. Some potentially important toxicity-modifying factors are currently not represented in bioavailability models and have received insufficient attention in toxicity testing. Temperature is probably of foremost importance; phosphate is likely important in plant and algae models. Acclimation may result in predictions that err on the side of protection. Striking a balance between comprehensive, mechanistically sound models and simplified approaches is a challenge. If empirical bioavailability tools such as multiple-linear regression models and look-up tables are employed in criteria, they should always be informed qualitatively and quantitatively by mechanistic models. If bioavailability models are to be used in environmental regulation, ongoing support and availability for use of the models in the public domain are essential.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.4560","usgsCitation":"Mebane, C.A., Chowdhury, M., De Schamphelaere, K.A., Lofts, S., Paquin, P.R., Santore, R.C., and Wood, C.M., 2020, Metal bioavailability models: Current status, lessons learned, considerations for regulatory use, and the path forward: Environmental Toxicology and Chemistry, v. 39, no. 1, p. 60-84, https://doi.org/10.1002/etc.4560.","productDescription":"25 p.","startPage":"60","endPage":"84","ipdsId":"IP-110208","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":458289,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.4560","text":"Publisher Index Page"},{"id":387661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":820503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chowdhury, M. Jasim","contributorId":261730,"corporation":false,"usgs":false,"family":"Chowdhury","given":"M. Jasim","affiliations":[{"id":52970,"text":"International Lead Association, Durham, North Carolina, USA","active":true,"usgs":false}],"preferred":false,"id":820504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Schamphelaere, Karel A.C.","contributorId":261731,"corporation":false,"usgs":false,"family":"De Schamphelaere","given":"Karel","email":"","middleInitial":"A.C.","affiliations":[{"id":52971,"text":"Ghent University, Gent, Belgium","active":true,"usgs":false}],"preferred":false,"id":820505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lofts, Stephen","contributorId":261732,"corporation":false,"usgs":false,"family":"Lofts","given":"Stephen","email":"","affiliations":[{"id":52972,"text":"Centre for Ecology and Hydrology, Bailrigg, Lancaster, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":820506,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paquin, Paul R.","contributorId":261733,"corporation":false,"usgs":false,"family":"Paquin","given":"Paul","email":"","middleInitial":"R.","affiliations":[{"id":52973,"text":"HDR, New York, New York, USA","active":true,"usgs":false}],"preferred":false,"id":820507,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Santore, Robert C.","contributorId":202449,"corporation":false,"usgs":false,"family":"Santore","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":36447,"text":"Windward Environmental LLC, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":820508,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wood, Chris M.","contributorId":261734,"corporation":false,"usgs":false,"family":"Wood","given":"Chris","email":"","middleInitial":"M.","affiliations":[{"id":52974,"text":"University of British Columbia, Vancouver, British Columbia, Canada.","active":true,"usgs":false}],"preferred":false,"id":820509,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70208100,"text":"70208100 - 2020 - Thresholds for post-wildfire debris flows: Insights from the Pinal Fire, Arizona, USA","interactions":[],"lastModifiedDate":"2020-06-04T16:48:14.988077","indexId":"70208100","displayToPublicDate":"2019-12-27T07:11:25","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":"Thresholds for post-wildfire debris flows: Insights from the Pinal Fire, Arizona, USA","docAbstract":"Wildfire significantly alters the hydrologic properties of a burned area, leading to increases in overland flow, erosion, and the potential for runoff-generated debris flows. The initiation of debris flows in recently burned areas is well-characterized by rainfall intensity-duration (ID) thresholds. However, there is currently a paucity of data quantifying the rainfall intensities required to trigger post-wildfire debris flows, which limits our understanding of how and why rainfall ID thresholds vary in different climatic and geologic settings. In this study, we monitored debris-flow activity following the Pinal Fire in central Arizona, which differs from both a climatic and hydrogeomorphic perspective from other regions in the western U.S. where ID thresholds for post-wildfire debris flows are well-established, namely the Transverse Ranges of southern CA. Since the peak rainfall intensity within a rainstorm may exceed the rainfall intensity required to trigger a debris flow, the development of robust rainfall ID thresholds requires knowledge of the timing of debris flows within rainstorms. Existing post-wildfire debris-flow studies in Arizona only constrain the peak rainfall intensity within debris-flow-producing storms, which may far exceed the intensity that actually triggered the observed debris flow. In this study, we used pressure transducers within 5 burned drainage basins to constrain the timing of debris flows within rainstorms. Rainfall ID thresholds derived here from triggering rainfall intensities are, on average, 22 mm/h lower than ID thresholds derived under the assumption that the triggering intensity is equal to the maximum rainfall intensity recorded during a rainstorm. We then use a hydrologic model to demonstrate that the magnitude of the 15-minute rainfall ID threshold at the Pinal Fire site is associated with the rainfall intensity required to exceed a recently proposed dimensionless discharge threshold for debris-flow initiation. Model results further suggest that previously observed differences in regional ID thresholds between Arizona and the San Gabriel Mountains of southern CA may be attributed, in large part, to differences in the hydraulic properties of burned soils.","language":"English","publisher":"Wiley","doi":"10.1002/esp.4805","usgsCitation":"Raymond, C.A., McGuire, L.A., Youberg, A.M., Staley, D.M., and Kean, J.W., 2020, Thresholds for post-wildfire debris flows: Insights from the Pinal Fire, Arizona, USA: Earth Surface Processes and Landforms, v. 45, no. 6, p. 1349-1360, https://doi.org/10.1002/esp.4805.","productDescription":"12 p.","startPage":"1349","endPage":"1360","ipdsId":"IP-112967","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":371633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.994873046875,\n 33.25936011503665\n ],\n [\n -110.60348510742188,\n 33.25936011503665\n ],\n [\n -110.60348510742188,\n 33.543683878655926\n ],\n [\n -110.994873046875,\n 33.543683878655926\n ],\n [\n -110.994873046875,\n 33.25936011503665\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Raymond, Carissa A","contributorId":221837,"corporation":false,"usgs":false,"family":"Raymond","given":"Carissa","email":"","middleInitial":"A","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":780463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Luke A. 0000-0001-8178-7922 lmcguire@usgs.gov","orcid":"https://orcid.org/0000-0001-8178-7922","contributorId":203420,"corporation":false,"usgs":false,"family":"McGuire","given":"Luke","email":"lmcguire@usgs.gov","middleInitial":"A.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":780464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Youberg, Ann M. 0000-0002-2005-3674","orcid":"https://orcid.org/0000-0002-2005-3674","contributorId":172609,"corporation":false,"usgs":false,"family":"Youberg","given":"Ann","email":"","middleInitial":"M.","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address: TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":true,"id":780465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":780466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":780462,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211487,"text":"70211487 - 2020 - Local climate determines vulnerability to camouflage mismatch in snowshoe hares","interactions":[],"lastModifiedDate":"2020-07-29T00:55:17.688689","indexId":"70211487","displayToPublicDate":"2019-12-26T19:45:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Local climate determines vulnerability to camouflage mismatch in snowshoe hares","docAbstract":"Phenological mismatches, when life‐events become mistimed with optimal environmental conditions, have become increasingly common under climate change. Population‐level susceptibility to mismatches depends on how phenology and phenotypic plasticity vary across a species’ distributional range. Here, we quantify the environmental drivers of colour moult phenology, phenotypic plasticity, and the extent of phenological mismatch in seasonal camouflage to assess vulnerability to mismatch in a common North American mammal.
North America.
2010–2017.
Snowshoe hare (Lepus americanus ).
We used > 5,500 by‐catch photographs of snowshoe hares from 448 remote camera trap sites at three independent study areas. To quantify moult phenology and phenotypic plasticity, we used multinomial logistic regression models that incorporated geospatial and high‐resolution climate data. We estimated occurrence of camouflage mismatch between hares’ coat colour and the presence and absence of snow over 7 years of monitoring.
Spatial and temporal variation in moult phenology depended on local climate conditions more so than on latitude. First, hares in colder, snowier areas moulted earlier in the fall and later in the spring. Next, hares exhibited phenotypic plasticity in moult phenology in response to annual variation in temperature and snow duration, especially in the spring. Finally, the occurrence of camouflage mismatch varied in space and time; white hares on dark, snowless background occurred primarily during low‐snow years in regions characterized by shallow, short‐lasting snowpack.
Long‐term climate and annual variation in snow and temperature determine coat colour moult phenology in snowshoe hares. In most areas, climate change leads to shorter snow seasons, but the occurrence of camouflage mismatch varies across the species’ range. Our results underscore the population‐specific susceptibility to climate change‐induced stressors and the necessity to understand this variation to prioritize the populations most vulnerable under global environmental change.
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Scott","contributorId":236757,"corporation":false,"usgs":false,"family":"Mills","given":"L.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":794288,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70208469,"text":"70208469 - 2020 - Microbial source tracking (MST) in Chattahoochee River National Recreation Area: Seasonal and precipitation trends in MST marker concentrations, and associations with E. coli levels, pathogenic marker presence, and land use","interactions":[],"lastModifiedDate":"2020-02-11T10:05:32","indexId":"70208469","displayToPublicDate":"2019-12-26T10:04:22","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Microbial source tracking (MST) in Chattahoochee River National Recreation Area: Seasonal and precipitation trends in MST marker concentrations, and associations with E. coli levels, pathogenic marker presence, and land use","title":"Microbial source tracking (MST) in Chattahoochee River National Recreation Area: Seasonal and precipitation trends in MST marker concentrations, and associations with E. coli levels, pathogenic marker presence, and land use","docAbstract":"Escherichia coli levels in recreational waters are often used to predict when fecal-associated pathogen levels are a human health risk. The reach of the Chattahoochee River that flows through the Chattahoochee River National Recreation Area (CRNRA), located in the Atlanta-metropolitan area, is a popular recreation area that frequently exceeds the U.S. Environmental Protection Agency beach action value (BAV) for E. coli. A BacteriALERT program has been implemented to provide real-time E. coli estimates in the reach and notify the public of potentially harmful levels of fecal-associated pathogens as indicated by surrogate models based on real-time turbidity measurements from continuous water quality monitoring stations. However, E. coli does not provide information about the sources of fecal contamination and its accuracy as a human health indicator is questionable when sources of contamination are non-human. The objectives of our study were to investigate, within the Park and surrounding watersheds, seasonal and precipitation-related patterns in microbial source tracking marker concentrations of possible sources (human, dog, and ruminant), assess correlations between source contamination levels and culturable E. coli levels, determine which sources best explained model-based E. coli estimates above the BAV and detection of esp2 (a marker for the esp gene associated with pathogenic strains of Enterococcus faecium and Enterococcus faecalis), and investigate associations between source contamination levels and land use features. Three BacteriALERT sites on the Chattahoochee River were sampled six times per season in the winter and summer from December 2015 through September 2017, and 11 additional stream sites (synoptic sites) from the CRNRA watershed were sampled once per season. Samples were screened with microbial source tracking (MST) quantitative PCR (qPCR) markers for humans (HF183 Taqman), dogs (DogBact), and ruminants (Rum2Bac), the esp2 qPCR marker, and culturable E. coli. At the BacteriALERT sites, HF183 Taqman concentrations were higher under wet conditions DogBact concentrations were greater in the winter and under wet conditions, and Rum2Bac concentrations were comparatively low throughout the study with no difference across seasons or precipitation conditions. Concentrations of HF183 Taqman, DogBact, and Rum2Bac were positively correlated with culturable E. coli concentrations; however, DogBact had the largest R2 value among the three markers, and the forward stepwise regression indicated it was the best predictor of culturable E. coli concentrations at the BacteriALERT sites. Recursive partitioning indicated that BAV exceedances of model-based E. coli estimates were best explained by DogBact concentrations ≥3 gene copies per mL (CN/mL). Detections of esp2 at BacteriALERT sites were best explained by DogBact concentrations ≥11 CN/mL, while detections of esp2 at synoptic sites were best explained by HF183 Taqman ≥29 CN/mL. At the synoptic sites, HF183 Taqman levels were associated with wastewater treatment plant density. However, this relationship was driven primarily by a single site, suggesting possible conveyance issues in that catchment. esp2 detections at synoptic sites were positively associated with development within a 2-km radius and negatively associated with development within the catchment, suggesting multiple sources of esp2 in the watershed. DogBact and Rum2Bac were not associated with the land use features included in our analyses. Implications for Park management include: 1) fecal contamination levels were highest during wet conditions and in the off season when fewer visitors are expected to be participating in water-based recreation, 2) dogs are likely contributors to fecal contamination in the CRNRA and may be sources of pathogenic bacteria indicating further investigation of the origins of this contamination may be warranted as would be research to understand the human health risks from exposure to dog fecal contamination, and 3) high levels of the human marker at one site in the CRNRA watershed suggests more extensive monitoring in that catchment may locate the origin of human fecal contamination detected during this study.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2019.115435","usgsCitation":"McKee, A.M., Molina, M., Cyterski, M., and Couch, A., 2020, Microbial source tracking (MST) in Chattahoochee River National Recreation Area: Seasonal and precipitation trends in MST marker concentrations, and associations with E. coli levels, pathogenic marker presence, and land use: Water Research, v. 171, 115435, 12 p., https://doi.org/10.1016/j.watres.2019.115435.","productDescription":"115435, 12 p.","ipdsId":"IP-105660","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":458294,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2019.115435","text":"Publisher Index Page"},{"id":437182,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P957P46S","text":"USGS data release","linkHelpText":"Microbial Source Tracking Marker Concentrations in the Chattahoochee River National Recreation Area Watershed in 2015-2017, Georgia, USA"},{"id":372227,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Chattahoochee River National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.51370239257812,\n 33.90347621404078\n ],\n [\n -83.91769409179688,\n 33.90347621404078\n ],\n [\n -83.91769409179688,\n 34.250405862125\n ],\n [\n -84.51370239257812,\n 34.250405862125\n ],\n [\n -84.51370239257812,\n 33.90347621404078\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"171","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McKee, Anna M. 0000-0003-2790-5320 amckee@usgs.gov","orcid":"https://orcid.org/0000-0003-2790-5320","contributorId":166725,"corporation":false,"usgs":true,"family":"McKee","given":"Anna","email":"amckee@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Molina, Marirosa","contributorId":220538,"corporation":false,"usgs":false,"family":"Molina","given":"Marirosa","email":"","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":782033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cyterski, Mike","contributorId":222389,"corporation":false,"usgs":false,"family":"Cyterski","given":"Mike","email":"","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":782034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Couch, Ann","contributorId":222390,"corporation":false,"usgs":false,"family":"Couch","given":"Ann","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":782035,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227717,"text":"70227717 - 2020 - Spatial sampling bias and model complexity in stream-based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, USA","interactions":[],"lastModifiedDate":"2022-01-27T16:55:07.591983","indexId":"70227717","displayToPublicDate":"2019-12-25T10:48:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7470,"text":"Ecology & Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatial sampling bias and model complexity in stream-based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, USA","title":"Spatial sampling bias and model complexity in stream-based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, USA","docAbstract":"Leveraging existing presence records and geospatial datasets, species distribution modeling has been widely applied to informing species conservation and restoration efforts. Maxent is one of the most popular modeling algorithms, yet recent research has demonstrated Maxent models are vulnerable to prediction errors related to spatial sampling bias and model complexity. Despite elevated rates of biodiversity imperilment in stream ecosystems, the application of Maxent models to stream networks has lagged, as has the availability of tools to address potential sources of error and calculate model evaluation metrics when modeling in nonraster environments (such as stream networks). Herein, we use Maxent and customized R code to estimate the potential distribution of paddlefish (Polyodon spathula) at a stream-segment level within the Arkansas River basin, USA, while accounting for potential spatial sampling bias and model complexity. Filtering the presence data appeared to adequately remove an eastward, large-river sampling bias that was evident within the unfiltered presence dataset. In particular, our novel riverscape filter provided a repeatable means of obtaining a relatively even coverage of presence data among watersheds and streams of varying sizes. The greatest differences in estimated distributions were observed among models constructed with default versus AICC-selected parameterization. Although all models had similarly high performance and evaluation metrics, the AICC-selected models were more inclusive of westward-situated and smaller, headwater streams. Overall, our results solidified the importance of accounting for model complexity and spatial sampling bias in SDMs constructed within stream networks and provided a roadmap for future paddlefish restoration efforts in the study area.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5913","usgsCitation":"Taylor, A., Hafen, T., Holley, C.T., Gonzalez, A., and Long, J.M., 2020, Spatial sampling bias and model complexity in stream-based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, USA: Ecology & Evolution, v. 10, no. 2, p. 705-717, https://doi.org/10.1002/ece3.5913.","productDescription":"13 p.","startPage":"705","endPage":"717","ipdsId":"IP-108639","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":458296,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5913","text":"Publisher Index Page"},{"id":394979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Colorado, Kansas, Missouri, Nebraska, New Mexico, Texas","otherGeospatial":"Arkansas River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.314453125,\n 34.08906131584994\n ],\n [\n -91.845703125,\n 34.08906131584994\n ],\n [\n -91.845703125,\n 39.30029918615029\n ],\n [\n -107.314453125,\n 39.30029918615029\n ],\n [\n -107.314453125,\n 34.08906131584994\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-12-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, A. T.","contributorId":264887,"corporation":false,"usgs":false,"family":"Taylor","given":"A. T.","affiliations":[{"id":54572,"text":"University of Central Oklahoma","active":true,"usgs":false}],"preferred":false,"id":831896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hafen, T.","contributorId":272271,"corporation":false,"usgs":false,"family":"Hafen","given":"T.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":831897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holley, Colt Taylor 0000-0003-4172-4331","orcid":"https://orcid.org/0000-0003-4172-4331","contributorId":272272,"corporation":false,"usgs":true,"family":"Holley","given":"Colt","email":"","middleInitial":"Taylor","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":831898,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gonzalez, A.","contributorId":272273,"corporation":false,"usgs":false,"family":"Gonzalez","given":"A.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":831899,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":831900,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208003,"text":"70208003 - 2020 - Assessing the water quality impacts of two Category-5 hurricanes on St. Thomas, Virgin Islands","interactions":[],"lastModifiedDate":"2020-01-23T09:34:37","indexId":"70208003","displayToPublicDate":"2019-12-24T09:28:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the water quality impacts of two Category-5 hurricanes on St. Thomas, Virgin Islands","docAbstract":"Managing waterborne and water-related diseases is one of the most critical factors in the aftermath of hurricane-induced natural disasters. The goal of the study was to identify water-quality impairments in order to set the priorities for post-hurricane relief and to guide future decisions on disaster preparation and relief administration. Field investigations were carried out on St. Thomas, U.S. Virgin Islands as soon as the disaster area became accessible after the back-to-back hurricane strikes by Irma and Maria in 2017. Water samples were collected from individual household rain cisterns, the coastal ocean, and street-surface runoffs for microbial concentration. The microbial community structure and the occurrence of potential human pathogens were investigated in samples using next generation sequencing. Loop mediated isothermal amplification was employed to detect fecal indicator bacteria, Enterococcus faecalis. The results showed both fecal indicator bacteria and Legionella genetic markers were prevalent but were low in concentration in the water samples. Among the 22 cistern samples, 86% were positive for Legionella and 82% for Escherichia-Shigella. Enterococcus faecalis was detected in over 68% of the rain cisterns and in 60% of the coastal waters (n = 20). Microbial community composition in coastal water samples was significantly different from cistern water and runoff water. Although identification at bacterial genus level is not direct evidence of human pathogens, our results suggest cistern water quality needs more organized attention for protection of human health, and that preparation and prevention measures should be taken before natural disasters strike.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2019.115440","usgsCitation":"Jiang, S., Han, M., Chandrasekaran, S., Fang, Y., and Kellogg, C.A., 2020, Assessing the water quality impacts of two Category-5 hurricanes on St. Thomas, Virgin Islands: Water Research, v. 171, 115440, 9 p., https://doi.org/10.1016/j.watres.2019.115440.","productDescription":"115440, 9 p.","ipdsId":"IP-109410","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":458299,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2019.115440","text":"Publisher Index Page"},{"id":371493,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"St. Thomas, U.S, Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -65.09811401367188,\n 18.24761153423444\n ],\n [\n -64.72457885742188,\n 18.24761153423444\n ],\n [\n -64.72457885742188,\n 18.419684546193967\n ],\n [\n -65.09811401367188,\n 18.419684546193967\n ],\n [\n -65.09811401367188,\n 18.24761153423444\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"171","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jiang, Sunny","contributorId":221746,"corporation":false,"usgs":false,"family":"Jiang","given":"Sunny","email":"","affiliations":[{"id":40412,"text":"University of California, Irvine, CA","active":true,"usgs":false}],"preferred":false,"id":780109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Han, Muyue","contributorId":221747,"corporation":false,"usgs":false,"family":"Han","given":"Muyue","email":"","affiliations":[{"id":40412,"text":"University of California, Irvine, CA","active":true,"usgs":false}],"preferred":false,"id":780110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chandrasekaran, Srikiran","contributorId":221748,"corporation":false,"usgs":false,"family":"Chandrasekaran","given":"Srikiran","email":"","affiliations":[{"id":40412,"text":"University of California, Irvine, CA","active":true,"usgs":false}],"preferred":false,"id":780111,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fang, Yingcong","contributorId":221749,"corporation":false,"usgs":false,"family":"Fang","given":"Yingcong","email":"","affiliations":[{"id":40412,"text":"University of California, Irvine, CA","active":true,"usgs":false}],"preferred":false,"id":780112,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":780108,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70209758,"text":"70209758 - 2020 - Effect of an environmental flow on vegetation growth and health using ground and remote sensing metrics","interactions":[],"lastModifiedDate":"2020-04-28T14:24:02.273893","indexId":"70209758","displayToPublicDate":"2019-12-24T08:13:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Effect of an environmental flow on vegetation growth and health using ground and remote sensing metrics","docAbstract":"Understanding the effectiveness of environmental flow deliveries along rivers requires monitoring vegetation. Monitoring data are often collected at multiple spatial scales. For riparian vegetation, optical remote sensing methods can estimate growth responses at the riparian corridor scale, and field‐based measures can quantify species composition; however, the extent to which these different measures are duplicative or complementary is important to understand when planning monitoring programmes with limited resources. In this study, we analysed riparian vegetation growth in the delta of the Colorado River in response to an experimental pulse flow. Our goal was to compare ground‐based measurements of vegetation structure and composition with satellite‐based Landsat radiometric variables, such as the normalized difference vegetation index (NDVI). We made this comparison in 21 transects following the delivery of 131.8 million cubic meters (mcm) of water in the stream channel during the spring of 2014 as a pulse flow and 38.4 mcm as base flows. Vegetation cover increased 14% and NDVI increased 0.02 (15%) by October 2015, and both variables returned to pre‐pulse flow values in October 2016. Observed changes in vegetation structure and composition did not persist after the second year. The highest increase in vegetation cover in October 2014 and October 2015 resulted from species that could respond rapidly to additional water such as reeds (Arundo donax and Phragmites australis), cattail (Typha domingensis), and herbaceous plants. Dominant shrubs, saltcedar (Tamarix spp.) and arrowweed (Pluchea sericea), both indicative of nonrestored habitats showed variable increases in cover, and native trees (Salicaceae family) presented low increases (1%). The strong NDVI–vegetation cover relationship indicates that NDVI is appropriate to detect changes at the riparian corridor scale but needs to be complemented with ground data to determine the contributions by different species to the observed trends.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13689","collaboration":"","usgsCitation":"Gomez-Sapiens, M.M., Jarchow, C., Flessa, K.W., Shafroth, P.B., Glenn, E., and Nagler, P.L., 2020, Effect of an environmental flow on vegetation growth and health using ground and remote sensing metrics: Hydrological Processes, v. 34, no. 8, p. 1682-1696, https://doi.org/10.1002/hyp.13689.","productDescription":"15 p.","startPage":"1682","endPage":"1696","ipdsId":"IP-109952","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488909,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/659868","text":"External Repository"},{"id":374314,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.3070068359375,\n 31.5691754490709\n ],\n [\n -114.70275878906249,\n 31.5691754490709\n ],\n [\n -114.70275878906249,\n 32.708733368521585\n ],\n [\n -115.3070068359375,\n 32.708733368521585\n ],\n [\n -115.3070068359375,\n 31.5691754490709\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"8","noUsgsAuthors":false,"publicationDate":"2020-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Gomez-Sapiens, Martha M.","contributorId":58172,"corporation":false,"usgs":true,"family":"Gomez-Sapiens","given":"Martha","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":787897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarchow, Christopher 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":196069,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":787898,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flessa, Karl W.","contributorId":175308,"corporation":false,"usgs":false,"family":"Flessa","given":"Karl","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":787899,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":787900,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Glenn, Edward P.","contributorId":56542,"corporation":false,"usgs":false,"family":"Glenn","given":"Edward P.","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":787901,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":787902,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208588,"text":"70208588 - 2020 - The effect of sediment cover and female characteristics on the hatching success of walleye","interactions":[],"lastModifiedDate":"2020-03-11T15:56:57","indexId":"70208588","displayToPublicDate":"2019-12-23T20:17:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"The effect of sediment cover and female characteristics on the hatching success of walleye","docAbstract":"Natural and anthropogenic sources of sedimentation have the potential to degrade spawning habitat and negatively affect incubating fish embryos. Walleye Sander vitreus are lithophilic broadcast spawners that use specific spawning habitats that are vulnerable to degradation caused by deposition of suspended sediments. We measured the effect of different types of sediment cover on hatching success of Walleye eggs and assessed whether differences in female Walleye (female length and mean egg size) account for tolerance to sediment cover. Experiments were carried out in 2018 to test the effect of sediment cover on hatching success and in 2019 to test how female identity and female length or mean egg size may interact with sediment cover to influence hatching success. Eggs in both experiments were exposed to instantaneous sediment cover (0–7 mm) of either sand or silt from fertilization until day 15 of incubation. Results indicated that Walleye eggs were sensitive to silt cover (71% mortality with 2 mm of silt cover) but not sand cover (47% mortality with 7 mm of sand cover). Hatching success differed significantly among individual females. Although there was an indication that hatching success was marginally negatively related to female length and positively related to mean egg size, sediment cover seemed to have similar effects on eggs, regardless of female length or egg size. Susceptibility of Walleye eggs to mortality caused by sediment cover further underscores the need to limit large‐scale sediment loading and resuspension in aquatic systems.
","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10407","usgsCitation":"Gatch, A., Koenigbauer, S., Roseman, E., and Hook, T., 2020, The effect of sediment cover and female characteristics on the hatching success of walleye: North American Journal of Fisheries Management, v. 40, no. 1, p. 293-302, https://doi.org/10.1002/nafm.10407.","productDescription":"10 p.","startPage":"293","endPage":"302","ipdsId":"IP-114620","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":458304,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10407","text":"Publisher Index Page"},{"id":437183,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O7N21F","text":"USGS data release","linkHelpText":"Substrate hardness and walleye (Sander vitreus) and lake whitefish (Coregonus clupeaformis) egg presence in Saginaw Bay, Lake Huron, before and after substrate cleaning experiments and walleye hatching success experiments, 2018-2019"},{"id":372438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","city":"Brookville","otherGeospatial":"Brookville Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.02525329589844,\n 39.433011014927224\n ],\n [\n -84.96826171874999,\n 39.433011014927224\n ],\n [\n -84.96826171874999,\n 39.62367272617737\n ],\n [\n -85.02525329589844,\n 39.62367272617737\n ],\n [\n -85.02525329589844,\n 39.433011014927224\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Gatch, Alex","contributorId":222574,"corporation":false,"usgs":false,"family":"Gatch","given":"Alex","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":782627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koenigbauer, S.K.","contributorId":222575,"corporation":false,"usgs":false,"family":"Koenigbauer","given":"S.K.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":782628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":782626,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hook, T.","contributorId":222576,"corporation":false,"usgs":false,"family":"Hook","given":"T.","email":"","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":782629,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207572,"text":"70207572 - 2020 - Algal toxins in Alaskan seabirds: Evaluating the role of saxitoxin and domoic acid in a large-scale die-off of Common Murres","interactions":[],"lastModifiedDate":"2019-12-26T13:30:58","indexId":"70207572","displayToPublicDate":"2019-12-23T13:28:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1878,"text":"Harmful Algae","active":true,"publicationSubtype":{"id":10}},"title":"Algal toxins in Alaskan seabirds: Evaluating the role of saxitoxin and domoic acid in a large-scale die-off of Common Murres","docAbstract":"Elevated seawater temperatures are linked to the development of harmful algal blooms (HABs), which pose a growing threat to marine birds and other wildlife. During late 2015 and early 2016, a massive die-off of Common Murres (Uria algae; hereafter, murres) was observed in the Gulf of Alaska coincident with a strong marine heat wave. Previous studies have documented illness and death among seabirds resulting from exposure to the HAB neurotoxins saxitoxin (STX) and domoic acid (DA). Given the unusual mortality event, corresponding warm water anomalies, and recent detection of STX and DA throughout coastal Alaskan waters, HABs were identified as a possible factor of concern. To evaluate whether algal toxins may have contributed to murre deaths, we tested for STX and DA in a suite of tissues obtained from beach-cast murre carcasses associated with the die-off as well as from apparently healthy murres and Black-legged Kittiwakes (Rissa tridactyla; hereafter, kittiwakes) in the preceding and following summers. We also tested forage fish and marine invertebrates collected in the Gulf of Alaska in 2015–2017 to evaluate potential sources of HAB toxin exposure for seabirds. Saxitoxin was present in multiple tissue types of both die-off (36.4%) and healthy (41.7%) murres and healthy kittiwakes (54.2%). Among birds, we detected the highest concentrations of STX in liver tissues (range 1.4 –10.8 µg 100 g-1) of die-off murres. Saxitoxin was relatively common in forage fish (20.3%) and marine invertebrates (53.8%). No established toxicity limits currently exist for seabirds, but concentrations of STX in birds and forage fish in our study were lower than values reported from most other bird die-offs in which STX intoxication was causally linked. We detected low concentrations of DA in a single bird sample and in 33.3% of marine invertebrates and 4.0% of forage fish samples. Although these results do not support the hypothesis that acute exposure to STX or DA was a primary factor in the 2015–2016 die-off event, additional information about the sensitivity of murres to these toxins is needed before we can discount their potential role in the die-off. The widespread occurrence of STX in seabirds, forage fish, and marine invertebrates in the Gulf of Alaska indicates that algal toxins should be considered in future assessments of seabird health, especially given the potential for greater occurrence of HABs in the future.","language":"English","publisher":"Elsevier","doi":"10.1016/j.hal.2019.101730","usgsCitation":"Van Hemert, C.R., Schoen, S.K., Litaker, R.W., Smith, M.M., Arimitsu, M.L., Piatt, J.F., Holland, W., Hardison, R., and Pearce, J.M., 2020, Algal toxins in Alaskan seabirds: Evaluating the role of saxitoxin and domoic acid in a large-scale die-off of Common Murres: Harmful Algae, v. 92, 101730, https://doi.org/10.1016/j.hal.2019.101730.","productDescription":"101730","ipdsId":"IP-111669","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":458309,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hal.2019.101730","text":"Publisher Index Page"},{"id":437184,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UNY0FR","text":"USGS data release","linkHelpText":"SUPERSEDED: Data Associated with Algal Toxin Testing of Common Murres (Uria aalge) and Forage Fish in Alaska, 2015–2017"},{"id":370688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.01708984375,\n 58.73400476743346\n ],\n [\n -143.08593749999997,\n 58.73400476743346\n ],\n [\n -143.08593749999997,\n 62.36999628130772\n ],\n [\n -155.01708984375,\n 62.36999628130772\n ],\n [\n -155.01708984375,\n 58.73400476743346\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"92","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Van Hemert, Caroline R. 0000-0002-6858-7165 cvanhemert@usgs.gov","orcid":"https://orcid.org/0000-0002-6858-7165","contributorId":3592,"corporation":false,"usgs":true,"family":"Van Hemert","given":"Caroline","email":"cvanhemert@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":778565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoen, Sarah K. 0000-0002-5685-5185 sschoen@usgs.gov","orcid":"https://orcid.org/0000-0002-5685-5185","contributorId":5136,"corporation":false,"usgs":true,"family":"Schoen","given":"Sarah","email":"sschoen@usgs.gov","middleInitial":"K.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":778566,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Litaker, R. Wayne","contributorId":202495,"corporation":false,"usgs":false,"family":"Litaker","given":"R.","email":"","middleInitial":"Wayne","affiliations":[{"id":36460,"text":"National Oceanic and Atmospheric Administration, National Ocean Service","active":true,"usgs":false}],"preferred":false,"id":778567,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Matthew M. 0000-0002-2259-5135 mmsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-2259-5135","contributorId":5115,"corporation":false,"usgs":true,"family":"Smith","given":"Matthew","email":"mmsmith@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":778568,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":778569,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":778570,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Holland, William C.","contributorId":221535,"corporation":false,"usgs":false,"family":"Holland","given":"William C.","affiliations":[{"id":40398,"text":"NOAA National Centers for Coastal Ocean Science","active":true,"usgs":false}],"preferred":false,"id":778571,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hardison, Ransom 0000-0001-9680-4924","orcid":"https://orcid.org/0000-0001-9680-4924","contributorId":221536,"corporation":false,"usgs":false,"family":"Hardison","given":"Ransom","email":"","affiliations":[{"id":40398,"text":"NOAA National Centers for Coastal Ocean Science","active":true,"usgs":false}],"preferred":false,"id":778572,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pearce, John M. 0000-0002-8503-5485 jpearce@usgs.gov","orcid":"https://orcid.org/0000-0002-8503-5485","contributorId":181766,"corporation":false,"usgs":true,"family":"Pearce","given":"John","email":"jpearce@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":778573,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70209448,"text":"70209448 - 2020 - Environmental tracer evidence for connection between shallow and bedrock aquifers and high intrinsic susceptibility to contamination of the conterminous U.S. glacial aquifer","interactions":[],"lastModifiedDate":"2020-05-04T18:29:03.706787","indexId":"70209448","displayToPublicDate":"2019-12-23T07:20:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Environmental tracer evidence for connection between shallow and bedrock aquifers and high intrinsic susceptibility to contamination of the conterminous U.S. glacial aquifer","docAbstract":"Covering a large portion of the northern conterminous United States (1.87 x 106 km2), the glacial aquifer serves as the primary water supply for 39 million public and domestic water users. Mean groundwater age, groundwater age distribution, and susceptibility to land surface contamination, using a new metric (Susceptibility Index; SI) based on the full age distribution and less prone to bias than estimated mean age, is reported for 168 public and domestic wells across the aquifer. Comparison of groundwater age metrics between well networks of varying spatial scale suggest an extensive sample network of equally spaced, long screened interval wells can be used to characterize aquifer wide groundwater age. Estimated mean age ranges from 1 to 50,000 years and, according to the composite age distribution, approximately 63 percent of all sampled water recharged after 1950 (i.e., modern) and 18 percent of the sampled water was recharged greater than 10,000 years ago. The later finding strongly suggests a connection between the glacial aquifer and underlying bedrock aquifers. Statistical analysis of glacial aquifer hydrogeology and age metrics show groundwater ages are young (less than few 100 years) and more susceptible to land surface contamination (larger SI) in unconfined and shallow portions of the aquifer. Old groundwater (greater than 1000 years) is more often associated with thicker sequences of fine grain sediments and/or shallow bedrock. Calculated SI is shown to be more strongly related to the number of land surface contaminants detected than mean age or fraction modern. Statistical analysis of SI and hydrogeology indicates SI is largely dictated by well depth and confinement. This study demonstrates how sample network design can be used to characterize groundwater age of large aquifers with a limited number of samples and how interpretation of environmental tracers can be used to improve conceptual models of groundwater aquifers and identify groundwater susceptible to contamination.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2019.124505","collaboration":"","usgsCitation":"Solder, J.E., Jurgens, B., Stackelberg, P.E., and Shope, C., 2020, Environmental tracer evidence for connection between shallow and bedrock aquifers and high intrinsic susceptibility to contamination of the conterminous U.S. glacial aquifer: Journal of Hydrology, v. 583, 124505, 12 p., https://doi.org/10.1016/j.jhydrol.2019.124505.","productDescription":"124505, 12 p.","ipdsId":"IP-090099","costCenters":[{"id":610,"text":"Utah Water Science 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0000-0002-1818-355X","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":204864,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","middleInitial":"E.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":786518,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shope, Christopher L. 0000-0003-4209-049X","orcid":"https://orcid.org/0000-0003-4209-049X","contributorId":223873,"corporation":false,"usgs":false,"family":"Shope","given":"Christopher L.","affiliations":[{"id":40783,"text":"State of Utah Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":786519,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207547,"text":"70207547 - 2020 - An experimental evaluation of the feasibility of inferring concentrations of a visible tracer dye from remotely sensed data in turbid rivers","interactions":[],"lastModifiedDate":"2019-12-24T12:08:16","indexId":"70207547","displayToPublicDate":"2019-12-22T11:55:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"An experimental evaluation of the feasibility of inferring concentrations of a visible tracer dye from remotely sensed data in turbid rivers","docAbstract":"The movement of contaminants and biota within river channels is influenced by the flow field via various processes of dispersion. Understanding and modeling of these processes thus can facilitate applications ranging from the prediction of travel times for spills of toxic materials to the simulation of larval drift for endangered species of fish. A common means of examining dispersion in rivers involves conducting tracer experiments with a visible tracer dye. Whereas conventional in situ instruments can only measure variations in dye concentration over time at specific, fixed locations, remote sensing could provide more detailed, spatially distributed information for characterizing dispersion patterns and validating two-dimensional numerical models. Although previous studies have demonstrated the potential to infer dye concentrations from remotely sensed data in clear-flowing streams, whether this approach can be applied to more turbid rivers remains an open question. To evaluate the feasibility of mapping spatial patterns of dispersion in streams with greater turbidity, we conducted an experiment that involved manipulating dye concentration and turbidity while acquiring field spectra and hyperspectral and RGB (red, green, blue) images from a small Unoccupied Aircraft System (sUAS). Applying an Optimal Band Ratio Analysis (OBRA) algorithm to these data sets indicated strong relationships between reflectance (i.e., water color) and Rhodamine WT dye concentration across four different turbidity levels from 40-60 NTU. Moreover, we obtained high correlations between spectrally based quantities (i.e., band ratios) and dye concentration for the original, essentially continuous field spectra; field spectra resampled to the bands of a five-band imaging system and an RGB camera; and both hyperspectral and RGB images acquired from a sUAS during the experiment. The results of this study thus confirmed the potential to map dispersion patterns of tracer dye via remote sensing and suggested that this approach can be extended to more turbid rivers than those examined previously.","language":"English","publisher":"MDPI","doi":"10.3390/rs12010057","usgsCitation":"Legleiter, C.J., Manley, P., Erwin, S.O., and Bulliner, E.A., 2020, An experimental evaluation of the feasibility of inferring concentrations of a visible tracer dye from remotely sensed data in turbid rivers: Remote Sensing, v. 12, no. 1, 57, 21 p., https://doi.org/10.3390/rs12010057.","productDescription":"57, 21 p.","ipdsId":"IP-112896","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":458311,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12010057","text":"Publisher Index Page"},{"id":437185,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91ZRGKQ","text":"USGS data release","linkHelpText":"Field spectra, UAS-based hyperspectral and RGB images, and in situ measurements of turbidity and Rhodamine WT dye concentration from an experiment conducted at the USGS Columbia Environmental Research Center, Columbia, MO, on April 2, 2019"},{"id":370672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","city":"Columbia","otherGeospatial":"Columbia Environmental Research Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.28494167327881,\n 38.905995699991145\n ],\n [\n -92.27007150650024,\n 38.905995699991145\n ],\n [\n -92.27007150650024,\n 38.91711561447239\n ],\n [\n -92.28494167327881,\n 38.91711561447239\n ],\n [\n -92.28494167327881,\n 38.905995699991145\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":778425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manley, Paul 0000-0001-6062-1149","orcid":"https://orcid.org/0000-0001-6062-1149","contributorId":221490,"corporation":false,"usgs":false,"family":"Manley","given":"Paul","email":"","affiliations":[{"id":37501,"text":"Missouri University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":778426,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erwin, Susannah O. 0000-0002-2799-0118 serwin@usgs.gov","orcid":"https://orcid.org/0000-0002-2799-0118","contributorId":5183,"corporation":false,"usgs":true,"family":"Erwin","given":"Susannah","email":"serwin@usgs.gov","middleInitial":"O.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":778427,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bulliner, Edward A. 0000-0002-2774-9295 ebulliner@usgs.gov","orcid":"https://orcid.org/0000-0002-2774-9295","contributorId":4983,"corporation":false,"usgs":true,"family":"Bulliner","given":"Edward","email":"ebulliner@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":778428,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}