Diadromous fish populations face multiple challenges along their migratory routes. These challenges include suboptimal water quality, harvest, and barriers to longitudinal and lateral connectivity. Interactions among factors influencing migration success make it challenging to assess management options for improving migratory fish conditions along riverine migration corridors. We describe a spatially explicit simulation model that integrates complex individual behaviors of fall-run Chinook Salmon (Oncorhynchus tshawytscha) and summer-run steelhead trout (O. mykiss) during migration, responds to variable habitat conditions over a large extent of the Columbia River, and links migration corridor conditions to fish condition outcomes. The model is built around a mechanistic behavioral decision tree that drives individual interactions of fish within their simulated environments. By simulating several thermalscapes with alternative scenarios of thermal refuge availability, we examined how behavioral thermoregulation in cold-water refuges influenced migrating fish conditions. Outcomes of the migration corridor simulation model show that cold-water refuges can provide relief from exposure to high water temperatures, but do not substantially contribute to energy conservation by migrating adults. Simulated cooling of the Columbia River decreased reliance on cold-water refuges and there were slight reductions in migratory energy expenditure. This modeling of simulated thermalscapes provides a framework for assessing the contribution of cold-water refuges to the success of migrating fishes, but any final determination will depend on analyzing fish survival and health for their entire migration, water temperature management goals and species recovery targets.
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Alliance","active":true,"usgs":false}],"preferred":false,"id":885190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGahuey, Mike","contributorId":330521,"corporation":false,"usgs":false,"family":"McGahuey","given":"Mike","email":"","affiliations":[{"id":78919,"text":"Fellow, Global Evergreening Alliance","active":true,"usgs":false}],"preferred":false,"id":885191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tappan, G. Gray 0000-0002-2240-6963 tappan@usgs.gov","orcid":"https://orcid.org/0000-0002-2240-6963","contributorId":3624,"corporation":false,"usgs":true,"family":"Tappan","given":"G.","email":"tappan@usgs.gov","middleInitial":"Gray","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":885192,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228389,"text":"70228389 - 2020 - Comparing husbandry techniques for optimal head-starting of the Mojave desert tortoise (Gopherus agassizii)","interactions":[],"lastModifiedDate":"2022-02-10T18:04:30.863092","indexId":"70228389","displayToPublicDate":"2020-12-16T11:54:09","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1894,"text":"Herpetological Conservation and Biology","onlineIssn":"2151-0733","printIssn":"1931-7603","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Comparing husbandry techniques for optimal head-starting of the Mojave desert tortoise (Gopherus agassizii)","title":"Comparing husbandry techniques for optimal head-starting of the Mojave desert tortoise (Gopherus agassizii)","docAbstract":"Mojave Desert Tortoise (Gopherus agassizii) populations continue to decline throughout their range. Head-starting—the captive rearing of offspring to a size where they are presumably more likely to survive post-release—is being explored as a potential recovery tool. Previous Desert Tortoise head-starting programs have reared neonates exclusively outdoors. Here, we explore using a combination of indoor and outdoor captive rearing to maximize post-release success and rearing efficiency. We assigned 68 neonates (2016 cohort) to one of two treatments: Outdoor HS (n = 38), where neonates were reared exclusively in outdoor predator-proof enclosures, and Combo HS (n = 30), where neonates were reared indoors for 1 y followed by outdoor rearing for 1 y. After 2 y of captive rearing, we randomly selected 24 Outdoor HS and 24 Combo HS juveniles for release in the Mojave National Preserve, CA on 25 September 2018. We compare pre-release size, body condition, and shell hardness as well as first year post-release movement and survival between the treatment groups. Pre-release body condition was not significantly different between groups. Outdoor HS tortoises, however, were significantly smaller and had significantly softer shells than Combo HS tortoises. Excluding two missing animals, released head-starts experienced 78.2% survival through their first year after release. Combo HS tortoises on average dispersed significantly shorter distances after 1 y than Outdoor HS animals. Our findings that Combo HS animals were larger and had harder shells at release, and exhibited high survival but low dispersal following release, support the implementation of combination head-starting as part of the recovery effort for the Mojave Desert Tortoise.
","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"McGovern, P., Buhlmann, K.A., Todd, B.D., Moore, C.T., Peaden, J.M., Hepinstall-Cymerman, J., Daly, J.A., and Tuberville, T.D., 2020, Comparing husbandry techniques for optimal head-starting of the Mojave desert tortoise (Gopherus agassizii): Herpetological Conservation and Biology, v. 15, no. 3, p. 626-641.","productDescription":"16 p.","startPage":"626","endPage":"641","ipdsId":"IP-115675","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":395787,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/contents_vol15_issue3.html"}],"country":"United States","state":"California","otherGeospatial":"Ivanpah Valley, Mojave National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.4608154296875,\n 35.110921809704756\n ],\n [\n -115.10925292968749,\n 35.110921809704756\n ],\n [\n -115.10925292968749,\n 35.50987173838399\n ],\n [\n -115.4608154296875,\n 35.50987173838399\n ],\n [\n -115.4608154296875,\n 35.110921809704756\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McGovern, P. A.","contributorId":275620,"corporation":false,"usgs":false,"family":"McGovern","given":"P. A.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buhlmann, K. A.","contributorId":275621,"corporation":false,"usgs":false,"family":"Buhlmann","given":"K.","email":"","middleInitial":"A.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Todd, B. D.","contributorId":275623,"corporation":false,"usgs":false,"family":"Todd","given":"B.","email":"","middleInitial":"D.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":834179,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834180,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peaden, J. M.","contributorId":275626,"corporation":false,"usgs":false,"family":"Peaden","given":"J.","email":"","middleInitial":"M.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":834181,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hepinstall-Cymerman, J.","contributorId":275628,"corporation":false,"usgs":false,"family":"Hepinstall-Cymerman","given":"J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834182,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Daly, J. A.","contributorId":275632,"corporation":false,"usgs":false,"family":"Daly","given":"J.","email":"","middleInitial":"A.","affiliations":[{"id":56868,"text":"Directorate of Public Works, Environmental Division, Dublin, CA","active":true,"usgs":false}],"preferred":false,"id":834183,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tuberville, T. D.","contributorId":275634,"corporation":false,"usgs":false,"family":"Tuberville","given":"T.","email":"","middleInitial":"D.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834184,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70218474,"text":"70218474 - 2020 - Stony coral tissue loss disease in Florida is associated with disruption of host–zooxanthellae physiology","interactions":[],"lastModifiedDate":"2021-03-01T15:53:30.188709","indexId":"70218474","displayToPublicDate":"2020-12-16T09:44:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Stony coral tissue loss disease in Florida is associated with disruption of host–zooxanthellae physiology","docAbstract":"Samples from eight species of corals (Colpophyllia natans, Dendrogyra cylindrus, Diploria labyrinthiformis, Meandrina meandrites, Montastraea cavernosa, Orbicella faveolata, Pseudodiploria strigosa, and Siderastrea siderea) that exhibited gross clinical signs of acute, subacute, or chronic tissue loss attributed to stony coral tissue loss disease (SCTLD) were collected from the Florida Reef Tract during 2016–2018 and examined histopathologically. The hallmark microscopic lesion seen in all eight species was focal to multifocal lytic necrosis (LN) originating in the gastrodermis of the basal body wall (BBW) and extending to the calicodermis, with more advanced lesions involving the surface body wall. This was accompanied by other degenerative changes in host cells such as mucocyte hypertrophy, degradation and fragmentation of gastrodermal architecture, and disintegration of the mesoglea. Zooxanthellae manifested various changes including necrosis (cytoplasmic hypereosinophilia, pyknosis); peripheral nuclear chromatin condensation; cytoplasmic vacuolation accompanied by deformation, swelling, or atrophy; swollen accumulation bodies; prominent pyrenoids; and degraded chloroplasts. Polyhedral intracytoplasmic eosinophilic periodic acid–Schiff-positive crystalline inclusion bodies (∼1–10 μm in length) were seen only in M. cavernosa and P. strigosa BBW gastrodermis in or adjacent to active lesions and some unaffected areas (without surface lesions) of diseased colonies. Coccoidlike or coccobacilloidlike structures (Gram-neutral) reminiscent of microorganisms were occasionally associated with LN lesions or seen in apparently healthy tissue of diseased colonies along with various parasites and other bacteria all considered likely secondary colonizers. Of the 82 samples showing gross lesions of SCTLD, 71 (87%) were confirmed histologically to have LN. Collectively, pathology indicates that SCTLD is the result of a disruption of host–symbiont physiology with lesions originating in the BBW leading to detachment and sloughing of tissues from the skeleton. Future investigations could focus on identifying the cause and pathogenesis of this process.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2020.576013","usgsCitation":"Landsberg, J., Kiryu, Y., Peters, E., Wilson, P., Waters, Y., Maxwell, K., Huebner, L., and Work, T.M., 2020, Stony coral tissue loss disease in Florida is associated with disruption of host–zooxanthellae physiology: Frontiers in Marine Science, v. 7, 576013, 24 p., https://doi.org/10.3389/fmars.2020.576013.","productDescription":"576013, 24 p.","ipdsId":"IP-122466","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":454646,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2020.576013","text":"Publisher Index Page"},{"id":383688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.167236328125,\n 27.371767300523047\n ],\n [\n -80.386962890625,\n 27.225325836903373\n ],\n [\n -80.15625,\n 26.470573022375085\n ],\n [\n -80.26611328125,\n 25.839449402063185\n ],\n [\n -80.44189453125,\n 25.27450351782018\n ],\n [\n -80.716552734375,\n 24.91633140459907\n ],\n [\n -82.08984375,\n 24.627044746156027\n ],\n [\n -81.88110351562499,\n 24.37712083961039\n ],\n [\n -80.760498046875,\n 24.647017162630366\n ],\n [\n -80.035400390625,\n 25.334096684794456\n ],\n [\n -79.9365234375,\n 26.56887654795065\n ],\n [\n -79.95849609375,\n 27.00040800352175\n ],\n [\n -80.167236328125,\n 27.371767300523047\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","noUsgsAuthors":false,"publicationDate":"2020-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Landsberg, Jan","contributorId":252919,"corporation":false,"usgs":false,"family":"Landsberg","given":"Jan","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiryu, Yasu","contributorId":252920,"corporation":false,"usgs":false,"family":"Kiryu","given":"Yasu","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peters, Esther","contributorId":252921,"corporation":false,"usgs":false,"family":"Peters","given":"Esther","affiliations":[{"id":50470,"text":"George Masson University","active":true,"usgs":false}],"preferred":false,"id":811124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Patrick","contributorId":252922,"corporation":false,"usgs":false,"family":"Wilson","given":"Patrick","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waters, Yvonne","contributorId":252923,"corporation":false,"usgs":false,"family":"Waters","given":"Yvonne","email":"","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811126,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maxwell, Kerry","contributorId":252924,"corporation":false,"usgs":false,"family":"Maxwell","given":"Kerry","email":"","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811127,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huebner, Lindsay","contributorId":252925,"corporation":false,"usgs":false,"family":"Huebner","given":"Lindsay","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811128,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":811129,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216871,"text":"sir20205091 - 2020 - Simulation of groundwater flow in the regional aquifer system on Long Island, New York, for pumping and recharge conditions in 2005–15","interactions":[],"lastModifiedDate":"2021-04-08T21:42:55.915848","indexId":"sir20205091","displayToPublicDate":"2020-12-16T09:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5091","displayTitle":"Simulation of Groundwater Flow in the Regional Aquifer System on Long Island, New York, for Pumping and Recharge Conditions in 2005–15","title":"Simulation of groundwater flow in the regional aquifer system on Long Island, New York, for pumping and recharge conditions in 2005–15","docAbstract":"A three-dimensional groundwater-flow model was developed for the aquifer system of Long Island, New York, to evaluate (1) responses of the hydrologic system to changes in natural and anthropogenic hydraulic stresses, (2) the subsurface distribution of groundwater age, and (3) the regional-scale distribution of groundwater travel times and the source of water to fresh surface waters and coastal receiving waters. The model also provides the groundwater flow components used to define model boundaries for possible inset models used for local-scale analyses.
The three-dimensional, groundwater flow model developed for this investigation uses the numerical code MODFLOW–NWT to represent steady-state conditions for average groundwater pumping and aquifer recharge for 2005–15. The particle-tracking algorithm MODPATH, which simulates advective transport in the aquifer, was used to estimate groundwater age, delineate the areas at the water table that contribute recharge to coastal and freshwater bodies, and estimate total travel times of water from the water table to discharge locations.
A three-dimensional, 1-meter (3.3-foot) topobathymetric model was used to determine land-surface altitudes for the island and seabed altitudes for the surrounding coastal waters. The mapped extents and surface altitudes of major geologic units were compiled and used to develop a three-dimensional hydrogeologic framework of the aquifer system, including aquifers and confining units. Lithologic data from deep boreholes and previous aquifer-test results were used to estimate the three-dimensional distribution of hydraulic conductivity in principal aquifers. Natural recharge from precipitation was estimated for 2005–15 using a modified Thornthwaite-Mather methodology as implemented in a soil-water balance model. Components of anthropogenic recharge—wastewater return flow, storm water inflow, and inflow from leaky infrastructure—also were estimated for 2005–15. Groundwater withdrawals for various sources, including public water supply, industrial, remediation, and agricultural, were compiled or estimated for the same period.
These data were incorporated into the model development to represent the aquifer system geometry, boundaries, and initial hydraulic properties of the regional aquifers and confining units within the Long Island aquifer system. Average hydraulic conditions—water levels and streamflows—for 2005–15 were estimated using existing data from the U.S. Geological Survey National Water Information System database. Model inputs were adjusted to best match average hydrologic conditions using inverse methods as implemented in the parameter-estimating software PEST. The calibrated model was used to simulate average hydrologic conditions in the aquifer system for 2005–15.
About 656 cubic feet per second of water was withdrawn on average annually for 2005–15 for water supply and an average of about 349 cubic feet per second of water recharged the aquifer annually from return flow and leaky infrastructure. Parts of New York City have drawdowns exceeding 25 feet, mostly because of urbanization and associated large decreases in recharge rates. Large areas in the western part of the island have drawdowns exceeding 10 feet, mostly from large groundwater withdrawals and sewering, which largely eliminates wastewater return flow. Water-table altitudes in eastern parts of the island increased by more than 2 feet in some areas as a result of wastewater return flow in unsewered areas and changes in land use. Changes in streamflows show a similar pattern as water-table altitudes. Streamflows generally decrease in western parts of the island where there are large drawdowns and increase in eastern parts of the island where water-table altitudes increase.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205091","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Walter, D.A., Masterson, J.P., Finkelstein, J.S., Monti, J., Jr., Misut, P.E., and Fienen, M.N., 2020, Simulation of groundwater flow in the regional aquifer system on Long Island, New York, for pumping and recharge conditions in 2005–15: U.S. Geological Survey Scientific Investigations Report 2020–5091, 75 p., https://doi.org/10.3133/sir20205091.","productDescription":"Report: ix, 75 p.; 3 Data Releases","numberOfPages":"75","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-112206","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":381521,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2020/5091/images/"},{"id":381195,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5091/sir20205091.pdf","text":"Report","size":"35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5091"},{"id":381194,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5091/coverthb2.jpg"},{"id":381192,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P954DLLC","text":"USGS data release","linkHelpText":"Aquifer texture data describing the Long Island aquifer system"},{"id":381191,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KWQSEJ","text":"USGS data release","linkHelpText":"MODFLOW–NWT and MODPATH6 used to simulate groundwater flow in the regional aquifer system on Long Island, New York, for pumping and recharge conditions in 2005–15"},{"id":381190,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90B6OTX","text":"USGS data release","linkHelpText":"Time domain electromagnetic surveys collected to estimate the extent of saltwater intrusion in Nassau and Queens Counties, New York, October-November 2017"},{"id":381520,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2020/5091/sir20205091.XML"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.102783203125,\n 40.55554790286311\n ],\n [\n -73.7017822265625,\n 40.49709237269567\n ],\n [\n -72.8778076171875,\n 40.65147128144057\n ],\n [\n -72.037353515625,\n 40.91351257612758\n ],\n [\n -71.6143798828125,\n 41.16211393939692\n ],\n [\n -71.9384765625,\n 41.178653972331674\n ],\n [\n -72.191162109375,\n 41.236511201246216\n ],\n [\n -72.65808105468749,\n 41.11660732012896\n ],\n [\n -73.4490966796875,\n 40.967455873296714\n ],\n [\n -73.751220703125,\n 40.89275342420696\n ],\n [\n -74.0203857421875,\n 40.718119379753446\n ],\n [\n -74.102783203125,\n 40.55554790286311\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
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10 Bearfoot Road
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Subduction zones drive plate tectonics on Earth, yet subduction initiation and the related upper plate depositional and structural kinematics remain poorly understood because upper plate records are rare and often strongly overprinted by magmatism and deformation. During the late Paleozoic time, Laurentia’s western margin was truncated by a sinistral strike-slip fault that transformed into a subduction zone. Thick Permian strata in the Inyo Mountains of central-eastern California record this transition. Two basins that were separated by a transpressional antiform contain sedimentary lithofacies that record distinct patterns of shoaling and deepening conditions before and during tectonism associated with subduction initiation. Sandstone petrography and lithofacies analysis show that rocks in a southeastern basin are dominated by carbonate grains derived from adjacent carbonate shelves, whereas sandstones in a northwestern basin are predominantly quartzose with likely derivation from distant ergs or underlying strata. Detrital zircon spectra from all but the youngest strata in both basins are typical of Laurentian continent spectra with prominent peaks that indicate ultimate sources in Appalachia, Grenville, Yavapai/Mazatzal, and the Wyoming or Superior cratons. The first Cordilleran arc-derived detrital zircon grains appear in the uppermost strata of the northwestern basin and record Late Permian (ca. 260 Ma) Cordilleran arc magmatism at this approximate latitude, and a possible source area is suggested by geochemical similarities between these detrital zircons and broadly coeval magmatic zircons in the El Paso Mountains to the southwest. Deformation responsible for basin partitioning is consistent with sinistrally oblique contraction in the earliest Permian time. The data presented from the Inyo Mountains shed more light on the nature of Cordilleran subduction initiation and the upper-crustal response to this transition.
Inlet-interrupted sandy coasts are dynamic and complex coastal systems with continuously evolving geomorphological behaviors under the influences of both climate change and human activities. These coastal systems are of great importance to society (e.g., providing habitats, navigation, and recreational activities) and are affected by both oceanic and terrestrial processes. Therefore, the evolution of these inlet-interrupted coasts is better assessed by considering the entirety of the Catchment-Estuary-Coastal (CEC) systems, under plausible future scenarios for climate change and increasing pressures due to population growth and human activities. Such a holistic assessment of the long-term evolution of CEC systems can be achieved via reduced-complexity modeling techniques, which are also ably quantifying the uncertainties associated with the projections due to their lower simulation times. Here, we develop a novel probabilistic modeling framework to quantify the input-driven uncertainties associated with the evolution of CEC systems over the 21st century. In this new approach, probabilistic assessment of the evolution of inlet-interrupted coasts is achieved by (1) probabilistically computing the exchange sediment volume between the inlet-estuary system and its adjacent coast, and (2) distributing the computed sediment volumes along the inlet-interrupted coast. The model is applied at three case study sites: Alsea estuary (United States), Dyfi estuary (United Kingdom), and Kalutara inlet (Sri Lanka). Model results indicate that there are significant uncertainties in projected volume exchange at all the CEC systems (min-max range of 2.0 million cubic meters in 2100 for RCP 8.5), and the uncertainties in these projected volumes illustrate the need for probabilistic modeling approaches to evaluate the long-term evolution of CEC systems. A comparison of 50th percentile probabilistic projections with deterministic estimates shows that the deterministic approach overestimates the sediment volume exchange in 2100 by 15–30% at Alsea and Kalutara estuary systems. Projections of coastline change obtained for the case study sites show that accounting for all key processes governing coastline change along inlet-interrupted coasts in computing coastline change results in projections that are between 20 and 134% greater than the projections that would be obtained if only the Bruun effect were taken into account, underlining the inaccuracies associated with using the Bruun rule at inlet-interrupted coasts.
Effective volcanic hazard management in regions where populations live in close proximity to persistent volcanic activity involves understanding the dynamic nature of hazards, and associated risk. Emphasis until now has been placed on identification and forecasting of the escalation phase of activity, in order to provide adequate warning of what might be to come. However, understanding eruption hiatus and post-eruption unrest hazards, or how to quantify residual hazard after the end of an eruption, is also important and often key to timely post-eruption recovery. Unfortunately, in many cases when the level of activity lessens, the hazards, although reduced, do not necessarily cease altogether. This is due to both the imprecise nature of determination of the “end” of an eruptive phase as well as to the possibility that post-eruption hazardous processes may continue to occur. An example of the latter is continued dome collapse hazard from lava domes which have ceased to grow, or sector collapse of parts of volcanic edifices, including lava dome complexes. We present a new probabilistic model for forecasting pyroclastic density currents (PDCs) from lava dome collapse that takes into account the heavy-tailed distribution of the lengths of eruptive phases, the periods of quiescence, and the forecast window of interest. In the hazard analysis, we also consider probabilistic scenario models describing the flow’s volume and initial direction. Further, with the use of statistical emulators, we combine these models with physics-based simulations of PDCs at Soufrière Hills Volcano to produce a series of probabilistic hazard maps for flow inundation over 5, 10, and 20 year periods. The development and application of this assessment approach is the first of its kind for the quantification of periods of diminished volcanic activity. As such, it offers evidence-based guidance for dome collapse hazards that can be used to inform decision-making around provisions of access and reoccupation in areas around volcanoes that are becoming less active over time.
This paper provides an overview of past, present and future themes for research and management of riparian zones, often relating to papers within this Wetlands Special Feature. Riparian research expanded in the United States around 1980 with themes that recognized (1) damage from excessive livestock, or (2) damage from river damming and diversion, and (3) the beneficial capacity of riparian buffers to intercept and assimilate nutrients and other water contaminants. Research expanded globally in the 1990s, with themes including (4) plant life history requirements and (5) reliance on fluvial geomorphic dynamics that enable riparian rejuvenation. Resource managers recognized that riparian areas provide (6) rich wildlife habitats (7) along with valued ecosystem services, (8) which encouraged conservation and restoration initiatives, (9) including environmental flow regimes. Floodplains are (10) vulnerable to invasive plants and management has included biocontrol such as for Tamarix in the American Southwest. Into the twenty-first century, (11) climate change is advancing, and riparian ecosystems may be especially impacted due to the compound challenges from increasing water demand and declining summer flows. As an emerging opportunity, (12) while reservoirs submerge floodplain vegetation, reservoir deltas may support compensatory riparian wetlands. (13) Studies increasingly utilize remote sensing tools including satellite imagery, LiDAR and unmanned aircraft systems, and (14) the coordination of large data sets invites digital ecology, including artificial intelligence and machine learning. Since riparian zones are centres for human activities, (15) there are opportunities for citizen science, social media and internet applications, which will increasingly democratize riparian research and management.
The maps and graphs in this summary describe national streamflow conditions for water year 2019 (October 1, 2018, to September 30, 2019) in the context of streamflow ranks relative to the 90-year period of water years 1930–2019. Annual runoff in the Nation’s rivers and streams during water year 2019 (13.62 inches) was much higher than the long-term (1930–2019) mean annual runoff of 9.37 inches for the contiguous United States. Nationwide, the 2019 streamflow ranked the highest out of the 90 years.
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415 National Center
Reston, VA 20192
About one-quarter of the water supply for the Village of Ruidoso, New Mexico, is from groundwater pumped from wells located along North Fork Eagle Creek in the National Forest System lands of the Lincoln National Forest near Alto, New Mexico. Because of concerns regarding the effects of groundwater pumping on surface-water hydrology in the North Fork Eagle Creek Basin and the effects of the 2012 Little Bear Fire, which resulted in substantial loss of vegetation in the basin, the U.S. Department of Agriculture Forest Service, Lincoln National Forest, has required monitoring of a portion of North Fork Eagle Creek for short-term geomorphic change as part of the permitting decision that allows for the continued pumping of the production wells. The objective of this study is to address the geomorphic monitoring requirements of the permitting decision by conducting annual geomorphic surveys of North Fork Eagle Creek along the stream reach between the North Fork Eagle Creek near Alto, New Mexico, streamflow-gaging station (U.S. Geological Survey [USGS] site 08387550) and the Eagle Creek below South Fork near Alto, New Mexico, streamflow-gaging station (USGS site 08387600). The monitoring of short-term geomorphic change in the stream reach began in June 2017 with surveys of select cross sections and surveys of all woody debris accumulations and pools found in the channel. In June 2018, the monitoring of short-term geomorphic change continued with another geomorphic survey of the stream reach (with some modification to the monitoring methods).
The 2017 and 2018 surveys were conducted by the USGS, in cooperation with the Village of Ruidoso, and were the first two in a planned series of five annual geomorphic surveys. The results of the 2017 geomorphic survey were summarized and interpreted in a previous USGS Open-File Report, and the data were published in the companion data release of that report. In this report, the results of the 2018 geomorphic survey are summarized, interpreted, and compared to the results of the 2017 survey. The data from the 2018 geomorphic survey are published in the companion data release of this report.
The study reach surveyed in June 2018 is 1.89 miles long, beginning about 260 feet upstream from the North Fork Eagle Creek near Alto, New Mexico, streamflow-gaging station and ending at the Eagle Creek below South Fork near Alto, New Mexico, streamflow-gaging station. Large sections of the study reach are characterized by intermittent streamflow, and where streamflow is normally continuous (including at the upper and lower portions of the study reach, near the streamflow-gaging stations), the streamflow typically remains less than 2 cubic feet per second throughout the year except during seasonal high flows, which most often result from rainfall during the North American monsoon months of July, August, and September or from snowmelt runoff in March, April, and May. Between the 2017 and 2018 surveys, high-flow events resulting from both rainfall (during the North American monsoon season) and snowmelt runoff (during the winter) occurred in the study reach, and those high-flow events appeared to have caused some minor and localized geomorphic changes in the study reach, which were evaluated through comparison of the 2017 and 2018 survey results.
For the 2017 geomorphic survey of North Fork Eagle Creek, cross sections were established and surveyed at 14 locations along the study reach, and in 2018, those same 14 cross sections were resurveyed. Comparisons of the cross-section survey results indicated that minor observable geomorphic changes had occurred in 3 of the 14 cross sections. These minor observable geomorphic changes included aggradation or degradation of surface materials by about 1–2 feet in some parts of the affected cross sections.
To further assess geomorphic changes within the study reach, other features, including woody debris accumulations and pools, were surveyed in both 2017 and 2018. During the 2018 geomorphic survey, 112 distinct accumulations of woody debris and 71 pools were identified in the study reach. Charred wood or burn-marked wood was present in at least 17 of the identified woody debris accumulations (and was present in some of the woody debris accumulations identified during the 2017 survey), indicating that some of the woody debris in the channel may have been sourced from trees or forest litter that had burned during 2012 Little Bear Fire. Only 22 of the 112 woody debris accumulations identified during the 2018 survey were certain to have also been present during the 2017 survey (when 58 woody debris accumulations were identified), indicating that most of the woody debris accumulations surveyed in 2017 were likely transported during the high-flow events between the 2017 and 2018 surveys but also indicating that the flows during those events were not high enough to remove some of the more firmly anchored woody debris accumulations. Most woody debris accumulations identified in 2018 did not appear to have substantially influenced geomorphic change in the locations where they were found. However, the formation of 10 of the 71 pools identified in the study reach in 2018 appeared to have been influenced by the presence of woody debris, indicating that some woody debris accumulations may have driven local geomorphic changes. Notably, pool totals from the 2017 survey could not be accurately compared to the pool totals from the 2018 survey because of differences between the two surveys in the methods used to identify pools.
Because the study began 5 years after the 2012 Little Bear Fire, and because the period and geomorphic scope of the study have so far been limited, it cannot be said that the geomorphic changes observed between the 2017 and 2018 surveys are representative of a pattern of geomorphic change following the 2012 Little Bear Fire. Though, once geomorphic changes between the 2017 and 2018 surveys can be compared with results from geomorphic surveys planned for 2019, 2020, and 2021, it may be possible to develop an understanding of the patterns in geomorphic change following the 2012 Little Bear Fire.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201121","collaboration":"Prepared in cooperation with the Village of Ruidoso, New Mexico","usgsCitation":"Graziano, A.P., 2020, Geomorphic survey of North Fork Eagle Creek, New Mexico, 2018: U.S. Geological Survey Open-File Report 2020–1121, 37 p., https://doi.org/10.3133/ofr20201121.","productDescription":"Report: v, 37 p.; Data Release","numberOfPages":"47","onlineOnly":"Y","ipdsId":"IP-112737","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":381235,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1121/ofr20201121.pdf","text":"Report","size":"16.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1121"},{"id":381236,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94ZQHKU","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data supporting the 2018 geomorphic survey of North Fork Eagle Creek, New Mexico"},{"id":381234,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1121/coverthb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"North Fork Eagle Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.5621337890625,\n 32.99023555965106\n ],\n [\n -104.7930908203125,\n 32.99023555965106\n ],\n [\n -104.7930908203125,\n 33.770015152780125\n ],\n [\n -105.5621337890625,\n 33.770015152780125\n ],\n [\n -105.5621337890625,\n 32.99023555965106\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
Management of stressors requires an understanding of how multiple stressors interact, how different species respond to those interactions and the underlying mechanisms driving observed patterns in species' responses. Salinization and rising temperatures are two pertinent stressors predicted to intensify in freshwater ecosystems, posing concern for how susceptible organisms achieve and maintain homeostasis (i.e. allostasis). Here, glucocorticoid hormones (e.g. cortisol), responsible for mobilizing energy (e.g. glucose) to relevant physiological processes for the duration of stressors, are liable to vary in response to the duration and severity of salinization and temperature rises. With field and laboratory studies, we evaluated how both salinity and temperature influence basal and stress-reactive cortisol and glucose levels in age 1+ mottled sculpin (Cottus bairdii), mountain sucker (Catostomus platyrhynchus) and Colorado River cutthroat trout (Oncorhynchus clarki pleuriticus). We found that temperature generally had the greatest effect on cortisol and glucose concentrations and the effect of salinity was often temperature dependent. We also found that when individuals were chronically exposed to higher salinities, baseline concentrations of cortisol and glucose usually declined as salinity increased. Reductions in baseline concentrations facilitated stronger stress reactivity for cortisol and glucose when exposed to additional stressors, which weakened as temperatures increased. Controlled temperatures near the species' thermal maxima became the overriding factor regulating fish physiology, resulting in inhibitory responses. With projected increases in freshwater salinization and temperatures, efforts to reduce the negative effects of increasing temperatures (i.e. increased refuge habitats and riparian cover) could moderate the inhibitory effects of temperature-dependent effects of salinization for freshwater fishes.
","language":"English","publisher":"Springer","doi":"10.1093/conphys/coaa107","usgsCitation":"Walker, R.H., Smith, G.D., Hudson, S.B., Susannah S. French, S.S., and Walters, A.W., 2020, Warmer temperatures interact with salinity to weaken physiological facilitation to stress in freshwater fishes: Conservation Physiology, v. 8, no. 1, coaa107, 18 p., https://doi.org/10.1093/conphys/coaa107.","productDescription":"coaa107, 18 p.","ipdsId":"IP-109141","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":454658,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coaa107","text":"Publisher Index Page"},{"id":436697,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IBV1RJ","text":"USGS data release","linkHelpText":"Salinity-temperature Interactions on Freshwater Fish Physiology (2015-2018)"},{"id":395556,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Upper Green River basin, Wyoming Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.73556518554688,\n 42.703632059618045\n ],\n [\n -109.8193359375,\n 42.67536823702857\n ],\n [\n -109.90859985351561,\n 42.62385465855651\n ],\n [\n -110.07064819335938,\n 42.53689200787317\n ],\n [\n -110.14068603515625,\n 42.48728928565912\n ],\n [\n -110.12763977050781,\n 42.407234661551875\n ],\n [\n -110.14892578125,\n 42.36158819524629\n ],\n [\n -110.2313232421875,\n 42.259016415705766\n ],\n [\n -110.20111083984375,\n 42.18579390537848\n ],\n [\n -110.20523071289061,\n 42.12674735753131\n ],\n [\n -110.14892578125,\n 41.98603585974727\n ],\n [\n -109.92095947265625,\n 41.90636538970964\n ],\n [\n -109.77539062499999,\n 41.72828028223453\n ],\n [\n -109.5391845703125,\n 41.45301999377133\n ],\n [\n -109.54193115234374,\n 41.3500103516271\n ],\n [\n -109.4073486328125,\n 41.29431726315258\n ],\n [\n -109.28375244140625,\n 41.413895564677304\n ],\n [\n -109.5611572265625,\n 41.84910468610387\n ],\n [\n -110.04180908203124,\n 42.338244963350846\n ],\n [\n -109.86328125,\n 42.559149812115876\n ],\n [\n -109.6490478515625,\n 42.68041629144619\n ],\n [\n -109.73556518554688,\n 42.703632059618045\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Walker, Richard H.","contributorId":274736,"corporation":false,"usgs":false,"family":"Walker","given":"Richard","email":"","middleInitial":"H.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":833270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Geoffrey D.","contributorId":274737,"corporation":false,"usgs":false,"family":"Smith","given":"Geoffrey","email":"","middleInitial":"D.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":833271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hudson, Spencer B","contributorId":274740,"corporation":false,"usgs":false,"family":"Hudson","given":"Spencer","email":"","middleInitial":"B","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":833272,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Susannah S. French, Susannah S.","contributorId":274743,"corporation":false,"usgs":false,"family":"Susannah S. French","given":"Susannah","email":"","middleInitial":"S.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":833273,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":833269,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70225719,"text":"70225719 - 2020 - Density dependence and adult survival drive the dynamics in two high elevation amphibian populations","interactions":[],"lastModifiedDate":"2021-11-04T14:37:39.384923","indexId":"70225719","displayToPublicDate":"2020-12-15T09:25:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Density dependence and adult survival drive the dynamics in two high elevation amphibian populations","docAbstract":"Amphibian conservation has progressed from the identification of declines to mitigation, but efforts are hampered by the lack of nuanced information about the effects of environmental characteristics and stressors on mechanistic processes of population regulation. Challenges include a paucity of long-term data and scant information about the relative roles of extrinsic (e.g., weather) and intrinsic (e.g., density dependence) factors. We used a Bayesian formulation of an open population capture-recapture model and >30 years of data to examine intrinsic and extrinsic factors regulating two adult boreal chorus frogs (Pseudacris maculata) populations. We modelled population growth rate and apparent survival directly, assessed their temporal variability, and derived estimates of recruitment. Populations were relatively stable (geometric mean population growth rate >1) and regulated by negative density dependence (i.e., higher population sizes reduced population growth rate). In the smaller population, density dependence also acted on adult survival. In the larger population, higher population growth was associated with warmer autumns. Survival estimates ranged from 0.30–0.87, per-capita recruitment was <1 in most years, and mean seniority probability was >0.50, suggesting adult survival is more important to population growth than recruitment. Our analysis indicates density dependence is a primary driver of population dynamics for P. maculata adults.
","language":"English","publisher":"MDPI","doi":"10.3390/d12120478","usgsCitation":"Kissel, A.M., Tenan, S., and Muths, E.L., 2020, Density dependence and adult survival drive the dynamics in two high elevation amphibian populations: Diversity, v. 12, no. 12, 478, 15 p., https://doi.org/10.3390/d12120478.","productDescription":"478, 15 p.","ipdsId":"IP-122660","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":454660,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d12120478","text":"Publisher Index Page"},{"id":436698,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9229ZLM","text":"USGS data release","linkHelpText":"Chorus frog density and population growth, Cameron Pass, Colorado, 1986-2020"},{"id":391386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Lily Pond, Matthews Pond","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.86,\n 40.6\n ],\n [\n -105.82,\n 40.6\n ],\n [\n -105.82,\n 40.56\n ],\n [\n -105.86,\n 40.56\n ],\n [\n -105.86,\n 40.6\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kissel, Amanda M.","contributorId":211917,"corporation":false,"usgs":false,"family":"Kissel","given":"Amanda","email":"","middleInitial":"M.","affiliations":[{"id":36678,"text":"Simon Fraser University","active":true,"usgs":false}],"preferred":false,"id":826397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tenan, Simone","contributorId":177519,"corporation":false,"usgs":false,"family":"Tenan","given":"Simone","email":"","affiliations":[],"preferred":false,"id":826398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":826396,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228740,"text":"70228740 - 2020 - Use of remote sensing tools to predict focal areas for sea turtle conservation in the Southwestern Atlantic","interactions":[],"lastModifiedDate":"2022-02-17T15:10:38.050995","indexId":"70228740","displayToPublicDate":"2020-12-15T09:05:47","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Use of remote sensing tools to predict focal areas for sea turtle conservation in the Southwestern Atlantic","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Soil and water conservation: A celebration of 75 years","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Soil and Water Conservation Society","usgsCitation":"Mushet, D.M., and Aram Calhoun, 2020, Wetland conservation in the United States: A swinging pendulum, chap. 14 of Soil and water conservation: A celebration of 75 years, p. 162-171.","productDescription":"10 p.","startPage":"162","endPage":"171","ipdsId":"IP-115447","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":381440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381426,"type":{"id":15,"text":"Index Page"},"url":"https://www.swcs.org/resources/publications/soil-and-water-conservation-a-celebration-of-75-years"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":807027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aram Calhoun","contributorId":245784,"corporation":false,"usgs":false,"family":"Aram Calhoun","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":807028,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216899,"text":"ofr20201140 - 2020 - Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2019","interactions":[],"lastModifiedDate":"2020-12-15T19:44:17.549778","indexId":"ofr20201140","displayToPublicDate":"2020-12-15T08:17:17","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1140","displayTitle":"Continuous Stream Discharge, Salinity, and Associated Data Collected in the Lower St. Johns River and Its Tributaries, Florida, 2019","title":"Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2019","docAbstract":"The U.S. Army Corps of Engineers, Jacksonville District, is deepening the St. Johns River channel in Jacksonville, Florida, from 40 to 47 feet along 13 miles of the river channel beginning at the mouth of the river at the Atlantic Ocean, in order to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, monitored stage, discharge, and (or) water temperature and salinity at 26 continuous data collection stations in the St. Johns River and its tributaries.
This is the fourth annual report by the U.S. Geological Survey on data collection for the Jacksonville Harbor deepening project. The report contains information pertinent to data collection during the 2019 water year, from October 2018 to September 2019. No changes to the previously installed data collection network were made during this period.
Discharge and salinity varied widely during the data collection period, which included above-average rainfall for all counties in the study area over the 3-month period from November to January, below-average annual rainfall for all counties, and effects from Hurricane Dorian in September 2019. Total annual rainfall for all counties ranked third among the annual totals computed for the 4 years considered for this study. Annual mean discharge at Durbin Creek was highest among the tributaries, followed by Trout River, Ortega River, Julington Creek, Pottsburg Creek, Broward River, Cedar River, Clapboard Creek, and Dunn Creek. The annual mean discharge for each of the main-stem sites was lower for the 2019 water year than for the 2018 water year. Since the beginning of the study in 2016, the St. Johns River at Astor station computed its lowest annual mean discharge, the Jacksonville station recorded its second lowest, and the Buffalo Bluff station recorded its second highest in 2019.
Among the tributary sites, annual mean salinity was highest at Clapboard Creek, the site closest to the Atlantic Ocean, and was lowest at Durbin Creek, the site farthest from the ocean. Annual mean salinity data from the main-stem sites on the St. Johns River indicate that salinity decreased with distance upstream from the ocean, which was expected. Relative to annual mean salinity calculated for the 2018 water year, annual mean salinity at all monitoring locations was higher for the 2019 water year except at the main-stem site below Shands Bridge and at the tributary sites of Durbin Creek and Julington Creek, which remained the same. The 2019 annual mean salinity at Dunn Creek was the highest on record for that site, and Clapboard Creek and Trout River were the second highest on record for those sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201140","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Ryan, P.J., 2020, Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2019: U.S. Geological Survey Open-File Report 2020–1140, 48 p., https://doi.org/10.3133/ofr20201140.","productDescription":"ix, 48 p.","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-118214","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":381275,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1140/coverthb.jpg"},{"id":381276,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1140/ofr20201140.pdf","text":"Report","size":"7.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1140"}],"country":"United States","state":"Florida","otherGeospatial":"St John's River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.93878173828125,\n 29.1161749329972\n ],\n [\n -81.4691162109375,\n 29.1161749329972\n ],\n [\n -81.4691162109375,\n 30.545704405480997\n ],\n [\n -81.93878173828125,\n 30.545704405480997\n ],\n [\n -81.93878173828125,\n 29.1161749329972\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Biological conservation is a fundamental purpose of the National Park system, and Catoctin Mountain Park (CATO) supports high-quality habitat for native fishes in the headwaters of the Chesapeake Bay watershed in eastern North America. However, native Blue Ridge sculpin (Cottus caeruleomentum) have been extirpated in Big Hunting Creek above Cunningham Falls in CATO. Prior research indicates that infection by the fungal-like protist Dermocystidium is a likely cause for the extirpation, but elevated stream temperatures also have been observed in the study area, and it remains unknown whether thermal stress may exacerbate infections or otherwise limit habitat suitability for fishes in CATO.
The purpose of this study was to quantify spatial variation in summer stream temperatures and to evaluate the effects of temperature on sculpin growth rates and susceptibility to Dermocystidium infection. We used observational and experimental methods to address these objectives. First, we deployed stream temperature gages at 10 sites throughout the study area to assess hourly and daily temperatures during the summer of 2019. Second, we conducted an in situ fish enclosure experiment at five of the temperature sites to assess fish growth and susceptibility to Dermocystidium infection over a 45-day exposure period. For this experiment we collected sculpin from a stream in CATO that supports a robust population of Blue Ridge sculpin (Owens Creek) and held them in quarantine for 50 days in the Experimental Stream Laboratory at the U.S. Geological Survey (USGS) Leetown Science Center. Pre-exposure histopathology confirmed the absence of Dermocystidium infection prior to the introduction of fish into experimental enclosures.
We found that stream temperatures were warmer where sculpin have been extirpated than elsewhere in CATO where sculpin persist. However, the fish enclosure experiment revealed a positive effect of temperature on fish growth, suggesting that increased food availability and foraging rates compensated for increased metabolic demands in the warmest sites. Moreover, fish held in enclosures did not develop Dermocystidium infection. Our results therefore suggest that current environmental conditions in upper Big Hunting Creek may be suitable for Blue Ridge sculpin reintroduction, and this could ultimately lead to sportfishing opportunities by increasing the forage base for native brook trout (Salvelinus fontinalis).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201137","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Hitt, N.P., Kessler, K.G., Kelly, Z.A., Rogers, K.M., Macmillan, H.E., and Walsh, H.L., 2020, Assessing native fish restoration potential in Catoctin Mountain Park: U.S. Geological Survey Open-File Report 2020–1137, 17 p., https://doi.org/10.3133/ofr20201137.","productDescription":"Report: vii, 17 p.; Data Release","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-122955","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":381222,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P950A13P","text":"USGS data release","linkHelpText":"Stream temperature and sculpin growth data collected from Catoctin Mountain Park in 2019"},{"id":381221,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1137/ofr20201137.pdf","text":"Report","size":"4.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1137"},{"id":381220,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1137/coverthb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Catoctin Mountain Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.51781463623047,\n 39.60621720230201\n ],\n [\n -77.38151550292969,\n 39.60621720230201\n ],\n [\n -77.38151550292969,\n 39.70137566512028\n ],\n [\n -77.51781463623047,\n 39.70137566512028\n ],\n [\n -77.51781463623047,\n 39.60621720230201\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Monitoring demographic response over time is valuable for understanding population dynamics of endangered species. We quantified the variation in survival patterns for three small isolated island populations of endangered waterfowl in the Hawaiian Archipelago. Laysan Teal Anas laysanensis were individually marked and the fate of 1,150 individuals were followed from different cohorts among the two reintroduced (Kure and Midway Atolls) and the single relict (Laysan Island) populations for time series of 4, 10 and 15 years respectively. We applied a non-parametric Kaplan-Meier estimator to describe variation between the populations in survival for different cohorts. For Laysan Island and Midway Atoll, we used log-rank tests to determine the effects of cohort, island and sex on survival. Birds in the Laysan Island population had significantly higher survival than those in the Midway population, and males had higher survival than females in both populations. The proportion of females surviving at Midway Atoll was 40% lower than for females on Laysan Island at year 5. The oldest bird observed from Laysan Island was at least 15.5 years old and had been ringed as an adult. The Kure Atoll founder cohort (n = 28) had 100% survival 18 months post-release, but this dropped by 39% during the first avian botulism type C outbreak. Ten of twenty-eight founders and a population of 60–70 birds persisted on Kure Atoll in 2020. We summarised mortality records to generate hypotheses to explain the cause-specific mechanisms driving the observed survival differences. Mortality data showed that the survival differences between islands in Laysan Teal survival was driven by chronic epizootics of avian botulism type C at Midway and Kure Atoll.
Previous work has proposed transfer of kinetic heat energy from low-energy broad ion beam (BIB) milling causes thermal alteration of sedimentary organic matter, resulting in increases of organic matter reflectance. Whereas, other studies have suggested the organic matter reflectance increase from BIB milling is due to decreased surface roughness. To test if reflectance increases to sedimentary organic matter (vitrinite) caused by BIB milling were related to molecular aromatization and condensation, Raman and Fourier transform infrared (FTIR) spectroscopies were used to evaluate potential compositional changes in the same vitrinite locations pre- and post-BIB milling. The same locations also were examined by atomic force microscopy (AFM) to determine topographic changes caused by BIB milling (as quantified by the areal root-mean-square roughness parameter Sq). Samples consisted of four medium volatile bituminous coals. A non-aggressive BIB milling approach was used with conditions of 5 min, 4 keV, 15°incline, 360° rotation at 25 rpm and 100% focus (1.5 kV discharge; ∼100 μA). This gentle BIB milling caused vitrinite reflectance (VRo) increases of 12 to 36% of the original values determined optically before milling (average 26% increase). When molecular proxies from FTIR (A- and C-factor, branching ratio) were plotted against each other for the same vitrinite locations pre- and post-milling, mean data points for each sample generally lie within error of a 1:1 line. Likewise, mean Raman thermal proxy [full-width half maximum of G-band (G-FWHM), Raman band separation (RBS) and D1/G band intensity ratio] values were similar for pre- and post-milled locations, also plotting within error of a 1:1 line. AFM confirms the majority (24 of 36) of pre- and post-ion milled surface pairs were smoother (lower Sq values) after BIB milling. These results are interpreted to indicate VRo increase induced by the gentle BIB milling conditions used in this study is an effect of decreased diffuse reflectance due to flatter surfaces, causing more photons to reflect directly back to the detector. Little evidence was observed for molecular aromatization and condensation of vitrinite molecules following BIB milling (with the conditions used). The presence of milling-induced artifacts, including differential milling effects dependent on location and the development of self-organized patterned structures, indicate much work remains in standardization of BIB milling before its promulgation as a routine sample preparation technique for organic petrography. These results provide better understanding of anthropogenic-induced changes to geological samples caused by the now widespread adoption of BIB milling as a disruptive innovation in sample preparation.
Predictions of river channel adjustment to changes in streamflow regime based on relations between mean channel characteristics and mean flood magnitude can be useful to evaluate average channel response. However, because these relations assume equilibrium sediment transport, their applicability to cases where streamflow and sediment transport are decoupled may be limited. These general relations also lack the specificity that is required to connect specific characteristics of the streamflow and sediment regime with the dynamics of channel morphological change that create channel complexity, which is often of ecological interest. We integrate historical records of channel change, observations of scour and fill during a snowmelt flood, measurements of sediment transport, and predictions from a two-dimensional streamflow model to describe how annual peak flow magnitude and peak-flow duration interact with the upstream sediment supply to control channel form for a 15-km study reach on the regulated Green River in Canyonlands National Park, Utah. Two major decadal-scale episodes of channel narrowing have occurred within the study area. For each of these episodes, the reduction in average channel width was consistent with the change predicted by hydraulic geometry relations as a function of average flood magnitude. However, channel narrowing occurred during periods of exceptionally low annual floods. The most recent episode of channel narrowing occurred between 1988 and 2009, during low-flow cycles when the 5-yr mean peak flow was less than 60% of the long-term (1959–2016) mean peak flow. These findings, together with findings from previous studies, demonstrate that decreases in peak-flow magnitude caused by streamflow regulation, climate change, or a combination of those factors have driven episodes of channel narrowing on the Green River. Observations of streamflow, sediment-transport, and morphologic change coupled with predictions from a two-dimensional streamflow model indicate that peak flow magnitudes of at least 75% of the long-term mean peak flow are required to transport bed-material sand in suspension in all regions of the multi-thread channel and that the ~2-month duration of the snowmelt flood played an important role in creating conditions necessary to maintain channel conveyance. These results indicate that detailed characterizations of channel response such as these are needed to predict how river channels will respond to changes in streamflow regime that affect annual peak flow magnitude and duration.
In 1869, John Wesley Powell completed the first well-recorded scientific river journey to explore an extensive region of the Colorado River Basin. Powell later helped to establish the U.S. Geological Survey (USGS) and served as its second director (1881–94), cementing his position in the folklore of the Survey. In 2019, the USGS marked the 150th anniversary of Powell’s first expedition with a broad-scale educational campaign as an opportunity to highlight current USGS science in the region through the lens of an exciting river expedition, with the goal of inspiring the next generation of USGS scientists. The project included a partnership with the Sesquicentennial Colorado River Exploring Expedition (SCREE), which traveled the length of the original route for ~1,000 river miles from Green River, Wyoming, to Lake Mead, Nevada, including the Grand Canyon. Small, interdisciplinary groups of USGS employees joined each segment of the journey, gathered data to be used for educational purposes, participated in community outreach events, and upon return shared their experiences with their local communities. This report documents a photographic journey of the expedition, personal vignettes from the USGS participants, Science Stories to explain the scope of the experiments, and Then and Now articles (which were published online during the expedition), to explore some of the changes that have occurred since the first expedition.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1475","usgsCitation":"Scott, A., and Snow, E., 2020, The 150th anniversary of the 1869 Powell expedition—USGS participation in the Sesquicentennial Colorado River Exploring Expedition and reflections from the ~1,000-mile journey down the Green and Colorado Rivers (ver. 1.1, December 14, 2020): U.S. Geological Survey Circular 1475, 88 p., https://doi.org/10.3133/cir1475.","productDescription":"Report: vii, 88 p.; Version History","numberOfPages":"88","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-119749","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"links":[{"id":381274,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/circ/1475/versionHist.txt","size":"1.17 KB","linkFileType":{"id":2,"text":"txt"}},{"id":381014,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1475/cir1475.pdf","text":"Report","size":"24.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1475"},{"id":380830,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1475/coverthb3.jpg"}],"country":"United States","state":"Arizona, Colorado, Utah, Wyoming","otherGeospatial":"Colorado River, Grand Canyon, Green River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.4073486328125,\n 41.6154423246811\n ],\n [\n -109.7479248046875,\n 41.32732632036622\n ],\n [\n -109.7039794921875,\n 40.88444793903562\n ],\n [\n -109.2095947265625,\n 40.84706035607122\n ],\n [\n -109.017333984375,\n 40.751418432997454\n ],\n [\n -109.09423828125,\n 40.55972134684838\n ],\n [\n -109.4677734375,\n 40.455307212131494\n ],\n [\n -109.8358154296875,\n 40.052847601823984\n ],\n [\n -110.1324462890625,\n 39.57182223734374\n ],\n [\n -110.2423095703125,\n 38.93377552819722\n ],\n [\n -110.093994140625,\n 38.49229419236133\n ],\n [\n -109.984130859375,\n 38.199338565983844\n ],\n [\n -110.1708984375,\n 38.03078569382294\n ],\n [\n -110.5828857421875,\n 37.79676317682161\n ],\n [\n -110.75866699218749,\n 37.57505900514996\n ],\n [\n -110.94543457031249,\n 37.38761749978395\n ],\n [\n -111.03881835937499,\n 37.204081555898526\n ],\n [\n -111.3848876953125,\n 37.18220222107978\n ],\n [\n -111.6375732421875,\n 37.077093191754436\n ],\n [\n -112.049560546875,\n 36.22211876039103\n ],\n [\n -112.4945068359375,\n 36.4566360115962\n ],\n [\n -113.302001953125,\n 36.25756282630298\n ],\n [\n -113.4613037109375,\n 36.01800375871416\n ],\n [\n -113.477783203125,\n 35.82672127366604\n ],\n [\n -113.97766113281249,\n 36.23984280222428\n ],\n [\n -114.0216064453125,\n 36.115690180653395\n ],\n [\n -113.917236328125,\n 35.875698032496665\n ],\n [\n -113.345947265625,\n 35.65729624809628\n ],\n [\n -113.203125,\n 36.02688935430189\n ],\n [\n -112.510986328125,\n 36.3106987841827\n ],\n [\n -112.0770263671875,\n 35.9157474194997\n ],\n [\n -111.741943359375,\n 36.06686213257888\n ],\n [\n -111.72546386718749,\n 36.48755716938576\n ],\n [\n -111.3629150390625,\n 36.932330061503144\n ],\n [\n -110.7861328125,\n 37.08585785263673\n ],\n [\n -110.40710449218749,\n 37.54893261064111\n ],\n [\n -109.8028564453125,\n 38.16047628099622\n ],\n [\n -109.0887451171875,\n 38.94232097947902\n ],\n [\n -109.22607421875,\n 39.0831721934762\n ],\n [\n -109.9346923828125,\n 38.47509432050245\n ],\n [\n -109.984130859375,\n 39.06184913429154\n ],\n [\n -109.599609375,\n 40.04864272291728\n ],\n [\n -108.8525390625,\n 40.40513069752789\n ],\n [\n -108.69873046875,\n 40.78885994449482\n ],\n [\n -109.0008544921875,\n 40.97160353279909\n ],\n [\n -109.3963623046875,\n 41.04621681452063\n ],\n [\n -109.3359375,\n 41.41801503608024\n ],\n [\n -109.2974853515625,\n 41.611335399441735\n ],\n [\n -109.4073486328125,\n 41.6154423246811\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: December 3, 2020; Version 1.1: December 14, 2020","contact":"https://www.usgs.gov
https://www.usgs.gov/powell150