On active alluvial fans, debris-flow deposits and frequent avulsions produce a rough topographic surface. As is the case in many initially rough landforms produced by catastrophic processes, the topography of alluvial fans is progressively smoothed, producing textural differences useful in establishing relative age criteria for fans. Here, we outline an approach for defining a quantitative, numerical chronology for the surfaces of alluvial fans from topographic analysis, although the method is generalizable to any arbitrary landform. Our chronology relies on predictions for the evolution of topography by purely diffusive modification. Specifically, by comparing the surface roughness of active and abandoned alluvial-fan surfaces measured from spectral transformations of topography, we can directly estimate a fan’s “morphologic age,” which is the product of the duration and efficiency of diffusive modification by surface processes. We tested the method on a suite of alluvial fans in the San Luis Valley, Colorado, USA, and evaluated the results against field observations and available geochronologic data. Estimated morphologic ages obey stratigraphic constraints and imply reasonable efficiencies of sediment transport. We highlight the fact that the oldest fan surfaces observed here, constrained to be older than 100 ka by U-series dating of pedogenic carbonates, have morphologic ages near the method’s saturation point. In addition, many fans have morphologies that are not entirely consistent with a purely diffusive modification from the initial fan morphology recorded on active fan surfaces, likely as a result of postdepositional modification by sediment transport driven by wind and overland flow. However, we remain optimistic that morphologic dating can provide useful insights into the history of alluvial-fan activity, in particular, because our method provides a means for both computing a morphologic age and assessing the validity of the assumptions required for that computation from analysis of topography alone.
","language":"English","publisher":"Geologic Society of America","doi":"10.1130/GES01680.1","usgsCitation":"Johnstone, S., Hudson, A.M., Nicovich, S., Ruleman, C.A., Sare, R.M., and Thompson, R., 2018, Establishing chronologies for alluvial-fan sequences with analysis of high-resolution topographic data: San Luis Valley, Colorado, USA: Geosphere, v. 14, no. 6, p. 1-18, https://doi.org/10.1130/GES01680.1.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-095218","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":468287,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01680.1","text":"Publisher Index Page"},{"id":437711,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q2BP9P","text":"USGS data release","linkHelpText":"U and Th isotope data for "Establishing chronologies for alluvial-fan sequences with analysis of high-resolution topographic data: San Luis Valley, Colorado, USA""},{"id":358813,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Luis Valley","volume":"14","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-24","publicationStatus":"PW","scienceBaseUri":"5bed4272e4b0b3fc5cf91c84","contributors":{"authors":[{"text":"Johnstone, Samuel 0000-0002-3945-2499","orcid":"https://orcid.org/0000-0002-3945-2499","contributorId":207545,"corporation":false,"usgs":true,"family":"Johnstone","given":"Samuel","email":"","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":749711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hudson, Adam M. 0000-0002-3387-9838 ahudson@usgs.gov","orcid":"https://orcid.org/0000-0002-3387-9838","contributorId":195419,"corporation":false,"usgs":true,"family":"Hudson","given":"Adam","email":"ahudson@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":749712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nicovich, Sylvia","contributorId":210054,"corporation":false,"usgs":false,"family":"Nicovich","given":"Sylvia","affiliations":[{"id":38060,"text":"Department of Earth Sciences, Montana State University, Bozeman, MT","active":true,"usgs":false}],"preferred":false,"id":749713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":749714,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sare, Robert M.","contributorId":210055,"corporation":false,"usgs":false,"family":"Sare","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":38061,"text":"Department of Geological Sciences, Stanford University, Stanford, CA","active":true,"usgs":false}],"preferred":false,"id":749715,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thompson, Ren A. 0000-0002-3044-3043","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":207982,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":749716,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70200596,"text":"70200596 - 2018 - Upstream migration and spawning success of Chinook salmon in a highly developed, seasonally warm river system","interactions":[],"lastModifiedDate":"2019-02-21T14:53:05","indexId":"70200596","displayToPublicDate":"2018-10-25T11:59:42","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5040,"text":"Reviews in Fisheries Science & Aquaculture","onlineIssn":"2330-8257","printIssn":"2330-8249","active":true,"publicationSubtype":{"id":10}},"title":"Upstream migration and spawning success of Chinook salmon in a highly developed, seasonally warm river system","docAbstract":"This review summarizes what is known about the influence of water temperature and velocity on the migration and spawning success of an inland population of Chinook salmon Oncorhynchus tshawytscha. Models are then developed and used to illustrate how migration and spawning success might change if temperatures and velocities increase under a future climate. The illustration shows the potential for moderate increases in temperature and velocity to reduce homing and increase energy expenditure. Those two outcomes would reduce the abundance, productivity, and diversity of the population studied. Under the future scenario illustrated, it would become difficult for fish management actions alone to recover conservation-reliant populations of inland Chinook salmon.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/23308249.2018.1477736","usgsCitation":"Connor, W.P., Tiffan, K.F., Chandler, J.A., Rondorf, D.W., Arnsberg, B.D., and Anderson, K.C., 2018, Upstream migration and spawning success of Chinook salmon in a highly developed, seasonally warm river system: Reviews in Fisheries Science & Aquaculture, v. 27, no. 1, p. 1-50, https://doi.org/10.1080/23308249.2018.1477736.","productDescription":"50 p.","startPage":"1","endPage":"50","ipdsId":"IP-097181","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468288,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/23308249.2018.1477736","text":"Publisher Index Page"},{"id":358809,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Columbia River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.87060546874999,\n 42.439674178149424\n ],\n [\n -111.9287109375,\n 42.439674178149424\n ],\n [\n -111.9287109375,\n 48.21003212234042\n ],\n [\n -124.87060546874999,\n 48.21003212234042\n ],\n [\n -124.87060546874999,\n 42.439674178149424\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-10","publicationStatus":"PW","scienceBaseUri":"5c10a916e4b034bf6a7e4f72","contributors":{"authors":[{"text":"Connor, William P.","contributorId":107589,"corporation":false,"usgs":false,"family":"Connor","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":16677,"text":"U.S. Fish and Wildlife Service, Idaho Fishery Resource Office, 276 Dworshak Complex Drive, Orofino, ID 83544","active":true,"usgs":false}],"preferred":false,"id":749678,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tiffan, Kenneth F. 0000-0002-5831-2846 ktiffan@usgs.gov","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":3200,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","email":"ktiffan@usgs.gov","middleInitial":"F.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749679,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chandler, James A.","contributorId":210045,"corporation":false,"usgs":false,"family":"Chandler","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":38056,"text":"Idaho Power Company 1221 West Idaho Street, Boise, ID 83702","active":true,"usgs":false}],"preferred":true,"id":749680,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rondorf, Dennis W. drondorf@usgs.gov","contributorId":2970,"corporation":false,"usgs":true,"family":"Rondorf","given":"Dennis","email":"drondorf@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749681,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arnsberg, Billy D.","contributorId":210047,"corporation":false,"usgs":false,"family":"Arnsberg","given":"Billy","email":"","middleInitial":"D.","affiliations":[{"id":38057,"text":"Nez Perce Tribe, Department of Fisheries Resources Management, P.O. Box 365, Lapwai, ID 83540","active":true,"usgs":false}],"preferred":false,"id":749682,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Kelvin C.","contributorId":210048,"corporation":false,"usgs":false,"family":"Anderson","given":"Kelvin","email":"","middleInitial":"C.","affiliations":[{"id":38058,"text":"Idaho Power Company, 1221 West Idaho Street, Boise, ID 83702","active":true,"usgs":false}],"preferred":false,"id":749683,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70223286,"text":"70223286 - 2018 - Evaluating inter-rater reliability and statistical power of vegetation measures assessing deer impact","interactions":[],"lastModifiedDate":"2021-08-20T14:43:09.267987","indexId":"70223286","displayToPublicDate":"2018-10-25T09:36:25","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1689,"text":"Forests","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating inter-rater reliability and statistical power of vegetation measures assessing deer impact","docAbstract":"Long-term vegetation monitoring projects are often used to evaluate how plant communities change through time in response to some external influence. Here, we evaluate the efficacy of vegetation monitoring to consistently detect changes in white-tailed deer browsing effects. Specifically, we compared inter-rater reliability (Cohen’s κ and Lin’s concordance correlation coefficient) between two identically trained field crews for several plant metrics used by Pennsylvania state agencies to monitor deer browsing impact. Additionally, we conducted a power analysis to determine the effect of sampling scale (1/2500th or 1/750th ha plots) on the ability to detect changes in tree seedling stem counts over time. Inter-rater reliability across sampling crews was substantial for most metrics based on direct measurements, while the observational based Deer Impact Index (DII) had only moderate inter-rater reliability. The smaller, 1/2500th ha sampling scale resulted in higher statistical power to detect changes in tree seedling stem counts due to reduced observer error. Overall, this study indicates that extensive training on plant identification, project protocols, and consistent data collection methods can result in reliable vegetation metrics useful for tracking understory responses to white-tailed deer browsing. Smaller sampling scales and objective plant measures (i.e., seedling counts, species richness) improve inter-rater reliability over subjective measures of deer impact (i.e., DII). However, considering objective plant measures when making a subjective assessment regarding deer browsing effects may also improve DII inter-rater reliability.
","language":"English","publisher":"MDPI","doi":"10.3390/f9110669","usgsCitation":"Begley-Miller, D.R., Diefenbach, D.R., McDill, M.E., Rosenberry, C., and Just, E.H., 2018, Evaluating inter-rater reliability and statistical power of vegetation measures assessing deer impact: Forests, v. 9, no. 11, 669, 17 p., https://doi.org/10.3390/f9110669.","productDescription":"669, 17 p.","ipdsId":"IP-101441","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468290,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/f9110669","text":"Publisher Index Page"},{"id":388235,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Bald Eagle State Forest, Rothrock State Forest, Susquehannock State Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.14437866210938,\n 41.49006348843993\n ],\n [\n -77.47833251953125,\n 41.49006348843993\n ],\n [\n -77.47833251953125,\n 41.840920397579936\n ],\n [\n -78.14437866210938,\n 41.840920397579936\n ],\n [\n -78.14437866210938,\n 41.49006348843993\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.25698852539062,\n 40.447992135544304\n ],\n [\n -76.93862915039062,\n 40.447992135544304\n ],\n [\n -76.93862915039062,\n 41.10212132036491\n ],\n [\n -78.25698852539062,\n 41.10212132036491\n ],\n [\n -78.25698852539062,\n 40.447992135544304\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"11","noUsgsAuthors":false,"publicationDate":"2018-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Begley-Miller, Danielle R.","contributorId":264498,"corporation":false,"usgs":false,"family":"Begley-Miller","given":"Danielle","email":"","middleInitial":"R.","affiliations":[{"id":54482,"text":"Teatown Lake Reservation","active":true,"usgs":false}],"preferred":false,"id":821615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":821614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McDill, Marc E.","contributorId":264499,"corporation":false,"usgs":false,"family":"McDill","given":"Marc","email":"","middleInitial":"E.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":821616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosenberry, Christopher S.","contributorId":264500,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher S.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":821617,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Just, Emily H.","contributorId":264501,"corporation":false,"usgs":false,"family":"Just","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":37212,"text":"Pennsylvania Department of Conservation and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":821618,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217042,"text":"70217042 - 2018 - Estimating the probability of movement and partitioning seasonal survival in an amphibian metapopulation","interactions":[],"lastModifiedDate":"2020-12-29T13:43:18.171874","indexId":"70217042","displayToPublicDate":"2018-10-25T07:38:29","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the probability of movement and partitioning seasonal survival in an amphibian metapopulation","docAbstract":"Movement of individuals has been described as one of the best studied, but least understood concepts in ecology. The magnitude of movements, routes, and probability of movement have significant application to conservation. Information about movement can inform efforts to model species persistence and is particularly applicable in situations where specific threats (e.g., disease) may depend on the movement of hosts and potential vectors. We estimated the probability of movement (breeding dispersal and permanent emigration) in a metapopulation of 16 breeding sites for boreal toads (Anaxyrus boreasboreas). We used a multi‐state mark–recapture approach unique in its complexity (16 sites over 18 yr) to address questions related to these movements and variation in resident survival. We found that individuals had a 1–2% probability of dispersing in a particular year and that approximately 10–20% of marked individuals were transient and observed in the metapopulation only once. Resident survival probabilities differed by season, with 71–90% survival from emergence from hibernation through early post‐breeding and >97% survival from mid‐/late active season through hibernation. Movement‐related probabilities are needed to predict species range expansions and contractions, estimate population and metapopulation dynamics, understand host–pathogen and native–invasive species interactions, and to evaluate the relative effects of proposed management actions.
Most approaches for assessing species vulnerability to climate change have focused on direct impacts via abiotic changes rather than indirect impacts mediated by changes in species interactions. Changes in rainfall regimes may influence species interactions from the bottom-up by increasing primary productivity in arid environments, but subsequently lead to less predictable top-down effects. Our study demonstrates how the effects of an EL Niño/Southern Oscillation (ENSO)-driven rainfall pulse ricochets along a chain of interactions between marine and terrestrial food webs, leading to enhanced predation of a vulnerable marine predator on its island breeding grounds. On Santa Barbara Island, barn owls (Tyto alba) are the main predator of a nocturnal seabird, the Scripps's murrelet (Synthliboramphus scrippsi), as well as an endemic deer mouse. We followed the links between rainfall, normalized difference vegetation index and subsequent peaks in mouse and owl abundance. After the mouse population declined steeply, there was approximately 15-fold increase in the number of murrelets killed by owls. We also simulated these dynamics with a mathematical model and demonstrate that bottom-up resource pulses can lead to subsequent declines in alternative prey. Our study highlights the need for understanding how species interactions will change with shifting rainfall patterns through the effects of ENSO under global change.
","language":"English","publisher":"The Royal Society","doi":"10.1098/rspb.2018.1161","usgsCitation":"Thomsen, S., Mazurkiewicz, D.M., Stanley, T.R., and Green, D.J., 2018, El Niño/Southern Oscillation-driven rainfall pulse amplifies predation by owls on seabirds via apparent competition with mice: Proceedings of the Royal Society B: Biological Sciences, v. 285, no. 1889, https://doi.org/10.1098/rspb.2018.1161.","ipdsId":"IP-096686","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468293,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspb.2018.1161","text":"Publisher Index Page"},{"id":359187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Barbara Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.05437469482422,\n 33.46266623370559\n ],\n [\n -119.02261734008788,\n 33.46266623370559\n ],\n [\n -119.02261734008788,\n 33.48979984340796\n ],\n [\n -119.05437469482422,\n 33.48979984340796\n ],\n [\n -119.05437469482422,\n 33.46266623370559\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"285","issue":"1889","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-24","publicationStatus":"PW","scienceBaseUri":"5be16511e4b0b3fc5cf3ffba","contributors":{"authors":[{"text":"Thomsen, Sarah K.","contributorId":210436,"corporation":false,"usgs":false,"family":"Thomsen","given":"Sarah K.","affiliations":[{"id":36678,"text":"Simon Fraser University","active":true,"usgs":false}],"preferred":false,"id":750701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mazurkiewicz, David M.","contributorId":210437,"corporation":false,"usgs":false,"family":"Mazurkiewicz","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":750702,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stanley, Thomas R. 0000-0002-8393-0005 stanleyt@usgs.gov","orcid":"https://orcid.org/0000-0002-8393-0005","contributorId":209928,"corporation":false,"usgs":true,"family":"Stanley","given":"Thomas","email":"stanleyt@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":750700,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Green, David J.","contributorId":210438,"corporation":false,"usgs":false,"family":"Green","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":36678,"text":"Simon Fraser University","active":true,"usgs":false}],"preferred":false,"id":750703,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200034,"text":"ofr20181164 - 2018 - Mars global digital dune database (MGD3)—Composition, stability, and thermal inertia","interactions":[],"lastModifiedDate":"2018-10-25T14:58:50","indexId":"ofr20181164","displayToPublicDate":"2018-10-24T11:53:29","publicationYear":"2018","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":"2018-1164","displayTitle":"Mars global digital dune database (MGD3)—Composition, stability, and thermal inertia","title":"Mars global digital dune database (MGD3)—Composition, stability, and thermal inertia","docAbstract":"The Mars Global Digital Dune Database (MGD3) is an online repository that has catalogued dune fields larger than 1 km2 located between latitudes 90° N. and 90° S. The work presented here expands upon previous MGD3 open-file reports, with a new emphasis upon characterizing dune fields through composition, stability, and thermal inertia. Included in this latest addition is a detailed compositional analysis and the associated observational data from Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) for dune fields 300 km2 or larger; a near-global dune stability assessment; Mars Odyssey (MO1) Thermal Emission Imaging System (THEMIS) apparent thermal inertia values; and vertical near-surface thermophysical heterogeneities determined by fitting a two-layer thermal model to observed temperatures. These additional datasets are divided into two workbooks: equatorial and south polar regions. A detailed description for the layout of these workbooks can be found in the corresponding metadata document. The continuing goal of the MGD3 is to provide a reliable and multifaceted repository of data for Mars’ dunes, with the intention that such data be easily accessible and useful to future research.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181164","usgsCitation":"Gullikson, A.L., Hayward, R.K., Titus, T.N., Charles, H., Fenton, L.K., Hoover, R., and Putzig, N.E., 2018, Mars global digital dune database (MGD3)—Composition, stability, and thermal inertia: U.S. Geological Survey Open-File Report 2018–1164, 17 p., https://doi.org/10.3133/ofr20181164.","productDescription":"Report: vi, 17 p.; Appendix 1; Dune Database","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-097409","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":358707,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1164/coverthb.jpg"},{"id":358708,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1164/ofr20181164.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1164"},{"id":358709,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1164/ofr20181164_appendix.pdf","text":"Appendix 1","size":"603 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1164 Appendix","linkHelpText":"Graphs pertaining to the spectral glitch"},{"id":358710,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1164/ofr20181164_dunedatabase.zip","text":"Dune Database","size":"3 MB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2018-1164 Database","linkHelpText":"Equatorial and South Polar Dune Databases and metadata"},{"id":358712,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20101170","text":"Open-File Report 2010–1170 —","linkHelpText":"Mars Global Digital Dune Database: MC–1"},{"id":358711,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20071158","text":"Open-File Report 2007–1158 —","linkHelpText":"Mars Global Digital Dune Database: MC2–MC29"},{"id":358713,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20121259","text":"Open-File Report 2012–1259 —","linkHelpText":"Mars Global Digital Dune Database: MC–30"}],"contact":"Contact Astrogeology Research Program staff
Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
The potential effect of cemetery leachate on groundwater quality in the United States has rarely been studied. Nutrients and other constituents associated with decomposition and burial processes (such as embalming) have the potential to reach shallow groundwater and could affect nearby drinking-water sources. The objective of this preliminary investigation was to evaluate the potential effect of cemetery leachate on shallow groundwater quality near Mt. Hope Cemetery in Ingham County, Lansing, Michigan, which is within the Well-head Protection Area for the City of Lansing. The constituents measured in this study include nutrients, trace metals, formaldehyde, fecal indicator bacteria, bacterial pathogen genes, contaminants of emerging concern (including pharmaceuticals, personal care products, and wastewater indicator compounds), and age-dating compounds. Three monitoring wells were installed 7 to 12 feet below land surface downgradient from the cemetery and sampled quarterly for 1 year. A fourth well (Fenner) was sampled to determine groundwater conditions outside the potential effects of cemetery leachate; samples from this well were collected near the water table.
Nitrogen and phosphorus compounds were present at higher concentrations in two of the three monitoring wells (wells C1 and C3) than in the Fenner well. Formaldehyde and pharmaceuticals were not detected in any of the wells; however, several trace metals, including arsenic, manganese, and aluminum, were present in high concentrations, with arsenic concentrations typically exceeding the U.S. Environmental Protection Agency (EPA) drinking-water standard. Several wastewater indicator compounds, including atrazine, phenol, p-cresol, camphor, and skatole, were detected in the monitoring wells. Microbial data indicate the presence of staphylococci, enterococci, and Escherichia coli (E. coli), with the highest concentrations being measured in the same two monitoring wells that exhibited elevated concentrations of nutrients in the groundwater (wells C1 and C3). Several bacterial pathogen genes were detected, including several Enterococcus species (spp.)—vanB (vancomycin-resistant enterococci), shiga-toxin-producing E. coli genes (including eaeA [attachment virulence trait] and stx1 [moderate toxin]), and the E. coli 16s ribosomal RNA (rDNA) gene ( E. coli species marker). These results were similar to results of studies conducted in Canada, Australia, and the United Kingdom, in which concentrations of bacteria, metals, and nutrients were elevated in groundwater near cemeteries.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185120","collaboration":"Prepared in cooperation with the Lansing Board of Water and Light and the Lansing Wellhead Protection Team","usgsCitation":"Brennan, A.K., Givens, C.E., Prokopec, J.G., and Hoard, C.J., 2018, Preliminary investigation of groundwater quality near a Michigan cemetery, 2016–17: U.S. Geological Survey Scientific Investigations Report 2018–5120, 23 p., https://doi.org/10.3133/sir20185120.","productDescription":"vi, 23 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-096238","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":358631,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5120/sir20185120.pdf","text":"Report","size":"17.8 MB","description":"SIR 2018-5120"},{"id":358630,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5120/coverthb.jpg"}],"country":"United States","state":"Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.52966690063477,\n 42.70460970722399\n ],\n [\n -84.51863765716553,\n 42.70460970722399\n ],\n [\n -84.51863765716553,\n 42.711862740860546\n ],\n [\n -84.52966690063477,\n 42.711862740860546\n ],\n [\n -84.52966690063477,\n 42.70460970722399\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Upper Midwest Water Science Center
U.S. Geological Survey
6520 Mercantile Way, Suite 5
Lansing, MI 48911
The aquaculture industry is growing rapidly to meet the needs for global protein consumption. Viral diseases in aquaculture are quite challenging due to lack of treatment options as well as limited injection-delivery vaccines, which are costly. Thus, water-immersion antiviral treatments are highly desirable. This study focused on broad-spectrum, light-activated antivirals that target the viral membrane (envelope) of viruses to prevent viral-cell membrane fusion, ultimately blocking viral entry into cells. Of the tested small-molecules, JL122, a new broad-spectrum antiviral previously unexplored against aquatic viruses, blocked infection of three aquatic rhabdoviruses (IHNV, VHSV and SVCV) in cell culture and in two live fish challenge models. Importantly, JL122 inhibited transmission of IHNV from infected to uninfected rainbow trout. Further, the effective antiviral concentrations were not toxic to cells or susceptible fish. These results show promise for JL122 to become an immersion treatment option for outbreaks of aquatic enveloped viral infections.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.virol.2018.09.009","usgsCitation":"Balmer, B.F., Getchell, R.G., Powers, R., Lee, J., Zhang, T., Jung, M.E., Purcell, M.K., Snekvik, K., and Aguilar, H.C., 2018, Broad-spectrum antiviral JL122 blocks infection and inhibits transmission of aquatic rhabdoviruses: Virology, v. 525, p. 143-149, https://doi.org/10.1016/j.virol.2018.09.009.","productDescription":"7 p.","startPage":"143","endPage":"149","ipdsId":"IP-097428","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468295,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10205048","text":"Publisher Index Page"},{"id":358695,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"525","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a917e4b034bf6a7e4f88","contributors":{"authors":[{"text":"Balmer, Bethany F.","contributorId":190169,"corporation":false,"usgs":false,"family":"Balmer","given":"Bethany","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":749433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Getchell, Rodman G.","contributorId":201129,"corporation":false,"usgs":false,"family":"Getchell","given":"Rodman","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":749434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powers, Rachel L. 0000-0001-6901-4361","orcid":"https://orcid.org/0000-0001-6901-4361","contributorId":190182,"corporation":false,"usgs":true,"family":"Powers","given":"Rachel L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749435,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lee, Jihye","contributorId":190171,"corporation":false,"usgs":false,"family":"Lee","given":"Jihye","email":"","affiliations":[],"preferred":false,"id":749472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Tinghu","contributorId":210005,"corporation":false,"usgs":false,"family":"Zhang","given":"Tinghu","email":"","affiliations":[],"preferred":false,"id":749473,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jung, Michael E.","contributorId":190174,"corporation":false,"usgs":false,"family":"Jung","given":"Michael","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":749436,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749437,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Snekvik, Kevin","contributorId":127574,"corporation":false,"usgs":false,"family":"Snekvik","given":"Kevin","email":"","affiliations":[{"id":7057,"text":"Washington Animal Disease Diagnostic Laboratory, Washington State Univeristy","active":true,"usgs":false}],"preferred":false,"id":749438,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Aguilar, Hector C.","contributorId":190175,"corporation":false,"usgs":false,"family":"Aguilar","given":"Hector","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":749439,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70200517,"text":"70200517 - 2018 - Rebuttal to “The case of the Biscayne Bay and aquifer near Miami, Florida: density-driven flow of seawater or gravitationally driven discharge of deep saline groundwater?” by Weyer (Environ Earth Sci 2018, 77:1–16)","interactions":[],"lastModifiedDate":"2018-10-23T10:39:05","indexId":"70200517","displayToPublicDate":"2018-10-23T10:38:59","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1534,"text":"Environmental Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Rebuttal to “The case of the Biscayne Bay and aquifer near Miami, Florida: density-driven flow of seawater or gravitationally driven discharge of deep saline groundwater?” by Weyer (Environ Earth Sci 2018, 77:1–16)","docAbstract":"A recent paper by Weyer (Environ Earth Sci 2018, 77:1–16) challenges the widely accepted interpretation of groundwater heads and salinities in the coastal Biscayne aquifer near Miami, Florida, USA. Weyer (2018) suggests that the body of saltwater that underlies fresh groundwater just inland of the coast is not a recirculating wedge of seawater, but results instead from upward migration of deep saline groundwater driven by regional flow. Perhaps more significantly, Weyer (2018) also asserts that established hydrologic theory is fundamentally incorrect with respect to buoyancy. Instead of acting along the direction of gravity (that is, vertically), Weyer (2018) claims, buoyancy acts instead along the direction of the pressure gradient. As a result, Weyer (2018) considers currently available density-dependent groundwater flow and transport modeling codes, and the analyses based on them, to be in error. In this rebuttal, we clarify the inaccuracies in the main points of Weyer’s (2018) paper. First, we explain that Weyer (2018) has misinterpreted observed equivalent freshwater heads in the Biscayne aquifer and that his alternative hypothesis concerning the source of the saltwater does not explain the observed salinities. Then, we review the established theory of buoyancy to identify the problem with Weyer’s (2018) alternative theory. Finally, we present theory and cite successful benchmark simulations to affirm the suitability of currently available codes for modeling density-dependent groundwater flow and transport.
","language":"English","publisher":"Springer","doi":"10.1007/s12665-018-7832-5","usgsCitation":"Provost, A.M., Werner, A.D., Post, V.E., Michael, H.A., and Langevin, C.D., 2018, Rebuttal to “The case of the Biscayne Bay and aquifer near Miami, Florida: density-driven flow of seawater or gravitationally driven discharge of deep saline groundwater?” by Weyer (Environ Earth Sci 2018, 77:1–16): Environmental Earth Sciences, v. 77, p. 1-6, https://doi.org/10.1007/s12665-018-7832-5.","productDescription":"Article 710; 6 p.","startPage":"1","endPage":"6","ipdsId":"IP-097832","costCenters":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"links":[{"id":468296,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12665-018-7832-5","text":"Publisher Index Page"},{"id":358665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"77","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-11","publicationStatus":"PW","scienceBaseUri":"5c10a917e4b034bf6a7e4f8e","contributors":{"authors":[{"text":"Provost, Alden M. 0000-0002-4443-1107 aprovost@usgs.gov","orcid":"https://orcid.org/0000-0002-4443-1107","contributorId":138757,"corporation":false,"usgs":true,"family":"Provost","given":"Alden","email":"aprovost@usgs.gov","middleInitial":"M.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":false,"id":749224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Werner, Adrian D.","contributorId":209967,"corporation":false,"usgs":false,"family":"Werner","given":"Adrian","email":"","middleInitial":"D.","affiliations":[{"id":38040,"text":"College of Science and Engineering, and National Centre for Groundwater Research and Training, Flinders University","active":true,"usgs":false}],"preferred":false,"id":749225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Post, Vincent E. A.","contributorId":209968,"corporation":false,"usgs":false,"family":"Post","given":"Vincent","email":"","middleInitial":"E. A.","affiliations":[{"id":38041,"text":"College of Science and Engineering, and National Centre for Groundwater Research and Training, Flinders University; Federal Institute for Geosciences and Natural Resources (BGR), Hannover, Germany","active":true,"usgs":false}],"preferred":false,"id":749226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Michael, Holly A.","contributorId":190224,"corporation":false,"usgs":false,"family":"Michael","given":"Holly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":749227,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":749228,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200726,"text":"70200726 - 2018 - Integrating encounter theory with decision analysis to evaluate collision risk and determine optimal protection zones for wildlife","interactions":[],"lastModifiedDate":"2019-05-29T09:35:51","indexId":"70200726","displayToPublicDate":"2018-10-23T09:59:35","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Integrating encounter theory with decision analysis to evaluate collision risk and determine optimal protection zones for wildlife","docAbstract":"1.Better understanding human‐wildlife interactions and their links with management can help improve the design of wildlife protection zones. One example is the problem of wildlife collisions with vehicles or human‐built structures (e.g. power lines, wind farms). In fact, collisions between marine wildlife and watercraft are among the major threats faced by several endangered species of marine mammals. Natural resource managers are therefore interested in finding cost‐effective solutions to mitigate these threats.
2.We combined abundance estimators with encounter rate theory to estimate relative lethal collision risk of the Florida manatee (Trichechus manatus latirostris) from watercraft. We first modeled seasonal abundance of watercraft and manatees using a Bayesian analysis of aerial survey count data. We then modeled relative lethal collision risk in space and across seasons. Finally, we applied decision analysis and Linear Integer Programming to determine the optimal design of speed zones in terms of relative risk to manatees and costs to waterway users. We used a Pareto efficient frontier approach to evaluate the performance of alternative zones, which included additional practical considerations (e.g. spatial aggregation of speed zones) in relation to the optimal zone configurations.
3.Under the various relationships for probability of death given strike speed that we considered, the current speed zones reduced the relative lethal collision risk by an average of 51.5% to 70% compared to the scenario in which all speed regulations were removed (i.e. the no‐protection scenario). We identified optimal zones and near‐optimal zones with additional management considerations that improved upon the current zones in terms of cost or relative risk.
4.Policy Implications: Our analytical framework combines encounter rate theory and decision analysis to quantify the effectiveness of speed zones protecting manatees while accounting for uncertainty. Our approach can be used to optimize the design of protection zones intended to reduce conflicts between human waterborne activity and marine mammals. This framework could be extended to address many other problems of human‐wildlife interactions, such as the optimal placement of wind farms to minimize collisions with wildlife or the optimal allocation of ranger effort to mitigate poaching threats.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13290","usgsCitation":"Udell, B., Martin, J., Fletcher, R., Bonneau, M., Edwards, H.H., Gowan, T., Hardy, S.K., Gurarie, E., Calleson, C., and Deutsch, C., 2018, Integrating encounter theory with decision analysis to evaluate collision risk and determine optimal protection zones for wildlife: Journal of Applied Ecology, v. 56, no. 5, p. 1050-1062, https://doi.org/10.1111/1365-2664.13290.","productDescription":"13 p.","startPage":"1050","endPage":"1062","ipdsId":"IP-084422","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":460829,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13290","text":"Publisher Index Page"},{"id":358933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-20","publicationStatus":"PW","scienceBaseUri":"5bee93e4e4b08f163c24a1b9","contributors":{"authors":[{"text":"Udell, B.J.","contributorId":210251,"corporation":false,"usgs":false,"family":"Udell","given":"B.J.","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":750250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Julien 0000-0002-7375-129X julienmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":5785,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","email":"julienmartin@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":750249,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fletcher, R.J.","contributorId":210252,"corporation":false,"usgs":false,"family":"Fletcher","given":"R.J.","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":750251,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonneau, Mathieu","contributorId":150041,"corporation":false,"usgs":false,"family":"Bonneau","given":"Mathieu","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":750252,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edwards, Holly H.","contributorId":66419,"corporation":false,"usgs":true,"family":"Edwards","given":"Holly","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":751323,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gowan, T.","contributorId":210253,"corporation":false,"usgs":false,"family":"Gowan","given":"T.","email":"","affiliations":[{"id":35758,"text":"FWC","active":true,"usgs":false}],"preferred":false,"id":750254,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hardy, Stacie K.","contributorId":210254,"corporation":false,"usgs":false,"family":"Hardy","given":"Stacie","email":"","middleInitial":"K.","affiliations":[{"id":35758,"text":"FWC","active":true,"usgs":false}],"preferred":false,"id":750255,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gurarie, E.","contributorId":210255,"corporation":false,"usgs":false,"family":"Gurarie","given":"E.","affiliations":[{"id":38092,"text":"UMD","active":true,"usgs":false}],"preferred":false,"id":750256,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Calleson, C.S.","contributorId":210257,"corporation":false,"usgs":false,"family":"Calleson","given":"C.S.","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":750258,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Deutsch, C.J.","contributorId":210256,"corporation":false,"usgs":false,"family":"Deutsch","given":"C.J.","email":"","affiliations":[{"id":35758,"text":"FWC","active":true,"usgs":false}],"preferred":false,"id":750257,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70200492,"text":"70200492 - 2018 - Detecting snow depth change in avalanche path starting zones using uninhabited aerial systems and structure from motion photogrammetry","interactions":[],"lastModifiedDate":"2018-10-23T15:17:46","indexId":"70200492","displayToPublicDate":"2018-10-22T15:17:31","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Detecting snow depth change in avalanche path starting zones using uninhabited aerial systems and structure from motion photogrammetry","docAbstract":"Understanding snow depth distribution and change is useful for avalanche forecasting and mitigation, runoff forecasting, and infrastructure planning. Advances in remote sensing are improving the ability to collect snow depth measurements. The development of structure from motion (SfM), a photogrammetry technique, combined with the use of uninhabited aerial systems (UASs) allows for high resolution mapping of snow depth over complex terrain. The primary objective of this study was to determine the feasibility and efficacy of SfM to examine snow depth distribution and variability in complex terrain such as avalanche path starting zones at multiple times during the season. We used a 3DR Solo quadcopter UAS equipped with a Ricoh GR II camera at 90 m above ground level to acquire images of one avalanche starting zone in northwest Montana, USA. We also placed 4 to 13 ground control points (GCPs) around the area of interest to avoid traveling in steep, avalanche terrain. Ground control measurements resulted in 5 to10 cm horizontal accuracy and 5 to 15 cm vertical accuracy for 90 to 95 % of the collected points (a minimum of 100 points collected at each GCP). In-situ measurements of snow depth difference between sampling days ranged from 20 to 60 cm. We processed the images to create point clouds and digital surface models (DSMs). The resolution of the resultant DSMs was approximately 5 cm. Preliminary DSM and point cloud differencing efforts suggest relative change detection of snow depth at 5 to 15 cm resolution. The use of these relatively low cost and easily accessible methods of snow depth data collection will enhance accuracy of snow depth change estimates in starting zones and can be used to inform avalanche forecasting and mitigation efforts.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the International Snow Science Workshop","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"International Snow Science Workshop","conferenceLocation":"Innsbruck, Austria","language":"English","usgsCitation":"Peitzsch, E.H., Fagre, D.B., Hendrikx, J., and Birkeland, K.W., 2018, Detecting snow depth change in avalanche path starting zones using uninhabited aerial systems and structure from motion photogrammetry, in Proceedings of the International Snow Science Workshop, Innsbruck, Austria, p. 408-412.","productDescription":"5 p.","startPage":"408","endPage":"412","ipdsId":"IP-100777","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":358692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":358592,"type":{"id":11,"text":"Document"},"url":"https://arc.lib.montana.edu/snow-science/objects/ISSW2018_P04.16.pdf"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a919e4b034bf6a7e4f9f","contributors":{"authors":[{"text":"Peitzsch, Erich H. 0000-0001-7624-0455 epeitzsch@usgs.gov","orcid":"https://orcid.org/0000-0001-7624-0455","contributorId":3786,"corporation":false,"usgs":true,"family":"Peitzsch","given":"Erich","email":"epeitzsch@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":749149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":749150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hendrikx, Jordy","contributorId":166967,"corporation":false,"usgs":false,"family":"Hendrikx","given":"Jordy","affiliations":[{"id":13628,"text":"Department of Earth Sciences, P.O. Box 173480, Montana State University, Bozeman, MT, USA. 59717.","active":true,"usgs":false}],"preferred":false,"id":749151,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birkeland, Karl W.","contributorId":209943,"corporation":false,"usgs":false,"family":"Birkeland","given":"Karl","email":"","middleInitial":"W.","affiliations":[{"id":38033,"text":"U.S.D.A. Forest Service National Avalanche Center, Bozeman, Montana, USA","active":true,"usgs":false}],"preferred":false,"id":749152,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200777,"text":"70200777 - 2018 - Integrative taxonomy resolves taxonomic uncertainty for freshwater mussels being considered for protection under the U.S. Endangered Species Act","interactions":[],"lastModifiedDate":"2019-09-04T14:58:47","indexId":"70200777","displayToPublicDate":"2018-10-22T14:26:29","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Integrative taxonomy resolves taxonomic uncertainty for freshwater mussels being considered for protection under the U.S. Endangered Species Act","docAbstract":"Objectively delimiting species boundaries remains an important challenge in systematics and becomes urgent when unresolved taxonomy complicates conservation and recovery efforts. We examined species boundaries in the imperiled freshwater mussel genus Cyclonaias(Bivalvia: Unionidae) using morphometrics, molecular phylogenetics, and multispecies coalescent models to help guide pending conservation assessments and legislative decisions. Congruence across multiple lines of evidence indicated that current taxonomy overestimates diversity in the C. pustulosa species complex. The only genetically and morphologically diagnosable species in the C. pustulosa species complex were C. pustulosa and C. succissa and we consider C. aurea, C. houstonensis, C. mortoni, and C. refulgens to be synonyms of C. pustulosa. In contrast, all three species in the C. nodulata complex (C. necki, C. nodulata, and C. petrina) were genetically, geographically, and morphologically diagnosable. Our findings have important conservation and management implications, as three nominal species (C. aurea, C. houstonensis, and C. petrina) are being considered for protection under the Endangered Species Act.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-018-33806-z","usgsCitation":"Johnson, N.A., Smith, C., Pfeiffer, J., Randklev, C., Williams, J.D., and Austin, J.D., 2018, Integrative taxonomy resolves taxonomic uncertainty for freshwater mussels being considered for protection under the U.S. Endangered Species Act: Scientific Reports, v. 8, p. 1-16, https://doi.org/10.1038/s41598-018-33806-z.","productDescription":"15892; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-096998","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468300,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-33806-z","text":"Publisher Index Page"},{"id":437713,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SRSHV2","text":"USGS data release","linkHelpText":"Molecular and morphological data on two species complexes in the freshwater mussel genus Cyclonaias"},{"id":359047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-26","publicationStatus":"PW","scienceBaseUri":"5c10a919e4b034bf6a7e4fa2","contributors":{"authors":[{"text":"Johnson, Nathan A. 0000-0001-5167-1988 najohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":4175,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","email":"najohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":750464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Chase H. 0000-0002-1499-0311","orcid":"https://orcid.org/0000-0002-1499-0311","contributorId":206797,"corporation":false,"usgs":true,"family":"Smith","given":"Chase H.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":13716,"text":"Baylor University","active":true,"usgs":false}],"preferred":true,"id":750465,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pfeiffer, John M.","contributorId":202521,"corporation":false,"usgs":false,"family":"Pfeiffer","given":"John M.","affiliations":[{"id":36469,"text":"Florida Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":750466,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Randklev, Chalres R.","contributorId":210322,"corporation":false,"usgs":false,"family":"Randklev","given":"Chalres R.","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":750467,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williams, James D.","contributorId":17690,"corporation":false,"usgs":false,"family":"Williams","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":750468,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Austin, James D.","contributorId":206799,"corporation":false,"usgs":false,"family":"Austin","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":750469,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70200174,"text":"sir20185140 - 2018 - 2018 update to the U.S. Geological Survey national volcanic threat assessment","interactions":[],"lastModifiedDate":"2018-10-23T10:56:27","indexId":"sir20185140","displayToPublicDate":"2018-10-22T13:54:23","publicationYear":"2018","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":"2018-5140","title":"2018 update to the U.S. Geological Survey national volcanic threat assessment","docAbstract":"When erupting, all volcanoes pose a degree of risk to people and infrastructure, however, the risks are not equivalent from one volcano to another because of differences in eruptive style and geographic location. Assessing the relative threats posed by U.S. volcanoes identifies which volcanoes warrant the greatest risk-mitigation efforts by the U.S. Geological Survey and its partners. This update of the volcano threat assessment of Ewert and others (2005) considers new research in order to determine which volcanic systems should be added or removed from the list of potentially active volcanoes, updates the scoring of active volcanoes, and updates the 24-factor hazard and exposure matrix used to create the threat ranking. The threat assessment places volcanoes into five threat categories: very low, low, moderate, high, and very high. Within all five threat categories there are changes in relative rankings of volcanoes, and in a few cases, volcanoes moved between categories owing to changes in our understanding of their hazard, unrest, and exposure factors. Scorings of hazard factors were updated for some volcanoes where new research has identified Holocene eruptive activity or clarified our understanding of Holocene eruptive history and the occurrence of particular hazards such as tephra fall or pyroclastic density currents. The most numerous scoring changes made in the threat matrix since 2005 have been made among the hazard factors, particularly those accounting for observed eruptive activity or unrest.
The very low threat category underwent the greatest amount of change, dropping from 32 to 21 volcanoes, owing to better knowledge of the eruptive histories of those volcanoes. The list of 18 very high threat volcanoes determined by Ewert and others (2005) remains the same; 11 of the 18 volcanoes are located in Washington, Oregon, or California, where explosive and often snow- and ice-covered edifices can project hazards long distances to densely populated and highly developed areas. Five of the 18 very high threat volcanoes are in Alaska near important population centers, economic infrastructure, or below busy air traffic corridors. The remaining two very high threat volcanoes are on the Island of Hawaiʻi, where densely populated and highly developed areas now exist on the flanks of highly active volcanoes. The high- and moderate-threat categories are dominated by Alaskan volcanoes. In these categories the generally more active and more explosive volcanoes in Alaska can have a substantial effect on national and international aviation, and large eruptions from any of the moderate- to very-high-threat volcanoes could cause regional or national-scale disasters. This revised threat assessment includes 18 very high threat, 39 high threat, 49 moderate threat, 34 low threat, and 21 very low threat volcanoes. The total of 161 volcanoes is a decrease of 8 from the total reported by Ewert and others (2005).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185140","usgsCitation":"Ewert, J.W., Diefenbach, A.K., and Ramsey, D.W., 2018, 2018 update to the U.S. Geological Survey national volcanic threat assessment: U.S. Geological Survey Scientific Investigations Report 2018–5140, 40 p., https://doi.org/10.3133/ sir20185140.","productDescription":"Report: v, 40 p.; Appendix","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-096246","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":358575,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5140/sir20185140_appendix.xlsx","text":"Appendix","size":"123 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2018–5140 Appendix","linkHelpText":"U.S. Volcanic Threat Score Sheet"},{"id":358573,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5140/coverthb.jpg"},{"id":358574,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5140/sir20185140.pdf","text":"Report","size":"24.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5140"}],"country":"United States","contact":"Contact Information,
Volcano Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, AK 99508
Data collected from April 2014 through September 2016 were used to assess geomorphic characteristics and geomorphic changes over time in a selected reach of Tenmile Creek, a small rural watershed near Clarksburg, Maryland. Longitudinal profiles of the channel bed, water surface, and bank features were developed from field surveys. Changes in cross-section geometry between field surveys were documented. Grain-size distributions for the channel bed were developed from pebble counts. Continuous-record streamflow and precipitation data were also collected in the Tenmile Creek watershed and used to supplement the geomorphic analyses.
The Rosgen system of stream classification was used to classify the stream channel according to morphological measurements of slope, entrenchment ratio, width-to-depth ratio, sinuosity, and median particle diameter of the channel materials. Boundary shear stress near the U.S. Geological Survey (USGS) streamflow-gaging station was assessed by using hydraulic variables computed from the cross-section surveys and slope measurements derived from crest-stage gages and temporary data loggers installed along the study reach.
Analysis of the longitudinal profiles indicated relatively small changes in the percentage and distribution of riffles, pools, and runs in the study reach between April 2014 and March 2015. More noticeable changes were observed during surveys conducted in March 2016 and September 2016. The channel-bed slope showed a net reduction over time from 0.0072 to 0.0040 feet per foot (ft/ft). The low-flow water-surface slope also showed a net reduction over time from 0.0065 to 0.0045 ft/ft. Net aggradation in the lower section of the study reach combined with net degradation in the upper section of the study reach contributed to the net reduction in channel-bed and water-surface slope. The large storm and resulting flood on July 30, 2016 was a major factor in observed changes in the longitudinal profiles between the March 2016 and September 2016 surveys.
Comparison of data from the cross-sectional surveys indicated vertical changes in all cross sections, with more extreme changes observed between surveys in the lower section of the study reach due in part to alternating periods of net storage and transport of sand. Lateral erosion was not a major factor in the study reach, with the exception of cross section Dd, where considerable lateral erosion was documented during the study period. The flood that resulted from the large storm on July 30, 2016 was a major factor in some of the vertical changes observed in the channel bed of the study reach cross sections.
Particle-size analyses of the channel bed from pebble counts indicated median particle diameters ranging from 15.5 millimeters (mm) to 23.1 mm, which is characterized as medium to coarse gravel. Sand percentages ranging from 3.4 percent to 16.4 percent of the total counts were observed over time. Net increases in storage of fine sediment in the reach were observed between April 2014 and March 2016, and a considerable reduction in storage was observed between March 2016 and September 2016.
The Tenmile Creek stream channel was classified as a C4 channel, based on morphological descriptions from the Rosgen system of stream classification. The C4 classification describes a single-thread channel with a slight entrenchment ratio; a moderate to high width-to-depth ratio; moderate to high sinuosity; a water-surface slope of less than 2 percent; and a median particle diameter in the gravel range of 2 to 64 mm.
The analysis of boundary shear stress indicated a range of 0.35 to 1.18 pounds per square foot for instantaneous streamflow ranging from 79 to 2,860 cubic feet per second during the study period. The relation between discharge and boundary shear stress for Tenmile Creek was compared to similar relations that were previously developed for Minebank Run, a small, urban watershed in the eastern section of the Piedmont Physiographic Province in Baltimore County, Md. that was physically restored during 2004–05. The comparison indicated a much flatter slope in the relation for Minebank Run in both its unrestored and restored conditions. This difference in the relations indicates that the erosive power in the urban watershed of Minebank Run is much more sensitive to increases in discharge magnitude than in the non-urban watershed of Tenmile Creek.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185098","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency and the Montgomery County Department of Environmental Protection","usgsCitation":"Doheny, E.J., and Baker, S.M., 2018, Geomorphic characteristics of Tenmile Creek, Montgomery County, Maryland, 2014–16: U.S. Geological Survey Scientific Investigations Report 2018–5098, 34 p., https://doi.org/10.3133/sir20185098.","productDescription":"Report: viii, 34 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-090630","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":437714,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WW7GKQ","text":"USGS data release","linkHelpText":"Datasets from an assessment of geomorphic characteristics of Tenmile Creek, Montgomery County, Maryland, 2014-16"},{"id":358408,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5098/coverthb.jpg"},{"id":358410,"rank":3,"type":{"id":30,"text":"Data Release"},"url":" https://doi.org/10.5066/F7WW7GKQ","text":"USGS data release","description":"USGS data release","linkHelpText":"Datasets from an assessment of geomorphic characteristics of Tenmile Creek, Montgomery County, Maryland, 2014–16"},{"id":358409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5098/sir20185098.pdf","text":"Report","size":"17.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5098"}],"country":"United States","state":"Maryland","county":"Montgomery County","otherGeospatial":"Tenmile Creek watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.3356,\n 39.2075\n ],\n [\n -77.2786,\n 39.2075\n ],\n [\n -77.2786,\n 39.2492\n ],\n [\n -77.3356,\n 39.2492\n ],\n [\n -77.3356,\n 39.2075\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
An earthquake early warning (EEW) system, ShakeAlert, is under development for the West Coast of the United States. This system currently uses the first few seconds of waveforms recorded by seismic instrumentation to rapidly characterize earthquake magnitude, location, and origin time; ShakeAlert recently added a seismic line source algorithm. For large to great earthquakes, magnitudes estimated from the earliest seismic data alone generally saturate. Real‐time Global Navigation Satellite System (GNSS) data can directly measure large displacements, enabling accurate magnitude estimates for
Trough ponds are ubiquitous features of Arctic landscapes and an important component of freshwater aquatic ecosystems. Permafrost thaw causes ground subsidence, creating depressions that gather water, creating ponds. Permafrost thaw also releases solutes and nutrients, which may fertilize these newly formed ponds. We measured water budget elements and chloride, ammonium, and dissolved organic nitrogen (DON) across a chronosequence of trough ponds representing different stages of ice wedge degradation and stabilization. We developed a coupled hydrologic and biogeochemical model to explore how ice wedge degradation affects hydrology and nutrient availability in trough ponds in the advanced degradation stages (DAs), which are characterized by deep troughs with warmer temperatures relative to the other stages. DAs experienced greater evaporation than the other stages, and subsurface inflows entered the DAs from a wide area. Chloride accumulated in the ponds with time since thaw, implying that subsurface fluxes are delivering solutes from the thawing permafrost. Ammonium accumulated at high rates in the initial degradation stage and was seasonally depleted over the summer in all degradation stages. Ammonium trends in the DAs were consistent with high concentration inflows and in‐pond assimilation at rates between 0.37 and 2.0 mg N m−2 day−1. Seasonal DON trends indicated that the accumulation of recalcitrant organic matter may eventually limit aquatic ecosystem production and foster pond infilling. These results provide direct evidence of nutrient release from thawing permafrost and the utilization of these nutrients by Arctic trough pond ecosystems and highlight infilling as a mechanism by which Arctic surface waters may be lost
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JG004528","usgsCitation":"Koch, J.C., Jorgenson, M., Wickland, K.P., Kanevskiy, M.Z., and Striegl, R.G., 2018, Ice wedge degradation and stabilization impacts water budgets and nutrient cycling in Arctic trough ponds: Journal of Geophysical Research: Biogeosciences, v. 123, no. 8, p. 2604-2616, https://doi.org/10.1029/2018JG004528.","productDescription":"13 p.","startPage":"2604","endPage":"2616","ipdsId":"IP-092115","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":468302,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jg004528","text":"Publisher Index Page"},{"id":358587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"8","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-29","publicationStatus":"PW","scienceBaseUri":"5c10a91ae4b034bf6a7e4fb8","contributors":{"authors":[{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":749081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jorgenson, M. Torre","contributorId":140457,"corporation":false,"usgs":false,"family":"Jorgenson","given":"M. Torre","affiliations":[{"id":13506,"text":"Alaska Ecoscience","active":true,"usgs":false}],"preferred":false,"id":749082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wickland, Kimberly P. 0000-0002-6400-0590 kpwick@usgs.gov","orcid":"https://orcid.org/0000-0002-6400-0590","contributorId":1835,"corporation":false,"usgs":true,"family":"Wickland","given":"Kimberly","email":"kpwick@usgs.gov","middleInitial":"P.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":749083,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kanevskiy, Mikhail Z.","contributorId":199153,"corporation":false,"usgs":false,"family":"Kanevskiy","given":"Mikhail","email":"","middleInitial":"Z.","affiliations":[],"preferred":false,"id":749084,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":false,"id":749085,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200486,"text":"70200486 - 2018 - Comparison of estimators for monitoring long-term population trends in deer mice, Peromyscus maniculatus, on the California Channel Islands","interactions":[],"lastModifiedDate":"2020-12-16T16:26:33.484207","indexId":"70200486","displayToPublicDate":"2018-10-20T12:45:41","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Comparison of estimators for monitoring long-term population trends in deer mice, Peromyscus maniculatus, on the California Channel Islands","title":"Comparison of estimators for monitoring long-term population trends in deer mice, Peromyscus maniculatus, on the California Channel Islands","docAbstract":"Capture-recapture methods are commonly used to estimate abundance and density of wild animal populations. Although a variety of sophisticated analytical techniques are available to evaluate capture-recapture data, vertebrate monitoring programs often lack the resources (e.g., time, personnel, and/or analytical expertise) to apply these methods. As an alternative, simple population indices, such as counts of unique individuals, may provide sufficient information to detect meaningful changes in population size. In this study we investigated whether a population index, easily generated from mark-recapture data under all conditions, might be used to provide valid ecological information for managers interested in long-term population trends of deer mice (Peromyscus maniculatus) on the California Channel Islands. In practice, determining the efficacy of estimating abundance from mark-recapture data and indices using empirical data (as opposed to simulated data) is difficult given the scarcity of long-term data sets that describe real populations. Using mark-recapture data that span 18 years (n = 122 trapping events, >12,000 marked individuals) for deer mice on 2 of the islands, we compared density estimates obtained from several commonly used mark-recapture models and also compared these estimates to index counts. Populations of island deer mice are extremely dynamic; estimated densities over the data period varied from 0 to >1200 mice/ha. Density estimates from models in program CAPTURE and program DENSITY, as well as from model-averaged Huggins models, were strongly correlated with each other and with the density index. Densities calculated by the models and the index showed similar patterns of population variation and trend over time for all 5 sites. For long-term population monitoring and assessment of population trends in deer mice, our findings suggest that the use of a simple index may provide adequate understanding of ecologically relevant population changes, though data collection methods that allow for more detailed analyses using advanced modeling techniques should be maintained.
","language":"English","publisher":"Monte L. Bean Life Science Museum, Brigham Young University","doi":"10.3398/064.078.0301","usgsCitation":"Schwemm, C.A., Drost, C.A., Orrock, J.L., Coonan, T.J., and Stanley, T.R., 2018, Comparison of estimators for monitoring long-term population trends in deer mice, Peromyscus maniculatus, on the California Channel Islands: Western North American Naturalist, v. 78, no. 3, p. 496-509, https://doi.org/10.3398/064.078.0301.","productDescription":"14 p.","startPage":"496","endPage":"509","ipdsId":"IP-076415","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":358583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Channel Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.56396484375,\n 34.161818161230386\n ],\n [\n -120.73974609374999,\n 33.95247360616282\n ],\n [\n -120.56396484375,\n 33.669496972795535\n ],\n [\n -119.86083984375,\n 33.4955977448657\n ],\n [\n -119.72900390625001,\n 33.109948297894285\n ],\n [\n -119.124755859375,\n 32.80574473290688\n ],\n [\n -118.41064453125,\n 32.55607364492026\n ],\n [\n -117.92724609375,\n 32.7503226078097\n ],\n [\n -117.92724609375,\n 33.08233672856376\n ],\n [\n -118.2568359375,\n 33.54139466898275\n ],\n [\n -118.93798828125,\n 33.669496972795535\n ],\n [\n -119.20166015625,\n 34.06176136129718\n ],\n [\n -119.81689453125,\n 34.21634468843463\n ],\n [\n -120.56396484375,\n 34.161818161230386\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a91be4b034bf6a7e4fc3","contributors":{"authors":[{"text":"Schwemm, Catherin A.","contributorId":209929,"corporation":false,"usgs":false,"family":"Schwemm","given":"Catherin","email":"","middleInitial":"A.","affiliations":[{"id":38029,"text":"Institute for Wildlife Studies, PO Box 1104, Arcata, CA 95518; schwemm@iws.org","active":true,"usgs":false}],"preferred":false,"id":749111,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drost, Charles A. 0000-0002-4792-7095 charles_drost@usgs.gov","orcid":"https://orcid.org/0000-0002-4792-7095","contributorId":3151,"corporation":false,"usgs":true,"family":"Drost","given":"Charles","email":"charles_drost@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":749109,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orrock, John L.","contributorId":209931,"corporation":false,"usgs":false,"family":"Orrock","given":"John","email":"","middleInitial":"L.","affiliations":[{"id":38031,"text":"Department of Zoology, University of Wisconsin, Madison, WI 53706; jorrock@wisc.edu","active":true,"usgs":false}],"preferred":false,"id":749113,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coonan, Timothy J.","contributorId":209930,"corporation":false,"usgs":false,"family":"Coonan","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":38030,"text":"National Park Service, Channel Islands National Park, Ventura, CA (retired); timcoonan81@gmail.com","active":true,"usgs":false}],"preferred":false,"id":749112,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stanley, Thomas R. 0000-0002-8393-0005 stanleyt@usgs.gov","orcid":"https://orcid.org/0000-0002-8393-0005","contributorId":209928,"corporation":false,"usgs":true,"family":"Stanley","given":"Thomas","email":"stanleyt@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":749110,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70265019,"text":"70265019 - 2018 - Zooplankton dynamics in the Cache Slough complex of the upper San Francisco Estuary","interactions":[],"lastModifiedDate":"2025-03-28T14:20:31.155907","indexId":"70265019","displayToPublicDate":"2018-10-19T09:17:28","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Zooplankton dynamics in the Cache Slough complex of the upper San Francisco Estuary","docAbstract":"We studied abundance and dynamics of zooplankton in the tidal freshwater Cache Slough Complex (CSC) in the northern Delta of the San Francisco Estuary during June, July, and October 2015. We asked whether the CSC was an area of high zooplankton production that could act as a source region for open waters of the estuary. Abundance of the copepod Pseudodiaptomus forbesi was similar to that in freshwater reaches of the central and eastern Delta and higher than that in the adjacent Sacramento River. Growth rate of P. forbesi was higher than previously measured in large estuarine channels because of higher temperature and phytoplankton biomass in the CSC. Samples of P. forbesi examined with molecular techniques contained an unexpectedly high proportion of DNA from cyanobacteria and little DNA from more nutritious phytoplankton. We also examined tidal exchanges of phytoplankton biomass and copepods between Liberty Island, a shallow tidal lake within the CSC, and the adjacent southern Cache Slough, which links the CSC to the Sacramento River. We calculated zero net flux of phytoplankton over 127 days between June and October. The tidal flux of copepods, calculated using tidal flow from an in situ flow station and half-hourly sampling over three 24.8-hr tidal cycles, varied a great deal because of temporal patchiness and day/night variation in abundance. Overall, the tidal flux was indistinguishable from zero, while the tidally-averaged water flow (and therefore the net copepod flux) was always into the wetland. Our results show some promise for the CSC as a productive habitat for planktivorous fishes and as a laboratory for learning how to design future wetland restoration. However, we remain cautious about whether wetlands such as the CSC may export large quantities of food organisms that can support fishes in other regions of the estuary.
","language":"English","publisher":"University of California at Davis (eScholarship)","doi":"10.15447/sfews.2018v16iss3art4","usgsCitation":"Kimmerer, W., Ignoffo, T., Bemowski, B., Moderan, J., Holmes, A.E., and Bergamaschi, B.A., 2018, Zooplankton dynamics in the Cache Slough complex of the upper San Francisco Estuary: San Francisco Estuary and Watershed Science, v. 16, no. 3, 4, 25 p., https://doi.org/10.15447/sfews.2018v16iss3art4.","productDescription":"4, 25 p.","ipdsId":"IP-099213","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":488730,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2018v16iss3art4","text":"Publisher Index Page"},{"id":483988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"3","noUsgsAuthors":false,"publicationDate":"2018-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Kimmerer, Wim","contributorId":349907,"corporation":false,"usgs":false,"family":"Kimmerer","given":"Wim","affiliations":[{"id":83531,"text":"Estuary & Ocean Science Center, San Francisco State University, Tiburon, CA, USA","active":true,"usgs":false}],"preferred":false,"id":932322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ignoffo, Toni R.","contributorId":352890,"corporation":false,"usgs":false,"family":"Ignoffo","given":"Toni R.","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":932323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bemowski, Brooke","contributorId":352891,"corporation":false,"usgs":false,"family":"Bemowski","given":"Brooke","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":932324,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moderan, Julien","contributorId":352892,"corporation":false,"usgs":false,"family":"Moderan","given":"Julien","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":932325,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holmes, Ann E.","contributorId":293911,"corporation":false,"usgs":false,"family":"Holmes","given":"Ann","email":"","middleInitial":"E.","affiliations":[{"id":63551,"text":"Department of Animal Science, University of California Davis, Davis, CA","active":true,"usgs":false}],"preferred":false,"id":932326,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932327,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70200452,"text":"70200452 - 2018 - Drought and fire in the western USA: Is climate attribution enough?","interactions":[],"lastModifiedDate":"2018-11-14T08:52:14","indexId":"70200452","displayToPublicDate":"2018-10-18T13:54:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5763,"text":"Current Climate Change Reports","active":true,"publicationSubtype":{"id":10}},"title":"Drought and fire in the western USA: Is climate attribution enough?","docAbstract":"Purpose of Review
I sought to review the contributions of recent literature and prior foundational papers to our understanding of drought and fire. In this review, I summarize recent literature on drought and fire in the western USA and discuss research directions that may increase the utility of that body of work for twenty-first century application. I then describe gaps in the synthetic knowledge of drought-driven fire in managed ecosystems and use concepts from use-inspired research to describe potentially useful extensions of current work.
Recent Findings
Fire responses to climate, and specifically various kinds of drought, are clear, but vary widely with fuel responses to surplus water and drought at different timescales. Ecological and physical factors interact with human management and ignitions to create fire regime and landscape trajectories that challenge prediction.
Summary
The mechanisms by which the climate system affects regional droughts and how they translate to fire in the western USA need more attention to accelerate both forecasting and adaptation. However, projections of future fire activity under climate change will require integrated advances on both fronts to achieve decision-relevant modeling. Concepts from transdisciplinary research and coupled human-natural systems can help frame strategic work to address fire in a changing world.
Domesticated Australian and Timor zebra finches (Taeniopygia guttata castanotis, and T. guttata guttata, respectively) were inoculated with canary (Serinus canaria) blood containing a Hawaiian isolate of Plasmodium relictum (lineage GRW04), a hemoparasite that causes avian malaria. In two experimental trials, Timor, but not Australian zebra finches developed parasitemia that was detected by microscopic examination of blood smears. In the second trial, in which molecular detection methods were used, a single Australian zebra finch and 5 of 6 challenged Timor birds were positive for the parasite. Additionally, P. relictum DNA was detected in multiple blood samples obtained from Timor birds over the 28 days following challenge. Timor zebra finches may provide a useful, easily maintained, laboratory model for the study of arbovirus/Plasmodium interactions in passerines, but are still inferior to canaries, the traditionally used model of avian malaria infection, in terms of supporting high parasitemia infections.
","language":"English","publisher":"American Association of Avian Pathologists","doi":"10.1637/11823-030518-ResNote.1","usgsCitation":"Hofmeister, E.K., Balakrishnan, C.N., and Atkinson, C.T., 2018, Population differences in susceptibility to Plasmodium relictum in zebra finches Taeniopygia guttata: Avian Diseases, v. 62, no. 4, p. 351-355, https://doi.org/10.1637/11823-030518-ResNote.1.","productDescription":"5 p.","startPage":"351","endPage":"355","ipdsId":"IP-099053","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":357437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f9de4b0fc368eb538fb","contributors":{"authors":[{"text":"Hofmeister, Erik K. 0000-0002-6360-3912 ehofmeister@usgs.gov","orcid":"https://orcid.org/0000-0002-6360-3912","contributorId":3230,"corporation":false,"usgs":true,"family":"Hofmeister","given":"Erik","email":"ehofmeister@usgs.gov","middleInitial":"K.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":745368,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Balakrishnan, Christopher N.","contributorId":177924,"corporation":false,"usgs":false,"family":"Balakrishnan","given":"Christopher","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":745369,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atkinson, Carter T. 0000-0002-4232-5335 catkinson@usgs.gov","orcid":"https://orcid.org/0000-0002-4232-5335","contributorId":1124,"corporation":false,"usgs":true,"family":"Atkinson","given":"Carter","email":"catkinson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":745370,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200456,"text":"70200456 - 2018 - Downscaling of climate model output for Alaskan stakeholders","interactions":[],"lastModifiedDate":"2018-12-05T14:11:06","indexId":"70200456","displayToPublicDate":"2018-10-18T12:51:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Downscaling of climate model output for Alaskan stakeholders","docAbstract":"The paper summarizes an end-to-end activity connecting the global climate modeling enterprise with users of climate information in Alaska. The effort included retrieval of the requisite observational datasets and model output, a model evaluation and selection procedure, the actual downscaling by the delta method with its inherent bias-adjustment, and the provision of products to a range of users through visualization software that empowers users to explore the downscaled output and its sensitivities. An additional software tool enables users to examine skill metrics and relative rankings of 21 global models for Alaska and six other domains in the Northern Hemisphere. The downscaled temperatures and precipitation are made available as calendar-month decadal means under three different greenhouse forcing scenarios through 2100 for more than 4000 communities in Alaska and western Canada. The visualization package displays the uncertainties inherent in the multi-model ensemble projections. These uncertainties are often larger than the projected changes.
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A.","contributorId":209874,"corporation":false,"usgs":false,"family":"Kurkowski","given":"Thomas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":749002,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bieniek, Peter A.","contributorId":209850,"corporation":false,"usgs":false,"family":"Bieniek","given":"Peter A.","affiliations":[{"id":38014,"text":"Alaska Climate Science Center, University of Alaska, Fairbanks, AK","active":true,"usgs":false}],"preferred":false,"id":748956,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thoman, Richard","contributorId":187613,"corporation":false,"usgs":false,"family":"Thoman","given":"Richard","affiliations":[],"preferred":false,"id":748957,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gray, Stephen T. 0000-0002-0959-3418 sgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0959-3418","contributorId":209851,"corporation":false,"usgs":true,"family":"Gray","given":"Stephen","email":"sgray@usgs.gov","middleInitial":"T.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":748958,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rupp, T. Scott","contributorId":195180,"corporation":false,"usgs":false,"family":"Rupp","given":"T.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":749003,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70201200,"text":"70201200 - 2018 - Mapping crop residue and tillage intensity using WorldView-3 satellite shortwave infrared residue indices","interactions":[],"lastModifiedDate":"2018-12-06T11:24:25","indexId":"70201200","displayToPublicDate":"2018-10-18T11:24:19","publicationYear":"2018","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":"Mapping crop residue and tillage intensity using WorldView-3 satellite shortwave infrared residue indices","docAbstract":"Crop residues serve many important functions in agricultural conservation including preserving soil moisture, building soil organic carbon, and preventing erosion. Percent crop residue cover on a field surface reflects the outcome of tillage intensity and crop management practices. Previous studies using proximal hyperspectral remote sensing have demonstrated accurate measurement of percent residue cover using residue indices that characterize cellulose and lignin absorption features found between 2100 nm and 2300 nm in the shortwave infrared (SWIR) region of the electromagnetic spectrum. The 2014 launch of the WorldView-3 (WV3) satellite has now provided a space-borne platform for the collection of narrow band SWIR reflectance imagery capable of measuring these cellulose and lignin absorption features. In this study, WorldView-3 SWIR imagery (14 May 2015) was acquired over farmland on the Eastern Shore of Chesapeake Bay (Maryland, USA), was converted to surface reflectance, and eight different SWIR reflectance indices were calculated. On-farm photographic sampling was used to measure percent residue cover at a total of 174 locations in 10 agricultural fields, ranging from plow-till to continuous no-till management, and these in situ measurements were used to develop percent residue cover prediction models from the SWIR indices using both polynomial and linear least squares regressions. Analysis was limited to agricultural fields with minimal green vegetation (Normalized Difference Vegetation Index < 0.3) due to expected interference of vegetation with the SWIR indices. In the resulting residue prediction models, spectrally narrow residue indices including the Shortwave Infrared Normalized Difference Residue Index (SINDRI) and the Lignin Cellulose Absorption Index (LCA) were determined to be more accurate than spectrally broad Landsat-compatible indices such as the Normalized Difference Tillage Index (NDTI), as determined by respective R2 values of 0.94, 0.92, and 0.84 and respective residual mean squared errors (RMSE) of 7.15, 8.40, and 12.00. Additionally, SINDRI and LCA were more resistant to interference from low levels of green vegetation. The model with the highest correlation (2nd order polynomial SINDRI, R2 = 0.94) was used to convert the SWIR imagery into a map of crop residue cover for non-vegetated agricultural fields throughout the imagery extent, describing the distribution of tillage intensity within the farm landscape. WorldView-3 satellite imagery provides spectrally narrow SWIR reflectance measurements that show utility for a robust mapping of crop residue cover.
","language":"English","publisher":"MDPI","doi":"10.3390/rs10101657","usgsCitation":"Hively, W.D., Lamb, B.T., Daughtry, C.S., Shermeyer, J., McCarty, G.W., and Quemada, M., 2018, Mapping crop residue and tillage intensity using WorldView-3 satellite shortwave infrared residue indices: Remote Sensing, v. 10, no. 10, p. 1-22, https://doi.org/10.3390/rs10101657.","productDescription":"Article 1657; 22 p.","startPage":"1","endPage":"22","ipdsId":"IP-090230","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":468309,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs10101657","text":"Publisher Index Page"},{"id":437715,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7930SDB","text":"USGS data release","linkHelpText":"WorldView-3 satellite imagery and crop residue field data collection, Talbot County, MD, May 2015"},{"id":359980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Choptank River watershed","volume":"10","issue":"10","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-18","publicationStatus":"PW","scienceBaseUri":"5c0a4357e4b0815414d28132","contributors":{"authors":[{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamb, Brian T.","contributorId":211092,"corporation":false,"usgs":false,"family":"Lamb","given":"Brian","email":"","middleInitial":"T.","affiliations":[{"id":38178,"text":"City College of New York","active":true,"usgs":false}],"preferred":false,"id":753191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daughtry, Craig S. T.","contributorId":211093,"corporation":false,"usgs":false,"family":"Daughtry","given":"Craig","email":"","middleInitial":"S. T.","affiliations":[{"id":38179,"text":"USDA Agricultural Research Service, Hydrology and Remote Sensing Laboratory","active":true,"usgs":false}],"preferred":false,"id":753192,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shermeyer, Jacob 0000-0002-8143-2790 jshermeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8143-2790","contributorId":211095,"corporation":false,"usgs":true,"family":"Shermeyer","given":"Jacob","email":"jshermeyer@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":753195,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCarty, Gregory W.","contributorId":192367,"corporation":false,"usgs":false,"family":"McCarty","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":753193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Quemada, Miguel","contributorId":211094,"corporation":false,"usgs":false,"family":"Quemada","given":"Miguel","email":"","affiliations":[{"id":38180,"text":"School of Agricultural Engineering and CEIGRAM, Technical University of Madrid","active":true,"usgs":false}],"preferred":false,"id":753194,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70215120,"text":"70215120 - 2018 - Growth and survival relationships of 71 tree species with nitrogen and sulfur deposition across the conterminous U.S.","interactions":[],"lastModifiedDate":"2020-10-08T14:22:55.777328","indexId":"70215120","displayToPublicDate":"2018-10-18T08:33:46","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Growth and survival relationships of 71 tree species with nitrogen and sulfur deposition across the conterminous U.S.","docAbstract":"Atmospheric deposition of nitrogen (N) influences forest demographics and carbon (C) uptake through multiple mechanisms that vary among tree species. Prior studies have estimated the effects of atmospheric N deposition on temperate forests by leveraging forest inventory measurements across regional gradients in deposition. However, in the United States (U.S.), these previous studies were limited in the number of species and the spatial scale of analysis, and did not include sulfur (S) deposition as a potential covariate. Here, we present a comprehensive analysis of how tree growth and survival for 71 species vary with N and S deposition across the conterminous U.S. Our analysis of 1,423,455 trees from forest plots inventoried between 2000 and 2016 reveals that the growth and/or survival of the vast majority of species in the analysis (n = 66, or 93%) were significantly affected by atmospheric deposition. Species co-occurred across the conterminous U.S. that had decreasing and increasing relationships between growth (or survival) and N deposition, with just over half of species responding negatively in either growth or survival to increased N deposition somewhere in their range (42 out of 71). Averaged across species and conterminous U.S., however, we found that an increase in deposition above current rates of N deposition would coincide with a small net increase in tree growth (1.7% per Δ kg N ha-1 yr-1), and a small net decrease in tree survival (-0.22% per Δ kg N ha-1 yr-1), with substantial regional and among-species variation. Adding S as a predictor improved the overall model performance for 70% of the species in the analysis. Our findings have potential to help inform ecosystem management and air pollution policy across the conterminous U.S., and suggest that N and S deposition have likely altered forest demographics in the U.S.
To improve the characterization of Holocene earthquakes on the Wasatch fault zone (WFZ), we conducted light detection and ranging (lidar)‐based neotectonic mapping and excavated a paleoseismic trench across an 8‐m‐high fault scarp near Alpine, Utah, located
Determining the spatial distribution of coastal foundation species is essential to accurately determine restoration goals, predict the ecological effects of climate change, and develop habitat management strategies. Mapping the distribution of submerged aquatic vegetation (SAV) species assemblages, which provide important habitat resource and ecological services in Louisiana, has been difficult due to the dynamic nature of SAV occurrence and the limited water clarity across much of the coast. Species distribution models (SDMs) link ecological conditions species occurrence across landscapes, and can predict the distribution of species across un-sampled or hard to sample areas and support the development of habitat maps. To predict SAV distribution in coastal Louisiana, a SDM was developed and projected across the landscape to create a spatial likelihood of occurrence (SLOO) model describing the probability of SAV presence in aquatic habitats. SAV presence and absence data were examined from over 500 field observations in relation to physical and hydrologic variables, including exposure, turbidity, water level, and salinity. A binary logistic regression model (p < 0.0001) identified three significant predictors of SAV presence: mean winter salinity, exposure, and turbidity. As each of these variables increased, the probability of SAV presence in the summer growing season decreased. The spatial application of this SDM helps to predict the likelihood of occurrence across the coastal landscape, creating a valuable tool to describe un-sampled SAV habitat and estimate future changes in habitat availability.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquabot.2018.08.007","usgsCitation":"DeMarco, K., Couvillion, B., Brown, S., and La Peyre, M., 2018, Submerged aquatic vegetation mapping in coastal Louisiana through development of a spatial likelihood occurrence (SLOO) model: Aquatic Botany, v. 151, p. 87-97, https://doi.org/10.1016/j.aquabot.2018.08.007.","productDescription":"11 p.","startPage":"87","endPage":"97","ipdsId":"IP-094080","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468312,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aquabot.2018.08.007","text":"Publisher Index Page"},{"id":358506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94,\n 28.75\n ],\n [\n -88.75,\n 28.75\n ],\n [\n -88.75,\n 30.5\n ],\n [\n -94,\n 30.5\n ],\n [\n -94,\n 28.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"151","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a91ce4b034bf6a7e4fd3","contributors":{"authors":[{"text":"DeMarco, Kristin","contributorId":200003,"corporation":false,"usgs":false,"family":"DeMarco","given":"Kristin","email":"","affiliations":[],"preferred":false,"id":748896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Couvillion, Brady 0000-0001-5323-1687 couvillionb@usgs.gov","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":146832,"corporation":false,"usgs":true,"family":"Couvillion","given":"Brady","email":"couvillionb@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":748897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Stuart","contributorId":209831,"corporation":false,"usgs":false,"family":"Brown","given":"Stuart","affiliations":[],"preferred":false,"id":748898,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"La Peyre, Megan 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":79375,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan","email":"mlapeyre@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748895,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}