{"pageNumber":"257","pageRowStart":"6400","pageSize":"25","recordCount":46679,"records":[{"id":70212637,"text":"70212637 - 2020 - Earthquake magnitude and Lg Q variations between the Grenville and northern Appalachian geologic provinces of eastern Canada","interactions":[],"lastModifiedDate":"2020-08-25T14:27:18.911636","indexId":"70212637","displayToPublicDate":"2020-02-04T09:18:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Earthquake magnitude and Lg Q variations between the Grenville and northern Appalachian geologic provinces of eastern Canada","title":"Earthquake magnitude and Lg Q variations between the Grenville and northern Appalachian geologic provinces of eastern Canada","docAbstract":"

This article assesses the ability of regionally specific, frequency‐dependent crustal attenuation (⁠1/Q\">1/Q⁠) to reduce mean magnitude discrepancies between seismic stations in the northern Appalachian and Grenville provinces (NAP and GP) of Canada. LgQ(f)\">Q(f) is an important parameter in ground‐motion models used in probabilistic seismic hazard analysis. Discrepancies in regional magnitude estimates have long been noted to exist between stations in the two provinces for common event origins. Such discrepancies could arise from systematic site condition variations between the geologic provinces or from varying crustal attenuative properties. To evaluate the effect of frequency‐dependent anelastic attenuation, LgQ(f)\">Q(f) on estimated magnitudes, we analyze Lg amplitudes from >6000\">>6000 waveforms recorded by Grenville and northern Appalachian receivers from 420 natural earthquakes of MN\">MN magnitude 3–5.6. Waveform analysis is strictly limited to analyst‐reviewed, vertical‐component waveforms in which Lg is clearly identified, ensuring that the datasets exhibit dominant, high‐frequency energy in the Lg velocity window. LgQ(f)\">Q(f) is found to be higher in the GP than in the northern Appalachians. In the Grenville, Q(f)=761(±145)f0.25(±0.014)\">Q(f)=761(±145)f0.25(±0.014)⁠, and in the northern Appalachians, attenuation is higher: Q(f)=506(±172)f0.33(±0.310)\">Q(f)=506(±172)f0.33(±0.310). Earthquake magnitude determined using the peak amplitude of the Lg phase (⁠mbLg\">mbLg) for eastern Canada is corrected to incorporate the frequency‐dependent, regionally specific LgQ(f)\">Q(f) determined in this study. Using the new LgQ(f)\">Q(f) values diminishes and nearly resolves magnitude discrepancies between the provinces. Correcting regional magnitude discrepancies between provinces is critical for reliable regional seismic hazard estimates because magnitude error in a particular region could lead to increased uncertainty in seismic hazard models.

","language":"English","publisher":"Geological Society of America","doi":"10.1785/0120190145","usgsCitation":"Perry, H.C., Bent, A.L., McNamara, D.E., Crane, S., and Kolaj, M., 2020, Earthquake magnitude and Lg Q variations between the Grenville and northern Appalachian geologic provinces of eastern Canada: Bulletin of the Seismological Society of America, v. 110, no. 2, p. 698-714, https://doi.org/10.1785/0120190145.","productDescription":"17 p.","startPage":"698","endPage":"714","ipdsId":"IP-114819","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":377820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Grenville Geologic Province, Northern Appalachian Geologic Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.3125,\n 42.8115217450979\n ],\n [\n -64.248046875,\n 43.58039085560784\n ],\n [\n -51.767578125,\n 46.800059446787316\n ],\n [\n -52.119140625,\n 49.32512199104001\n ],\n [\n -56.42578125,\n 53.74871079689897\n ],\n [\n -58.095703125,\n 55.178867663281984\n ],\n [\n -60.20507812499999,\n 55.27911529201561\n ],\n [\n -72.24609375,\n 49.83798245308484\n ],\n [\n -81.03515625,\n 45.9511496866914\n ],\n [\n -78.22265625,\n 43.96119063892024\n ],\n [\n -75.5859375,\n 42.94033923363181\n ],\n [\n -70.3125,\n 42.8115217450979\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"110","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Perry, H.K. Claire","contributorId":239554,"corporation":false,"usgs":false,"family":"Perry","given":"H.K.","email":"","middleInitial":"Claire","affiliations":[{"id":47914,"text":"Canadian Hazards Information Service","active":true,"usgs":false}],"preferred":false,"id":797186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bent, Allison L.","contributorId":239555,"corporation":false,"usgs":false,"family":"Bent","given":"Allison","email":"","middleInitial":"L.","affiliations":[{"id":47914,"text":"Canadian Hazards Information Service","active":true,"usgs":false}],"preferred":false,"id":797187,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McNamara, Daniel E. 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":402,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":797188,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crane, Stephen","contributorId":239556,"corporation":false,"usgs":false,"family":"Crane","given":"Stephen","email":"","affiliations":[{"id":47914,"text":"Canadian Hazards Information Service","active":true,"usgs":false}],"preferred":false,"id":797189,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kolaj, Michal","contributorId":239557,"corporation":false,"usgs":false,"family":"Kolaj","given":"Michal","affiliations":[{"id":47914,"text":"Canadian Hazards Information Service","active":true,"usgs":false}],"preferred":false,"id":797190,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208599,"text":"70208599 - 2020 - The response of stream ecosystems in the Adirondack region of New York to historical and future changes in atmospheric deposition of sulfur and nitrogen","interactions":[],"lastModifiedDate":"2020-02-20T09:19:21","indexId":"70208599","displayToPublicDate":"2020-02-04T09:13:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"The response of stream ecosystems in the Adirondack region of New York to historical and future changes in atmospheric deposition of sulfur and nitrogen","docAbstract":"

The present-day acid-base chemistry of surface waters can be directly linked to contemporary observations of acid deposition; however, pre-industrial conditions are key to predicting the potential future recovery of stream ecosystems under decreasing loads of atmospheric sulfur (S) and nitrogen (N) deposition. The integrated biogeochemical model PnET-BGC was applied to 25 forest watersheds that represent a range of acid sensitivity in the Adirondack region of New York, USA to simulate the response of streams to past and future changes in atmospheric S and N deposition, and calculate the target loads of acidity for protecting and restoring stream water quality and ecosystem health. Using measured data, the model was calibrated and applied to simulate soil and stream chemistry at all study sites. Model hindcasts indicate that historically stream water chemistry in the Adirondacks was variable, but inherently sensitive to acid deposition. The median model-simulated acid neutralizing capacity (ANC) of the streams was projected to be 55 μeq L−1 before the advent of anthropogenic acid deposition (~1850), decreasing to minimum values of 10 μeq L−1 around the year 2000. The median simulated ANC increased to 13 μeq L−1 by 2015 in response to decreases in acid deposition that have occurred over recent decades. Model projections suggest that simultaneous decreases in sulfate, nitrate and ammonium deposition are more effective in restoring stream ANC than individual decreases in sulfur or nitrogen deposition. However, the increases in stream ANC per unit equivalent decrease in S deposition is greater compared to decreases in N deposition. Using empirical algorithms, fish community density and biomass are projected to increase under several deposition-control scenarios that coincide with increases in stream ANC. Model projections suggest that even under the most aggressive deposition-reduction scenarios, stream chemistry and fisheries will not fully recover from historical acidification by 2200.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.137113","usgsCitation":"Shao, S., Driscoll, C.T., Sullivan, T.J., Burns, D., Baldigo, B.P., Lawrence, G.B., and McDonnell, T.C., 2020, The response of stream ecosystems in the Adirondack region of New York to historical and future changes in atmospheric deposition of sulfur and nitrogen: Science of the Total Environment, v. 716, 137113, 12 p., https://doi.org/10.1016/j.scitotenv.2020.137113.","productDescription":"137113, 12 p.","ipdsId":"IP-109009","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":457861,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.137113","text":"Publisher Index Page"},{"id":372447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.476318359375,\n 43.69965122967144\n ],\n [\n -73.927001953125,\n 43.69965122967144\n ],\n [\n -73.927001953125,\n 44.07969327425713\n ],\n [\n -74.476318359375,\n 44.07969327425713\n ],\n [\n -74.476318359375,\n 43.69965122967144\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"716","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shao, Shuai","contributorId":222597,"corporation":false,"usgs":false,"family":"Shao","given":"Shuai","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":782668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driscoll, Charles T.","contributorId":167460,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":782669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Timothy J.","contributorId":196720,"corporation":false,"usgs":false,"family":"Sullivan","given":"Timothy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":782670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":782667,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782671,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782672,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McDonnell, Todd C. 0000-0002-5231-105X","orcid":"https://orcid.org/0000-0002-5231-105X","contributorId":196721,"corporation":false,"usgs":false,"family":"McDonnell","given":"Todd","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":782673,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228637,"text":"70228637 - 2020 - Mapping habitat suitability at range-wide scales: Spatially explicit distribution models to inform conservation and research for marsh birds","interactions":[],"lastModifiedDate":"2022-02-16T21:04:33.98395","indexId":"70228637","displayToPublicDate":"2020-02-03T14:52:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Mapping habitat suitability at range-wide scales: Spatially explicit distribution models to inform conservation and research for marsh birds","docAbstract":"Habitat Loss is a primary cause of species decline, and predicting the distribution of quality habitats across broad scales is needed for conservation of rare species. Secretive marsh birds are a group of emergent-wetland specialists that include multiple threatened and endangered species whose populations have been impacted by wetland loss and modification. Habitat suitability for marsh birds is poorly mapped, and predictions of habitat quality over broad scales are primarily generated via expert judgment. We developed data-driven models to predict fine-resolution habitat quality for 13 marsh bird species across their ranges within the U.S. We demonstrate how these models are useful for conservation by quantifying range contraction, assessing the usefulness of existing protected areas, and assessing the vulnerability of habitats to global change for rare species. These tools provide a quantitative foundation for broad-scale conservation, research, and monitoring efforts, and a starting point for adaptive conservation of marsh bird breeding habitat over broad spatial extents.","language":"English","publisher":"Wiley","doi":"10.1111/csp2.178","usgsCitation":"Stevens, B.S., and Conway, C.J., 2020, Mapping habitat suitability at range-wide scales: Spatially explicit distribution models to inform conservation and research for marsh birds: Conservation Science and Practice, v. 2, no. 4, e178, 8 p., https://doi.org/10.1111/csp2.178.","productDescription":"e178, 8 p.","ipdsId":"IP-113280","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":457877,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.178","text":"Publisher Index Page"},{"id":396039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Stevens, Bryan S.","contributorId":171809,"corporation":false,"usgs":false,"family":"Stevens","given":"Bryan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":835048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834900,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70209087,"text":"70209087 - 2020 - The Modern Geological Survey; a model for research, innovation, synthjesis: A USGS perspective","interactions":[],"lastModifiedDate":"2020-03-15T14:31:51","indexId":"70209087","displayToPublicDate":"2020-02-03T14:30:52","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"The Modern Geological Survey; a model for research, innovation, synthjesis: A USGS perspective","docAbstract":"Geological Surveys have long filled the role of providing Earth system science data and knowledge. These functions are increasingly complicated by accelerating environmental and societal change. Here we describe the USGS response to these evolving conditions. Underpinning the USGS approach is the recognition that many of the issues facing the U.S. and the world involve the interaction among geologic, hydrologic, and biologic processes, and how these interactions in turn affect society. Therefore, a goal of USGS planning is fostering interdisciplinary science. This focus is occurring in part through implementation of the recommendations of strategic planning teams. The USGS has also put in place groups building a broad information technology infrastructure as well as identifying and disseminating new Earth science research tools. In addition, the USGS has established an analysis and synthesis center that brings together groups of scientists who address interdisciplinary Earth system science issues. The goal is for these building blocks to evolve towards a comprehensive USGS data and knowledge platform; EarthMAP (Earth Monitoring, Assessment, and Projection). We also recognize that the modern geological survey must be a member of a community of geological surveys contributing data to a global database of 3-dimensional biogeophysical observations and interpretations.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Folding and fracturing of rocks: 50 years of research since the seminal text book of J. G. Ramsay","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of London","doi":"10.1144/SP499-2019-250","usgsCitation":"Kimball, S., Goldhaber, M.B., Baron, J., and Labson, V.F., 2020, The Modern Geological Survey; a model for research, innovation, synthjesis: A USGS perspective, chap. of Folding and fracturing of rocks: 50 years of research since the seminal text book of J. G. Ramsay, https://doi.org/10.1144/SP499-2019-250.","ipdsId":"IP-113562","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":373278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2020-04-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Kimball, Suzette 0000-0003-2777-1596 suzette_kimball@usgs.gov","orcid":"https://orcid.org/0000-0003-2777-1596","contributorId":223371,"corporation":false,"usgs":true,"family":"Kimball","given":"Suzette","email":"suzette_kimball@usgs.gov","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":784877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldhaber, Martin B. 0000-0002-1785-4243 mgold@usgs.gov","orcid":"https://orcid.org/0000-0002-1785-4243","contributorId":1339,"corporation":false,"usgs":true,"family":"Goldhaber","given":"Martin","email":"mgold@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":784875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baron, Jill S. 0000-0002-5902-6251","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":215101,"corporation":false,"usgs":true,"family":"Baron","given":"Jill S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":784874,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Labson, Victor F. 0000-0003-1905-1820 vlabson@usgs.gov","orcid":"https://orcid.org/0000-0003-1905-1820","contributorId":326,"corporation":false,"usgs":true,"family":"Labson","given":"Victor","email":"vlabson@usgs.gov","middleInitial":"F.","affiliations":[{"id":349,"text":"International Water Resources Branch","active":true,"usgs":true}],"preferred":true,"id":784876,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228278,"text":"70228278 - 2020 - Dynamic Habitat Disturbance and Ecological Resilience (DyHDER): Modeling population responses to habitat condition","interactions":[],"lastModifiedDate":"2022-02-08T17:59:30.227932","indexId":"70228278","displayToPublicDate":"2020-02-03T11:56:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic Habitat Disturbance and Ecological Resilience (DyHDER): Modeling population responses to habitat condition","docAbstract":"

Understanding how populations respond to spatially heterogeneous habitat disturbance is as critical to conservation as it is challenging. Here, we present a new, free, and open-source metapopulation model: Dynamic Habitat Disturbance and Ecological Resilience (DyHDER), which incorporates subpopulation habitat condition and connectivity into a population viability analysis framework. Modeling temporally dynamic and spatially explicit habitat disturbance of varying magnitude and duration is accomplished through the use of habitat time-series data and a mechanistic approach to adjusting subpopulation vital rates. Additionally, DyHDER uses a probabilistic dispersal model driven by site-specific habitat suitability, density dependence, and directionally dependent connectivity. In the first application of DyHDER, we explore how fragmentation and projected climate change are predicted to impact a well-studied Bonneville cutthroat trout metapopulation in the Logan River (Utah, USA). The DyHDER model predicts which subpopulations are most susceptible to disturbance, as well as the potential interactions between stressors. Further, the model predicts how populations may be expected to redistribute following disturbance. This information is valuable to conservationists and managers faced with protecting populations of conservation concern across landscapes undergoing changing disturbance regimes. The DyHDER model provides a valuable and generalizable new tool to explore metapopulation resilience to spatially and temporally dynamic stressors for a diverse range of taxa and ecosystems.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3023","usgsCitation":"Murphy, B.P., Walsworth, T., Belmont, P., Conner, M., and Budy, P., 2020, Dynamic Habitat Disturbance and Ecological Resilience (DyHDER): Modeling population responses to habitat condition: Ecosphere, v. 11, no. 1, e03023, 26 p., https://doi.org/10.1002/ecs2.3023.","productDescription":"e03023, 26 p.","ipdsId":"IP-110023","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":457883,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3023","text":"Publisher Index Page"},{"id":395640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Brendan P.","contributorId":275031,"corporation":false,"usgs":false,"family":"Murphy","given":"Brendan","email":"","middleInitial":"P.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":833590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsworth, Timothy E.","contributorId":275032,"corporation":false,"usgs":false,"family":"Walsworth","given":"Timothy E.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":833591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belmont, Patrick","contributorId":275033,"corporation":false,"usgs":false,"family":"Belmont","given":"Patrick","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":833592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conner, Mary M.","contributorId":275034,"corporation":false,"usgs":false,"family":"Conner","given":"Mary M.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":833593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":833589,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260140,"text":"70260140 - 2020 - Influence of grain size and shape on volcanic ash electrical conductivity","interactions":[],"lastModifiedDate":"2024-10-29T16:52:16.429331","indexId":"70260140","displayToPublicDate":"2020-02-03T11:49:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Influence of grain size and shape on volcanic ash electrical conductivity","docAbstract":"

Few studies have examined the electrical properties of volcanic ash or considered the effects of physical characteristics, such as grain size and shape on its electrification. This study measures the resistivity of eight volcanic ash samples, three milled-samples and five natural ashfall samples from Alaska, U.S.A., using a current amplifier and examines the influence of particle size and particle shape on calculated grain conductivity. Grain conductivities are calculated by applying spherical, oblate, and prolate ellipsoidal shape parameters within a general effective media equation. Volcanic ash is an electrically insulating material with average resistivity values ranging from 1.732E7 to 1.606E12 Ωm. Results show that grain size has a limited impact on resistivity. Calculated grain conductivities remained within the same order of magnitude between the three different shape calculations ranging between 1.367E−7 and 2.196E−12 S/m using the spherical shape parameter. Electrical measurements of heterogeneous powders are complex and challenging. This study aims to expand the community's dataset and understanding of the electrical properties of volcanic ash and the impact of different physical characteristics. This has implication for understanding ash hazards to electrical infrastructure and volcanic lightning.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2020.106788","usgsCitation":"Woods, T., Genareau, K., and Wallace, K.L., 2020, Influence of grain size and shape on volcanic ash electrical conductivity: Journal of Volcanology and Geothermal Research, v. 393, 106788, 9 p., https://doi.org/10.1016/j.jvolgeores.2020.106788.","productDescription":"106788, 9 p.","ipdsId":"IP-101220","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467298,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2020.106788","text":"Publisher Index Page"},{"id":463357,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"393","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Woods, Taylor","contributorId":345647,"corporation":false,"usgs":false,"family":"Woods","given":"Taylor","affiliations":[{"id":82675,"text":"The University of Alabama, Tuscaloosa, AL","active":true,"usgs":false}],"preferred":false,"id":917163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Genareau, Kimberly","contributorId":345648,"corporation":false,"usgs":false,"family":"Genareau","given":"Kimberly","affiliations":[{"id":82675,"text":"The University of Alabama, Tuscaloosa, AL","active":true,"usgs":false}],"preferred":false,"id":917164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wallace, Kristi L. 0000-0002-0962-048X kwallace@usgs.gov","orcid":"https://orcid.org/0000-0002-0962-048X","contributorId":3454,"corporation":false,"usgs":true,"family":"Wallace","given":"Kristi","email":"kwallace@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917165,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70206113,"text":"sir20195116 - 2020 - Simulation of water-management scenarios for the Mississippi Delta","interactions":[],"lastModifiedDate":"2022-04-25T18:41:20.950804","indexId":"sir20195116","displayToPublicDate":"2020-02-03T10:20:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5116","displayTitle":"Simulation of Water-Management Scenarios for the Mississippi Delta","title":"Simulation of water-management scenarios for the Mississippi Delta","docAbstract":"

To compare the effectiveness of proposed alternative water-supply scenarios on future water availability in the Mississippi Delta, the U.S. Geological Survey and the Mississippi Department of Environmental Quality are collaborating on the update and enhancement of an existing regional groundwater-flow model of the area. Through this collaboration, the model has been updated to include boundary conditions through March 2014 with the most recent water-use data, precipitation and recharge data, and streamflow and water-level observation data. The updated model has been used to evaluate selected alternative water-supply scenarios to determine relative effects on the Mississippi River Valley alluvial aquifer. Alternative water-supply options evaluated in this report include: (1) irrigation efficiency, (2) on-farm storage and tailwater recovery, (3) instream weirs to increase surface-water availability, (4) intrabasin transfer of surface water, and (5) groundwater transfer and injection. A relative comparison approach was used to calculate the simulated water-level response caused by each scenario. Water-level response is the difference between water levels simulated by the alternative water-supply scenario and those simulated by a base or “no action” scenario. Water-level response in the alluvial aquifer varied for each scenario based on the location, magnitude, and (or) adoption rates of the simulated alternative water-supply option. The groundwater transfer and injection scenario showed the largest water-level response.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20195116","collaboration":"Prepared in cooperation with the Mississippi Department of Environmental Quality","usgsCitation":"Haugh, C.J., Killian, C.D., and Barlow, J.R.B., 2020, Simulation of water-management scenarios for the Mississippi Delta: U.S. Geological Survey Scientific Investigations Report 2019–5116, 15 p., https://doi.org/10.3133/sir20195116.","productDescription":"Report: iv, 15 p.; Data Release","onlineOnly":"N","ipdsId":"IP-088687","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":399601,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109661.htm"},{"id":371205,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9906VM5","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-2005 model used to evaluate water-management scenarios for the Mississippi Delta"},{"id":371202,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5116/coverthb.jpg"},{"id":371203,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5116/sir20195116.pdf","text":"Report","size":"5.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5116"}],"country":"United States","state":"Arkansas, Louisiana, Mississippi, Missouri","otherGeospatial":"Mississippi River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.69238281249999,\n 36.659606226479696\n ],\n [\n -90.318603515625,\n 35.7019167328534\n ],\n [\n -91.746826171875,\n 33.60546961227188\n ],\n [\n -91.109619140625,\n 32.20350534542368\n ],\n [\n -90.318603515625,\n 32.37996146435729\n ],\n [\n -89.659423828125,\n 33.37641235124676\n ],\n [\n -89.05517578125,\n 34.6241677899049\n ],\n [\n -88.857421875,\n 35.85343961959182\n ],\n [\n -89.69238281249999,\n 36.659606226479696\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, Tennessee 37211

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-02-03","noUsgsAuthors":false,"publicationDate":"2020-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Haugh, Connor J. 0000-0002-5204-8271","orcid":"https://orcid.org/0000-0002-5204-8271","contributorId":219945,"corporation":false,"usgs":true,"family":"Haugh","given":"Connor J.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773628,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Killian, Courtney D. 0000-0002-2137-2722","orcid":"https://orcid.org/0000-0002-2137-2722","contributorId":213990,"corporation":false,"usgs":true,"family":"Killian","given":"Courtney","email":"","middleInitial":"D.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773629,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barlow, Jeannie R. B. 0000-0002-0799-4656 jbarlow@usgs.gov","orcid":"https://orcid.org/0000-0002-0799-4656","contributorId":3701,"corporation":false,"usgs":true,"family":"Barlow","given":"Jeannie","email":"jbarlow@usgs.gov","middleInitial":"R. B.","affiliations":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":773630,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208643,"text":"70208643 - 2020 - Persistence and plasticity in conifer water-use strategies","interactions":[],"lastModifiedDate":"2020-02-25T06:33:22","indexId":"70208643","displayToPublicDate":"2020-02-03T06:46:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Persistence and plasticity in conifer water-use strategies","docAbstract":"The selective use of seasonal precipitation by vegetation is critical to understanding the residence time and flow path of water in watersheds, yet there are limited datasets to test how climate alters these dynamics. Here, we use measurements of the seasonal cycle of tree ring 18O for two widespread conifer species in the Rocky Mountains of North America to provide a multi-decadal depiction of the seasonal origins of forest water use. The results show that while the conifer tree stands had a dominant preference for use of snowmelt, there were multi-annual periods over the last four decades when use of summer precipitation was preferential. Utilization of summer rain emerged during years with increased snowfall and tree growth, suggesting that summer rain enhanced the transpiration stream only during the periods of highest water use. We hypothesize this could be explained through shallowing of the root profile during wetter periods and/or through the influence of changing water table depths on the residence time of summer precipitation in the root zone. We suggest the tree ring proxy approach used here could be applied in other watersheds to provide critical insight into the temporal dynamics of plant water use that could not be inferred from short measurement campaigns. These data on the seasonal origins of forest water are critical for understanding forest vulnerability to drought, the processes that affect precipitation pathways and residence time in watersheds and the interpretation of tree ring proxy data.","language":"English","publisher":"AGU","doi":"10.1029/2018JG004845","usgsCitation":"Berkelhammer, M., Still, C., Ritter, F., Winnik, M., Anderson, L., Carroll, R., Carbone, M., and Williams, K., 2020, Persistence and plasticity in conifer water-use strategies: Journal of Geophysical Research: Biogeosciences, v. 125, no. 2, e2018JG004845, 20 p., https://doi.org/10.1029/2018JG004845.","productDescription":"e2018JG004845, 20 p.","ipdsId":"IP-097269","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":457901,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1600566","text":"Publisher Index Page"},{"id":372535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.17138671875,\n 38.42777351132902\n ],\n [\n -105.9521484375,\n 38.42777351132902\n ],\n [\n -105.9521484375,\n 39.774769485295465\n ],\n [\n -108.17138671875,\n 39.774769485295465\n ],\n [\n -108.17138671875,\n 38.42777351132902\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Berkelhammer, Max ","contributorId":150891,"corporation":false,"usgs":false,"family":"Berkelhammer","given":"Max ","affiliations":[{"id":18133,"text":"University of Illinois Chicago","active":true,"usgs":false}],"preferred":false,"id":782873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Still, Chris","contributorId":222677,"corporation":false,"usgs":false,"family":"Still","given":"Chris","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":782874,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ritter, Francois","contributorId":222678,"corporation":false,"usgs":false,"family":"Ritter","given":"Francois","email":"","affiliations":[{"id":18137,"text":"University of Illinois at Chicago","active":true,"usgs":false}],"preferred":false,"id":782875,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winnik, Matthew","contributorId":222679,"corporation":false,"usgs":false,"family":"Winnik","given":"Matthew","email":"","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":782876,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Lesleigh 0000-0002-5264-089X land@usgs.gov","orcid":"https://orcid.org/0000-0002-5264-089X","contributorId":436,"corporation":false,"usgs":true,"family":"Anderson","given":"Lesleigh","email":"land@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":782872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carroll, Rosemary ","contributorId":222680,"corporation":false,"usgs":false,"family":"Carroll","given":"Rosemary ","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":782877,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carbone, Mariah ","contributorId":222681,"corporation":false,"usgs":false,"family":"Carbone","given":"Mariah ","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":782878,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, Kenneth ","contributorId":222682,"corporation":false,"usgs":false,"family":"Williams","given":"Kenneth ","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":782879,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70260131,"text":"70260131 - 2020 - Evolution of the submarine–subaerial edifice of Bogoslof volcano, Alaska, during its 2016–2017 eruption based on analysis of satellite imagery","interactions":[],"lastModifiedDate":"2024-10-30T11:19:12.419484","indexId":"70260131","displayToPublicDate":"2020-02-03T06:15:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Evolution of the submarine–subaerial edifice of Bogoslof volcano, Alaska, during its 2016–2017 eruption based on analysis of satellite imagery","docAbstract":"

The 2016–2017 eruption of Bogoslof volcano involved at least 70 detected eruptive events between mid-December 2016 and August 30, 2017. Acquisition of high-resolution satellite imagery throughout the duration of the eruptive period allowed us to document and map the various morphologic changes that occurred on the subaerial part of Bogoslof Island. The emplacement of pyroclastic-flow and surge deposits caused the island to increase in area by about 1.5 km2. The dominant volcanic landforms of the eruption were a series of tuff rings emplaced around various submarine vents. Many of the tuff rings were mantled with surface dunes and impressive amounts of ballistic ejecta, likely derived from erupting magma bodies or previously emplaced submarine lava domes. Debris-flow deposits and surface channels extending over tuff ring surfaces apparent in multiple satellite images are evidence for explosive ejection of seawater. In most cases, erupting vents were initially submarine or began at subaerial lava domes and were largely flooded by seawater suggesting that water-magma ratios were likely high. Under such conditions where water is abundant, eruptive products typically reflect a high degree of water involvement and are dominated by the formation of wet tephra jets and flows and associated deposits typically consist of fine ash and lapilli, contain accretionary lapilli and ash aggregates, and usually form tuff cones and mounds. We observed none of these features in our analysis of satellite data or during our examination of eruptive deposits on Bogoslof Island in 2018. On the contrary, the dominant landform associated with the Bogoslof eruption was tuff rings. The development of tuff rings and surface dunes are commonly associated with the formation of pyroclastic base surges that are by comparison emplaced relatively dry. Dry base surge deposits can be generated from phreatomagmatic explosions involving superheated steam. It is possible that shallow submarine, magma–wet sediment interactions were a characteristic and possibly a dominant eruptive process of the 2016–2017 Bogoslof eruption.

","language":"English","publisher":"Springer","doi":"10.1007/s00445-020-1363-0","usgsCitation":"Waythomas, C.F., Angeli, K.M., and Wessels, R., 2020, Evolution of the submarine–subaerial edifice of Bogoslof volcano, Alaska, during its 2016–2017 eruption based on analysis of satellite imagery: Bulletin of Volcanology, v. 82, 21, https://doi.org/10.1007/s00445-020-1363-0.","productDescription":"21","ipdsId":"IP-113627","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":463385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof volcano","volume":"82","noUsgsAuthors":false,"publicationDate":"2020-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Waythomas, Christopher F. 0000-0002-3898-272X cwaythomas@usgs.gov","orcid":"https://orcid.org/0000-0002-3898-272X","contributorId":640,"corporation":false,"usgs":true,"family":"Waythomas","given":"Christopher","email":"cwaythomas@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angeli, Kim M. 0000-0003-2427-3241 kangeli@usgs.gov","orcid":"https://orcid.org/0000-0003-2427-3241","contributorId":238809,"corporation":false,"usgs":true,"family":"Angeli","given":"Kim","email":"kangeli@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wessels, Rick 0000-0001-9711-6402 rwessels@usgs.gov","orcid":"https://orcid.org/0000-0001-9711-6402","contributorId":198602,"corporation":false,"usgs":true,"family":"Wessels","given":"Rick","email":"rwessels@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917114,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208450,"text":"70208450 - 2020 - Development of a global seismic risk model","interactions":[],"lastModifiedDate":"2020-10-28T15:19:00.996524","indexId":"70208450","displayToPublicDate":"2020-02-02T07:31:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Development of a global seismic risk model","docAbstract":"Since 2015 the Global Earthquake Model (GEM) Foundation and its partners have been supporting regional programmes and bilateral collaborations to develop an open global earthquake risk model. These efforts led to the development of a repository of probabilistic seismic hazard models, a global exposure dataset comprising structural and occupancy information regarding the residential, commercial and industrial buildings, and a comprehensive set of fragility and vulnerability functions for the most common building classes. These components were used to estimate probabilistic earthquake risk globally using the OpenQuake-engine, an open-source software for seismic hazard and risk analysis. This model allows estimating a number of risk metrics such as annualized average losses or aggregated losses for particular return periods, which are fundamental to the development and implementation of earthquake risk mitigation measures.","language":"English","publisher":"SAGE","doi":"10.1177/8755293019899953","usgsCitation":"Silva, V., Amo-Oduro, D., Calderon, A., Costa, C., Dabbeek, J., Despotaki, V., Martins, L., Pagani, M., Rao, A., Simionato, M., Vigano, D., Yepes-Estrada, C., Acevedo, A.B., Crowley, H., Horspool, N., Jaiswal, K.S., Journeay, M., and Pittore, M., 2020, Development of a global seismic risk model: Earthquake Spectra, v. 36, no. s1, p. 372-394, https://doi.org/10.1177/8755293019899953.","productDescription":"13 p.","startPage":"372","endPage":"394","ipdsId":"IP-114831","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":457907,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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Natural groundwater brine discharge to the Dolores River where it passes through the collapsed salt anticline of the Paradox Valley in western Colorado is a significant source of salt to the Colorado River. An airborne electromagnetic survey of Paradox Valley has provided insights into the 3D distribution of brine in the surficial aquifer. A combination of stochastic and deterministic resistivity inversions were used to interpret the top of the freshwater-brine interface and to qualitatively describe the vertical salinity gradients across the interface. Low-resistivity regions indicative of brine occur near the land surface where brine discharges to the Dolores River and increase in depth several kilometers up-gradient along the axis of the valley. The most conductive parts of the brine plume are found in the areas below and adjacent to the river, suggesting that the brine becomes shallower and more concentrated as it reaches its natural discharge location. A significant freshwater lens overlying the brine west of the Dolores River is spatially correlated to the intermittent West Paradox Creek and agricultural irrigation. Below this lens, the transition from freshwater to brine appears to occur abruptly over a few meters and correlates to available well information. However, away from these regions and particularly with distance from the river, the freshwater-brine interface appears to be more diffuse.","language":"English","publisher":"Springer","doi":"10.1007/s10040-019-02102-z","usgsCitation":"Ball, L.B., Bedrosian, P.A., and Minsley, B.J., 2020, High-resolution mapping of the freshwater-brine interface using deterministic and Bayesian inversion of airborne electromagnetic data at Paradox Valley, USA: Hydrogeology Journal, v. 28, no. 3, p. 941-954, https://doi.org/10.1007/s10040-019-02102-z.","productDescription":"14 p.","startPage":"941","endPage":"954","ipdsId":"IP-109154","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":376365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Paradox Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.083251953125,\n 36.98500309285596\n ],\n [\n -105.732421875,\n 36.98500309285596\n ],\n [\n -105.732421875,\n 39.36827914916014\n ],\n [\n -109.083251953125,\n 39.36827914916014\n ],\n [\n -109.083251953125,\n 36.98500309285596\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":792704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":792705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":792706,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228268,"text":"70228268 - 2020 - Influence of population density and length structure on angler catch rate in kokanee fisheries","interactions":[],"lastModifiedDate":"2022-02-08T16:41:38.191284","indexId":"70228268","displayToPublicDate":"2020-02-01T10:22:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Influence of population density and length structure on angler catch rate in kokanee fisheries","docAbstract":"

Management agencies are often charged with providing fisheries that lead to angler participation. Catch rate is one of the primary drivers of angler participation but can be influenced by a suite of factors, including population structure (e.g., density and size structure). The complexity of understanding how population structure influences angler catch rate is typified in kokanee Oncorhynchus nerka fisheries. Previous research suggests that angler catch rates of kokanee are positively influenced by fish density and total length. However, that research was based on data collected using size-selective midwater trawls. Due to the potential limitation of previous research, we sought to (1) understand the relative bias of midwater trawls and gill nets for describing the size structure of kokanee available to anglers and (2) re-evaluate the influence of fish density and fish length on angler catch rates in kokanee fisheries. Midwater trawl, gill-net, and creel data were collected on five prominent kokanee fisheries throughout Idaho in 2016 and 2017. Catch composition and percent overlap of midwater trawls, gill nets, and angler-caught fish were compared to understand the efficacy of midwater trawls and gill nets for representing the size structure of kokanee available to anglers. In addition, the influence of kokanee density and length on angler catch rates was evaluated. Midwater trawls primarily sampled small kokanee (<330 mm) and exhibited little overlap with angler-caught fish, whereas gill nets sampled more large fish (>330 mm) and exhibited higher overlap with angler-caught fish when compared to midwater trawls. Fish length was not positively associated with angler catch rates. However, fish density exhibited a positive relationship with angler catch rates. Our results highlight the importance of gear choice for understanding how kokanee populations function and elucidate the tradeoffs associated with population density, fish length, and resulting kokanee fisheries.

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temperature (SST) data collected using sensors mounted on low-flying aircraft to characterize NCCS water masses and identify patterns among seasons and between years. To accomplish this, we applied k-means clustering to measured and derived ecologically-relevant physical and bio-optical variables (SST, Chla, absorbance by colored dissolved organic matter [aCDOM], proxy particle load). These classifications will be used in the future to evaluate species habitat distributions in the NCCS.","language":"English","publisher":"BOEM","usgsCitation":"Schulien, J.A., Adams, J., and Felis, J.J., 2020, Pacific Continental Shelf Environmental Assessment (PaCSEA): Characterization of Seasonal Water Masses within the Northern California Current System Using Airborne Remote Sensing off Northern California, Oregon, and Washington, 2011–2012, iv, 26 p.","productDescription":"iv, 26 p.","ipdsId":"IP-075956","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":374387,"type":{"id":15,"text":"Index Page"},"url":"https://www.boem.gov/environment/environmental-studies/recently-completed-environmental-studies-pacific"},{"id":374397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Pacific Continental Shelf","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.0791015625,\n 42.19596877629178\n ],\n [\n -124.76074218749999,\n 37.47485808497102\n ],\n [\n -122.4755859375,\n 37.47485808497102\n ],\n [\n -122.4755859375,\n 46.76996843356982\n ],\n [\n -124.76074218749999,\n 46.76996843356982\n ],\n [\n -126.0791015625,\n 42.19596877629178\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schulien, J A","contributorId":224409,"corporation":false,"usgs":false,"family":"Schulien","given":"J","email":"","middleInitial":"A","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":788212,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Josh 0000-0003-3056-925X","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":213442,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":788213,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Felis, Jonathan J. 0000-0002-0608-8950 jfelis@usgs.gov","orcid":"https://orcid.org/0000-0002-0608-8950","contributorId":4825,"corporation":false,"usgs":true,"family":"Felis","given":"Jonathan","email":"jfelis@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":788214,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70209147,"text":"70209147 - 2020 - Influence of remediation on sediment toxicity within the Grand Calumet River, Indiana, USA","interactions":[],"lastModifiedDate":"2020-03-20T06:47:36","indexId":"70209147","displayToPublicDate":"2020-01-31T18:49:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1226,"text":"Chemosphere","active":true,"publicationSubtype":{"id":10}},"title":"Influence of remediation on sediment toxicity within the Grand Calumet River, Indiana, USA","docAbstract":"The Grand Calumet River (GCR), located in northern Indiana, is contaminated due to a wide range of historical industrial activities. This study was conducted to determine the influence of sediment remediation within the GCR on concentrations of chemical contaminants and toxicity to sediment-dwelling organisms. Between 2005 and 2016, sediments with high concentrations of metals and toxic organic compounds were remediated through a combination of removal, addition of activated carbon and organoclay amendments, and capping with sand or relatively uncontaminated sediment. Short-term and long-term sediment toxicity tests with the amphipod Hyalella azteca, the midge Chironomus dilutus, and the mussel Lampsilis siliquoidea were conducted with samples collected in 2013, 2015, and 2017, from 29 sites, including both remediated and non-remediated sites. Sediment chemistry and toxicity data for three groups of remediated sites (US Steel, West Branch, and East Branch) were compared to samples from contaminated but unremediated sites and to relatively uncontaminated reference sites. In general, remediated sediments had lower levels of PAHs, PCBs and metals, although sediments from the US Steel area still had elevated levels of PAH, PCB and chromium. Sediments from the three remediated sites and from reference sites showed significantly reduced toxic effects in short-term sediment bioassays, compared to unremediated sites. Variation in the long-term success of remediation may reflect site-specific factors such as the type of remediation and the potential for recontamination from uncontrolled sources.","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2020.126056","usgsCitation":"Steevens, J.A., Besser, J.M., Dorman, R.A., and Sparks, D.W., 2020, Influence of remediation on sediment toxicity within the Grand Calumet River, Indiana, USA: Chemosphere, v. 249, 126056, https://doi.org/10.1016/j.chemosphere.2020.126056.","productDescription":"126056","ipdsId":"IP-113273","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":437131,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XIDHOV","text":"USGS data release","linkHelpText":"Chemical and biological exposure bioassay data from sediment collected within the Grand Calumet River, Indiana, 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Rebecca A. 0000-0002-5748-7046","orcid":"https://orcid.org/0000-0002-5748-7046","contributorId":28522,"corporation":false,"usgs":true,"family":"Dorman","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":785124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sparks, Daniel W.","contributorId":223469,"corporation":false,"usgs":false,"family":"Sparks","given":"Daniel","email":"","middleInitial":"W.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":785125,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208237,"text":"70208237 - 2020 - Direct trace element determination in oil and gas produced waters with inductively coupled plasma - Optical emission spectrometry (ICP-OES): Advantages of high salinity tolerance","interactions":[],"lastModifiedDate":"2020-06-04T16:51:39.984534","indexId":"70208237","displayToPublicDate":"2020-01-31T16:07:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1822,"text":"Geostandards and Geoanalytical Research","active":true,"publicationSubtype":{"id":10}},"title":"Direct trace element determination in oil and gas produced waters with inductively coupled plasma - Optical emission spectrometry (ICP-OES): Advantages of high salinity tolerance","docAbstract":"Waters co-produced during petroleum extraction are the largest waste stream from oil and gas development. Reuse or disposal of these waters is difficult due to their high salinities and the sheer volumes generated. Produced waters may also contain valuable mineral commodities. While an understanding of produced water trace element composition is required for evaluating the associated resource and waste potential of these materials, measuring trace elements in brines is challenging due to the dilution requirements of typical methods. Alternatively, inductively coupled plasma-optical emission spectrometry (ICP-OES) has shown promise as being capable of direct measurements of trace elements within produced waters with minimal dilution. Here we evaluate direct ICP-OES trace element quantification in produced waters for 17 trace elements (As, Al, Ba, Be, Cd, Cr, Co, Cu, Hg, Mo, Ni, Pb, Rb, Sb, U, V, and Zn) within 15 produced waters from five U.S. continuous reservoirs. The ICP-OES results are compared against trace element levels determined using inductively coupled plasma-mass spectrometry from the same samples. Our results demonstrate the potential for direct analysis of high salinity waters using ICP-OES with minimal dilution and provide trace element concentrations in waters from several important U.S. petroleum-generating reservoirs where available data is sparse.","language":"English","publisher":"Wiley","doi":"10.1111/GGR.12316","usgsCitation":"Jubb, A., Engle, M., Chenault, J., Blondes, M., Danforth, C.G., Doolan, C., Gallegos, T., Mueller, D., and Shelton, J., 2020, Direct trace element determination in oil and gas produced waters with inductively coupled plasma - Optical emission spectrometry (ICP-OES): Advantages of high salinity tolerance: Geostandards and Geoanalytical Research, v. 44, no. 2, p. 385-397, https://doi.org/10.1111/GGR.12316.","productDescription":"13 p.","startPage":"385","endPage":"397","ipdsId":"IP-111055","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":457922,"rank":0,"type":{"id":40,"text":"Open 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mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":222079,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":781119,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Danforth, Cloelle G.","contributorId":222080,"corporation":false,"usgs":false,"family":"Danforth","given":"Cloelle","email":"","middleInitial":"G.","affiliations":[{"id":15310,"text":"Environmental Defense Fund","active":true,"usgs":false}],"preferred":false,"id":781219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Doolan, Colin 0000-0002-7595-7566 cdoolan@usgs.gov","orcid":"https://orcid.org/0000-0002-7595-7566","contributorId":222081,"corporation":false,"usgs":true,"family":"Doolan","given":"Colin","email":"cdoolan@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":781121,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gallegos, Tanya 0000-0003-3350-6473 tgallegos@usgs.gov","orcid":"https://orcid.org/0000-0003-3350-6473","contributorId":222082,"corporation":false,"usgs":true,"family":"Gallegos","given":"Tanya","email":"tgallegos@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":781122,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mueller, Dan","contributorId":222083,"corporation":false,"usgs":false,"family":"Mueller","given":"Dan","email":"","affiliations":[{"id":15310,"text":"Environmental Defense Fund","active":true,"usgs":false}],"preferred":false,"id":781220,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shelton, Jenna 0000-0002-1377-0675 jlshelton@usgs.gov","orcid":"https://orcid.org/0000-0002-1377-0675","contributorId":222084,"corporation":false,"usgs":true,"family":"Shelton","given":"Jenna","email":"jlshelton@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":781124,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70217164,"text":"70217164 - 2020 - Predictive relations between acid-base chemistry and fish assemblages in streams of the Adirondack Mountains","interactions":[],"lastModifiedDate":"2021-01-08T17:30:33.449604","indexId":"70217164","displayToPublicDate":"2020-01-31T11:26:17","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5590,"text":"NYSERDA Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"20-04","title":"Predictive relations between acid-base chemistry and fish assemblages in streams of the Adirondack Mountains","docAbstract":"

Surface waters across much of New York State’s Adirondack Mountains were acidified in the late 20th century but began to recover following the 1990 Title IV Amendments to the Clean Air Act. Previous assessments of acidification recovery in the Adirondacks have generally been based on surface water chemistry data and inferred relationships to fish and other aquatic biota. Little data, however, has been available to characterize biological impacts and predict recovery of fish assemblages in streams of the region. Here, we use quantitative fish surveys combined with chemistry data from 48 headwater streams sampled during summer 2014–2016 to develop logistic (probability) models that characterize the status of contemporary fish assemblages and predict how different N and S deposition loads may affect future fish assemblages. Statistical models for inorganic aluminum (Ali) and richness ≥1 species; and for acid neutralizing capacity (ANC) and total density >400 fish/0.1 ha, total biomass >1500 g/0.1 ha, brook trout Salvelinus fontinalis density >0 or >200 fish/0.1 ha, and brook trout biomass >1000 g/0.1 ha were suitable for evaluating community and population responses to changes in acid-base chemistry. Predictions of fish-assemblage responses using several of these models demonstrated that anticipated changes in national (U.S.) secondary standards for atmospheric emissions of NOx and SOx to achieve target N and S deposition loads are likely to alter the acid-base chemistry and the probabilities of observing various levels of brook trout population and fish-community metrics in streams across the region and elsewhere.

","language":"English","publisher":"New York State Energy Research and Development Authority","usgsCitation":"Bertok, D., Baldigo, B.P., and George, S.D., 2020, Predictive relations between acid-base chemistry and fish assemblages in streams of the Adirondack Mountains: NYSERDA Report 20-04, v, 24 p.","productDescription":"v, 24 p.","ipdsId":"IP-107973","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":382030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":382011,"type":{"id":15,"text":"Index Page"},"url":"https://www.nyserda.ny.gov/About/Publications/Research-and-Development-Technical-Reports/Environmental-Research-and-Development-Technical-Reports"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.728759765625,\n 43.22118973298753\n ],\n [\n -73.7567138671875,\n 43.22118973298753\n ],\n [\n -73.7567138671875,\n 44.22945656830167\n ],\n [\n -75.728759765625,\n 44.22945656830167\n ],\n [\n -75.728759765625,\n 43.22118973298753\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bertok, Diane","contributorId":247518,"corporation":false,"usgs":false,"family":"Bertok","given":"Diane","email":"","affiliations":[],"preferred":false,"id":807829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807800,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807801,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208466,"text":"70208466 - 2020 - Expert bioblitzes facilitate non-native fish tracking and interagency partnerships","interactions":[],"lastModifiedDate":"2020-03-11T15:32:23","indexId":"70208466","displayToPublicDate":"2020-01-31T09:40:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Expert bioblitzes facilitate non-native fish tracking and interagency partnerships","docAbstract":"Documenting the distribution and composition of non-native species populations can be challenging, especially when species cross jurisdictional boundaries that require interagency coordination. Herein I report the development of three tools that have been used in Florida over the past seven years to assist with tracking of non-native fishes: 1) an overarching organization to increase coordination and communication amongst stakeholders (Florida Non-Native Fish Action Alliance); 2) regularly-scheduled expert bioblitzes (Fish Slams); and 3) symposia (Fish Chats). Ten Fish Slams were held since 2012, which have included nearly 100 individuals from 20 organizations. Participants have sampled nearly 200 unique sites, capturing 36 non-native fish taxa. These activities have generated over 600 records for the U.S. Geological Survey’s Nonindigenous Aquatic Species database. Many specimens collected during Fish Slams are deposited into natural history museums or used by researchers. Informal interactions amongst colleagues working together in the field, at check-in meetings at the end of the day, and during more structured Fish Chat symposia allow members of various organizations to become acquainted, build trust, and share information and technology, which may then lead to professional collaborations. While this program is focused on non-native fish species in south Florida, I also discuss how the expert bioblitz may be adapted to suit other taxonomic groups and a variety of conservation needs.","language":"English","publisher":"REABIC","doi":"10.3391/mbi.2020.11.1.10","usgsCitation":"Schofield, P.J., 2020, Expert bioblitzes facilitate non-native fish tracking and interagency partnerships: Management of Biological Invasions, v. 11, no. 1, p. 139-154, https://doi.org/10.3391/mbi.2020.11.1.10.","productDescription":"16 p.","startPage":"139","endPage":"154","ipdsId":"IP-109058","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":457927,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.3391/mbi.2020.11.1.10","text":"Publisher Index Page"},{"id":372225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.7822265625,\n 25.08062377244484\n ],\n [\n -80.013427734375,\n 25.08062377244484\n ],\n [\n -80.013427734375,\n 26.59343927024179\n ],\n [\n -81.7822265625,\n 26.59343927024179\n ],\n [\n -81.7822265625,\n 25.08062377244484\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schofield, Pamela J. 0000-0002-8752-2797 pschofield@usgs.gov","orcid":"https://orcid.org/0000-0002-8752-2797","contributorId":168659,"corporation":false,"usgs":true,"family":"Schofield","given":"Pamela","email":"pschofield@usgs.gov","middleInitial":"J.","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":782015,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70208591,"text":"70208591 - 2020 - Applications of correlative light and electron microscopy (CLEM) to organic matter in the North American shale petroleum systems","interactions":[],"lastModifiedDate":"2020-02-20T09:12:46","indexId":"70208591","displayToPublicDate":"2020-01-31T09:12:37","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"1","title":"Applications of correlative light and electron microscopy (CLEM) to organic matter in the North American shale petroleum systems","docAbstract":"

Scanning electron microscopy (SEM) has revolutionized our understanding of shale petroleum systems through microstructural characterization of dispersed organic matter (OM). However, due to the low atomic weight of carbon, all OM appears black in SEM (BSE image) regardless of differences in thermal maturity or OM type (kerogen types or solid bitumen). Traditional petrographic identification of OM uses optical microscopy, where reflectance (%Ro), form, relief and fluorescence can be used to discern OM types and thermal maturation stage. Unfortunately, most SEM studies of shale OM do not employ correlative optical techniques, leading to misidentifications or to the conclusion that all OM (i.e., kerogen and solid bitumen) is the same. To improve the accuracy of SEM identifications of dispersed OM in shale, this study used correlative light and electron microscopy (CLEM) to create optical and SEM images of OM in the same fields of view (500x magnification) under white light, blue light, secondary electron, and backscatter electron conditions. Samples (n=8) of varying thermal maturities and typical of the North American shale petroleum systems were used, including the Green River Mahogany Zone, Bakken Formation, Ohio Shale, Eagle Ford Formation, Barnett Formation, Haynesville Formation and Woodford Shale. The CLEM image sets demonstrate the importance of correlative microscopy by showing how easily OM can be misidentified when viewed by SEM alone. Without CLEM techniques, petrographic data from SEM such as observations of organic nano-porosity may be misinterpreted, resulting in false or ambiguous results and impairing an improved understanding of organic diagenesis and catagenesis.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Mudstone diagenesis: Research perspectives for shale hydrocarbon reservoirs, seals, and source rocks","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"AAPG","isbn":"9180891814252","usgsCitation":"Valentine, B.J., and Hackley, P.C., 2020, Applications of correlative light and electron microscopy (CLEM) to organic matter in the North American shale petroleum systems, chap. 1 of Mudstone diagenesis: Research perspectives for shale hydrocarbon reservoirs, seals, and source rocks, p. 1-18.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-093317","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":372446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372421,"type":{"id":15,"text":"Index Page"},"url":"https://store.aapg.org/detail.aspx?id=1310"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Valentine, Brett J. 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":3846,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":782638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":782677,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70209332,"text":"70209332 - 2020 - Habitat affinities and at-sea ranging behaviors among main Hawaiian Island seabirds: Breeding seabird telemetry, 2013–2016","interactions":[],"lastModifiedDate":"2020-04-01T08:39:57","indexId":"70209332","displayToPublicDate":"2020-01-31T08:36:24","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Habitat affinities and at-sea ranging behaviors among main Hawaiian Island seabirds: Breeding seabird telemetry, 2013–2016","docAbstract":"Recent Hawaiʻi state clean energy policy mandates and federal interest in developing offshore renewable energy resources have prompted unsolicited lease requests for offshore wind energy infrastructure (OWEI) to be located in ocean waters off Hawaiʻi. This study describing at-sea ranging behaviors for five seabirds was intended to provide new information on Hawaiian breeding seabird distribution at sea, habitat utilization, and ranging behaviors within near-island waters and throughout outer continental shelf (OCS) waters surrounding the main Hawaiian Islands (MHI). We also estimate the percentage of time the five study species spent flying at altitudes equivalent to an expected rotor-swept-zone (RSZ; 30–194 m) for an offshore wind turbine and discuss potential collision risk from OWEI to the seabirds studied here. The MHI supports important seabird breeding populations and individual seabirds can now be equipped with a wide-variety of data loggers and location tracking devices that can provide complex, high-resolution information on movement patterns at sea. In this study, we used GPS loggers and temperature-depth-recorders (TDRs) to examine the at-sea distributions and ranging behaviors of five abundantly breeding species in the MHI: Red-tailed Tropicbird, Laysan Albatross, Wedge-tailed Shearwater, Brown Booby, and Red-footed Booby. We tracked these breeding seabirds from 14 different sites throughout the MHI; study colonies were located on the main islands of Maui, Oʻahu, Kauaʻi, and on associated islets. We used the Residence in Space and Time (RST) algorithm to classify behavior into resting, transiting, and searching/foraging (Torres et al. 2017). We used GPS altitude measurements to examine species-specific flight height and to estimate time spent flying in the RSZ. We mapped rediscretized tracking data for seabirds at each study colony according to behavioral class and trip type (when applicable) using kernel density estimates. During 2014–2016, we obtained GPS and TDR data from 59 and 34 Red-tailed Tropicbirds, respectively. Taken together, individuals revealed a bimodal (short- [~3 h, <100 km range] and long- [>3 d, >800 km range]) trip foraging strategy. While ranging at sea, we estimated that Red-tailed Tropicbirds spend 70.6% (95% confidence interval [CI] 70.1–71.0%) of flight time in the RSZ. TDR data for tropicbirds was noisy and we could not reliably identify dives. During 2014 and 2016, we obtained GPS data from 35 Laysan Albatrosses nesting on Kauaʻi and Oʻahu. Individuals during the mid- to late-chick rearing period engaged in a bimodal short- (<6 d, <400 km range) and long- (>6 d, >2,000 km range) trip foraging strategy. While ranging at sea, we estimated that Laysan Albatrosses spend 2.57% (95% CI 2.50–2.64%) of flight time in the RSZ. During 2013–2015, we obtained GPS and TDR data from 313 and 55 Wedge-tailed Shearwaters, respectively. Considering all the data together, individuals revealed a multi-modal trip duration foraging strategy consisting of intra-day (<24 h, <100 km range), short (<4 d, ~200 km range), and long (>4 d, ~100–400 km range) trips. While ranging at sea, we estimated that Wedge-tailed Shearwaters spend 5.20% (95% CI 5.13–5.27%) of flight time in the RSZ. Wedge-tailed Shearwaters dove to a mean (± SD) depth of 1.78 ± 1.35 m (median = 1.38 m); the deepest dive recorded was to 10.06 m. The mean dive duration for Wedge-tailed Shearwaters was 3.12 ± 3.44 s (median = 1.80 s). During 2014–2015, we obtained GPS and TDR data from 42 and 37 Brown Boobies, respectively. Almost all foraging trips (97%) were single-day trips and we did not detect any bimodality in the distribution of single-day trip durations. Brown Boobies foraged relatively close to their colony (<60 km range) and focused their at-sea use in nearshore, coastal waters off Kauaʻi and Niʻihau. While foraging at sea, we estimated that Brown Boobies spend 3.41% (95% CI 3.16–3.67%) of flight time in the RSZ","language":"English","publisher":"BOEM","collaboration":"BOEM","usgsCitation":"Adams, J., Felis, J.J., and Czapanskiy, M., 2020, Habitat affinities and at-sea ranging behaviors among main Hawaiian Island seabirds: Breeding seabird telemetry, 2013–2016, viii, 111 p. .","productDescription":"viii, 111 p. 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\"}}]}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Adams, Josh 0000-0003-3056-925X","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":213442,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":786134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Felis, Jonathan J. 0000-0002-0608-8950 jfelis@usgs.gov","orcid":"https://orcid.org/0000-0002-0608-8950","contributorId":4825,"corporation":false,"usgs":true,"family":"Felis","given":"Jonathan","email":"jfelis@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":786135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Czapanskiy, Max 0000-0002-6302-905X","orcid":"https://orcid.org/0000-0002-6302-905X","contributorId":207793,"corporation":false,"usgs":false,"family":"Czapanskiy","given":"Max","email":"","affiliations":[{"id":37635,"text":"San Fransciso State University","active":true,"usgs":false}],"preferred":false,"id":786136,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208453,"text":"70208453 - 2020 - Estimating late 19th century hydrology in the Greater Everglades Ecosystem: An integration of paleoecologic data and models","interactions":[],"lastModifiedDate":"2020-02-11T07:40:36","indexId":"70208453","displayToPublicDate":"2020-01-31T07:37:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Estimating late 19th century hydrology in the Greater Everglades Ecosystem: An integration of paleoecologic data and models","docAbstract":"Determining hydrologic conditions prior to instrumental records is a challenge for restoration of freshwater ecosystems worldwide. Paleoecologic data provide this information on past conditions and when these data are used to adjust hydrologic models, allow conditions to be hindcast that may not be directly estimated from the paleo-data alone. In this context, the paleo-data provide real-world estimates as input to the models. Restoration of the Greater Everglades Ecosystem requires this understanding of the hydrology of the natural system prior to significant alterations due to water management and land use. Large scale models such as the Natural Systems Model (NSM 4.6.2) have been used by the South Florida Water Management District and other agencies responsible for restoration to estimate past hydrologic conditions; however, these models typically portray a drier natural system for the beginning of the 20th century than what is indicated by paleoecologic analyses and historical data. The purpose of this study is to estimate pre-20th century water levels, hydroperiods and flow in the freshwater wetlands of the Everglades by using pollen assemblage data in three sediment cores to adjust the Natural Systems Model. This study is designed to further test estimates of flow through the Everglades derived from analysis of sediment cores collected in Florida Bay. The results demonstrate that the NSM 4.6.2 underestimates water levels and hydroperiods in the Everglades compared to the paleo-adjusted NSM 4.6.2 model outputs. Flow models that use the paleo-adjusted water levels as input indicate flow through Shark River Slough in the late 19th century was approximately two times flow between 1990 and 2000, and flow through Taylor Slough was approximately three times flow between 1990 and 2000. The flow estimates derived from this study agree with the estimates derived from earlier studies using estuarine cores. This integration of paleoecologic information and hydrologic models provides resource managers with the best available estimates of past conditions and allows them to set realistic targets for restoration of freshwater ecosystems.","language":"English","publisher":"Frontiers","doi":"10.3389/fenvs.2020.00003","usgsCitation":"Marshall, F.E., Bernhardt, C.E., and Wingard, G.L., 2020, Estimating late 19th century hydrology in the Greater Everglades Ecosystem: An integration of paleoecologic data and models: Frontiers in Environmental Science, v. 8, no. 3, 21 p., https://doi.org/10.3389/fenvs.2020.00003.","productDescription":"21 p.","ipdsId":"IP-099728","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":457934,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2020.00003","text":"Publisher Index Page"},{"id":372206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.58447265624999,\n 25.110471486223346\n ],\n [\n -80.2716064453125,\n 25.110471486223346\n ],\n [\n -80.2716064453125,\n 25.903703303407667\n ],\n [\n -81.58447265624999,\n 25.903703303407667\n ],\n [\n -81.58447265624999,\n 25.110471486223346\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Marshall, Frank E.","contributorId":222355,"corporation":false,"usgs":false,"family":"Marshall","given":"Frank","email":"","middleInitial":"E.","affiliations":[{"id":40533,"text":"Cetacean Logic Foundation","active":true,"usgs":false}],"preferred":false,"id":781946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernhardt, Christopher E. 0000-0003-0082-4731 cbernhardt@usgs.gov","orcid":"https://orcid.org/0000-0003-0082-4731","contributorId":2131,"corporation":false,"usgs":true,"family":"Bernhardt","given":"Christopher","email":"cbernhardt@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":781947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wingard, G. Lynn 0000-0002-3833-5207 lwingard@usgs.gov","orcid":"https://orcid.org/0000-0002-3833-5207","contributorId":605,"corporation":false,"usgs":true,"family":"Wingard","given":"G.","email":"lwingard@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":781945,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208119,"text":"sir20195148 - 2020 - A system design for implementing advanced feature descriptions for a map knowledge base","interactions":[],"lastModifiedDate":"2020-01-31T06:30:23","indexId":"sir20195148","displayToPublicDate":"2020-01-30T17:09:24","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5148","displayTitle":"A System Design for Implementing Advanced Feature Descriptions for a Map Knowledge Base","title":"A system design for implementing advanced feature descriptions for a map knowledge base","docAbstract":"

A prototype system to explore Linked Data that semantically integrates geospatial data in various formats from different publication sources with data from The National Map of the U.S. Geological Survey is presented. The focus is on accessing advanced feature descriptions for data from The National Map with data coreferenced from other sources. The prototype uses Geoserver to access The National Map data, which are converted to Resource Description Framework triples using Karma and stored in the Marmotta triplestore. Marmotta uses a Postgres relational database as a backend for the project and queries to the Marmotta triplestore are converted to structured query language and executed by Postgres. Triples retrieved are linked with same_as relationships to external data sources. The links to these sources provide additional attributes and relationships of the data from The National Map. Visualization of the results is provided using Leaflet and workflows for all parts of the system are defined. A use case for the system is provided to access structures and names information from The National Map for the Washington, D.C., area and link these to Geonames data, with visualization of the graphical and tabular results.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195148","usgsCitation":"Wagner, M., Varanka, D.E., and Usery, E.L., 2020, A system design for implementing advanced feature descriptions for a map knowledge base: U.S. Geological Survey Scientific Investigations Report 2019–5148, 25 p., https://doi.org/10.3133/sir20195148. ","productDescription":"viii, 25 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-111001","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":371735,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5148/coverthb.jpg"},{"id":371736,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5148/sir20195148.pdf","text":"Report","size":"3.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5148"}],"contact":"

Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-01-30","noUsgsAuthors":false,"publicationDate":"2020-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Wagner, Matthew 0000-0002-3987-072X","orcid":"https://orcid.org/0000-0002-3987-072X","contributorId":221861,"corporation":false,"usgs":false,"family":"Wagner","given":"Matthew","affiliations":[{"id":40445,"text":"Student contractor to the U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":780557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Varanka, Dalia E. 0000-0003-2857-9600 dvaranka@usgs.gov","orcid":"https://orcid.org/0000-0003-2857-9600","contributorId":1296,"corporation":false,"usgs":true,"family":"Varanka","given":"Dalia","email":"dvaranka@usgs.gov","middleInitial":"E.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":780556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Usery, E. Lynn 0000-0002-2766-2173 usery@usgs.gov","orcid":"https://orcid.org/0000-0002-2766-2173","contributorId":231,"corporation":false,"usgs":true,"family":"Usery","given":"E.","email":"usery@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":780882,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208330,"text":"70208330 - 2020 - A geospatially resolved wetland vulnerability index: Synthesis of physical drivers","interactions":[],"lastModifiedDate":"2020-02-04T15:36:39","indexId":"70208330","displayToPublicDate":"2020-01-30T15:30:57","publicationYear":"2020","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":"A geospatially resolved wetland vulnerability index: Synthesis of physical drivers","docAbstract":"Assessing wetland vulnerability to chronic and episodic physical drivers is fundamental\nfor establishing restoration priorities. We synthesized multiple data sets from E.B\nForsythe National Wildlife Refuge, New Jersey, to establish a wetland vulnerability\nmetric that integrates a range of physical processes, regulatory information and\nphysical/biophysical features. The geospatial data are based on aerial imagery, remote\nsensing, regulatory information, and hydrodynamic modeling, and include elevation,\ntidal range, unvegetated to vegetated marsh ratio (UVVR), shoreline erosion, potential\nexposure to contaminants, residence time, marsh condition change, change in salinity\nand salinity exposure, and sediment concentration. First, we delineated the wetland\ncomplex into individual marsh units based on surface contours and then defined a\nwetland vulnerability index that combined contributions from all parameters. We\napplied principal component and cluster analyses to explore the interrelations between\nthe data layers and separate regions that exhibited common characteristics. Our\nanalysis shows that the spatial variation of vulnerability in this domain cannot be\nexplained satisfactorily by a smaller subset of the variables. The most influential factor\non the vulnerability index was the combined effect of elevation, tide range, residence\ntime, and UVVR. Tide range and residence time had the highest correlation, and\nsimilar bay-wide spatial variation. Some variables (e.g., shoreline erosion) had no\nsignificant correlation with the rest of the variables. The aggregated index based on the\ncomplete dataset allows us to assess the overall state of a given marsh unit and quickly\nlocate the most vulnerable units in a larger marsh complex. The application of\ngeospatially complete datasets and consideration of chronic and episodic physical drivers\nrepresents an advance over traditional point-based methods for wetland assessment.","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0228504","usgsCitation":"Defne, Z., Aretxabaleta, A., Ganju, N., Kalra, T., Jones, D.K., and Smith, K., 2020, A geospatially resolved wetland vulnerability index: Synthesis of physical drivers: PLoS ONE, v. 15, no. 1, e0228504, 27 p., https://doi.org/10.1371/journal.pone.0228504.","productDescription":"e0228504, 27 p.","ipdsId":"IP-109605","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":457943,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0228504","text":"Publisher Index Page"},{"id":372025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"E.B. Forsythe National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.476318359375,\n 39.37889504706486\n ],\n [\n -74.0478515625,\n 39.37889504706486\n ],\n [\n -74.0478515625,\n 40.1095880747414\n ],\n [\n -74.476318359375,\n 40.1095880747414\n ],\n [\n -74.476318359375,\n 39.37889504706486\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"1","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":781431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aretxabaleta, Alfredo 0000-0002-9914-8018 aaretxabaleta@usgs.gov","orcid":"https://orcid.org/0000-0002-9914-8018","contributorId":140090,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo","email":"aaretxabaleta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":781432,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":781434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":781433,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Daniel K. 0000-0003-0724-8001 dkjones@usgs.gov","orcid":"https://orcid.org/0000-0003-0724-8001","contributorId":4959,"corporation":false,"usgs":true,"family":"Jones","given":"Daniel","email":"dkjones@usgs.gov","middleInitial":"K.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781435,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Kathryn E.L. 0000-0002-7521-7875 kelsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-7521-7875","contributorId":173264,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E.L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":781436,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70207582,"text":"sir20195150 - 2020 - Numerical simulation of groundwater availability in central Moloka‘i, Hawai‘i","interactions":[],"lastModifiedDate":"2022-04-25T20:32:20.678493","indexId":"sir20195150","displayToPublicDate":"2020-01-30T12:22:46","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5150","displayTitle":"Numerical Simulation of Groundwater Availability in Central Moloka‘i, Hawai‘i","title":"Numerical simulation of groundwater availability in central Moloka‘i, Hawai‘i","docAbstract":"

Since the 1990s, increased chloride concentrations of water pumped from wells (much of which is used for drinking water) and the effects of withdrawals on groundwater-dependent ecosystems have led to concerns over groundwater availability on the island of Molokaʻi, Hawaiʻi. An improved understanding of the hydrologic effects of proposed groundwater withdrawals is needed to ensure effective management of the groundwater resources of Molokaʻi, plan for possible growth, and accommodate cultural, social, and economic concerns. To address the information needs of managers and community stakeholders on Molokaʻi, the U.S. Geological Survey developed a numerical groundwater model capable of simulating salinity change and reduction in groundwater discharge in coastal areas of central and southern Molokaʻi. Estimates of groundwater recharge needed as input to the numerical groundwater model were made using a daily water budget for each decade during 1940−2012 (the period 2000−12 spanned 13 years) and the most current available data, including the distributions of monthly rainfall and potential evapotranspiration. Total island recharge during the decadal periods ranged from a low of about 189 Mgal/d during the 1970s to a high of 278 Mgal/d during the 1960s. These recharge estimates were used to develop an island-wide numerical groundwater model with simplifying assumptions (sharp interface between freshwater and saltwater; two-dimensional flow). The island-wide model provided estimates of groundwater inflows to the main area of interest simulated with a three-dimensional numerical groundwater model. Simulated withdrawal scenarios were selected in consultation with water managers and stakeholders and consisted of: (1) a baseline scenario using average recharge (1978−2007 rainfall and 2010 land cover) and average 2016−17 withdrawals; (2) a scenario using average recharge and withdrawals from existing wells at pending (as of January 2019) water-use permit rates; (3) six scenarios using average recharge and selected withdrawals from existing and proposed wells; and (4) a scenario using reduced recharge and selected withdrawals from existing and proposed wells. Results of the simulated withdrawal scenarios indicate that wells may be capable of producing groundwater with chloride concentrations below 250 mg/L at withdrawal rates exceeding average 2016−17 rates. However, the quality of water withdrawn from production wells is dependent on the rate and distribution of the withdrawals. For all nonbaseline scenarios, simulated groundwater discharge to the nearshore environment is reduced relative to the baseline scenario. Areas of discharge reduction may correspond to areas used for cultural or subsistence purposes. The three-dimensional numerical groundwater model developed for this study utilizes the latest available hydrologic and geologic information and is a useful tool for understanding the hydrologic effects of additional groundwater withdrawals in central Molokaʻi. The model has several limitations, including its nonuniqueness and inability to account for local-scale heterogeneities.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195150","collaboration":"Prepared in cooperation with the State of Hawai‘i Department of Hawaiian Home Lands, State of Hawai‘i Office of Hawaiian Affairs, and County of Maui Department of Water Supply","usgsCitation":"Oki, D.S., Engott, J.A., and Rotzoll, K., 2020, Numerical simulation of groundwater availability in central Moloka‘i, Hawai‘i: U.S. Geological Survey Scientific Investigations Report 2019–5150, 95 p., https://doi.org/10.3133/sir20195150.","productDescription":"Report: ix, 95 p.; Data Release","numberOfPages":"95","onlineOnly":"Y","ipdsId":"IP-032683","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":399622,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109628.htm"},{"id":371721,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HRQASS","linkHelpText":"Central Molokaʻi, Hawaiʻi, SUTRA model"},{"id":371719,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5150/coverthb.jpg"},{"id":371720,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5150/sir20195150.pdf","text":"Report","size":"40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5150"}],"country":"United States","state":"Hawaii","otherGeospatial":"Moloka‘i","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.77352905273438,\n 21.179289725795993\n ],\n [\n -156.8572998046875,\n 21.163922551671376\n ],\n [\n -156.92184448242188,\n 21.167764494849468\n ],\n [\n -156.97265625,\n 21.211299542246586\n ],\n [\n -156.99737548828125,\n 21.189533621502626\n ],\n [\n -157.1429443359375,\n 21.199776807250093\n ],\n [\n -157.21298217773435,\n 21.220261047755002\n ],\n [\n -157.25830078125,\n 21.218980865996457\n ],\n [\n -157.25555419921875,\n 21.17672864097083\n ],\n [\n -157.2967529296875,\n 21.14599216495789\n ],\n [\n -157.30499267578125,\n 21.097313035028538\n ],\n [\n -157.18826293945312,\n 21.090906697412837\n ],\n [\n -157.08801269531247,\n 21.103719096296263\n ],\n [\n -157.03582763671875,\n 21.090906697412837\n ],\n [\n -156.90811157226562,\n 21.051181240269393\n ],\n [\n -156.84906005859375,\n 21.047336278183312\n ],\n [\n -156.77215576171875,\n 21.08450008351735\n ],\n [\n -156.70074462890625,\n 21.15879980561845\n ],\n [\n -156.77352905273438,\n 21.179289725795993\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818

","tableOfContents":"

","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2020-01-30","noUsgsAuthors":false,"publicationDate":"2020-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Oki, Delwyn S. 0000-0002-6913-8804","orcid":"https://orcid.org/0000-0002-6913-8804","contributorId":221122,"corporation":false,"usgs":true,"family":"Oki","given":"Delwyn","email":"","middleInitial":"S.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":778606,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engott, John A. 0000-0003-1889-4519 jaengott@usgs.gov","orcid":"https://orcid.org/0000-0003-1889-4519","contributorId":1142,"corporation":false,"usgs":true,"family":"Engott","given":"John","email":"jaengott@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":778607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rotzoll, Kolja 0000-0002-5910-888X kolja@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-888X","contributorId":3325,"corporation":false,"usgs":true,"family":"Rotzoll","given":"Kolja","email":"kolja@usgs.gov","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":false,"id":778608,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70209826,"text":"70209826 - 2020 - Climate relationships with increasing wildfire in the southwestern US from 1984 to 2015","interactions":[],"lastModifiedDate":"2020-04-30T12:22:10.730349","indexId":"70209826","displayToPublicDate":"2020-01-30T07:17:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Climate relationships with increasing wildfire in the southwestern US from 1984 to 2015","docAbstract":"Over the last several decades in forest and woodland ecosystems of the southwestern United States, wildfire size and severity have increased, thereby increasing the vulnerability of these systems to type conversions, invasive species, and other disturbances. A combination of land use history and climate change is widely thought to be contributing to the changing fire regimes. We examined climate-fire relationships in forest and woodland ecosystems from 1984 – 2015 in Arizona and New Mexico using 1) an expanded satellite-derived burn severity dataset that incorporates over one million additional burned hectares when compared to MTBS data, and 2) climate variables including temperature, precipitation, and vapor pressure deficit (VPD). Regional climate-fire relationships were assessed by correlating annual area burned, area burned at high and low severity, and percent high severity with fire season (May-August) and water-year (October-September) climate variables. We also analyzed relationships between climate and high-severity fire at the scale of the individual fires using a hurdle model. We found that increasing temperature and VPD and decreasing precipitation were associated with increasing area burned regionally, and that area burned at high severity had the strongest relationships with climate metrics. The relationship between climate and fire activity in the Southwest appears to be strengthening since 2000. VPD-fire correlations were consistently as strong as, or stronger than, temperature or precipitation variables alone, both regionally and at the scale of the individual fires. Notably, at the scale of the individual fires, temperature and precipitation were not significant predictors of fire activity. Thus, our results support the use of VPD as a more integrative climate metric to forecast fire activity. We suggest that the strong relationship between VPD and fire activity may be useful to assess the likelihood of high-severity fire occurrence through continued development of the high-severity fire threshold model we present. The link between increasing aridity and increasing wildfire activity suggests a future with more fire in Southwest forests and woodlands with projected warming, underscoring the urgency of restoration in dry forests to reduce the likelihood of uncharacteristic, large high-severity fires.","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2019.117861","collaboration":"","usgsCitation":"Mueller, S., Thode, A.E., Margolis, E.Q., Yocom, L., Young, J.M., and Iniguez, J.M., 2020, Climate relationships with increasing wildfire in the southwestern US from 1984 to 2015: Forest Ecology and Management, v. 460, no. , https://doi.org/10.1016/j.foreco.2019.117861.","productDescription":"117861, 14 p.","startPage":"","ipdsId":"IP-109702","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":457950,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Center","active":true,"usgs":true}],"preferred":true,"id":788189,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yocom, Larissa","contributorId":224404,"corporation":false,"usgs":false,"family":"Yocom","given":"Larissa","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":788190,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Young, Jesse M.","contributorId":199828,"corporation":false,"usgs":false,"family":"Young","given":"Jesse","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":788191,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Iniguez, Jose M. 0000-0002-4566-1297","orcid":"https://orcid.org/0000-0002-4566-1297","contributorId":213972,"corporation":false,"usgs":false,"family":"Iniguez","given":"Jose","email":"","middleInitial":"M.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":788192,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228631,"text":"70228631 - 2020 - Upper plate heterogeneity along the Southern Hikurangi Margin, New Zealand","interactions":[],"lastModifiedDate":"2022-02-15T12:50:52.660668","indexId":"70228631","displayToPublicDate":"2020-01-30T06:45:37","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Upper plate heterogeneity along the Southern Hikurangi Margin, New Zealand","docAbstract":"

Controlled and natural source seismic data are used to build a 3-D P wave model for southern North Island, New Zealand, where the Pacific Plate subducts beneath the Australian Plate at a rate of ~41 mm/year. Our analysis reveals an abrupt along-strike transition in overthrusting plate structure within Cook Strait. Contrasts in properties (Vp, Vp/Vs, and Qs) likely reflects the degree of deformation in the Australian Plate, where the Alpine-Wairau and Awatere Faults mark the northern boundary of a terrane that has undergone >50° of clockwise vertical-axis rotation since the early Miocene. Heterogeneity of the crustal transition is likely associated with changes in frictional and elastic properties that may impact elastic stress accumulation and inhibit southward propagation of megathrust earthquakes. Low connectivity of faults in Cook Strait is consistent with the heterogeneity we observe and may promote complex earthquake triggering by lateral stress loading during earthquakes or slow slip events.

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