{"pageNumber":"350","pageRowStart":"8725","pageSize":"25","recordCount":41079,"records":[{"id":70204785,"text":"70204785 - 2019 - Integrating magnetotellurics, soil gas geochemistry and structural analysis to identify hidden, high enthalpy, extensional geothermal systems","interactions":[],"lastModifiedDate":"2019-08-16T11:44:10","indexId":"70204785","displayToPublicDate":"2019-03-01T11:43:38","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"title":"Integrating magnetotellurics, soil gas geochemistry and structural analysis to identify hidden, high enthalpy, extensional geothermal systems","docAbstract":"We applied magnetotellurics (MT), diagnostic structural affiliations, soil gas flux, and fluid geochemistry to assist in identifying hidden, high-enthalpy geothermal systems in extensional regimes of the U.S. Great Basin. We are specifically looking for high-angle, low-resistivity zones and dilatant geologic structures that can carry fluids from magmatic or high-grade metamorphic conditions in the deep crust upward to exploitable depths, and to verify the nature of the deep sources through soil gas and fluid compositions. The project was motivated by prior MT transect coverage of western and central Nevada centered upon the Dixie Valley producing geothermal system where such favorable indicators were first recognized. The high-angle MT structures are taken to be fluidized fault zones connecting deep magmatic/metamorphic activity with the geothermal system, but the concept required verification by testing at other systems.\nThe project was set up with a two-phased organization. Phase I was carried out at the McGinness Hills system, central Nevada, where Ormat Inc flagship power facility is located and a considerable amount of pre-existing data were available. Resistivity models along MT transects also showed a strong low-resistivity upwelling originating from interpreted deep crustal magmatic underplating. Controlling structures on production as indicated by Ormat data and our new mapping were favorable to dilatancy, comprising an accommodation zone between major normal faults of opposing dip. A 3D MT survey and inversion confirmed the existence of the steep low-resistivity zone dipping ESE toward the deep crust and placed N-S bounds upon the feature. In cooperation with Ormat personnel, we sampled well fluids from production intervals for He isotope composition. Elevated 3He was verified through mass spectrometry analysis confirming a magmatic connection with the producing system. High CO2 soil gas flux including possibly metamorphic 13C and 14C component was measured over the area of dilatant structures. Hence, the triad of indicators posed above was confirmed in Phase I.\nSubsequently, Phase II of the project proceeded in the greenfield Kumiva-Blackrock Desert district of northwestern Nevada to see if a new system could be identified. Transect MT data also showed a low-resistivity upwelling originating from interpreted deep crustal magmatic underplating. An MT survey of 131 sites was imaged through 3D inversion using an in-house, DOE-supported finite element algorithm. Low resistivity upwellings that warranted follow up study occur under the flanks of the Seven Troughs Range, under Kumiva Playa immediately west of the Blue Wing Mountains, and under northern Granite Springs Valley. Structural assessment of the project area by Co-I J. Faulds at UNR provided numerous favorable Quaternary fault settings, which were correlated to the MT upwelling structures. Soil CO2 gas flux anomalies generally were not large but did show correlation with resistivity upwelling structure and favorable geological structures. Isotope analyses showed presence of possible inorganic/metamorphic 13C but 14C concentrations did not exceed background values.\nWe view the initial concept of a confluence of low-resistivity upwelling, favorably dilatant 3D geological structure, and elevated soil gas flux including 13C component to be supported by the further evidence of this project although the indicators in the Phase II study were more diffuse. Mass balance calculations based upon 3He R/Ra values indicates that the proportion of magmatic fluids in a producing system is fairly low, 10-15% by volume. We suggest that the diagnostic MT geophysical structures denote zones of concentrated extensional deformation that increases permeability, potentially enabling a circulating upper crustal geothermal system, while at the same time connecting telltale deep component signatures to the upper crust. The northern Granite Springs Valley structure is receiving followup stu","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings, 44nd Workshop on Geothermal Reservoir Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Stanford Geothermal Conference","conferenceDate":"Feb 11-13, 2019","language":"English","publisher":"Stanford Universtiy","usgsCitation":"Philip E. Wannamaker, Faulds, J.E., B. Mack Kennedy, Maris, V., Siler, D.L., Craig Ulrich, and Moore, J., 2019, Integrating magnetotellurics, soil gas geochemistry and structural analysis to identify hidden, high enthalpy, extensional geothermal systems, <i>in</i> Proceedings, 44nd Workshop on Geothermal Reservoir Engineering, v. 44, Feb 11-13, 2019, SGP-TR-214, 19 p.","productDescription":"SGP-TR-214, 19 p.","ipdsId":"IP-104742","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":366604,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":366576,"type":{"id":15,"text":"Index Page"},"url":"https://pangea.stanford.edu/ERE/db/IGAstandard/record_detail.php?id=29105"}],"country":"United States","state":"Nevada","otherGeospatial":"McGinness Hills","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.39715576171875,\n              39.31942523123949\n            ],\n            [\n              -116.224365234375,\n              39.31942523123949\n            ],\n            [\n              -116.224365234375,\n              39.87601941962116\n            ],\n            [\n              -117.39715576171875,\n              39.87601941962116\n            ],\n            [\n              -117.39715576171875,\n              39.31942523123949\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"44","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Philip E. Wannamaker","contributorId":218146,"corporation":false,"usgs":false,"family":"Philip E. Wannamaker","affiliations":[{"id":39762,"text":"EGI/University of Utah","active":true,"usgs":false}],"preferred":false,"id":768472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faulds, James E","contributorId":218147,"corporation":false,"usgs":false,"family":"Faulds","given":"James","email":"","middleInitial":"E","affiliations":[{"id":39739,"text":"Nevada Bureau of Mines and Geology, University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":768473,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"B. Mack Kennedy","contributorId":218148,"corporation":false,"usgs":false,"family":"B. Mack Kennedy","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":768474,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maris, Virginie","contributorId":218149,"corporation":false,"usgs":false,"family":"Maris","given":"Virginie","email":"","affiliations":[{"id":39762,"text":"EGI/University of Utah","active":true,"usgs":false}],"preferred":false,"id":768475,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Siler, Drew L. 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":203341,"corporation":false,"usgs":true,"family":"Siler","given":"Drew","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":768471,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Craig Ulrich","contributorId":218150,"corporation":false,"usgs":false,"family":"Craig Ulrich","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":768476,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moore, Joseph","contributorId":218163,"corporation":false,"usgs":false,"family":"Moore","given":"Joseph","affiliations":[],"preferred":false,"id":768501,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70202437,"text":"70202437 - 2019 - Microclimate influences mangrove freeze damage: Implications for range expansion in response to changing macroclimate","interactions":[],"lastModifiedDate":"2019-06-18T10:27:40","indexId":"70202437","displayToPublicDate":"2019-03-01T10:39:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Microclimate influences mangrove freeze damage: Implications for range expansion in response to changing macroclimate","docAbstract":"<p><span>In response to warming winter air temperatures, freeze-sensitive mangrove forests are expected to expand at the expense of freeze-tolerant salt marshes. To better anticipate and prepare for mangrove range expansion, there is a need to advance understanding of the modulating role of microclimate. Here, we synthesized hypotheses regarding the effects of microclimatic variation on temperature gradients and mangrove freeze damage. Temperature data from the literature and from temperature loggers were used to quantify ecologically relevant temperature gradients. Then, literature-derived mangrove freeze damage data were used to quantify the ecological effects of these temperature gradients. Six microclimatic factors are described that produce air temperature gradients that modulate mangrove responses to winter temperature extremes: (1) distance from the ocean; (2) distance from wind buffers; (3) mangrove canopy cover; (4) height above the soil surface; (5) local slope concavity; and (6) tidal inundation. Variation in these factors produces local temperature differences that range from 2 to 14&nbsp;°C, with concomitant effects on horizontal and vertical patterns of biological damage from freezing. Collectively, our results elucidate the influence of microclimate on spatial patterns of biological damage and mortality due to winter temperature extremes. As mangrove ranges expand in response to climate change, we anticipate that microclimatic variation will produce adverse environments where mangrove expansion is prohibited as well as expansion hot spots where mangroves are protected. Subsequent expansion into newly available habitat will occur from protection zones, and microclimatic gradients may even produce positive feedback cycles that ultimately accelerate the rate of range expansion in response to warming.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s12237-019-00533-1","usgsCitation":"Osland, M.J., Hartmann, A.M., Day, R.H., Ross, M.S., Hall, C., Feher, L.C., and Vervaeke, W., 2019, Microclimate influences mangrove freeze damage: Implications for range expansion in response to changing macroclimate: Estuaries and Coasts, v. 42, no. 4, p. 1084-1096, https://doi.org/10.1007/s12237-019-00533-1.","productDescription":"13 p.","startPage":"1084","endPage":"1096","ipdsId":"IP-098812","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":437551,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YWSV4O","text":"USGS data release","linkHelpText":"Microclimate influences mangrove freeze damage: Implications for range expansion in response to changing macroclimate"},{"id":361637,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"4","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Osland, Michael J. 0000-0001-9902-8692 mosland@usgs.gov","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":3080,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","email":"mosland@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":758506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartmann, Arik M.","contributorId":213401,"corporation":false,"usgs":false,"family":"Hartmann","given":"Arik","email":"","middleInitial":"M.","affiliations":[{"id":38748,"text":"Hartmann Consulting Services at the U.S. Geological Survey, Wetland and Aquatic Research Center","active":true,"usgs":false}],"preferred":false,"id":758507,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day, Richard H. 0000-0002-5959-7054 dayr@usgs.gov","orcid":"https://orcid.org/0000-0002-5959-7054","contributorId":2427,"corporation":false,"usgs":true,"family":"Day","given":"Richard","email":"dayr@usgs.gov","middleInitial":"H.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":758508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ross, Michael S.","contributorId":202431,"corporation":false,"usgs":false,"family":"Ross","given":"Michael","email":"","middleInitial":"S.","affiliations":[{"id":36434,"text":"Florida International University, Miami, FL","active":true,"usgs":false}],"preferred":false,"id":758509,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hall, Courtney T. 0000-0003-0990-5212","orcid":"https://orcid.org/0000-0003-0990-5212","contributorId":176330,"corporation":false,"usgs":true,"family":"Hall","given":"Courtney T.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":758510,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Feher, Laura C. 0000-0002-5983-6190 lhundy@usgs.gov","orcid":"https://orcid.org/0000-0002-5983-6190","contributorId":176788,"corporation":false,"usgs":true,"family":"Feher","given":"Laura","email":"lhundy@usgs.gov","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":758511,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vervaeke, William 0000-0002-1518-5197 vervaekew@usgs.gov","orcid":"https://orcid.org/0000-0002-1518-5197","contributorId":3265,"corporation":false,"usgs":true,"family":"Vervaeke","given":"William","email":"vervaekew@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":758512,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70202442,"text":"70202442 - 2019 - Hillslope hydrology in global change research and earth system modeling","interactions":[],"lastModifiedDate":"2019-03-26T16:04:00","indexId":"70202442","displayToPublicDate":"2019-03-01T10:35:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Hillslope hydrology in global change research and earth system modeling","docAbstract":"<p><span>Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope‐scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid‐level water, energy, and biogeochemical fluxes. In contrast to the one‐dimensional (1‐D), 2‐ to 3‐m deep, and free‐draining soil hydrology in most ESM land models, we hypothesize that 3‐D, lateral ridge‐to‐valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018WR023903","usgsCitation":"Fan, Y., Clark, M., Lawrence, D.M., Swenson, S., Band, L.E., Brantley, S.L., Brooks, P.D., Dietrich, W.E., Flores, A., Grant, G., Kirchner, J.W., Mackay, D., McDonnell, J., Milly, P.C., Sullivan, P.L., Tague, C., Ajami, H., Chaney, N.W., Hartmann, A., Hazenberg, P., McNamara, J., Pelletier, J., Perket, J., Rouholahnejad-Freund, E., Wagener, T., Zeng, X., Beighley, E., Buzan, J., Huang, M., Livneh, B., Mohanty, B.P., Nijssen, B., Safeeq, M., Shen, C., van Verseveld, W., Volk, J., and Yamazaki, D., 2019, Hillslope hydrology in global change research and earth system modeling: Water Resources Research, v. 55, no. 2, p. 1737-1772, https://doi.org/10.1029/2018WR023903.","productDescription":"36 p.","startPage":"1737","endPage":"1772","ipdsId":"IP-102674","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":467856,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018wr023903","text":"Publisher Index Page"},{"id":361636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Fan, Ying","contributorId":213846,"corporation":false,"usgs":false,"family":"Fan","given":"Ying","email":"","affiliations":[{"id":38903,"text":"Rutgers Univ.","active":true,"usgs":false}],"preferred":false,"id":758550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Martyn","contributorId":176319,"corporation":false,"usgs":false,"family":"Clark","given":"Martyn","affiliations":[],"preferred":false,"id":758551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawrence, David M.","contributorId":105206,"corporation":false,"usgs":false,"family":"Lawrence","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":7166,"text":"Johns Hopkins University Applied Physics Laboratory","active":true,"usgs":false}],"preferred":false,"id":758552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swenson, Sean","contributorId":213847,"corporation":false,"usgs":false,"family":"Swenson","given":"Sean","email":"","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":758553,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Band, L. E.","contributorId":213848,"corporation":false,"usgs":false,"family":"Band","given":"L.","email":"","middleInitial":"E.","affiliations":[{"id":38904,"text":"Univ. Virginia","active":true,"usgs":false}],"preferred":false,"id":758554,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brantley, S. L.","contributorId":213849,"corporation":false,"usgs":false,"family":"Brantley","given":"S.","email":"","middleInitial":"L.","affiliations":[{"id":25381,"text":"Penn State Univ.","active":true,"usgs":false}],"preferred":false,"id":758555,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brooks, P. D.","contributorId":213850,"corporation":false,"usgs":false,"family":"Brooks","given":"P.","email":"","middleInitial":"D.","affiliations":[{"id":38905,"text":"Univ. Utah","active":true,"usgs":false}],"preferred":false,"id":758556,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dietrich, W. E.","contributorId":213851,"corporation":false,"usgs":false,"family":"Dietrich","given":"W.","email":"","middleInitial":"E.","affiliations":[{"id":38906,"text":"Univ. California Berkeley","active":true,"usgs":false}],"preferred":false,"id":758557,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Flores, A.","contributorId":213852,"corporation":false,"usgs":false,"family":"Flores","given":"A.","email":"","affiliations":[{"id":18083,"text":"Boise State Univ.","active":true,"usgs":false}],"preferred":false,"id":758558,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Grant, G.","contributorId":213853,"corporation":false,"usgs":false,"family":"Grant","given":"G.","affiliations":[{"id":16757,"text":"Oregon State Univ.","active":true,"usgs":false}],"preferred":false,"id":758559,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kirchner, J. W.","contributorId":213854,"corporation":false,"usgs":false,"family":"Kirchner","given":"J.","email":"","middleInitial":"W.","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":758560,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mackay, D. S.","contributorId":213855,"corporation":false,"usgs":false,"family":"Mackay","given":"D. S.","affiliations":[{"id":38907,"text":"SUNY Buffalo","active":true,"usgs":false}],"preferred":false,"id":758561,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McDonnell, J.J.","contributorId":168898,"corporation":false,"usgs":false,"family":"McDonnell","given":"J.J.","email":"","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":758562,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Milly, Paul C. D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":176836,"corporation":false,"usgs":true,"family":"Milly","given":"Paul","email":"cmilly@usgs.gov","middleInitial":"C. D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":false,"id":758549,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sullivan, P. L.","contributorId":213856,"corporation":false,"usgs":false,"family":"Sullivan","given":"P.","email":"","middleInitial":"L.","affiliations":[{"id":38908,"text":"Univ. Kansas","active":true,"usgs":false}],"preferred":false,"id":758563,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tague, C.","contributorId":213857,"corporation":false,"usgs":false,"family":"Tague","given":"C.","email":"","affiliations":[{"id":38909,"text":"Univ. California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":758564,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Ajami, H.","contributorId":213858,"corporation":false,"usgs":false,"family":"Ajami","given":"H.","affiliations":[{"id":38910,"text":"Univ. California Riverside","active":true,"usgs":false}],"preferred":false,"id":758565,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Chaney, N. W.","contributorId":209887,"corporation":false,"usgs":false,"family":"Chaney","given":"N.","email":"","middleInitial":"W.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":758566,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Hartmann, A.","contributorId":213859,"corporation":false,"usgs":false,"family":"Hartmann","given":"A.","email":"","affiliations":[{"id":38911,"text":"Universities of Freiburg","active":true,"usgs":false}],"preferred":false,"id":758567,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Hazenberg, P.","contributorId":213860,"corporation":false,"usgs":false,"family":"Hazenberg","given":"P.","email":"","affiliations":[{"id":24657,"text":"Univ. 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,{"id":70201001,"text":"70201001 - 2019 - Spatiotemporal remote sensing of ecosystem change and causation across Alaska","interactions":[],"lastModifiedDate":"2024-05-17T15:00:39.48988","indexId":"70201001","displayToPublicDate":"2019-03-01T10:33:02","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal remote sensing of ecosystem change and causation across Alaska","docAbstract":"<p><span>Contemporary climate change in Alaska has resulted in amplified rates of press and pulse disturbances that drive ecosystem change with significant consequences for socio‐environmental systems. Despite the vulnerability of Arctic and boreal landscapes to change, little has been done to characterize landscape change and associated drivers across northern high‐latitude ecosystems. Here we characterize the historical sensitivity of Alaska's ecosystems to environmental change and anthropogenic disturbances using expert knowledge, remote sensing data, and spatiotemporal analyses and modeling. Time‐series analysis of moderate—and high‐resolution imagery was used to characterize land‐ and water‐surface dynamics across Alaska. Some 430,000 interpretations of ecological and geomorphological change were made using historical air photos and satellite imagery, and corroborate land‐surface greening, browning, and wetness/moisture trend parameters derived from peak‐growing season Landsat imagery acquired from 1984 to 2015. The time series of change metrics, together with climatic data and maps of landscape characteristics, were incorporated into a modeling framework for mapping and understanding of drivers of change throughout Alaska. According to our analysis, approximately 13% (~174,000&nbsp;±&nbsp;8700&nbsp;km</span><sup>2</sup><span>) of Alaska has experienced directional change in the last 32&nbsp;years (±95% confidence intervals). At the ecoregions level, substantial increases in remotely sensed vegetation productivity were most pronounced in western and northern foothills of Alaska, which is explained by vegetation growth associated with increasing air temperatures. Significant browning trends were largely the result of recent wildfires in interior Alaska, but browning trends are also driven by increases in evaporative demand and surface‐water gains that have predominately occurred over warming permafrost landscapes. Increased rates of photosynthetic activity are associated with stabilization and recovery processes following wildfire, timber harvesting, insect damage, thermokarst, glacial retreat, and lake infilling and drainage events. Our results fill a critical gap in the understanding of historical and potential future trajectories of change in northern high‐latitude regions.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.14279","usgsCitation":"Pastick, N.J., Jorgenson, M., Goetz, S., Jones, B.M., Wylie, B.K., Minsley, B.J., Genet, H., Knight, J.F., Swanson, D.K., and Jorgenson, J.C., 2019, Spatiotemporal remote sensing of ecosystem change and causation across Alaska: Global Change Biology, v. 25, no. 3, p. 1171-1189, https://doi.org/10.1111/gcb.14279.","productDescription":"18 p.","startPage":"1171","endPage":"1189","ipdsId":"IP-096342","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":437552,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DV1J6N","text":"USGS data release","linkHelpText":"Probabilistic estimates of landscape change in Alaska (1984 to 2015)"},{"id":359597,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Torre","affiliations":[],"preferred":false,"id":751666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goetz, Scott J.","contributorId":22232,"corporation":false,"usgs":true,"family":"Goetz","given":"Scott J.","affiliations":[],"preferred":false,"id":751667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":751668,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":751669,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":751670,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Genet, Hélène","contributorId":195179,"corporation":false,"usgs":false,"family":"Genet","given":"Hélène","affiliations":[],"preferred":false,"id":751671,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Knight, Joseph F.","contributorId":55311,"corporation":false,"usgs":true,"family":"Knight","given":"Joseph","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":751672,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Swanson, David K.","contributorId":178902,"corporation":false,"usgs":false,"family":"Swanson","given":"David","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":751673,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jorgenson, Janet C.","contributorId":191903,"corporation":false,"usgs":false,"family":"Jorgenson","given":"Janet","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":751674,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70202444,"text":"70202444 - 2019 - Prediction of ice‐free conditions for a perennially ice‐covered Antarctic lake","interactions":[],"lastModifiedDate":"2019-03-26T16:04:41","indexId":"70202444","displayToPublicDate":"2019-03-01T10:31:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Prediction of ice‐free conditions for a perennially ice‐covered Antarctic lake","docAbstract":"<p><span>Although perennially ice‐covered Antarctic lakes have experienced variable ice thicknesses over the past several decades, future ice thickness trends and associated aquatic biological responses under projected global warming remain unknown. Heat stored in the water column in chemically stratified Antarctic lakes that have middepth temperature maxima can significantly influence the ice thickness trends via upward heat flux to the ice/water interface. We modeled the ice thickness of the west lobe of Lake Bonney, Antarctica, based on possible future climate scenarios utilizing a 1D thermodynamic model that accounts for surface radiative fluxes as well as the heat flux associated with the temperature evolution of the water column. Model results predict that the ice cover of Lake Bonney will shift from perennial to seasonal within one to four decades, a change that will drastically influence ecosystem processes within the lake.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JF004756","usgsCitation":"Obryk, M., Doran, P.T., and Priscu, J.C., 2019, Prediction of ice‐free conditions for a perennially ice‐covered Antarctic lake: Journal of Geophysical Research F: Earth Surface, v. 124, no. 2, p. 686-694, https://doi.org/10.1029/2018JF004756.","productDescription":"9 p.","startPage":"686","endPage":"694","ipdsId":"IP-097873","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467857,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jf004756","text":"Publisher Index Page"},{"id":361635,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Taylor Valley, McMurdo Dry Valleys, Antarctica","volume":"124","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Obryk, Maciej K. 0000-0002-8182-8656","orcid":"https://orcid.org/0000-0002-8182-8656","contributorId":203477,"corporation":false,"usgs":true,"family":"Obryk","given":"Maciej","middleInitial":"K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":758589,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doran, P. T.","contributorId":213879,"corporation":false,"usgs":false,"family":"Doran","given":"P.","email":"","middleInitial":"T.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":758590,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Priscu, J. C.","contributorId":213880,"corporation":false,"usgs":false,"family":"Priscu","given":"J.","email":"","middleInitial":"C.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":758591,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70202431,"text":"70202431 - 2019 - An improved mechanical owl for efficient capture of nesting raptors","interactions":[],"lastModifiedDate":"2019-03-01T10:28:12","indexId":"70202431","displayToPublicDate":"2019-03-01T10:28:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"An improved mechanical owl for efficient capture of nesting raptors","docAbstract":"<p><span>Scientific study of raptors often requires the use of a lure to capture individuals for marking or collecting various data and samples. Live lure owls in the genus&nbsp;</span><i>Bubo</i><span>&nbsp;are commonly used with mist nets or dho-gazas to trap nesting raptors, but the use of these live lures presents ethical, logistical, and financial challenges. Although owls mounted by taxidermists and mechanical owls have been used in place of a live bird, the success of these types of lures varies widely. We created a more realistic mechanical owl with a greater range of motion than previous models, and then tested the owl on six raptor species in a variety of habitats. For all but one species, capture rates using our mechanical owl were similar to or slightly higher than those reported in studies using live lure owls or previously designed mechanical owls. Time to capture of Northern Goshawks (</span><i>Accipiter gentilis</i><span>) was, on average, 8 min faster when using our mechanical owl compared to a live owl. Cost analysis revealed that both the initial expense and long-term maintenance of a mechanical owl were less than that of a live lure owl. Mechanical owls can be a useful tool for capturing raptors. Although there are some drawbacks to using a mechanical owl, our results suggest that mechanical birds are comparable to live lure owls and we believe the benefits of using a mechanical owl often outweigh the costs.</span></p>","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-18-30","usgsCitation":"Jensen, M.K., Hamburg, S.D., Rota, C.T., Brinker, D.F., Coles, D.L., Manske, M.A., Slabe, V.A., Stuber, M.J., Welsh, A.B., and Katzner, T., 2019, An improved mechanical owl for efficient capture of nesting raptors: Journal of Raptor Research, v. 53, no. 1, p. 14-25, https://doi.org/10.3356/JRR-18-30.","productDescription":"12 p.","startPage":"14","endPage":"25","ipdsId":"IP-096341","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":467858,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3356/jrr-18-30","text":"Publisher Index Page"},{"id":361634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jensen, Meghan K.","contributorId":213759,"corporation":false,"usgs":false,"family":"Jensen","given":"Meghan","email":"","middleInitial":"K.","affiliations":[{"id":38849,"text":"West VA University","active":true,"usgs":false}],"preferred":false,"id":758426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hamburg, Shanti D.","contributorId":213760,"corporation":false,"usgs":false,"family":"Hamburg","given":"Shanti","email":"","middleInitial":"D.","affiliations":[{"id":38849,"text":"West VA University","active":true,"usgs":false}],"preferred":false,"id":758427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rota, Christopher T.","contributorId":213761,"corporation":false,"usgs":false,"family":"Rota","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":38849,"text":"West VA University","active":true,"usgs":false}],"preferred":false,"id":758428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brinker, David F.","contributorId":207103,"corporation":false,"usgs":false,"family":"Brinker","given":"David","email":"","middleInitial":"F.","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":758429,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coles, Dustin L.","contributorId":213762,"corporation":false,"usgs":false,"family":"Coles","given":"Dustin","email":"","middleInitial":"L.","affiliations":[{"id":38849,"text":"West VA University","active":true,"usgs":false}],"preferred":false,"id":758430,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Manske, Mark A.","contributorId":213763,"corporation":false,"usgs":false,"family":"Manske","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":38850,"text":"Paul Smiths College","active":true,"usgs":false}],"preferred":false,"id":758431,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Slabe, Vincent A.","contributorId":213764,"corporation":false,"usgs":false,"family":"Slabe","given":"Vincent","email":"","middleInitial":"A.","affiliations":[{"id":38849,"text":"West VA University","active":true,"usgs":false}],"preferred":false,"id":758432,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stuber, Matthew J.","contributorId":213765,"corporation":false,"usgs":false,"family":"Stuber","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":758433,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Welsh, Amy B.","contributorId":192239,"corporation":false,"usgs":false,"family":"Welsh","given":"Amy","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":758434,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":758425,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70204631,"text":"70204631 - 2019 - Principles of translational science education","interactions":[],"lastModifiedDate":"2019-08-07T09:58:03","indexId":"70204631","displayToPublicDate":"2019-03-01T09:56:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Principles of translational science education","docAbstract":"In a recent special issue in Frontiers in Ecology and the Environment,\nEnquist et al. (2017) present a welcome streamlining of modern applied\necology emphasizing a collaborative approach to applied ecological\nresearch involving resource-managers and scientists to produce actionable\nscience: translational ecology (TE). The authors, including ecologists, social\nscientists, and conservation professionals, identified six principles defining\nthe practice of translational ecology: collaboration, engagement,\ncommitment, communication, process, and framing (Figure 1). In thinking\nabout how science education can be enhanced by directly involving\nresearchers in science education, we recognized remarkable overlap\nbetween the principles of translational ecology (Enquist et al. 2017) and a\nframework for developing mutually beneficial integrative partnerships\nbetween scientists and educators. Here, we describe scientist-educator\nanalogies of the six principles of translational ecology: translational science\neducation (TSE).","language":"English","publisher":"Ecological Society of America","doi":"10.1002/fee.2007","usgsCitation":"Sutherland, C., Padilla, B., and Campbell Grant, E.H., 2019, Principles of translational science education: Frontiers in Ecology and Evolution, v. 17, no. 2, p. 82-84, https://doi.org/10.1002/fee.2007.","productDescription":"3 p.","startPage":"82","endPage":"84","ipdsId":"IP-096063","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":366330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sutherland, Chris","contributorId":150670,"corporation":false,"usgs":false,"family":"Sutherland","given":"Chris","affiliations":[],"preferred":false,"id":767843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Padilla, B","contributorId":217935,"corporation":false,"usgs":false,"family":"Padilla","given":"B","email":"","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":767844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":767842,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70227748,"text":"70227748 - 2019 - Factors influencing anuran wetland occupancy in an agricultural landscape","interactions":[],"lastModifiedDate":"2022-01-28T15:45:44.931393","indexId":"70227748","displayToPublicDate":"2019-03-01T09:30:13","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1892,"text":"Herpetologica","active":true,"publicationSubtype":{"id":10}},"title":"Factors influencing anuran wetland occupancy in an agricultural landscape","docAbstract":"<p>Habitat disturbance is an important cause of global amphibian declines, with especially strong effects in areas of high agricultural use. Determining the influence of site characteristics on amphibian presence and success is vital to developing effective conservation strategies. We used occupancy analysis to estimate presence of four anuran species at wetlands in northern Iowa as a function of eight environmental covariates hypothesized to affect occupancy: fish and salamander abundance, invertebrate density, aquatic vegetative cover, wetland area, atrazine concentration in water, surrounding agricultural land use, and an overall wetland health score (wetland condition index [WCI]). We surveyed 27 wetlands multiple times in 2015 and 2016. Leopard Frogs (<i>Lithobates pipiens</i>) and American Toads (<i>Anaxyrus americanus</i>) were observed at 100% of the sites, Boreal Chorus Frogs (<i>Pseudacris maculata</i>) at 96%, and Gray Treefrogs (<i>Hyla</i><span>&nbsp;</span>spp.) at 81%. Wetland site occupancy for all species in our study ranged from 0.23 (<i>Hyla</i><span>&nbsp;</span>spp. tadpoles) to 0.95 (<i>L. pipiens</i><span>&nbsp;</span>adults), indicating that agricultural wetlands can provide refuge or habitat for amphibians. Fish abundance, percentage of cropland cover within 500 m of the wetland, and salamander abundance were among the variables best supported by our models although their estimated effects were weak. Wetland area, atrazine concentration, vegetative cover, and WCI also influenced occupancy probability, but for only a small number of species and life stages. The direction of predicted effects varied by species and life stage. Despite only weak evidence that the environmental factors we measured influenced anuran occupancy, our results provide insights for managers seeking to understand how amphibians use landscapes modified by agriculture.</p>","language":"English","publisher":"Allen Press","doi":"10.1655/HERPETOLOGICA-D-18-00013.1","usgsCitation":"Swanson, J.E., Pierce, C., Dinsmore, S., Smalling, K., Vandever, M.W., Stewart, T.W., and Muths, E., 2019, Factors influencing anuran wetland occupancy in an agricultural landscape: Herpetologica, v. 75, no. 1, p. 47-56, https://doi.org/10.1655/HERPETOLOGICA-D-18-00013.1.","productDescription":"10 p.","startPage":"47","endPage":"56","ipdsId":"IP-090725","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":350,"text":"Iowa Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true},{"id":470,"text":"New Jersey Water Science 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]\n}","volume":"75","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Swanson, Jennifer E.","contributorId":140894,"corporation":false,"usgs":false,"family":"Swanson","given":"Jennifer","email":"","middleInitial":"E.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":832143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pierce, Clay 0000-0001-5088-5431 cpierce@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-5431","contributorId":150492,"corporation":false,"usgs":true,"family":"Pierce","given":"Clay","email":"cpierce@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dinsmore, Stephen J.","contributorId":61718,"corporation":false,"usgs":true,"family":"Dinsmore","given":"Stephen J.","affiliations":[],"preferred":false,"id":832144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832025,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vandever, Mark W. 0000-0003-0247-2629 vandeverm@usgs.gov","orcid":"https://orcid.org/0000-0003-0247-2629","contributorId":197674,"corporation":false,"usgs":true,"family":"Vandever","given":"Mark","email":"vandeverm@usgs.gov","middleInitial":"W.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":832026,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stewart, Timothy W.","contributorId":171433,"corporation":false,"usgs":false,"family":"Stewart","given":"Timothy","email":"","middleInitial":"W.","affiliations":[{"id":26913,"text":"Iowa State University, Ames, Iowa","active":true,"usgs":false}],"preferred":false,"id":832145,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Muths, Erin L. 0000-0002-5498-3132","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":245922,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":832027,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70206132,"text":"70206132 - 2019 - Role of recovering river herring population on smallmouth bass diet and growth","interactions":[],"lastModifiedDate":"2019-10-30T06:31:02","indexId":"70206132","displayToPublicDate":"2019-03-01T09:06:53","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Role of recovering river herring population on smallmouth bass diet and growth","docAbstract":"Fish assemblages in Atlantic coastal rivers have undergone extensive ecological change in the last two and a half centuries due to human influence, including extirpation of many migratory fish species, such as river herring (Alosa spp.) and introduction of nonnative piscivores, notably Smallmouth Bass Micropterus dolomieu. Recently, dam removals and fish passage improvements in the Penobscot River, Maine, have allowed river herring to return to reaches of the river that have been inaccessible since the late 19th century. Alosine populations have increased and this trend is anticipated to continue. This may increase forage in the system which could potentially increase growth for Smallmouth Bass, the dominant piscivore. We examined the diet and growth of Smallmouth Bass collected from areas of the Penobscot River watershed with and without access to river herring as prey. We collected 765 Smallmouth Bass throughout 2015, examined the stomach contents of 573 individuals, and found notable differences in diet among three river reaches with common seasonal trends. Juvenile river herring composed an average of 19% (SE = ±6%) of stomach contents by mass from Smallmouth Bass collected in the freshwater tidal area but were rarely observed in the diets upstream. We used estimates from von Bertalanffy growth models to examine differences in growth among reaches and found that asymptotic length was the longest (425 mm TL) in the Tidal reach where access to river herring was unrestricted. We then used these data to predict changes to growth associated with increased access to juvenile river herring prey with bioenergetics models. Results indicated that substituting juvenile river herring for less energy-dense prey (e.g.,invertebrates) may lead to increases in seasonal growth throughout the watershed as river herring populations continue to rebound in response to dam removal. Our results provide insight into the diet and growth of Smallmouth Bass in a large New England river, and provide a foundation for future work investigating unfolding changes to these characteristics following recent dam removals.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Managing centrarchid fisheries in rivers and streams","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","isbn":"9781934874523","usgsCitation":"Watson, J.M., Coghlan, S.M., Zydlewski, J.D., Hayes, D.B., and Stich, D.S., 2019, Role of recovering river herring population on smallmouth bass diet and growth, chap. <i>of</i> Managing centrarchid fisheries in rivers and streams, 18 p.","productDescription":"18 p.","ipdsId":"IP-086810","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":368699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368671,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://fisheries.org/bookstore/all-titles/afs-symposia/54087p/"}],"country":"United States","state":"Maine","otherGeospatial":"Penobscot River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -68.8348388671875,\n              44.70770622183535\n            ],\n            [\n              -68.34869384765625,\n              44.70770622183535\n            ],\n            [\n              -68.34869384765625,\n              45.94160076422081\n            ],\n            [\n              -68.8348388671875,\n              45.94160076422081\n            ],\n            [\n              -68.8348388671875,\n              44.70770622183535\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Watson, Jonathan M.","contributorId":207174,"corporation":false,"usgs":false,"family":"Watson","given":"Jonathan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":773992,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coghlan, Stephen M. Jr.","contributorId":169678,"corporation":false,"usgs":false,"family":"Coghlan","given":"Stephen","suffix":"Jr.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":773993,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":773683,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayes, Daniel B.","contributorId":16799,"corporation":false,"usgs":true,"family":"Hayes","given":"Daniel","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":773994,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stich, Daniel S.","contributorId":139212,"corporation":false,"usgs":false,"family":"Stich","given":"Daniel","email":"","middleInitial":"S.","affiliations":[{"id":12606,"text":"University of Maine, Dept of Plant, Soil, & Envir Sciences","active":true,"usgs":false}],"preferred":false,"id":773995,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70202393,"text":"70202393 - 2019 - Adapting a regional water-quality model for local application: A case study for Tennessee, USA","interactions":[],"lastModifiedDate":"2019-02-27T12:59:07","indexId":"70202393","displayToPublicDate":"2019-02-27T12:59:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Adapting a regional water-quality model for local application: A case study for Tennessee, USA","docAbstract":"<p><span>We evaluated whether SPAtially Referenced Regression On Watershed attributes (SPARROW) models calibrated for two adjacent USA regions could be applied at the local scale to support&nbsp;management decisions&nbsp;for streams in Tennessee. Nutrient-source apportionment of load is important for this local-scale application and demands&nbsp;</span>careful consideration<span>&nbsp;of uncertainty in the calibrated coefficients. We used Gauss-Newton regression to test the published SPARROW models for constancy of coefficient estimates between calibration sites on streams within (n = 59) versus outside (n = 327) Tennessee and concluded&nbsp;source apportionment&nbsp;was unbiased for Tennessee streams. The SPARROW models were then applied without re-calibration to predict stream loads and source apportionment for Tennessee streams and to build tools for displaying model results and evaluating source-change scenarios. This approach may inform the adaptation of other regional-scale regression models for use to address&nbsp;water-resource management&nbsp;issues in smaller-scale watersheds.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2019.01.001","usgsCitation":"Hoos, A.B., Wang, S.H., and Schwarz, G., 2019, Adapting a regional water-quality model for local application: A case study for Tennessee, USA: Environmental Modelling and Software, v. 115, p. 187-199, https://doi.org/10.1016/j.envsoft.2019.01.001.","productDescription":"13 p.","startPage":"187","endPage":"199","ipdsId":"IP-083893","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":460459,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2019.01.001","text":"Publisher Index Page"},{"id":361588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","volume":"115","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hoos, Anne B. 0000-0001-9845-7831","orcid":"https://orcid.org/0000-0001-9845-7831","contributorId":207575,"corporation":false,"usgs":true,"family":"Hoos","given":"Anne","email":"","middleInitial":"B.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":758165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Sherry H.","contributorId":213620,"corporation":false,"usgs":false,"family":"Wang","given":"Sherry","email":"","middleInitial":"H.","affiliations":[{"id":38823,"text":"TDEC","active":true,"usgs":false}],"preferred":false,"id":758166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":543,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory E.","email":"gschwarz@usgs.gov","affiliations":[{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":758167,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70202392,"text":"70202392 - 2019 - Geochemically distinct oil families in the onshore and offshore Santa Maria basins, California","interactions":[],"lastModifiedDate":"2019-02-27T12:56:23","indexId":"70202392","displayToPublicDate":"2019-02-27T12:56:18","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":605,"text":"AAPG Bulletin","printIssn":"0149-1423","active":true,"publicationSubtype":{"id":10}},"title":"Geochemically distinct oil families in the onshore and offshore Santa Maria basins, California","docAbstract":"<p><span>The purpose of this work is to identify genetic affinities among 48 crude oil samples from the onshore and offshore Santa Maria basins. A total of 21 source-related biomarker and stable carbon isotope ratios among the samples were assessed to assure that they were unaffected by secondary processes. Chemometric analysis of these data identifies six oil families with map and stratigraphic distributions that reflect organofacies variations within the Miocene Monterey Formation source rock. The data comprise a training set that was used to create a chemometric decision tree to classify newly collected oil samples. Three onshore families originated from two synclines, which may contain one or more pods of thermally mature source rock. Multiple biomarker parameters indicate that the six oil families achieved early oil window maturity in the range of 0.6%–0.7% equivalent vitrinite reflectance. The offshore oil samples consist of one family from Point Pedernales field and two families from the “B” prospect. Geochemical characteristics of these families indicate origins under differing water column and sediment oxicity and carbonate versus siliceous and detrital input in ‘carbonate,’ ‘marl,’ and ‘shale’ organofacies like those in the lower calcareous–siliceous, carbonaceous marl, and clayey–siliceous members of the Monterey Formation elsewhere in coastal California. The corresponding lithofacies and organofacies appear to be linked to the early–middle Miocene climate optimum and subsequent paleoclimatic cooling after circa 14 Ma, a systematic up-section increase in the stable carbon isotope composition of related oil samples, decreased preservation of calcium carbonate shells from planktic foraminifera and coccoliths, and increased preservation of clay-sized siliceous shells of diatoms and radiolarians. The results show that organofacies within the Monterey source rock are responsible for many of the geochemical differences between the oil families. This paleoclimate–organofacies model for crude oil from the Monterey Formation can be used to enhance future exploration efforts in many areas of coastal California.</span></p>","language":"English","publisher":"American Association of Petroleum Geology","doi":"10.1306/07111818014","usgsCitation":"Peters, K.E., Lillis, P.G., Lorenson, T., and Zumberge, J.E., 2019, Geochemically distinct oil families in the onshore and offshore Santa Maria basins, California: AAPG Bulletin, v. 103, no. 2, p. 243-271, https://doi.org/10.1306/07111818014.","productDescription":"28 p.","startPage":"243","endPage":"271","ipdsId":"IP-093274","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":361587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Maria basins","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121,\n              34.5\n            ],\n            [\n              -120,\n              34.5\n            ],\n            [\n              -120,\n              35.1667\n            ],\n            [\n              -121,\n              35.1667\n            ],\n            [\n              -121,\n              34.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"103","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peters, Kenneth E.","contributorId":213618,"corporation":false,"usgs":false,"family":"Peters","given":"Kenneth","email":"","middleInitial":"E.","affiliations":[{"id":27162,"text":"Schlumberger","active":true,"usgs":false}],"preferred":false,"id":758162,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lillis, Paul G. 0000-0002-7508-1699 plillis@usgs.gov","orcid":"https://orcid.org/0000-0002-7508-1699","contributorId":1817,"corporation":false,"usgs":true,"family":"Lillis","given":"Paul","email":"plillis@usgs.gov","middleInitial":"G.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":758163,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorenson, Thomas 0000-0001-7669-2873 tlorenson@usgs.gov","orcid":"https://orcid.org/0000-0001-7669-2873","contributorId":174599,"corporation":false,"usgs":true,"family":"Lorenson","given":"Thomas","email":"tlorenson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":758161,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zumberge, J. E.","contributorId":213619,"corporation":false,"usgs":false,"family":"Zumberge","given":"J.","email":"","middleInitial":"E.","affiliations":[{"id":38822,"text":"GeoMark Research LLC","active":true,"usgs":false}],"preferred":false,"id":758164,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70209686,"text":"70209686 - 2019 - Lithospheric signature of late Cenozoic extension in electrical resistivity structure of the Rio Grande rift, New Mexico, USA","interactions":[],"lastModifiedDate":"2020-04-21T16:13:12.68067","indexId":"70209686","displayToPublicDate":"2019-02-27T11:08:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Lithospheric signature of late Cenozoic extension in electrical resistivity structure of the Rio Grande rift, New Mexico, USA","docAbstract":"We present electrical resistivity models of the crust and upper mantle from two‐dimensional (2‐D) inversion of magnetotelluric (MT) data collected in the Rio Grande rift, New Mexico, USA. Previous geophysical studies of the lithosphere beneath the rift identified a low‐velocity zone several hundred kilometers wide, suggesting that the upper mantle is characterized by a very broad zone of modified lithosphere. In contrast, the surface expression of the rift (e.g., high‐angle normal faults and synrift sedimentary units) is confined to a narrow region a few tens of kilometers wide about the rift axis. MT data are uniquely suited to probing the depths of the lithosphere that fill the gap between surface geology and body wave seismic tomography, namely the middle to lower crust and uppermost mantle. We model the electrical resistivity structure of the lithosphere along two east‐west trending profiles straddling the rift axis at the latitudes of 36.2 and 32.0°N. We present results from both isotropic and anisotropic 2‐D inversions of MT data along these profiles, with a strong preference for the latter in our interpretation. A key feature of the anisotropic resistivity modeling is a broad (~200‐km wide) zone of enhanced conductivity (<20 Ωm) in the middle to lower crust imaged beneath both profiles. We attribute this lower crustal conductor to the accumulation of free saline fluids and partial melt, a direct result of magmatic activity along the rift. High‐conductivity anomalies in the midcrust and upper mantle are interpreted as fault zone alteration and partial melt, respectively.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JB016242","collaboration":"","usgsCitation":"Feucht, D., Bedrosian, P.A., and Sheehan, A.F., 2019, Lithospheric signature of late Cenozoic extension in electrical resistivity structure of the Rio Grande rift, New Mexico, USA: Journal of Geophysical Research B: Solid Earth, v. 124, no. 3, p. 2331-2351, https://doi.org/10.1029/2018JB016242.","productDescription":"21 p.","startPage":"2331","endPage":"2351","ipdsId":"IP-102825","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":467866,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jb016242","text":"Publisher Index Page"},{"id":374160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Rio Grande rift","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.02978515625,\n              37.00255267215955\n            ],\n            [\n              -109.0283203125,\n              36.98500309285596\n            ],\n            [\n              -109.05029296875,\n              31.372399104880525\n            ],\n            [\n              -108.19335937499999,\n              31.353636941500987\n            ],\n            [\n              -108.1494140625,\n              31.840232667909365\n            ],\n            [\n              -103.0078125,\n              32.045332838858506\n            ],\n            [\n              -103.02978515625,\n              37.00255267215955\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"124","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Feucht, D. W. 0000-0002-3672-4719","orcid":"https://orcid.org/0000-0002-3672-4719","contributorId":224277,"corporation":false,"usgs":false,"family":"Feucht","given":"D. W.","affiliations":[],"preferred":false,"id":787518,"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":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":787519,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheehan, Anne F 0000-0002-9629-1687","orcid":"https://orcid.org/0000-0002-9629-1687","contributorId":224234,"corporation":false,"usgs":false,"family":"Sheehan","given":"Anne","email":"","middleInitial":"F","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":787520,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70227711,"text":"70227711 - 2019 - Satellite-detected forest disturbance forecasts American marten population decline: The case for supportive space-based monitoring","interactions":[],"lastModifiedDate":"2022-01-27T15:55:13.344451","indexId":"70227711","displayToPublicDate":"2019-02-27T09:48:02","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Satellite-detected forest disturbance forecasts American marten population decline: The case for supportive space-based monitoring","docAbstract":"<p><span>Limited monitoring resources often constrain rigorous monitoring practices to species or populations of conservation concern. Insufficient monitoring can induce a tautology as lack of monitoring resources makes it difficult to determine whether a species or population deserves additional monitoring resources. When in-situ monitoring resources are limited, remote habitat monitoring could be a useful supplementary tool, as linking parameterized&nbsp;species distribution models&nbsp;to spatially explicit time-series of environmental correlates allows iterative prediction of population change. Yet the performance of predictive forecasts or hindcasts has been difficult to evaluate. We paired contemporary field data, historic population estimates, and a remotely-sensed archive of landscape change to evaluate predictions of American marten (</span><span><i><a class=\"topic-link\" title=\"Learn more about Martes americana from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/martes-americana\" data-mce-href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/martes-americana\">Martes americana</a></i></span><span>) population decline owing to habitat loss in Maine, USA. We estimated contemporary spatial patterns in marten density relative to landscape disturbance with spatial capture-recapture models. We compared current density estimates to historical density calculations to evaluate population decline, and compared historical calculations to habitat-based model predictions to evaluate the efficacy of habitat monitoring as a proxy for direct monitoring. Marten density was negatively associated with the proportion of surrounding regenerating forest, and point estimates within focal townships were 50–80% lower than historical calculations. Habitat-based hindcasts of marten density across our entire focal area interest suggested a smaller population decline (roughly 50%) within our focal area. Thus, although habitat-based predictions underpredicted marten decline, they provided correct directional inference. Habitat monitoring and predictions from species distribution models may provide useful inference about population changes given trends in habitat at limited expense when in-situ information is lacking.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2019.02.020","usgsCitation":"Clare, J., McKinney, S.T., Simons-Legaard, E.M., DePue, J.E., and Loftin, C., 2019, Satellite-detected forest disturbance forecasts American marten population decline: The case for supportive space-based monitoring: Biological Conservation, v. 233, p. 336-345, https://doi.org/10.1016/j.biocon.2019.02.020.","productDescription":"10 p.","startPage":"336","endPage":"345","ipdsId":"IP-078363","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":394973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -70.91125488281249,\n              45.286481972782816\n            ],\n            [\n              -69.136962890625,\n              44.999767019181284\n            ],\n            [\n              -68.4503173828125,\n              46.39619977845332\n            ],\n            [\n              -69.99938964843749,\n              46.717268685073954\n            ],\n            [\n              -70.91125488281249,\n              45.286481972782816\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"233","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Clare, John","contributorId":200304,"corporation":false,"usgs":false,"family":"Clare","given":"John","affiliations":[],"preferred":false,"id":831975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKinney, Shawn T. smckinney@usgs.gov","contributorId":5175,"corporation":false,"usgs":true,"family":"McKinney","given":"Shawn","email":"smckinney@usgs.gov","middleInitial":"T.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":831976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simons-Legaard, Erin M.","contributorId":272366,"corporation":false,"usgs":false,"family":"Simons-Legaard","given":"Erin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":831977,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DePue, John E.","contributorId":200305,"corporation":false,"usgs":false,"family":"DePue","given":"John","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":831978,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":831862,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70202294,"text":"ofr20191012 - 2019 - Planetary geologic mapping—Program status and future needs","interactions":[],"lastModifiedDate":"2019-03-01T09:22:11","indexId":"ofr20191012","displayToPublicDate":"2019-02-27T07:01:20","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1012","displayTitle":"Planetary Geologic Mapping—Program Status and Future Needs","title":"Planetary geologic mapping—Program status and future needs","docAbstract":"<p class=\"m_-2305864567869916980gmail-Pa19\"><span>The United States Geological Survey’s (USGS) Planetary Geologic Map Coordination Group (Flagstaff, Ariz.) surveyed planetary geoscience map makers and users to determine the importance, relevance, and usability of such products to their planetary science research and to current and future needs of the planetary science community. This survey was prepared because the planetary science community lacks a modern assessment of the value invested in geoscience map products and processes (including the diverse scientific and technical personnel who add to and maintain this infrastructure) and a strategy that ensures these efforts appropriately prioritize mapping efforts across all solid surface bodies in the Solar System.</span></p><p class=\"m_-2305864567869916980gmail-Pa19\"><span>A 30-question survey was conducted through an online questionnaire and was designed to (1) take &lt;10 minutes, (2) instill a sense that responses would be acted upon, and (3) encourage community participation through a user-friendly interface. The survey made a distinction between “standardized” geoscience maps (those published by the USGS that require adherence to specific cartographic standards, conventions, and principles) and “non-standardized” geoscience maps (those published by other venues such as peer-reviewed journals that are not required to, but might, adhere to some cartographic standards, conventions, and principles). The survey was opened on Sunday, March 18, 2017 (to coincide with the annual Lunar and Planetary Science Conference in The Woodlands, Tex.) and was closed on Thursday, May 25, 2017. There was a total of 265 unique responses that were formulated into 17 unique findings that were matched with one or more recommendations to be addressed by the planetary science community.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191012","usgsCitation":"Skinner, J.A. Jr., Huff, A.E., Fortezzo, C.M., Gaither, T., Hare, T.M., Hunter, M.A., Buban, H., 2019, Planetary geologic mapping—program status and future needs: U.S. Geological Survey Open-File Report 2019–1012, 40 p., https://doi.org/10.3133/ofr20191012","productDescription":"vi, 39 p.","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-102821","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":361568,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1012/ofr20191012.pdf","text":"Report","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1012"},{"id":361567,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1012/coverthb.jpg"}],"contact":"<p><a href=\"https://astrogeology.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://astrogeology.usgs.gov/\">Astrogeology Science Center</a><br>U.S. Geological Survey<br>2255 N. Gemini Dr. <br>Flagstaff, AZ 86001</p>","tableOfContents":"<ul><li>USGS Astrogeology Science Center—Planetary Geologic Map Coordination Group</li><li>Executive Summary</li><li>Introduction</li><li>USGS-NASA Planetary Geologic Mapping Program</li><li>Survey Rationale</li><li>Survey Questionnaire</li><li>Summary Responses</li><li>Key Findings and Recommendations</li><li>Next Steps</li><li>References Cited</li><li>Appendixes 1—2</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2019-02-27","noUsgsAuthors":false,"publicationDate":"2019-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Skinner, James A. Jr. 0000-0002-3644-7010 jskinner@usgs.gov","orcid":"https://orcid.org/0000-0002-3644-7010","contributorId":213622,"corporation":false,"usgs":true,"family":"Skinner","given":"James","suffix":"Jr.","email":"jskinner@usgs.gov","middleInitial":"A.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":757682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huff, Alexandra E. 0000-0001-9778-4814","orcid":"https://orcid.org/0000-0001-9778-4814","contributorId":213420,"corporation":false,"usgs":true,"family":"Huff","given":"Alexandra","email":"","middleInitial":"E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":757683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fortezzo, Corey M. 0000-0001-8188-5530 cfortezzo@usgs.gov","orcid":"https://orcid.org/0000-0001-8188-5530","contributorId":25383,"corporation":false,"usgs":true,"family":"Fortezzo","given":"Corey","email":"cfortezzo@usgs.gov","middleInitial":"M.","affiliations":[{"id":130,"text":"Astrogeology Research Center","active":false,"usgs":true}],"preferred":false,"id":757684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gaither, Tenielle 0000-0003-4230-3678 tgaither@usgs.gov","orcid":"https://orcid.org/0000-0003-4230-3678","contributorId":213422,"corporation":false,"usgs":false,"family":"Gaither","given":"Tenielle","email":"tgaither@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":757685,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hare, Trent M. 0000-0001-8842-389X thare@usgs.gov","orcid":"https://orcid.org/0000-0001-8842-389X","contributorId":3188,"corporation":false,"usgs":true,"family":"Hare","given":"Trent","email":"thare@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":757686,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hunter, Marc A. 0000-0002-6999-3245 mahunter@usgs.gov","orcid":"https://orcid.org/0000-0002-6999-3245","contributorId":210560,"corporation":false,"usgs":true,"family":"Hunter","given":"Marc","email":"mahunter@usgs.gov","middleInitial":"A.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":757687,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Buban, Holly 0000-0002-7346-8478","orcid":"https://orcid.org/0000-0002-7346-8478","contributorId":213425,"corporation":false,"usgs":true,"family":"Buban","given":"Holly","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":757688,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70218702,"text":"70218702 - 2019 - Mapping a keystone shrub species, huckleberry (Vaccinium membranaceum), using seasonal colour change in the Rocky Mountains","interactions":[],"lastModifiedDate":"2021-03-05T21:56:58.666116","indexId":"70218702","displayToPublicDate":"2019-02-26T15:51:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Mapping a keystone shrub species, huckleberry (<i>Vaccinium membranaceum</i>), using seasonal colour change in the Rocky Mountains","title":"Mapping a keystone shrub species, huckleberry (Vaccinium membranaceum), using seasonal colour change in the Rocky Mountains","docAbstract":"<p><span>Black huckleberries (</span><i>Vaccinium membranaceum</i><span>) provide a critical food resource to many wildlife species, including apex omnivores such as the grizzly bear (</span><i>Ursus arctos</i><span>), and play an important socioeconomic role for many communities in western North America, especially indigenous peoples. Remote sensing imagery offers the potential for accurate landscape-level mapping of huckleberries because the shrub changes colour seasonally. We developed two methods, for local and regional scales, to map a shrub species using leaf seasonal colour change from remote sensing imagery. We assessed accuracy with ground-based vegetation surveys. The high-resolution supervised random forest classification from one-meter resolution National Agricultural Imagery Program (NAIP) imagery achieved an overall accuracy of 75.31% (kappa&nbsp;=&nbsp;0.26). The approach using multi-temporal 30-meter Landsat imagery similarly had an overall accuracy of 79.19% (kappa&nbsp;=&nbsp;.31). We found underprediction error was related to higher forest cover and a lack of visible colour change on the ground in some plots. Where forest cover was low, both models performed better. In areas with &lt;10% forest cover, the high-resolution classification achieved an accuracy of 80.73% (kappa&nbsp;=&nbsp;0.48), while the Landsat model had an accuracy of 82.55% (kappa&nbsp;=&nbsp;0.47). Based on the fine-scale predictions, we found that 94% of huckleberry shrubs identified in our study area of Glacier National Park, Montana, USA are over 100 meters from human recreation trails. This information could be combined with productivity and phenology information to estimate the timing and availability of food resources for wildlife and to provide managers with a tool to identify and manage huckleberries. The development of the multi-temporal Landsat models sets the stage for assessment of impacts of disturbance at regional scales on this ecologically, culturally, and economically important shrub species. Our approach to map huckleberries is straightforward, efficient and accessible to wildlife and environmental managers and researchers in diverse fields.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2019.1580819","usgsCitation":"Shores, C.R., Mikle, N., and Graves, T.A., 2019, Mapping a keystone shrub species, huckleberry (Vaccinium membranaceum), using seasonal colour change in the Rocky Mountains: International Journal of Remote Sensing, v. 40, no. 15, p. 5695-5715, https://doi.org/10.1080/01431161.2019.1580819.","productDescription":"21 p.","startPage":"5695","endPage":"5715","ipdsId":"IP-095407","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":384206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.961181640625,\n              48.31060120649363\n            ],\n            [\n              -112.939453125,\n              48.242967421301366\n            ],\n            [\n              -113.65631103515625,\n              48.99103162515999\n            ],\n            [\n              -114.81536865234374,\n              49.005447494058096\n            ],\n            [\n              -114.5050048828125,\n              48.545705491847464\n            ],\n            [\n              -114.15618896484375,\n              48.35989909002194\n            ],\n            [\n              -113.961181640625,\n              48.31060120649363\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"40","issue":"15","noUsgsAuthors":false,"publicationDate":"2019-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Shores, Carolyn R.","contributorId":254828,"corporation":false,"usgs":false,"family":"Shores","given":"Carolyn","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":811433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mikle, Nathaniel 0000-0002-6529-8210 nmikle@usgs.gov","orcid":"https://orcid.org/0000-0002-6529-8210","contributorId":177026,"corporation":false,"usgs":true,"family":"Mikle","given":"Nathaniel","email":"nmikle@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":811434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graves, Tabitha A. 0000-0001-5145-2400 tgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":5898,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha","email":"tgraves@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":811435,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70202376,"text":"70202376 - 2019 - Applying concepts of general resilience to large river ecosystems: A case study from the Upper Mississippi and Illinois rivers","interactions":[],"lastModifiedDate":"2019-02-26T15:01:06","indexId":"70202376","displayToPublicDate":"2019-02-26T15:01:02","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Applying concepts of general resilience to large river ecosystems: A case study from the Upper Mississippi and Illinois rivers","docAbstract":"<p><span>Large floodplain-river ecosystems are often highly modified to provide services that society desires, yet these modifications can limit an ecosystem’s ability to adapt to changing conditions. The adaptive capacity of an ecosystem, its general resilience, is a conceptual framework for considering how a system will respond to such changes. We sought to apply aspects of three general resilience principles (diversity and redundancy, connectivity, and controlling variables) to our understanding of floodplain-river ecosystem structure and function. We demonstrate the applicability of this approach in a case study of the Upper Mississippi River System (UMRS). In doing so, we developed ten indicators that highlight important structural and functional aspects of this floodplain-river ecosystem, and likely underlie the capacity of large rivers to cope with environmental change and disturbance. We developed diversity and redundancy indicators for aquatic habitats, patterns of floodplain inundation, and fish communities. Connectivity indicators included metrics of longitudinal and lateral connections. Controlling variable indicators included deviations from historic water surface elevation fluctuations, water clarity, nutrient concentrations, and aquatic invasive species. This set of indicators provides a simple description of the adaptive capacity of four distinct reaches of the UMRS: Upper Impounded, Lower Impounded, Unimpounded Reaches of the Upper Mississippi River and the entire Illinois River. High aquatic habitat diversity and redundancy, fish functional diversity and redundancy, and water clarity, and the scarcity of invasive fish species are all factors that likely contribute to the high general resilience of the Upper Impounded Reach. However, the limited longitudinal connectivity and establishment of a minimum water level for navigation are factors that may inhibit the general resilience of this reach. In the Lower Impounded Reach, there is high within-reach variability for individual indicators such as aquatic habitat diversity, fish functional diversity and redundancy, and longitudinal and lateral connectivity. In the Unimpounded Reach, a high degree of longitudinal connectivity likely enhances its general resilience, but low aquatic habitat diversity, low lateral connectivity, and relatively high number of invasive fish species inhibit general resilience. For the Illinois River Reach, the relatively high fish functional diversity and redundancy likely contributes to its general resilience, whereas high number of invasive fish species, low water clarity, low lateral connectivity, and high range of water levels may inhibit general resilience. Indicators derived from application of concepts of general resilience provide insight into the current coping capacity of the UMRS and identify opportunities for enhancing resilience.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2019.02.002","usgsCitation":"Bouska, K.L., Houser, J.N., De Jager, N.R., Van Appledorn, M., and Rogala, J.T., 2019, Applying concepts of general resilience to large river ecosystems: A case study from the Upper Mississippi and Illinois rivers: Ecological Indicators, v. 101, p. 1094-1110, https://doi.org/10.1016/j.ecolind.2019.02.002.","productDescription":"7 p.","startPage":"1094","endPage":"1110","ipdsId":"IP-099227","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437559,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J8BBQ3","text":"USGS data release","linkHelpText":"Percentage of annual days that river stage exceeds 'open river' conditions for lock and dams on the Upper Mississippi River, 1985-2015"},{"id":361559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Mississippi River System","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.31787109374999,\n              36.87962060502676\n            ],\n            [\n              -87.51708984375,\n              36.87962060502676\n            ],\n            [\n              -87.51708984375,\n              45.01141864227728\n            ],\n            [\n              -93.31787109374999,\n              45.01141864227728\n            ],\n            [\n              -93.31787109374999,\n              36.87962060502676\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"101","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bouska, Kristen L. 0000-0002-4115-2313 kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houser, Jeffrey N. 0000-0003-3295-3132 jhouser@usgs.gov","orcid":"https://orcid.org/0000-0003-3295-3132","contributorId":2769,"corporation":false,"usgs":true,"family":"Houser","given":"Jeffrey","email":"jhouser@usgs.gov","middleInitial":"N.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758093,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758094,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rogala, James T. 0000-0002-1954-4097 jrogala@usgs.gov","orcid":"https://orcid.org/0000-0002-1954-4097","contributorId":2651,"corporation":false,"usgs":true,"family":"Rogala","given":"James","email":"jrogala@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758095,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70202387,"text":"70202387 - 2019 - Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data","interactions":[],"lastModifiedDate":"2019-02-26T14:14:42","indexId":"70202387","displayToPublicDate":"2019-02-26T14:14:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data","docAbstract":"<p><span>Obtaining inferences on disease dynamics (e.g., host population size, pathogen prevalence, transmission rate, host survival probability) typically requires marking and tracking individuals over time. While multistate mark–recapture models can produce high‐quality inference, these techniques are difficult to employ at large spatial and long temporal scales or in small remnant host populations decimated by virulent pathogens, where low recapture rates may preclude the use of mark–recapture techniques. Recently developed&nbsp;</span><i>N</i><span>‐mixture models offer a statistical framework for estimating wildlife disease dynamics from count data.&nbsp;</span><i>N</i><span>‐mixture models are a type of state‐space model in which observation error is attributed to failing to detect some individuals when they are present (i.e., false negatives). The analysis approach uses repeated surveys of sites over a period of population closure to estimate detection probability. We review the challenges of modeling disease dynamics and describe how&nbsp;</span><i>N</i><span>‐mixture models can be used to estimate common metrics, including pathogen prevalence, transmission, and recovery rates while accounting for imperfect host and pathogen detection. We also offer a perspective on future research directions at the intersection of quantitative and disease ecology, including the estimation of false positives in pathogen presence, spatially explicit disease‐structured&nbsp;</span><i>N</i><span>‐mixture models, and the integration of other data types with count data to inform disease dynamics. Managers rely on accurate and precise estimates of disease dynamics to develop strategies to mitigate pathogen impacts on host populations. At a time when pathogens pose one of the greatest threats to biodiversity, statistical methods that lead to robust inferences on host populations are critically needed for rapid, rather than incremental, assessments of the impacts of emerging infectious diseases.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4849","usgsCitation":"DiRenzo, G.V., Che-Castaldo, C., Saunders, S.P., Campbell Grant, E.H., and Zipkin, E.F., 2019, Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data: Ecology and Evolution, v. 9, no. 2, p. 899-909, https://doi.org/10.1002/ece3.4849.","productDescription":"11 p.","startPage":"899","endPage":"909","ipdsId":"IP-099044","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467871,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4849","text":"Publisher Index Page"},{"id":361552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"DiRenzo, Graziella V.","contributorId":192177,"corporation":false,"usgs":false,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":758142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Che-Castaldo, Christian","contributorId":202588,"corporation":false,"usgs":false,"family":"Che-Castaldo","given":"Christian","email":"","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":758143,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saunders, Sarah P.","contributorId":192752,"corporation":false,"usgs":false,"family":"Saunders","given":"Sarah","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":758144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":758141,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zipkin, Elise F. 0000-0003-4155-6139","orcid":"https://orcid.org/0000-0003-4155-6139","contributorId":192755,"corporation":false,"usgs":false,"family":"Zipkin","given":"Elise","email":"","middleInitial":"F.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":758145,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70201177,"text":"sir20185145 - 2019 - Catchment-level estimates of nitrogen and phosphorus agricultural use from commercial fertilizer sales for the conterminous United States, 2012","interactions":[],"lastModifiedDate":"2019-02-27T11:51:29","indexId":"sir20185145","displayToPublicDate":"2019-02-26T12:06:29","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5145","displayTitle":"Catchment-Level Estimates of Nitrogen and Phosphorus Agricultural Use from Commercial Fertilizer Sales for the Conterminous United States, 2012","title":"Catchment-level estimates of nitrogen and phosphorus agricultural use from commercial fertilizer sales for the conterminous United States, 2012","docAbstract":"<p>Nutrient inputs from commercial agricultural fertilizer, particularly nitrogen and phosphorus, are important factors contributing to the degradation of surface-water quality and the alteration of aquatic ecosystems. Despite this importance, information about the application of fertilizer to agricultural land is not available in a consistent manner across the United States at a scale useful for regional water-quality assessment. To address this need, an approach is developed to relate commercial fertilizer sales to a set of explanatory variables using spatially referenced modeling methods. Spatially referenced modeling in this study refers to statistically relating fertilizer use, estimated from commercial fertilizer sales data, to spatially referenced data on watershed attributes. Separate models for nitrogen and phosphorus are developed to estimate elemental fertilizer use on agricultural lands for the conterminous United States at the National Hydrography Dataset Plus (NHDPlus) catchment scale for the year 2012. The approach builds on earlier efforts that use Association of American Plant Food Control Officials data on fertilizer sales to provide county-level estimates of nitrogen and phosphorus fertilizer use. The spatially referenced method improves on these efforts by allowing for varying nitrogen to phosphorus ratios at the catchment scale and expanding the set of variables used to allocate county-level sales data to the catchment scale. The models include catchment-level factors that are either primary determinants of fertilizer use, such as the acreage of different crop types, or measures reflecting the intensity of use, such as climate. Explanatory variables available only at the county scale, such as U.S. Department of Agriculture Census of Agriculture estimates of fertilizer expenditures, are included to improve the model predictions of elemental use. The nitrogen and phosphorus models explain more than 90 percent of the variation in elemental use at the state level, and the statistical approach allows for the estimation of uncertainty of predicted use in each catchment. The spatial patterns of model predictions reflect known agricultural cropping practices across the United States that transcend political boundaries, despite the county/state orientation of the fertilizer sales information. The results are expected to be useful for a variety of water-quality assessments that are intended to estimate nitrogen and phosphorus loads to streams.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185145","usgsCitation":"Stewart, J.S., Schwarz, G.E., Brakebill, J.W., and Preston, S.D., 2019, Catchment-level estimates of nitrogen and phosphorus agricultural use from commercial fertilizer sales for the conterminous United States, 2012: U.S. Geological Survey Scientific Investigations Report 2018–5145, 52 p., https://doi.org/10.3133/sir20185145.","productDescription":"Report: x, 52 p.; Data releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-092916","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":361425,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5145/sir20185145.pdf","text":"Report","size":"54.8 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53562</p>","tableOfContents":"<ul><li>Foreword</li><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Methods</li><li>Results</li><li>Model Evaluation</li><li>Summary and Conclusions</li><li>References Cited</li><li>Appendixes 1–5</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-02-26","noUsgsAuthors":false,"publicationDate":"2019-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Stewart, Jana S. 0000-0002-8121-1373 jsstewar@usgs.gov","orcid":"https://orcid.org/0000-0002-8121-1373","contributorId":539,"corporation":false,"usgs":true,"family":"Stewart","given":"Jana","email":"jsstewar@usgs.gov","middleInitial":"S.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":543,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory E.","email":"gschwarz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":false,"id":753060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brakebill, John W. 0000-0001-9235-6810 jwbrakeb@usgs.gov","orcid":"https://orcid.org/0000-0001-9235-6810","contributorId":1061,"corporation":false,"usgs":true,"family":"Brakebill","given":"John","email":"jwbrakeb@usgs.gov","middleInitial":"W.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753061,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Preston, Stephen D. 0000-0003-1515-6692 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,{"id":70202722,"text":"70202722 - 2019 - Effects of nest exposure and spring temperatures on golden eagle brood survival: An opportunity for mitigation","interactions":[],"lastModifiedDate":"2019-03-21T16:34:14","indexId":"70202722","displayToPublicDate":"2019-02-25T13:58:32","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Effects of nest exposure and spring temperatures on golden eagle brood survival: An opportunity for mitigation","docAbstract":"<p><span>We examined Golden Eagle (</span><i>Aquila chrysaetos</i><span>) brood survival in relation to spring temperatures and exposure of nests to afternoon sun in southwestern Idaho from 1970 through 2012. Most (77%) nests classified as shaded in a subset of 96 nests had northwest to east aspects, and most (71%) nests classified as exposed had south to west aspects. We analyzed survival of 1154 Golden Eagle broods in 64 territories. Golden Eagle brood survival at shaded and exposed nests did not differ when the daily maximum temperature was &lt;32.2°C. Survival in exposed nests declined as the number of days with maximum temperature ≥32.2°C increased, but survival in shaded nests did not change. All broods survived from hatching to fledging age in eight exposed nests with artificial shade structures installed over a 6-yr period. During the same period, 7 of 42 broods in nests without shade structures failed to reach fledging age, with two failures (29%) attributed to thermal stress. Use of artificial shade structures in exposed nests may reduce or prevent mortality caused by heat stress, and thus might be a potential tool for mitigation of “take” from anthropogenic structures and activities. Additional experimentation under an adaptive management framework could provide more information about the effectiveness of using shade structures to offset nestling mortality associated with increasing temperatures predicted by climate change models.</span></p>","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-17-100","usgsCitation":"Kochert, M.N., Steenhof, K., and Brown, J.L., 2019, Effects of nest exposure and spring temperatures on golden eagle brood survival: An opportunity for mitigation: Journal of Raptor Research, v. 53, no. 1, p. 91-97, https://doi.org/10.3356/JRR-17-100.","productDescription":"7 p.","startPage":"91","endPage":"97","ipdsId":"IP-093510","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":362249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":" Morley Nelson Snake River Birds of Prey National Conservation Area ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.33148193359375,\n              43.100982876188546\n            ],\n            [\n              -116.01287841796874,\n              43.100982876188546\n            ],\n            [\n              -116.01287841796874,\n              43.27320591705845\n            ],\n            [\n              -116.33148193359375,\n              43.27320591705845\n            ],\n            [\n              -116.33148193359375,\n              43.100982876188546\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"53","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kochert, Michael N. 0000-0002-4380-3298 mkochert@usgs.gov","orcid":"https://orcid.org/0000-0002-4380-3298","contributorId":3037,"corporation":false,"usgs":true,"family":"Kochert","given":"Michael","email":"mkochert@usgs.gov","middleInitial":"N.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":759650,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steenhof, Karen karen_steenhof@usgs.gov","contributorId":203439,"corporation":false,"usgs":false,"family":"Steenhof","given":"Karen","email":"karen_steenhof@usgs.gov","affiliations":[],"preferred":false,"id":759651,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Jessi L.","contributorId":44817,"corporation":false,"usgs":false,"family":"Brown","given":"Jessi","email":"","middleInitial":"L.","affiliations":[{"id":13184,"text":"Program in Ecology, Evolution and Conservation Biology, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":759652,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70202362,"text":"70202362 - 2019 - Modeling riparian restoration impacts on the hydrologic cycle at the Babacomari Ranch, SE Arizona, USA","interactions":[],"lastModifiedDate":"2019-02-25T13:49:06","indexId":"70202362","displayToPublicDate":"2019-02-25T13:49:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Modeling riparian restoration impacts on the hydrologic cycle at the Babacomari Ranch, SE Arizona, USA","docAbstract":"<p><span>This paper describes coupling field experiments with surface and groundwater modeling to investigate rangelands of SE Arizona, USA using erosion-control structures to augment shallow and deep aquifer recharge. We collected field data to describe the physical and hydrological properties before and after gabions (caged riprap) were installed in an ephemeral channel. The modular finite-difference flow model is applied to simulate the amount of increase needed to raise groundwater levels. We used the average increase in infiltration measured in the field and projected on site, assuming all infiltration becomes recharge, to estimate how many gabions would be needed to increase recharge in the larger watershed. A watershed model was then applied and calibrated with discharge and 3D terrain measurements, to simulate flow volumes. Findings were coupled to extrapolate simulations and quantify long-term impacts of riparian restoration. Projected scenarios demonstrate how erosion-control structures could impact all components of the annual water budget. Results support the potential of watershed-wide gabion installation to increase total aquifer recharge, with models portraying increased subsurface connectivity and accentuated lateral flow contributions.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w11020381","usgsCitation":"Norman, L., Callegary, J.B., Lacher, L., Wilson, N., Fandel, C., Forbes, B.T., and Swetnam, T., 2019, Modeling riparian restoration impacts on the hydrologic cycle at the Babacomari Ranch, SE Arizona, USA: Water, v. 11, no. 2, p. 1-20, https://doi.org/10.3390/w11020381.","productDescription":"Article 381; 20 p.","startPage":"1","endPage":"20","ipdsId":"IP-090323","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":467872,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w11020381","text":"Publisher Index Page"},{"id":361505,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Babacomari Ranch","volume":"11","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":757998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Callegary, James B. 0000-0003-3604-0517 jcallega@usgs.gov","orcid":"https://orcid.org/0000-0003-3604-0517","contributorId":2171,"corporation":false,"usgs":true,"family":"Callegary","given":"James","email":"jcallega@usgs.gov","middleInitial":"B.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lacher, Laurel","contributorId":213547,"corporation":false,"usgs":false,"family":"Lacher","given":"Laurel","affiliations":[{"id":38785,"text":"Lacher Hydrological Consulting, Tucson, AZ 85719","active":true,"usgs":false}],"preferred":false,"id":758000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Natalie R. 0000-0001-5145-1221","orcid":"https://orcid.org/0000-0001-5145-1221","contributorId":202534,"corporation":false,"usgs":true,"family":"Wilson","given":"Natalie R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":758001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fandel, Chloé","contributorId":213548,"corporation":false,"usgs":false,"family":"Fandel","given":"Chloé","affiliations":[{"id":38786,"text":"University of Arizona, Hydrology and Water Resources, Tucson, AZ 85719","active":true,"usgs":false}],"preferred":false,"id":758002,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Forbes, Brandon T. 0000-0003-4051-0593 bforbes@usgs.gov","orcid":"https://orcid.org/0000-0003-4051-0593","contributorId":213549,"corporation":false,"usgs":true,"family":"Forbes","given":"Brandon","email":"bforbes@usgs.gov","middleInitial":"T.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":758003,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swetnam, Tyson","contributorId":213550,"corporation":false,"usgs":false,"family":"Swetnam","given":"Tyson","email":"","affiliations":[{"id":38787,"text":"University of Arizona , BIO5 Institute, Tucson, AZ 85719","active":true,"usgs":false}],"preferred":false,"id":758004,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70202345,"text":"70202345 - 2019 - Optimizing historic preservation under climate change: Decision support for cultural resource adaptation planning in national parks","interactions":[],"lastModifiedDate":"2019-02-25T13:44:39","indexId":"70202345","displayToPublicDate":"2019-02-25T13:44:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2599,"text":"Land Use Policy","active":true,"publicationSubtype":{"id":10}},"title":"Optimizing historic preservation under climate change: Decision support for cultural resource adaptation planning in national parks","docAbstract":"<p><span>Climate change&nbsp;poses great challenges for&nbsp;cultural resource&nbsp;management, particularly in coastal areas. Cultural resources, such as&nbsp;historic buildings, in coastal areas are vulnerable to&nbsp;climate impacts&nbsp;including inundation,&nbsp;</span>deterioration<span>, and destruction from&nbsp;sea-level&nbsp;rise and storm-related flooding and erosion. However, research that assesses the trade-offs between actions for protecting vulnerable and valuable cultural resources under budgetary constraints is limited. This study focused on developing a decision support model for managing historic buildings at Cape Lookout National Seashore. We designed the Optimal Preservation Decision Support (OptiPres) model to: (a) identify optimal, annual adaptation actions for historic buildings across a 30-year planning horizon, (b) quantify trade-offs between different actions and the timing of adaptation actions under constrained budgets, and (c) estimate the effectiveness of budget&nbsp;allocations&nbsp;on the resource value of historic buildings. Our analysis of the model suggests that: (1) funding allocation thresholds may exist for&nbsp;national parks&nbsp;to maintain the historical significance and use potential of historic buildings under climate change, (2) the quantitative assessment of trade-offs among alternative adaptation actions provides generalizable guidance for decision makers about the dynamics of their managed system, and (3) the OptiPres model can identify cost-efficient approaches to allocate funding to maintain the historical value of buildings vulnerable to the effects of climate change. Therefore, the OptiPres model, while not designed as a prescriptive decision tool, allows managers to understand the consequences of proposed adaptation actions. The OptiPres model can guide park managers to make cost-effective climate adaptation decisions for historic buildings more transparently and robustly.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.landusepol.2019.02.011","usgsCitation":"Xiao, X., Seekamp, E., Post van der Burg, M., Eaton, M.J., Fatoric, S., and McCreary, A., 2019, Optimizing historic preservation under climate change: Decision support for cultural resource adaptation planning in national parks: Land Use Policy, v. 83, p. 379-389, https://doi.org/10.1016/j.landusepol.2019.02.011.","productDescription":"11 p.","startPage":"379","endPage":"389","ipdsId":"IP-102168","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":467873,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.landusepol.2019.02.011","text":"Publisher Index Page"},{"id":361504,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"83","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Xiao, Xiao","contributorId":212835,"corporation":false,"usgs":false,"family":"Xiao","given":"Xiao","email":"","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":757944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seekamp, Erin","contributorId":212832,"corporation":false,"usgs":false,"family":"Seekamp","given":"Erin","email":"","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":757945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":757946,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":757943,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fatoric, Sandra","contributorId":212834,"corporation":false,"usgs":false,"family":"Fatoric","given":"Sandra","email":"","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":757947,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCreary, Allie","contributorId":212836,"corporation":false,"usgs":false,"family":"McCreary","given":"Allie","email":"","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":757948,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70202357,"text":"70202357 - 2019 - Modeling δ18O as an early indicator of regime shift arising from salinity stress in coastal vegetation","interactions":[],"lastModifiedDate":"2019-06-18T10:22:04","indexId":"70202357","displayToPublicDate":"2019-02-25T13:41:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Modeling δ<sup>18</sup>O as an early indicator of regime shift arising from salinity stress in coastal vegetation","title":"Modeling δ18O as an early indicator of regime shift arising from salinity stress in coastal vegetation","docAbstract":"<p><span>In many important coastal habitats, a combination of increasing soil salinization due to sea level rise, reduced precipitation and storm surges may induce regime shift from salinity-intolerant glycophytic vegetation to salinity-tolerant halophytic species. Early detection of regime shift due to salinity stress in vegetation may facilitate conservation efforts. It has been shown that the&nbsp;</span><sup>18</sup><span>O value of water in the xylem of trees can be used as a surrogate for salinity in the rooting zone of plants. Coupling measured δ</span><sup>18</sup><span>O values in the tree xylem with simulated δ</span><sup>18</sup><span>O values in trees and salinity in the vadose zone can be used to investigate competitive responses of glycophytic versus halophytic trees. MANTRA-O18 simulations suggest that the impacts of salinization on diminishing the resilience of salinity-intolerant trees can be detected up to 25&nbsp;years before the glycophytic trees are threatened with regime shift to halophytic species. This early detection provides critical lead time and valuable information and insights useful for planning adaptation strategy to mitigate against the adverse impacts of sea level rise and climate change.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10040-019-01930-3","usgsCitation":"Teh, S.Y., Koh, H.L., DeAngelis, D.L., Voss, C.I., and da Silveira Lobo Sternberg, L., 2019, Modeling δ18O as an early indicator of regime shift arising from salinity stress in coastal vegetation: Hydrogeology Journal, v. 27, no. 4, p. 1257-1276, https://doi.org/10.1007/s10040-019-01930-3.","productDescription":"10 p.","startPage":"1257","endPage":"1276","ipdsId":"IP-095257","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":361502,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"4","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Teh, Su Yean","contributorId":202650,"corporation":false,"usgs":false,"family":"Teh","given":"Su","email":"","middleInitial":"Yean","affiliations":[{"id":36510,"text":"School of Mathematicla Sciences, Universiti Sains Malaysia","active":true,"usgs":false}],"preferred":false,"id":757975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koh, Hock Lye","contributorId":202651,"corporation":false,"usgs":false,"family":"Koh","given":"Hock","email":"","middleInitial":"Lye","affiliations":[{"id":36511,"text":"Sunway University Business School, Jalan Universiti, Malaysia","active":true,"usgs":false}],"preferred":false,"id":757976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":757974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":757977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"da Silveira Lobo Sternberg, Leonel","contributorId":206740,"corporation":false,"usgs":false,"family":"da Silveira Lobo Sternberg","given":"Leonel","email":"","affiliations":[{"id":13532,"text":"Department of Biology, University of Miami","active":true,"usgs":false}],"preferred":false,"id":757978,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70201029,"text":"sir20185159 - 2019 - California’s exposure to volcanic hazards","interactions":[],"lastModifiedDate":"2019-12-10T12:19:03","indexId":"sir20185159","displayToPublicDate":"2019-02-25T05:35:49","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5159","displayTitle":"California’s Exposure to Volcanic Hazards","title":"California’s exposure to volcanic hazards","docAbstract":"<p>The potential for damaging earthquakes, landslides, floods, tsunamis, and wildfires is widely recognized in California. The same cannot be said for volcanic eruptions, despite the fact that they occur in the state about as frequently as the largest earthquakes on the San Andreas Fault. At least ten eruptions have taken place in the past 1,000 years, and future volcanic eruptions are inevitable.</p><p>The U.S. Geological Survey’s (USGS) national volcanic threat assessment identifies eight young volcanic areas in California as moderate, high, or very high threat. Of the eight volcanic areas that exist in California, molten rock resides beneath at least seven of these—Medicine Lake volcano, Mount Shasta, Lassen Volcanic Center, Clear Lake volcanic field, the Long Valley volcanic region, Coso volcanic field, and Salton Buttes—and are therefore considered “active” volcanoes producing volcanic earthquakes, toxic gas emissions, hot springs, geothermal systems, and (or) ground movement.</p><p>The USGS California Volcano Observatory in Menlo Park, California, monitors these potentially hazardous volcanoes to help communities and government authorities understand, prepare for, and respond to volcanic activity. Although volcanic activity can sometimes be forecast, eruptions, like earthquakes or tsunamis, cannot be prevented. Understanding the hazards and identifying what and who is in harm’s way is the first step in mitigating volcanic risk and building community resilience to volcanic hazards.</p><p>This report, which was prepared in collaboration with the California Governor’s Office of Emergency Services and the California Geological Survey, provides a broad perspective on the state’s exposure to volcanic hazards by integrating volcanic hazard information with geospatial data on at-risk populations, infrastructure, and resources. This information is intended to prompt site- and sector-specific vulnerability analyses and preparation of hazard mitigation and response plans.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185159","collaboration":"Prepared in cooperation with the California Governor’s Office of Emergency Services and the California Geological Survey","usgsCitation":"Mangan, M., Ball, J., Wood, N., Jones, J.L., Peters, J., Abdollahian, N., Dinitz, L., Blankenheim, S., Fenton, J., and Pridmore, C., 2019, California’s exposure to volcanic hazards (ver. 1.1, December 2019): U.S. Geological Survey Scientific Investigations Report 2018–5159, 49 p., https://doi.org/10.3133/sir20185159.","productDescription":"Report: vi, 49 p.; 2 Appendixes","numberOfPages":"58","ipdsId":"IP-092973","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":370069,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2018/5159/versionHist.txt"},{"id":361550,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5159/sir20185159_appendix2_ver1.1.xlsx","text":"Appendix 2","size":"39 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2018-5159 Appendix 2"},{"id":361551,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5159/sir20185159_appendix3_ver1.1.xlsx","text":"Appendix 3","size":"34 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2018-5159 Appendix 3"},{"id":361442,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5159/sir20185159ver1.1.pdf","text":"Report","size":"33.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5159"},{"id":370115,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5159/coverthb.jpg"}],"country":"United 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 \"}}]}","contact":"<p><a href=\"https://volcanoes.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://volcanoes.usgs.gov/\">Volcano Science Center</a><br>U.S. Geological Survey<br>345 Middlefield Road, MS 910<br>Menlo Park, CA 94025</p>","tableOfContents":"<ul><li>Introduction</li><li>Hazards and Impacts</li><li>“Watch List” Volcanoes and Hazard Zones</li><li>Societal Exposure to Volcanic Hazards</li><li>Summary and Next Steps</li><li>Acknowledgments</li><li>References</li><li>Glossary</li><li>Appendixes 1–3</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2019-02-25","revisedDate":"2019-12-06","noUsgsAuthors":false,"publicationDate":"2019-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Mangan, Margaret 0000-0002-5273-8053 mmangan@usgs.gov","orcid":"https://orcid.org/0000-0002-5273-8053","contributorId":107982,"corporation":false,"usgs":true,"family":"Mangan","given":"Margaret","email":"mmangan@usgs.gov","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":751908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ball, Jessica 0000-0002-7837-8180 jlball@usgs.gov","orcid":"https://orcid.org/0000-0002-7837-8180","contributorId":213475,"corporation":false,"usgs":true,"family":"Ball","given":"Jessica","email":"jlball@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":751909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Nathan 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":71151,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":751910,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Jamie L. 0000-0002-9967-3314 jamiejones@usgs.gov","orcid":"https://orcid.org/0000-0002-9967-3314","contributorId":172111,"corporation":false,"usgs":true,"family":"Jones","given":"Jamie L.","email":"jamiejones@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":751912,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peters, Jeff 0000-0003-4312-0590 jpeters@usgs.gov","orcid":"https://orcid.org/0000-0003-4312-0590","contributorId":4711,"corporation":false,"usgs":true,"family":"Peters","given":"Jeff","email":"jpeters@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":751917,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Abdollahian, Nina 0000-0002-8607-2202 nabdollahian@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-2202","contributorId":92149,"corporation":false,"usgs":true,"family":"Abdollahian","given":"Nina","email":"nabdollahian@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":751911,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dinitz, Laura","contributorId":52330,"corporation":false,"usgs":true,"family":"Dinitz","given":"Laura","affiliations":[],"preferred":false,"id":751913,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blankenheim, Sharon","contributorId":210773,"corporation":false,"usgs":false,"family":"Blankenheim","given":"Sharon","email":"","affiliations":[{"id":28116,"text":"California Office of Emergency Services","active":true,"usgs":false}],"preferred":false,"id":751914,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fenton, Johanna","contributorId":210774,"corporation":false,"usgs":false,"family":"Fenton","given":"Johanna","affiliations":[{"id":38146,"text":"Caliifornia Office of Emergency Services","active":true,"usgs":false}],"preferred":false,"id":751915,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pridmore, Cynthia","contributorId":210775,"corporation":false,"usgs":false,"family":"Pridmore","given":"Cynthia","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":751916,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70201151,"text":"sir20185163 - 2019 - Upgrades to a Fortran program for estimating stream transit losses of reusable water, El Paso and Pueblo Counties, Colorado","interactions":[],"lastModifiedDate":"2019-02-26T09:23:15","indexId":"sir20185163","displayToPublicDate":"2019-02-22T14:30:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5163","displayTitle":"Upgrades to a Fortran Program for Estimating Stream Transit Losses of Reusable Water, El Paso and Pueblo Counties, Colorado","title":"Upgrades to a Fortran program for estimating stream transit losses of reusable water, El Paso and Pueblo Counties, Colorado","docAbstract":"<p>In 2016, the U.S. Geological Survey, in cooperation with Pikes Peak Regional Water Authority and the Colorado Water Conservation Board, began a study to modernize a Fortran transit-loss accounting program developed by the U.S. Geological Survey to estimate net reusable flows in Fountain and Monument Creeks in El Paso and Pueblo Counties, Colorado. More than 6,000 lines of this FORTRAN77 transit-loss accounting program were revised to comply with the newer Fortran 2003 standard. The upgrade to the newer standard involved making changes in formatting and syntax on each line and, when available, adding new programming constructs that comply with the new standard. These upgrades produced a more readable Fortran program that includes safeguards to prevent accidental mistyping of variables and unintentional changes in named constants during program execution. Program revisions also introduced dynamic array allocation, whole array processing, and handling of input errors to the upgraded transit-loss accounting program.</p><p>During the upgrade from FORTRAN77 to the Fortran 2003 standard, revisions were made incrementally to the original transit-loss Fortran program. Because FORTRAN77 is a subset of Fortran 2003, the legacy FORTRAN77 statements and the upgraded Fortran 2003 statements can be compiled within the same program, permitting program revisions to be gradually phased in on a line-by-line basis. This incremental approach helped mitigate risks of introducing logic errors into the Fortran program that could produce incorrect transit-loss estimates.</p><p>Verification of the upgraded transit-loss accounting program focused on reproducing archived reusable return flows (RRF) for historical daily runs from January 5, 2015, to October 31, 2018. Because interim files storing daily streambank losses were not historically archived, no record of antecedent streambank storage losses to hydraulically connected alluvial deposits were available to provide initial conditions for each daily run. To overcome the problem of missing historical bank storage and recovery files that contain important information relating to antecedent streambank storage conditions, a 104-day “spin-up” period was required before RRFs calculated by the upgraded program and the original program matched. Estimated daily reusable return flows from archived output generated by the original program and output generated by the upgraded program were compared after this initial “spin-up” period. Daily reusable return flow estimates at delivery nodes and at the bottoms of subreaches from the upgraded Fortran program matched those output by the original program to within 0.01 and 0.0001 cubic feet per second, respectively.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185163","collaboration":"Prepared in cooperation with the Pikes Peak Regional Water Authority and the Colorado Water Conservation Board","usgsCitation":"Colarullo, S.J., and Miller, L.D., 2019, Upgrades to a Fortran program for estimating stream transit losses of reusable water, El Paso and Pueblo Counties, Colorado: U.S. Geological Survey Scientific Investigations Report 2018–5163, 21 p., https://doi.org/10.3133/sir20185163.","productDescription":"Report: vi, 21 p.; 1 Sheet (14 x 26 inches)","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101530","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":361220,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5163/sir20185163.pdf","text":"Report","size":"3.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5163"},{"id":361462,"rank":4,"type":{"id":22,"text":"Related Work"},"url":" https://code.usgs.gov/water/Transit-Loss","text":"Water- Transit Loss","linkHelpText":"- FORTRAN 77 transit-loss accounting program"},{"id":361221,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2018/5163/sir20185163_plate01.pdf","size":"316 KB"},{"id":361219,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5163/coverthb.jpg"}],"country":"United States","state":"Colorado","city":"El Paso, Pueblo","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -105.26687622070312,\n              38.151837403006766\n            ],\n            [\n              -104.3536376953125,\n              38.151837403006766\n            ],\n            [\n              -104.3536376953125,\n              39.102357437817595\n            ],\n            [\n              -105.26687622070312,\n              39.102357437817595\n            ],\n            [\n              -105.26687622070312,\n              38.151837403006766\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_co@usgs.gov\" data-mce-href=\"mailto:dc_co@usgs.gov\">Director</a>, <a href=\"https://co.water.usgs.gov/\" data-mce-href=\"https://co.water.usgs.gov/\">Colorado Water Science Center</a><br>U.S. Geological Survey<br>Denver Federal Center, MS-415<br>Lakewood, CO 80225</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Description of the Transit-Loss Accounting Program</li><li>Transit-Loss Accounting Program Modifications, 1987–2012</li><li>Upgrade of the Transit-Loss Accounting Program from FORTRAN77 to Fortran 2003</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2019-02-22","noUsgsAuthors":false,"publicationDate":"2019-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Colarullo, Susan J. 0000-0003-4504-0068","orcid":"https://orcid.org/0000-0003-4504-0068","contributorId":205315,"corporation":false,"usgs":true,"family":"Colarullo","given":"Susan","email":"","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":752936,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Lisa D. 0000-0002-3523-0768 ldmiller@usgs.gov","orcid":"https://orcid.org/0000-0002-3523-0768","contributorId":1125,"corporation":false,"usgs":true,"family":"Miller","given":"Lisa","email":"ldmiller@usgs.gov","middleInitial":"D.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":752937,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70204681,"text":"70204681 - 2019 - Can’t see the random forest for the decision trees: Selecting predictive models for restoration ecology","interactions":[],"lastModifiedDate":"2019-09-16T12:29:37","indexId":"70204681","displayToPublicDate":"2019-02-22T14:18:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Can’t see the random forest for the decision trees: Selecting predictive models for restoration ecology","docAbstract":"Improving predictions of restoration outcomes is increasingly important to resource managers for accountability and adaptive management, yet there is limited guidance for selecting a predictive model from the multitude available. The goal of this paper was to identify an optimal predictive framework for restoration ecology using eleven modeling frameworks (including, machine learning, inferential, and ensemble approaches), and three data groups (field data, geographic data [GIS], and a combination thereof). We test this approach with a dataset from a large post-fire sagebrush reestablishment project in the Great Basin, USA. Predictive power varied among models and data groups, ranging from 58-79% accuracy. Finer scale field data generally had the greatest predictive power, although GIS data were present in the best models overall. An ensemble prediction computed from the ten models parameterized to field data was well above average for accuracy but was outperformed by others that prioritized model parsimony by selecting predictor variables based on rankings of their importance among all candidate models. The variation in predictive power among a suite of modeling frameworks underscores the importance of a model comparison and refinement approach that evaluates multiple models and data groups, and selects variables based on their contribution to predictive power. The enhanced understanding of factors influencing restoration outcomes accomplished by this framework has the potential to aid the adaptive management process for improving future restoration outcomes.","language":"English","publisher":"Wiley","doi":"10.1111/rec.12938","usgsCitation":"Barnard, D., Germino, M., Pilliod, D., Arkle, R., Applestein, C., Davidson, B., and Fisk, M., 2019, Can’t see the random forest for the decision trees: Selecting predictive models for restoration ecology: Restoration Ecology, v. 27, no. 5, p. 1053-1063, https://doi.org/10.1111/rec.12938.","productDescription":"11 p.","startPage":"1053","endPage":"1063","ipdsId":"IP-092214","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":366415,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnard, David 0000-0003-1877-3151","orcid":"https://orcid.org/0000-0003-1877-3151","contributorId":218008,"corporation":false,"usgs":true,"family":"Barnard","given":"David","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":218007,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":218009,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768049,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arkle, Robert 0000-0003-3021-1389","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":218013,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Applestein, Cara 0000-0002-7923-8526","orcid":"https://orcid.org/0000-0002-7923-8526","contributorId":218010,"corporation":false,"usgs":true,"family":"Applestein","given":"Cara","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768050,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Davidson, Bill 0000-0003-1315-479X","orcid":"https://orcid.org/0000-0003-1315-479X","contributorId":218011,"corporation":false,"usgs":true,"family":"Davidson","given":"Bill","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768051,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fisk, Matthew 0000-0002-2250-0116","orcid":"https://orcid.org/0000-0002-2250-0116","contributorId":218012,"corporation":false,"usgs":true,"family":"Fisk","given":"Matthew","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768052,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
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