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The revision of federal safety regulations for integrity management of gas transmission pipelines to require explicit consideration of seismicity increases the importance for operators to be actively identifying high-consequence areas (HCAs), evaluating seismic-related threats, and choosing a risk model to support risk management decisions. To ensure equal access to information by both operators and inspectors, the authors have compiled publicly available data and tools for practical seismic risk assessments, such as Microsoft building footprints, the USGS National Seismic Hazard Models, and the USGS Ground Failure product.

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River waters contain complex chemical mixtures derived from natural and anthropogenic sources. Aquatic organisms are exposed to the entire chemical composition of the water, resulting in potential effects at the organismal through ecosystem level. This study applied a holistic approach to assess landscape, hydrological, chemical, and biological variables. On-site mobile laboratory experiments were conducted to evaluate biological effects of exposure to chemical mixtures in the Shenandoah River Watershed. A suite of 534 inorganic and organic constituents were analyzed, of which 273 were detected. A watershed-scale accumulated wastewater model was developed to predict environmental concentrations of chemicals derived from wastewater treatment plants (WWTPs) to assess potential aquatic organism exposure for all stream reaches in the watershed. Measured and modeled concentrations generally were within a factor of 2. Ecotoxicological effects from exposure to individual components of the chemical mixture were evaluated using risk quotients (RQs) based on measured or predicted environmental concentrations and no effect concentrations or chronic toxicity threshold values. Seventy-two percent of the compounds had RQ values <0.1, indicating limited risk from individual chemicals. However, when individual RQs were aggregated into a risk index, most stream reaches receiving WWTP effluent posed potential risk to aquatic organisms from exposure to complex chemical mixtures.

","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.1c04045","usgsCitation":"Barber, L., Faunce, K.E., Bertolatus, D., Hladik, M.L., Jasmann, J., Keefe, S.H., Kolpin, D., Meyer, M., Rapp, J.L., Roth, D.A., and Vajda, A.M., 2022, Watershed-scale risk to aquatic organisms from complex chemical mixtures in the Shenandoah River: Environmental Science & Technology, v. 56, no. 2, p. 845-861, https://doi.org/10.1021/acs.est.1c04045.","productDescription":"17 p.","startPage":"845","endPage":"861","ipdsId":"IP-117896","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":395760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.265625,\n 36.69485094156225\n ],\n [\n -77.640380859375,\n 36.69485094156225\n ],\n [\n -77.640380859375,\n 39.00211029922515\n ],\n [\n -82.265625,\n 39.00211029922515\n ],\n [\n -82.265625,\n 36.69485094156225\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-01-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Barber, Larry B. 0000-0002-0561-0831","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":218953,"corporation":false,"usgs":true,"family":"Barber","given":"Larry B.","affiliations":[{"id":5044,"text":"National Research Program - 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Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":834303,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keefe, Steffanie H. 0000-0002-3805-6101 shkeefe@usgs.gov","orcid":"https://orcid.org/0000-0002-3805-6101","contributorId":2843,"corporation":false,"usgs":true,"family":"Keefe","given":"Steffanie","email":"shkeefe@usgs.gov","middleInitial":"H.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":834304,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834305,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Meyer, Michael T. 0000-0001-6006-7985","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":205665,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":834306,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rapp, Jennifer L. 0000-0003-2253-9886 jrapp@usgs.gov","orcid":"https://orcid.org/0000-0003-2253-9886","contributorId":197342,"corporation":false,"usgs":true,"family":"Rapp","given":"Jennifer","email":"jrapp@usgs.gov","middleInitial":"L.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":834314,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Roth, David A. 0000-0002-7515-3533 daroth@usgs.gov","orcid":"https://orcid.org/0000-0002-7515-3533","contributorId":2340,"corporation":false,"usgs":true,"family":"Roth","given":"David","email":"daroth@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":834308,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Vajda, Alan M.","contributorId":156301,"corporation":false,"usgs":false,"family":"Vajda","given":"Alan","email":"","middleInitial":"M.","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":834309,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70228318,"text":"70228318 - 2022 - Pathways for avian influenza virus spread: GPS reveals wild waterfowl in commercial livestock facilities and connectivity with the natural wetland landscape","interactions":[],"lastModifiedDate":"2022-09-27T16:42:47.008718","indexId":"70228318","displayToPublicDate":"2022-01-02T06:47:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3849,"text":"Transboundary and Emerging Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Pathways for avian influenza virus spread: GPS reveals wild waterfowl in commercial livestock facilities and connectivity with the natural wetland landscape","docAbstract":"

Zoonotic diseases are of considerable concern to the human population and viruses such as avian influenza (AIV) threaten food security, wildlife conservation and human health. Wild waterfowl and the natural wetlands they use are known AIV reservoirs, with birds capable of virus transmission to domestic poultry populations. While infection risk models have linked migration routes and AIV outbreaks, there is a limited understanding of wild waterfowl presence on commercial livestock facilities, and movement patterns linked to natural wetlands. We documented 11 wild waterfowl (three Anatidae species) in or near eight commercial livestock facilities in Washington and California with GPS telemetry data. Wild ducks used dairy and beef cattle feed lots and facility retention ponds during both day and night suggesting use for roosting and foraging. Two individuals (single locations) were observed inside poultry facility boundaries while using nearby wetlands. Ducks demonstrated high site fidelity, returning to the same areas of habitats (at livestock facilities and nearby wetlands), across months or years, showed strong connectivity with surrounding wetlands, and arrived from wetlands up to 1251 km away in the week prior. Telemetry data provides substantial advantages over observational data, allowing assessment of individual movement behaviour and wetland connectivity that has significant implications for outbreak management. Telemetry improves our understanding of risk factors for waterfowl–livestock virus transmission and helps identify factors associated with coincident space use at the wild waterfowl–domestic livestock interface. Our research suggests that even relatively small or isolated natural and artificial water or food sources in/near facilities increases the likelihood of attracting waterfowl, which has important consequences for managers attempting to minimize or prevent AIV outbreaks. Use and interpretation of telemetry data, especially in near-real-time, could provide key information for reducing virus transmission risk between waterfowl and livestock, improving protective barriers between wild and domestic species, and abating outbreaks.

","language":"English","publisher":"Wiley","doi":"10.1111/tbed.14445","usgsCitation":"McDuie, F., Matchett, E., Prosser, D., Takekawa, J., Pitesky, M.E., Lorenz, A., McCuen, M.M., Overton, C.T., Ackerman, J.T., De La Cruz, S.E., and Casazza, M.L., 2022, Pathways for avian influenza virus spread: GPS reveals wild waterfowl in commercial livestock facilities and connectivity with the natural wetland landscape: Transboundary and Emerging Diseases, v. 69, no. 5, p. 2898-2912, https://doi.org/10.1111/tbed.14445.","productDescription":"15 p.","startPage":"2898","endPage":"2912","ipdsId":"IP-133143","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":449295,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/tbed.14445","text":"External Repository"},{"id":436018,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YANKHK","text":"USGS data release","linkHelpText":"Locations of Pacific Flyway Ducks in and near Commercial Livestock Facilities of the Western USA (2015-2021)"},{"id":395605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"69","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"McDuie, Fiona 0000-0002-1948-5613","orcid":"https://orcid.org/0000-0002-1948-5613","contributorId":222936,"corporation":false,"usgs":true,"family":"McDuie","given":"Fiona","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833681,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833682,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":833683,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takekawa, John Y. 0000-0003-0217-5907","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":203805,"corporation":false,"usgs":false,"family":"Takekawa","given":"John Y.","affiliations":[{"id":36724,"text":"Audubon California, Richardson Bay Audubon Center and Sanctuary, Tiburon, CA","active":true,"usgs":false}],"preferred":false,"id":833684,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pitesky, Maurice E.","contributorId":176920,"corporation":false,"usgs":false,"family":"Pitesky","given":"Maurice","email":"","middleInitial":"E.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":833685,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lorenz, Austen 0000-0003-3657-5941","orcid":"https://orcid.org/0000-0003-3657-5941","contributorId":222610,"corporation":false,"usgs":true,"family":"Lorenz","given":"Austen","email":"","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":833686,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCuen, Madeline M","contributorId":275139,"corporation":false,"usgs":false,"family":"McCuen","given":"Madeline","email":"","middleInitial":"M","affiliations":[{"id":39913,"text":"former WERC","active":true,"usgs":false}],"preferred":false,"id":833687,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833688,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833689,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":202774,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833690,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833691,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70230312,"text":"70230312 - 2022 - Response in the water level of Anvil Lake, Wisconsin, to changes in meteorological and climatic changes, Wisconsin","interactions":[],"lastModifiedDate":"2022-09-13T16:42:30.131021","indexId":"70230312","displayToPublicDate":"2022-01-01T11:39:31","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"title":"Response in the water level of Anvil Lake, Wisconsin, to changes in meteorological and climatic changes, Wisconsin","docAbstract":"Anvil Lake, a relatively shallow seepage lake in northern Wisconsin, USA, has experienced dramatic changes in water level since elevation records began in 1938 in response to changes in meteorological and climatic conditions (Figure 1. Robertson et al., 2018). Anvil Lake’s water level record shows a pronounced 10–15-yr cycle, with recurring highs and lows with a typical swing of over 1 m. Although experiencing large cycles in water levels, the long-term average levels were relatively stable until about 1987, when water level dropped dramatically by an additional 1 m (in 2016). Water levels then rebounded dramatically, reaching near “normal” water levels in 2020. At its lowest level, the lake had a maximum depth of 8.2 m (mean depth of 4.7 m) and an area of 128 ha.\nLike most long-term records, Anvil Lake’s water level record has been measured by several observers using various techniques. To verify the consistency of the various datums used throughout this period, historical photographs with the water’s edge identified were obtained, tied to NAVD 1988 using a Real Time Kinematic satellite global positioning system, and compared with the measured water levels (See Figure 1).\nTo determine the causes of the changes in water level, a complete water budget was estimated for Anvil Lake from 1980 to 2014. Water levels in Anvil Lake were simulated (Figure 1) using a hydrodynamic model (General Lake Model, GLM), with daily lake evaporation estimated by\nGLM, monthly lake/groundwater exchange estimated with a groundwater model (MODFLOW), daily precipitation from the North American Land Data Assimilation System (NLDAS), and stream inflow and outflow were set as zero because the lake has no inlets or outlet. Atmospheric fluxes (precipitation minus evaporation) primarily drove the lake-level fluctuations and trends, but sub-decadal fluctuations in net groundwater exchange (groundwater inflow minus lake seepage) either enhanced or reduced the lake level response to the atmospheric drivers.\nThe changes in water levels were shown to affect the extent of stratification and water quality in the lake (Robertson et al., 2018). During periods of lower precipitation and lower water levels, Anvil Lake was a polymictic lake, whereas during periods of higher precipitation and higher water levels the lake was a dimictic lake with stratification lasting throughout summer. During periods with higher water levels, the water quality in the lake was shown to improve slightly as a result of the nutrients being diluted in a larger volume of water. If precipitation increases in the future, as results from many General Circulation Models (GCMs) suggest (Robertson et al., 2016), and if that outweighs the effects of increased evaporation caused by increased air temperatures, water levels in Anvil Lake may be expected to fluctuate at a higher level. Higher water levels in Anvil Lake are expected to result in the lake becoming more strongly stratified and have slightly improved water quality (lower nutrient and algal concentrations and increased water clarity) (Robertson et al., 2018).","language":"English","publisher":"Wisconsin Department of Natural Resources","usgsCitation":"Robertson, D., 2022, Response in the water level of Anvil Lake, Wisconsin, to changes in meteorological and climatic changes, Wisconsin, 2 p.","productDescription":"2 p.","ipdsId":"IP-130734","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":406607,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":398290,"type":{"id":15,"text":"Index Page"},"url":"https://wicci.wisc.edu/water-resources-working-group/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wisconsin","otherGeospatial":"Anvil Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.07800674438477,\n 45.93515431167519\n ],\n [\n -89.05139923095703,\n 45.93515431167519\n ],\n [\n -89.05139923095703,\n 45.9536560062781\n ],\n [\n -89.07800674438477,\n 45.9536560062781\n ],\n [\n -89.07800674438477,\n 45.93515431167519\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":217258,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":839932,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70262314,"text":"70262314 - 2022 - Kirtland’s Warbler breeding productivity and habitat use in red pine-dominated habitat in Wisconsin, USA","interactions":[],"lastModifiedDate":"2025-01-23T17:39:20.813095","indexId":"70262314","displayToPublicDate":"2022-01-01T11:26:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Kirtland’s Warbler breeding productivity and habitat use in red pine-dominated habitat in Wisconsin, USA","docAbstract":"

During the breeding season, Kirtland’s Warblers (Setophaga kirtlandii) are strongly associated with young jack pine (Pinus banksiana) forests in northern Lower Michigan, USA. Since 2007, the species has been breeding in unusual habitat, red pine (Pinus resinosa) dominated plantations, in central Wisconsin, USA. Kirtland’s Warbler productivity and habitat use in red pine is not well understood, and the central Wisconsin population is at a range edge, a situation often associated with lower productivity. To compare range-edge and range-core populations, we estimated reproductive success and characterized habitat use of Kirtland’s Warblers in central Wisconsin red pine-dominated plantations during 2015–2017 using logistic regression models. We also monitored nests and fledgling success, and estimated nest survival using logistic exposure models. Trees were closer together and herbaceous vegetation was taller and denser within territories than at randomly located points outside of territories. Females selected nest sites with deeper dead ground vegetation and live vegetation that was taller and denser than was available at randomly located points within male territories. Nest success was not strongly influenced by within-patch habitat factors. Nest daily survival rate was 0.97 (95% CI = 0.94–0.98). The average number of young fledged per nest was between 2.5 and 2.8. Nest parasitism by Brown-headed Cowbirds (Molothrus ater) was 22.7%. Overall, reproductive success in the peripheral central Wisconsin breeding population of Kirtland’s Warblers that used red pine-dominated plantations was similar to that of Kirtland’s Warblers breeding in typical jack pine habitat in the range core. Young red pine-dominated habitat appears to approximate young jack pine in habitat quality for Kirtland’s Warblers, and this may provide managers some flexibility in habitat maintenance for this conservation-reliant species.

","language":"English","publisher":"Resilience Alliance","doi":"10.5751/ace-02009-170103","usgsCitation":"Olah, A., Ribic, C., Grveles, K., Warner, S., Lopez, D., and Pidgeon, A., 2022, Kirtland’s Warbler breeding productivity and habitat use in red pine-dominated habitat in Wisconsin, USA: Avian Conservation and Ecology, v. 17, no. 1, 3, 23 p., https://doi.org/10.5751/ace-02009-170103.","productDescription":"3, 23 p.","ipdsId":"IP-107637","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481096,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-02009-170103","text":"Publisher Index Page"},{"id":481018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Adams County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-89.8982,44.2493],[-89.8376,44.249],[-89.7247,44.2479],[-89.717,44.2475],[-89.606,44.2458],[-89.5977,44.2458],[-89.5976,44.156],[-89.5981,44.0685],[-89.598,43.9824],[-89.5972,43.8945],[-89.5978,43.818],[-89.5995,43.7306],[-89.6,43.6427],[-89.7195,43.643],[-89.779,43.6411],[-89.7866,43.6411],[-89.7891,43.6433],[-89.786,43.6506],[-89.7892,43.6597],[-89.7892,43.6647],[-89.7924,43.667],[-89.7974,43.6693],[-89.8012,43.6697],[-89.8114,43.6788],[-89.8178,43.6915],[-89.8273,43.7034],[-89.828,43.7065],[-89.828,43.7106],[-89.828,43.7165],[-89.8318,43.722],[-89.8376,43.727],[-89.842,43.7288],[-89.8433,43.7338],[-89.8446,43.7411],[-89.8447,43.7497],[-89.8466,43.7566],[-89.8504,43.762],[-89.8549,43.7661],[-89.8612,43.772],[-89.8613,43.7766],[-89.8695,43.7834],[-89.8785,43.7924],[-89.8855,43.8002],[-89.8912,43.8052],[-89.9033,43.8133],[-89.9084,43.8174],[-89.9135,43.8242],[-89.9174,43.832],[-89.9231,43.8397],[-89.9327,43.8469],[-89.9384,43.8515],[-89.9479,43.8546],[-89.9524,43.8596],[-89.9633,43.8723],[-89.9659,43.8805],[-89.9672,43.8914],[-89.9705,43.901],[-89.9731,43.9101],[-89.9731,43.9178],[-89.9719,43.9206],[-89.9674,43.922],[-89.956,43.922],[-89.9522,43.9238],[-89.9503,43.9252],[-89.9484,43.9311],[-89.9504,43.9425],[-89.9492,43.9457],[-89.9524,43.9539],[-89.9582,43.9603],[-89.964,43.9785],[-89.9685,43.9875],[-89.973,43.9944],[-89.9769,43.9985],[-89.98,43.9998],[-89.9915,44.0029],[-89.9979,44.0047],[-90.0036,44.0075],[-90.0062,44.0102],[-90.0049,44.0129],[-89.9999,44.0166],[-89.9974,44.0184],[-89.9955,44.0221],[-89.9993,44.028],[-90.0032,44.0316],[-90.0108,44.0384],[-90.0154,44.0443],[-90.0179,44.0498],[-90.0186,44.0561],[-90.018,44.0598],[-90.0206,44.0616],[-90.0238,44.0675],[-90.0264,44.0748],[-90.0265,44.083],[-90.0253,44.0903],[-90.0234,44.0953],[-90.0209,44.0985],[-90.0139,44.1013],[-90.0107,44.104],[-90.0088,44.1072],[-90.0108,44.1109],[-90.0114,44.1172],[-90.0076,44.1204],[-90.0019,44.1223],[-89.9949,44.1232],[-89.9886,44.1241],[-89.9797,44.1287],[-89.9753,44.1338],[-89.9715,44.1415],[-89.9715,44.1497],[-89.971,44.1598],[-89.9697,44.162],[-89.9685,44.163],[-89.964,44.1634],[-89.957,44.1644],[-89.9519,44.1648],[-89.9474,44.1653],[-89.943,44.1644],[-89.9385,44.1622],[-89.9353,44.1581],[-89.9308,44.1521],[-89.9289,44.1517],[-89.9263,44.1526],[-89.9219,44.1554],[-89.9181,44.1618],[-89.9188,44.1668],[-89.9226,44.1722],[-89.9227,44.174],[-89.9207,44.175],[-89.9195,44.175],[-89.9163,44.1741],[-89.9118,44.1732],[-89.9074,44.1736],[-89.901,44.1764],[-89.8972,44.1805],[-89.8979,44.1842],[-89.903,44.1864],[-89.9106,44.1878],[-89.9151,44.1914],[-89.9164,44.1932],[-89.9145,44.1955],[-89.9056,44.1969],[-89.9024,44.1992],[-89.9043,44.2014],[-89.9114,44.2051],[-89.9165,44.2092],[-89.9191,44.2142],[-89.9185,44.2183],[-89.9127,44.221],[-89.9051,44.2224],[-89.9,44.2279],[-89.893,44.2284],[-89.8924,44.2325],[-89.8944,44.2398],[-89.8982,44.2493]]]},\"properties\":{\"name\":\"Adams\",\"state\":\"WI\"}}]}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Olah, Ashley","contributorId":348827,"corporation":false,"usgs":false,"family":"Olah","given":"Ashley","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":923813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":923812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grveles, Kim","contributorId":348828,"corporation":false,"usgs":false,"family":"Grveles","given":"Kim","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":923814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, Sarah","contributorId":348829,"corporation":false,"usgs":false,"family":"Warner","given":"Sarah","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":923815,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lopez, Davin","contributorId":348830,"corporation":false,"usgs":false,"family":"Lopez","given":"Davin","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":923816,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pidgeon, Anna","contributorId":348831,"corporation":false,"usgs":false,"family":"Pidgeon","given":"Anna","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":923817,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256646,"text":"70256646 - 2022 - Agent-based modeling of movements and habitat selection by mid-continent mallards","interactions":[],"lastModifiedDate":"2024-09-09T16:11:44.295133","indexId":"70256646","displayToPublicDate":"2022-01-01T11:07:39","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"FWS/CSS-143-2022","title":"Agent-based modeling of movements and habitat selection by mid-continent mallards","docAbstract":"

We found that the absence of existing conservation measures would reduce wintering mallard population size by ~70-80%, underlining the importance of current wetland easements for waterfowl foraging. Under standard conditions, the partial active flooding of easements later in the season and the upgrading of unmanaged wetlands to managed status resulted in greatest mallard populations, indicating that active flooding (stored water release) was able to considerably increase carrying capacity under strong drought conditions.

","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Weller, F., Webb, E.B., Beatty, W., Fogenburg, S., Kesler, D., Blenk, R., Eadie, J., Ringelman, K., and Miller, M.L., 2022, Agent-based modeling of movements and habitat selection by mid-continent mallards: Cooperator Science Series FWS/CSS-143-2022, ii, 102 p.","productDescription":"ii, 102 p.","ipdsId":"IP-138825","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":431977,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/media/agent-based-modeling-movements-and-habitat-selection-mid-continent-mallards"},{"id":433631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Weller, Florian G.","contributorId":341462,"corporation":false,"usgs":false,"family":"Weller","given":"Florian G.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":908463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":908464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beatty, William S. 0000-0003-0013-3113","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":224795,"corporation":false,"usgs":true,"family":"Beatty","given":"William S.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":908465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fogenburg, Sean","contributorId":341463,"corporation":false,"usgs":false,"family":"Fogenburg","given":"Sean","affiliations":[],"preferred":false,"id":908466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kesler, Dylan","contributorId":341464,"corporation":false,"usgs":false,"family":"Kesler","given":"Dylan","affiliations":[{"id":37290,"text":"The Institute for Bird Populations","active":true,"usgs":false}],"preferred":false,"id":908467,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blenk, Robert H.","contributorId":341465,"corporation":false,"usgs":false,"family":"Blenk","given":"Robert H.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":908468,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eadie, John M.","contributorId":341466,"corporation":false,"usgs":false,"family":"Eadie","given":"John M.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":908469,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ringelman, Kevin","contributorId":341467,"corporation":false,"usgs":false,"family":"Ringelman","given":"Kevin","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908470,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Miller, Matt L.","contributorId":341468,"corporation":false,"usgs":false,"family":"Miller","given":"Matt","email":"","middleInitial":"L.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":908471,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70227426,"text":"70227426 - 2022 - Gas hydrates on Alaskan marine margins","interactions":[],"lastModifiedDate":"2022-01-14T16:38:17.536274","indexId":"70227426","displayToPublicDate":"2022-01-01T10:32:18","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Gas hydrates on Alaskan marine margins","docAbstract":"

Gas hydrate distributions on the marine margins of the U.S. state of Alaska are more poorly known than those on other U.S. margins, where bottom simulating reflections have been systematically mapped on marine seismic data to support modern, quantitative assessments of gas-in-place in gas hydrates. The extent of bottom simulating reflections in the U.S. Beaufort Sea has been known since the late 1970s, and researchers have investigated the possibility that remnant gas hydrate persists in association with decaying subsea permafrost on both the U.S. and Canadian Beaufort continental shelves. In the Bering Sea, possible gas hydrate-related features have been widely mapped, revealing zones of free gas and concentrated gas hydrate within the hydrate stability zone in features called velocity amplitude anomalies (VAMPs). However, there are few reports on bottom simulating reflections along the more than 2500 km of the Aleutian arc and along the transform plate margin in southeast Alaska. Here we examine selected seismic profiles from southeast Alaska, along the Aleutian margin, and on the Bering continental slope, emphasizing surveys acquired with large airgun arrays, and review the results obtained from Bering Sea’s Aleutian Basin and from the U.S. Beaufort Sea. In the new analyses, we detect hydrate-related bottom simulating reflections in southeastern Alaska and the eastern and central parts of the Aleutian arc, but not in the western Aleutian arc or beneath the continental slope from the island arc north into the Aleutian Basin. In the Bering Sea, recognition of hydrate-related bottom simulating reflections is complicated by the widespread existence of a bottom simulating reflector associated with a diagenetic transition (opal CT). Our detection of continental slope hydrate-related bottom simulating reflections in southeast Alaska and the eastern and central Aleutian arcs expands the area of potential gas hydrate distribution on Alaskan margins and underscores the need for more systematic analysis of existing seismic data to inform quantitative evaluation of gas-in-place.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"World atlas of submarine gas hydrates in continental margins","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-81186-0_17","usgsCitation":"Ruppel, C.D., and Hart, P.E., 2022, Gas hydrates on Alaskan marine margins, chap. of World atlas of submarine gas hydrates in continental margins, p. 209-223, https://doi.org/10.1007/978-3-030-81186-0_17.","productDescription":"15 p.","startPage":"209","endPage":"223","ipdsId":"IP-122791","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":394384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bering Sea’s Aleutian basin, U.S. Beaufort Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -159.169921875,\n 69.59589006237648\n ],\n [\n -140.18554687499997,\n 69.59589006237648\n ],\n [\n -140.18554687499997,\n 73.42842364106816\n ],\n [\n -159.169921875,\n 73.42842364106816\n ],\n [\n -159.169921875,\n 69.59589006237648\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -177.01171875,\n 47.87214396888731\n ],\n [\n -153.017578125,\n 47.87214396888731\n ],\n [\n -153.017578125,\n 61.39671887310411\n ],\n [\n -177.01171875,\n 61.39671887310411\n ],\n [\n -177.01171875,\n 47.87214396888731\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-01-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruppel, Carolyn D. 0000-0003-2284-6632 cruppel@usgs.gov","orcid":"https://orcid.org/0000-0003-2284-6632","contributorId":195778,"corporation":false,"usgs":true,"family":"Ruppel","given":"Carolyn","email":"cruppel@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":830832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hart, Patrick E. 0000-0002-5080-1426 hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5080-1426","contributorId":2879,"corporation":false,"usgs":true,"family":"Hart","given":"Patrick","email":"hart@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":830833,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70228833,"text":"70228833 - 2022 - Interagency Flood Risk Management (InFRM) watershed hydrology assessment for the Neches River basin. Appendix D: RiverWare analyses","interactions":[],"lastModifiedDate":"2024-03-27T15:12:27.207997","indexId":"70228833","displayToPublicDate":"2022-01-01T10:07:41","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":17147,"text":"Interagency Flood Risk Management Report","active":true,"publicationSubtype":{"id":1}},"title":"Interagency Flood Risk Management (InFRM) watershed hydrology assessment for the Neches River basin. Appendix D: RiverWare analyses","docAbstract":"

RiverWare is a river system modeling tool developed by CADSWES (Center of Advanced Decision Support for Water and Environmental Systems) that allows the user to simulate complex reservoir operations and perform period-of-record analyses for different scenarios. For the InFRM hydrology studies, RiverWare is used to generate a homogeneous regulated POR by simulating the basin as if the reservoirs and their current rule sets had been present in the basin for the entire time period. Statistical analyses can then be performed on the extended records at the gages. This report summarizes the RiverWare portion of the hydrologic analysis being completed for the InFRM Hydrology study of the Neches River Basin.

The RiverWare model described in this chapter presents development of the Neches River Basin hydrology, which mimics current operational conditions. The use of the RiverWare program allows for data extension to periods prior to dam construction. The utilization of longer streamgage record improves discharge frequency results and increases the confidence of the analysis being performed. The modeling evaluation criteria are: (1) evaluate output based on validating policies and functions, and (2) prioritize operation based on surcharge and flood control. A detailed explanation of the Neches River Basin POR hydrology will be in a later section.

Calibration results will also be shown that illustrate model performance since the Salt Water Barrier (SWB) construction was completed in 2005. The time window simulation run is for water year (WY) 2005 – WY 2018. This time window also captures the time when Hurricane Harvey occurred (late August of 2017). Each simulated water year was inspected individually to better validate the results.

After calibration, a general run for January 01, 1929 through WY 2018 was made. Historical pool elevations along with observed inflows and outflows were compared against the model simulated results. More emphasis was put on B.A. Steinhagen’s operations because the dam captures two major rivers (i.e. the Angelina and the Neches Rivers). Results were inspected closely for B.A. Steinhagen’s pool and releases, the simulated discharges at the Neches at Evadale gage, and the simulated discharges at the SWB at Beaumont, Texas.

","language":"English","publisher":"Interagency Flood Risk Management","collaboration":"U.S. Army Corps of Engineers, Federal Emergency Management Agency","usgsCitation":"Wallace, D., 2022, Interagency Flood Risk Management (InFRM) watershed hydrology assessment for the Neches River basin. Appendix D: RiverWare analyses: Interagency Flood Risk Management Report, 66 p.","productDescription":"66 p.","ipdsId":"IP-113418","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":427144,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396305,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://webapps.usgs.gov/infrm/#ha"}],"country":"United States","state":"Texas","otherGeospatial":"Neches River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96,\n 32\n ],\n [\n -96,\n 30\n ],\n [\n -94,\n 30\n ],\n [\n -94,\n 32\n ],\n [\n -96,\n 32\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wallace, David S. 0000-0002-9134-8197","orcid":"https://orcid.org/0000-0002-9134-8197","contributorId":205198,"corporation":false,"usgs":true,"family":"Wallace","given":"David S.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":835669,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70229817,"text":"70229817 - 2022 - Relative bias in catch among long-term fish monitoring surveys within the San Francisco Estuary","interactions":[],"lastModifiedDate":"2022-03-18T14:34:13.706782","indexId":"70229817","displayToPublicDate":"2022-01-01T09:21:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Relative bias in catch among long-term fish monitoring surveys within the San Francisco Estuary","docAbstract":"

Fish monitoring gears rarely capture all available fish, an inherent bias in monitoring programs referred to as catchability. Catchability is a source of bias that can be affected by numerous aspects of gear deployment (e.g., deployment speed, mesh size, and avoidance behavior). Thus, care must be taken when multiple surveys—especially those using different sampling methods—are combined to answer spatio-temporal questions about population and community dynamics. We assessed relative catchability differences among four long-term fish monitoring surveys from the San Francisco Estuary: the Bay Study Otter Trawl (BSOT), the Bay Study Midwater Trawl (BSMT), the Fall Midwater Trawl (FMWT), and the Suisun Marsh Otter Trawl (SMOT). We used generalized additive models with a spatio-temporal smoother and survey as a fixed effect to predict gear-specific estimates of catch for 45 different fish species within large and small size classes. We used estimates of the fixed effect coefficients for each survey (e.g., BSOT) relative to the reference gear (FMWT) to develop relative measures of catchability among taxa, surveys, and fish-size classes, termed the catch-ratio. We found higher relative catchability of 27%, 22%, and 57% of fish species in large size classes from the FMWT than in the BSMT, BSOT, or SMOT, respectively. In the small size class, relative catchability was higher in the FMWT than the BSMT, BSOT, or SMOT for 50%, 18%, and 25% of fish species, respectively. As expected, relative catchability of demersal species was higher in the otter trawls (BSOT, SMOT) while relative catchability of pelagic species was higher in the midwater trawls (FMWT, BSMT). Our results demonstrate that catchability is a source of bias among monitoring efforts within the San Francisco Estuary, and assuming equal catchability among surveys, species, and size classes could result in significant bias when describing spatio-temporal patterns in catch if ignored.

","language":"English","publisher":"University of California Davis","doi":"10.15447/sfews.2022v20iss1art3","usgsCitation":"Huntsman, B., Mahardja, B., and Bashevkin, S., 2022, Relative bias in catch among long-term fish monitoring surveys within the San Francisco Estuary: San Francisco Estuary and Watershed Science, v. 20, no. 1, 3, 17 p., https://doi.org/10.15447/sfews.2022v20iss1art3.","productDescription":"3, 17 p.","ipdsId":"IP-130127","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":449301,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2022v20iss1art3","text":"Publisher Index Page"},{"id":397305,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.684326171875,\n 37.1165261849112\n ],\n [\n -121.2,\n 37.1165261849112\n ],\n [\n -121.2,\n 39.00211029922515\n ],\n [\n -122.684326171875,\n 39.00211029922515\n ],\n [\n -122.684326171875,\n 37.1165261849112\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Huntsman, Brock 0000-0003-4090-1949","orcid":"https://orcid.org/0000-0003-4090-1949","contributorId":223101,"corporation":false,"usgs":true,"family":"Huntsman","given":"Brock","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":838466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahardja, Brian 0000-0003-0695-3745","orcid":"https://orcid.org/0000-0003-0695-3745","contributorId":288940,"corporation":false,"usgs":false,"family":"Mahardja","given":"Brian","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":838467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bashevkin, Samuel M.","contributorId":288941,"corporation":false,"usgs":false,"family":"Bashevkin","given":"Samuel M.","affiliations":[{"id":61910,"text":"Delta Science Program, Delta Stewardship Council","active":true,"usgs":false}],"preferred":false,"id":838468,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229656,"text":"70229656 - 2022 - San Francisco Estuary chlorophyll sensor and sample analysis intercomparison","interactions":[],"lastModifiedDate":"2022-03-11T15:26:53.094975","indexId":"70229656","displayToPublicDate":"2022-01-01T09:19:02","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":10383,"text":"Intercomparison Report","active":true,"publicationSubtype":{"id":3}},"title":"San Francisco Estuary chlorophyll sensor and sample analysis intercomparison","docAbstract":"

This report presents an assessment of chlorophyll collection methods and anonymous results of field and laboratory comparisons in 2018 - 2019 by agencies in the San Francisco Estuary (SFE). The methods assessment and comparison exercises, with funding provided by the Delta Regional Monitoring Program and Bay Nutrient Management Strategy and in-kind contributions from participating agencies, are a first step to facilitate future comparisons and syntheses of data and inform best science practices in the region. In situ sonde comparison exercises found general agreement between two models of Yellow Springs Instrument (YSI) sensors, but the newer sensor (EXO v2 - total algae) measured higher chlorophyll fluorescence (fCHL) relative to the older YSI sensor (6-series 6025). Results may be attributed to the use of a two-point calibration and the fluorescence response of algal cultures in sensor development by the manufacturer. The laboratory comparison included participation by 12 distinct field - laboratory pairs (or groups), with one group analyzing filters using two analytical methods. Filters were collected in triplicate across three sampling events in 2018, and all sample results were pooled together. Results of statistical analyses indicated that nominal filter pore size, the grinding method associated with pigment extraction, and analytical methods do not introduce variability to the chlorophyll-a measurement (Chl-a). When Chl-a results were assessed by sample event, however, significant differences between nominal pore size and analytical methods existed; these differences could be attributed to the small sample size per event. Consistent reporting units and high-concentration calibration standards for field sensors among data collection agencies would improve the consistency and comparability of data collected in the SFE. More routine split sampling events, longer term sensor comparison exercises, and further processing and analytical comparisons that control for individual filterers may also enhance comparability in the region.

","language":"English","publisher":"Delta Regional Monitoring Program","usgsCitation":"Stumpner, E.B., Yin, J.S., Heberger, M., Wu, J., Wong, A., and Saraceno, J., 2022, San Francisco Estuary chlorophyll sensor and sample analysis intercomparison: Intercomparison Report, 61 p.","productDescription":"61 p.","ipdsId":"IP-123558","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":397022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":397021,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://deltarmp.org/documents/"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.67608642578126,\n 37.36579146999664\n ],\n [\n -121.4,\n 37.36579146999664\n ],\n [\n -121.4,\n 38.348118547988065\n ],\n [\n -122.67608642578126,\n 38.348118547988065\n ],\n [\n -122.67608642578126,\n 37.36579146999664\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stumpner, Elizabeth B. 0000-0003-2356-2244 estumpner@usgs.gov","orcid":"https://orcid.org/0000-0003-2356-2244","contributorId":181854,"corporation":false,"usgs":true,"family":"Stumpner","given":"Elizabeth","email":"estumpner@usgs.gov","middleInitial":"B.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yin, Jamie S.","contributorId":288390,"corporation":false,"usgs":false,"family":"Yin","given":"Jamie","email":"","middleInitial":"S.","affiliations":[{"id":61747,"text":"San Francisco Estuary Institute - Aquatic Science Center","active":true,"usgs":false}],"preferred":false,"id":837826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heberger, Matthew","contributorId":288391,"corporation":false,"usgs":false,"family":"Heberger","given":"Matthew","email":"","affiliations":[{"id":61747,"text":"San Francisco Estuary Institute - Aquatic Science Center","active":true,"usgs":false}],"preferred":false,"id":837827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, Jing","contributorId":191126,"corporation":false,"usgs":false,"family":"Wu","given":"Jing","email":"","affiliations":[],"preferred":false,"id":837828,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wong, Adam","contributorId":288392,"corporation":false,"usgs":false,"family":"Wong","given":"Adam","affiliations":[{"id":61747,"text":"San Francisco Estuary Institute - Aquatic Science Center","active":true,"usgs":false}],"preferred":false,"id":837829,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Saraceno, John Franco 0000-0003-0064-1820","orcid":"https://orcid.org/0000-0003-0064-1820","contributorId":217534,"corporation":false,"usgs":false,"family":"Saraceno","given":"John Franco","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":837830,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70240413,"text":"70240413 - 2022 - Workshops report for mesophotic and deep benthic community fish, mobile invertebrates, sessile invertebrates and infauna","interactions":[],"lastModifiedDate":"2023-02-08T11:59:25.77461","indexId":"70240413","displayToPublicDate":"2022-01-01T09:01:19","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":13296,"text":"DWH MDBC Summary Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"SR-22-01","title":"Workshops report for mesophotic and deep benthic community fish, mobile invertebrates, sessile invertebrates and infauna","docAbstract":"Two workshops with subject matter experts in the appropriate fields, were held in November and December 2021 to elicit guidance and feedback from the broader mesophotic and deep benthic scientific community. These workshops focused on best practices/approaches and identifying data gaps relative to habitat assessment and evaluation goals of the Mesophotic and Deep Benthic Community (MDBC) restoration portfolio. The first workshop was a combined effort of the Habitat Assessment and Evaluation (HAE) Project Team and the Deepwater Horizon (DWH) Program. Industrial Economics, Inc. (IEc) provided extensive workshop planning, organizing, execution, and facilitation support during all stages of the workshop. Based on a questionnaire sent to scientists in August, 2021, the workshop focused on fish and mobile invertebrate habitat associations, abundance trends, community metrics, and food web functionality. Topical presentations and discussions focused not only on demersal fish and mobile invertebrates that are directly associated with mesophotic and deep benthic habitats, but also considered water column species and communities that benefit from these habitats more broadly. The second workshop, intended to complement the first workshop, focused on identifying best practices and critical information gaps for key community metrics, larval dispersal modeling, connectivity, effects and variability of environmental parameters, and recovery trajectories of corals, infauna, and other sessile invertebrates. Through literature review, internal HAE scientists considered these topics to be critical for restoration success. Products from the literature review included topical summaries (see Appendix B) that summarized the current state-of-the-science and provided the framework for the workshop. Information generated from the workshops will assist the MDBC HAE Project, and more broadly the DWH Program, identify data gaps and develop a suite of best practices for restoration activities.","language":"English","publisher":"NOAA","doi":"10.25923/8ph6-j393","usgsCitation":"Bassett, R., Harter, S.L., Clark, R., Zink, I., Hornick, K., Hartman, J., Bliska, H., Carle, M., Sutton, T., Demopoulos, A., David, A., Benson, K., Bourque, J., Nizinski, M.S., Prouty, N.G., Sharuga, S.M., Caporaso, A., Le, J., Herting, J., Morrison, C., and Poti, M., 2022, Workshops report for mesophotic and deep benthic community fish, mobile invertebrates, sessile invertebrates and infauna: DWH MDBC Summary Report SR-22-01, 177 p., https://doi.org/10.25923/8ph6-j393.","productDescription":"177 p.","startPage":"1","endPage":"177","ipdsId":"IP-143984","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":412815,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bassett, Rachel","contributorId":302194,"corporation":false,"usgs":false,"family":"Bassett","given":"Rachel","email":"","affiliations":[{"id":65431,"text":"CSS Inc, under contract to NOAA/NOS","active":true,"usgs":false}],"preferred":false,"id":863705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harter, Stacey L.","contributorId":302195,"corporation":false,"usgs":false,"family":"Harter","given":"Stacey","email":"","middleInitial":"L.","affiliations":[{"id":62397,"text":"NOAA/NMFS","active":true,"usgs":false}],"preferred":false,"id":863706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Randy","contributorId":218497,"corporation":false,"usgs":false,"family":"Clark","given":"Randy","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":863707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zink, Ian","contributorId":289796,"corporation":false,"usgs":false,"family":"Zink","given":"Ian","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":863708,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hornick, Katherine","contributorId":302196,"corporation":false,"usgs":false,"family":"Hornick","given":"Katherine","email":"","affiliations":[{"id":65433,"text":"Earth Resources Technology, Inc. Under contract to NOAA/NMFS","active":true,"usgs":false}],"preferred":false,"id":863709,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hartman, Jennifer","contributorId":265721,"corporation":false,"usgs":false,"family":"Hartman","given":"Jennifer","email":"","affiliations":[{"id":54777,"text":"Rogue Detection Teams, Rice, Washington, USA","active":true,"usgs":false}],"preferred":false,"id":863710,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bliska, Hanna","contributorId":302197,"corporation":false,"usgs":false,"family":"Bliska","given":"Hanna","email":"","affiliations":[{"id":65434,"text":"Industrial Economics, Inc","active":true,"usgs":false}],"preferred":false,"id":863711,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carle, 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NOAA/NMFS","active":true,"usgs":false}],"preferred":false,"id":863723,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Morrison, Cheryl L. 0000-0001-9425-691X","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":239844,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":863724,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Poti, Matthew","contributorId":278594,"corporation":false,"usgs":false,"family":"Poti","given":"Matthew","email":"","affiliations":[{"id":16685,"text":"National Oceanic and Atmopheric Administration","active":true,"usgs":false}],"preferred":false,"id":863725,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70233204,"text":"70233204 - 2022 - Analysis of ocean dynamics during the impact of Hurricane Matthew using ocean-atmosphere coupling","interactions":[],"lastModifiedDate":"2024-09-25T15:54:28.499952","indexId":"70233204","displayToPublicDate":"2022-01-01T08:38:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":11126,"text":"Cuban Journal of Meteorology (Revista Cubana de Meteorología)","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of ocean dynamics during the impact of Hurricane Matthew using ocean-atmosphere coupling","docAbstract":"The main goal of this investigation is to improve the understanding of ocean-atmosphere coupling during hurricanes. The present work involves the integration of the ocean-atmosphere coupled components of the Coupled Ocean-Atmosphere-Wave-Sediment Transport Modeling System in the Very Short Term Prediction System (SisPI). Three experiments are performed: First, using a dynamic sea surface temperature, consistent with the daily updated atmospheric model Weather Research and Forecast (SisPI); second, using the Regional Oceanic Modeling System and third, using a dynamic coupling between the atmospheric and the oceanic models. The coupled system improves the tracks of the hurricane simulations respect to the SisPI. The use of the oceanic model allows a more detailed representation of the sea surface temperature. Using the coupled model, a more precise diurnal cycle of the surface net heat fluxes is obtained.","language":"English","publisher":"Instituto de Meteorología de Cuba","doi":"2377/v28n1e05","usgsCitation":"Vazquez Proveyer, L., Sierra Lorenzo, M., Cruz Rodriguez, R.C., and Warner, J.C., 2022, Analysis of ocean dynamics during the impact of Hurricane Matthew using ocean-atmosphere coupling: Cuban Journal of Meteorology (Revista Cubana de Meteorología), v. 28, no. 1, e05, 11 p., https://doi.org/2377/v28n1e05.","productDescription":"e05, 11 p.","ipdsId":"IP-133711","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":404011,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Cuba","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-82.26815,23.18861],[-81.40446,23.11727],[-80.61877,23.10598],[-79.67952,22.7653],[-79.28149,22.3992],[-78.34743,22.51217],[-77.9933,22.27719],[-77.14642,21.65785],[-76.52382,21.20682],[-76.19462,21.22057],[-75.59822,21.01662],[-75.67106,20.73509],[-74.9339,20.69391],[-74.17802,20.28463],[-74.29665,20.05038],[-74.96159,19.92344],[-75.63468,19.87377],[-76.32366,19.95289],[-77.75548,19.85548],[-77.08511,20.41335],[-77.49265,20.67311],[-78.13729,20.73995],[-78.48283,21.02861],[-78.71987,21.59811],[-79.285,21.55918],[-80.21748,21.82732],[-80.51753,22.03708],[-81.82094,22.19206],[-82.16999,22.38711],[-81.795,22.63696],[-82.7759,22.68815],[-83.49446,22.16852],[-83.9088,22.15457],[-84.05215,21.91058],[-84.54703,21.80123],[-84.97491,21.89603],[-84.44706,22.20495],[-84.23036,22.56575],[-83.77824,22.78812],[-83.26755,22.98304],[-82.51044,23.07875],[-82.26815,23.18861]]]},\"properties\":{\"name\":\"Cuba\"}}]}","volume":"28","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Vazquez Proveyer, Liset","contributorId":293212,"corporation":false,"usgs":false,"family":"Vazquez Proveyer","given":"Liset","email":"","affiliations":[{"id":63246,"text":"Center for Atmospheric Physics, Institute of Meteorology, Casablanca, 10900, Havana, Cuba","active":true,"usgs":false}],"preferred":false,"id":846779,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sierra Lorenzo, Maibys","contributorId":293213,"corporation":false,"usgs":false,"family":"Sierra Lorenzo","given":"Maibys","email":"","affiliations":[{"id":63246,"text":"Center for Atmospheric Physics, Institute of Meteorology, Casablanca, 10900, Havana, Cuba","active":true,"usgs":false}],"preferred":false,"id":846780,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cruz Rodriguez, Roberto Carlos","contributorId":293214,"corporation":false,"usgs":false,"family":"Cruz Rodriguez","given":"Roberto","email":"","middleInitial":"Carlos","affiliations":[{"id":63247,"text":"Department of Atmospheric Physics, National Autonomous University of Mexico, Av. Universidad 3000, 04510, DF, Mexico","active":true,"usgs":false}],"preferred":false,"id":846781,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":258015,"corporation":false,"usgs":true,"family":"Warner","given":"John","email":"jcwarner@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":846782,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70236142,"text":"70236142 - 2022 - Extensive droughts in the conterminous United States during multiple centuries","interactions":[],"lastModifiedDate":"2022-08-30T13:12:56.867999","indexId":"70236142","displayToPublicDate":"2022-01-01T08:09:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Extensive droughts in the conterminous United States during multiple centuries","docAbstract":"

Extensive and severe droughts have substantial effects on water supplies, agriculture, and aquatic ecosystems. To better understand these droughts, we used tree-ring-based reconstructions of the Palmer drought severity index (PDSI) for the period 1475–2017 to examine droughts that covered at least 33% of the conterminous United States (CONUS). We identified 37 spatially extensive drought events for the CONUS and examined their spatial and temporal patterns. The duration of the extensive drought events ranged from 3 to 12 yr and on average affected 43% of the CONUS. The recent (2000–08) drought in the southwestern CONUS, often referred to as the turn-of-the-century drought, is likely one of the longest droughts in the CONUS during the past 500 years. A principal components analysis of the PDSI data from 1475 through 2017 resulted in three principal components (PCs) that explain about 48% of the variability of PDSI and are helpful to understand the temporal and spatial variability of the 37 extensive droughts in the CONUS. Analyses of the relations between the three PCs and well-known climate indices, such as indices of El Niño–Southern Oscillation, indicate statistically significant correlations; however, the correlations do not appear to be large enough (all with an absolute value less than 0.45) to be useful for the development of drought prediction models.

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Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":850242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":219213,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":850243,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70225504,"text":"70225504 - 2022 - Impact of spectral resolution on quantifying cyanobacteria in lakes and reservoirs: A machine-learning assessment","interactions":[],"lastModifiedDate":"2024-05-17T17:00:12.08779","indexId":"70225504","displayToPublicDate":"2022-01-01T05:55:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9530,"text":"IEEE Transactions in Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Impact of spectral resolution on quantifying cyanobacteria in lakes and reservoirs: A machine-learning assessment","docAbstract":"

Cyanobacterial harmful algal blooms are an increasing threat to coastal and inland waters. These blooms can be detected using optical radiometers due to the presence of phycocyanin (PC) pigments. The spectral resolution of best-available multispectral sensors limits their ability to diagnostically detect PC in the presence of other photosynthetic pigments. To assess the role of spectral resolution in the determination of PC, a large (N = 905) database of colocated in situ radiometric spectra and PC are employed. We first examine the performance of selected widely used machine-learning (ML) models against that of benchmark algorithms for hyperspectral remote sensing reflectance ( Rrs) spectra resampled to the spectral configuration of the Hyperspectral Imager for the Coastal Ocean (HICO) with a full-width at half-maximum (FWHM) of < 6 nm. Results show that the multilayer perceptron (MLP) neural network applied to HICO spectral configurations (median errors < 65%) outperforms other ML models. This model is subsequently applied to Rrs spectra resampled to the band configuration of existing satellite instruments and of the one proposed for the next Landsat sensor. These results confirm that employing MLP models to estimate PC from hyperspectral data delivers tangible improvements compared with retrievals from multispectral data and benchmark algorithms (with median errors between ~73% and 126%) and shows promise for developing a globally applicable cyanobacteria measurement approach.

","language":"English","publisher":"IEEE","doi":"10.1109/TGRS.2021.3114635","usgsCitation":"Zolfaghari, K., Pahlevan, N., Binding, C., Gurlin, D., Simis, S.G., Verdu, A.R., Li, L., Crawford, C., VanderWoude, A., Errera, R., Zastepa, A., and Duguay, C.R., 2022, Impact of spectral resolution on quantifying cyanobacteria in lakes and reservoirs: A machine-learning assessment: IEEE Transactions in Geoscience and Remote Sensing, v. 60, 5515520, 20 p., https://doi.org/10.1109/TGRS.2021.3114635.","productDescription":"5515520, 20 p.","ipdsId":"IP-132686","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":449319,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1109/tgrs.2021.3114635","text":"Publisher Index Page"},{"id":390590,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zolfaghari, Kiana","contributorId":267804,"corporation":false,"usgs":false,"family":"Zolfaghari","given":"Kiana","email":"","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":825333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pahlevan, Nima","contributorId":267805,"corporation":false,"usgs":false,"family":"Pahlevan","given":"Nima","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":825334,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Binding, Caren","contributorId":267806,"corporation":false,"usgs":false,"family":"Binding","given":"Caren","affiliations":[],"preferred":false,"id":825335,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gurlin, Daniela","contributorId":267807,"corporation":false,"usgs":false,"family":"Gurlin","given":"Daniela","email":"","affiliations":[],"preferred":false,"id":825336,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Simis, Stefan G.H.","contributorId":267808,"corporation":false,"usgs":false,"family":"Simis","given":"Stefan","email":"","middleInitial":"G.H.","affiliations":[],"preferred":false,"id":825337,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Verdu, Antonio Ruiz","contributorId":267809,"corporation":false,"usgs":false,"family":"Verdu","given":"Antonio","email":"","middleInitial":"Ruiz","affiliations":[],"preferred":false,"id":825338,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Li, Lin","contributorId":267810,"corporation":false,"usgs":false,"family":"Li","given":"Lin","email":"","affiliations":[],"preferred":false,"id":825339,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crawford, Christopher J. 0000-0002-7145-0709 cjcrawford@usgs.gov","orcid":"https://orcid.org/0000-0002-7145-0709","contributorId":213607,"corporation":false,"usgs":true,"family":"Crawford","given":"Christopher J.","email":"cjcrawford@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":825340,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"VanderWoude, Andrea","contributorId":267811,"corporation":false,"usgs":false,"family":"VanderWoude","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":825341,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Errera, Reagan","contributorId":267812,"corporation":false,"usgs":false,"family":"Errera","given":"Reagan","email":"","affiliations":[],"preferred":false,"id":825342,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zastepa, Arthur","contributorId":267813,"corporation":false,"usgs":false,"family":"Zastepa","given":"Arthur","email":"","affiliations":[],"preferred":false,"id":825343,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Duguay, Claude R.","contributorId":267814,"corporation":false,"usgs":false,"family":"Duguay","given":"Claude","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":825344,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70262046,"text":"70262046 - 2022 - Demography and site fidelity of a grassland bird, the Henslow’s Sparrow, in powerline right-of-way habitat","interactions":[],"lastModifiedDate":"2025-01-10T16:40:33.895421","indexId":"70262046","displayToPublicDate":"2022-01-01T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Demography and site fidelity of a grassland bird, the Henslow’s Sparrow, in powerline right-of-way habitat","docAbstract":"

Grassland birds are among the fastest declining avian species in North America, primarily due to habitat loss. In the southeastern U.S., much grassland and open savanna habitat has been converted to timber production or agriculture, neither of which typically provides habitat for breeding or wintering grassland birds. Powerline right-of-ways could provide suitable habitat for many grassland species as these areas are maintained to be treeless. We studied the population dynamics of Henslow’s Sparrows (Centronyx henslowii) wintering in powerline right-of-ways in southeastern Georgia through an 11-year mark-recapture study. We used a robust design Cormack-Jolly-Seber model to estimate probability of detection and apparent survival. Abundance varied substantially among years at each site, with density varying from 1.7 to 8.5 birds/ha. Within-year detection probability was moderately high at 28% (24-33%, 95% credible interval [CI]), but apparent survival was very low at 13% (9-17%, 95% CI). This low apparent survival was likely due to low return rates (and not necessarily low survival). However, birds that did return to the study sites had extremely high site fidelity, with 82% of across-year recaptures < 200 m apart. This apparent incongruity between low apparent survival rates (likely due to emigration from the study sites) and high site fidelity for returning individuals could be explained by the dependability of the right-of-way habitat, which differs from typically patchy and temporally variable grassland and savanna wintering habitats. Dependable habitat may allow for higher site fidelity than this species would otherwise have, potentially resulting in the high densities we observed. Thousands of miles of right-of-ways in Georgia, and other southeastern states, could be managed to maximize potential habitat for declining grassland bird species. 

","language":"English","publisher":"Resilience Alliance","doi":"10.5751/jfo-00077-930109","usgsCitation":"Hunter, E.A., Dwire, A., and Schneider, T., 2022, Demography and site fidelity of a grassland bird, the Henslow’s Sparrow, in powerline right-of-way habitat: Journal of Field Ornithology, v. 93, no. 1, 9, 8 p., https://doi.org/10.5751/jfo-00077-930109.","productDescription":"9, 8 p.","ipdsId":"IP-135429","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467210,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/jfo-00077-930109","text":"Publisher Index Page"},{"id":465998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Moody Forest Wildlife Management Area, Paulks Pasture Wildlife Management Area, Townsend Wildlife Management 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\"}}]}","volume":"93","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dwire, Abigail","contributorId":348000,"corporation":false,"usgs":false,"family":"Dwire","given":"Abigail","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":922809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schneider, Todd M.","contributorId":348001,"corporation":false,"usgs":false,"family":"Schneider","given":"Todd M.","affiliations":[{"id":36378,"text":"Georgia Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":922810,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227422,"text":"70227422 - 2022 - Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics","interactions":[],"lastModifiedDate":"2022-01-14T15:32:34.362133","indexId":"70227422","displayToPublicDate":"2021-12-31T09:21:06","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9944,"text":"Remote Sensing of the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics","docAbstract":"

Mounting evidence indicates dryland ecosystems play an important role in driving the interannual variability and trend of the terrestrial carbon sink. Nevertheless, our understanding of the seasonal dynamics of dryland ecosystem carbon uptake through photosynthesis [gross primary productivity (GPP)] remains relatively limited due in part to the limited availability of long-term data and unique challenges associated with satellite remote sensing across dryland ecosystems. Here, we comprehensively evaluated longstanding and emerging satellite vegetation proxies in their ability to capture seasonal dryland GPP dynamics. Specifically, we evaluated: 1) reflectance-based proxies normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), near infrared reflectance index (NIRv), and kernel NDVI (kNDVI) from the MODerate resolution Imaging Spectroradiometer (MODIS); and 2) newly available physiologically-based proxy solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI). As a performance benchmark, we used GPP estimates from a robust network of 21 western United States eddy covariance tower sites that span representative gradients in dryland ecosystem climate and functional composition. We found that NIRv and SIF were the best performing GPP proxies and captured complementary aspects of seasonal GPP dynamics across dryland ecosystem types. NIRv offered better performance than the other proxies across relatively low-productivity, sparsely non-evergreen vegetated sites (R2 = 0.59 ± 0.13); whereas SIF best captured seasonal dynamics across relatively high-productivity sites, including evergreen-dominated sites (R2 = 0.74 ± 0.07). Notably, across grass-dominated sites, all reflectance-based proxies (NDVI, SAVI, NIRv and kNDVI) showed significant seasonal bias (hysteresis) that strengthened with the total fraction of woody vegetation cover, likely due to seasonal patterns in woody vegetation reflectance that are unrelated to or decoupled from GPP. Future efforts to fully integrate the complementary strengths of NIRv and SIF could significantly improve our understanding and representation of dryland GPP dynamics in satellite-based models.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2021.112858","usgsCitation":"Wang, X., Biederman, J.A., Knowles, J.F., Scott, R.L., Turner, A.J., Dannenberg, M.P., Kohler, P., Frankenberg, C., Litvak, M.E., Flerchinger, G.N., Law, B.E., Kwon, H., Reed, S., Parton, W.J., Barron-Gafford, G.A., and Smith, W.K., 2022, Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics: Remote Sensing of the Environment, v. 270, 112858, 11 p., https://doi.org/10.1016/j.rse.2021.112858.","productDescription":"112858, 11 p.","ipdsId":"IP-133234","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":449323,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1981744","text":"Publisher Index 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Albuquerque, NM, USA","active":true,"usgs":false}],"preferred":false,"id":830804,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Flerchinger, Gerald N.","contributorId":257377,"corporation":false,"usgs":false,"family":"Flerchinger","given":"Gerald","email":"","middleInitial":"N.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":830805,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Law, Beverly E.","contributorId":222527,"corporation":false,"usgs":false,"family":"Law","given":"Beverly","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":830806,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kwon, Hyojung","contributorId":271096,"corporation":false,"usgs":false,"family":"Kwon","given":"Hyojung","email":"","affiliations":[{"id":56277,"text":"Department of Forest Ecosystems and Society, College of Forestry, Oregon State University, Corvallis, OR, 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A.","contributorId":19058,"corporation":false,"usgs":false,"family":"Barron-Gafford","given":"Greg","email":"","middleInitial":"A.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":830810,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Smith, William K. 0000-0002-5785-6489","orcid":"https://orcid.org/0000-0002-5785-6489","contributorId":239667,"corporation":false,"usgs":false,"family":"Smith","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":47959,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":830811,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70227508,"text":"70227508 - 2022 - Nitrogen reductions have decreased hypoxia in the Chesapeake Bay: Evidence from empirical and numerical modeling","interactions":[],"lastModifiedDate":"2022-01-20T13:30:49.473216","indexId":"70227508","displayToPublicDate":"2021-12-31T07:30:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Nitrogen reductions have decreased hypoxia in the Chesapeake Bay: Evidence from empirical and numerical modeling","docAbstract":"

Seasonal hypoxia is a characteristic feature of the Chesapeake Bay due to anthropogenic nutrient input from agriculture and urbanization throughout the watershed. Although coordinated management efforts since 1985 have reduced nutrient inputs to the Bay, oxygen concentrations at depth in the summer still frequently fail to meet water quality standards that have been set to protect critical estuarine living resources. To quantify the impact of watershed nitrogen reductions on Bay hypoxia during a recent period including both average discharge and extremely wet years (2016–2019), this study employed both statistical and three-dimensional (3-D) numerical modeling analyses. Numerical model results suggest that if the nitrogen reductions since 1985 had not occurred, annual hypoxic volumes (O2 < 3 mg L−1) would have been ~50–120% greater during the average discharge years of 2016–2017 and ~20–50% greater during the wet years of 2018–2019. The effect was even greater for O2 < 1 mg L−1, where annual volumes would have been ~80–280% greater in 2016–2017 and ~30–100% greater in 2018–2019. These results were supported by statistical analysis of empirical data, though the magnitude of improvement due to nitrogen reductions was greater in the numerical modeling results than in the statistical analysis. This discrepancy is largely accounted for by warming in the Bay that has exacerbated hypoxia and offset roughly 6–34% of the improvement from nitrogen reductions. Although these results may reassure policymakers and stakeholders that their efforts to reduce hypoxia have improved ecosystem health in the Bay, they also indicate that greater reductions are needed to counteract the ever-increasing impacts of climate change.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.152722","usgsCitation":"Frankel, L.T., Friedrichs, M.A., St-Laurent, P., Bever, A.J., Lipcius, R.N., Bhatt, G., and Shenk, G.W., 2022, Nitrogen reductions have decreased hypoxia in the Chesapeake Bay: Evidence from empirical and numerical modeling: Science of the Total Environment, v. 814, 152722, 17 p., https://doi.org/10.1016/j.scitotenv.2021.152722.","productDescription":"152722, 17 p.","ipdsId":"IP-135162","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":449327,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2021.152722","text":"Publisher Index Page"},{"id":394573,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.50830078125001,\n 35.72867704485167\n ],\n [\n -74.794921875,\n 35.72867704485167\n ],\n [\n -74.794921875,\n 40.94671366507999\n ],\n [\n -78.50830078125001,\n 40.94671366507999\n ],\n [\n -78.50830078125001,\n 35.72867704485167\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"814","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Frankel, Luke T 0000-0001-9690-2671","orcid":"https://orcid.org/0000-0001-9690-2671","contributorId":271212,"corporation":false,"usgs":false,"family":"Frankel","given":"Luke","email":"","middleInitial":"T","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":831198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Friedrichs, Marjorie A. M. 0000-0003-2828-7595","orcid":"https://orcid.org/0000-0003-2828-7595","contributorId":222588,"corporation":false,"usgs":false,"family":"Friedrichs","given":"Marjorie","email":"","middleInitial":"A. M.","affiliations":[{"id":40564,"text":"Virginia Institute of Marine Science, William & Mary","active":true,"usgs":false}],"preferred":false,"id":831199,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"St-Laurent, Pierre 0000-0002-1700-9509","orcid":"https://orcid.org/0000-0002-1700-9509","contributorId":261288,"corporation":false,"usgs":false,"family":"St-Laurent","given":"Pierre","email":"","affiliations":[{"id":40564,"text":"Virginia Institute of Marine Science, William & Mary","active":true,"usgs":false}],"preferred":false,"id":831200,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bever, Aaron J.","contributorId":173009,"corporation":false,"usgs":false,"family":"Bever","given":"Aaron","email":"","middleInitial":"J.","affiliations":[{"id":27140,"text":"Delta Modeling Associates, Inc.","active":true,"usgs":false}],"preferred":false,"id":831201,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lipcius, Romuald N.","contributorId":101451,"corporation":false,"usgs":false,"family":"Lipcius","given":"Romuald","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":831202,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bhatt, Gopal 0000-0002-6627-793X","orcid":"https://orcid.org/0000-0002-6627-793X","contributorId":252963,"corporation":false,"usgs":false,"family":"Bhatt","given":"Gopal","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":831203,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shenk, Gary W. 0000-0001-6451-2513","orcid":"https://orcid.org/0000-0001-6451-2513","contributorId":225440,"corporation":false,"usgs":true,"family":"Shenk","given":"Gary","email":"","middleInitial":"W.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":831204,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229111,"text":"70229111 - 2022 - Acute and lagged fitness consequences for a sagebrush obligate in a post mega-wildfire landscape","interactions":[],"lastModifiedDate":"2022-03-02T12:06:50.746406","indexId":"70229111","displayToPublicDate":"2021-12-30T18:24:28","publicationYear":"2022","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":"Acute and lagged fitness consequences for a sagebrush obligate in a post mega-wildfire landscape","docAbstract":"
Species responses to disturbance influence their extinction risks. Greater sage- grouse (Centrocercus urophasianus) are bioindicators of sagebrush ecosystem health and the loss of sagebrush (Artemisia spp.) due to wildfire, can cause long-term declines in sage- grouse populations and other sagebrush obligate species. We examined the de-mographic response of a greater sage- grouse population following a mega-wildfire using stochastic age-structured female- based matrix models over 6 years (2013– 2018). Notably, chick survival (range = 0.18–0.38) and female survival (yearling range: 0.20–0.68; adult range: 0.27–0.75) were low compared to values reported for greater sage- grouse in other parts of their distribution. Greater sage- grouse displayed vari-ation in demographic tactics after the fire; however, adult female survival explained most of the variation in λ during each year, which reflected a declining population in 3 of 6 years with more uncertainty observed in 2015 when populations may have been increasing, and 2017 and 2018, when populations may have been declining. The continued annual population decline observed since 2016 suggested there were ad-ditional strong environmental impacts that may have been compounded by the fire effects, prolonging recovery of greater sage- grouse. Our results support others that reported negative effects to greater sage- grouse demographics from broad-scale fire and provide a baseline for understanding how this species responds to loss of sage-brush cover based on their life history strategy.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8488","usgsCitation":"Anthony, C., Foster, L.J., Hagen, C., and Dugger, K., 2022, Acute and lagged fitness consequences for a sagebrush obligate in a post mega-wildfire landscape: Ecology and Evolution, v. 12, e8488, 12 p., https://doi.org/10.1002/ece3.8488.","productDescription":"e8488, 12 p.","ipdsId":"IP-122398","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449329,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.8488","text":"External Repository"},{"id":396616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Oregon","otherGeospatial":"Trout Creek Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.76220703125001,\n 41.16211393939692\n ],\n [\n -117.04833984375001,\n 41.16211393939692\n ],\n [\n -117.04833984375001,\n 42.924251753870685\n ],\n [\n -118.76220703125001,\n 42.924251753870685\n ],\n [\n -118.76220703125001,\n 41.16211393939692\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2021-12-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Anthony, Christopher R.","contributorId":287179,"corporation":false,"usgs":false,"family":"Anthony","given":"Christopher R.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":836546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster, Lee J.","contributorId":287180,"corporation":false,"usgs":false,"family":"Foster","given":"Lee","email":"","middleInitial":"J.","affiliations":[{"id":36223,"text":"Oregon Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":836547,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagen, Christian A.","contributorId":287181,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian A.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":836548,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":836545,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248809,"text":"70248809 - 2022 - Acquisition of Moon measurements by Earth orbiting sensors for lunar calibration","interactions":[],"lastModifiedDate":"2023-09-21T11:57:01.547194","indexId":"70248809","displayToPublicDate":"2021-12-30T06:55:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Acquisition of Moon measurements by Earth orbiting sensors for lunar calibration","docAbstract":"
The reflected light from the Moon can be utilized as a reference for radiometric calibration by employing a model to generate reference values corresponding to the Moon observations made by instruments. Using a calibration target that is outside the atmosphere provides a distinct advantage for space-based instruments; however, the lunar irradiance sensed by satellite instruments naturally changes as the host spacecraft traverses its orbit. This article presents a study of the potential impact on lunar radiometric measurements due to their acquisition from an orbiting platform. A simulation of a Sun-synchronous orbit was coupled to the U.S. Geological Survey (USGS) lunar model to generate predicted irradiances for points along orbit passes through several lunations. These irradiance values exhibit variations tied to the spacecraft motion, arising primarily from changes in the Moon-sensor distance and the phase angle. The two effects are similar in overall magnitude, but their respective contributions depend on the time of month and the orbit. Relative changes in irradiance mostly fall within an envelope of ±0.006% per second, except at the smallest phase angles. These studies enable planning space-based Moon observations to minimize the change in the target irradiance, an important consideration for measurements acquired for radiometric characterization of the Moon.
","language":"English","publisher":"IEEE","doi":"10.1109/TGRS.2021.3132590","usgsCitation":"Stone, T.C., 2022, Acquisition of Moon measurements by Earth orbiting sensors for lunar calibration: IEEE Transactions on Geoscience and Remote Sensing, v. 60, 1001706, 6 p., https://doi.org/10.1109/TGRS.2021.3132590.","productDescription":"1001706, 6 p.","ipdsId":"IP-132828","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":449338,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1109/tgrs.2021.3132590","text":"Publisher Index Page"},{"id":421016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stone, Thomas C. 0000-0001-5088-3495 tstone@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-3495","contributorId":242004,"corporation":false,"usgs":true,"family":"Stone","given":"Thomas","email":"tstone@usgs.gov","middleInitial":"C.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":883742,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70227325,"text":"70227325 - 2022 - Representing plant diversity in land models: An evolutionary approach to make ‘Functional Types’ more functional","interactions":[],"lastModifiedDate":"2022-03-28T16:37:58.702915","indexId":"70227325","displayToPublicDate":"2021-12-29T07:02:48","publicationYear":"2022","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":"Representing plant diversity in land models: An evolutionary approach to make ‘Functional Types’ more functional","docAbstract":"

Plants are critical mediators of terrestrial mass and energy fluxes, and their structural and functional traits have profound impacts on local and global climate, biogeochemistry, biodiversity, and hydrology. Yet Earth System Models (ESMs), our most powerful tools for predicting the effects of humans on the coupled biosphere-atmosphere system, simplify the incredible diversity of land plants into a handful of coarse categories of ‘Plant Functional Types’ (PFTs) that often fail to capture ecological dynamics such as biome distributions. The inclusion of more realistic functional diversity is a recognized goal for ESMs, yet there is currently no consistent, widely accepted way to add diversity to models, i.e. to determine what new PFTs to add and with what data to constrain their parameters. We review approaches to representing plant diversity in ESMs and draw on recent ecological and evolutionary findings to present an evolution-based functional type approach for further disaggregating functional diversity. Specifically, the prevalence of niche conservatism, or the tendency of closely related taxa to retain similar ecological and functional attributes through evolutionary time, reveals that evolutionary relatedness is a powerful framework for summarizing functional similarities and differences among plant types. We advocate that Plant Functional Types based on dominant evolutionary lineages (‘Lineage Functional Types’) will provide an ecologically defensible, tractable, and scalable framework for representing plant diversity in next-generation ESMs, with the potential to improve parameterization, process representation, and model benchmarking. We highlight how the importance of evolutionary history for plant function can unify the work of disparate fields to improve predictive modeling of the Earth system.

","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16040","usgsCitation":"Anderegg, L.D., Griffith, D.M., Cavender-Bares, J., Riley, W.J., Berry, J.A., Dawson, T.E., and Still, C.J., 2022, Representing plant diversity in land models: An evolutionary approach to make ‘Functional Types’ more functional: Global Change Biology, v. 28, no. 8, p. 2541-2554, https://doi.org/10.1111/gcb.16040.","productDescription":"14 p.","startPage":"2541","endPage":"2554","ipdsId":"IP-114038","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":449340,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/3xc708ps","text":"External Repository"},{"id":394091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-01-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderegg, Leander D.L.","contributorId":256917,"corporation":false,"usgs":false,"family":"Anderegg","given":"Leander","email":"","middleInitial":"D.L.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":830468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffith, Daniel Mark 0000-0001-7463-4004","orcid":"https://orcid.org/0000-0001-7463-4004","contributorId":271033,"corporation":false,"usgs":true,"family":"Griffith","given":"Daniel","email":"","middleInitial":"Mark","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":830469,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cavender-Bares, Jeannine","contributorId":219596,"corporation":false,"usgs":false,"family":"Cavender-Bares","given":"Jeannine","email":"","affiliations":[{"id":40035,"text":"U Minnesota","active":true,"usgs":false}],"preferred":false,"id":830470,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Riley, William J. 0000-0002-4615-2304","orcid":"https://orcid.org/0000-0002-4615-2304","contributorId":194645,"corporation":false,"usgs":false,"family":"Riley","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":830471,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berry, Joseph A.","contributorId":182349,"corporation":false,"usgs":false,"family":"Berry","given":"Joseph","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":830472,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dawson, Todd E.","contributorId":176594,"corporation":false,"usgs":false,"family":"Dawson","given":"Todd","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":830473,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Still, Christopher J.","contributorId":167581,"corporation":false,"usgs":false,"family":"Still","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":24761,"text":"University of California, Santa Barbara; Oregon State University","active":true,"usgs":false}],"preferred":false,"id":830474,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70236051,"text":"70236051 - 2022 - Relational database for horizontal‐to‐vertical spectral ratios","interactions":[],"lastModifiedDate":"2022-08-26T12:01:07.832992","indexId":"70236051","displayToPublicDate":"2021-12-29T06:57:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Relational database for horizontal‐to‐vertical spectral ratios","docAbstract":"

Frequency‐dependent horizontal‐to‐vertical spectral ratios (HVSRs) of Fourier amplitudes from three‐component recordings can provide useful information for site response modeling. However, such information is not incorporated into most ground‐motion models, including those from Next‐Generation Attenuation projects, which instead use the time‐averaged shear‐wave velocity (⁠VS\">VSVS⁠) in the upper 30 m of the site and sediment depth terms. To facilitate utilization of HVSR, we developed a publicly accessible relational database. This database is adapted from a similar repository for VS\">VSVS data and provides microtremor‐based HVSR data (mHVSR) and supporting metadata, but not parameters derived from the data. Users can interact with the data directly within a web portal that contains a graphical user interface (GUI) or through external tools that perform cloud‐based computations. Within the database GUI, the median horizontal‐component mHVSR can be plotted against frequency, with the mean and mean ± one standard deviation (representing variability across time windows) provided. Using external interactive tools (provided as a Jupyter Notebook and an R script), users can replot mHVSR (as in the database) or create polar plots. These tools can also derive parameters of potential interest for modeling purposes, including a binary variable indicating whether an mHVSR plot contains peaks, as well as the fitted properties of those peaks (frequencies, amplitudes, and widths). Metadata are also accessible, which includes site location, details about the instruments used to make the measurements, and data processing information related to windowing, antitrigger routines, and filtering.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220210128","usgsCitation":"Wang, P., Zimmaro, P., Buckreis, T.E., Gospe, T., Brandenberg, S.J., Ahdi, S.K., Yong, A., and Stewart, J.P., 2022, Relational database for horizontal‐to‐vertical spectral ratios: Seismological Research Letters, v. 93, no. 2A, p. 1075-1088, https://doi.org/10.1785/0220210128.","productDescription":"14 p.","startPage":"1075","endPage":"1088","ipdsId":"IP-132531","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":405675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"93","issue":"2A","noUsgsAuthors":false,"publicationDate":"2021-12-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Pengfei","contributorId":217351,"corporation":false,"usgs":false,"family":"Wang","given":"Pengfei","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":849826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmaro, Paolo","contributorId":219068,"corporation":false,"usgs":false,"family":"Zimmaro","given":"Paolo","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":849827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckreis, Tristan E","contributorId":295733,"corporation":false,"usgs":false,"family":"Buckreis","given":"Tristan","email":"","middleInitial":"E","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":849828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gospe, Tatiana","contributorId":265142,"corporation":false,"usgs":false,"family":"Gospe","given":"Tatiana","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":849829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brandenberg, Scott J","contributorId":217350,"corporation":false,"usgs":false,"family":"Brandenberg","given":"Scott","email":"","middleInitial":"J","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":849830,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ahdi, Sean Kamran 0000-0003-0274-5180","orcid":"https://orcid.org/0000-0003-0274-5180","contributorId":265143,"corporation":false,"usgs":true,"family":"Ahdi","given":"Sean","email":"","middleInitial":"Kamran","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":849831,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yong, Alan 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":204730,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":849832,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stewart, Jonathan P.","contributorId":100110,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":849833,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70227360,"text":"70227360 - 2022 - Modeling the occurrence of M ∼ 5 caldera collapse-related earthquakes in Kīlauea volcano, Hawai'i","interactions":[],"lastModifiedDate":"2022-01-11T12:58:57.121497","indexId":"70227360","displayToPublicDate":"2021-12-28T06:56:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the occurrence of M ∼ 5 caldera collapse-related earthquakes in Kīlauea volcano, Hawai'i","docAbstract":"

During the 2018 Kīlauea eruption and caldera collapse, M ∼ 5 caldera collapse earthquakes occurred almost daily from mid-May until the beginning of August. While caldera collapses happen infrequently, the collapse-related seismicity damaged nearby structures, and so these events should be included in a complete seismic hazard assessment. Here, we present an approach to forecast the seismic hazard of the collapse earthquakes. We model their occurrence by combining a Poisson distribution for the number of collapses with a negative binomial for the number of earthquakes in a collapse, based on observations at Kīlauea. This rate model is then combined with a ground motion model to assess the seismic hazard posed by caldera collapse events. The rate model is non-Poisson but a Poisson model is adequate for low exceedance probabilities (e.g., <10% in 50 years). This approach could be generalized to model the hazard from earthquakes triggered by other underlying processes.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL092242","usgsCitation":"Llenos, A.L., and Michael, A.J., 2022, Modeling the occurrence of M ∼ 5 caldera collapse-related earthquakes in Kīlauea volcano, Hawai'i: Geophysical Research Letters, v. 49, no. 1, e2020GL092242, 9 p., https://doi.org/10.1029/2020GL092242.","productDescription":"e2020GL092242, 9 p.","ipdsId":"IP-130647","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":449344,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020gl092242","text":"Publisher Index Page"},{"id":394174,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.41671752929688,\n 19.15165474470855\n ],\n [\n -155.03082275390622,\n 19.15165474470855\n ],\n [\n -155.03082275390622,\n 19.530024424775405\n ],\n [\n -155.41671752929688,\n 19.530024424775405\n ],\n [\n -155.41671752929688,\n 19.15165474470855\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-01-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Llenos, Andrea L. 0000-0002-4088-6737 allenos@usgs.gov","orcid":"https://orcid.org/0000-0002-4088-6737","contributorId":4455,"corporation":false,"usgs":true,"family":"Llenos","given":"Andrea","email":"allenos@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":830585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Michael, Andrew J. 0000-0002-2403-5019 michael@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-5019","contributorId":1280,"corporation":false,"usgs":true,"family":"Michael","given":"Andrew","email":"michael@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":830586,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227262,"text":"70227262 - 2022 - A quantitative soil-geomorphic framework for developing and mapping ecological site groups","interactions":[],"lastModifiedDate":"2022-01-05T12:54:42.95958","indexId":"70227262","displayToPublicDate":"2021-12-28T06:51:17","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"A quantitative soil-geomorphic framework for developing and mapping ecological site groups","docAbstract":"

Land management decisions need context about how landscapes will respond to different circumstances or actions. As ecologists’ understanding of nonlinear ecological dynamics has evolved into state-and-transition models (STMs), they have put more emphasis on defining and mapping the soil, geomorphological, and climate parameters that mediate these dynamics. The US Department of Agriculture Natural Resources Conservation Service ecological site descriptions (ESDs) have become the foremost system in classifying lands into ecological units based on STMs. However, an exhaustive inventory of ESDs has proved challenging to complete in the United States, and there have been questions about the consistency of detail in areas completed and the ability to objectively support some assertions made in existing ESDs. To address these issues, this study examines ESDs in the diverse Upper Colorado River region, where ESDs are only partially complete, to look at quantitative approaches to generalizing ecological site concepts based on unifying underlying soil, geomorphology, and climate patterns. Using existing ESDs and vegetation monitoring plot data, results show that a simple hierarchical soil geomorphic unit (SGU) framework based on topographic mediation of moisture, soil salinity, soil depth, slope, rock content, and soil texture can represent much of the ecological dynamics cataloged in ESDs. Analyses of reference plant production data, ecological state attribution, and regional monitoring data show that the new SGUs represent more variation than common climate parameters. This study also included predictively mapping SGUs at 30-m resolution (Kappa of 0.53, 74% agreement with top two predictions in validation). An optimized combination of SGUs with climate zones derived from an aridity index and maximum temperature of the hottest month resulted in an ecological site group framework that condensed over 826 unique ecological site records at various stages of completeness in the regional soil survey down to 35 intuitive and mappable ecological site groups.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2021.11.003","usgsCitation":"Nauman, T.W., Burch, S.S., Humphries, J.T., Knight, A.C., and Duniway, M.C., 2022, A quantitative soil-geomorphic framework for developing and mapping ecological site groups: Rangeland Ecology and Management, v. 81, p. 9-33, https://doi.org/10.1016/j.rama.2021.11.003.","productDescription":"25 p.","startPage":"9","endPage":"33","ipdsId":"IP-132575","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":449346,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2021.11.003","text":"Publisher Index Page"},{"id":393902,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"81","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burch, Samuel S 0000-0002-1142-7953","orcid":"https://orcid.org/0000-0002-1142-7953","contributorId":270936,"corporation":false,"usgs":true,"family":"Burch","given":"Samuel","email":"","middleInitial":"S","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830165,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Humphries, Joel T.","contributorId":270937,"corporation":false,"usgs":false,"family":"Humphries","given":"Joel","email":"","middleInitial":"T.","affiliations":[{"id":56221,"text":"US Bureau of Land Management, Colorado State Office, Lakewood, CO 80215, USA","active":true,"usgs":false}],"preferred":false,"id":830166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knight, Anna C. 0000-0002-9455-2855","orcid":"https://orcid.org/0000-0002-9455-2855","contributorId":255113,"corporation":false,"usgs":true,"family":"Knight","given":"Anna","email":"","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830168,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227293,"text":"70227293 - 2022 - Demographic response of brown treesnakes to extended population suppression","interactions":[],"lastModifiedDate":"2022-02-15T16:21:59.502366","indexId":"70227293","displayToPublicDate":"2021-12-28T06:50:21","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Demographic response of brown treesnakes to extended population suppression","docAbstract":"

From a management perspective, reptiles are relatively novel invasive taxa. Few methods for reptile control have been developed and very little is known about their effectiveness for reducing reptile populations, particularly when the goal is eradication. Many reptiles, and especially snakes, are cryptic, secretive, and undergo extended periods of inactivity, traits that decrease detection probabilities and create challenges in estimating population size or evaluating management effects. The brown treesnake (Boiga irregularis) is a notorious invasive species that continues to cause major ecological and economic harm following their introduction to the island of Guam after World War II. They have been the subject of intensive research on the effectiveness of various techniques to control snakes, including the first ever aerial system for the distribution of toxic acetaminophen baits for reptile control. We provide a cohort-based life table for a cryptic and invasive reptile undergoing extended population control using toxic baits from March 2017–2020. We also evaluated the effects of single (toxic bait) versus multi-tool (toxic bait and live trapping) management efforts on population trajectories, and estimated which population vital rates are most important for influencing population growth or decline in a treated landscape. Treatment of the population with acetaminophen-laced baits resulted in an immediate reduction followed by a gradual population decline that suggested that eradication was the probable outcome given sufficient treatment time but that the period of treatment was decades in magnitude. Inclusion of live trapping reduced the predicted time required to achieve eradication by more than half. Preventing the transition of 1,000-mm snout-vent length (SVL) females to larger sizes was predicted to have the greatest effect on population reduction based on integral projection modeling. Our results suggest that toxic baits are capable of eradicating brown treesnakes in an enclosure, although inclusion of trapping reduced overall treatment time required. Tools that effectively target females >1,000 mm SVL may have the greatest effect on reducing overall treatment timelines.

","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22136","usgsCitation":"Nafus, M.G., Siers, S.R., Levine, B.A., Quiogue, Z.C., and Yackel Adams, A.A., 2022, Demographic response of brown treesnakes to extended population suppression: Journal of Wildlife Management, v. 86, no. 1, e22136, 19 p., https://doi.org/10.1002/jwmg.22136.","productDescription":"e22136, 19 p.","ipdsId":"IP-120666","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":449349,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22136","text":"Publisher Index Page"},{"id":436022,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NUZCGX","text":"USGS data release","linkHelpText":"Demographic data for toxicant based trial eradication of brown treesnakes in the USGS Closed Population on Guam, 2016 - 2020"},{"id":394009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 144.96734619140625,\n 13.605947651142655\n ],\n [\n 144.85061645507812,\n 13.663335011040553\n ],\n [\n 144.69680786132812,\n 13.507155459536346\n ],\n [\n 144.57870483398438,\n 13.445723447606865\n ],\n [\n 144.68032836914062,\n 13.219892851041191\n ],\n [\n 144.72976684570312,\n 13.21855594917547\n ],\n [\n 144.78057861328125,\n 13.318803207592538\n ],\n [\n 144.8011779785156,\n 13.417673157887597\n ],\n [\n 144.93850708007812,\n 13.516502424147102\n ],\n [\n 144.96734619140625,\n 13.605947651142655\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"86","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-12-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Nafus, Melia G. 0000-0002-7325-3055 mnafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7325-3055","contributorId":197462,"corporation":false,"usgs":true,"family":"Nafus","given":"Melia","email":"mnafus@usgs.gov","middleInitial":"G.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":830326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siers, Shane R.","contributorId":152305,"corporation":false,"usgs":false,"family":"Siers","given":"Shane","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":830327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Levine, Brenna A.","contributorId":270994,"corporation":false,"usgs":false,"family":"Levine","given":"Brenna","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":830328,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quiogue, Zachary C.","contributorId":270995,"corporation":false,"usgs":false,"family":"Quiogue","given":"Zachary","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":830329,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":830330,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70246520,"text":"70246520 - 2022 - Reconstructing the paleoceanographic and redox conditions responsible for variations in uranium content in North American Devonian black shales","interactions":[],"lastModifiedDate":"2023-07-07T12:17:22.507283","indexId":"70246520","displayToPublicDate":"2021-12-27T07:13:04","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"Reconstructing the paleoceanographic and redox conditions responsible for variations in uranium content in North American Devonian black shales","docAbstract":"

The uranium (U) content, and more recently, the ratio between 238U and 235U in black shales are commonly applied as a proxy to determine redox conditions and infer organic-richness. Uranium contents typically display a linear relationship with total organic carbon (TOC) in shales. This relationship is due to the processes and mechanisms responsible for the incorporation of U into the sediment during the deposition and remineralization of organic matter. This U/TOC relationship can vary, however, and some shales display uncharacteristically low U content despite having high TOC content, while others show large enrichments of U relative to TOC. Here we examine the U to TOC ratios and U-isotope compositions of three Upper Devonian-Lower Mississippian shales: the Woodford Shale, the Cleveland Shale, and the Bakken Shale, with two study sites in Oklahoma, one site in eastern Kentucky, and three sites in eastern Montana and western North Dakota, respectively. The U/TOC ratios of each shale are distinct from one another exhibiting average ratios ranging from 3 in the Cleveland Shale, to over 10 in the Bakken Shale. The distinct geochemical composition of the three shales suggests that, although lithologically similar, each study site represents a markedly different and dynamic depositional environment. The low average U/TOC (~3) along with the relatively high δ238U values (~0.03‰) of the Cleveland Shale core suggests deposition along the basin margin under normal marine conditions with periods of reduced bottom water oxygenation, likely due to fluctuations in the location of the pycnocline. The Woodford Shale on the other hand, shows higher U/TOC ratios (~4, George core, ~9, Poe core) and δ238U (~0.02‰ average, George core, ~0.06‰ average, Poe core), which suggests an unrestricted setting with intermittent euxinic conditions. In contrast, high U/TOC ratios (2–15), and very high δ238U values (up to 0.55‰) in the Bakken Shale cores indicate intense metal draw-down into sediments under sulfidic waters. The results show that when the U/TOC ratios and U-isotopic compositions of each studied shale are compared to modern anoxic basins and upwelling areas, it allows for an enhanced understanding of the paleoenvironmental conditions such as basin restriction and redox state of waters within the Late Devonian epicontinental seas of North America.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.palaeo.2021.110763","usgsCitation":"Abshire, M.L., Riedinger, N., Clymer, J.M., Scott, C., Severmann, S., Romaniello, S.J., and Puckette, J.O., 2022, Reconstructing the paleoceanographic and redox conditions responsible for variations in uranium content in North American Devonian black shales: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 587, 110763, 11 p., https://doi.org/10.1016/j.palaeo.2021.110763.","productDescription":"110763, 11 p.","ipdsId":"IP-126011","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":449352,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.palaeo.2021.110763","text":"Publisher Index Page"},{"id":418743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"587","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Abshire, Michelle L.","contributorId":316208,"corporation":false,"usgs":false,"family":"Abshire","given":"Michelle","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":877030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riedinger, Natascha","contributorId":316209,"corporation":false,"usgs":false,"family":"Riedinger","given":"Natascha","email":"","affiliations":[],"preferred":false,"id":877031,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clymer, John M.","contributorId":316210,"corporation":false,"usgs":false,"family":"Clymer","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":877032,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scott, Clint 0000-0003-2778-2711 clintonscott@usgs.gov","orcid":"https://orcid.org/0000-0003-2778-2711","contributorId":5332,"corporation":false,"usgs":true,"family":"Scott","given":"Clint","email":"clintonscott@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":877033,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Severmann, Silke","contributorId":316211,"corporation":false,"usgs":false,"family":"Severmann","given":"Silke","email":"","affiliations":[],"preferred":false,"id":877034,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Romaniello, Stephen J.","contributorId":316212,"corporation":false,"usgs":false,"family":"Romaniello","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":877035,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Puckette, James O.","contributorId":316213,"corporation":false,"usgs":false,"family":"Puckette","given":"James","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":877036,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}