One of the most prominent challenges related to legacy seismic data is determining how these data can be appropriately used in modern research applications. The wide variety of instrumentation used in the analog era, the format of recording on paper wrapped around a helicorder drum, and limited metadata information introduces ambiguities that are not typical of modern digital data. Therefore, techniques must be developed to help characterize uncertainties in legacy data. This article presents an analysis that compares corecorded signals from two instruments—a Trillium Compact or Press‐Ewing (PE) seismometer for sensing ground motion and two recording systems: a modern Q330 digitizer or heated‐stylus system. Analyses of the recordings in both time and frequency domains indicate time uncertainty on the order of one second, identify a flat response in a 10–60 s band for the PE and drum recorder, and highlight how specific features of scans and paper seismograms (e.g., repeated portions of scans and line thickness) can cause timing jumps or reduced trace amplitude.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220230129","usgsCitation":"Lee, T., Ringler, A.T., Anthony, R.E., and Ishii, M., 2023, Comparison of co-recorded analog and digital systems for characterization of responses and uncertainties: Seismological Research Letters, v. 94, no. 5, p. 2301-2312, https://doi.org/10.1785/0220230129.","productDescription":"12 p.","startPage":"2301","endPage":"2312","ipdsId":"IP-154154","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":420230,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-07-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Lee, Thomas A.","contributorId":328830,"corporation":false,"usgs":false,"family":"Lee","given":"Thomas A.","affiliations":[],"preferred":false,"id":881246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":3946,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":881247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":881248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ishii, Miaki","contributorId":140929,"corporation":false,"usgs":false,"family":"Ishii","given":"Miaki","email":"","affiliations":[{"id":13619,"text":"Department of Earth & Planetary Sciences, Harvard University, Cambridge, MA","active":true,"usgs":false}],"preferred":false,"id":881249,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249589,"text":"70249589 - 2023 - Tree-ring derived avalanche frequency and climate associations in a high-latitude, maritime climate","interactions":[],"lastModifiedDate":"2023-10-18T12:09:25.06511","indexId":"70249589","displayToPublicDate":"2023-07-28T07:07:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6454,"text":"Journal of Geophysical Research - Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Tree-ring derived avalanche frequency and climate associations in a high-latitude, maritime climate","docAbstract":"Snow avalanches are a natural hazard in mountainous areas worldwide with severe impacts that include fatalities, damage to infrastructure, disruption to commerce, and landscape disturbance. Understanding long-term avalanche frequency patterns, and associated climate and weather influences, improves our understanding of how climate change may affect avalanche activity. We used dendrochronological techniques to evaluate the historical frequency of large magnitude avalanches (LMAs) in the high-latitude climate of southeast Alaska, United States. We collected 434 cross sections throughout six avalanche paths near Juneau, Alaska. This resulted in 2706 identified avalanche growth disturbances between 1720 and 2018, which allowed us to reconstruct 82 years with LMA activity across three sub-regions. By combining this tree-ring-derived avalanche data set with a suite of climate and atmospheric variables and applying a generalized linear model to fit a binomial regression, we found that February and March precipitation and the Oceanic Niño Index (ONI) were significant predictors of LMA activity in the study area. Specifically, LMA activity occurred during winters with substantial February and March precipitation and neutral or negative (cold) ONI values, while years not characterized by LMAs occur more frequently during warm winters (positive ONI values). Our examination of the climate-avalanche relationship in southeast Alaska sheds light on important climate variables and physical processes associated with LMA years. These results can be used to inform long-term infrastructure planning and avalanche mitigation operations in an urban area, such as Juneau, where critical infrastructure is subject to substantial avalanche hazard.
Climate change is influencing polar bear (Ursus maritimus) habitat, diet, and behavior but the effects of these changes on their physiology is not well understood. Blood-based biomarkers are used to assess the physiologic health of individuals but their usefulness for evaluating population health, especially as it relates to changing environmental conditions, has rarely been explored. We describe links between environmental conditions and physiologic functions of southern Beaufort Sea polar bears using data from blood samples collected from 1984 to 2018, a period marked by extensive environmental change. We evaluated associations between 13 physiologic biomarkers and circumpolar (Arctic oscillation index) and regional (wind patterns and ice-free days) environmental metrics and seasonal and demographic co-variates (age, sex, season, and year) known to affect polar bear ecology. We observed signs of dysregulation of water balance in polar bears following years with a lower annual Arctic oscillation index. In addition, liver enzyme values increased over time, which is suggestive of potential hepatocyte damage as the Arctic has warmed. Biomarkers of immune function increased with regional-scale wind patterns and the number of ice-free days over the Beaufort Sea continental shelf and were lower in years with a lower winter Arctic oscillation index, suggesting an increased allocation of energetic resources for immune processes under these conditions. We propose that the variation in polar bear immune and metabolic function is likely indicative of physiologic plasticity, a response that allows polar bears to remain in homeostasis even as they experience changes in nutrition and habitat in response to changing environments.
Spawning phenology and associated migrations of fishes are often regulated by factors such as temperature and stream discharge, but flow regulation of mainstem rivers coupled with climate change might disrupt these cues and affect fitness. Flannelmouth sucker (Catostomus latipinnis) persisting in heavily modified river networks are known to spawn in tributaries that might provide better spawning habitat than neighboring mainstem rivers subject to habitat degradation (e.g., embedded sediments, altered thermal regimes, and disconnected floodplains). Passive integrative transponder (PIT) tag data and radio telemetry were used to quantify the timing and duration of flannelmouth sucker tributary spawning migrations in relation to environmental cues in McElmo Creek, a tributary to the San Juan River in the American Southwest. We also tested the extent of the tributary migration and assessed mainstem movements prior to and following tributary migrations. Additionally, multi-year datasets of PIT detections from other tributaries in the Colorado River basin were used to quantify interannual and cross-site variation in the timing of flannelmouth sucker spawning migrations in relation to environmental cues. The arrival and residence times of fish spawning in McElmo Creek varied among years with earlier migration and a three-week increase in residence time in relatively wet years compared to drier years. Classification tree analysis suggested a combination of discharge and temperature determined arrival timing. Of fish PIT tagged in the fall, 56% tagged within 10 km of McElmo Creek spawned in the tributary the following spring, as did 60% of radio-tagged fish, with a decline in its use corresponding to increased distance of tagging location. A broader analysis of four tributaries in the Colorado River basin, including McElmo Creek, found photoperiod and temperature of tributary and mainstem rivers were the most important variables in determining migration timing, but tributary and mainstem discharge also aided in classification success. The largest tributary, the Little Colorado River, had more residential fish or fish that stayed for longer periods (median = 30 days), while McElmo Creek fish stayed an average of just 10 days in 2022. Our results generally suggest that higher discharge, across years or across sites, results in extended use of tributaries by flannelmouth suckers. Conservation actions that limit water extraction and maintain natural flow regimes in tributaries, while maintaining open connection with mainstem rivers may benefit migratory species including flannelmouth suckers.
","language":"English","publisher":"Wiley","doi":"10.1111/jfb.15509","usgsCitation":"Bonjour, S.M., Gido, K.B., McKinstry, M.C., Cathcart, C.N., Bogaard, M.R., Dzul, M.C., Healy, B.D., Hooley-Underwood, Z.E., Rogowski, D.L., and Yackulic, C., 2023, Migration timing and tributary use of spawning flannelmouth sucker (Catostomus latipinnis): Journal of Fish Biology, v. 103, no. 5, p. 1144-1162, https://doi.org/10.1111/jfb.15509.","productDescription":"19 p.","startPage":"1144","endPage":"1162","ipdsId":"IP-148081","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":419436,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"103","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-08-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Bonjour, Sophia M.","contributorId":317812,"corporation":false,"usgs":false,"family":"Bonjour","given":"Sophia","email":"","middleInitial":"M.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":879348,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gido, Keith B.","contributorId":317813,"corporation":false,"usgs":false,"family":"Gido","given":"Keith","email":"","middleInitial":"B.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":879349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKinstry, Mark C.","contributorId":301155,"corporation":false,"usgs":false,"family":"McKinstry","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":65322,"text":"Upper Colorado Regional Office","active":true,"usgs":false}],"preferred":false,"id":879350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cathcart, Charles N.","contributorId":317814,"corporation":false,"usgs":false,"family":"Cathcart","given":"Charles","email":"","middleInitial":"N.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":879351,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bogaard, Matthew R.","contributorId":317815,"corporation":false,"usgs":false,"family":"Bogaard","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":879352,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dzul, Maria C. 0000-0002-4798-5930 mdzul@usgs.gov","orcid":"https://orcid.org/0000-0002-4798-5930","contributorId":5469,"corporation":false,"usgs":true,"family":"Dzul","given":"Maria","email":"mdzul@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":879353,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Healy, Brian D. 0000-0002-4402-638X","orcid":"https://orcid.org/0000-0002-4402-638X","contributorId":304257,"corporation":false,"usgs":true,"family":"Healy","given":"Brian","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":879354,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hooley-Underwood, Zachary E.","contributorId":317816,"corporation":false,"usgs":false,"family":"Hooley-Underwood","given":"Zachary","email":"","middleInitial":"E.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":879355,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rogowski, David L.","contributorId":175084,"corporation":false,"usgs":false,"family":"Rogowski","given":"David","email":"","middleInitial":"L.","affiliations":[{"id":27527,"text":"AZ Game and FIsh Department","active":true,"usgs":false}],"preferred":false,"id":879356,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":879357,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70246988,"text":"ofr20231045 - 2023 - LANDFIRE technical documentation","interactions":[],"lastModifiedDate":"2026-02-11T21:26:11.184045","indexId":"ofr20231045","displayToPublicDate":"2023-07-26T12:31:40","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1045","displayTitle":"LANDFIRE Technical Documentation","title":"LANDFIRE technical documentation","docAbstract":"LANDFIRE (LF) completed the LF 2016 Remap effort in 2021, the biggest revision of its product suite since its inception. This document serves to describe the processes that went into this effort and elucidate the methods for creating each LF product. Although the document focuses on the LF 2016 Remap effort, it also details the two updates that have been completed since that effort, LF 2019 Limited (released June 2021) and LF 2020 (underway at the writing of this document).
The LF program is complex, requiring a team of interdisciplinary professionals to manage, produce, and maintain it. LF data production falls under six primary categories: reference, disturbance, vegetation, fuels, fire regime, and topography. Several data production units have the dual goals of producing a valuable stand-alone dataset and serving subsequent LF production needs. This document delves into the technical details of the six primary categories individually while also describing the connections to other LF products. Importantly, this LF technical documentation provides a transparent view of actual LF data layer production processes and can become a general information source for future production, production improvements, user questions, and leadership reference.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231045","usgsCitation":"La Puma, I.P., ed., 2023, LANDFIRE technical documentation: U.S. Geological Survey Open-File Report 2023–1045, 103 p., https://doi.org/10.3133/ofr20231045.","productDescription":"Report: xii, 103 p.; 2 Data Releases","numberOfPages":"120","onlineOnly":"Y","ipdsId":"IP-139238","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":419200,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZS2TM0","text":"USGS data release","linkHelpText":"GAP/LANDFIRE National Terrestrial Ecosystems 2011"},{"id":419201,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P955KPLE","text":"USGS data release","linkHelpText":"Protected Areas Database of the United States (PAD-US)"},{"id":419198,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1045/coverthb.jpg"},{"id":419199,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1045/ofr20231045.pdf","text":"Report","size":"9.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1045"},{"id":499782,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115017.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","contact":"LANDFIRE help desk
Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The nesting biology and demography of spectacled eiders (Somateria fischeri) along the lower Kashunuk River on the Yukon-Kuskokwim Delta, Alaska, were studied from 1993 to 2002. This previous work demonstrated that the breeding population on the study area was declining, and demographic modeling predicted that the population would continue to decline from 2002 forward. The predicted decline was primarily because of lead shot in tundra wetlands in the area, exposure of nesting females to lead, resulting in low adult female survival. The model predicted that lead pellets already in wetlands would slowly settle beyond the foraging depth of eiders, and that, lead exposure rates would decline. The goal of this project was to test this prediction by revisiting the lower Kashunuk River study area in 2022 to (1) update previous datasets regarding demographic parameters and (2) validate (or refute) existing models relative to lead exposure rates and the effects of lead on population dynamics. In the summer of 2022, a total of 37 nests were found in a sub-area of the historical study area. Comparing to past efforts in this same sub-area, more nests were found than predicted but the proportion of nesting female spectacled eiders exposed to lead in 2022 (24.3 percent) was still similar to levels of exposure observed between 1994 and 2002 (28.5 percent). Thus, data from the 2022 survey suggests that the earlier decline in numbers of nesting spectacled eiders has reversed, but there has been little decrease in lead exposure over time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231052","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Flint, P.L., 2023, Status of spectacled eiders (Somateria fischeri) on the Yukon-Kuskokwim Delta, Alaska, 2022—Testing and updating predictive models: U.S. Geological Survey Open-File Report 2023–1052, 5 p., https://doi.org/10.3133/ofr20231052.","productDescription":"vi, 5 p.","onlineOnly":"Y","ipdsId":"IP-151770","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":419316,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1052/ofr20231052.XML"},{"id":419315,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1052/images"},{"id":419314,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231052/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1052"},{"id":419313,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1052/ofr20231052.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1052"},{"id":419312,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1052/coverthb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon-Kuskokwim Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -166.06721221943172,\n 61.59887493914758\n ],\n [\n -166.06721221943172,\n 60.1670676261173\n ],\n [\n -162.86058022136012,\n 60.1670676261173\n ],\n [\n -162.86058022136012,\n 61.59887493914758\n ],\n [\n -166.06721221943172,\n 61.59887493914758\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Annual peak-flow data collected at U.S. Geological Survey streamgages in Minnesota and adjacent areas of neighboring states of Iowa and South Dakota were analyzed to develop and update regional regression equations that can be used to estimate the magnitude and frequency of peak streamflow for ungaged streams in Minnesota, excluding the Lake of the Woods-Rainy River Basin upstream from Kenora, Ontario, Canada. Hydraulic engineers use peak-flow frequency estimates to inform designs of bridges, culverts, and dams, and water managers use the estimates for regulation and planning activities. Peak-flow estimates are provided for the 66.7-, 50-, 20-, 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probabilities (AEPs), which are equivalent to annual flood-frequency recurrence intervals of 1.5-, 2-, 5-, 10-, 25-, 50-, 100-, and 500-years, respectively. The estimates were computed by applying the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak flows for 298 streamgages based on annual peak-flow data collected through water year 2019. The study area is represented by six hydrologic regions delineated on the basis of a pattern of residuals of statewide regressions, using basin characteristics such as drainage area, main-channel slope, lake area, storage area, and mean annual runoff as explanatory variables. The concept and principles of hydrologic landscape units was used to validate the regions. Residual analysis of the regional regression equations was used to subsequently develop equations relating the peak flow estimates for selected AEPs using 17 characteristics tested as explanatory variables in the regression analysis.
The equations developed in this study can be used to produce AEPs within the six regions and to update equations developed in earlier, similar studies in Minnesota. Furthermore, updating the equations in StreamStats, a web-based geographic information system tool developed by the U.S. Geological Survey, will allow hydraulic engineers and water managers to obtain AEPs and basin characteristics for user-selected locations on streams through an interactive map.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235079","collaboration":"Prepared in cooperation with the Minnesota Department of Transportation","usgsCitation":"Sanocki, C.A., and Levin, S.B., 2023, Techniques for estimating the magnitude and frequency of peak flows on small streams in Minnesota, excluding the Rainy River Basin, based on data through water year 2019: U.S. Geological Survey Scientific Investigations Report 2023–5079, 15 p., https://doi.org/10.3133/sir20235079.","productDescription":"Report: v, 15 p.; 2 Data Releases; Dataset","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-127955","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":419307,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235079/full"},{"id":419262,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":419257,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5079/coverthb.jpg"},{"id":435242,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UNQ0IV","text":"USGS data release","linkHelpText":"PeakFQ input and outputs for selected streamgages in Minnesota and border areas of adjacent states through water year 2019"},{"id":419261,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9T1HO7Q","text":"USGS data release","linkHelpText":"Model archive of regional flood frequency equations for Minnesota streams"},{"id":419260,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5079/images/"},{"id":419259,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5079/sir20235079.XML"},{"id":419258,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5079/sir20235079.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5079"},{"id":501042,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115013.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Minnesota","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-92.204691,46.704041],[-92.205192,46.698341],[-92.183091,46.695241],[-92.176091,46.686341],[-92.204092,46.666941],[-92.201592,46.656641],[-92.207092,46.651941],[-92.242493,46.649241],[-92.256592,46.658741],[-92.270592,46.650741],[-92.274392,46.657441],[-92.286192,46.660342],[-92.287392,46.667342],[-92.291292,46.668142],[-92.292192,46.663308],[-92.294033,46.074377],[-92.332912,46.062697],[-92.35176,46.015685],[-92.372717,46.014198],[-92.410649,46.027259],[-92.428555,46.024241],[-92.442259,46.016177],[-92.453373,45.992913],[-92.464512,45.985038],[-92.461138,45.980216],[-92.469354,45.973811],[-92.527052,45.983245],[-92.548459,45.969056],[-92.551186,45.95224],[-92.60246,45.940815],[-92.614314,45.934529],[-92.638824,45.934166],[-92.638474,45.925971],[-92.659549,45.922937],[-92.676167,45.912072],[-92.675737,45.907478],[-92.707702,45.894901],[-92.734039,45.868108],[-92.739278,45.84758],[-92.765146,45.830183],[-92.757815,45.806574],[-92.776496,45.790014],[-92.784621,45.764196],[-92.809837,45.744172],[-92.869193,45.717568],[-92.870025,45.697272],[-92.875488,45.689014],[-92.887929,45.639006],[-92.882529,45.610216],[-92.886442,45.598679],[-92.883749,45.575483],[-92.871082,45.567581],[-92.823309,45.560934],[-92.770223,45.566939],[-92.726082,45.541112],[-92.726677,45.514462],[-92.702224,45.493046],[-92.680234,45.464344],[-92.653549,45.455346],[-92.646602,45.441635],[-92.650422,45.398507],[-92.664102,45.393309],[-92.676961,45.380137],[-92.678223,45.373604],[-92.70272,45.358472],[-92.698967,45.336374],[-92.709968,45.321302],[-92.737122,45.300459],[-92.761013,45.289028],[-92.760615,45.278827],[-92.751659,45.26591],[-92.760249,45.2496],[-92.751708,45.218666],[-92.763908,45.204866],[-92.767408,45.190166],[-92.764872,45.182812],[-92.752404,45.173916],[-92.757707,45.155466],[-92.739584,45.115598],[-92.744938,45.108309],[-92.791528,45.079647],[-92.803079,45.060978],[-92.793282,45.047178],[-92.770362,45.033803],[-92.76206,45.02432],[-92.771231,45.001378],[-92.769445,44.97215],[-92.754603,44.955767],[-92.750645,44.937299],[-92.758701,44.908979],[-92.774571,44.898084],[-92.773946,44.889997],[-92.764133,44.875905],[-92.769102,44.862167],[-92.765278,44.837186],[-92.78043,44.812589],[-92.785206,44.792303],[-92.805287,44.768361],[-92.807988,44.75147],[-92.787906,44.737432],[-92.737259,44.717155],[-92.700948,44.693751],[-92.660988,44.660884],[-92.632105,44.649027],[-92.619779,44.634195],[-92.621456,44.615017],[-92.601516,44.612052],[-92.586216,44.600088],[-92.569434,44.603539],[-92.549777,44.58113],[-92.549957,44.568988],[-92.540551,44.567258],[-92.518358,44.575183],[-92.493808,44.566063],[-92.481001,44.568276],[-92.455105,44.561886],[-92.433256,44.5655],[-92.399281,44.558292],[-92.361518,44.558935],[-92.336114,44.554004],[-92.314071,44.538014],[-92.302466,44.516487],[-92.302215,44.500298],[-92.291005,44.485464],[-92.232472,44.445434],[-92.195378,44.433792],[-92.124513,44.422115],[-92.111085,44.413948],[-92.078605,44.404869],[-92.056486,44.402729],[-92.038147,44.388731],[-91.970266,44.365842],[-91.941311,44.340978],[-91.92559,44.333548],[-91.918625,44.322671],[-91.913534,44.311392],[-91.924613,44.291815],[-91.896388,44.27469],[-91.896008,44.262871],[-91.88704,44.251772],[-91.892698,44.231105],[-91.877429,44.212921],[-91.872369,44.199167],[-91.829167,44.17835],[-91.808064,44.159262],[-91.751747,44.134786],[-91.721552,44.130342],[-91.710597,44.12048],[-91.708207,44.105186],[-91.69531,44.09857],[-91.68153,44.0974],[-91.667006,44.086964],[-91.647873,44.064109],[-91.638115,44.063285],[-91.610487,44.04931],[-91.59207,44.031372],[-91.507121,44.01898],[-91.48087,44.008145],[-91.463515,44.009041],[-91.432522,43.996827],[-91.407395,43.965148],[-91.385785,43.954239],[-91.366642,43.937463],[-91.357426,43.917231],[-91.347741,43.911964],[-91.338141,43.897664],[-91.320605,43.888491],[-91.310991,43.867381],[-91.284138,43.847065],[-91.262436,43.792166],[-91.244135,43.774667],[-91.255431,43.744876],[-91.255932,43.729849],[-91.268455,43.709824],[-91.273252,43.666623],[-91.271749,43.654929],[-91.262397,43.64176],[-91.268748,43.615348],[-91.232707,43.583533],[-91.232812,43.564842],[-91.243214,43.550722],[-91.243183,43.540309],[-91.232941,43.523967],[-91.218292,43.514434],[-91.217706,43.50055],[-96.453049,43.500415],[-96.453067,45.298115],[-96.489065,45.357071],[-96.521787,45.375645],[-96.562142,45.38609],[-96.617726,45.408092],[-96.680454,45.410499],[-96.692541,45.417338],[-96.731396,45.45702],[-96.76528,45.521414],[-96.857751,45.605962],[-96.844211,45.639583],[-96.835769,45.649648],[-96.760866,45.687518],[-96.745086,45.701576],[-96.662595,45.738682],[-96.641941,45.759871],[-96.627778,45.786239],[-96.583085,45.820024],[-96.574517,45.843098],[-96.561334,45.945655],[-96.57035,45.963595],[-96.57794,46.026874],[-96.559271,46.058272],[-96.554507,46.083978],[-96.557952,46.102442],[-96.56692,46.11475],[-96.563043,46.119512],[-96.571439,46.12572],[-96.56926,46.133686],[-96.579453,46.147601],[-96.577952,46.165843],[-96.587408,46.178164],[-96.584372,46.204155],[-96.59755,46.227733],[-96.598645,46.241626],[-96.590942,46.250183],[-96.59887,46.26069],[-96.595014,46.275135],[-96.60136,46.30413],[-96.599761,46.330386],[-96.619991,46.340135],[-96.618147,46.344295],[-96.629211,46.352654],[-96.644335,46.351908],[-96.646341,46.360982],[-96.655206,46.365964],[-96.658436,46.373391],[-96.666028,46.374566],[-96.669132,46.390037],[-96.680687,46.407383],[-96.688082,46.40788],[-96.701358,46.420584],[-96.703078,46.429467],[-96.718074,46.438255],[-96.715557,46.463232],[-96.73627,46.48138],[-96.737798,46.489785],[-96.733612,46.497224],[-96.737702,46.50077],[-96.738475,46.525793],[-96.744341,46.533006],[-96.743003,46.54294],[-96.74883,46.558127],[-96.744436,46.56596],[-96.746442,46.574078],[-96.772446,46.600129],[-96.774094,46.613288],[-96.78995,46.631531],[-96.790663,46.649112],[-96.798823,46.658071],[-96.792958,46.677427],[-96.784339,46.685054],[-96.790906,46.70297],[-96.779252,46.727429],[-96.784279,46.732993],[-96.781216,46.740944],[-96.787466,46.756753],[-96.784314,46.766973],[-96.796195,46.789881],[-96.795756,46.807795],[-96.801446,46.810401],[-96.80016,46.819664],[-96.787657,46.827817],[-96.789663,46.832306],[-96.779347,46.843672],[-96.781358,46.879363],[-96.768458,46.879563],[-96.767358,46.883663],[-96.773558,46.884763],[-96.776558,46.895663],[-96.759241,46.918223],[-96.761757,46.934663],[-96.78312,46.925482],[-96.79038,46.929398],[-96.791558,46.944464],[-96.797734,46.9464],[-96.798737,46.962399],[-96.821852,46.969372],[-96.82318,46.999965],[-96.834221,47.006671],[-96.829499,47.021537],[-96.818557,47.02778],[-96.821422,47.032842],[-96.819321,47.0529],[-96.824479,47.059682],[-96.818175,47.104193],[-96.827344,47.120144],[-96.824807,47.124968],[-96.831547,47.142017],[-96.822377,47.162744],[-96.829637,47.17497],[-96.826962,47.182802],[-96.838806,47.197894],[-96.832789,47.203911],[-96.838806,47.22502],[-96.832946,47.237588],[-96.83766,47.240876],[-96.835368,47.250428],[-96.841672,47.258164],[-96.838997,47.267716],[-96.842531,47.269531],[-96.844088,47.289981],[-96.832884,47.30449],[-96.841958,47.316907],[-96.835845,47.321014],[-96.835845,47.335914],[-96.852417,47.366241],[-96.848907,47.370565],[-96.852676,47.374973],[-96.846925,47.376891],[-96.840621,47.389881],[-96.845492,47.394179],[-96.844919,47.399815],[-96.863593,47.418775],[-96.85748,47.440457],[-96.859868,47.470926],[-96.85471,47.478281],[-96.85853,47.489934],[-96.851653,47.497098],[-96.851367,47.509037],[-96.866363,47.524893],[-96.85471,47.535973],[-96.859153,47.566355],[-96.853689,47.570381],[-96.856373,47.575749],[-96.851293,47.589264],[-96.856903,47.602329],[-96.855421,47.60875],[-96.873671,47.613654],[-96.871005,47.616832],[-96.879496,47.620576],[-96.882393,47.633489],[-96.888573,47.63845],[-96.882376,47.649025],[-96.88697,47.653049],[-96.887126,47.666369],[-96.895271,47.67357],[-96.899352,47.689473],[-96.908928,47.688722],[-96.907266,47.693976],[-96.920119,47.710383],[-96.923544,47.718201],[-96.919471,47.722515],[-96.932809,47.737139],[-96.928505,47.748037],[-96.934173,47.752412],[-96.939179,47.768397],[-96.9644,47.782995],[-96.957283,47.790147],[-96.966068,47.797297],[-96.975131,47.798326],[-96.980579,47.805614],[-96.979327,47.824533],[-96.986685,47.837639],[-96.998295,47.841724],[-96.998144,47.858882],[-97.005557,47.863977],[-97.002456,47.868677],[-97.023156,47.874978],[-97.019355,47.880278],[-97.024955,47.886878],[-97.019155,47.889778],[-97.024955,47.894978],[-97.020155,47.900478],[-97.024955,47.908178],[-97.017254,47.905678],[-97.015354,47.910278],[-97.023754,47.915878],[-97.018054,47.918078],[-97.035754,47.930179],[-97.036054,47.939379],[-97.054554,47.946279],[-97.052454,47.957179],[-97.061454,47.96358],[-97.053553,47.991612],[-97.064289,47.998508],[-97.066762,48.009558],[-97.063012,48.013179],[-97.072239,48.019107],[-97.068987,48.026267],[-97.072257,48.048068],[-97.097772,48.07108],[-97.103052,48.071669],[-97.099431,48.082106],[-97.105226,48.09044],[-97.104872,48.097851],[-97.109535,48.104723],[-97.123205,48.106648],[-97.120702,48.114987],[-97.131956,48.139563],[-97.141401,48.14359],[-97.138911,48.157793],[-97.146745,48.168556],[-97.141474,48.179099],[-97.146233,48.186054],[-97.134372,48.210434],[-97.136304,48.228984],[-97.141254,48.234668],[-97.135763,48.237596],[-97.138765,48.244991],[-97.127276,48.253323],[-97.131846,48.267589],[-97.11657,48.279661],[-97.12216,48.290056],[-97.128862,48.292882],[-97.122072,48.300865],[-97.132443,48.315489],[-97.127601,48.323319],[-97.134854,48.331314],[-97.131145,48.339722],[-97.147748,48.359905],[-97.140106,48.380479],[-97.145592,48.394195],[-97.135012,48.406735],[-97.142849,48.419471],[-97.1356,48.424369],[-97.139173,48.430528],[-97.134229,48.439797],[-97.137689,48.447583],[-97.132746,48.459942],[-97.144116,48.469212],[-97.141397,48.476256],[-97.144981,48.481571],[-97.140291,48.484722],[-97.138864,48.494362],[-97.148133,48.503384],[-97.153076,48.524148],[-97.150481,48.536877],[-97.163105,48.543855],[-97.160863,48.549236],[-97.152459,48.552326],[-97.158638,48.564067],[-97.149616,48.569876],[-97.14974,48.579516],[-97.142915,48.583733],[-97.143684,48.597066],[-97.137504,48.612268],[-97.132931,48.61338],[-97.130089,48.621166],[-97.125639,48.620919],[-97.125269,48.629694],[-97.108466,48.632658],[-97.111921,48.642918],[-97.100551,48.658614],[-97.102652,48.664793],[-97.097708,48.68395],[-97.118286,48.700573],[-97.116185,48.709348],[-97.136083,48.727763],[-97.139488,48.746611],[-97.151289,48.757428],[-97.147478,48.763698],[-97.154854,48.774515],[-97.157093,48.790024],[-97.163535,48.79507],[-97.165624,48.809627],[-97.180028,48.81845],[-97.177747,48.824815],[-97.181116,48.832741],[-97.173811,48.838309],[-97.175618,48.853105],[-97.187362,48.867598],[-97.185738,48.87222],[-97.197982,48.880341],[-97.197982,48.898332],[-97.210541,48.90439],[-97.211161,48.916649],[-97.217992,48.919735],[-97.218666,48.931781],[-97.224505,48.9341],[-97.232147,48.948955],[-97.230859,48.960891],[-97.239209,48.968684],[-97.237297,48.985696],[-97.230833,48.991303],[-97.229039,49.000687],[-95.153711,48.998903],[-95.15335,49.383079],[-95.126467,49.369439],[-95.058404,49.35317],[-95.014415,49.356405],[-94.988908,49.368897],[-94.957465,49.370186],[-94.854245,49.324154],[-94.816222,49.320987],[-94.824291,49.308834],[-94.82516,49.294283],[-94.797244,49.214284],[-94.797527,49.197791],[-94.773223,49.120733],[-94.750221,49.099763],[-94.750218,48.999992],[-94.718932,48.999991],[-94.683069,48.883929],[-94.684217,48.872399],[-94.692527,48.86895],[-94.693044,48.853392],[-94.685681,48.840119],[-94.701968,48.831778],[-94.704284,48.824284],[-94.694974,48.809206],[-94.694312,48.789352],[-94.690889,48.778066],[-94.651765,48.755913],[-94.645164,48.749975],[-94.645083,48.744143],[-94.61901,48.737374],[-94.58715,48.717599],[-94.549069,48.714653],[-94.533057,48.701262],[-94.452332,48.692444],[-94.438701,48.694889],[-94.416191,48.710948],[-94.384221,48.711806],[-94.342758,48.703382],[-94.308446,48.710239],[-94.290737,48.707747],[-94.260541,48.696381],[-94.251169,48.683514],[-94.254643,48.663888],[-94.250497,48.656654],[-94.224276,48.649527],[-94.091244,48.643669],[-94.065775,48.646104],[-94.035616,48.641018],[-94.006933,48.643193],[-93.944221,48.632294],[-93.91153,48.634673],[-93.840754,48.628548],[-93.824144,48.610724],[-93.806763,48.577616],[-93.811201,48.542385],[-93.818253,48.530046],[-93.794454,48.516021],[-93.656652,48.515731],[-93.643091,48.518294],[-93.628865,48.53121],[-93.612844,48.521876],[-93.60587,48.522472],[-93.594379,48.528793],[-93.547191,48.528684],[-93.467504,48.545664],[-93.460798,48.550552],[-93.456675,48.561834],[-93.465199,48.590659],[-93.438494,48.59338],[-93.405269,48.609344],[-93.395022,48.603303],[-93.371156,48.605085],[-93.362132,48.613832],[-93.35324,48.613378],[-93.349095,48.624935],[-93.254854,48.642784],[-93.207398,48.642474],[-93.178095,48.623339],[-93.088438,48.627597],[-92.984963,48.623731],[-92.954876,48.631493],[-92.95012,48.630419],[-92.949839,48.608269],[-92.929614,48.606874],[-92.909947,48.596313],[-92.894687,48.594915],[-92.728046,48.53929],[-92.657881,48.546263],[-92.634931,48.542873],[-92.625739,48.518189],[-92.631117,48.508252],[-92.627237,48.503383],[-92.636696,48.499428],[-92.654039,48.501635],[-92.661418,48.496557],[-92.698824,48.494892],[-92.712562,48.463013],[-92.687998,48.443889],[-92.656027,48.436709],[-92.507285,48.447875],[-92.475585,48.418793],[-92.456325,48.414204],[-92.456389,48.401134],[-92.47675,48.37176],[-92.469948,48.351836],[-92.437825,48.309839],[-92.416285,48.295463],[-92.369174,48.220268],[-92.336831,48.235383],[-92.269742,48.248241],[-92.273706,48.256747],[-92.294541,48.27156],[-92.292999,48.276404],[-92.301451,48.288608],[-92.294527,48.306454],[-92.306309,48.316442],[-92.304561,48.322977],[-92.295412,48.323957],[-92.288994,48.342991],[-92.26228,48.354933],[-92.222813,48.349203],[-92.216983,48.345114],[-92.206803,48.345596],[-92.203684,48.352063],[-92.178418,48.351881],[-92.177354,48.357228],[-92.145049,48.365651],[-92.143583,48.356121],[-92.083513,48.353865],[-92.077961,48.358253],[-92.055228,48.359213],[-92.045734,48.347901],[-92.046562,48.33474],[-92.037721,48.333183],[-92.030872,48.325824],[-92.000133,48.321355],[-92.01298,48.297391],[-92.006577,48.265421],[-91.989545,48.260214],[-91.976903,48.244626],[-91.971056,48.247667],[-91.971779,48.252977],[-91.954432,48.251678],[-91.952209,48.244394],[-91.957683,48.242683],[-91.957798,48.232989],[-91.941838,48.230602],[-91.915772,48.238871],[-91.89347,48.237699],[-91.884691,48.227321],[-91.867882,48.219095],[-91.864382,48.207031],[-91.815772,48.211748],[-91.809038,48.206013],[-91.79181,48.202492],[-91.789011,48.196549],[-91.756637,48.205022],[-91.749075,48.198844],[-91.741932,48.199122],[-91.742313,48.204491],[-91.714931,48.19913],[-91.711611,48.1891],[-91.721413,48.180255],[-91.724584,48.170657],[-91.705318,48.170775],[-91.70726,48.153661],[-91.698174,48.141643],[-91.699981,48.13184],[-91.712226,48.116883],[-91.703524,48.113548],[-91.682845,48.122118],[-91.687623,48.111698],[-91.676876,48.107264],[-91.665208,48.107011],[-91.653261,48.114137],[-91.653571,48.109567],[-91.640175,48.096926],[-91.559272,48.108268],[-91.552962,48.103012],[-91.569746,48.093348],[-91.575471,48.066294],[-91.575672,48.048791],[-91.567254,48.043719],[-91.488646,48.068065],[-91.45033,48.068806],[-91.437582,48.049248],[-91.429642,48.048608],[-91.391128,48.057075],[-91.370872,48.06941],[-91.365143,48.066968],[-91.340159,48.073236],[-91.332589,48.069331],[-91.26638,48.078713],[-91.214428,48.10294],[-91.190461,48.124891],[-91.183207,48.122235],[-91.176181,48.125811],[-91.137733,48.14915],[-91.139402,48.154738],[-91.092258,48.173101],[-91.082731,48.180756],[-91.024208,48.190072],[-90.976955,48.219452],[-90.914971,48.230603],[-90.88548,48.245784],[-90.875107,48.237784],[-90.847352,48.244443],[-90.839176,48.239511],[-90.836313,48.176963],[-90.832589,48.173765],[-90.821115,48.184709],[-90.817698,48.179569],[-90.804207,48.177833],[-90.796596,48.159373],[-90.777917,48.163801],[-90.778031,48.148723],[-90.79797,48.136894],[-90.787305,48.134196],[-90.789919,48.129902],[-90.76911,48.116585],[-90.761555,48.100133],[-90.751608,48.090968],[-90.641596,48.103515],[-90.626886,48.111846],[-90.59146,48.117546],[-90.582217,48.123784],[-90.55929,48.121683],[-90.555845,48.117069],[-90.569763,48.106951],[-90.567482,48.101178],[-90.556838,48.096008],[-90.487077,48.099082],[-90.467712,48.108818],[-90.438449,48.098747],[-90.403219,48.105114],[-90.374542,48.090942],[-90.367658,48.094577],[-90.344234,48.094447],[-90.330052,48.102399],[-90.312386,48.1053],[-90.289337,48.098993],[-90.224692,48.108148],[-90.188679,48.107947],[-90.176605,48.112445],[-90.136191,48.112136],[-90.116259,48.104303],[-90.073873,48.101138],[-90.023595,48.084708],[-90.015057,48.067188],[-90.008446,48.068396],[-89.997852,48.057567],[-89.99305,48.028404],[-89.97718,48.023501],[-89.968255,48.014482],[-89.954605,48.011516],[-89.95059,48.015901],[-89.934489,48.015628],[-89.915341,47.994866],[-89.897414,47.987599],[-89.873286,47.985419],[-89.868153,47.989898],[-89.847571,47.992442],[-89.842568,48.001368],[-89.830385,48.000284],[-89.820483,48.014665],[-89.797744,48.014505],[-89.763967,48.022969],[-89.724048,48.018996],[-89.721038,48.017965],[-89.724044,48.013675],[-89.716114,48.016441],[-89.716417,48.010251],[-89.702528,48.006325],[-89.673798,48.01151],[-89.667128,48.007421],[-89.657051,48.009954],[-89.649057,48.003853],[-89.617867,48.010947],[-89.611678,48.017529],[-89.607821,48.006566],[-89.594749,48.004332],[-89.582117,47.996314],[-89.564288,48.00293],[-89.489226,48.014528],[-89.495344,48.002356],[-89.541521,47.992841],[-89.551555,47.987305],[-89.555015,47.974849],[-89.572315,47.967238],[-89.58823,47.9662],[-89.611412,47.980731],[-89.624559,47.983153],[-89.631825,47.980039],[-89.640129,47.96793],[-89.638285,47.954275],[-89.697619,47.941288],[-89.793539,47.891358],[-89.85396,47.873997],[-89.87158,47.874194],[-89.923649,47.862062],[-89.930844,47.857723],[-89.92752,47.850825],[-89.933899,47.84676],[-89.974296,47.830514],[-90.072025,47.811105],[-90.075559,47.803303],[-90.1168,47.79538],[-90.16079,47.792807],[-90.178755,47.786414],[-90.187636,47.77813],[-90.248794,47.772763],[-90.323446,47.753771],[-90.332686,47.746387],[-90.437712,47.731612],[-90.441912,47.726404],[-90.458365,47.7214],[-90.537105,47.703055],[-90.551291,47.690266],[-90.735927,47.624343],[-90.86827,47.5569],[-90.907494,47.532873],[-90.914247,47.522639],[-90.939072,47.514532],[-91.032945,47.458236],[-91.045646,47.456525],[-91.097569,47.413888],[-91.128131,47.399619],[-91.146958,47.381464],[-91.156513,47.378816],[-91.188772,47.340082],[-91.238658,47.304976],[-91.262512,47.27929],[-91.288478,47.26596],[-91.326019,47.238993],[-91.357803,47.206743],[-91.418805,47.172152],[-91.477351,47.125667],[-91.497902,47.122579],[-91.518793,47.108121],[-91.573817,47.089917],[-91.591508,47.068684],[-91.626824,47.049953],[-91.644564,47.026491],[-91.666477,47.014297],[-91.704649,47.005246],[-91.780675,46.945881],[-91.806851,46.933727],[-91.841349,46.925215],[-91.883238,46.905728],[-91.914984,46.883836],[-91.952985,46.867037],[-92.094089,46.787839],[-92.088289,46.773639],[-92.06449,46.745439],[-92.025789,46.710839],[-92.01529,46.706469],[-92.020289,46.704039],[-92.03399,46.708939],[-92.08949,46.74924],[-92.10819,46.74914],[-92.13789,46.73954],[-92.14329,46.73464],[-92.141291,46.72524],[-92.146291,46.71594],[-92.167291,46.719941],[-92.189091,46.717541],[-92.204691,46.704041]]]},\"properties\":{\"name\":\"Minnesota\",\"nation\":\"USA \"}}]}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
This report outlines quality assurance (QA) processes, including radiometric and geometric calibration guidelines, and guidelines for data acquisition and quality control to be followed by U.S. Geological Survey (USGS) researchers for acquiring and processing uncrewed aircraft systems (UAS) data. These QA processes ensure that UAS data can be used for quantitative analysis and are comparable with other standard geospatial data.
Remote sensing data play a critical role in monitoring Earth’s resources. Traditionally, the USGS and Department of the Interior have used well calibrated metric sensors mounted on satellite or aircraft platforms to collect these data. These sensors and platforms are stable, and data have been processed using standard pipelines. These processes ensured that the data are generally consistent with each other and benefitted a diverse group of users. These data are shared among multiple researchers around the world through the internet and other means, using standard formats and metadata.
In the last few years, UAS platforms have democratized the remote sensing data collection further, bringing an unparalleled level of control of time, sensors, and processes to individual researchers. Together with the development of cheaper and lighter sensors and relaxation of prohibitions against UAS operation in the National Airspace System by the Federal Aviation Authority, researchers can collect remote sensing data using UAS platforms. Researchers often customize the sensors on these UAS systems based on their specific requirements and use ad hoc processing steps to generate data.
A challenge is that these data are often produced by a wide array of sensors and processes that render them potentially inconsistent with each other. Therefore, unlike data collected from metric sensors, UAS-based data are designed to benefit only specific user groups. The data thus generated often lack traceability to known standards, making them difficult to use with other geospatial data.
This report provides radiometric and geometric calibration guidelines, as well as guidelines for data acquisition and quality control, that can be followed by USGS researchers in acquiring and processing UAS data. Instead of calibrating sensors, researchers collecting UAS data can focus on calibrating the data. Various radiometric calibration processes are provided, and the two panel empirical line method is highlighted for radiometric calibration.
For geometric calibration, USGS and Department of the Interior researchers are experienced in following standard calibration procedures provided by standard UAS data processing software. However, researchers may be aided in paying attention to the tie points and the accuracy of the ground control points used for geometric calibration and data production. The accuracy of ground control points are related to the requirements of the project. The ground control points and the quality of tie points directly contribute to the geometric accuracy of the data, regardless of the ground sample distance of the imagery.
The guidelines outlined in this report are intended to ensure that the data are in common units and are quantifiable and comparable with other data. These QA and calibration processes can be critical in ensuring that these datasets are used to the maximum extent possible. Including the calibration parameters (and their uncertainties) as part of metadata can allow for easier data discovery and analytical filters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231033","usgsCitation":"Sampath, A., Shrestha, M., While, M., and Scholl, V.M., 2023, Guidelines for calibration of uncrewed aircraft systems imagery: U.S. Geological Survey Open-File Report 2023–1033, 23 p., https://doi.org/10.3133/ofr20231033.","productDescription":"v, 23 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-146359","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":419305,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231033/full"},{"id":419252,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1033/images/"},{"id":419251,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1033/ofr20231033.XML"},{"id":419250,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1033/ofr20231033.pdf","text":"Report","size":"3.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1033"},{"id":419249,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1033/coverthb.jpg"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Herbivorous animals tend to seek out plants at intermediate phenological states to improve energy intake while minimizing consumption of fibrous material. In some ecosystems, the timing of green-up is heterogeneous and propagates across space in a wave-like pattern, known as the green wave. Tracking the green wave allows individuals to prolong access to higher-quality forage. While there is a plethora of empirical support for such behavior in herbivorous taxa, the green wave hypothesis (GWH) is nuanced based on factors such as body morphometrics and digestive capacity. Furthermore, little is known about whether other taxa, such as omnivores, track the green wave. Our objective was to assess whether the GWH can be extended to explain the movements of omnivores. Using GPS collar data from seven populations (n = 127 individuals) of brown bears Ursus arctos across their entire North American range, we first tested whether bears tracked the green wave. Using conditional resource selection functions (RSFs), we found that variation in proxies of vegetative forage quality better explained movement and habitat selection than proxies of forage biomass in over half of the bears in our study, providing evidence of green wave tracking. Second, we assess factors that explained variation in green wave tracking using linear mixed effects models. Green wave tracking in brown bears was explained by the variation in availability of green-up within spring home ranges, and how green-up transitioned across those home ranges. Our results demonstrate that the GWH can partially explain movement of a non-migratory omnivorous species, extending the generality of the GWH as a broad predictor of animal space use. The green wave is another resource wave brown bears track, and our findings help predict brown bear space use, which can be used to guide conservation and habitat restoration efforts.
","language":"English","publisher":"Wiley","doi":"10.1111/ecog.06549","usgsCitation":"Bowersock, N.R., Ciarniello, L.M., Deacy, W.W., Heard, D.C., Joly, K., Lamb, C.T., Leacock, W.B., Mclellan, B., Mowat, G., Sorum, M.S., van Manen, F.T., and Merkle, J., 2023, A test of the green wave hypothesis in omnivorous brown bears across North America: Ecography, v. 2023, no. 10, e06549, 12 p., https://doi.org/10.1111/ecog.06549.","productDescription":"e06549, 12 p.","ipdsId":"IP-142801","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":442652,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ecog.06549","text":"Publisher Index Page"},{"id":419350,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, British Columbia, Idaho, Montana, Wyoming","otherGeospatial":"Elk Valley, Flathead Valley, Gates of the Arctic, Greater Yellowstone ecosystem, Kodiak Island, Parsnip Mountain, Parsnip Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.58270702767695,\n 43.58074880621092\n ],\n [\n -114.86203363678416,\n 50.16374484994262\n ],\n [\n -122.08539027157664,\n 55.91094145040341\n ],\n [\n -144.08820653499708,\n 68.6311238737492\n ],\n [\n -152.21192576584002,\n 69.43288028347476\n ],\n [\n -161.02170588000897,\n 68.55829959585586\n ],\n [\n -155.54559520650918,\n 56.09696676721251\n ],\n [\n -150.40416182908686,\n 57.307524490103276\n ],\n [\n -144.85601862056535,\n 61.07891762933866\n ],\n [\n -130.33415600545123,\n 54.54538997683014\n ],\n [\n -121.6241105920378,\n 49.020537277214885\n ],\n [\n -111.72137354906724,\n 44.96531210384342\n ],\n [\n -111.36242529627467,\n 42.9172213366808\n ],\n [\n -106.9583587691117,\n 42.788416970678725\n ],\n [\n -107.58270702767695,\n 43.58074880621092\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2023","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Bowersock, Nathaniel R.","contributorId":268804,"corporation":false,"usgs":false,"family":"Bowersock","given":"Nathaniel","email":"","middleInitial":"R.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":879090,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ciarniello, L. M.","contributorId":317704,"corporation":false,"usgs":false,"family":"Ciarniello","given":"L.","email":"","middleInitial":"M.","affiliations":[{"id":69132,"text":"Aklak Wildlife Consulting","active":true,"usgs":false}],"preferred":false,"id":879091,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deacy, William W.","contributorId":287298,"corporation":false,"usgs":false,"family":"Deacy","given":"William","email":"","middleInitial":"W.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":879092,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heard, D. C.","contributorId":317706,"corporation":false,"usgs":false,"family":"Heard","given":"D.","email":"","middleInitial":"C.","affiliations":[{"id":69134,"text":"BC Ministry of Forests, Lands and Natural Resource Operations","active":true,"usgs":false}],"preferred":false,"id":879093,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Joly, Kyle","contributorId":53117,"corporation":false,"usgs":false,"family":"Joly","given":"Kyle","email":"","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":879094,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lamb, Clayton T.","contributorId":216009,"corporation":false,"usgs":false,"family":"Lamb","given":"Clayton","email":"","middleInitial":"T.","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":879095,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leacock, William B.","contributorId":211732,"corporation":false,"usgs":false,"family":"Leacock","given":"William","email":"","middleInitial":"B.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":879096,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mclellan, Bruce","contributorId":167051,"corporation":false,"usgs":false,"family":"Mclellan","given":"Bruce","email":"","affiliations":[{"id":24603,"text":"British Columbia Ministry of Forests Research Branch","active":true,"usgs":false}],"preferred":false,"id":879097,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mowat, Garth","contributorId":216012,"corporation":false,"usgs":false,"family":"Mowat","given":"Garth","email":"","affiliations":[{"id":13452,"text":"Univ. British Columbia","active":true,"usgs":false}],"preferred":false,"id":879098,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sorum, Mathew S","contributorId":243500,"corporation":false,"usgs":false,"family":"Sorum","given":"Mathew","email":"","middleInitial":"S","affiliations":[],"preferred":false,"id":879099,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":879100,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Merkle, Jerod A.","contributorId":270421,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod A.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":879101,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70247704,"text":"70247704 - 2023 - Accuracy of finite fault slip estimates in subduction zone regions with topographic Green's functions and seafloor geodesy","interactions":[],"lastModifiedDate":"2023-08-14T12:25:52.922387","indexId":"70247704","displayToPublicDate":"2023-07-25T07:24:37","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Accuracy of finite fault slip estimates in subduction zone regions with topographic Green's functions and seafloor geodesy","docAbstract":"Until recently, the lack of seafloor geodetic instrumentation and the use of unrealistically simple, half-space based forward models have resulted in poor resolution of near-trench slip in subduction zone settings. Here, we use a synthetic framework to investigate the impact of topography and geodetic data distribution on coseismic slip estimates in various subduction zone settings. We calculate surface displacements in two synthetic topographic domains that have topography similar to that of Chile and Japan, respectively. We then attempt to image target slip distributions by using a Bayesian approach to solve for slip with two sets of Green's functions—one that accounts for topography and one that does not—and five sets of 50 or more observation points selected from the synthetic surface displacements. Three of these sets of observation points are entirely onland, and two include 5–10 seafloor geodetic sites. We find that the use of topographic Green's functions always improves inferred slip models, and with seafloor geodetic data, it enables an almost perfect recovery of a target slip model, even in the near-trench region. Critically, our results demonstrate that it would be impossible for non-topographic Green's functions to properly recover the true slip distribution, particularly in the near-trench region. We also perform a parameter study with approximately 4,000 slip models estimated using a least-square approach, and find that topographic Green's functions yield significantly more accurate slip models in cases where good data (well distributed and reasonably dense) are available, even in the absence of seafloor geodetic sites.
Introduced fungal pathogens have caused declines and extinctions of naïve wildlife populations across vertebrate classes. Consequences of introduced pathogens to hosts with small ranges might be especially severe because of limited redundancy to rescue populations and lower abundance that may limit the resilience of populations to perturbations like disease introduction. As a complement to biosecurity measures to prevent the spread of pathogens, surveillance programs may enable early detection of pathogens, when management actions to limit the effects of pathogens on naïve hosts might be most beneficial. We analyzed surveillance data for the endangered and narrowly endemic Dixie Valley toad (Anaxyrus [= Bufo] williamsi) from two time periods (2011–2014 and 2019–2021) to estimate the minimum detectable prevalence of the amphibian fungal pathogen Batrachochytrium dendrobatidis (Bd). We assessed if detection efficiency could be improved by using samples from both Dixie Valley toads and co-occurring introduced American bullfrogs (Lithobates catesbeianus) and literature-derived surveillance weights. We further evaluated a weighted surveillance design to increase the efficiency of surveillance efforts for Bd within the toad’s small (<6 km2) range. We found that monitoring adult and larval American bullfrogs would probably detect Bd more efficiently than monitoring Dixie Valley toads alone. Given that no Bd was detected, minimum detectable prevalence of Bd was <3% in 2011–2014, and <5% (Dixie Valley toads only) and <10% (American bullfrogs only) in 2019–2021. Optimal management for Bd depends on the mechanisms underlying its apparent absence from the range of Dixie Valley toads, but a balanced surveillance scheme that includes sampling American bullfrogs to increase the likelihood of detecting Bd, and adult Dixie Valley toads to ensure broad spatial coverage where American bullfrogs do not occur, would probably result in efficient surveillance, which might permit timely management of Bd if it is detected.
Given the burgeoning dam removal movement and the large number of dams approaching obsolescence in the United States, cost estimating data and tools are needed for dam removal prioritization, planning, and execution. We used the list of removed dams compiled by American Rivers to search for publicly available reported costs for dam removal projects. Total cost information could include component costs related to project planning, dam deconstruction, monitoring, and several categories of mitigation activities. We compiled reported costs from 455 unique sources for 668 dams removed in the United States from 1965 to 2020. The dam removals occurred within 571 unique projects involving 1–18 dams. When adjusted for inflation into 2020 USD, cost of these projects totaled \\$1.522 billion, with per-dam costs ranging from $1 thousand (k) to \\$268.8 million (M). The median cost for dam removals was \\$157k, \\$823k, and \\$6.2M for dams that were< 5 m, between 5–10 m, and > 10 m in height, respectively. Geographic differences in total costs showed that northern states in general, and the Pacific Northwest in particular, spent the most on dam removal. The Midwest and the Northeast spent proportionally more on removal of dams less than 5 m in height, whereas the Northwest and Southwest spent the most on larger dam removals > 10 m tall. We used stochastic gradient boosting with quantile regression to model dam removal cost against potential predictor variables including dam characteristics (dam height and material), hydrography (average annual discharge and drainage area), project complexity (inferred from construction and sediment management, mitigation, and post-removal cost drivers), and geographic region. Dam height, annual average discharge at the dam site, and project complexity were the predominant drivers of removal cost. The final model had an R2 of 57% and when applied to a test dataset model predictions had a root mean squared error of $5.09M and a mean absolute error of \\$1.45M, indicating its potential utility to predict estimated costs of dam removal. We developed a R shiny application for estimating dam removal costs using customized model inputs for exploratory analyses and potential dam removal planning.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2023.1215471","usgsCitation":"Duda, J.J., Jumani, S., Wieferich, D.J., Tullos, D.D., McKay, S.K., Randle, T.J., Jansen, A., Bailey, S., Jensen, B.L., Johnson, R.C., Wagner, E.J., Richards, K.B., Wenger, S., Walther, E.J., and Bountry, J.A., 2023, Patterns, drivers, and a predictive model of dam removal cost in the United States: Frontiers in Ecology and Evolution, v. 11, 1215471. 16 p., https://doi.org/10.3389/fevo.2023.1215471.","productDescription":"1215471. 16 p.","ipdsId":"IP-153157","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":442673,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1215471","text":"Publisher Index Page"},{"id":435246,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G8V371","text":"USGS data release","linkHelpText":"Compilation of cost estimates for dam removal projects in the United States"},{"id":419297,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-07-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":878956,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jumani, Suman 0000-0002-2292-7996","orcid":"https://orcid.org/0000-0002-2292-7996","contributorId":305995,"corporation":false,"usgs":false,"family":"Jumani","given":"Suman","email":"","affiliations":[{"id":66338,"text":"Network for Engineering with Nature, Georgia, USA","active":true,"usgs":false}],"preferred":false,"id":878957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wieferich, Daniel J. 0000-0003-1554-7992 dwieferich@usgs.gov","orcid":"https://orcid.org/0000-0003-1554-7992","contributorId":176205,"corporation":false,"usgs":true,"family":"Wieferich","given":"Daniel","email":"dwieferich@usgs.gov","middleInitial":"J.","affiliations":[{"id":5069,"text":"Office of the AD Core Science Systems","active":true,"usgs":true},{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":878958,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tullos, Desiree D.","contributorId":176667,"corporation":false,"usgs":false,"family":"Tullos","given":"Desiree","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":878959,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKay, S. Kyle","contributorId":169086,"corporation":false,"usgs":false,"family":"McKay","given":"S.","email":"","middleInitial":"Kyle","affiliations":[],"preferred":false,"id":878960,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Randle, Timothy J.","contributorId":90994,"corporation":false,"usgs":false,"family":"Randle","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":878961,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jansen, Alvin","contributorId":317292,"corporation":false,"usgs":false,"family":"Jansen","given":"Alvin","email":"","affiliations":[{"id":68995,"text":"Technical Service Center, Bureau of Reclamation, Denver, Colorado, USA","active":true,"usgs":false}],"preferred":false,"id":878962,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bailey, Susan","contributorId":317293,"corporation":false,"usgs":false,"family":"Bailey","given":"Susan","email":"","affiliations":[{"id":68996,"text":"Engineer Research and Development Center - Environmental Laboratory, U.S. Army Corps of Engineers, Vicksburg, Mississippi, USA","active":true,"usgs":false}],"preferred":false,"id":878963,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jensen, Benjamin Lorenz 0000-0003-1199-973X","orcid":"https://orcid.org/0000-0003-1199-973X","contributorId":306036,"corporation":false,"usgs":true,"family":"Jensen","given":"Benjamin","email":"","middleInitial":"Lorenz","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":878964,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Johnson, Rachelle Carina 0000-0003-1480-4088","orcid":"https://orcid.org/0000-0003-1480-4088","contributorId":241962,"corporation":false,"usgs":true,"family":"Johnson","given":"Rachelle","email":"","middleInitial":"Carina","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":878965,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wagner, Ella J.","contributorId":306038,"corporation":false,"usgs":false,"family":"Wagner","given":"Ella","email":"","middleInitial":"J.","affiliations":[{"id":66358,"text":"Previously USGS, WFRC, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":878966,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Richards, Kyla Breanne 0000-0001-7504-6239","orcid":"https://orcid.org/0000-0001-7504-6239","contributorId":306039,"corporation":false,"usgs":true,"family":"Richards","given":"Kyla","email":"","middleInitial":"Breanne","affiliations":[{"id":5069,"text":"Office of the AD Core Science Systems","active":true,"usgs":true}],"preferred":true,"id":878967,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":878968,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Walther, Eric J.","contributorId":304288,"corporation":false,"usgs":false,"family":"Walther","given":"Eric","email":"","middleInitial":"J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":878969,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Bountry, Jennifer A.","contributorId":30114,"corporation":false,"usgs":false,"family":"Bountry","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":878970,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70256486,"text":"70256486 - 2023 - Waterbody size predicts bank- and boat-angler efforts","interactions":[],"lastModifiedDate":"2024-08-06T16:58:22.279736","indexId":"70256486","displayToPublicDate":"2023-07-23T11:55:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Waterbody size predicts bank- and boat-angler efforts","docAbstract":"Bank- and boat-angler efforts are logistically difficult and costly to estimate, preventing landscape-scale estimates that are required to address current and future challenges (e.g., climate change, invasive species) for inland recreational fisheries. Using a large Nebraska, USA, recreational fishery dataset (N = 67 waterbodies), we demonstrate that waterbody size can be used to predict bank- and boat-angler efforts across a heterogeneous landscape of extra small (< 104 ha) and large (> 647 ha) waterbodies. Bank and boat anglers respond to waterbody size, however these relationships appear to be unique between the two angler types. Boat-angler efforts increased as a function of waterbody size, whereas bank-angler efforts increased as a function of waterbody size for extra small waterbodies but not for large waterbodies. The ability to connect waterbody size and angler effort will be important for continued effective inland fisheries management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2023.106801","usgsCitation":"Kanee, D., Pope, K.L., Koupal, K., Pegg, M., Chizinski, C., and Kaemingk, M., 2023, Waterbody size predicts bank- and boat-angler efforts: Fisheries Research, v. 267,, 106801, 5 p., https://doi.org/10.1016/j.fishres.2023.106801.","productDescription":"106801, 5 p.","ipdsId":"IP-148165","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":442681,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fishres.2023.106801","text":"Publisher Index Page"},{"id":432297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.053249,41.001406],[-104.053127,43.000585],[-101.849982,42.999329],[-101.625424,42.996238],[-100.472742,42.999288],[-98.49855,42.99856],[-98.490483,42.977948],[-98.467356,42.947556],[-98.448309,42.936428],[-98.444145,42.929242],[-98.437285,42.928393],[-98.430934,42.931504],[-98.42074,42.931924],[-98.34623,42.902747],[-98.325864,42.8865],[-98.280007,42.874996],[-98.25181,42.872824],[-98.219826,42.853157],[-98.189765,42.841628],[-98.167523,42.836925],[-98.14806,42.840013],[-98.137912,42.832728],[-98.127489,42.820127],[-98.107688,42.810633],[-98.094574,42.799309],[-98.067388,42.784759],[-98.062913,42.781119],[-98.059838,42.772772],[-98.056625,42.770781],[-98.035034,42.764205],[-98.013046,42.762299],[-98.005739,42.764167],[-98.000348,42.763256],[-97.977588,42.769923],[-97.950147,42.769619],[-97.936716,42.775754],[-97.921434,42.788352],[-97.908983,42.794909],[-97.888562,42.817251],[-97.879878,42.835395],[-97.878976,42.843673],[-97.875849,42.847725],[-97.877003,42.854394],[-97.875345,42.858724],[-97.84527,42.867734],[-97.828496,42.868797],[-97.817075,42.861781],[-97.774456,42.849774],[-97.72045,42.847439],[-97.686506,42.842435],[-97.657846,42.844626],[-97.611811,42.858367],[-97.603762,42.858329],[-97.591916,42.853837],[-97.561928,42.847552],[-97.531867,42.850105],[-97.504847,42.858477],[-97.49149,42.851625],[-97.470529,42.850455],[-97.452177,42.846048],[-97.442279,42.846224],[-97.431951,42.851542],[-97.417066,42.865918],[-97.408315,42.868334],[-97.393966,42.86425],[-97.376695,42.865195],[-97.368643,42.858419],[-97.359569,42.854816],[-97.336156,42.856802],[-97.306677,42.867604],[-97.289859,42.855499],[-97.267946,42.852583],[-97.248556,42.855386],[-97.218825,42.845848],[-97.217411,42.843519],[-97.218269,42.829561],[-97.213957,42.820143],[-97.213084,42.813007],[-97.210126,42.809296],[-97.200431,42.805485],[-97.166978,42.802087],[-97.150763,42.795566],[-97.138216,42.783428],[-97.134461,42.774494],[-97.131331,42.771929],[-97.096128,42.76934],[-97.065592,42.772189],[-97.033229,42.765904],[-97.02485,42.76243],[-96.99282,42.759481],[-96.97912,42.76009],[-96.96888,42.754278],[-96.96123,42.740623],[-96.965833,42.727096],[-96.964776,42.722455],[-96.961576,42.719841],[-96.948902,42.719465],[-96.924156,42.730327],[-96.906797,42.7338],[-96.886845,42.725222],[-96.860436,42.720797],[-96.843419,42.712024],[-96.806223,42.704154],[-96.801652,42.698774],[-96.800485,42.692466],[-96.802178,42.672237],[-96.800986,42.669758],[-96.793238,42.666024],[-96.76406,42.661985],[-96.746949,42.666223],[-96.728024,42.666882],[-96.691269,42.6562],[-96.687669,42.653126],[-96.687788,42.645992],[-96.709485,42.621932],[-96.711546,42.614758],[-96.7093,42.603753],[-96.681369,42.574486],[-96.658754,42.566426],[-96.643589,42.557604],[-96.63533,42.54764],[-96.632882,42.528987],[-96.628179,42.516963],[-96.625958,42.513576],[-96.611489,42.506088],[-96.603468,42.50446],[-96.591121,42.50541],[-96.567896,42.517877],[-96.548791,42.520547],[-96.538036,42.518131],[-96.528753,42.513273],[-96.520683,42.504761],[-96.515891,42.49427],[-96.508587,42.486691],[-96.501321,42.482749],[-96.478792,42.479635],[-96.443408,42.489495],[-96.423892,42.48898],[-96.396107,42.484095],[-96.386007,42.474495],[-96.381307,42.461694],[-96.380707,42.446394],[-96.387608,42.432494],[-96.413609,42.407894],[-96.41498,42.393442],[-96.408436,42.376092],[-96.417093,42.361443],[-96.417786,42.351449],[-96.413895,42.343393],[-96.407998,42.337408],[-96.384169,42.325874],[-96.375307,42.318339],[-96.369212,42.308344],[-96.368454,42.291848],[-96.365792,42.285875],[-96.356406,42.276493],[-96.336003,42.264806],[-96.328905,42.254734],[-96.327706,42.249992],[-96.330004,42.240224],[-96.322868,42.233637],[-96.323723,42.229887],[-96.336323,42.218922],[-96.356591,42.215182],[-96.35987,42.210545],[-96.348066,42.194747],[-96.347243,42.186721],[-96.350323,42.17744],[-96.347752,42.166806],[-96.33798,42.157197],[-96.319528,42.146647],[-96.310085,42.132523],[-96.301023,42.128042],[-96.279203,42.12348],[-96.2689,42.11359],[-96.266594,42.103262],[-96.267636,42.096177],[-96.276758,42.081416],[-96.279079,42.074026],[-96.278445,42.060399],[-96.275548,42.051976],[-96.271427,42.044988],[-96.263886,42.039858],[-96.256087,42.03808],[-96.246832,42.041616],[-96.238392,42.041088],[-96.225656,42.035217],[-96.221901,42.029558],[-96.223611,42.022652],[-96.238859,42.012315],[-96.241932,42.006965],[-96.240713,41.999351],[-96.236487,41.996428],[-96.225463,41.994734],[-96.215225,42.006701],[-96.206083,42.009267],[-96.194556,42.008662],[-96.188067,42.006323],[-96.183568,41.999987],[-96.192141,41.984461],[-96.186265,41.977417],[-96.177203,41.976325],[-96.156538,41.980137],[-96.141228,41.978063],[-96.129505,41.971673],[-96.129186,41.965136],[-96.133318,41.955732],[-96.144583,41.941544],[-96.136613,41.927167],[-96.136743,41.920826],[-96.142265,41.915379],[-96.159098,41.910057],[-96.161988,41.905553],[-96.161756,41.90182],[-96.148826,41.888132],[-96.146083,41.874988],[-96.142045,41.868865],[-96.135253,41.863128],[-96.116202,41.854869],[-96.110246,41.84885],[-96.107911,41.840339],[-96.11081,41.828172],[-96.107592,41.820685],[-96.09827,41.814206],[-96.075548,41.807811],[-96.069662,41.803509],[-96.064879,41.79623],[-96.066413,41.788913],[-96.077543,41.777824],[-96.079915,41.757895],[-96.084673,41.753314],[-96.102772,41.746339],[-96.106425,41.73789],[-96.105582,41.731647],[-96.10261,41.728016],[-96.079682,41.717962],[-96.073376,41.710674],[-96.073063,41.705004],[-96.082429,41.698159],[-96.090579,41.697425],[-96.105119,41.699917],[-96.111968,41.697773],[-96.117751,41.694221],[-96.121401,41.688522],[-96.120983,41.677861],[-96.114978,41.67122],[-96.099837,41.66103],[-96.095415,41.652736],[-96.095046,41.647365],[-96.100701,41.635507],[-96.116233,41.621574],[-96.117558,41.609999],[-96.109387,41.596871],[-96.101496,41.59158],[-96.085771,41.585746],[-96.081152,41.577289],[-96.082406,41.571229],[-96.093613,41.558271],[-96.096186,41.547192],[-96.09409,41.539265],[-96.08822,41.530595],[-96.07307,41.525052],[-96.05369,41.508859],[-96.040701,41.507076],[-96.036603,41.509047],[-96.034305,41.512853],[-96.027289,41.541081],[-96.023182,41.544364],[-96.016474,41.546085],[-96.005079,41.544004],[-96.001161,41.541146],[-95.993891,41.523412],[-95.992833,41.512002],[-95.997903,41.504789],[-96.019224,41.489296],[-96.019542,41.486617],[-96.011757,41.476212],[-96.004708,41.472342],[-95.982962,41.469778],[-95.962329,41.46281],[-95.946465,41.466166],[-95.936801,41.46519],[-95.925713,41.459382],[-95.920281,41.451566],[-95.921833,41.442062],[-95.933169,41.42943],[-95.929721,41.411331],[-95.93749,41.393095],[-95.92879,41.370096],[-95.93099,41.364696],[-95.93549,41.360596],[-95.954891,41.351796],[-95.956691,41.345496],[-95.946891,41.334096],[-95.92569,41.322197],[-95.88869,41.319097],[-95.883089,41.316697],[-95.874689,41.307097],[-95.871489,41.295797],[-95.872889,41.289497],[-95.88239,41.281397],[-95.90249,41.273398],[-95.912491,41.279498],[-95.90429,41.293497],[-95.90429,41.299597],[-95.920291,41.301097],[-95.927491,41.298397],[-95.929591,41.292297],[-95.928691,41.281398],[-95.913991,41.271398],[-95.920391,41.268398],[-95.921891,41.264598],[-95.921291,41.258498],[-95.910891,41.233998],[-95.912591,41.226998],[-95.924891,41.211198],[-95.927491,41.202198],[-95.923219,41.191046],[-95.91459,41.185098],[-95.864789,41.188298],[-95.850188,41.184798],[-95.844088,41.180598],[-95.841288,41.174998],[-95.841888,41.171098],[-95.846188,41.166698],[-95.852788,41.165398],[-95.867344,41.168734],[-95.871912,41.168122],[-95.880936,41.160269],[-95.883489,41.154898],[-95.882088,41.143998],[-95.865888,41.117898],[-95.86545,41.101266],[-95.862587,41.088399],[-95.865463,41.080367],[-95.878103,41.069587],[-95.882415,41.060411],[-95.879487,41.053299],[-95.861782,41.039427],[-95.859654,41.035695],[-95.859918,41.025403],[-95.869486,41.009399],[-95.867286,41.001599],[-95.860116,40.995242],[-95.838908,40.986484],[-95.833537,40.98266],[-95.829074,40.975688],[-95.829829,40.963857],[-95.837951,40.950618],[-95.839743,40.93278],[-95.836438,40.921642],[-95.830699,40.915004],[-95.814302,40.902936],[-95.809775,40.895447],[-95.809474,40.891228],[-95.815933,40.879846],[-95.824989,40.875],[-95.838735,40.872191],[-95.844073,40.869248],[-95.847785,40.864328],[-95.847084,40.854174],[-95.837186,40.835347],[-95.838601,40.826175],[-95.843921,40.817686],[-95.845342,40.811324],[-95.843745,40.803783],[-95.834523,40.787778],[-95.835232,40.779151],[-95.84662,40.768619],[-95.869982,40.759645],[-95.883643,40.747831],[-95.888697,40.736292],[-95.885349,40.721093],[-95.883178,40.717579],[-95.859378,40.708055],[-95.852615,40.702262],[-95.847931,40.694197],[-95.846034,40.682605],[-95.842801,40.677496],[-95.822913,40.66724],[-95.804307,40.664886],[-95.786568,40.657253],[-95.772832,40.642496],[-95.768926,40.621264],[-95.749685,40.606842],[-95.748858,40.599965],[-95.753148,40.59284],[-95.768527,40.583296],[-95.773549,40.578205],[-95.774704,40.573574],[-95.763833,40.553873],[-95.763624,40.548298],[-95.769281,40.536656],[-95.76692,40.531563],[-95.762857,40.528371],[-95.74868,40.524275],[-95.73725,40.52393],[-95.725214,40.527773],[-95.714291,40.527208],[-95.708591,40.521551],[-95.69721,40.528477],[-95.69505,40.533124],[-95.697281,40.536985],[-95.694147,40.556942],[-95.678718,40.56256],[-95.671754,40.562626],[-95.665486,40.556686],[-95.662097,40.549959],[-95.655848,40.546609],[-95.652262,40.538114],[-95.655674,40.523557],[-95.661687,40.517309],[-95.699969,40.505275],[-95.694726,40.493602],[-95.696756,40.478849],[-95.694651,40.471452],[-95.671742,40.456695],[-95.65819,40.44188],[-95.65563,40.434736],[-95.661463,40.415947],[-95.659134,40.40869],[-95.643934,40.386849],[-95.641027,40.366399],[-95.627124,40.3528],[-95.623728,40.346567],[-95.622704,40.340856],[-95.625204,40.334288],[-95.633807,40.329297],[-95.653729,40.322582],[-95.657764,40.315788],[-95.657328,40.310856],[-95.651507,40.306684],[-95.645329,40.305693],[-95.617931,40.313728],[-95.610439,40.31397],[-95.598657,40.309809],[-95.581787,40.29958],[-95.562157,40.297359],[-95.55162,40.288666],[-95.551488,40.281061],[-95.556275,40.270761],[-95.552473,40.261904],[-95.521925,40.24947],[-95.490333,40.248966],[-95.477501,40.24272],[-95.472548,40.236078],[-95.469718,40.227908],[-95.471393,40.217333],[-95.482319,40.200667],[-95.48254,40.192283],[-95.479193,40.185652],[-95.460746,40.169173],[-95.442818,40.163261],[-95.436348,40.15872],[-95.432165,40.141025],[-95.428749,40.135577],[-95.419186,40.130586],[-95.409481,40.130052],[-95.398667,40.126419],[-95.393347,40.119212],[-95.394216,40.108263],[-95.407591,40.09803],[-95.410643,40.091531],[-95.408455,40.079158],[-95.409856,40.07432],[-95.418345,40.066509],[-95.42164,40.058952],[-95.41932,40.048442],[-95.413588,40.038424],[-95.402665,40.030567],[-95.391527,40.027058],[-95.382957,40.027112],[-95.363983,40.031498],[-95.348777,40.029297],[-95.336242,40.019104],[-95.315271,40.01207],[-95.311163,40.007806],[-95.30829,39.999998],[-98.193483,40.002614],[-99.756835,40.001342],[-102.051744,40.003078],[-102.051614,41.002377],[-104.053249,41.001406]]]},\"properties\":{\"name\":\"Nebraska\",\"nation\":\"USA \"}}]}","volume":"267,","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kanee, D.S.","contributorId":340845,"corporation":false,"usgs":false,"family":"Kanee","given":"D.S.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":907602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":907603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koupal, Keith D.","contributorId":340847,"corporation":false,"usgs":false,"family":"Koupal","given":"Keith D.","affiliations":[{"id":17640,"text":"Nebraska Game and Parks Commission","active":true,"usgs":false}],"preferred":false,"id":907604,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pegg, M.A.","contributorId":274523,"corporation":false,"usgs":false,"family":"Pegg","given":"M.A.","affiliations":[{"id":16602,"text":"University of Nebraska, Lincoln","active":true,"usgs":false}],"preferred":false,"id":907605,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chizinski, C.J.","contributorId":340849,"corporation":false,"usgs":false,"family":"Chizinski","given":"C.J.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":907606,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kaemingk, M.A.","contributorId":340850,"corporation":false,"usgs":false,"family":"Kaemingk","given":"M.A.","email":"","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":907607,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70255163,"text":"70255163 - 2023 - Conserving habitat for migratory ungulates: How wide is a migration corridor?","interactions":[],"lastModifiedDate":"2024-06-14T13:32:12.209183","indexId":"70255163","displayToPublicDate":"2023-07-23T08:23:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Conserving habitat for migratory ungulates: How wide is a migration corridor?","docAbstract":"To better understand differential sensitivities among fish species to the piscicidal compound Antimycin-A (ANT-A), we hypothesized that variations in amino acids at the ANT-A binding site may reflect toxicity differences. Protein sequences for six motifs comprising the ANT-A binding site were obtained and compared for invasive carp species (N = 515) and seven non-target species (N = 277); a consensus was delineated from each species. The carp species, Common Carp (Cyprinus carpio), Silver Carp (Hypophthalmichthys molitrix), Bighead Carp (Hypophthalmichthys nobilis), Grass Carp (Ctenopharyngodon idella), and Black Carp (Mylopharyngodon piceus), showed the same amino acids at the site; thus, it was termed the carp consensus motif sequence (CCM). Channel Catfish (Ictalurus punctatus) showed the most amino acid polymorphisms, with three motifs 96–100% different from CCM. Within a species, Bluegill (Lepomis macrochirus) and Fathead Minnow (Pimephales promelas) variation per motif was most dissimilar (46.7% and 21.6%, respectively). Organismal mortality data from the literature indicated Yellow Perch (Perca flavescens), Walleye (Sander vitreus), and American Gizzard Shad (Dorosoma cepedianum) to be most sensitive to the piscicide, Catfish least sensitive, and all others intermediate. The protein sequence variations of the binding site appeared to be in accord with organismal sensitivity categories when they differed from the CCM; the motifs in Gizzard Shad and Walleye were the same as in CCM. The physical/chemical nature of ANT-A is important to consider in organismal response comparisons. This cellular approach of studying ANT-A binding at its target enzyme is a non-destructive way to predict piscicidal efficacy of ANT-A against fishes of interest, informs management decisions in control efforts for invasives, and can be used to forecast effects on sympatric species.
","language":"English","publisher":"MDPI","doi":"10.3390/fishes8070381","usgsCitation":"Baudoin, B., Brown, B.L., Calfee, R.D., and Jenkins, J., 2023, Amino acid variation at the mitochondrial binding site of Antimycin A is proposed to reflect sensitivity and toxicity differences among fish species: Fishes, v. 8, no. 7, 381, 17 p., https://doi.org/10.3390/fishes8070381.","productDescription":"381, 17 p.","ipdsId":"IP-144658","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":442691,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes8070381","text":"Publisher Index Page"},{"id":419410,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"8","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Baudoin, Brooke A. 0000-0003-2874-1604","orcid":"https://orcid.org/0000-0003-2874-1604","contributorId":317787,"corporation":false,"usgs":false,"family":"Baudoin","given":"Brooke A.","affiliations":[{"id":69159,"text":"William Carey University","active":true,"usgs":false}],"preferred":false,"id":879308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Bonnie L.","contributorId":23083,"corporation":false,"usgs":false,"family":"Brown","given":"Bonnie","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":879309,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":879310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jenkins, Jill 0000-0002-5087-0894","orcid":"https://orcid.org/0000-0002-5087-0894","contributorId":206579,"corporation":false,"usgs":true,"family":"Jenkins","given":"Jill","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":879311,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70246679,"text":"sir20235042 - 2023 - Selenium hazards in the Salton Sea environment—Summary of current knowledge to inform future wetland management","interactions":[],"lastModifiedDate":"2026-03-06T21:38:07.222047","indexId":"sir20235042","displayToPublicDate":"2023-07-20T14:20:47","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5042","displayTitle":"Selenium Hazards in the Salton Sea Environment—Summary of Current Knowledge to Inform Future Wetland Management","title":"Selenium hazards in the Salton Sea environment—Summary of current knowledge to inform future wetland management","docAbstract":"Quaternary marine and continental shales in the western United States are sources of selenium that can be loaded into the aquatic environment through mining, agricultural, and energy production processes. The mobilization of selenium from shales through agricultural irrigation has been recognized since the 1930s; however, discovery of deformities in birds and other wildlife using agricultural habitats during the 1980s spurred studies to determine the extent and effects of the contamination. Through these early studies, researchers determined that biota in the Salton Sea drainage basin was at risk from legacy selenium contamination in the Colorado River watershed.
The Salton Sea and its surrounding managed and unmanaged wetlands provide vital inland habitat and trophic support for diverse assemblages of resident and migratory wildlife, and understanding regional selenium hazards for these trust species is a priority for many Federal and State agencies. The modern Salton Sea is a shallow, landlocked saline lake in Riverside and Imperial Counties (not shown) of California that is sustained by irrigation return and perennial river inflow. Changes in water transfer agreements under the 2003 Quantification Settlement Agreement (QSA) have resulted in reduced irrigation flow, declining lake levels, and the evolution of unmanaged wetlands in areas where drains and rivers no longer reach the Salton Sea. These wetlands provide additional habitat for some species of concern, but their potential to increase selenium hazards for trust species is largely unknown.
From the 1980s to 2020, efforts to document selenium contamination and effects throughout the region have resulted in a considerable amount of selenium data from the Salton Sea and its surrounding drainage basin; however, no long-term (greater than 20 years), consistent sampling program has been established, and all data have been collected by different entities using a variety of protocols and analytical techniques. This lack of coordination has been previously documented in regional management plans and has led to difficulty in reliably assessing selenium hazards in the Salton Sea environment. This report provides a summary of the available disparate selenium information collected from water, sediment, and biota in the Salton Sea region since the 1980s and to identify data gaps that need to be filled to understand the potential effects of selenium on species of concern, including federally endangered desert pupfish (Cyprinodon macularius) and Yuma Ridgway’s Rail (Rallus obsoletus yumanensis; formerly Yuma Clapper Rail, Rallus longirostris yumanensis).
Available data from the Salton Sea drainage basin show that water from the Colorado River has the lowest selenium concentration of all surface water sources. All other surface water flowing into the Salton Sea has elevated selenium concentrations due to evaporation and evapotranspiration that occurs in agricultural fields and associated water delivery infrastructure or leaching of selenium from irrigated farmland soils. The Salton Sea has lower selenium concentrations because of various biogeochemical processes that recycle selenium into the sediment or volatilize it to the atmosphere; however, these mechanisms are not well defined, and it is not clear if selenium cycling will change in response to possible changes in the oxidation state of the Salton Sea bottom waters as water levels decline. Agricultural drains have the highest average selenium concentrations, but few drains have been sampled since changes in irrigation practices have occurred (due to the 2003 QSA). Groundwater selenium concentrations are variable; some wells south of the Salton Sea have selenium concentrations as high as 300 micrograms per liter (µg/L), whereas selenium concentrations are below detection in other wells. Groundwater and surface-water geothermal discharge zones around the margins of the Salton Sea and in unmanaged wetlands have not been studied in detail, and published selenium measurements are not available for these surface features.
Selenium concentrations in the sediment of the Salton Sea drainage basin are highest in wetland particulate organic matter and the Salton Sea lakebed, indicating that removal of selenium from the water to the sediment has been a primary mechanism for keeping selenium concentrations low in the water column. Sediment selenium concentrations in wetlands are lower than in the Salton Sea but higher than inflowing drains and rivers, indicating the lentic wetland sites also may be important sinks for selenium because of biogeochemical processes. Sediment selenium data have not been collected in agricultural drains since changes in irrigation practices occurred (due to the 2003 QSA), and it is unknown if selenium sequestration from the water column has changed in these systems.
We divided biological data into broad taxonomic categories, including primary producers, invertebrates, herpetofauna, mammals, fishes, and birds to facilitate evaluation of selenium concentrations and spatiotemporal trends observed in the Salton Sea. Overall, selenium concentrations were substantially greater in algae samples compared to all vascular plant samples combined. Median selenium concentrations in several invertebrate taxa (Chironomidae, Formicidae, Corixidae, Corbiculidae and Nereididae, and Decapoda) exceeded the maximum suggested dietary threshold of 3.0–4.0 micrograms per gram (µg/g) dry weight (dw) for predators consuming invertebrates in aquatic food webs. The greatest number of samples were collected from fish, and selenium distributions among species and locations showed that the range for most samples was lower than the U.S. Environmental Protection Agency selenium criterion for aquatic life (8.5 µg/g dw whole body, 11.3 µg/g dw fillets). The median selenium concentrations for whole body fish were below the selenium criterion in most locations, except for bairdiella (Bairdiella icistia) from the Salton Sea and irrigation drains, a few individual tilapia spp. (family Cichlidae, including genera Tilapia, Oreochromis, and their hybrids) from the river and river outlets, and several western mosquitofish (Gambusia affinis) and sailfin molly (Poecilia latipinna) from irrigation drain outlets. For avian samples combined among years and locations, median selenium concentrations in livers from all families except waders and Ibis (family Threskiornithidae) were higher than levels expected to cause selenium toxicosis (10–20 µg/g dw), and all median egg concentrations were above or near 6.0 μg/g dw, which is a conservative threshold value for reproductive impairment.
Most knowledge gaps we identified for water, sediment, and biota were interrelated, and the use of integrated approaches to address knowledge gaps can provide greater insight into the drivers behind selenium hazards. Integrated water, sediment, and biota studies could help identify cost-effective management solutions that serve multiple purposes. A comprehensive analysis of the hydrology, biogeochemistry, and food-web processes in wetlands and other habitats can inform predictive models to identify drivers of selenium bioavailability, uptake from the environment and subsequent trophic transfer, ultimately forming the basis for experimental habitat management manipulations to minimize selenium hazards to wildlife. Furthermore, a comprehensive, long-term sampling and analytical laboratory plan would enable comparison of data among different entities that are sampling at the Salton Sea. Such efforts are well suited to help fill knowledge gaps that preclude understanding of selenium hazards and future management options for biota using Salton Sea habitats, including newly formed wetlands throughout the region.
All data compiled for this report are available in two U.S. Geological Survey data releases: Groover and others (2022) for water and sediment samples and De La Cruz and others (2022) for biological samples. The data releases include all publicly available data for selenium concentrations in water, sediment, and biological samples collected in and around the Salton Sea, including the Coachella and Imperial Valleys. The data releases also include previously unpublished data.
Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Polychlorinated biphenyls (PCBs), some of the earliest “forever chemicals,” were used for decades in the United States before 1979 when PCB manufacturing was banned. High PCB concentrations were found recently in the lower Clinton River in the Great Lakes drainage. To determine the possible existence, location, and significance of a current source of PCBs, the U.S. Geological Survey (USGS) deployed passive water samplers (SPMDs, semipermeable membrane devices) in the river at 15 sites for 1 month in 2019 near outfalls of interest and other locations. USGS also deployed passive stream sediment samplers at a subset of four sites during the same period and collected bank sediment samples at a subset of four sites. Sediment from nearby catch basins was also collected. Samples were assayed for 209 individual PCB congeners, and patterns in total and individual congeners were evaluated; ancillary sediment data included grain size, total organic carbon, and moisture. U.S. Army Corps of Engineers (USACE) data for total PCBs and 209 PCB congeners in surficial sediment samples collected in 2019 were also evaluated. In general, total PCBs were highest in streambed sediment, followed by catch basin sediment, bank sediment, and then water as estimated from SPMDs. Total PCBs in sediment were low in all catch basins but one (sample CB19–02) that drains from an historical landfill area to one of two adjacent outfalls of interest: the outfall for a nearby wastewater treatment plant and adjacent outfall MTC–R–060, where the highest total PCBs in USGS stream sediment samples were found (site 14, sample 14STRM; 1,260,000 picograms per gram). Also, the SPMD at site 14 was the only water sample with more “light” (three or fewer chlorine atoms) than “heavy” (four or more chlorine atoms) PCB congeners, and the passive sediment sample had the highest proportion of light PCBs in USGS sediment samples. Light PCB congeners degrade more quickly than heavy PCB congeners and results may indicate that one or more current sources of PCBs are contributing to total PCBs in sediment at four river sites. Of 209 possible PCB congeners assayed, 117 congeners were detected in water samples; 155 and 154 congeners were detected in USGS and USACE sediment samples, respectively. PCBs 28, 73, 31, and 18 (highest to lowest) contributed most toward total PCBs in water samples overall; PCBs 20/28, 31, 52, and 44/47/65 contributed most toward total PCBs for sediment in USGS stream samples overall and USACE samples overall; these rankings were also true for catch basins overall except for PCB–31. After omitting coeluting congeners to allow further comparison, 5 key PCB congeners are in the top 20 congeners across all assay groups: 17, 31, 52, 95, and 118. The importance of these congeners in multiple assays aligns with their importance as components of certain Aroclors. Sediment from the high PCB catch basin (sample CB19–02) had a different pattern of top congeners than the other catch basins, and multivariate analyses indicated a high degree of similarity in its overall congener pattern with that of the highest PCB sediment sample (sample 14STRM) collected by the outfalls for the catch basin and the wastewater treatment plant. Similarities in overall congener patterns across sample media as determined by multivariate analyses confirmed some site linkages and the possibility of more than one source of PCBs to the reach. Furthermore, equilibrium partitioning calculations indicated that water concentrations as estimated by SPMDs were high enough to result in the PCB concentrations measured in USGS passive sediment samples but not USACE surficial sediment samples when normalized by organic carbon. However, the SPMDs and passive sediment samples reflect only one month of contribution to the river and higher concentrations would be expected to result with years of PCB accumulation. PCBs contributed to the river water by outfalls could eventually partition to sediment in the reach. Thus, the river could have a current source or sources of PCBs, perhaps one or more outfalls near four sites. Additional investigation is needed to better define the relative significance of each outfall and areas in nearby drainage systems that may be contributing PCBs to outfalls and the river.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235030","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency and the U.S. Army Corps of Engineers","usgsCitation":"Scudder Eikenberry, B.C., Olds, H.T., Stefaniak, O.M., and Alvarez, D.A., 2023, PCB source assessment in the lower Clinton River, Clinton River Area of Concern, Mount Clemens, Michigan: U.S. Geological Survey Scientific Investigations Report 2023–5030, 37 p., https://doi.org/10.3133/sir20235030.","productDescription":"Report: viii, 37 p.; Data Release; Database","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-133016","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":500892,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115014.htm","linkFileType":{"id":5,"text":"html"}},{"id":419191,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235030/full"},{"id":419073,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5030/sir20235030.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023–5030"},{"id":419065,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M870XM","text":"USGS data release","linkHelpText":"Polychlorinated biphenyl (PCB) data from instream water and sediment passive samplers, stream bank sediment, and catch basin sediment in the Clinton River Area of Concern, Michigan, USA, 2019 (Under Revision)"},{"id":419066,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":419064,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5030/sir20235030.pdf","text":"Report","size":"4.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5030"},{"id":419072,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5030/images/"},{"id":419063,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5030/coverthb.jpg"}],"country":"United States","state":"Michigan","city":"Mount Clemens","otherGeospatial":"lower Clinton River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.87419476806319,\n 42.602\n ],\n [\n -82.87419476806319,\n 42.596\n ],\n [\n -82.86189203439089,\n 42.596\n ],\n [\n -82.86189203439089,\n 42.602\n ],\n [\n -82.87419476806319,\n 42.602\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
Gifford Pinchot Drive
Madison, WI 53726
Forest harvest is a primary landscape-scale management action affecting riparian forests. Although concerns about impacts of forest harvest on stream amphibians is generally limited to areas adjacent to harvest, there is a paucity of information regarding potential downstream effects of forest harvest on these species. We designed a before-after, control-impact (BACI) experiment to quantify potential impacts of clearcut logging that included 12-m buffers or smaller variable-width buffers on the distribution and abundance of headwater stream amphibians in adjacent and downstream areas. We sampled larval coastal tailed frogs (Ascaphus truei), coastal giant salamanders (Dicamptodon tenebrosus), and Columbia torrent salamanders (Rhyacotriton kezeri) across 3,915 sampling occasions that spanned 13 study reaches in 2008–2011 (pre-harvest) and 2013–2016 (post-harvest) as part of the Trask River Watershed Study in the Oregon Coast Range, U.S.A. We analyzed these data using occupancy models to estimate occupancy and (when possible) relative abundance, while accounting for various sources of imperfect detection. All species exhibited reduced occupancy adjacent to clearcuts with variable-width buffers (odds ratios [ORs] ranged = 0.24–0.48), and these negative impacts were not always diminished when increasing the buffer size to 12 m (ORs ranged = 0.20–3.56). Dicamptodon tenebrosus was the only species to have occupancy impacted in downstream areas, and this negative impact was related to clearcut logging with uniform 12-m buffers (OR = 0.60). This species was also the only species to have abundance negatively impacted by forest harvest in downstream areas (OR = 0.41 with uniform 12-m buffers, OR = 0.38 with variable-width buffers), albeit impacts to abundance were not evaluated for R. kezeri. Ascaphus truei abundance increased in areas downstream of clearcut logging with uniform 12-m buffers (OR = 2.92). Although we found the direction and magnitude of responses varied by species, our study confirms that clearcut logging can have negative impacts on amphibians that inhabit the adjacent stream areas. Perhaps more importantly, we also found that forest harvest can have negative effects on stream amphibians downstream of the harvested area and that increasing the buffer size to 12 m did not necessarily diminish these impacts in adjacent and downstream areas. Altogether, our study provides a nuanced picture of adjacent and downstream effects of forest harvest on three endemic headwater stream amphibians, and our findings demonstrate that forest management practices should consider downstream effects on aquatic taxa when assessing the impact of harvesting trees near headwater streams.
Animal movement is the mechanism connecting landscapes to fitness, and understanding variation in seasonal animal movements has benefited from the analysis and categorization of animal displacement. However, seasonal movement patterns can defy classification when movements are highly variable. Hidden Markov movement models (HMMs) are a class of latent-state models well-suited to modeling movement data. Here, we used HMMs to assess seasonal patterns of variation in the movement of pronghorn (Antilocapra americana), a species known for variable seasonal movements that challenge analytical approaches, while using a population of mule deer (Odocoileus hemionus), for whom seasonal movements are well-documented, as a comparison. We used population-level HMMs in a Bayesian framework to estimate a seasonal trend in the daily probability of transitioning between a short-distance local movement state and a long-distance movement state. The estimated seasonal patterns of movements in mule deer closely aligned with prior work based on indices of animal displacement: a short period of long-distance movements in the fall season and again in the spring, consistent with migrations to and from seasonal ranges. We found seasonal movement patterns for pronghorn were more variable, as a period of long-distance movements in the fall was followed by a winter period in which pronghorn were much more likely to further initiate and remain in a long-distance movement pattern compared with the movement patterns of mule deer. Overall, pronghorn were simply more likely to be in a long-distance movement pattern throughout the year. Hidden Markov movement models provide inference on seasonal movements similar to other methods, while providing a robust framework to understand movement patterns on shorter timescales and for more challenging movement patterns. Hidden Markov movement models can allow a rigorous assessment of the drivers of changes in movement patterns such as extreme weather events and land development, important for management and conservation.
Compressional-wave seismic velocity (velocity) and bulk density (density) data were compiled from published sources for rock suites and earth materials that are significant for geophysical modeling of the Mesoproterozoic Midcontinent Rift System in the Lake Superior region. The data include laboratory measurements of outcrop and drill core samples, seismic refraction studies, and a sonic log from a 1.5-kilometer-deep exploration well. Rock suites of the Midcontinent Rift System include basalts of the Mesoproterozoic Keweenawan Supergroup, Oronto Group sedimentary rocks (divided into arenaceous versus argillaceous units), and several sedimentary formations overlying the Oronto Group that have been correlated across the area. Intrusive units include diabase, gabbro, and felsic igneous rocks. Other geologic units important for geophysical modeling in the Lake Superior region include Archean crystalline crust, Paleoproterozoic metasedimentary and crystalline rocks, lower Mesoproterozoic sedimentary rocks, and Holocene to Pleistocene surficial deposits.
Empirical velocity-density relations for each rock suite were determined by comparing the compiled data to published relations, such as the Nafe-Drake curve, Gardner’s relation, and best-fit equations developed for different rock types from laboratory studies. Graphical representations of these velocity-density relations provide a way to easily understand how velocity and density differ between tectonic settings and by rock type. Overlaps in velocity and density ranges for different geologic units are significant and have especially important implications for geologic interpretation of seismic data. Important examples include similar velocities but differing densities for argillaceous Oronto Group versus units overlying the Oronto Group and arenaceous Oronto Group versus basalt of the Keweenawan Supergroup. Similar densities but differing velocities were found for diabase versus gabbro. In addition, expected velocity ranges by rock type show that high-velocity intervals (6.9–7.1 kilometers per second) interpreted as basalt in previous seismic-reflection studies more likely indicate diabase or gabbro, suggesting that these interpretations may warrant additional consideration.
Center Director, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, Mail Stop 973
Denver, CO 80225
The wildland–urban interface (WUI) is where buildings and wildland vegetation meet or intermingle. It is where human–environmental conflicts and risks can be concentrated, including the loss of houses and lives to wildfire, habitat loss and fragmentation and the spread of zoonotic diseases. However, a global analysis of the WUI has been lacking. Here, we present a global map of the 2020 WUI at 10 m resolution using a globally consistent and validated approach based on remote sensing-derived datasets of building area and wildland vegetation. We show that the WUI is a global phenomenon, identify many previously undocumented WUI hotspots and highlight the wide range of population density, land cover types and biomass levels in different parts of the global WUI. The WUI covers only 4.7% of the land surface but is home to nearly half its population (3.5 billion). The WUI is especially widespread in Europe (15% of the land area) and the temperate broadleaf and mixed forests biome (18%). Of all people living near 2003–2020 wildfires (0.4 billion), two thirds have their home in the WUI, most of them in Africa (150 million). Given that wildfire activity is predicted to increase because of climate change in many regions, there is a need to understand housing growth and vegetation patterns as drivers of WUI change.
","language":"English","publisher":"Springer","doi":"10.1038/s41586-023-06320-0","usgsCitation":"Schug, F., Bar-Massada, A., Carlson, A.R., Cox, H., Hawbaker, T., Helmers, D., Hostert, P., Kaim, D., Kasraee, N., Martinuzzi, S., Mockrin, M.H., Pfoch, K.A., and Radeloff, V., 2023, The global wildland-urban interface: Nature, v. 621, p. 94-99, https://doi.org/10.1038/s41586-023-06320-0.","productDescription":"18 p.","startPage":"94","endPage":"99","ipdsId":"IP-147006","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":442714,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41586-023-06320-0","text":"Publisher Index Page"},{"id":421684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Earth","volume":"621","noUsgsAuthors":false,"publicationDate":"2023-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Schug, F.","contributorId":330629,"corporation":false,"usgs":false,"family":"Schug","given":"F.","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":885469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bar-Massada, Avi","contributorId":176995,"corporation":false,"usgs":false,"family":"Bar-Massada","given":"Avi","affiliations":[],"preferred":false,"id":885470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlson, Amanda Renee 0000-0002-0450-2636","orcid":"https://orcid.org/0000-0002-0450-2636","contributorId":303685,"corporation":false,"usgs":true,"family":"Carlson","given":"Amanda","email":"","middleInitial":"Renee","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":885471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cox, H.","contributorId":330630,"corporation":false,"usgs":false,"family":"Cox","given":"H.","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":885472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":885473,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Helmers, D.","contributorId":211616,"corporation":false,"usgs":false,"family":"Helmers","given":"D.","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":885474,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hostert, Patrick","contributorId":294426,"corporation":false,"usgs":false,"family":"Hostert","given":"Patrick","affiliations":[{"id":63572,"text":"Humboldt University of Berlin","active":true,"usgs":false}],"preferred":false,"id":885475,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kaim, D.","contributorId":330634,"corporation":false,"usgs":false,"family":"Kaim","given":"D.","email":"","affiliations":[{"id":78943,"text":"Jagiellonian University","active":true,"usgs":false}],"preferred":false,"id":885476,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kasraee, Neda K.","contributorId":330635,"corporation":false,"usgs":false,"family":"Kasraee","given":"Neda K.","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":885477,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Martinuzzi, S.","contributorId":211621,"corporation":false,"usgs":false,"family":"Martinuzzi","given":"S.","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":885478,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mockrin, Miranda H.","contributorId":296768,"corporation":false,"usgs":false,"family":"Mockrin","given":"Miranda","email":"","middleInitial":"H.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":885479,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Pfoch, Kira A.","contributorId":330637,"corporation":false,"usgs":false,"family":"Pfoch","given":"Kira","email":"","middleInitial":"A.","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":885480,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Radeloff, Volker C.","contributorId":296767,"corporation":false,"usgs":false,"family":"Radeloff","given":"Volker C.","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":885481,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70246879,"text":"ofr20231050 - 2023 - ECCOE Landsat quarterly Calibration and Validation report—Quarter 1, 2023","interactions":[],"lastModifiedDate":"2023-07-20T13:40:55.659896","indexId":"ofr20231050","displayToPublicDate":"2023-07-19T08:10:12","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1050","displayTitle":"ECCOE Landsat Quarterly Calibration and Validation Report—Quarter 1, 2023","title":"ECCOE Landsat quarterly Calibration and Validation report—Quarter 1, 2023","docAbstract":"The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level.
This report provides observed geometric and radiometric analysis results for Landsats 7–8 for quarter 1 (January–March) of 2023. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov.
One specific activity that the ECCOE Landsat Cal/Val Team closely monitored was a Landsat 8 safehold anomaly. On January 26, 2023, the Global Positioning System (GPS) onboard Landsat 8 became invalid because the GPS fault tripped. Later that same day, the GPS was reinitialized, but a Field of View 1 fault trip occurred early the next morning, causing the observatory to go into Earth Point Safe mode, which put the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) into safehold. Once it was safe to reactivate the sensors, the OLI was transitioned to operational status late on January 27 and TIRS was reactivated early on January 28. Additional information about the Landsat 8 safehold anomaly is here: https://www.usgs.gov/landsat-missions/news/landsat-8-recovers-safehold.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231050","usgsCitation":"Haque, M.O., Rengarajan, R., Lubke, M., Hasan, M.N., Shrestha, A., Tuli, F.T.Z., Shaw, J.L., Denevan, A., Franks, S., Micijevic, E., Choate, M.J., Anderson, C., Thome, K., Kaita, E., Barsi, J., Levy, R., and Miller, J., 2023, ECCOE Landsat quarterly Calibration and Validation report—Quarter 1, 2023: U.S. Geological Survey Open-File Report 2023–1050, 39 p., https://doi.org/10.3133/ofr20231050.","productDescription":"Report: vii, 39 p.; Dataset","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-152817","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":419162,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov","text":"USGS database","linkHelpText":"—EarthExplorer"},{"id":419161,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1050/images/"},{"id":419158,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1050/coverthb.jpg"},{"id":419181,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231050/full"},{"id":419160,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1050/ofr20231050.XML"},{"id":419159,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1050/ofr20231050.pdf","text":"Report","size":"4.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1050"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
River turbulence is spatially variable due to interactions between morphology of rivers and physical mechanics of flowing water. Understanding the variation of turbulence in rivers is important for characterizing transport processes of soluble and particulate materials in these systems. We present an exploratory effort to understand ecologically relevant flow patterns using measurements of mean flow and turbulence in a highly engineered river channel around an island in the lower Missouri River. Specifically, the profiles of mean river velocities were investigated to examine the logarithmic relation and associated parameters, including shear velocity and bed roughness. Turbulence intensity and Reynolds shear stress were compared with classic open-channel profiles and previously reported river data in the hydraulics literature. With the capability of pulse-to-pulse coherent Doppler velocity profiling in high spatial resolution, we estimated the profiles of turbulence dissipation rate using resolved one-dimensional velocity spectra. These measurement data allow us to examine the validity of turbulence production-dissipation balance and the classic open-channel profiles of turbulence statistics, including turbulence intensity, Reynolds shear stress, dissipation rate, and eddy viscosity. The field data show a strong variation of turbulence profiles in close vicinity of the river island. In shallow water depths close to the island, turbulence is substantially enhanced in comparison with classic open-channel profiles. Such turbulence enhancement is likely attributed to non-uniformity of the flow structures.
New geophysical profiles across the central Dead Sea Transform (DST) near the Sea of Galilee, Israel, and surrounding highlands, augmented by static stress modeling, allow us to study continental transform plate deformation. The DST separates a ∼10 km thick sedimentary column above a thinned (16–23 km) crust to the west from a ∼7 km column above a ∼30-km thick crust to the east. Crustal thinning starts under the DST, as observed also farther south, indicating that the DST is indeed located along the boundary between the Arabian plate and its continental margin. Moho step here is gradual. The DST's eastern shoulder dips westward toward the DST unlike the upward flexed shoulder observed farther south, perhaps delineating the northern limit of a thinner and hotter lithosphere. The shape of the Sea of Galilee is modeled as an asymmetric pull-apart basin formed by a left-lateral stepover of 2.6 km between slightly divergent and underlapping strike-slip fault strands dipping 70° to the west. Reflection data indicate that these strands are not connected. Several fault traces within the Sea of Galilee have previously been suggested to carry part of the relative plate motion. However, given slip along the main DST faults, Coulomb stress will increase only on fault portions in the northern part of the lake, in accord with the geographical distribution of seismicity, suggesting that these faults are likely secondary. Mismatch between the DST strand locations in the geophysical profiles and the subsidence model, may reflect temporal changes in fault geometry.