No abstract available.
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To mitigate some of these losses in Oklahoma, Paddlefish have been stocked into reservoirs throughout the state, with variable success in establishing self-sustaining populations. Two factors thought to contribute to success of Paddlefish stocking are spawning substrate and prey availability, which were quantified in six reservoirs and nine reservoir tributaries. Side-scan sonar and supervised classification of aerial imagery were used to classify 4517-ha of river substrate upstream of the river-reservoir interface in reservoir tributaries. Zooplankton community structure, water clarity, and nutrient availability were also assessed in the same reservoirs and tributaries. One tributary had suitable spawning substrate (>40%), and the rest had minimal (<1.5%), which suggested that availability of suitable spawning substrate was not directly correlated with Paddlefish stocking success. Reservoirs with self-sustaining Paddlefish populations had higher abundance of large zooplankton (copepods and cladocerans) than reservoirs without a reproducing population. Notably, tributaries associated with Lake Texoma, the one known example of failed restoration, were much more turbid than other rivers. We conclude that abiotic factors such as water clarity may contribute more to variable recruitment than spawning substrate or zooplankton abundance by mediating foraging success of Paddlefish post-larvae.
","language":"English","publisher":"Wiley","doi":"10.1111/fme.12677","usgsCitation":"Gary, R.A., Long, J.M., Eachus, B.T., Dzialowski, A., and Schooley, J.D., 2024, Factors associated with Paddlefish (Polyodon spathula) restoration success in Oklahoma: Fisheries Management and Ecology, v. 31, no. 2, e12677, 10 p., https://doi.org/10.1111/fme.12677.","productDescription":"e12677, 10 p.","ipdsId":"IP-155693","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":498059,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/fme.12677","text":"Publisher Index Page"},{"id":432291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"31","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Gary, Ryan A.","contributorId":340752,"corporation":false,"usgs":false,"family":"Gary","given":"Ryan","email":"","middleInitial":"A.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907515,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eachus, Brian T.","contributorId":340753,"corporation":false,"usgs":false,"family":"Eachus","given":"Brian","email":"","middleInitial":"T.","affiliations":[{"id":81660,"text":"Oklahoma State Universtiy","active":true,"usgs":false}],"preferred":false,"id":907516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dzialowski, Andrew R.","contributorId":340754,"corporation":false,"usgs":false,"family":"Dzialowski","given":"Andrew R.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907517,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schooley, Jason D.","contributorId":340755,"corporation":false,"usgs":false,"family":"Schooley","given":"Jason","email":"","middleInitial":"D.","affiliations":[{"id":27443,"text":"Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":907518,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261323,"text":"70261323 - 2024 - Improving how science informs policy within the Ecosystem Approach","interactions":[],"lastModifiedDate":"2026-02-12T17:34:19.139008","indexId":"70261323","displayToPublicDate":"2024-04-01T10:50:21","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":865,"text":"Aquatic Ecosystem Health & Management","active":true,"publicationSubtype":{"id":10}},"title":"Improving how science informs policy within the Ecosystem Approach","docAbstract":"Science is fundamental to sound policies, particularly when it comes to implementing an Ecosystem Approach. Science can and should inform nearly all facets of an Ecosystem Approach, yet challenges remain to realizing this goal. To help identify and better understand these challenges we used a qualitative comparative case study approach to identify and characterize the challenges and successes of implementing a science-driven Ecosystem Approach in the Laurentian Great Lakes. These case studies include delisting of Areas of Concern, improving coastal resilience, and addressing declining offshore lake productivity. These case studies were selected because they provide a set of very different, yet complementary, cases for assessing implementation, as well as the factors influencing the science-policy exchange. Through this comparative study, we identified a diverse set of challenges and successes, that were both systemic and case specific. Emerging from this comparative assessment were principles and enabling conditions (e.g. scale, governance, shared goals) we believe are critical to consider when establishing or improving a science-driven Ecosystem Approach.
","language":"English","publisher":"Michigan State University Press","doi":"10.14321/aehm.027.02.27","usgsCitation":"Williams, K., Sowa, S.P., Child, M., Gaden, M., Anderson, J., Bunnell, D.B., Drca, P., Knight, R.L., Norton, R., and Taylor, R., 2024, Improving how science informs policy within the Ecosystem Approach: Aquatic Ecosystem Health & Management, v. 27, no. 2, p. 27-48, https://doi.org/10.14321/aehm.027.02.27.","productDescription":"22 p.","startPage":"27","endPage":"48","ipdsId":"IP-152920","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":499816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-04-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, Kathleen","contributorId":346955,"corporation":false,"usgs":false,"family":"Williams","given":"Kathleen","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":920374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sowa, Scott P. 0000-0002-5425-2591 sowasp@missouri.edu","orcid":"https://orcid.org/0000-0002-5425-2591","contributorId":146672,"corporation":false,"usgs":false,"family":"Sowa","given":"Scott","email":"sowasp@missouri.edu","middleInitial":"P.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":920375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Child, Matthew","contributorId":346956,"corporation":false,"usgs":false,"family":"Child","given":"Matthew","affiliations":[{"id":38322,"text":"International Joint Commission","active":true,"usgs":false}],"preferred":false,"id":920376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gaden, Marc","contributorId":346957,"corporation":false,"usgs":false,"family":"Gaden","given":"Marc","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":920377,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Janette","contributorId":346958,"corporation":false,"usgs":false,"family":"Anderson","given":"Janette","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":920378,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bunnell, David B. 0000-0003-3521-7747 dbunnell@usgs.gov","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":195888,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","email":"dbunnell@usgs.gov","middleInitial":"B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":920379,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Drca, Paul","contributorId":346959,"corporation":false,"usgs":false,"family":"Drca","given":"Paul","affiliations":[{"id":39523,"text":"Essex Region Conservation Authority","active":true,"usgs":false}],"preferred":false,"id":920380,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Knight, Roger L.","contributorId":81049,"corporation":false,"usgs":true,"family":"Knight","given":"Roger","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":920381,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Norton, Richard","contributorId":346960,"corporation":false,"usgs":false,"family":"Norton","given":"Richard","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":920382,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Taylor, Rachael","contributorId":346961,"corporation":false,"usgs":false,"family":"Taylor","given":"Rachael","affiliations":[{"id":83025,"text":"CSS Inc.","active":true,"usgs":false}],"preferred":false,"id":920383,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70262564,"text":"70262564 - 2024 - The Ecosystem Approach in the 21st century: Guiding science and management – A synthesis","interactions":[],"lastModifiedDate":"2025-01-21T16:46:28.837065","indexId":"70262564","displayToPublicDate":"2024-04-01T10:44:07","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":865,"text":"Aquatic Ecosystem Health & Management","active":true,"publicationSubtype":{"id":10}},"title":"The Ecosystem Approach in the 21st century: Guiding science and management – A synthesis","docAbstract":"Maintaining the integrity and health of aquatic ecosystems is critical to sustaining the many valued services that they provide society. Unfortunately, achieving this goal has proven challenging in most of the world's large ecosystems owing to rampant environmental change caused by human-driven stress, including accelerating climate change, pollution of waterways, habitat modification and destruction, and the continued spread of non-native species (He and Silliman, 2019; Jenny et al., 2020; Smith et al., 2015; Steffen et al., 2007). These stressors, which can also include purposeful management actions (e.g. nutrient and fisheries management), are presenting a grave challenge globally to efforts aimed at securing a sustainable future for nature, society, and the economy.
","language":"English","publisher":"Scholarly Publishing Collective","doi":"10.14321/aehm.027.02.108","usgsCitation":"Ludsin, S., Carlson, A.K., Duncan, A., Febria, C., Hartig, J., Kellogg, W., Minns, C., Munawar, M., Nolan, S., Van der Knaap, M., Verhamme, E., and Williams, K., 2024, The Ecosystem Approach in the 21st century: Guiding science and management – A synthesis: Aquatic Ecosystem Health & Management, v. 27, no. 2, p. 108-116, https://doi.org/10.14321/aehm.027.02.108.","productDescription":"9 p.","startPage":"108","endPage":"116","ipdsId":"IP-163794","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":500797,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12927115/","text":"External Repository"},{"id":480834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-04-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Ludsin, S.A.","contributorId":349662,"corporation":false,"usgs":false,"family":"Ludsin","given":"S.A.","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":924550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Andrew Kenneth 0000-0002-6681-0853","orcid":"https://orcid.org/0000-0002-6681-0853","contributorId":340581,"corporation":false,"usgs":true,"family":"Carlson","given":"Andrew","email":"","middleInitial":"Kenneth","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":924551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duncan, A.T.","contributorId":349726,"corporation":false,"usgs":false,"family":"Duncan","given":"A.T.","affiliations":[],"preferred":false,"id":924667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Febria, C.M.","contributorId":349665,"corporation":false,"usgs":false,"family":"Febria","given":"C.M.","affiliations":[{"id":83499,"text":"Traditional Territories of the Three Fires Confederacy of First Nations – Ojibway, Odawa and Potawatomi","active":true,"usgs":false}],"preferred":false,"id":924552,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartig, J.H.","contributorId":349666,"corporation":false,"usgs":false,"family":"Hartig","given":"J.H.","affiliations":[{"id":48871,"text":"University of Windsor","active":true,"usgs":false}],"preferred":false,"id":924553,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kellogg, W.A.","contributorId":349667,"corporation":false,"usgs":false,"family":"Kellogg","given":"W.A.","affiliations":[{"id":18143,"text":"Cleveland State University","active":true,"usgs":false}],"preferred":false,"id":924554,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Minns, C.K.","contributorId":349668,"corporation":false,"usgs":false,"family":"Minns","given":"C.K.","affiliations":[{"id":7044,"text":"University of Toronto","active":true,"usgs":false}],"preferred":false,"id":924555,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Munawar, M.","contributorId":349669,"corporation":false,"usgs":false,"family":"Munawar","given":"M.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":924556,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nolan, S.","contributorId":349670,"corporation":false,"usgs":false,"family":"Nolan","given":"S.","affiliations":[{"id":48871,"text":"University of Windsor","active":true,"usgs":false}],"preferred":false,"id":924557,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Van der Knaap, M.","contributorId":349671,"corporation":false,"usgs":false,"family":"Van der Knaap","given":"M.","affiliations":[{"id":83502,"text":"University of Liège","active":true,"usgs":false}],"preferred":false,"id":924558,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Verhamme, E.M.","contributorId":349672,"corporation":false,"usgs":false,"family":"Verhamme","given":"E.M.","affiliations":[{"id":83503,"text":"LimnoTech, Inc.","active":true,"usgs":false}],"preferred":false,"id":924559,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Williams, K.C.","contributorId":349673,"corporation":false,"usgs":false,"family":"Williams","given":"K.C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":924560,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70252753,"text":"70252753 - 2024 - Fishes move to transient local refuges, not persistent landscape refuges during river drying experiment","interactions":[],"lastModifiedDate":"2024-06-03T14:57:50.547672","indexId":"70252753","displayToPublicDate":"2024-04-01T10:43:10","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Fishes move to transient local refuges, not persistent landscape refuges during river drying experiment","docAbstract":"Summer Lake is located in south-central Oregon at the extreme northwestern extent of the Basin and Range Province, bordered by the Cascade Volcanic Province to the west and the High Lava Plains to the north. The valley hosts numerous hot springs and a small geothermal powerplant at the southeastern end of the valley in the town of Paisley. This tectonically active region has undergone significant ENE-directed extension producing highly faulted terrain with fault blocks tilting on average 60° from the maximum extension direction. Local geology consists of young volcanics which have been extensively dissected by predominantly NNW-trending normal faults. These same structures likely extend through the basin but are concealed by young basin fill sediments and volcanics. As a result, potential field geophysical methods are ideally suited for characterizing subsurface geology and structures in this region which are important for understanding basin evolution and tectonics within the valley. New ground-based gravity and magnetic data, as well as sUAS- (small uncrewed aerial systems) based magnetic data reveal a prevalent NNW-trending fabric beneath the basin fill in southern Summer Lake valley that likely plays an important role in controlling the flow of subsurface hydrothermal fluids. Additionally, measurements were performed on outcrops, hand samples and paleomagnetic cores to constrain the physical properties (density, magnetic susceptibility and magnetic remanence) of local geology. Together, these data help resolve basin geometry and delineate concealed faults and contacts, informing our understanding of the structural framework and geothermal resource potential of southern Summer Lake valley.
","conferenceTitle":"49th Workshop on Geothermal Reservoir Engineering","conferenceDate":"February 12-14, 2024","conferenceLocation":"Stanford, CA","language":"English","publisher":"Stanford University","usgsCitation":"Earney, T.E., and Glen, J.M., 2024, Characterizing structure in southern Summer Lake valley, Oregon using ground- and sUAS-based potential field geophysics, 49th Workshop on Geothermal Reservoir Engineering, Stanford, CA, February 12-14, 2024, 16 p.","productDescription":"16 p.","ipdsId":"IP-161623","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":432320,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pangea.stanford.edu/ERE/db/IGAstandard/record_detail.php?id=36321","linkFileType":{"id":5,"text":"html"}},{"id":432336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Summer Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.96741614462996,\n 43.12495779691321\n ],\n [\n -120.96741614462996,\n 42.57546720866469\n ],\n [\n -120.36914716752312,\n 42.57546720866469\n ],\n [\n -120.36914716752312,\n 43.12495779691321\n ],\n [\n -120.96741614462996,\n 43.12495779691321\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Earney, Tait E. 0000-0002-1504-0457","orcid":"https://orcid.org/0000-0002-1504-0457","contributorId":210080,"corporation":false,"usgs":true,"family":"Earney","given":"Tait","email":"","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":909204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":909205,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70251772,"text":"70251772 - 2024 - Serologic survey of selected arthropod-borne pathogens in free-ranging snowshoe hares (Lepus americanus) captured in Northern Michigan, USA","interactions":[],"lastModifiedDate":"2024-09-11T16:04:50.972326","indexId":"70251772","displayToPublicDate":"2024-04-01T08:57:40","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Serologic survey of selected arthropod-borne pathogens in free-ranging snowshoe hares (Lepus americanus) captured in Northern Michigan, USA","docAbstract":"Snowshoe hares (Lepus americanus) in the Upper Peninsula (UP) of Michigan, USA, occupy the southern periphery of the species' range and are vulnerable to climate change. In the eastern UP, hares are isolated by the Great Lakes, potentially exacerbating exposure to climate-change-induced habitat alterations. Climate change is also measurably affecting distribution and prevalence of vector-borne pathogens in North America, and increases in disease occurrence and prevalence can be one signal of climate-stressed wildlife populations. We conducted a serosurvey for vector-borne pathogens in snowshoe hares that were captured in the Hiawatha National Forest in the eastern UP of Michigan, USA, 2016-2017. The most commonly detected antibody response was to the mosquito-borne California serogroup snowshoe hare virus (SSHV). Overall, 24 (51%) hares screened positive for SSHV antibodies and of these, 23 (96%) were confirmed positive by plaque reduction neutralization test. We found a positive association between seroprevalence of SSHV and live weight of snowshoe hares. Additionally, we detected a significant effect of ecological land type group on seroprevalence of SSHV, with strong positive support for a group representing areas that tend to support high numbers of hares (i.e., acidic mineral containing soils with cedar, mixed swamp conifers, tamarack and balsam fir as common overstory vegetation). We also detected and confirmed antibodies for Jamestown Canyon virus and Silverwater virus in a single hare each. We did not detect antibodies to other zoonotic vector-borne pathogens, including Lacrosse encephalitis virus, West Nile virus, Borrelia burgdorferi, Powassan virus, and Francisella tularensis. These results provide a baseline for future serological studies of vector-transmitted diseases that may increase climate vulnerability of snowshoe hares in the UP of Michigan, as well as pose a climate-related zoonotic risk.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/JWD-D-23-00009","usgsCitation":"Hofmeister, E.K., Clark, E., Lund, M., and Grear, D.A., 2024, Serologic survey of selected arthropod-borne pathogens in free-ranging snowshoe hares (Lepus americanus) captured in Northern Michigan, USA: Journal of Wildlife Diseases, v. 60, no. 2, p. 375-387, https://doi.org/10.7589/JWD-D-23-00009.","productDescription":"13 p.","startPage":"375","endPage":"387","ipdsId":"IP-137598","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":426054,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Hiawatha National Forest, Upper Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.12495684063921,\n 46.50986311167162\n ],\n [\n -85.11801650695072,\n 46.02046787491247\n ],\n [\n -84.89592582891105,\n 45.92035440284381\n ],\n [\n -84.71721223642521,\n 45.93302539211934\n ],\n [\n -84.62872298189352,\n 45.993959465281165\n ],\n [\n -84.5940213134503,\n 46.488365359475324\n ],\n [\n -85.12495684063921,\n 46.50986311167162\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"60","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hofmeister, Erik K. 0000-0002-2305-519X ehofmeister@usgs.gov","orcid":"https://orcid.org/0000-0002-2305-519X","contributorId":269350,"corporation":false,"usgs":true,"family":"Hofmeister","given":"Erik","email":"ehofmeister@usgs.gov","middleInitial":"K.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":895506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Eric","contributorId":333599,"corporation":false,"usgs":false,"family":"Clark","given":"Eric","email":"","affiliations":[{"id":79941,"text":"Inland Fish and Wildlife Department of the Sault Ste. Marie Tribe of Chippewa Indians, 523 Ashmun St.","active":true,"usgs":false}],"preferred":false,"id":895509,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lund, Melissa 0000-0003-4577-2015","orcid":"https://orcid.org/0000-0003-4577-2015","contributorId":333600,"corporation":false,"usgs":false,"family":"Lund","given":"Melissa","affiliations":[{"id":79942,"text":"NWHC","active":true,"usgs":false}],"preferred":false,"id":895507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":895508,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70252666,"text":"70252666 - 2024 - A Robot Operating System (ROS) package for mapping flow fields in rivers via Particle Image Velocimetry (PIV)","interactions":[],"lastModifiedDate":"2024-04-03T13:47:52.663272","indexId":"70252666","displayToPublicDate":"2024-04-01T08:45:21","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17446,"text":"Software X","active":true,"publicationSubtype":{"id":10}},"title":"A Robot Operating System (ROS) package for mapping flow fields in rivers via Particle Image Velocimetry (PIV)","docAbstract":"Non-contact, remote sensing approaches to measuring flow velocities in river channels are widely used, but typical workflows involve acquiring images in the field and then processing data later in the office. To reduce latency between acquisition and output, with the ultimate goal of enabling real-time image velocimetry, we developed a Robot Operating System (ROS) package for Particle Image Velocimetry (PIV) that can be deployed on an embedded computer aboard an uncrewed aircraft system (UAS). The ROSPIV package consists of a series of nodes that can be run in parallel and comprise an end-to-end PIV workflow. Software development involved converting MATLAB code to C++, organizing files within a catkin workspace, and building nodes using catkin_make. The codebase is available via a repository that includes a user’s guide and demo script. This paper describes the nodes in the ROSPIV package as well as functions for preparing inputs, facilitating code generation, and visualizing PIV output. To illustrate the application of the software, we present two examples, one based on a simulated image sequence and the other based on data acquired from a UAS. For the simulated data, the velocity field derived via the ROSPIV package closely matched the known flow field used to generate the image sequence. Using real data as input demonstrated the ability of the ROSPIV package to ingest and pre-process raw images. Our initial results suggest that the ROSPIV package could become a viable approach for mapping river surface velocities in real time.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.softx.2024.101711","usgsCitation":"Legleiter, C.J., and Dille, M., 2024, A Robot Operating System (ROS) package for mapping flow fields in rivers via Particle Image Velocimetry (PIV): Software X, v. 26, 101711, 7 p., https://doi.org/10.1016/j.softx.2024.101711.","productDescription":"101711, 7 p.","ipdsId":"IP-157370","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":439989,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.softx.2024.101711","text":"Publisher Index Page"},{"id":435001,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96BQQQ6","text":"USGS data release","linkHelpText":"Remotely sensed data from a reach of the Sacramento River near Glenn, California, used to perform Particle Image Velocimetry (PIV) within the Robot Operating System (ROS)"},{"id":427352,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":897859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dille, Michael","contributorId":331596,"corporation":false,"usgs":false,"family":"Dille","given":"Michael","email":"","affiliations":[{"id":79249,"text":"NASA Ames Research Center Intelligent Robotics Group","active":true,"usgs":false}],"preferred":false,"id":897860,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70255026,"text":"70255026 - 2024 - Estimating migration timing and abundance in partial migratory systems by integrating continuous antenna detections with physical captures","interactions":[],"lastModifiedDate":"2024-07-15T15:13:06.675879","indexId":"70255026","displayToPublicDate":"2024-04-01T08:31:53","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating migration timing and abundance in partial migratory systems by integrating continuous antenna detections with physical captures","docAbstract":"Surface-water supplies are important sources of drinking water for residents in the Triangle area of North Carolina, which is located within the upper Cape Fear and Neuse River Basins. Since 1988, the U.S. Geological Survey and a consortium of local governments have participated in a cooperative effort, known as the Triangle Area Water Supply Monitoring Project, to track water-quality and quantity conditions in several of the area’s water-supply reservoirs and streams. This report summarizes the hydrologic and water-quality monitoring activities through this cooperative effort, including an overview of previous and current data collection and quality-assurance and quality-control activities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241003","issn":"2331-1258","collaboration":"Prepared in cooperation with the Triangle Area Water Supply Monitoring Project Steering Committee","usgsCitation":"Diaz, J.C., and Fanelli, R.M., 2024, Triangle Area Water Supply Monitoring Project, North Carolina—Overview of hydrologic and water-quality monitoring activities and data quality assurance: U.S. Geological Survey Open-File Report 2024–1003, 8 p., https://doi.org/10.3133/ofr20241003.","productDescription":"Report: vi, 8 p.; Data Release","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-140656","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":499203,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116211.htm","linkFileType":{"id":5,"text":"html"}},{"id":426743,"rank":1,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1003/images"},{"id":426744,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1003/coverthb.jpg"},{"id":426745,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1003/ofr20241003.pdf","size":"1.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1003"},{"id":426747,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1003/ofr20241003.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2024-1003 XML"},{"id":426746,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241003/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1003 HTML"},{"id":426748,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MU5BAZ","text":"USGS Data Release","linkHelpText":"Associated data for the Triangle Area Water Supply Monitoring Project, North Carolina, October 2019–September 2022"}],"country":"United States","state":"North Carolina","otherGeospatial":"Triangle area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.65,\n 36.25\n ],\n [\n -79.375,\n 36.25\n ],\n [\n -79.375,\n 35.5\n ],\n [\n -78.65,\n 35.5\n ],\n [\n -78.65,\n 36.25\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, Suite 500
Norcross, GA 30093
Prior to 2014, local utilities and State agencies monitored for cyanotoxins and taste-and-odor (T&O) compounds and reported occasional detections in three water-supply reservoirs in Wake County, North Carolina. Comparable data for cyanotoxins and T&O compounds were lacking for other water-supply reservoirs in the Triangle area of North Carolina. This report assesses whether cyanotoxins and T&O compounds occurred in four previously unmonitored North Carolina Triangle area water-supply reservoirs at levels that exceed existing North Carolina and U.S. Environmental Protection Agency recreational and drinking water health advisory, guidance, and criterion levels based on data collected during the peak phytoplankton growth period in 2014. Samples were collected from five sites across the study reservoirs (Cane Creek Reservoir, West Fork Eno River Reservoir, B. Everett Jordan Lake, and University Lake) between April and October 2014 and analyzed for physical characteristics, chemical constituents, phytoplankton communities, cyanotoxins, and T&O compounds.
Lake stratification during the sampling period in 2014 could indicate that the deep zones of the water column, during stratified anoxic conditions, may serve as possible sources of nutrients and metals for algal growth and other biogeochemical processes. Differences in phytoplankton communities were attributed to variability in environmental conditions across the sites and sampling events. Differences generally were greater among sites than among sampling events for phytoplankton communities and environmental conditions.
Phytoplankton community assemblages, within reservoirs, often were dominated by cyanobacteria that contained genera capable of producing T&O compounds and cyanotoxins during summer and fall months. The occurrence and associated biovolumes of potential producers of cyanotoxins and T&O compounds varied across the sites and sampling events. Of 20 samples collected during the study, the T&O compound geosmin and the cyanotoxin microcystin were present in 19 and 18 samples, respectively. While not harmful, the aesthetically displeasing geosmin concentrations periodically exceeded the human detection threshold of 15 nanograms per liter at most sites. The T&O compound 2-methylisoborneol (MIB) was detected in 11 of 20 samples, with concentrations below the human detection threshold of 15 nanograms per liter in all but one sample. The cyanotoxin anatoxin-a was detected in two of the samples. No other cyanotoxins were detected during the study.
In general, results did not indicate the biovolume of any given phytoplankton genera in the study was correlated with increased concentrations of MIB, geosmin, or microcystin. Results from this study indicated that microcystin concentrations in the water-supply reservoirs in the Triangle area were below EPA-recommended recreational level of 8 micrograms per liter, but periodically exceeded the EPA finished-water 10-day health advisory level of 0.3 microgram per liter for bottle-fed infants and preschool-age children. This suggests longer term data collection may be necessary to better understand the magnitude and frequency of cyanotoxin concentrations in these four water-supply reservoirs, particularly those with an elevated risk of exceeding the EPA 10-day health advisory levels in the finished drinking water or those with a higher frequency of T&O compound occurrence.
Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, Suite 500
Norcross, GA 30093
Exotic annual grass invasion is a widespread threat to the integrity of sagebrush ecosystems in Western North America. Although many predictors of annual grass prevalence and native perennial vegetation have been identified, there remains substantial uncertainty about how regional-scale and local-scale predictors interact to determine vegetation heterogeneity, and how associations between vegetation and cattle grazing vary with environmental context. Here, we conducted a regionally extensive, one-season field survey across burned and unburned, grazed, public lands in Oregon and Idaho, with plots stratified by aspect and distance to water within pastures to capture variation in environmental context and grazing intensity. We analyzed regional-scale and local-scale patterns of annual grass, perennial grass, and shrub cover, and examined to what extent plot-level variation was contingent on pasture-level predictions of site favorability. Annual grasses were widespread at burned and unburned sites alike, contrary to assumptions of annual grasses depending on fire, and more common at lower elevations and higher temperatures regionally, as well as on warmer slopes locally. Pasture-level grazing pressure interacted with temperature such that annual grass cover was associated positively with grazing pressure at higher temperatures but associated negatively with grazing pressure at lower temperatures. This suggests that pasture-level temperature and grazing relationships with annual grass abundance are complex and context dependent, although the causality of this relationship deserves further examination. At the plot-level within pastures, annual grass cover did not vary with grazing metrics, but perennial cover did; perennial grasses, for example, had lower cover closer to water sources, but higher cover at higher dung counts within a pasture, suggesting contrasting interpretations of these two grazing proxies. Importantly for predictions of ecosystem response to temperature change, we found that pasture-level and plot-level favorability interacted: perennial grasses had a higher plot-level cover on cooler slopes, and this difference across topography was starkest in pastures that were less favorable for perennial grasses regionally. Understanding the mechanisms behind cross-scale interactions and contingent responses of vegetation to grazing in these increasingly invaded ecosystems will be critical to land management in a changing world.
This paper describes development of a nitrate decision support tool for groundwater wells (GW-NDST) that combines nitrate leaching and groundwater lag-times to compute well concentrations. The GW-NDST uses output from support models that simulate leached nitrate, groundwater age distributions, and nitrate reduction rates. The support models are linked through convolution to simulate nitrate transport to wells. Spatially distributed parameters were adjusted through calibration to 34,255 nitrate sample targets. Prediction uncertainty is illustrated via Monte Carlo realizations informed during calibration. Over 78% of target concentrations were within the simulated range of results from 450 realizations. An example forecasting scenario illustrates that a range of feasible outcomes exist and should be considered when interpreting forecasts for decision making. Uncertainty in forecasting is unavoidable; the intent of characterizing uncertainty in the GW-NDST is to facilitate decision making by increasing insight into the response of nitrate contamination to physical and chemical processes.
Predicting the potential distribution of a non-native species can assist management efforts to mitigate impacts on recipient ecosystems. However, such predictions are lacking for marine species, such as the non-native regal demoiselle, Neopomacentrus cyanomos, that is currently expanding its distribution in the western Atlantic. We used correlative species distribution models with three common algorithms to predict suitable habitat for N. cyanomos in the region. We compared models developed using native, non-native, and global occurrences to differentiate drivers across separate ranges using a suite of 12 environmental characteristics. While final models included an ensemble of variables, the majority ranked the combined effect of temperature variables as a key predictor correlated with the distribution of N. cyanomos. Habitat suitability increased as water temperatures increased beyond 16 °C and where annual thermal ranges were greater than 10 °C at the shallowest depth with substrate within a study cell (~ 9.2 km2 resolution). Habitat suitability also increased where maximum surface temperatures were greater than 27 °C. In the non-native range, the proportion of reef available in each cell was another important variable increasing the suitable habitat for N. cyanomos. Our models predicted high habitat suitability for N. cyanomos throughout the Greater Caribbean, in higher latitudes along North and South American Atlantic coasts, in the eastern Pacific Ocean, and highlights key areas where managers can monitor and target potential removal efforts. The distribution of this non-native species is likely to continue expanding throughout the region with little known about potential implications on native communities.
Fall bottom trawl (fall BT) and lakewide acoustic (AC) surveys are conducted annually to generate indices of pelagic and benthic prey fish densities in Lake Michigan. The fall BT survey has been conducted each fall since 1973 using 12-m trawls at depths ranging from 9 to 110 m at fixed locations distributed across seven transects; this survey estimates densities of seven prey fish species [i.e., Alewife (Alosa pseudoharengus), Bloater (Coregonus hoyi), Rainbow Smelt (Osmerus mordax), Deepwater Sculpin (Myoxocephalus thompsonii), Slimy Sculpin (Cottus cognatus), Round Goby (Neogobius melanostomus), Ninespine Stickleback (Pungitius pungitius)] as well as age-0 Yellow Perch (Perca flavescens) and large (> 350 mm) Burbot (Lota lota). The AC survey has been conducted each late summer/early fall since 2004, and the 2023 survey consisted of 20 transects [450 km total (336 miles)] covering bottom depths ranging from 12 to 248 m and 29 midwater trawl tows above bottom depths ranging 16 to 246 m; this survey estimates densities of three prey fish species (i.e., Alewife, Bloater, and Rainbow Smelt). The data generated from these surveys are used to estimate various population parameters that are, in turn, used by state and tribal agencies in managing Lake Michigan fish stocks. A spring bottom trawl survey (spring BT) was implemented across 3 of the transects sampled in the fall and sites ranged in depth from 18 to 164 m. The goal of the spring BT is to explore seasonal differences in biomass density and distributions of key prey species, most notably Alewife. Additionally, we conducted acoustic sampling while bottom trawling to evaluate the vertical distribution of fish relative to the height of the trawl.
The abbreviated spring BT survey results indicated that Alewives were primarily offshore with peak biomass density at the 91 m bottom depth. There was no evidence of higher acoustic density above the trawl at depths of 18, 73, 128, and 146 m. At 91 and 164 m, acoustic density above the trawl was >2x that in the trawl path, but sample size at these two depths was low. For the AC survey, total biomass density of prey fish equaled 14.8 kg/ha, 223% higher than the longterm average (2004-2022) of 4.6 kg/ha and 8.8 kg/ha higher than the 2022 estimate. For the fall BT, total biomass density of prey fish equaled 3.6 kg/ha, about 50% lower than the average value from 2004-2022 (6.9 kg/ha). The 2023 fall BT biomass was an order of magnitude lower than the average over the entirety of the time series (1973-2022; 33.7 kg/ha).
Bloater was the dominant species (by biomass) among prey fishes in the fall BT, while the AC survey reported dominance of Alewife. Mean biomass of yearling and older (YAO) Alewife was 10.3 kg/ha in the AC survey, and 0.7 kg/ha in the fall BT. Since 2014, catchability of YAO Alewives for the fall BT has been substantially lower than the AC survey. While limited in scope, the results of the 2023 spring BT do not suggest that catchability is substantially higher in the spring than the fall, which aligns with the 2022 survey results.
Comparing the AC estimate to previous years, YAO Alewife biomass was 359% higher than the average from 2004-2022. Numeric density of age-0 Alewife from the AC survey was 1,205 fish/ha in 2023, which is the third highest in the time series and well above the long-term mean of 428 fish/ha. Biomass density of large (≥120 mm) Bloater in 2023 was 3.5 kg/ha in the AC survey and 2.1 kg/ha in the fall BT - each at least an order of magnitude lower than what was estimated by the fall BT between 1985 and 1997. Following a record high year in 2021 (1,034 fish/ha), the numeric density of small (<120 mm) Bloater was 142 fish/ha in the AC survey, similar to the long-term mean of 120 fish/ha. Meanwhile, small Bloater density estimated in the fall BT was 2 fish/ha. Biomass density of large Rainbow Smelt (≥90 mm) was <0.05 kg/ha in the AC and fall BT surveys, continuing the trend of low Rainbow Smelt biomass that has been observed since 2001. Numeric density of small (<90 mm) Rainbow Smelt was 119 fish/ha in the AC survey and 7 fish/ha in the fall BT, indicating a weak year-class. All four prey fish species sampled only by the fall BT indicated below average biomass densities. Deepwater Sculpin biomass density was estimated at 0.4 kg/ha, which makes 13 of the past 14 years when biomass was <1 kg/ha. Slimy Sculpin was estimated at 0.02 kg/ha, only 5% of the long-term average. Round Goby was estimated at 0.3 kg/ha, below the average biomass of 0.85 kg/ha since 2008 but similar to intermittent low values observed throughout the dataset. Ninespine Stickleback density was 1 fish/ha. Only 35 small (<100 mm) Yellow Perch were caught, indicating a weak Yellow Perch year-class in 2023.
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S. Geological Survey-Great Lakes Science Center has monitored annual changes in the offshore (depth >9m) prey fish community of Lake Huron since 1973. Monitoring of prey fish populations in Lake Huron is based on a bottom trawl survey that targets demersal (benthic) species and an acoustic-midwater trawl survey that targets pelagic species and life stages. In 2023, Bloater (Coregonus hoyi) accounted for 77% of the main basin biomass in bottom trawls and 86% of the main basin biomass in the acoustics survey. Despite this sustained importance of native species in the main basin, species diversity is below desired levels. Bloater in the main basin has exhibited population growth and strong recruitment in recent years, and Cisco (Coregonus artedi) has exhibited increased biomass in the North Channel since 2015. In contrast non-native Alewife (Alosa pseudoharengus), whose population collapsed in 2004 and has not recovered, were less than 1% of fish biomass in 2023. Rainbow Smelt (Osmerus mordax) accounted for 7% of the main basin biomass in bottom trawls and 22% of the main basin biomass in the acoustics survey. Despite remaining the second-most abundant prey species in the main basin, Rainbow Smelt has not shown appreciable increases in biomass despite recent strong year classes. Deepwater Sculpin (Myoxocephalus thompsonii) increased by 47% in 2023 and were 33% of the long-term average. Slimy Sculpin (Cottus cognatus) increased to 60% of the long-term average but remained rare in bottom trawl catches. In contrast, biomass of Round Goby (Neogobius melanostomus), a non-native species similar ecologically to the sculpin species, remained near the record high biomass reached in 2022. Current lake conditions characterized by ongoing oligotrophication seem to favor native coregonines over non-native fishes. Use of complementary surveys (bottom trawl, acoustics) remains important for evaluating prey fish status in Lake Huron, where prey fish community dynamics vary by basin and prey fish responses to changing environmental conditions depend on species and/or habitat.
","language":"English","publisher":"Great lakes Fishery Commission","usgsCitation":"O’Brien, T.P., Hondorp, D.W., Roseman, E.F., Esselman, P.C., Brant, C., Farha, S.A., and Phillips, K., 2024, Status and trends of the Lake Huron prey fish community, 1976-2023, 27 p.","productDescription":"27 p.","ipdsId":"IP-163919","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":501738,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501737,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://glfc.org/publication-media-search.php"}],"country":"Canada, United States","otherGeospatial":"Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.7705078125,\n 45.81348649679973\n ],\n [\n -84.4189453125,\n 45.5679096098613\n ],\n [\n 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dhondorp@usgs.gov","orcid":"https://orcid.org/0000-0002-5182-1963","contributorId":5376,"corporation":false,"usgs":true,"family":"Hondorp","given":"Darryl","email":"dhondorp@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":901803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roseman, Edward F. 0000-0002-5315-9838 eroseman@usgs.gov","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":168428,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward","email":"eroseman@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":901804,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esselman, Peter C. 0000-0002-0085-903X 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A.","contributorId":79026,"corporation":false,"usgs":true,"family":"Farha","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":901807,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Phillips, Kristy 0000-0001-8378-0660","orcid":"https://orcid.org/0000-0001-8378-0660","contributorId":204292,"corporation":false,"usgs":true,"family":"Phillips","given":"Kristy","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":901808,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70252659,"text":"70252659 - 2024 - Simulating past and future fire impacts on Mediterranean ecosystems","interactions":[],"lastModifiedDate":"2024-05-20T15:28:13.244929","indexId":"70252659","displayToPublicDate":"2024-03-31T07:17:50","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Simulating past and future fire impacts on Mediterranean ecosystems","docAbstract":"Stable isotopes (SI) and fatty acid (FA) biomarkers can provide insights regarding trophic pathways and habitats associated with contaminant bioaccumulation. We assessed relationships between SI and FA biomarkers and published data on concentrations of two pesticides [dichlorodiphenyltrichloroethane and degradation products (DDX) and bifenthrin] in juvenile Chinook Salmon (Oncorhynchus tshawytscha) from the Sacramento River and Yolo Bypass floodplain in Northern California near Sacramento. We also conducted SI and FA analyses of zooplankton and macroinvertebrates to determine whether particular trophic pathways and habitats were associated with elevated pesticide concentrations in fish. Relationships between DDX and both sulfur (δ34S) and carbon (δ13C) SI ratios in salmon indicated that diet is a major exposure route for DDX, particularly for individuals with a benthic detrital energy base. Greater use of a benthic detrital energy base likely accounted for the higher frequency of salmon with DDX concentrations > 60 ng/g dw in the Yolo Bypass compared to the Sacramento River. Chironomid larvae and zooplankton were implicated as prey items likely responsible for trophic transfer of DDX to salmon. Sulfur SI ratios enabled identification of hatchery-origin fish that had likely spent insufficient time in the wild to substantially bioaccumulate DDX. Bifenthrin concentration was unrelated to SI or FA biomarkers in salmon, potentially due to aqueous uptake, biotransformation and elimination of the pesticide, or indistinct biomarker compositions among invertebrates with low and high bifenthrin concentrations. One FA [docosahexaenoic acid (DHA)] and DDX were negatively correlated in salmon, potentially due to a greater uptake of DDX from invertebrates with low DHA or effects of DDX on FA metabolism. Trophic biomarkers may be useful indicators of DDX accumulation and effects in juvenile Chinook Salmon in the Sacramento River Delta.
Clumped isotope paleothermometry using pedogenic carbonates is a powerful tool for investigating past climate changes. However, location-specific seasonal patterns of precipitation and soil moisture cause systematic biases in the temperatures they record, hampering comparison of data across large areas or differing climate states. To account for biases, more systematic studies of carbonate forming processes are needed. We measured modern soil temperatures within the San Luis Valley of the Rocky Mountains and compared them to paleotemperatures determined using clumped isotopes. For Holocene-age samples, clumped isotope results indicate carbonate accumulated at a range of temperatures with site averages similar to the annual mean. Paleotemperatures for late Pleistocene-age samples (ranging 19–72 ka in age) yielded site averages only 2°C lower, despite evidence that annual temperatures during glacial periods were 5–9°C colder than modern. We use a 1D numerical model of soil physics to support the idea that differences in hydrologic conditions in interglacial versus glacial periods promote differences in the seasonal distribution of soil carbonate accumulation. Model simulations of modern (Holocene) conditions suggest that soil drying under low soil pCO2 favors year-round carbonate accumulation in this region but peaking during post-monsoon soil drying. During a “glacial” simulation with lowered temperatures and added snowpack, more carbonate accumulation shifted to the summer season. These experiments show that changing hydrologic regimes could change the seasonality of carbonate accumulation, which in this study blunts the use of clumped isotopes to quantify glacial-interglacial temperature changes. This highlights the importance of understanding seasonal biases of climate proxies for accurate paleoenvironmental reconstruction.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023GC011221","usgsCitation":"Hudson, A.M., Kelson, J.R., Paces, J., Ruleman, C.A., Huntington, K.W., and Schauer, A.J., 2024, Clumped isotopes record a glacial-interglacial shift in seasonality of soil carbonate accumulation in the San Luis Valley, southern Rocky Mountains, USA: Geochemistry, Geophysics, Geosystems, v. 25, no. 4, e2023GC011221, 23 p., https://doi.org/10.1029/2023GC011221.","productDescription":"e2023GC011221, 23 p.","ipdsId":"IP-114357","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":440002,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023gc011221","text":"Publisher Index Page"},{"id":435011,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TJF3PZ","text":"USGS data release","linkHelpText":"Isotopic, geochronologic and soil temperature data for Holocene and late Pleistocene soil carbonates of the San Luis Valley, Colorado and New Mexico, USA"},{"id":427311,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, new Mexico","otherGeospatial":"San Luis Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107,\n 38.5\n ],\n [\n -107,\n 35.5\n ],\n [\n -105,\n 35.5\n ],\n [\n -105,\n 38.5\n ],\n [\n -107,\n 38.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-03-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Hudson, Adam M. 0000-0002-3387-9838 ahudson@usgs.gov","orcid":"https://orcid.org/0000-0002-3387-9838","contributorId":195419,"corporation":false,"usgs":true,"family":"Hudson","given":"Adam","email":"ahudson@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":897780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelson, Julia R.","contributorId":335224,"corporation":false,"usgs":false,"family":"Kelson","given":"Julia","email":"","middleInitial":"R.","affiliations":[{"id":80344,"text":"Department of Geosciences, University of Michigan, Ann Arbor, MI, USA, Department of Earth and Atmospheric Sciences, Indiana University, Indianapolis, Indiana, USA","active":true,"usgs":false}],"preferred":false,"id":897781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paces, James B. 0000-0002-9809-8493","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":118216,"corporation":false,"usgs":true,"family":"Paces","given":"James B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":897782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":897783,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huntington, Katharine W.","contributorId":195423,"corporation":false,"usgs":false,"family":"Huntington","given":"Katharine","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":897784,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schauer, Andrew J.","contributorId":140713,"corporation":false,"usgs":false,"family":"Schauer","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":897785,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70263277,"text":"70263277 - 2024 - Methane clumped isotopologue variability from ebullition in a mid-latitude lake","interactions":[],"lastModifiedDate":"2025-02-04T15:16:16.078706","indexId":"70263277","displayToPublicDate":"2024-03-30T09:12:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5615,"text":"ACS Earth and Space Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Methane clumped isotopologue variability from ebullition in a mid-latitude lake","docAbstract":"Methane is a greenhouse gas and is an important component of carbon cycling in freshwater environments. Isotope ratios of methane (13C/12C and D/H) are used extensively as tracers to identify methane sources. Recent advances in the measurement of clumped methane isotopologues (13CH3D, 12CH2D2) offer new opportunities to constrain sources and sinks of atmospheric methane. Previous measurements of clumped methane isotopologues from freshwater environments have been spatially and temporally limited. The abundance of 13CH3D and methane flux from ebullition in the deep basin of Upper Mystic Lake were measured from May to November 2021 to characterize the source isotopologue signatures and methane fluxes for mid-latitude lakes. The trends in δ13C and δD values support decreased methane oxidation in the early summer compared to fall. The Δ13CH3D values from this study range from 2.0 to 4.2‰, reflecting methane oxidation occurring anaerobically in lake sediments and euxinic bottom waters at sample sites. The relatively large variation in the Δ13CH3D values observed within this lake basin aligns with previous observations of bubbles from arctic lakes. The values of Δ13CH3D do not correlate with methane flux, suggesting that Δ13CH3D measurements from background ebullition are not sensitive as a proxy for ebullition rates. This study presents a uniquely large (n = 40) set of freshwater Δ13CH3D values from a single lake basin, which we use to recommend a sampling strategy of ≥9 samples to constrain the Δ13CH3D source signal within ∼0.5‰ from similar environments. This data demonstrates the utility of clumped methane isotopologues to gain insights into local biogeochemical processes from field studies and points to the challenge of using clumped isotopologue measurements to constrain global freshwater–methane sources to the atmosphere.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acsearthspacechem.3c00282","usgsCitation":"Lalk, E., Velez, A., and Ono, S., 2024, Methane clumped isotopologue variability from ebullition in a mid-latitude lake: ACS Earth and Space Chemistry, v. 8, no. 4, p. 689-701, https://doi.org/10.1021/acsearthspacechem.3c00282.","productDescription":"13 p.","startPage":"689","endPage":"701","ipdsId":"IP-157992","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":481663,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-03-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Lalk, Ellen Jennifer 0000-0002-9843-9278","orcid":"https://orcid.org/0000-0002-9843-9278","contributorId":350488,"corporation":false,"usgs":true,"family":"Lalk","given":"Ellen Jennifer","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":926126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Velez, Amber","contributorId":350489,"corporation":false,"usgs":false,"family":"Velez","given":"Amber","affiliations":[{"id":47799,"text":"MIT","active":true,"usgs":false}],"preferred":false,"id":926127,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ono, Shuhei","contributorId":100627,"corporation":false,"usgs":false,"family":"Ono","given":"Shuhei","email":"","affiliations":[{"id":13295,"text":"1Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139,","active":true,"usgs":false}],"preferred":false,"id":926128,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70252640,"text":"70252640 - 2024 - Potential impacts of an autumn oil spill on polar bears summering on land in northern Alaska","interactions":[],"lastModifiedDate":"2024-04-02T13:44:30.319646","indexId":"70252640","displayToPublicDate":"2024-03-30T07:03:34","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Potential impacts of an autumn oil spill on polar bears summering on land in northern Alaska","docAbstract":"Demand for oil and natural gas continues to increase, leading to the development of remote regions where it is riskier to operate. Many of these regions have had limited development, so understanding potential impacts to wildlife could inform management decisions. In 2017, the United States passed legislation allowing oil and gas development in the coastal plain of the Arctic National Wildlife Refuge in northeastern Alaska. This area has received limited industrial development and is an important region for polar bears that use the coastline as a travel corridor in autumn. We sought to understand how an autumn near-shore oil spill in the Refuge could affect polar bears. We simulated oil spills from shallow sub-sea pipelines at 3 locations along the coastline of the Refuge and allowed spills to discharge 4800 barrels of oil per day for 6 days, and tracked oil for 50 days. We interacted the trajectories with simulated polar bear movements to estimate how many bears might be exposed. Oil spread quickly along the coastline and during some weeks exposed an average of 10 bears (95 % CI: 0–37) to lethal levels of oil, and 60 (95 % CI: 9–120) to sub-lethal levels. Our results suggest a significant number of polar bears could become oiled from a spill in the region and require decontamination. Therefore, future mitigation strategies could include careful siting of future development and additional capacity to capture and decontaminate bears in the event of an oil spill.
Recharge to and flow within the Columbia River Basalt Group (CRBG) groundwater flow system of northeastern Oregon were characterized using isotopic, gas, and age-tracer samples from wells completed in basalt, springs, and stream base flow. Most groundwater samples were late-Pleistocene to early-Holocene; median age of well samples was 11,100 years. The relation between mean groundwater age and completed well depth across the eastern portion of the study area was similar despite differences in precipitation, topographic position, incision, thickness of the sedimentary overburden, and CRBG geologic unit. However, the lateral continuity in groundwater age was disrupted across large regional fault zones indicating these structures are substantial impediments to groundwater flow from the high-precipitation uplands to adjacent lower-precipitation and lower-elevation portions of the study area. Recharge rates calculated from the age-depth relations were <3 mm/yr and independent of the modern precipitation gradient across the study area. The age-constrained recharge rates to the CRBG groundwater system are considerably smaller than previously published estimates and highlight the uncertainty of prevailing models used to estimate recharge to the CRBG groundwater system across the Columbia Plateau in Oregon and Washington. Age tracer and isotopic evidence indicate recharge to the CRBG groundwater system is an exceedingly slow and localized process.
Eight springs and seeps at Fort Irwin National Training Center were described and categorized by their general characteristics, discharge, geophysical properties, and water quality between 2015 and 2017. The data collected establish a modern (2017) baseline of hydrologic conditions at the springs. Two types of springs were identified: (1) precipitation-fed upland springs (Cave, Desert King, Devouge, No Name, and Panther Springs) and (2) groundwater discharge-fed basin springs (Garlic, Bitter, and Jack Springs). Comparison of electrical resistivity tomography data collected at groundwater basin springs from 2015 to 2017 indicated that spring discharge and connection to the underlying groundwater system is highly focused, although the springs themselves appear diffuse and are spread out over a large area.
Spring discharge was consistently less than reported by Thompson (1929), except at Garlic Spring where discharges and vegetation have increased in recent years. Multiple discrete flume and seepage meter measurements taken between October 2015 and April 2016 indicated that discharge changed predictably on diurnal and seasonal timescales in response to evapotranspiration. These preliminary results and the lush vegetation noted at some of the springs, particularly at Bitter, Garlic, and Jack Springs, indicated plant evapotranspiration accounts for a substantial part of the discharge from these springs.
The quality of water ranges from fresh in precipitation-fed upland springs (Cave, Desert King, Devouge, and Panther Springs) to slightly saline (Garlic and Jack Springs) and moderately saline (Bitter Spring) in groundwater-fed discharge springs. Nitrate concentrations from water at most of the springs were less than 3 milligrams per liter, except for samples from Devouge and Desert King Springs and one sample from Jack Spring. An analysis of delta nitrogen-15 in nitrate (δ15N-NO3) and delta oxygen-18 in nitrate (δ18O-NO3) indicates high nitrate concentrations in excess of the U.S. Environmental Protection Agency maximum contaminant level at Jack Spring and Desert King Spring resulting from the dissolution of nitrate-bearing caliche deposits; nitrate concentrations at Devouge Spring are a result of algal growth within the spring, and the source of nitrate concentrations in Garlic Spring are consistent with a treated wastewater origin from Langford Valley-Irwin subbasin upgradient. The source of water in upland springs, indicated by values of delta oxygen-18 (δ18O) and delta deuterium (δD) are consistent with recharge from winter precipitation. In groundwater basin springs, values of δ18O and δD are consistent with groundwater sampled from nearby wells. Summer monsoonal precipitation appears to contribute little water to spring flow. Most springs contain low levels of tritium and appear to be primarily older (pre-1950s) groundwater. Groundwater basin springs with detectable tritium may result from occasional streamflow in nearby washes. These springs could be susceptible to decreases in flow during extended dry periods when the localized recharge may be reduced due to the loss of focused recharge through nearby washes.
Groundwater samples from Garlic and Bitter Springs contained arsenic concentrations above the U.S. Environmental Protection Agency maximum contaminant level. Groundwater samples from all springs, except Cave, Desert King, and Devouge Springs, exceeded the State of California maximum contaminant level for fluoride. Garlic Spring was the only sampled spring that contained vanadium concentrations that exceeded the State of California notification level. Only a single water sample from Jack Spring contained uranium at a concentration that exceeded the U.S. Environmental Protection Agency maximum contaminant level.
Many other constituents of concern were analyzed, including those from anthropogenic sources that may be a result of military activities. Most of these constituents were not detected above their respective reporting levels in spring water; only 15 were detected in spring waters. Diesel and gasoline degradants, many of which also occur naturally, were the most commonly detected compounds. Several other organic compounds, primarily solvents or their degradants, were detected in groundwater basin springs. These constituents, in order of decreasing detection frequency, were carbon disulfide; perchlorate; mercury; acetone; methylnaphthalene; toluene; methyl ethyl ketone; cyanide; and styrene; 4-iso-propyl-toluene; isopropylbenzene; methyl salicylate; and phenol. Except for Garlic Spring, which is affected by discharges of treated wastewater, the quality of water from most springs appears to be relatively unaffected by activities at the Fort Irwin National Training Center.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235142","collaboration":"Prepared in cooperation with the U.S. Army Fort Irwin National Training Center","programNote":"Water Availability and Use Science Program","usgsCitation":"Densmore, J.N., Thayer, D.C., Dick, M.C., Swarzenski, P.W., Ball, L.B., Rosecrans, C.Z., and Johnson, C., 2024, Evaluation of the characteristics, discharge, and water quality of selected springs at Fort Irwin National Training Center, San Bernardino County, California: U.S. Geological Survey Scientific Investigations Report 2023–5142, 87 p., https://doi.org/10.3133/sir20235142.","productDescription":"Report: xii, 87 p.; 2 Data Releases","numberOfPages":"87","onlineOnly":"Y","ipdsId":"IP-098665","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":426854,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P901E9C2","text":"USGS Data Release","description":"Mesmer, R.D., Dick, M.C., and Densmore, J.N., 2024, Temperature and discharge data of selected springs at Fort Irwin National Training Center, San Bernardino County, California: U.S. Geological Survey data release, available at https://doi.org/10.5066/P901E9C2.","linkHelpText":"Temperature and discharge data of selected springs at Fort Irwin National Training Center, San Bernardino County, California"},{"id":499404,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116216.htm","linkFileType":{"id":5,"text":"html"}},{"id":426868,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5142/images"},{"id":426867,"rank":6,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5142/covrthb.jpg"},{"id":426866,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235142/full"},{"id":426865,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5142/sir20235142.xml"},{"id":426864,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5142/sir20235142.pdf","text":"Report","size":"25.9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":426853,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77W6BF0","text":"USGS Data Release","description":"Thayer, D.C., Ball, L.B., Densmore, J.N., Swarzenski, P.W., and Johnson, C., 2018, Electrical resistivity tomography data at Fort Irwin National Training Center, San Bernardino County, California, 2015 and 2017: U.S. Geological Survey data release, available at https://doi.org/10.5066/F77W6BF0.","linkHelpText":"Electrical resistivity tomography data at Fort Irwin National Training Center, San Bernardino County, California, 2015 and 2017"}],"country":"United States","state":"California","otherGeospatial":"Fort Irwin National Training Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.65077467771744,\n 36.01045506303355\n ],\n [\n -117.65077467771744,\n 34.68622540325404\n ],\n [\n -115.49481045780325,\n 34.68622540325404\n ],\n [\n -115.49481045780325,\n 36.01045506303355\n ],\n [\n -117.65077467771744,\n 36.01045506303355\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The Arizona Toad (Anaxyrus microscaphus) is restricted to riverine corridors and adjacent uplands in the arid southwestern United States. As with numerous amphibians worldwide, populations are declining and face various known or suspected threats, from disease to habitat modification resulting from climate change. The Arizona Toad has been petitioned to be listed under the U.S. Endangered Species Act and was considered “warranted but precluded” citing the need for additional information – particularly regarding natural history (e.g., connectivity and dispersal ability). The objectives of this study were to characterize population structure and genetic diversity across the species’ range. We used reduced-representation genomic sequencing to genotype 3,601 single nucleotide polymorphisms in 99 Arizona Toads from ten drainages across its range. Multiple analytical methods revealed two distinct genetic groups bisected by the Colorado River; one in the northwestern portion of the range in southwestern Utah and eastern Nevada and the other in the southeastern portion of the range in central and eastern Arizona and New Mexico. We also found subtle substructure within both groups, particularly in central Arizona where toads at lower elevations were less connected than those at higher elevations. The northern and southern parts of the Arizona Toad range are not well connected genetically and could be managed as separate units. Further, these data could be used to identify source populations for assisted migration or translocations to support small or potentially declining populations.
","language":"English","publisher":"Springer","doi":"10.1007/s10592-024-01606-w","usgsCitation":"Oyler-McCance, S.J., Ryan, M.J., Sullivan, B.K., Fike, J., Cornman, R.S., Giermakowski, J.T., Zimmerman, S.J., Harrow, R.L., Hedwell, S., Hossack, B., Latella, I., Lovish, R.E., Siefken, S., Sigafus, B., and Muths, E., 2024, Genetic Connectivity in the Arizona toad (Anaxyrus microscaphus): implications for conservation of a stream dwelling amphibian in the arid Southwestern U.S.: Conservation Genetics, v. 25, p. 835-848, https://doi.org/10.1007/s10592-024-01606-w.","productDescription":"14 p.","startPage":"835","endPage":"848","ipdsId":"IP-154561","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":440011,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10592-024-01606-w","text":"Publisher Index Page"},{"id":427560,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Nevada, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.0000406770512,\n 38.468528390736736\n ],\n [\n -118.0000406770512,\n 30.615684527609147\n ],\n [\n -106.80078434694725,\n 30.615684527609147\n ],\n [\n -106.80078434694725,\n 38.468528390736736\n ],\n [\n -118.0000406770512,\n 38.468528390736736\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","noUsgsAuthors":false,"publicationDate":"2024-03-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":898325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ryan, Mason J.","contributorId":266045,"corporation":false,"usgs":false,"family":"Ryan","given":"Mason","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":898326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Brian K.","contributorId":177225,"corporation":false,"usgs":false,"family":"Sullivan","given":"Brian","email":"","middleInitial":"K.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":898327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fike, Jennifer A. 0000-0001-8797-7823","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":207268,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":898328,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":898329,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Giermakowski, J. 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