The stygobitic Caney Mountain cave crayfish, Orconectes stygocaneyi, is among the rarest crayfish species in North America. It is known only from Mud Cave, a small linear cave on the 3,200 ha Caney Mountain Conservation Area in Ozark County, Missouri. The species is listed as “Endangered” by the state of Missouri, and “Threatened” by the American Fisheries Society. Previous studies documented its population range and limited life history notes; but little is known about Mud Cave’s habitat. We conducted a one-year study to document the cave’s water chemistry, quality, and interior wetted pool volume, and how this habitat varies monthly, to establish a baseline for future study.
","language":"English","publisher":"International Association of Astacology","doi":"10.5869/fc.2024.v29-1.121","collaboration":"Missouri Department of Conservation","usgsCitation":"Ellingsworth, E.A., DiStefano, R., Westhoff, J.T., and O'Brian, B., 2024, The endangered Caney Mountain cave crayfish: A preliminary study of its habitat with brief life history notes: Freshwater Crayfish, v. 29, no. 1, p. 121-132, https://doi.org/10.5869/fc.2024.v29-1.121.","productDescription":"12 p.","startPage":"121","endPage":"132","ipdsId":"IP-166086","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":494532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","county":"Ozark County","otherGeospatial":"Caney Mountain Conservation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.45151688083625,\n 36.66449702263134\n ],\n [\n -92.45151688083625,\n 36.625266091515115\n ],\n [\n -92.40079722946713,\n 36.625266091515115\n ],\n [\n -92.40079722946713,\n 36.66449702263134\n ],\n [\n -92.45151688083625,\n 36.66449702263134\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Ellingsworth, Emila A.","contributorId":360156,"corporation":false,"usgs":false,"family":"Ellingsworth","given":"Emila","middleInitial":"A.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":946864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DiStefano, R.J.","contributorId":360159,"corporation":false,"usgs":false,"family":"DiStefano","given":"R.J.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":946865,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Westhoff, Jacob Thomas 0000-0002-2347-5098","orcid":"https://orcid.org/0000-0002-2347-5098","contributorId":288958,"corporation":false,"usgs":true,"family":"Westhoff","given":"Jacob","email":"","middleInitial":"Thomas","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":946866,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O'Brian, B.M.","contributorId":360164,"corporation":false,"usgs":false,"family":"O'Brian","given":"B.M.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":946867,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70271332,"text":"70271332 - 2024 - Don’t move a mussel: The role of key environmental drivers and management scale in assessing spatial variation in dreissenid spread risk in the Missouri River Basin","interactions":[],"lastModifiedDate":"2025-09-05T15:31:48.53114","indexId":"70271332","displayToPublicDate":"2024-12-31T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Don’t move a mussel: The role of key environmental drivers and management scale in assessing spatial variation in dreissenid spread risk in the Missouri River Basin","docAbstract":"The spread of non-native freshwater mussels in North America is a growing threat that has already resulted in substantial ecological and economic damage to infested areas. A primary vector by which invasive mussels spread is watercraft that are transported over land from an infested waterbody to an uninfested waterbody. Management efforts such as watercraft inspection and detection programs that attempt to intercept infected watercraft can help limit this type of spread, but optimizing the effectiveness of these programs under limited resources is complicated. Studies have looked at developing watercraft inspection and decontamination program strategies that focus on policy-specific objectives such as maximizing the number of infested watercraft interceptions. However, there is limited work that has considered the heterogeneous impact of protection efforts across different regions and waterbodies. Knowledge about this heterogeneity can highlight regions that would benefit the most from protection as well as regions that would require less effort to protect, e.g., areas with naturally unsuitable water quality for dreissenids. To this end, we construct a composite relative risk index (CRR) for watersheds within the Missouri River Basin, a region in the United States on the front line of dreissenid spread. The CRR uses a model that mirrors an expected value model but uses relative indexing as a proxy for the model components. The CRR incorporates a wide array of data sets to account for the direct and indirect damages from a potential infestation along with the risk of an infestation occurring. Our results suggest that the relative priority of a specific watershed—measured through CRR—can depend on whether we consider the entire Missouri River Basin or just the watersheds in the same state. This also indicates substantial state-level heterogeneity in the CRR. Another contribution is that the CRR index includes user-specified weights for certain parameters so that a user can adjust the relative importance of various factors to match their specific context. An accompanying web tool allows users to view the CRR results and adjust multiple parameters to see the resulting impacts on the CCR for watersheds in the Missouri River Basin.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2024.112526","usgsCitation":"Raymond, J., Bair, L., Counihan, T., Daniel, W., Duntugan, S., Neilson, M., and Springborn, M.R., 2024, Don’t move a mussel: The role of key environmental drivers and management scale in assessing spatial variation in dreissenid spread risk in the Missouri River Basin: Ecological Indicators, v. 170, 112526, 14 p., https://doi.org/10.1016/j.ecolind.2024.112526.","productDescription":"112526, 14 p.","ipdsId":"IP-160154","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":495378,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2024.112526","text":"Publisher Index 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0000-0002-9911-3624","orcid":"https://orcid.org/0000-0002-9911-3624","contributorId":248714,"corporation":false,"usgs":true,"family":"Bair","given":"Lucas","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":948066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Counihan, Timothy D. 0000-0003-4967-6514","orcid":"https://orcid.org/0000-0003-4967-6514","contributorId":207532,"corporation":false,"usgs":true,"family":"Counihan","given":"Timothy D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":948067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daniel, Wesley M. 0000-0002-7656-8474","orcid":"https://orcid.org/0000-0002-7656-8474","contributorId":214505,"corporation":false,"usgs":true,"family":"Daniel","given":"Wesley","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":948068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duntugan, Sofie","contributorId":360981,"corporation":false,"usgs":false,"family":"Duntugan","given":"Sofie","affiliations":[{"id":86140,"text":"formerly: US Geological Survey, Western Fisheries Research Center, Seattle, WA 98115","active":true,"usgs":false}],"preferred":false,"id":948069,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Neilson, Matthew 0000-0002-5139-5677","orcid":"https://orcid.org/0000-0002-5139-5677","contributorId":214507,"corporation":false,"usgs":true,"family":"Neilson","given":"Matthew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":948070,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Springborn, Michael R.","contributorId":207552,"corporation":false,"usgs":false,"family":"Springborn","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":37562,"text":"University of California Davis, 1 Shields Avenue Davis, CA 95616, USA","active":true,"usgs":false}],"preferred":false,"id":948071,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274212,"text":"70274212 - 2024 - Community synchrony in seed production is associated with trait similarity and climate across North America","interactions":[],"lastModifiedDate":"2026-03-13T15:03:12.321279","indexId":"70274212","displayToPublicDate":"2024-12-31T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Community synchrony in seed production is associated with trait similarity and climate across North America","docAbstract":"Mast seeding, the synchronous and highly variable production of seed crops in perennial plants, is a population level phenomenon and has cascading effects in ecosystems. Mast seeding studies are typically conducted at the population/species level. Much less is known about synchrony in mast seeding between species because the necessary long-term data are rarely available. To investigate synchrony between species within communities, we used long-term data from seven forest communities in the US Long-Term Ecological Research (LTER) network, ranging from tropical rainforest to taiga. We focus on cross-species synchrony and i) quantify synchrony in reproduction overall and within LTER sites, ii) test for relationships between synchrony with trait and phylogenetic similarity, and iii) investigate how climate conditions are related to levels of synchrony. Overall, synchrony in reproduction between woody plant species was greater than expected by chance, but also spanned a wide range of values between species. Based on 11 traits for 103 species (plus phylogenetic relatedness), cross-species synchrony in reproduction was driven primarily by trait similarity with phylogeny being largely unimportant, and synchrony was higher in sites with greater climatic water deficit. Synchronous masting within a community has consequences for understanding forest regeneration dynamics and consumer-resource interactions.","language":"English","publisher":"Wiley","doi":"10.1111/ele.14498","usgsCitation":"LaMontagne, J.M., Greene, D.F., Holland, E., Johnstone, J.F., Schulze, M., Zimmerman, J.K., Lyon, N.J., Chen, A., Miller, T.E., Nigro, K.M., Snell Rebecca S., Barton, J.H., Chaudhary, V., Cleavitt, N.L., Crone, E., Koenig, W.D., Macias, D., Pearse, I.S., and Redmond, M.D., 2024, Community synchrony in seed production is associated with trait similarity and climate across North America: Ecology Letters, v. 27, no. 12, e14498, 15 p., https://doi.org/10.1111/ele.14498.","productDescription":"e14498, 15 p.","ipdsId":"IP-162505","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":501361,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ele.14498","text":"Publisher Index Page"},{"id":501146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -174.57469846241375,\n 59.07732223048754\n ],\n [\n -132.94118629888828,\n 46.634323740727496\n ],\n [\n -102.87615155066331,\n 14.159655778644463\n ],\n [\n -86.60507271467972,\n 18.528872570028568\n ],\n [\n -76.70651169792454,\n 26.155075649047504\n ],\n [\n -55.08810680677202,\n 45.22442345962252\n ],\n [\n -93.39098226670879,\n 53.00878959626715\n ],\n [\n -134.4869880449841,\n 65.05021822139254\n ],\n [\n -154.62493341933438,\n 66.11219190375385\n ],\n [\n -174.57469846241375,\n 59.07732223048754\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"27","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"LaMontagne, Jalene M.","contributorId":223096,"corporation":false,"usgs":false,"family":"LaMontagne","given":"Jalene","middleInitial":"M.","affiliations":[{"id":36623,"text":"DePaul University","active":true,"usgs":false}],"preferred":false,"id":957043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Greene, David F.","contributorId":302454,"corporation":false,"usgs":false,"family":"Greene","given":"David","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":957044,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holland, E. Penelope","contributorId":367192,"corporation":false,"usgs":false,"family":"Holland","given":"E. Penelope","affiliations":[{"id":87596,"text":"U York","active":true,"usgs":false}],"preferred":false,"id":957045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnstone, Jill F.","contributorId":367203,"corporation":false,"usgs":false,"family":"Johnstone","given":"Jill","middleInitial":"F.","affiliations":[{"id":17775,"text":"U Alaska","active":true,"usgs":false}],"preferred":false,"id":957046,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schulze, Mark","contributorId":192221,"corporation":false,"usgs":false,"family":"Schulze","given":"Mark","email":"","affiliations":[],"preferred":false,"id":957047,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zimmerman, Jess K.","contributorId":196419,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Jess","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":957048,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lyon, Nicholas J.","contributorId":367204,"corporation":false,"usgs":false,"family":"Lyon","given":"Nicholas","middleInitial":"J.","affiliations":[{"id":28104,"text":"NCEAS","active":true,"usgs":false}],"preferred":false,"id":957049,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chen, Angel","contributorId":345830,"corporation":false,"usgs":false,"family":"Chen","given":"Angel","affiliations":[{"id":65228,"text":"National Center for Ecological Analysis and Synthesis","active":true,"usgs":false}],"preferred":false,"id":957050,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Miller, Tom E.X.","contributorId":367205,"corporation":false,"usgs":false,"family":"Miller","given":"Tom","middleInitial":"E.X.","affiliations":[{"id":48394,"text":"Rice U","active":true,"usgs":false}],"preferred":false,"id":957051,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nigro, Katherine M.","contributorId":189487,"corporation":false,"usgs":false,"family":"Nigro","given":"Katherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":957052,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Snell Rebecca S.","contributorId":367206,"corporation":false,"usgs":false,"family":"Snell Rebecca S.","affiliations":[{"id":12807,"text":"Ohio University","active":true,"usgs":false}],"preferred":false,"id":957053,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Barton, Jessica H.","contributorId":302438,"corporation":false,"usgs":false,"family":"Barton","given":"Jessica","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":957054,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Chaudhary, V. 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Bala","affiliations":[{"id":39657,"text":"Dartmouth College","active":true,"usgs":false}],"preferred":false,"id":957055,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Cleavitt, Natalie L.","contributorId":303063,"corporation":false,"usgs":false,"family":"Cleavitt","given":"Natalie","email":"","middleInitial":"L.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":957056,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Crone, Elizabeth E.","contributorId":352543,"corporation":false,"usgs":false,"family":"Crone","given":"Elizabeth E.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":957057,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Koenig, Walter D.","contributorId":367208,"corporation":false,"usgs":false,"family":"Koenig","given":"Walter","middleInitial":"D.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":957058,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Macias, Diana","contributorId":256880,"corporation":false,"usgs":false,"family":"Macias","given":"Diana","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":957059,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":211154,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":957060,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Redmond, Miranda D.","contributorId":225094,"corporation":false,"usgs":false,"family":"Redmond","given":"Miranda","middleInitial":"D.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":957061,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70261830,"text":"ofr20241080 - 2024 - Hydrologic investigations and a preliminary conceptual model of the groundwater system at North Penn Area 1 Superfund Site, Souderton, Montgomery County, Pennsylvania","interactions":[],"lastModifiedDate":"2025-08-15T16:08:29.355622","indexId":"ofr20241080","displayToPublicDate":"2024-12-30T12:40:00","publicationYear":"2024","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":"2024-1080","displayTitle":"Hydrogeologic Investigations and a Preliminary Conceptual Model of the Groundwater System at North Penn Area 1 Superfund Site, Souderton, Montgomery County, Pennsylvania","title":"Hydrologic investigations and a preliminary conceptual model of the groundwater system at North Penn Area 1 Superfund Site, Souderton, Montgomery County, Pennsylvania","docAbstract":"The U.S. Geological Survey (USGS) conducted hydrogeologic investigations, reviewed existing data, and developed a preliminary conceptual model of the groundwater system as part of technical support of the U.S. Environmental Protection Agency (EPA) at the North Penn Area 1 Superfund Site (hereafter, the NP1 Site) located within the Borough of Souderton in Montgomery County, Pennsylvania. Field work and monitoring took place during 2012–18. The area is underlain by sedimentary formations that form a fractured-rock aquifer used for drinking water and industrial supply. The EPA placed the Site on the National Priorities List in 1989, identifying tetrachloroethylene (PCE) and trichloroethylene (TCE) as contaminants of concern.
During 2012–18, the USGS conducted field activities that included drilling an 82-foot (ft)-deep monitoring well (MG 2220) in 2016, reconstructing a 208-ft-deep former industrial production well (MG 668 [Granite Knitting Mill]), and collecting borehole geophysical and video logs and water levels from those and five additional wells, which ranged in depth from about 50 to 200 ft below land surface. Continuous water levels were collected during 2014–17, and a synoptic set of water levels were measured in April 2018 in the seven wells.
The borehole geophysical logs (caliper, acoustic televiewer, natural gamma, single-point resistance, vertical flow, and fluid temperature and resistivity) and borehole video logs in the seven wells were evaluated to assess potential for lithologic correlation and to identify and describe water-bearing features, which included both low- and high-angle fractures and other openings oriented along dipping bedding planes, joints, or possible faults. Borehole geophysical logs collected by USGS in 1992 in a 300-ft-deep former production well near the Site were also evaluated. Few to no distinctive features were identified on geophysical logs (natural gamma and single-point resistance) that could be used for correlation, thus limiting this approach to determining local geologic structure. Extensive fracturing in the upper 62 ft of monitoring well MG 2220 indicates that the well was likely drilled through a zone of faulting, and other evidence of faulting is present in the area near the Site. Assessment of continuous water levels showed hydraulic connections among some wells as indicated by rising or falling water levels in response to changes in pumping rates at nearby wells. A map of water levels measured in April 2018 indicates potential for groundwater flow generally toward the stream to the south and southwest of the Site, but the limited water-level data are insufficient to describe vertical groundwater gradients or lateral gradients in any detail.
Review of 1999–2022 volatile organic compound (VOC) monitoring data collected by the Pennsylvania Department of Environmental Protection for five monitoring wells indicates that the highest groundwater concentrations of PCE and TCE were found in samples from extraction well MG 2201 (S-1) downgradient from, and nearest to, the previously identified Site contaminant source area, and these concentrations fluctuated through time. PCE concentrations were higher than TCE concentrations in samples from all five monitoring wells and were much higher than TCE concentrations in samples from extraction well MG 2201 (S-1). Temporally variable recharge is a possible factor affecting observed fluctuations in PCE concentrations in groundwater samples from well extraction MG 2201 (S-1), as indicated by a general inverse relation between PCE concentrations and water levels in a nearby long-term observation well. The PCE concentration of 1,830 micrograms per liter (μg/L) in a May 2018 water sample from monitoring well MG 2220 was more than four times the PCE concentration of 444 μg/L in a December 2017 sample from the nearby extraction well MG 2201 (S-1), which is open to fewer fractures. Low concentrations of VOCs were measured in surface water at two stream sites downgradient from wells with the highest groundwater VOC concentrations at the Site, indicating that discharge of contaminated groundwater to the stream is likely.
Development of a conceptual model of the groundwater system was constrained by limited data. In areas with no pumping, groundwater-flow directions generally are thought to be controlled by topography and geologic structure (bedding orientation) and likely to the south and southwest of the Site, with local flow directions affected by orientations of fractures, joints, and local faults. Additional investigations that could help improve the conceptual model of the groundwater system and help delineate the extent of groundwater contamination and its transport are discussed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241080","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Senior, L.A., Risser, D.W., Goode, D.J., and Bird, P.H., 2024, Hydrologic investigations and a preliminary conceptual model of the groundwater system at North Penn Area 1 Superfund Site, Souderton, Montgomery County, Pennsylvania: U.S. Geological Survey Open-File Report 2024–1080, 78 p., https://doi.org/10.3133/ofr20241080.","productDescription":"xi, 78 p.","numberOfPages":"78","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-151018","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":494216,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118273.htm","linkFileType":{"id":5,"text":"html"}},{"id":465486,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1080/ofr20241080.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2024-1080 XML"},{"id":465485,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241080/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1080 HTML"},{"id":465479,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1080/images/"},{"id":465476,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1080/ofr20241080.pdf","text":"Report","size":"18.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1080 PDF"},{"id":465475,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1080/coverthb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Montgomery County","city":"Souderton","otherGeospatial":"North Penn Area 1 Superfund Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.33380565402877,\n 40.30337215850042\n ],\n [\n -75.33067431094733,\n 40.30297414782885\n ],\n [\n -75.32310689850118,\n 40.30864557850933\n ],\n [\n -75.32121504538941,\n 40.31133187946756\n ],\n [\n -75.32415067952832,\n 40.31496319053656\n ],\n [\n -75.33002194780529,\n 40.3133714069823\n ],\n [\n -75.33432754454195,\n 40.307053646040714\n ],\n [\n -75.33380565402877,\n 40.30337215850042\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, Pennsylvania 17070
New geologic mapping (Wells and others, 2020b) and geophysical mapping (Blakely and others, 2000; McPhee and others, 2014; Wells and others, 2020a) document kilometers of Cenozoic right-lateral offset along the Gales Creek Fault Zone, a major, northwest-striking fault zone forming the boundary between the Tualatin Valley and the Coast Range. The Bureau of Reclamation’s (Reclamation) Scoggins Dam (fig. 1), in the Coast Range foothills west of Forest Grove, Oregon, lies within the Gales Creek Fault Zone as mapped by Wells and others (2020a, 2020b; fig. 2).
Active faults of the Gales Creek Fault Zone defined by paleoseismic trenching (Redwine and others, 2017, 2019b, Horst and others, 2018, 2019, 2021, and Wells and others, 2020a) are presently mapped as projecting through the existing dam. The Pacific Northwest Region of Reclamation requested assistance with geologic studies around Scoggins Dam to provide better understanding of fault locations and their activity, which are needed to design a modification of the dam (Maguire, 2019a, b). The scope of this project includes detailed geology of the existing Scoggins Dam site, Henry Hagg Lake, the reservoir behind the dam, and Scoggins Valley downstream of the existing dam, particularly around a potential new dam site, where Scoggins Creek cuts through a narrow gap formed by a resistant felsic tuff bed that crosses the valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3528","collaboration":"Bureau of Reclamation, Clean Water Services","usgsCitation":"Wells, R.E., Bennett, S.E.K., Redwine, J.R., Staisch, L.M., Holm-Denoma, C.S., and Mahan, S.A., 2024, Geologic map of Scoggins Dam, Henry Hagg Lake, and Scoggins Valley, Washington County, Oregon: U.S. Geological Survey Scientific Investigations Map 3528, 4 sheets, scales 1:2,000 and, 1:12,000, 37 p. pamphlet, https://doi.org/10.3133/sim3528.","productDescription":"Pamphlet: x, 37 p.; 4 Sheets: 43.91 x 34.01 inches or smaller; 3 Data Releases","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-121928","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":494215,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118270.htm","linkFileType":{"id":5,"text":"html"}},{"id":465359,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91ZSKV3","text":"USGS Data Release","description":"Pianowski, L.S., Holm-Denoma, C.S., Staisch, L.M., and Wells, R.E., 2023, U-Pb zircon data for Cenozoic clastic and volcaniclastic units deformed along the Gales Creek Fault Zone, northwestern Oregon: U.S. Geological Survey data release, https://doi.org/10.5066/P91ZSKV3.","linkHelpText":"U-Pb zircon data for Cenozoic clastic and volcaniclastic units deformed along the Gales Creek Fault Zone, northwestern Oregon"},{"id":465358,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PVK0Q3","text":"USGS Data Release","description":"Mahan, S.A., Krolczyk, E.T., and Redwine, J., 2022, Data Release for Luminescence; Geologic map of Scoggins Dam, Henry Hagg Lake, and the Scoggins Valley area, Washington County, Oregon: U.S. Geological Survey data release, https://doi.org/10.5066/P9PVK0Q3.","linkHelpText":"Data Release for Luminescence; Geologic map of Scoggins Dam, Henry Hagg Lake, and the Scoggins Valley area, Washington County, Oregon"},{"id":465357,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M5300X","text":"USGS Data Release","description":"Wells, R.E., Bennett, S.E.K., Redwine, J.R., Staisch, L.M., Holm-Denoma, C.S., and Mahan, S.A.,2024, Digital data for the geologic map of Scoggins Dam, Henry Hagg Lake, and Scoggins Valley, Washington County, Oregon: U.S. Geological Survey data release, https://doi.org/10.5066/P9M5300X.","linkHelpText":"Digital data for the geologic map of Scoggins Dam, Henry Hagg Lake, and Scoggins Valley, Washington County, Oregon"},{"id":465356,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3528/sim3528_pamphlet.pdf","text":"Pamphlet","size":"53 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":465355,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3528/sim3528_sheet4.pdf","text":"Sheet 4","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Geologic Cross Sections of the Option 3 Dam Site"},{"id":465354,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3528/sim3528_sheet3.pdf","text":"Sheet 3","size":"15 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Geologic Map of the Option 3 Dam Site"},{"id":465353,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3528/sim3528_sheet2.pdf","text":"Sheet 2","size":"15 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Geologic Map of Scoggins Dam"},{"id":465352,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3528/sim3528_sheet1.pdf","text":"Sheet 1","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Geologic Map of Scoggins Dam, Henry Hagg Lake, and Scoggins Valley, Washington County, Oregon"},{"id":465351,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3528/covrthb.jpg"}],"country":"United States","state":"Oregon","county":"Washington County","otherGeospatial":"Henry Hagg Lake, Scoggins Dam, Scoggins Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.30887944247891,\n 45.55096796789627\n ],\n [\n -123.30887944247891,\n 45.44121330051283\n ],\n [\n -123.1570053249566,\n 45.44121330051283\n ],\n [\n -123.1570053249566,\n 45.55096796789627\n ],\n [\n -123.30887944247891,\n 45.55096796789627\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
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Moffett Field, CA 94035
Climate-driven changes in high-elevation forest distribution and reductions in snow and ice cover have major implications for ecosystems and global water security. In the Greater Yellowstone Ecosystem of the Rocky Mountains (United States), recent melting of a high-elevation (3,091 m asl) ice patch exposed a mature stand of whitebark pine (Pinus albicaulis) trees, located ~180 m in elevation above modern treeline, that date to the mid-Holocene (c. 5,950 to 5,440 cal y BP). Here, we used this subfossil wood record to develop tree-ring-based temperature estimates for the upper-elevation climate conditions that resulted in ancient forest establishment and growth and the subsequent regional ice-patch growth and downslope shift of treeline. Results suggest that mid-Holocene forest establishment and growth occurred under warm-season (May-Oct) mean temperatures of 6.2 °C (±0.2 °C), until a multicentury cooling anomaly suppressed temperatures below 5.8 °C, resulting in stand mortality by c. 5,440 y BP. Transient climate model simulations indicate that regional cooling was driven by changes in summer insolation and Northern Hemisphere volcanism. The initial cooling event was followed centuries later (c. 5,100 y BP) by sustained Icelandic volcanic eruptions that forced a centennial-scale 1.0 °C summer cooling anomaly and led to rapid ice-patch growth and preservation of the trees. With recent warming (c. 2000–2020 CE), warm-season temperatures now equal and will soon exceed those of the mid-Holocene period of high treeline. It is likely that perennial ice cover will again disappear from the region, and treeline may expand upslope so long as plant-available moisture and disturbance are not limiting.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2412162121","usgsCitation":"Pederson, G.T., Stahle, D.K., McWethy, D.B., Toohey, M., Jungclaus, J., Lee, C., Martin, J.T., Alt, M., Kichas, N.E., Chellman, N.J., McConnell, J.R., and Whitlock, C., 2024, Dynamic treeline and cryosphere response to pronounced mid-Holocene climatic variability in the US Rocky Mountains: Proceedings of the National Academy of Sciences, v. 122, e2412162121, 11 p., https://doi.org/10.1073/pnas.2412162121.","productDescription":"e2412162121, 11 p.","ipdsId":"IP-163460","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":466697,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2412162121","text":"Publisher Index Page"},{"id":465611,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.40405049321484,\n 45.200185933759144\n ],\n [\n -110.40405049321484,\n 44.77582421595028\n ],\n [\n -109.75503610328678,\n 44.77582421595028\n ],\n [\n -109.75503610328678,\n 45.200185933759144\n ],\n [\n -110.40405049321484,\n 45.200185933759144\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"122","noUsgsAuthors":false,"publicationDate":"2024-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science 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Oregon","active":true,"usgs":false}],"preferred":false,"id":922193,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70263186,"text":"70263186 - 2024 - The MIEM guidelines: Minimum information for reporting of environmental metabarcoding data","interactions":[],"lastModifiedDate":"2025-01-31T15:26:41.141271","indexId":"70263186","displayToPublicDate":"2024-12-30T09:18:37","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8122,"text":"Metabarcoding and Metagenomics","active":true,"publicationSubtype":{"id":10}},"title":"The MIEM guidelines: Minimum information for reporting of environmental metabarcoding data","docAbstract":"Environmental DNA (eDNA) and RNA (eRNA) metabarcoding has become a popular tool for assessing biodiversity from environmental samples, but inconsistent documentation of methods, data and metadata makes results difficult to reproduce and synthesise. A working group of scientists have collaborated to produce a set of minimum reporting guidelines for the constituent steps of metabarcoding workflows, from the physical layout of laboratories through to data archiving. We emphasise how reporting the suite of data and metadata should adhere to findable, accessible, interoperable and reproducible (FAIR) data standards, thereby providing context for evaluating and understanding study results. An overview of the documentation considerations for each workflow step is presented and then summarised in a checklist that can accompany a published study or report. Ensuring workflows are transparent and documented is critical to reproducible research and should allow for more efficient uptake of metabarcoding data into management decision-making.
","language":"English","publisher":"Pensoft Publishers","doi":"10.3897/mbmg.8.128689","usgsCitation":"Klymus, K.E., Baker, J., Abbott, C., Brown, R., Craine, J.M., Gold, Z., Hunter, M., Johnson, M., Jones-Slobodian, D.N., Jungbluth, M., Jungbluth, S., Lor, Y., Maloy, A., Merkes, C.M., Noble, R.T., Patin, N., Sepulveda, A., Spear, S.F., Steele, J., Takahashi, M., Watts, A.W., and Theroux, S., 2024, The MIEM guidelines: Minimum information for reporting of environmental metabarcoding data: Metabarcoding and Metagenomics, v. 8, e128689, 30 p., https://doi.org/10.3897/mbmg.8.128689.","productDescription":"e128689, 30 p.","ipdsId":"IP-166699","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research 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Limited studies explore the impacts of wildfires on aquatic taxa and few focus on lentic habitats that are essential for amphibians, many of which are of conservation concern. We capitalized on existing pre-fire surveys for anuran species and resurveyed a random subset of wetlands across a gradient of soil burn severity to investigate the short-term effects of wildfire on a relict population of wood frogs in the southern Rocky Mountains. We also investigated whether maps created to support rapid post-fire emergency response activities (i.e., United States Forest Service Burned Area Emergency Response program) accurately characterize soil burn severity around small habitat features (i.e., ponds) that serve as important amphibian breeding and rearing habitat. Soil burn severity reflects fire impacts on soil and surface organic layers, including vegetation loss and changes in soil structure and function. We found that wood frog (Lithobates sylvaticus) breeding persistence following fires was negatively influenced by the percentage of their terrestrial habitat (100 m buffer surrounding breeding ponds) that was burned. Wood frog colonization probability of previously unoccupied ponds was low (∼ 0.10) and unaffected by soil burn severity. Importantly, we found that remotely sensed data typically produced to predict flooding and erosion at broad (catchment) scales is a poor representation of the amount and variation in soil burn severity surrounding small habitat features, suggesting that additional field sampling is necessary to understand wildfire responses for species that rely on these small habitat features. Understanding short-term geographic- and species-specific variation in response to wildfires provides the basis to explore time to recovery (e.g., when wood frogs return to burned breeding sites) or to determine if declines in breeding distributions intensify over time.
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As requested by the U.S. Fish and Wildlife Service, we used aerial photography and satellite remote sensing data to map surface water and other land cover types within the wetland complexes. We identified five land cover classes using the green normalized difference vegetation index (gNDVI) and its inverse relationship to the normalized difference water index (NDWI) within three U.S. Department of Agriculture National Agriculture Imagery Program aerial images (acquired in 2015, 2017, and 2019) and 110 European Space Agency Sentinel-2 satellite images (acquired 2015–2022). The relative wetness of soil conditions within each land cover class is estimated by comparison to previously published observations of relative conductivity measured by 79 field-based sensors within the wetlands from 2019 to 2021. We mapped the areal coverage of the five land cover classes for approximately 385 acres (1,559,000 square meters [m²]) comprising six individual wetland complexes as well as a larger 1,298- acre (5,254,000-m2) area of interest inclusive of the wetland complexes and adjacent landscape. Land cover of open water (Class 5) primarily within ponds at one of the wetland complexes comprised 8,333 m2, on average, of the wetland complexes. Land cover of mixed shallow surface water, saturated soil, and vegetation (Class 4) comprised 111,723 m2 on average of the wetland complexes. Land cover of dense green vegetation canopy cover (Class 3) that often (46 percent of observations) had underlying surface water or saturated soil conditions comprised 592,522 m2 on average of the wetland complexes. The remaining areas of the wetland complexes not mapped as these three land cover types (Classes 2 and 1) had sparse vegetation or bare soil cover and commonly (greater than or equal to 67 percent of observations) had dry soil conditions. The investigation of land cover detailed in this report could inform future efforts to map land cover more precisely via higher resolution remote sensing or ground-based surveying or could be incorporated with other environmental monitoring data to characterize habitat and hydrology of the wetland complexes at Dixie Meadows.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241029","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Sankey, J.B., Bransky, N.D., and Caster, J.J., 2024, Investigation of land cover within wetland complexes at Dixie Meadows, Churchill County, Nevada, from October 2015 to January 2022: U.S. Geological Survey Open-File Report 2024–1029, 10 p., https://doi.org/10.3133/ofr20241029.","productDescription":"Report: vi, 10 p.; Data Release","numberOfPages":"10","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-150955","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":494217,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118272.htm","linkFileType":{"id":5,"text":"html"}},{"id":465474,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1029/images/"},{"id":465473,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1029/ofr20241029.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2024-1029 XML"},{"id":465466,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90U1VAM","text":"USGS data release","linkHelpText":"Land cover classification data for wetland complexes at Dixie Meadows, Nevada from October 2015 to January 2022"},{"id":465472,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241029/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1029 HTML"},{"id":465465,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1029/ofr20241029.pdf","text":"Report","size":"5.93 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1029 PDF"},{"id":465464,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1029/coverthb.jpg"}],"country":"United States","state":"Nevada","county":"Churchill County","otherGeospatial":"Dixie Meadows","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.0333,\n 39.808333\n ],\n [\n -118.091667,\n 39.808333\n ],\n [\n -118.091667,\n 39.75\n ],\n [\n -118.0333,\n 39.75\n ],\n [\n -118.0333,\n 39.808333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
The topography of New Hampshire ranges from the Coastal Lowlands to the Eastern New England Upland to the White Mountains region. High-quality statewide elevation data are useful in managing this very diverse landscape. For example, the short coastline, including the Great Bay estuary and the Hampton-Seabrook marshes, is of disproportionately high value to New Hampshire’s tourist economy. The vulnerability of the coast to the effects of sea-level rise underscores the need for accurate, high-quality nearshore topographic elevation data and offshore bathymetric data to effectively manage the coast’s valuable resources, which include important fisheries, habitat, and infrastructure. Another important use for accurate elevation data in New Hampshire is in the evaluation of flood hazards and their potential environmental and infrastructure effects. This evaluation includes mapping of inundation and sediment transport, and assessing the associated costs of flooding. Addressing this challenge requires detailed knowledge of both surface topography and inland bathymetry. Other important activities having a substantial economic element and needing accurate elevation data include geologic resource assessment and hazard mitigation, urban and regional planning, infrastructure and construction management, and cultural resources preservation and management. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional model of the Earth’s surface and aboveground features.
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Hampshire\",\"nation\":\"USA \"}}]}","contact":"Director, National Geospatial Program
U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
Reston, VA 20192
Email: 3DEP@usgs.gov
","tableOfContents":"Prevention and early detection of invasive species are championed as the most cost-effective and efficient strategies for reducing or preventing negative impacts on ecosystems. Spotted lanternfly (SLF), Lycorma delicatula, is a recently introduced invasive insect whose range in the United States has been expanding rapidly since it was first discovered in Pennsylvania in 2014. Feeding by this planthopper can cause severe impacts on agricultural production, particularly grapes (Vitis spp.). Human visual surveys are the most common search method employed for detection but can be ineffective due to the insect's cryptic egg masses and low density during early stages of infestation. Therefore, finding alternative early detection methods has become a priority for agencies tasked with addressing SLF management. This study experimentally tested whether trained detector dogs could improve the probability of detecting SLF in both agricultural and forest settings. We surveyed transects in 20 vineyards and their adjacent wooded areas in Pennsylvania and New Jersey, USA, and used a multiscale occupancy model to estimate detection probability achieved by human observers and detection dogs as a function of SLF infestation level, weather, and habitat covariates. We modeled transect-level occupancy of SLF as a function of infestation level, habitat type, topographic position index, and distance to forests. Occupancy probability of SLF was higher on vines within vineyards than in forests, and occupancy declined with increasing distance from forests, which is informative for future search efforts. Detection probability of SLF was lower at forested sites but was higher at high infestation sites. Detection dogs had a lower detection probability than humans in the vineyards, but the detection probability of dogs was >3× greater than that of humans in forested sites. Our study suggests that detection dogs are more effective than human visual searches as an early detection method for SLF in forested areas, and utilizing detector dogs could strengthen SLF early detection efforts. This study demonstrates the potential applicability of using canine-assisted search strategies combined with occupancy models to enhance the surveillance and prevention of other difficult-to-detect invasive species.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70113","usgsCitation":"Fuller, A.K., Augustine, B., Clifton, E., Hajek, A., Blumenthal, A., Beese, J., Hurt, A., and Brown-Lima, C., 2024, Effectiveness of canine-assisted surveillance and human searches for early detection of invasive spotted lanternfly: Ecological Applications, v. 15, no. 12, e70113, 22 p., https://doi.org/10.1002/ecs2.70113.","productDescription":"e70113, 22 p.","ipdsId":"IP-161109","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466698,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70113","text":"Publisher Index Page"},{"id":466010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, 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Conference","active":true,"usgs":false}],"preferred":false,"id":922720,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hurt, Aimee","contributorId":347881,"corporation":false,"usgs":false,"family":"Hurt","given":"Aimee","affiliations":[{"id":40629,"text":"Working Dogs for Conservation","active":true,"usgs":false}],"preferred":false,"id":922721,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brown-Lima, Carrie J.","contributorId":347882,"corporation":false,"usgs":false,"family":"Brown-Lima","given":"Carrie J.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922722,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70261925,"text":"70261925 - 2024 - Nitrogen deposition weakens soil carbon control of nitrogen dynamics across the contiguous United States","interactions":[],"lastModifiedDate":"2025-01-03T15:17:09.57762","indexId":"70261925","displayToPublicDate":"2024-12-26T09:08:36","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Nitrogen deposition weakens soil carbon control of nitrogen dynamics across the contiguous United States","docAbstract":"Anthropogenic nitrogen (N) deposition is unequally distributed across space and time, with inputs to terrestrial ecosystems impacted by industry regulations and variations in human activity. Soil carbon (C) content normally controls the fraction of mineralized N that is nitrified (ƒnitrified), affecting N bioavailability for plants and microbes. However, it is unknown whether N deposition has modified the relationships among soil C, net N mineralization, and net nitrification. To test whether N deposition alters the relationship between soil C and net N transformations, we collected soils from coniferous and deciduous forests, grasslands, and residential yards in 14 regions across the contiguous United States that vary in N deposition rates. We quantified rates of net nitrification and N mineralization, soil chemistry (soil C, N, and pH), and microbial biomass and function (as beta-glucosidase (BG) and N-acetylglucosaminidase (NAG) activity) across these regions. Following expectations, soil C was a driver of ƒnitrified across regions, whereby increasing soil C resulted in a decline in net nitrification and ƒnitrified. The ƒnitrified value increased with lower microbial enzymatic investment in N acquisition (increasing BG:NAG ratio) and lower active microbial biomass, providing some evidence that heterotrophic microbial N demand controls the ammonium pool for nitrifiers. However, higher total N deposition increased ƒnitrified, including for high soil C sites predicted to have low ƒnitrified, which decreased the role of soil C as a predictor of ƒnitrified. Notably, the drop in contemporary atmospheric N deposition rates during the 2020 COVID-19 pandemic did not weaken the effect of N deposition on relationships between soil C and ƒnitrified. Our results suggest that N deposition can disrupt the relationship between soil C and net N transformations, with this change potentially explained by weaker microbial competition for N. Therefore, past N inputs and soil C should be used together to predict N dynamics across terrestrial ecosystems.
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The volcano has been monitored by a network of permanent, short period and broadband seismometers. I used the continuous waveform data from that network starting in 2012 to generate a catalog of seismicity that enhances the US Geological Survey Hawaiian Volcano Observatory’s public seismic catalog with four times the number of earthquakes, which were then grouped by waveform similarity. Analysis of subtle delays in the timing of arrivals of scattered waves between pairs of earthquakes in this catalog yields a history of small changes in the shallow seismic velocity structure of the volcano. Seismic velocities have been shown at other volcanoes to change during unrest and eruption. My results show a decrease in seismic velocity centered on the summit beginning in September 2022, corresponding to the onset of a vigorous precursory swarm of seismic activity and shallow inflation. During the eruption itself, I observe large changes due likely to dike opening along the northeast rift zone and deflation of the summit reservoir. However, seismic velocity changes associated with non-volcanic sources such as ground shaking from large earthquakes and meteorological influences at seasonal and diurnal time scales are also observed, and these dominate the velocity changes prior to the eruption. Proper accounting of these effects will be a requirement for use in real-time monitoring, and this work serves as a starting point in that endeavor for Mauna Loa.","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-024-01793-x","usgsCitation":"Hotovec-Ellis, A.J., 2024, Seismic velocity changes from repetitive seismicity at Mauna Loa prior to and during its 2022 eruption: Bulletin of Volcanology, v. 87, 9, 18 p., https://doi.org/10.1007/s00445-024-01793-x.","productDescription":"9, 18 p.","ipdsId":"IP-167796","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466699,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-024-01793-x","text":"Publisher Index Page"},{"id":465750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Loa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.6256226783436,\n 19.49598540207714\n ],\n [\n -155.6256226783436,\n 19.445066390638345\n ],\n [\n -155.56470750742835,\n 19.445066390638345\n ],\n [\n -155.56470750742835,\n 19.49598540207714\n ],\n [\n -155.6256226783436,\n 19.49598540207714\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"87","noUsgsAuthors":false,"publicationDate":"2024-12-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Hotovec-Ellis, Alicia J. 0000-0003-1917-0205","orcid":"https://orcid.org/0000-0003-1917-0205","contributorId":211785,"corporation":false,"usgs":true,"family":"Hotovec-Ellis","given":"Alicia","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":922542,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70262837,"text":"70262837 - 2024 - An intercomparison of DOC estimated from fDOM sensors in wildfire affected streams of the western United States","interactions":[],"lastModifiedDate":"2025-01-24T16:00:41.024114","indexId":"70262837","displayToPublicDate":"2024-12-25T08:54:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"An intercomparison of DOC estimated from fDOM sensors in wildfire affected streams of the western United States","docAbstract":"Wildfires in the western United States (US) have been demonstrated to affect water quality, including dissolved organic carbon (DOC), in streams. Elevated post-wildfire DOC concentration poses a potential risk to drinking water treatment systems. In-stream measurements of fluorescent dissolved organic matter (fDOM), a proxy for DOC, have shown potential to detect dynamic changes in DOC. High frequency monitoring of water temperature, turbidity, and fDOM was used in conjunction with discrete sampling during targeted storm events and at fixed intervals to estimate DOC in five western US streams following wildfires in 2020 and 2021 with the objective to characterise and compare responses to wildfire among sites. The elevated turbidity conditions typical after wildfire presented a challenge to fDOM measurements and there was a need to identify appropriate turbidity corrections at burned sites. A combination of established and novel methods corrected fDOM concentrations for turbidity effects up to 800 Formazin nephelometric units (FNU). Pre-wildfire high frequency water quality data in adjacent burned and unburned watersheds allowed for separation of climate effects on DOC at one of the sites. Hydrology, climate and landcover were more important drivers of post-wildfire DOC yield than wildfire characteristics. Seasonal patterns of DOC were unchanged by wildfire in snowmelt-driven watersheds. Large, transient spikes in DOC concentration following frontal and convective storms were observed post-wildfire at all burned sites, but not at the unburned site. These spikes often exceeded operational thresholds for drinking water treatment. This study highlights the ability to develop high frequency DOC estimates in surface waters up to 800 FNU using fDOM sensors and targeted storm sampling and emphasises the value of high frequency pre-wildfire data in adjacent burned and unburned watersheds for separating climate and wildfire effects.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70023","usgsCitation":"Akie, G.A., Clow, D.W., Murphy, S.F., Clark, G.D., Meador, M.R., and Ebel, B., 2024, An intercomparison of DOC estimated from fDOM sensors in wildfire affected streams of the western United States: Hydrological Processes, v. 38, no. 12, e70023, 20 p., https://doi.org/10.1002/hyp.70023.","productDescription":"e70023, 20 p.","ipdsId":"IP-164617","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":489141,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70023","text":"Publisher Index Page"},{"id":481139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Colorado, Montana, 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\"}}]}","volume":"38","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Akie, Garrett Alexander 0000-0002-6356-7106","orcid":"https://orcid.org/0000-0002-6356-7106","contributorId":290236,"corporation":false,"usgs":true,"family":"Akie","given":"Garrett","email":"","middleInitial":"Alexander","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":924966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clark, Gregory D. 0000-0003-0066-8193 gmclark@usgs.gov","orcid":"https://orcid.org/0000-0003-0066-8193","contributorId":224364,"corporation":false,"usgs":true,"family":"Clark","given":"Gregory","email":"gmclark@usgs.gov","middleInitial":"D.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924967,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meador, Michael R. 0000-0001-5956-3340 mrmeador@usgs.gov","orcid":"https://orcid.org/0000-0001-5956-3340","contributorId":219878,"corporation":false,"usgs":true,"family":"Meador","given":"Michael","email":"mrmeador@usgs.gov","middleInitial":"R.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":924968,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ebel, Brian A. 0000-0002-5413-3963","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":211845,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":924969,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267704,"text":"70267704 - 2024 - Gene flow prevents genetic diversity loss despite small effective population size in fragmented grizzly bear (Ursus arctos) populations","interactions":[],"lastModifiedDate":"2025-05-29T16:45:22.117743","indexId":"70267704","displayToPublicDate":"2024-12-25T08:37:08","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Gene flow prevents genetic diversity loss despite small effective population size in fragmented grizzly bear (Ursus arctos) populations","docAbstract":"Genetic monitoring is important in small, fragmented populations that rely on gene flow to maintain genetic diversity. The Selkirk, Yaak, and Cabinet grizzly bear (Ursus arctos) populations are among the smallest in North America and are near the southernmost extent of the species’ range. These populations received little to no effective migration for generations but have recently experienced increased gene flow through natural migration and a population augmentation program. A long-term dataset of grizzly bear microsatellite genotypes from 1973 to 2021 presented a unique opportunity to examine genetic trends in these populations over time. We used this dataset of 464 bears to evaluate if gene flow affected observed heterozygosity (HO), expected heterozygosity (HE), allelic richness (AR), and average pairwise relatedness (r) in each of these populations. We also estimated effective population size (Ne) using the temporal and linkage disequilibrium (LD) methods. Post gene flow, AR increased in the Selkirk and Cabinet populations and r decreased in all three populations. We did not observe any significant changes in HE or HO, but HE values in our populations were significantly higher than those estimated using a model without gene flow. Our Ne estimates were consistent between the temporal and LD methods and ranged from 15.2 to 15.8, 15.4–17.5, and 5.6–8.9 for the Selkirk, Yaak, and Cabinet populations, respectively. Overall, our findings indicate that gene flow is increasing or maintaining genetic diversity in these populations. However, Ne remains low and additional connectivity or augmentation may be needed, particularly in the Cabinet population.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10592-024-01666-y","usgsCitation":"Turnock, M., Teisberg, J., Kasworm, W., Falcy, M.R., Proctor, M., and Waits, L., 2024, Gene flow prevents genetic diversity loss despite small effective population size in fragmented grizzly bear (Ursus arctos) populations: Conservation Genetics, v. 26, p. 279-291, https://doi.org/10.1007/s10592-024-01666-y.","productDescription":"13 p.","startPage":"279","endPage":"291","ipdsId":"IP-166778","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488451,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10592-024-01666-y","text":"Publisher Index Page"},{"id":486760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Idaho, Montana, Washington","otherGeospatial":"British Columbia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.3821304045668,\n 50.132013169608314\n ],\n [\n -118.3821304045668,\n 47.95130403023194\n ],\n [\n -114.75140702492735,\n 47.95130403023194\n ],\n [\n -114.75140702492735,\n 50.132013169608314\n ],\n [\n -118.3821304045668,\n 50.132013169608314\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","noUsgsAuthors":false,"publicationDate":"2024-12-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Turnock, Megan F.","contributorId":356036,"corporation":false,"usgs":false,"family":"Turnock","given":"Megan F.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":938583,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Teisberg, Justin E.","contributorId":356039,"corporation":false,"usgs":false,"family":"Teisberg","given":"Justin E.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":938584,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kasworm, Wayne F.","contributorId":356042,"corporation":false,"usgs":false,"family":"Kasworm","given":"Wayne F.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":938585,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Falcy, Matthew Richard 0000-0002-3332-2239","orcid":"https://orcid.org/0000-0002-3332-2239","contributorId":288500,"corporation":false,"usgs":true,"family":"Falcy","given":"Matthew","email":"","middleInitial":"Richard","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938586,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Proctor, Michael F.","contributorId":356045,"corporation":false,"usgs":false,"family":"Proctor","given":"Michael F.","affiliations":[{"id":84901,"text":"Birchdale Ecological, Ltd.","active":true,"usgs":false}],"preferred":false,"id":938587,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waits, Lisette P.","contributorId":356046,"corporation":false,"usgs":false,"family":"Waits","given":"Lisette P.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":938588,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70263381,"text":"70263381 - 2024 - Sensitivity analysis of a dynamic vegetation-sediment transport model using equadratures: Exploring inorganic accretion on a marsh platform","interactions":[],"lastModifiedDate":"2025-02-10T16:17:14.052147","indexId":"70263381","displayToPublicDate":"2024-12-24T13:39:34","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7357,"text":"JGR Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity analysis of a dynamic vegetation-sediment transport model using equadratures: Exploring inorganic accretion on a marsh platform","docAbstract":"Salt marsh systems require a net import of inorganic sediment to maintain their structure in response to sea‐level rise. Marshes are affected by physical processes including tides, waves, sediment transport, and the influence of vegetation, and these processes interact in complex ways leading to sediment accretion or erosion. We implement a 3‐D hydrodynamic sediment transport model in an idealized marsh‐bay complex with a gently sloping edge, and use it as a laboratory to explore the processes leading to bed elevation change through the bay‐marsh continuum. We use the novel equadratures method for efficient sensitivity analysis to test the roles of wave, vegetation, and sediment parameters on wave dissipation, bed shear stress, sediment fluxes, and deposition and erosion across a transect spanning bay shallows to the marsh. Within the explored bounds of parameter uncertainty, significant wave height (Hsig), settling velocity (ws), and critical shear stress (τcrit) most strongly affect accretion on the marsh platform. Deposition is affected more by parameter‐parameter interactions, that is, both τcrit and ws or both Hsig and ws, than by a single parameter varying alone. The sediment that accretes on the marsh platform originates beyond the marsh edge, indicating that the dynamics of the adjacent mudflat are important for predicting the fate of the marsh. Applying efficient sensitivity analysis techniques can empower process‐based models to test more parameters, larger ranges, and longer timeframes, enabling future predictions of marsh response to sea‐level rise based on physical processes
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JF007945","usgsCitation":"Allen, R., Ganju, N., Kalra, T., Aretxabaleta, A., and Lacy, J.R., 2024, Sensitivity analysis of a dynamic vegetation-sediment transport model using equadratures: Exploring inorganic accretion on a marsh platform: JGR Earth Surface, v. 129, no. 10, e2024JF007945, 21 p., https://doi.org/10.1029/2024JF007945.","productDescription":"e2024JF007945, 21 p.","ipdsId":"IP-159248","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":487466,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024jf007945","text":"Publisher Index Page"},{"id":481871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"China Camp march, San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.5,\n 38.016667\n ],\n [\n -122.5,\n 38\n ],\n [\n -122.466667,\n 38\n ],\n [\n -122.466667,\n 38.016667\n ],\n [\n -122.5,\n 38.016667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"129","issue":"10","noUsgsAuthors":false,"publicationDate":"2024-12-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Rachel 0000-0002-0287-6466","orcid":"https://orcid.org/0000-0002-0287-6466","contributorId":216002,"corporation":false,"usgs":true,"family":"Allen","given":"Rachel","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":926716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":926717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kalra, Tarandeep 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":304428,"corporation":false,"usgs":false,"family":"Kalra","given":"Tarandeep","email":"tkalra@usgs.gov","affiliations":[{"id":66067,"text":"Jupiter Intelligence, San Mateo, California","active":true,"usgs":false}],"preferred":false,"id":926718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aretxabaleta, Alfredo 0000-0002-9914-8018 aaretxabaleta@usgs.gov","orcid":"https://orcid.org/0000-0002-9914-8018","contributorId":140090,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo","email":"aaretxabaleta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":926719,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":926720,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261835,"text":"70261835 - 2024 - Self-guided decision support groundwater modelling with Python","interactions":[],"lastModifiedDate":"2024-12-30T15:49:23.123549","indexId":"70261835","displayToPublicDate":"2024-12-24T09:16:53","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19861,"text":"Journal of Open Source Education","active":true,"publicationSubtype":{"id":10}},"title":"Self-guided decision support groundwater modelling with Python","docAbstract":"The GMDSI tutorial notebooks repository provides learners with a comprehensive set of tutorials for self-guided training on decision-support groundwater modelling using Python-based tools. Although targeted at groundwater modelling, they are based around model-agnostic tools and readily transferable to other environmental modelling workflows. The tutorials are divided into three parts. The first covers fundamental theoretical concepts. These are intended as background reading for reference on an as-needed basis. Tutorials in the second part introduce learners to some of the core concepts parameter estimation in a groundwater modelling context, as well as providing a gentle introduction to the PEST, PEST++ and pyEMU software. Lastly, the third part demonstrates how to implement highly-parameterized applied decision-support modelling workflows. The tutorials aim to provide examples of both “how to use” the software as well as “how to think” about using the software. A key advantage to using notebooks in this context is that the workflows described run the same code as practitioners would run on a large-scale real- world application. Using a small synthetic model facilitates rapid progression through the workflow.","language":"English","publisher":"Open Journals","doi":"10.21105/jose.00240","usgsCitation":"Hugman, R., White, J., Fienen, M., Hemmings, B., and Markovich, K., 2024, Self-guided decision support groundwater modelling with Python: Journal of Open Source Education, v. 7, no. 82, 240, 6 p., https://doi.org/10.21105/jose.00240.","productDescription":"240, 6 p.","ipdsId":"IP-166010","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":466700,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.21105/jose.00240","text":"Publisher Index Page"},{"id":465530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"82","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hugman, Rui 0000-0003-0891-3886","orcid":"https://orcid.org/0000-0003-0891-3886","contributorId":299138,"corporation":false,"usgs":false,"family":"Hugman","given":"Rui","affiliations":[{"id":64778,"text":"Univeristy of Flinders","active":true,"usgs":false}],"preferred":false,"id":921991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Jeremy T. 0000-0002-4950-1469","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":214251,"corporation":false,"usgs":false,"family":"White","given":"Jeremy T.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":921992,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hemmings, Brioch","contributorId":260167,"corporation":false,"usgs":false,"family":"Hemmings","given":"Brioch","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":921994,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Markovich, Katie","contributorId":347560,"corporation":false,"usgs":false,"family":"Markovich","given":"Katie","affiliations":[{"id":83190,"text":"INTERA Geosciences","active":true,"usgs":false}],"preferred":false,"id":921995,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70262817,"text":"70262817 - 2024 - A comparison of survival and behavior of lake whitefish following transmitter implantation using electro- or chemical immobilization","interactions":[],"lastModifiedDate":"2025-01-23T15:25:55.35842","indexId":"70262817","displayToPublicDate":"2024-12-24T08:18:56","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of survival and behavior of lake whitefish following transmitter implantation using electro- or chemical immobilization","docAbstract":"Background
The number of telemetry studies focused on lake whitefish (Coregonus clupeaformis) in the Laurentian Great Lakes has steadily increased over the last decade, but field tests of immobilization methods used for tag implantation, which have the potential to affect survival and behavior of fish after release, are lacking. We compared post-tagging survival and behavior of lake whitefish that were immobilized for tag implantation using electroimmobilization via a transcutaneous electrical nerve stimulation (TENS) unit or by chemical immobilization via exposure to 10% eugenol.
Results
Acoustic tags were implanted into 126 adult lake whitefish (N = 126; N = 67 TENS treatment group, N = 59 eugenol treatment group) collected from the Fox River, Wisconsin, during the spawning period in November 2021. We found no significant differences between treatments in the number of days that lake whitefish spent in the Fox River following tagging (TENS mean = 13.4 days, eugenol mean = 14.7), and also found that the proportions of fish within each treatment group that returned to the Fox River during fall 2022 (51% from TENS treatment group, 49% from eugenol treatment group) did not differ from the proportions for all fish that were confirmed to be alive at that time. The best Cormack–Jolly–Seber model indicated no differences in survival between the two treatment groups (monthly survival = 0.980, 95% CI 0.970–0.987). Fish immobilized using TENS underwent almost immediate induction and recovery from surgeries, while fish immobilized using eugenol had induction times that ranged 167–487 s (mean = 347 s) and recovery times that ranged 51–2358 s (mean = 1242 s).
Conclusions
Short- and long-term behavior (time to exit of Fox River, return to Fox River in the next spawning season) and monthly survival estimates of lake whitefish did not differ between the immobilization treatments. Either method may be suitable for immobilization during tag implantation, but the additional time needed for induction and recovery of fish when using eugenol may be a limiting factor in some field-based tagging situations.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s40317-024-00393-y","usgsCitation":"Izzo, L., Dembkowski, D., Binder, T., Hansen, S., Vandergoot, C., and Isermann, D.A., 2024, A comparison of survival and behavior of lake whitefish following transmitter implantation using electro- or chemical immobilization: Animal Biotelemetry, v. 12, 39, 10 p., https://doi.org/10.1186/s40317-024-00393-y.","productDescription":"39, 10 p.","ipdsId":"IP-169427","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481041,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-024-00393-y","text":"Publisher Index Page"},{"id":480989,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Fox River, Green Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.05808785412178,\n 44.69153434457186\n ],\n [\n -88.05808785412178,\n 44.4951220149938\n ],\n [\n -87.86450882150862,\n 44.4951220149938\n ],\n [\n -87.86450882150862,\n 44.69153434457186\n ],\n [\n -88.05808785412178,\n 44.69153434457186\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-12-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Izzo, Lisa K.","contributorId":349826,"corporation":false,"usgs":false,"family":"Izzo","given":"Lisa K.","affiliations":[{"id":65894,"text":"Wisconsin Cooperative Fishery Research Unit","active":true,"usgs":false}],"preferred":false,"id":924889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dembkowski, Daniel J.","contributorId":349827,"corporation":false,"usgs":false,"family":"Dembkowski","given":"Daniel J.","affiliations":[{"id":65894,"text":"Wisconsin Cooperative Fishery Research Unit","active":true,"usgs":false}],"preferred":false,"id":924890,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Binder, Thomas R.","contributorId":349828,"corporation":false,"usgs":false,"family":"Binder","given":"Thomas R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":924891,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, Scott P.","contributorId":349829,"corporation":false,"usgs":false,"family":"Hansen","given":"Scott P.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":924892,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vandergoot, Christopher S.","contributorId":349830,"corporation":false,"usgs":false,"family":"Vandergoot","given":"Christopher S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":924893,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924894,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70261520,"text":"sim3514 - 2024 - Geologic map and structure sections along the southern part of the Bartlett Springs Fault Zone and adjacent areas from Cache Creek to Lake Berryessa, northern Coast Ranges, California","interactions":[],"lastModifiedDate":"2025-08-15T16:11:32.54982","indexId":"sim3514","displayToPublicDate":"2024-12-23T10:32:03","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3514","displayTitle":"Geologic Map and Structure Sections Along the Southern Part of the Bartlett Springs Fault Zone and Adjacent Areas from Cache Creek to Lake Berryessa, Northern Coast Ranges, California","title":"Geologic map and structure sections along the southern part of the Bartlett Springs Fault Zone and adjacent areas from Cache Creek to Lake Berryessa, northern Coast Ranges, California","docAbstract":"Located in the Coast Ranges of northern California, the Bartlett Springs Fault Zone is the easternmost fault in the San Andreas Fault system in northern California. The fault is a right-lateral, strike-slip structure considered capable of producing an earthquake of moment magnitude 7. The purpose of this mapping is to better characterize the geology and earthquake hazards associated with the southern part of the Bartlett Springs Fault Zone and to help identify any evidence of active uplift on the faults bounding the Coast Ranges. Although the area immediately surrounding the Bartlett Springs Fault Zone is sparsely populated, its southern segment presents a potential seismic hazard to northern California communities as far away as the San Francisco Bay region and Sacramento. There are also nearby water resources, mineral resources, and public lands used for public recreation.
The Coast Ranges of northern California are a series of northwest-southeast-oriented mountain ranges and valleys located north of the San Francisco Bay region, between the Pacific Ocean to the west and the Sacramento Valley to the east. The region has rugged terrain, high mountain peaks that reach more than 2,400 meters above sea level, isolated and narrow valley bottoms on which most human settlements are located, and large drainage systems that tend to follow the northwest-southeast-oriented topographic grain. The physiographic character of the region is shaped by its bedrock geology, deformational history, and active faulting.
The basement rocks of the northern Coast Ranges consist of the Franciscan Complex and the Great Valley complex, the latter of which consists of two informal units, the Coast Range ophiolite and the Great Valley sequence. The Franciscan Complex and the Great Valley complex are in structural contact along the Coast Range Fault, a regional-scale structure and fundamental crustal boundary.
The Franciscan Complex and the Great Valley complex are superposed by active, northwest-southeast-striking strike-slip faults that are associated with seismicity swarms. These active strike-slip faults can produce moderate to large earthquakes that have moment magnitudes of 7–8. In places, these active structures bound large ranges and valleys, suggesting that much of the modern topographic expression is the result of active deformation processes.
This report contains new 1:24,000-scale geologic mapping along the southern part of the Bartlett Springs Fault Zone between Clear Lake and Lake Berryessa. The map area spans 738 square kilometers in northern Napa County, southern Lake County, and parts of Yolo and Colusa Counties. The south and east borders of the map are 90 kilometers north of San Francisco and 70 kilometers west of Sacramento, respectively. The map area is within the Knoxville mining district, which has a history of mercury and gold mining dating back to the mid-19th century. The two main towns in the region, Lower Lake and Clearlake, California, are west-northwest of the map area. Approximately 71,000 people live in the cities and rural communities located within a 40-kilometer radius of the center of the map area.
The bedrock geology, cross sections, and structural data presented herein are critical for evaluating the long-term evolution of the Bartlett Springs Fault Zone. This work will supplement studies on local seismic hazards, liquefaction potential, landslide hazards, earthquake geology, natural resources, groundwater resources, engineering geology, and tectonic history by providing the background information for site-specific investigations on these subjects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3514","usgsCitation":"Melosh, B.L., Bodtker, J.W., and Valin, Z.C., 2024, Geologic map and structure sections along the southern part of the Bartlett Springs Fault Zone and adjacent areas from Cache Creek to Lake Berryessa, northern Coast Ranges, California: U.S. Geological Survey Scientific Investigations Map 3514, 2 sheets, scale 1:24,000, 20 p. pamphlet, https://doi.org/10.3133/sim3514.","productDescription":"Pamphlet: vi, 20 p.; 2 Sheets: 46.15 x 78.86 inches and 58.26 x 41.78 inches; Data Release","numberOfPages":"20","additionalOnlineFiles":"Y","ipdsId":"IP-128914","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":494218,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118060.htm","linkFileType":{"id":5,"text":"html"}},{"id":465095,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1YJRCZD","text":"USGS Data Release","description":"Melosh, B.L., Bodtker, J.W., Valin, Z.C., and Sullivan, K., 2024, Geospatial database of the geologic map and structure sections along the southern part of the Bartlett Springs Fault Zone and adjacent areas from Cache Creek to Lake Berryessa, northern Coast Ranges, California: U.S. Geological Survey data release, https://doi.org/10.5066/P1YJRCZD.","linkHelpText":"Geospatial database of the geologic map and structure sections along the southern part of the Bartlett Springs Fault Zone and adjacent areas from Cache Creek to Lake Berryessa, northern Coast Ranges, California"},{"id":465094,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3514/covrthb.jpg"},{"id":465093,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3514/sim3514_sheet2.pdf","text":"Sheet 2","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":465092,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3514/sim3514_sheet1.pdf","text":"Sheet 1","size":"30 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":465091,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3514/sim3514_pamphlet.pdf","text":"Pamphlet","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"Northern Coast Ranges","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.5457,\n 39.0012\n ],\n [\n -122.5457,\n 38.6099\n ],\n [\n -122.2368,\n 38.6099\n ],\n [\n -122.2368,\n 39.0012\n ],\n [\n -122.5457,\n 39.0012\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
350 N. Akron Rd.
Moffett Field, CA 94035
The rapid diversification of terminology associated with invasion ecology is a known barrier to effective communication and management. These challenges are magnified by the addition of terms and concepts related to climate-induced range-shifting taxa and/or changes to impacts. Further, institutional policies and terminologies for invasive species introduce new ambiguities when considering climate change. To alleviate communication and application challenges, we introduce a conceptual framework that organizes climate-related invasion terms, revealing ambiguities and gaps. Additionally, we illustrate how these ambiguities can affect management with four case studies and consider situations where resolution can improve policy and management outcomes. The framework can help users avoid inconsistent use of terminology, and prioritize when to address management and policy consequences related to associated terminological ambiguity.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.tree.2024.08.005","usgsCitation":"Fusco, E.J., Falk, B., Heimowitz, P.J., Lieurance, D., Parsons, E., Rottler, C.M., Thurman, L., and Evans, A., 2024, The emerging invasive species and climate change lexicon: Trends in Ecology and Evolution, v. 39, no. 12, p. 1119-1129, https://doi.org/10.1016/j.tree.2024.08.005.","productDescription":"11 p.","startPage":"1119","endPage":"1129","ipdsId":"IP-159995","costCenters":[{"id":49226,"text":"Northwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":491008,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.tree.2024.08.005","text":"Publisher Index Page"},{"id":481604,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fusco, Emily J.","contributorId":236821,"corporation":false,"usgs":false,"family":"Fusco","given":"Emily","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":925944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falk, Bryan G. 0000-0002-9690-5626","orcid":"https://orcid.org/0000-0002-9690-5626","contributorId":265395,"corporation":false,"usgs":false,"family":"Falk","given":"Bryan G.","affiliations":[{"id":54672,"text":"National Park Service, Everglades National Park, 40001 SR 9336, Homestead, Florida 33034, USA","active":true,"usgs":false}],"preferred":false,"id":925945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heimowitz, Paul J. 0000-0001-7291-0175","orcid":"https://orcid.org/0000-0001-7291-0175","contributorId":334250,"corporation":false,"usgs":true,"family":"Heimowitz","given":"Paul","email":"","middleInitial":"J.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":925946,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lieurance, Deah 0000-0001-8176-3146","orcid":"https://orcid.org/0000-0001-8176-3146","contributorId":293605,"corporation":false,"usgs":false,"family":"Lieurance","given":"Deah","email":"","affiliations":[{"id":63333,"text":"Agronomy Department, University of Florida","active":true,"usgs":false}],"preferred":false,"id":925947,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parsons, Elliott","contributorId":221123,"corporation":false,"usgs":false,"family":"Parsons","given":"Elliott","affiliations":[{"id":40328,"text":"State of Hawai‘i Division of Forestry and Wildlife, Pu‘u Wa‘awa‘a Forest Reserve","active":true,"usgs":false}],"preferred":false,"id":925948,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rottler, Caitlin M.","contributorId":138853,"corporation":false,"usgs":false,"family":"Rottler","given":"Caitlin","email":"","middleInitial":"M.","affiliations":[{"id":12546,"text":"Univ of Wyoming, Department of Botany, 1000 E. University Ave., Laramie, WY 82071; Univ of WY, Program in Ecology, 1000 E. University Ave., Laramie, WY 82071 USA","active":true,"usgs":false}],"preferred":false,"id":925949,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thurman, Lindsey 0000-0003-3142-4909","orcid":"https://orcid.org/0000-0003-3142-4909","contributorId":269425,"corporation":false,"usgs":true,"family":"Thurman","given":"Lindsey","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":925950,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Evans, Annette","contributorId":300029,"corporation":false,"usgs":false,"family":"Evans","given":"Annette","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":925951,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70267722,"text":"70267722 - 2024 - A comparative framework to develop transferable species distribution models for animal telemetry data","interactions":[],"lastModifiedDate":"2025-05-29T14:19:47.317741","indexId":"70267722","displayToPublicDate":"2024-12-22T09:12:20","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"A comparative framework to develop transferable species distribution models for animal telemetry data","docAbstract":"Species distribution models (SDMs) have become increasingly popular for making ecological inferences, as well as predictions to inform conservation and management. In predictive modeling, practitioners often use correlative SDMs that only evaluate a single spatial scale and do not account for differences in life stages. These modeling decisions may limit the performance of SDMs beyond the study region or sampling period. Given the increasing desire to develop transferable SDMs, a robust framework is necessary that can account for known challenges of model transferability. Here, we propose a comparative framework to develop transferable SDMs, which was tested using satellite telemetry data from green turtles (Chelonia mydas). This framework is characterized by a set of steps comparing among different models based on (1) model algorithm (e.g., generalized linear model vs. Gaussian process regression) and formulation (e.g., correlative model vs. hybrid model), (2) spatial scale, and (3) accounting for life stage. SDMs were fitted as resource selection functions and trained on data from the Gulf of Mexico with bathymetric depth, net primary productivity, and sea surface temperature as covariates. Independent validation datasets from Brazil and Qatar were used to assess model transferability. A correlative SDM using a hierarchical Gaussian process regression (HGPR) algorithm exhibited greater transferability than a hybrid SDM using HGPR, as well as correlative and hybrid forms of hierarchical generalized linear models. Additionally, models that evaluated habitat selection at the finest spatial scale and that did not account for life stage proved to be the most transferable in this study. The comparative framework presented here may be applied to a variety of species, ecological datasets (e.g., presence-only, presence-absence, mark-recapture), and modeling frameworks (e.g., resource selection functions, step selection functions, occupancy models) to generate transferable predictions of species–habitat associations. We expect that SDM predictions resulting from this comparative framework will be more informative management tools and may be used to more accurately assess climate change impacts on a wide array of taxa.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70136","usgsCitation":"Cullen, J., Domit, C.A., Lamont, M., Marshall, C., Santos, A.J., Sasso, C.R., Al Ansi, M., Hart, K., and Fuentes, M.M., 2024, A comparative framework to develop transferable species distribution models for animal telemetry data: Ecosphere, v. 15, no. 12, e70136, 20 p., https://doi.org/10.1002/ecs2.70136.","productDescription":"e70136, 20 p.","ipdsId":"IP-155304","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488433,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70136","text":"Publisher Index Page"},{"id":486722,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil, Qatar, Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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83255000","active":true,"usgs":false}],"preferred":false,"id":938643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":222403,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":938644,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marshall, Christopher D.","contributorId":356063,"corporation":false,"usgs":false,"family":"Marshall","given":"Christopher D.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":938645,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Santos, Armando J.B.","contributorId":174284,"corporation":false,"usgs":false,"family":"Santos","given":"Armando","email":"","middleInitial":"J.B.","affiliations":[],"preferred":false,"id":938646,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sasso, Christopher R.","contributorId":296894,"corporation":false,"usgs":false,"family":"Sasso","given":"Christopher","email":"","middleInitial":"R.","affiliations":[{"id":64230,"text":"NOAA-NMFS Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":938647,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Al Ansi, Mehsin","contributorId":356065,"corporation":false,"usgs":false,"family":"Al Ansi","given":"Mehsin","affiliations":[{"id":54794,"text":"Qatar University","active":true,"usgs":false}],"preferred":false,"id":938648,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":220333,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":938649,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fuentes, Mariana M.P.B.","contributorId":331394,"corporation":false,"usgs":false,"family":"Fuentes","given":"Mariana","email":"","middleInitial":"M.P.B.","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":938650,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70261948,"text":"70261948 - 2024 - Sequoia groves of Yosemite: Visitor use and impacts monitoring","interactions":[],"lastModifiedDate":"2025-01-06T14:57:47.15225","indexId":"70261948","displayToPublicDate":"2024-12-22T07:51:11","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1689,"text":"Forests","active":true,"publicationSubtype":{"id":10}},"title":"Sequoia groves of Yosemite: Visitor use and impacts monitoring","docAbstract":"Despite being long-lived and massive, giant sequoias (Sequoiadendron giganteum (Lindl.) J. Bucholz) are susceptible to erosion given their relatively shallow root structure. Human-caused soil compaction and vegetation loss through social trails are primary drivers of erosion in giant sequoia groves, particularly for trees that are near formal trails and access roads. We develop a method to observe and quantify the near-tree impacts from park visitors and to relate the overall amount of use with ground cover impact parameters to assess whether the desired conditions of each grove are being met for the park to maintain a spectrum of recreational opportunities. We collected data on visitation, ground cover, soil compaction, and social trailing using a combination of targeted surveys and observations at the three giant sequoia groves in Yosemite National Park. The Mariposa Grove receives the most visitation, and use levels among groves were consistent with relative size and facilities available. Selected parameters for ground cover data were analyzed by comparing values within undisturbed versus trampling-disturbed subplots at both 0–2 m and 2–8 m. Exposed soil cover and compaction were generally higher in anthropogenically disturbed subplots versus undisturbed subplots, and vegetation cover was reduced in some disturbed subplots. Each grove had one surveyed tree where average soil compaction was ≥2.2 kg/cm2, which may limit root growth and impact seedling regeneration. Each of the three groves had some trees with social trail presence, yet less than 7% of mature trees within any grove were impacted by social trails, and most social trails were rated as having low impairment. Coupling soil compaction measurements and estimates of trampling-disturbed areas with mapping of social trail conditions within groves provides a general assessment of visitor-associated impacts to sequoia groves and can facilitate a relatively rapid way to track hotspot (i.e., increasingly impacted) trees over time.
","language":"English","publisher":"MDPI","doi":"10.3390/f15122256","usgsCitation":"Shiflett, S., Jenkins, J., Mattos, R., Ibsen, P.C., and Athearn, N., 2024, Sequoia groves of Yosemite: Visitor use and impacts monitoring: Forests, v. 15, no. 12, 2256, 19 p., https://doi.org/10.3390/f15122256.","productDescription":"2256, 19 p.","ipdsId":"IP-170087","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":466702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/f15122256","text":"Publisher Index Page"},{"id":465665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.6799910466818,\n 37.9097240904418\n ],\n [\n -119.6799910466818,\n 37.729468979298204\n ],\n [\n -119.43926891028742,\n 37.729468979298204\n ],\n [\n -119.43926891028742,\n 37.9097240904418\n ],\n [\n -119.6799910466818,\n 37.9097240904418\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Shiflett, Sheri A.","contributorId":347753,"corporation":false,"usgs":false,"family":"Shiflett","given":"Sheri A.","affiliations":[{"id":39509,"text":"National Park Service, Yosemite National Park","active":true,"usgs":false}],"preferred":false,"id":922376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Jeffery S.","contributorId":347754,"corporation":false,"usgs":false,"family":"Jenkins","given":"Jeffery S.","affiliations":[{"id":38695,"text":"University of California Merced","active":true,"usgs":false}],"preferred":false,"id":922377,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mattos, Rachel F.","contributorId":347755,"corporation":false,"usgs":false,"family":"Mattos","given":"Rachel F.","affiliations":[{"id":39509,"text":"National Park Service, Yosemite National Park","active":true,"usgs":false}],"preferred":false,"id":922378,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ibsen, Peter Christian 0000-0002-3436-9100","orcid":"https://orcid.org/0000-0002-3436-9100","contributorId":260735,"corporation":false,"usgs":true,"family":"Ibsen","given":"Peter","email":"","middleInitial":"Christian","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":922379,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Athearn, Nicole D.","contributorId":347757,"corporation":false,"usgs":false,"family":"Athearn","given":"Nicole D.","affiliations":[{"id":39509,"text":"National Park Service, Yosemite National Park","active":true,"usgs":false}],"preferred":false,"id":922380,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267895,"text":"70267895 - 2024 - New tools for a legacy problem: How isotope tracers inform area of concern actions in the St. Louis River in Lake Superior","interactions":[],"lastModifiedDate":"2025-06-06T14:54:41.50936","indexId":"70267895","displayToPublicDate":"2024-12-22T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21812,"text":"Journal of Great Lakes Research (JGLR)","active":true,"publicationSubtype":{"id":10}},"title":"New tools for a legacy problem: How isotope tracers inform area of concern actions in the St. Louis River in Lake Superior","docAbstract":"Numerous mercury (Hg) sources can contribute to biological burdens within the Great Lakes, including atmospheric deposition (e.g., precipitation), non-point source land runoff (e.g., watershed), and legacy contamination. Due to these different environmental entry points, it is often difficult to ascertain if legacy Hg contamination contributes to contemporary fish consumption advisories within Areas of Concern (AOCs), as designated by the United States-Canada Great Lakes Water Quality Agreement. In this study, we aimed to assess the contributions of legacy Hg to sediments in nearshore wetland habitats and co-located prey items (dragonfly larvae and yellow perch) within the St. Louis River AOC using Hg stable isotopes. We observed that nearshore sediments had the same Hg source portfolio as previously examined main channel sites. Furthermore, this data confirmed that two major Hg sources were contributing to sediments within nearshore regions of the St. Louis River AOC: legacy and watershed Hg. The contribution of legacy Hg was estimated in biota and demonstrated that up to 64% of the Hg in fish tissue in the lower estuary (St. Louis Bay) was from legacy sources, but that this percentage declined substantially when examining upstream regions of the AOC. These data indicate the influence of legacy Hg to the food web varies spatially within the St. Louis River. We further found that watershed Hg sources are an important Hg contributor to the St. Louis River, which likely applies to other impacted and unimpacted tributaries across the Great Lakes region.
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