We present the complete genome sequence of Splendidofilaria pectoralis, a nematode parasite of grouse (Aves: Galliformes: Tetraonini). Illumina paired-end reads were assembled by a de novo method followed by a finishing step. The raw and assembled data are publicly available via GenBank: Sequence Read Archive (SRR28509439) and assembled genome (JBFSWT000000000).
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Due to practical constraints, the number of response spectral periods was limited to three standard periods (0.3, 1.0, and 3.0 sec). We have recently developed the tools that are necessary to expand this functionality to include 22 periods (matching the current U.S. National Seismic Hazard Model periods) as well as the orientation-independent components (e.g., “RotD50”). We refer to ShakeMap products that include these extensions as “extended ShakeMaps.” The added level of complexity motivated us to also develop a user-friendly tool called the “ShakeMap Sampling Tool” (SST) that gives all the estimated shaking metrics for a specific location (or list of locations). Additionally, we develop a web application where users can input locations of interest and view/download the SST results. We further familiarize users with the concept of “Composite ShakeMaps.” For earthquakes sequences such as a mainshock and larger foreshocks and aftershocks, this provides a map of the maximum value of each shaking metric, which is useful for overall loss estimates, the full extent of ground failure triggering potential, and a better portrayal of the repeated shaking levels at a given point for a series of earthquakes. Such a site-specific shaking history facilitates earthquake forensics at building or infrastructure sites for which damage may be of concern, as described in the Disproportionate Damage Earthquake trigger specified in the IEBC (2018, Section 405.2.2) and in developing ATC-145 guidelines (Guidelines for Post-Earthquake Assessment, Repair, and Retrofit of Buildings). The composite ShakeMap can be combined with the SST for a variety of earthquake-hazard applications, such as systematically inferring triggering shaking estimates at specific sites of geotechnical interest for landsliding, liquefaction, and lateral-spreading hazards.
","conferenceTitle":"18th World Conerence on Earthquake Engineering","conferenceDate":"June 30 to July 5, 2024","conferenceLocation":"MIlan, Italy","language":"English","publisher":"World Conerence on Earthquake Engineering","usgsCitation":"Thompson, E.M., Hearne, M., Worden, C., Quitoriano, V., Cunningham, A., and Wald, D.J., 2025, Site-specific, extended ShakeMaps for earthquake engineering applications, 18th World Conerence on Earthquake Engineering, MIlan, Italy, June 30 to July 5, 2024, 9 p.","productDescription":"9 p.","ipdsId":"IP-162029","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":499756,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499755,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://proceedings-wcee.org/view.html?id=22651&conference=18WCEE"}],"country":"Turkey","city":"Kahramanmaraş","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 34,\n 40\n ],\n [\n 34,\n 35\n ],\n [\n 41,\n 35\n ],\n [\n 41,\n 40\n ],\n [\n 34,\n 40\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hearne, Mike 0000-0002-8225-2396 mhearne@usgs.gov","orcid":"https://orcid.org/0000-0002-8225-2396","contributorId":4659,"corporation":false,"usgs":true,"family":"Hearne","given":"Mike","email":"mhearne@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932196,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Worden, Charles 0000-0003-1181-685X cbworden@usgs.gov","orcid":"https://orcid.org/0000-0003-1181-685X","contributorId":152042,"corporation":false,"usgs":true,"family":"Worden","given":"Charles","email":"cbworden@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932197,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quitoriano, Vince 0000-0003-4157-1101 vinceq@usgs.gov","orcid":"https://orcid.org/0000-0003-4157-1101","contributorId":2582,"corporation":false,"usgs":true,"family":"Quitoriano","given":"Vince","email":"vinceq@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932198,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cunningham, Annabelle Elizabeth 0009-0001-0073-6144","orcid":"https://orcid.org/0009-0001-0073-6144","contributorId":352840,"corporation":false,"usgs":true,"family":"Cunningham","given":"Annabelle Elizabeth","affiliations":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"preferred":true,"id":932199,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932200,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271401,"text":"70271401 - 2025 - The influence of pre-existing structures on geothermal springs: Inferences from potential field mapping in Surprise Valley, CA and other sites In the northwestern Great Basin","interactions":[],"lastModifiedDate":"2025-09-11T14:11:27.743233","indexId":"70271401","displayToPublicDate":"2024-12-01T09:07:45","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"The influence of pre-existing structures on geothermal springs: Inferences from potential field mapping in Surprise Valley, CA and other sites In the northwestern Great Basin","docAbstract":"Surprise Valley, located in the northwestern Great Basin, is an asymmetric extensional basin that marks a major tectonic transition between the relatively un-extended volcanic Modoc Plateau to the west, and the Basin and Range to the east that has undergone 10-15% extension. In addition, it sits just north of the Walker Lane which accommodates up to 20% of dextral slip associated with Pacific-North American plate interactions.\nThermal springs issue from eight areas within Surprise Valley. Most of these occur within the basin and are not situated on the main basin forming range-front faults. As a result, efforts to resolve the structural setting of the valley’s hydrothermal system have relied on geophysics to characterize basin structure and geology. \nExtensive efforts to map the basin with ground and airborne magnetics have revealed a >35 km-long linear, intra-basin magnetic high, interpreted as a buried dike swarm. Geothermal springs on the eastern side of the valley, including Seifert hot springs, Leonards hot springs, and Surprise Valley hot springs (SVHS), are all situated along the magnetic high and occur at local breaks and bends in the anomaly, suggesting that fracture permeability is enhanced along the feature and particularly at these discontinuities. \nRecent studies, including drilling over the anomaly near SVHS that likely intersected dike material, as well as subsequent mapping and sampling of dikes outcropping along the anomaly on the playa surface south of SVHS, confirm (as previously inferred) that mafic intrusives are the principal source of the anomaly. Similar interpretations made in two other valleys (in southern Oregon and northwestern Nevada), where inferred intra-basin dikes appear to be spatially correlated with hot springs or prospective geothermal resource areas, suggest that the impact of pre-existing basement structure on hydrothermal activity may pertain more generally to other hydrothermal settings throughout the Great Basin. If so, efforts to map basement may enhance understanding structural controls on some geothermal systems.\nFurthermore, similarities across these disparate sites suggest that magmatism may play a much larger role in accommodating extension and influencing basin evolution across the western Great Basin than previously recognized.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Using the Earth to save the Earth","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Rising","usgsCitation":"Glen, J.M., and Earney, T.E., 2025, The influence of pre-existing structures on geothermal springs: Inferences from potential field mapping in Surprise Valley, CA and other sites In the northwestern Great Basin, in Using the Earth to save the Earth, v. 48, p. 1786-1800.","productDescription":"15 p.","startPage":"1786","endPage":"1800","ipdsId":"IP-168956","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":495307,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":495304,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1035058","linkFileType":{"id":5,"text":"html"}}],"volume":"48","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":948388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Earney, Tait E. 0000-0002-1504-0457","orcid":"https://orcid.org/0000-0002-1504-0457","contributorId":210080,"corporation":false,"usgs":true,"family":"Earney","given":"Tait","email":"","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":948389,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70263212,"text":"70263212 - 2025 - Chapter 6: Climate change, wildlife, and wildlife habitats in the Oregon Coast Range","interactions":[],"lastModifiedDate":"2025-02-03T15:11:10.664948","indexId":"70263212","displayToPublicDate":"2024-12-01T09:03:50","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":32,"text":"General Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"PNW-GTR-1024","chapter":"6","title":"Chapter 6: Climate change, wildlife, and wildlife habitats in the Oregon Coast Range","docAbstract":"Climate change is likely to have profound effects on wildlife species within the Oregon Coast Adaptation Partnership (OCAP) assessment area, although the direction and magnitude of effects are likely to vary across species. Increased mean and extreme temperatures, especially during summer, may cause shifts in plant and animal species ranges, reduce habitat for some temperature-sensitive wildlife, alter plant phenology and the timing of available food resources, and affect species interactions (e.g., predation, competition). Altered timing of precipitation, summer drought, loss of fog, increased flooding events, earlier snowmelt, and rising sea level may reduce plant productivity, increase tree mortality, shift plant species composition, and lead to reduced wildlife habitat and habitat quality for some forests, riparian areas, wetlands, meadows, estuaries, and beaches. In addition, increasing frequency and extent of wildfire and insect outbreaks may reduce the extent of late-successional forest, reduce habitat connectivity, and increase the spread of invasive species. The biggest change expected for the assessment area is an increase in area where climatic conditions favor coastal mixed forest and a large reduction in area favoring montane conifer forest. Although actual changes in forest types may not necessarily occur by the end of the 21st century, climate change may add physiological and behavioral stress to wildlife. Some wildlife species will be able to persist in place and adapt to new conditions; some may be able to migrate to find suitable habitat; and some may be greatly reduced or extirpated from the assessment area or even go extinct. Shifts in major tree and shrub species will play a major role in food, den, and cover availability for wildlife. Rising sea level will reduce low-elevation habitats along the coast. An increase in the frequency of high-severity weather events will increase frequency and magnitude of flooding, including debris flow events. Coupled with increased temperatures during summer, this may reduce or fragment important ecosystems for aquatic and semi-aquatic species. Evaluation of the vulnerabilities of nine wildlife species based on literature reviews suggests that each species has life-history attributes that can lead to resilience or vulnerability to climate change effects. Depending on long-term objectives, several broad adaptation strategies focus on protecting refugia, establishing redundant wildlife strongholds with large-scale connectivity, and promoting structural and biological complexity.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Climate change vulnerability and adaptation in coastal Oregon","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"U.S. Forest Service","doi":"https://doi.org/10.2737/pnw-gtr-1024","usgsCitation":"Wilson, T., Thurman, L., Beever, E.A., Singleton, P.H., Olson, D., Williams, D., and Glavich, D., 2025, Chapter 6: Climate change, wildlife, and wildlife habitats in the Oregon Coast Range: General Technical Report PNW-GTR-1024, 58 p., https://doi.org/https://doi.org/10.2737/pnw-gtr-1024.","productDescription":"58 p.","startPage":"201","endPage":"258","ipdsId":"IP-157880","costCenters":[{"id":49226,"text":"Northwest Climate Adaptation Science 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By utilizing a comprehensive hydrodynamic and morphodynamic dataset measured in a large wave flume and high-fidelity 3D large-eddy simulation (LES) data, a rigorous model validation was conducted to assess its capability in predicting inner-surf zone hydrodynamics and to explore how the improved hydrodynamic performance impacts the predicted morphodynamics. Using the default model parameters of the model, the undertow was overestimated with the peak magnitude being 30%–35% larger in the inner surf zone. Combining Monte Carlo simulation, the optimum hydrodynamic calibration for the simulated undertow was achieved when the roller energy dissipation parameter (
Public lands worldwide provide diverse resources, uses, and values, ranging from wilderness to extractive uses. Decision-making on public lands is complex as a result and is required by law to be informed by science. However, public land managers may not always have the science they need. We developed a methodology for identifying priority science needs for public land management agencies. We relied on two core data sources: environmental effects analyses conducted for agency decisions and legal challenges to those decisions. We considered needs in four categories: data, science, methods, and mitigation measures. We classified topics as primary science needs when (1) the topic was analyzed frequently in agency environmental analyses, (2) our metric of quality/defensibility was low or mitigation measures were frequently included for the topic, and (3) the agency was challenged on its use of science for the topic. We applied our methodology to the Bureau of Land Management—the largest public land manager in the United States—in Colorado, a state with abundant and diverse public lands. Primary identified needs were data on vegetation; science about effects of oil and gas development and livestock grazing on multiple resources, including terrestrial wildlife; methods for analyzing environmental effects for many topics; and mitigation measures for protecting vegetation, soils, water quality, and archaeological and historic resources. Science needs often reflect needs for facilitating and supporting the use of existing science in agency decision-making. Our method can be applied across agencies, geographies, and timeframes to help strengthen science use in public lands decision-making.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-024-02080-3","usgsCitation":"Carter, S.K., Haby, T., Samuel, E.M., Foster, A., Meineke, J., McCall, L., Burton, M., Domschke, C., Espy, L., and Gilbert, M., 2025, Identifying priority science information needs for managing public lands: Environmental Management, v. 75, p. 444-463, https://doi.org/10.1007/s00267-024-02080-3.","productDescription":"20 p.","startPage":"444","endPage":"463","ipdsId":"IP-151598","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":487607,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00267-024-02080-3","text":"Publisher Index Page"},{"id":481495,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","noUsgsAuthors":false,"publicationDate":"2024-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Carter, Sarah K. 0000-0003-3778-8615","orcid":"https://orcid.org/0000-0003-3778-8615","contributorId":192418,"corporation":false,"usgs":true,"family":"Carter","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":925706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haby, Travis","contributorId":202409,"corporation":false,"usgs":false,"family":"Haby","given":"Travis","affiliations":[{"id":36421,"text":"Bureau of Land Management National Operations Center","active":true,"usgs":false}],"preferred":false,"id":925707,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Samuel, Ella M. 0000-0001-5085-7369","orcid":"https://orcid.org/0000-0001-5085-7369","contributorId":300515,"corporation":false,"usgs":true,"family":"Samuel","given":"Ella","email":"","middleInitial":"M.","affiliations":[{"id":65185,"text":"School of Earth and Sustainability, Northern Arizona University, Flagstaff, Arizona, USA","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":925708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foster, Alison C. 0000-0002-6659-2120","orcid":"https://orcid.org/0000-0002-6659-2120","contributorId":331240,"corporation":false,"usgs":false,"family":"Foster","given":"Alison C.","affiliations":[{"id":79166,"text":"USGS, currently US Forest Service","active":true,"usgs":false}],"preferred":false,"id":925709,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meineke, Jennifer K. 0000-0002-7136-5854","orcid":"https://orcid.org/0000-0002-7136-5854","contributorId":331238,"corporation":false,"usgs":false,"family":"Meineke","given":"Jennifer K.","affiliations":[{"id":79165,"text":"USGS, currently with Colorado State University","active":true,"usgs":false}],"preferred":false,"id":925710,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCall, Laine E. 0000-0003-2624-8453","orcid":"https://orcid.org/0000-0003-2624-8453","contributorId":336893,"corporation":false,"usgs":false,"family":"McCall","given":"Laine E.","affiliations":[{"id":80900,"text":"Student Contractor, U.S. Geological Survey, Fort Collins Science Center","active":true,"usgs":false}],"preferred":false,"id":925711,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Burton, Malia","contributorId":350331,"corporation":false,"usgs":false,"family":"Burton","given":"Malia","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":925712,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Domschke, Chris","contributorId":267281,"corporation":false,"usgs":false,"family":"Domschke","given":"Chris","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":925713,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Espy, Leigh","contributorId":329383,"corporation":false,"usgs":false,"family":"Espy","given":"Leigh","email":"","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":925714,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gilbert, Megan A.","contributorId":329384,"corporation":false,"usgs":false,"family":"Gilbert","given":"Megan A.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":925715,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70261540,"text":"70261540 - 2025 - Establishment of a cell culture from Daphnia magna as an in vitro model for (eco)toxicology assays: Case study using Bisphenol A as a representative cytotoxic and endocrine disrupting chemical","interactions":[],"lastModifiedDate":"2024-12-13T14:45:27.579534","indexId":"70261540","displayToPublicDate":"2024-11-28T08:35:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":874,"text":"Aquatic Toxicology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Establishment of a cell culture from Daphnia magna as an in vitro model for (eco)toxicology assays: Case study using Bisphenol A as a representative cytotoxic and endocrine disrupting chemical","title":"Establishment of a cell culture from Daphnia magna as an in vitro model for (eco)toxicology assays: Case study using Bisphenol A as a representative cytotoxic and endocrine disrupting chemical","docAbstract":"Bisphenol A (BPA) is a widely used industrial compound found in polycarbonate plastics, epoxy resin, and various polymer materials, leading to its ubiquitous presence in the environment. The toxicity of BPA to aquatic organisms has been well documented following in vivo exposure scenarios, with known cytotoxic and endocrine-disrupting effects. As such, BPA was used in this study as a well-characterized chemical to implement more ethical and resource-efficient scientific practices in toxicity testing through new approach methods (NAMs). Due to the frequent use of Daphnia spp. as a model organism in toxicology, we developed an in vitro cell culture system from Daphnia magna embryos, with optimized medium to support cell longevity. The cultures were maintained for up to two months, demonstrating their stability and suitability for cytotoxicity studies. Using this novel system, lethal concentration 50 (LC50) values were determined at the 24 and 48 h time points following BPA exposure. Subsequently, oxidative stress, endocrine disruption, and DNA damage were assessed through gene expression, activity assays, and a comet assay in BPA-exposed cells. LC50 values of 52 µM and 20 µM BPA were calculated after 24 and 48 h exposures, respectively. BPA cells exposed to 20 and 52 µM had significantly increased GSH, GPx, and GST activity levels. mRNA expression analysis revealed significant upregulations in the expression of hsp70, hsp90, gst, gpx, vtg1, and cyp4, with downregulations of sod, cat, and ecr following BPA exposure. Furthermore, comet assays showed a significantly higher level of DNA damage induced by BPA compared to controls, with greater comet and tail lengths. This study established a novel in vitro Daphnia model, using BPA as a case study for determining toxic effects, further highlighting the importance and applicability of utilizing alternative methods in ecotoxicological research through reducing animal use.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquatox.2024.107173","usgsCitation":"CP, S., TM, M.K., Balakrishnana, S., Kunjiramana, S., Sarasan, M., Magnuson, J.T., and Puthumana, J., 2025, Establishment of a cell culture from Daphnia magna as an in vitro model for (eco)toxicology assays: Case study using Bisphenol A as a representative cytotoxic and endocrine disrupting chemical: Aquatic Toxicology, v. 278, https://doi.org/10.1016/j.aquatox.2024.107173.","productDescription":"107173, 10 p.","startPage":"107173","ipdsId":"IP-169586","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":465107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"278","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"CP, Sreevidya","contributorId":347142,"corporation":false,"usgs":false,"family":"CP","given":"Sreevidya","email":"","affiliations":[{"id":83081,"text":"Cochin University of Science and Technology, India","active":true,"usgs":false}],"preferred":false,"id":920928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"TM, Manoj Kumar","contributorId":347143,"corporation":false,"usgs":false,"family":"TM","given":"Manoj","email":"","middleInitial":"Kumar","affiliations":[{"id":83081,"text":"Cochin University of Science and Technology, India","active":true,"usgs":false}],"preferred":false,"id":920929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balakrishnana, Soumya","contributorId":347144,"corporation":false,"usgs":false,"family":"Balakrishnana","given":"Soumya","email":"","affiliations":[{"id":83081,"text":"Cochin University of Science and Technology, India","active":true,"usgs":false}],"preferred":false,"id":920930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kunjiramana, Suresh","contributorId":347145,"corporation":false,"usgs":false,"family":"Kunjiramana","given":"Suresh","email":"","affiliations":[{"id":83081,"text":"Cochin University of Science and Technology, India","active":true,"usgs":false}],"preferred":false,"id":920931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sarasan, Manomi","contributorId":347146,"corporation":false,"usgs":false,"family":"Sarasan","given":"Manomi","email":"","affiliations":[{"id":83081,"text":"Cochin University of Science and Technology, India","active":true,"usgs":false}],"preferred":false,"id":920932,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Magnuson, Jason Tyler 0000-0001-6841-8014","orcid":"https://orcid.org/0000-0001-6841-8014","contributorId":329838,"corporation":false,"usgs":true,"family":"Magnuson","given":"Jason","email":"","middleInitial":"Tyler","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":920933,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Puthumana, Jayesh","contributorId":347147,"corporation":false,"usgs":false,"family":"Puthumana","given":"Jayesh","email":"","affiliations":[{"id":83081,"text":"Cochin University of Science and Technology, India","active":true,"usgs":false}],"preferred":false,"id":920934,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261786,"text":"70261786 - 2025 - Combining past and contemporary species occurrences with ordinal species distribution modeling to investigate responses to climate change","interactions":[],"lastModifiedDate":"2025-02-24T16:54:46.11919","indexId":"70261786","displayToPublicDate":"2024-11-27T10:42:42","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Combining past and contemporary species occurrences with ordinal species distribution modeling to investigate responses to climate change","docAbstract":"Many organisms leave evidence of their former occurrence, such as scat, abandoned burrows, middens, ancient eDNA or fossils, which indicate areas from which a species has since disappeared. However, combining this evidence with contemporary occurrences within a single modeling framework remains challenging. Traditional binary species-distribution modeling reduces occurrence to two temporally coarse states (present/absent), so thus cannot leverage the information inherent in temporal sequences of evidence of past occurrence. In contrast, ordinal modeling can use the natural time-varying order of states (e.g. never occupied versus previously occupied versus currently occupied) to provide greater insights into range shifts. We demonstrate the power of ordinal modeling for identifying the major influences of biogeographic and climatic variables on current and past occupancy of the American pika Ochotona princeps, a climate-sensitive mammal. Sampling over five years across the species' southernmost, warm-edge range limit, we tested the effects of these variables at 570 habitat patches where occurrence was classified either as binary or ordinal. The two analyses produced different top models and predictors – ordinal modeling highlighted chronic cold as the most-important predictor of occurrence, whereas binary modeling indicated primacy of average summer-long temperatures. Colder wintertime temperatures were associated in ordinal models with higher likelihood of occurrence, which we hypothesize reflect longer retention of insulative and meltwater-provisioning snowpacks. Our binary results mirrored those of other past pika investigations employing binary analysis, wherein warmer temperatures decrease likelihood of occurrence. Because both ordinal- and binary-analysis top models included climatic and biogeographic factors, results constitute important considerations for climate-adaptation planning. Cross-time evidences of species occurrences remain underutilized for assessing responses to climate change. Compared to multi-state occupancy modeling, which presumes all states occur in the same time period, ordinal models enable use of historical evidence of species' occurrence to identify factors driving species' distributions more finely across time.
","language":"English","publisher":"Nordic Society Oikos","doi":"10.1111/ecog.07382","usgsCitation":"Beever, E.A., Westover, M.L., Smith, A., Gerraty, F.D., Billman, P.D., and Smith, F.A., 2025, Combining past and contemporary species occurrences with ordinal species distribution modeling to investigate responses to climate change: Ecography, v. 2025, no. 2, e07382, 14 p., https://doi.org/10.1111/ecog.07382.","productDescription":"e07382, 14 p.","ipdsId":"IP-145828","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":465440,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":466741,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ecog.07382","text":"Publisher Index Page"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.05328351330944,\n 36.99589825246876\n ],\n [\n -108.05328351330944,\n 34.884832495351716\n ],\n [\n -104.26082548698709,\n 34.884832495351716\n ],\n [\n -104.26082548698709,\n 36.99589825246876\n ],\n [\n -108.05328351330944,\n 36.99589825246876\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2025","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Beever, Erik A. 0000-0002-9369-486X ebeever@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-486X","contributorId":2934,"corporation":false,"usgs":true,"family":"Beever","given":"Erik","email":"ebeever@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":921801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Westover, Marie L.","contributorId":274853,"corporation":false,"usgs":false,"family":"Westover","given":"Marie","email":"","middleInitial":"L.","affiliations":[{"id":48790,"text":"Dept. of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":921802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Adam B.","contributorId":328715,"corporation":false,"usgs":false,"family":"Smith","given":"Adam B.","affiliations":[{"id":38790,"text":"Missouri Botanical Garden","active":true,"usgs":false}],"preferred":false,"id":921803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerraty, Francis D.","contributorId":328697,"corporation":false,"usgs":false,"family":"Gerraty","given":"Francis","email":"","middleInitial":"D.","affiliations":[{"id":34029,"text":"U.C. Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":921804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Billman, Peter D.","contributorId":311242,"corporation":false,"usgs":false,"family":"Billman","given":"Peter","email":"","middleInitial":"D.","affiliations":[{"id":67370,"text":"University of Connecticut, Dept. of Ecology and Evolution","active":true,"usgs":false}],"preferred":false,"id":921805,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Felisa A.","contributorId":194657,"corporation":false,"usgs":false,"family":"Smith","given":"Felisa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":921806,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267224,"text":"70267224 - 2025 - Oblique contraction along the fastest ocean-continent transform plate boundary focuses rock uplift west of the Fairweather fault, southeast Alaska","interactions":[],"lastModifiedDate":"2025-05-16T15:17:10.500555","indexId":"70267224","displayToPublicDate":"2024-11-27T10:10:23","publicationYear":"2025","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"17","title":"Oblique contraction along the fastest ocean-continent transform plate boundary focuses rock uplift west of the Fairweather fault, southeast Alaska","docAbstract":"Contraction along the Yakutat–North America plate boundary drives 4.6–9.0 mm/year Holocene rock uplift rates along Earth's fastest slipping (≥49 mm/year) ocean–continent transform fault, the Fairweather Fault. Between Icy Point and Lituya Bay, the near-vertical Fairweather fault focuses rock uplift and rapid right-lateral slip by accommodating both vertical and fault-parallel strain during oblique-slip and separate, predominantly strike-slip ruptures. Unusually high uplift rates, indicated by radiocarbon and luminescence dating, result from a 10-km-wide, asymmetric, positive flower structure along a 20°, ∼30-km-long restraining double bend in the Fairweather fault. The principal reverse fault in the flower structure, the offshore, blind Icy Point–Lituya Bay fault, ruptures no more than every 460–1040 years evidenced by uplifted Holocene shorelines. Maximum 3–5 m coseismic uplifts imply 3.1–10 m dip slip per event and earthquake magnitudes of M w 7.0–7.5. The Yakutat block collides obliquely into North America, and our model entails oblique slip on the Fairweather fault with and without corupture on the reverse fault. Oblique slip is evident by vertically offset (>25 m) fluvial and marine terraces and by the primary Fairweather fault strand that strikes >20° to the west of plate-boundary motion.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Tectonics and seismic structure of Alaska and northwestern Canada: EarthScope and beyond","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Wiley","doi":"10.1002/9781394195947.ch17","usgsCitation":"Witter, R., Kelsey, H., Lease, R.O., Bender, A., Scharer, K., Haeussler, P., and Brothers, D., 2025, Oblique contraction along the fastest ocean-continent transform plate boundary focuses rock uplift west of the Fairweather fault, southeast Alaska, chap. 17 of Tectonics and seismic structure of Alaska and northwestern Canada: EarthScope and beyond, p. 461-495, https://doi.org/10.1002/9781394195947.ch17.","productDescription":"35 p.","startPage":"461","endPage":"495","ipdsId":"IP-154317","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":498443,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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0000-0003-0614-0306","orcid":"https://orcid.org/0000-0003-0614-0306","contributorId":244609,"corporation":false,"usgs":false,"family":"Freymueller","given":"Jeffery","email":"","middleInitial":"T.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":937393,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":937356,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelsey, Harvey M.","contributorId":206893,"corporation":false,"usgs":false,"family":"Kelsey","given":"Harvey M.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":937357,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lease, Richard O. 0000-0003-2582-8966 rlease@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-8966","contributorId":5098,"corporation":false,"usgs":true,"family":"Lease","given":"Richard","email":"rlease@usgs.gov","middleInitial":"O.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":937358,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bender, Adrian 0000-0001-7469-1957","orcid":"https://orcid.org/0000-0001-7469-1957","contributorId":219952,"corporation":false,"usgs":true,"family":"Bender","given":"Adrian","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":937359,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scharer, Katherine M. 0000-0003-2811-2496","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":217361,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":937360,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":937361,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brothers, Daniel S. 0000-0001-7702-157X","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":210199,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":937362,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70263535,"text":"70263535 - 2025 - Constraining the earthquake recording threshold of intraslab earthquakes with turbidites in southcentral Alaska’s lakes and fjords","interactions":[],"lastModifiedDate":"2025-02-13T16:02:28.444976","indexId":"70263535","displayToPublicDate":"2024-11-27T09:54:54","publicationYear":"2025","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"14","title":"Constraining the earthquake recording threshold of intraslab earthquakes with turbidites in southcentral Alaska’s lakes and fjords","docAbstract":"Strong ground motion from intraslab earthquakes, which do not produce primary paleoseismic evidence, may initiate gravity-driven turbidity flows in subaqueous basins. The resulting deposits (turbidites) can provide a paleoseismic proxy if the conditions that initiate these flows are known. To better constrain the initiating conditions, we use two recent intraslab earthquakes in southcentral Alaska, the M w 7.1 30 November 2018 Anchorage earthquake and the M w 7.1 24 January 2016 Iniskin earthquake, as calibration events. Through a multilake investigation, we document the occurrence, or the absence, of earthquake-generated turbidity flows from these two events. Both earthquakes are recorded by centimeter-scale turbidites that can be differentiated from climatically generated deposits, as well as other seismic sources based on deposit thickness, sedimentological properties, and deposit age. We show that a Modified Mercalli Intensity (MMI) of ∼V–V1/2 is the minimum shaking intensity required to generate localized sediment remobilization from deltaic slopes, and an MMI of ∼V1/2 is required to produce a deposit of sufficient thickness that a seismic origin can be confidently assigned. The documentation of seismically generated deposits in quick succession (∼2 years) with diagnostic features highlights the utility of using recent earthquakes as calibration events to investigate the subaqueous response to strong ground motion.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Tectonics and seismic structure of Alaska and northwestern Canada: EarthScope and beyond","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/9781394195947.ch14","usgsCitation":"Singleton, D.M., Brothers, D., Haeussler, P., Witter, R., and Hill, J.C., 2025, Constraining the earthquake recording threshold of intraslab earthquakes with turbidites in southcentral Alaska’s lakes and fjords, chap. 14 of Tectonics and seismic structure of Alaska and northwestern Canada: EarthScope and beyond, p. 389-418, https://doi.org/10.1002/9781394195947.ch14.","productDescription":"30 p.","startPage":"389","endPage":"418","ipdsId":"IP-149309","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":482031,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","noUsgsAuthors":false,"publicationDate":"2024-12-13","publicationStatus":"PW","contributors":{"editors":[{"text":"Ruppert, Natalia A.","contributorId":89117,"corporation":false,"usgs":true,"family":"Ruppert","given":"Natalia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":927366,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Jadamec, M.","contributorId":83326,"corporation":false,"usgs":true,"family":"Jadamec","given":"M.","email":"","affiliations":[],"preferred":false,"id":927367,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Freymueller, Jeffrey T.","contributorId":97458,"corporation":false,"usgs":true,"family":"Freymueller","given":"Jeffrey","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":927368,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Singleton, Drake Moore 0000-0001-5346-0623","orcid":"https://orcid.org/0000-0001-5346-0623","contributorId":261207,"corporation":false,"usgs":true,"family":"Singleton","given":"Drake","email":"","middleInitial":"Moore","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":927292,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Daniel S. 0000-0001-7702-157X","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":210199,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":927293,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":927294,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":927295,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hill, Jenna C. 0000-0002-7475-357X","orcid":"https://orcid.org/0000-0002-7475-357X","contributorId":21987,"corporation":false,"usgs":true,"family":"Hill","given":"Jenna","email":"","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":927296,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70264974,"text":"70264974 - 2025 - Tectonic tremor observations across Alaska","interactions":[],"lastModifiedDate":"2025-03-27T14:56:35.624651","indexId":"70264974","displayToPublicDate":"2024-11-27T09:42:12","publicationYear":"2025","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"11","title":"Tectonic tremor observations across Alaska","docAbstract":"Tectonic tremor is a semicontinuous, low-frequency seismic signal associated with stable fault motion at major plate boundaries worldwide. In subduction zones, tremor often coincides with geodetic transients that indicate discrete slow slip on the subducting plate interface. Because tremor epicenters offer better spatial and temporal resolution than geodetic inversions of slip, detecting tremor can provide important constraints on plate interface properties, coupling, and dynamics. But in Alaska, challenges abound. The geographic scale of the Alaska–Aleutian subduction zone, the limited land available for instruments in the Aleutian Islands, and the messy nature of the tremor signal itself inhibit efforts to uniformly catalog tremor. Here, I present an overview of such efforts and what can and cannot be inferred from where tremor has been observed. Reliable tremor observations are confined to south-central Alaska in conjunction with the subducting Yakutat microplate, and one section of the eastern Aleutian Islands near Unalaska, with scant evidence of tremor elsewhere. Unique fault interface conditions may explain why tremor is limited to these regions, but most null results are not robust, and the limited observations preclude any large-scale interpretations.
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The background noise spectrum at a station is a combination of cultural noise, ocean-generated microseism noise, intrinsic instrument self-noise, and the sensitivity of the instrument to nonseismic noise sources. The USArray-Transportable Array Alaska deployed 195 stations across Alaska and parts of Canada (Yukon, British Columbia, and Northwest Territories). These stations were all installed using similar techniques and made use of instruments with similar self-noise levels. As such, this network provides an opportunity to look at how geographic location influences seismic background. Using these broadband stations, we report background noise levels from 0.2 to 75 s period in six discrete bands. By constructing “noise maps,” we depict both spatial and temporal changes in the background noise field. Using these maps, combined with targeted analysis, we infer sources and contributing factors to noise levels in these different period bands. These include cultural noise, the formation of sea ice, seasonal changes in permafrost and wave activity in the Gulf of Alaska, and magnetic field variability. We use this study as an opportunity to review several previous studies examining seismic noise in Arctic regions.
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2025 - Evaluation of the gap intercept method to measure rangeland connectivity","interactions":[],"lastModifiedDate":"2024-12-16T16:15:42.684883","indexId":"70261572","displayToPublicDate":"2024-11-26T10:06:07","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6002,"text":"Rangeland Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of the gap intercept method to measure rangeland connectivity","docAbstract":"Characterizing the connectivity of materials, organisms, and energy on rangelands is critical to understanding and managing ecosystem response to disturbances. For over twenty years, scientists and rangeland managers have used the gap intercept method to monitor connectivity. However, using gap intercept measurements to infer ecosystem processes or inform management actions and conservation practices on rangelands has been limited because there are few tools and syntheses to help managers pragmatically interpret gap measurements. In this synthesis, we review the different ways the gap intercept method is conducted and highlight considerations when collecting and using gap intercept data. We discuss what is known about how gap intercept data can be used to assess wind and water erosion, biocrust abundance and composition, soil fertility, plant community dynamics, wildlife habitat characteristics, and fuel connectivity and fire behavior. Finally, we identify emerging opportunities regarding the collection and use of gap intercept data to assess rangeland connectivity, ecosystem function, and ecological processes. Through this synthesis we demonstrate the value of the gap intercept method, particularly “all-plant” (i.e., whole-community) canopy gap, in supporting assessments of rangeland condition and vulnerability, and in planning future management actions.
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4118","active":true,"usgs":false}],"preferred":false,"id":921083,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":229349,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":921084,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Schaefer, Anthony","contributorId":347229,"corporation":false,"usgs":false,"family":"Schaefer","given":"Anthony","email":"","affiliations":[],"preferred":false,"id":921085,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Webb, Nicholas P.","contributorId":195924,"corporation":false,"usgs":false,"family":"Webb","given":"Nicholas","email":"","middleInitial":"P.","affiliations":[{"id":6973,"text":"USDA-ARS Jornada Experimental Range and Jornada Basin LTER, Las Cruces, NM; New Mexico State University, Dept. of Plant and Environmental Sciences, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":921086,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Wheeler, Brandi E.","contributorId":334182,"corporation":false,"usgs":false,"family":"Wheeler","given":"Brandi","email":"","middleInitial":"E.","affiliations":[{"id":80080,"text":"USDA-ARS Jornada Experimental Range, Las Cruces, NM, USA","active":true,"usgs":false}],"preferred":false,"id":921087,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Williams, C. Jason","contributorId":292512,"corporation":false,"usgs":false,"family":"Williams","given":"C. Jason","affiliations":[{"id":62926,"text":"Agricultural Research Service, U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":921088,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Young, Kristina E.","contributorId":195945,"corporation":false,"usgs":false,"family":"Young","given":"Kristina E.","affiliations":[],"preferred":false,"id":921089,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70262089,"text":"70262089 - 2025 - U.S. Geological Survey research and assessments supporting carbon dioxide removal","interactions":[],"lastModifiedDate":"2025-01-13T15:21:36.376397","indexId":"70262089","displayToPublicDate":"2024-11-26T09:17:50","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"U.S. Geological Survey research and assessments supporting carbon dioxide removal","docAbstract":"Both carbon capture and storage (CCS) and carbon dioxide removal (CDR) are methods to limit future global temperature rise and ocean acidification. CCS sequesters (stores) carbon dioxide (CO2) captured from industrial sources thereby preventing the CO2 from reaching the atmosphere. The captured CO2 is injected into underground geologic reservoirs or is converted into stable industrial products. CDR enhances natural processes or uses technical approaches to remove excess CO2 from the atmosphere. Carbon dioxide is sequestered in natural sinks such as vegetation and soil, or injected into underground reservoirs or converted into durable products. The U.S. Geological Survey (USGS) conducts research and resource assessments that support biologic and geologic CDR approaches. This report will review some of the ongoing USGS CDR research and assessment efforts.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 17th Greenhouse Gas Control Technologies Conference (GHGT-17)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"17th Greenhouse Gas Control Technologies Conference (GHGT-17)","conferenceDate":"October 20-24, 2024","conferenceLocation":"Calgary, Alberta, Canada","language":"English","publisher":"Elsevier","doi":"10.2139/ssrn.5034821","usgsCitation":"Warwick, P., Blondes, M., Drexler, J.Z., Kroeger, K.D., and Zhu, Z., 2025, U.S. Geological Survey research and assessments supporting carbon dioxide removal, in Proceedings of the 17th Greenhouse Gas Control Technologies Conference (GHGT-17), v. 17, Calgary, Alberta, Canada, October 20-24, 2024, 7 p., https://doi.org/10.2139/ssrn.5034821.","productDescription":"7 p.","ipdsId":"IP-171749","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":494420,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.2139/ssrn.5034821","text":"Publisher Index Page"},{"id":466113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Warwick, Peter D. 0000-0002-3152-7783","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":207248,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":923048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blondes, Madalyn S. 0000-0003-0320-0107","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":348170,"corporation":false,"usgs":false,"family":"Blondes","given":"Madalyn S.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":923049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":923050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":923051,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":923052,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261242,"text":"70261242 - 2025 - The ghost plume phenomenon and its impact on zenith-facing remote sensing measurements of volcanic SO2 emission rates","interactions":[],"lastModifiedDate":"2024-12-03T15:12:15.341309","indexId":"70261242","displayToPublicDate":"2024-11-26T09:07:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19844,"text":"Journal of Volcanology and Goethermal Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The ghost plume phenomenon and its impact on zenith-facing remote sensing measurements of volcanic SO2 emission rates","title":"The ghost plume phenomenon and its impact on zenith-facing remote sensing measurements of volcanic SO2 emission rates","docAbstract":"A large source of error in SO2 emission rates derived from mobile Differential Optical Absorption Spectroscopy (DOAS) of volcanic gas plumes is the uncertainty in atmospheric light paths between the sun and the instrument, particularly under non-ideal atmospheric conditions, such as the presence of low clouds. DOAS instruments measure the SO2 column density along the effective light path, so changes to that pathway directly affect the measured SO2 signal. Due to complex radiative transfer mechanisms when a cloud is between the DOAS viewing position and a volcanic plume, measured plumes can appear spatially offset from their true location, a phenomenon informally referred to as “ghost plumes.” In addition to the appearance of ghost plumes, DOAS measurements recorded in non-ideal conditions have poorly characterized errors and are often discarded, limiting the data available to characterize volcanic degassing. In this study we simulate the radiative transfer associated with zenith-facing mobile DOAS traverses using the McArtim radiative transfer model for scenarios when there is a cloud layer between the instrument and the volcanic plume. In total, 217 permutations of atmospheric optical conditions are considered with varying cloud opacities (AOD = 0, 1, 2, 4, 8, 20), plume opacities (AOD = 0, 1, 2, 4, 8), solar zenith angles (SZA = 1°, 30°, 60°), and cloud thicknesses (200, 400, 800 m). We first develop objective criteria for selecting SO2 baseline absorption levels and plume spatial extents. The simulated plume traverses are then integrated to obtain the SO2 cross-sectional burdens which, after multiplication with the wind speed, yield SO2 emission rates. We find large modification in the shape of the modeled cross-sectional burdens even under translucent (low AOD) cloud conditions in our modeled scenarios. Despite modification of the plume shape, the presence of a low cloud layer is typically not a large source of error in the SO2 cross-sectional burden or emission rate obtained from zenith-facing DOAS traverses. We find that all measured cross-sectional burdens simulated using an aerosol-free plume in the above conditions and SZA ≤ 30° are within ±25% of the true value.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2024.108217","usgsCitation":"Kushner, D., Lopez, T., Kern, C., Arellano, S., Perez, N.M., and Barrancos, J., 2025, The ghost plume phenomenon and its impact on zenith-facing remote sensing measurements of volcanic SO2 emission rates: Journal of Volcanology and Goethermal Research, v. 457, 108217, 9 p., https://doi.org/10.1016/j.jvolgeores.2024.108217.","productDescription":"108217, 9 p.","ipdsId":"IP-159740","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488997,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://research.chalmers.se/en/publication/543987","text":"Publisher Index Page"},{"id":464697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"457","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kushner, D.S.","contributorId":346874,"corporation":false,"usgs":false,"family":"Kushner","given":"D.S.","email":"","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":920081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lopez, T.M.","contributorId":346875,"corporation":false,"usgs":false,"family":"Lopez","given":"T.M.","email":"","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":920082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":920083,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arellano, Santiago","contributorId":205719,"corporation":false,"usgs":false,"family":"Arellano","given":"Santiago","affiliations":[{"id":37153,"text":"Department of Earth and Space Sciences – Chalmers University of Technology, Göteborg, Sweden","active":true,"usgs":false}],"preferred":false,"id":920084,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Perez, Nemesio M.","contributorId":177622,"corporation":false,"usgs":false,"family":"Perez","given":"Nemesio","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":920085,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barrancos, J","contributorId":346876,"corporation":false,"usgs":false,"family":"Barrancos","given":"J","email":"","affiliations":[{"id":83004,"text":"Instituto Volcanologico de Canarias","active":true,"usgs":false}],"preferred":false,"id":920086,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70265937,"text":"70265937 - 2025 - Population increases of the threatened American burying beetle (Nicrophorus americanus) linked to large-scale collaborations in a working lands ecoregion","interactions":[],"lastModifiedDate":"2025-04-22T17:39:21.057701","indexId":"70265937","displayToPublicDate":"2024-11-24T12:29:28","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Population increases of the threatened American burying beetle (Nicrophorus americanus) linked to large-scale collaborations in a working lands ecoregion","title":"Population increases of the threatened American burying beetle (Nicrophorus americanus) linked to large-scale collaborations in a working lands ecoregion","docAbstract":"Woody plant encroachment and row-crop agricultural land conversion are existential threats to species that rely on grassland ecosystems. The American Burying Beetle (Nicrophorus americanus) is a threatened species whose largest remnant populations are predominantly located in grassland ecoregions comprised of privately-owned ranching lands. Here, we seek to determine functional scaling patterns and population trends of the American Burying Beetle in the face of conservation threats and grassland restoration. We used 13 years (2007–2019) of American Burying Beetle abundance data collected from permanent sampling locations across the Loess Canyons ecoregion (Nebraska, USA), where a network of ranchers have been restoring large-scale grasslands. To estimate beetle abundance relative to land cover variables, we developed a Bayesian N-mixture model, incorporating the Bayesian latent indicator scale selection (BLISS) method to probabilistically determine at which scales land cover variables best explained beetle abundance. American Burying Beetle abundance exhibited high interannual variation but overall significantly increased across the ecoregion. Increases in beetle abundance were associated with large-scale (1149 ha extent) grassland cover. Decreases in abundance were associated with large-scale crop conversion (590 ha extent) and large-scale increases in woody cover (1149 ha extent). This study provides the first evidence of ecoregion-scale population increases of the American Burying Beetle. These increases are tied to landscape variables that are managed in a large-scale, coordinated private lands grassland restoration effort. Our results suggest that successful grassland restoration will depend on coordinating across property boundaries to implement conservation at scales necessary to conserve species that require large-scale, unfragmented grasslands.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2024.110865","usgsCitation":"Roberts, C.P., Ludwig, A., Fogarty, D., Stuber, E.F., Uden, D., Walker, T., and Twidwell, D., 2025, Population increases of the threatened American burying beetle (Nicrophorus americanus) linked to large-scale collaborations in a working lands ecoregion: Biological Conservation, v. 301, 110865, 11 p., https://doi.org/10.1016/j.biocon.2024.110865.","productDescription":"110865, 11 p.","ipdsId":"IP-168131","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":484857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Loess Canyons experimental landscape","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -101.28914746227895,\n 41.45522213058922\n ],\n [\n -101.28914746227895,\n 40.41937056355326\n ],\n [\n -99.7780551382092,\n 40.41937056355326\n ],\n [\n -99.7780551382092,\n 41.45522213058922\n ],\n [\n -101.28914746227895,\n 41.45522213058922\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"301","noUsgsAuthors":false,"publicationDate":"2024-11-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts, Caleb Powell 0000-0002-8716-0423","orcid":"https://orcid.org/0000-0002-8716-0423","contributorId":288567,"corporation":false,"usgs":true,"family":"Roberts","given":"Caleb","email":"","middleInitial":"Powell","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":934085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ludwig, Alison K.","contributorId":353601,"corporation":false,"usgs":false,"family":"Ludwig","given":"Alison K.","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":934086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fogarty, Dillon T.","contributorId":353602,"corporation":false,"usgs":false,"family":"Fogarty","given":"Dillon T.","affiliations":[{"id":12471,"text":"North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":934087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stuber, Erica Francis 0000-0002-2687-6874","orcid":"https://orcid.org/0000-0002-2687-6874","contributorId":298084,"corporation":false,"usgs":true,"family":"Stuber","given":"Erica","email":"","middleInitial":"Francis","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":934088,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Uden, Daniel R.","contributorId":353603,"corporation":false,"usgs":false,"family":"Uden","given":"Daniel R.","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":934089,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walker, Thomas L. Jr.","contributorId":353604,"corporation":false,"usgs":false,"family":"Walker","given":"Thomas L.","suffix":"Jr.","affiliations":[{"id":17640,"text":"Nebraska Game and Parks Commission","active":true,"usgs":false}],"preferred":false,"id":934090,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Twidwell, Dirac","contributorId":353605,"corporation":false,"usgs":false,"family":"Twidwell","given":"Dirac","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":934091,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261709,"text":"70261709 - 2025 - A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples","interactions":[{"subject":{"id":70258184,"text":"70258184 - 2024 - A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples","indexId":"70258184","publicationYear":"2024","noYear":false,"title":"A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples"},"predicate":"SUPERSEDED_BY","object":{"id":70261709,"text":"70261709 - 2025 - A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples","indexId":"70261709","publicationYear":"2025","noYear":false,"title":"A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples"},"id":1}],"lastModifiedDate":"2025-03-25T15:48:58.14773","indexId":"70261709","displayToPublicDate":"2024-11-24T09:12:51","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1573,"text":"Environmental and Ecological Statistics","active":true,"publicationSubtype":{"id":10}},"title":"A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples","docAbstract":"Environmental DNA (eDNA) sampling is an increasingly important tool for answering ecological questions and informing aquatic species management; however, several factors currently limit the reliability of ecological inference from eDNA sampling. Two particular challenges are (1) determining species source location(s) and (2) accurately and precisely measuring low concentration eDNA samples in the presence of multiple sources of ecological and measurement variability. The recently introduced eDNA Integrating Transport and Hydrology (eDITH) model provides a framework for relating eDNA measurements to source locations in riverine networks, but little empirical work has been done to test and refine model assumptions or accommodate low concentration samples, that can be systematically undermeasured. To better understand eDNA fate and transport dynamics and our ability to reliably quantify low concentration samples, we developed a hierarchical model and used it to evaluate a fate and transport experiment. Our model addresses several low concentration challenges by modeling the number of copies in each PCR replicate as a latent variable with a count distribution and conditioning detection and quantification on replicate copy number. We provide evidence that the eDNA removal rate declined through time, estimating that over 80% of eDNA was removed over the first 10 m, traversed in 41 s. After this initial period of rapid decay, eDNA decayed slowly with consistent detection through our farthest site 1 km from the release location, traversed in 67.8 min. Our model further allowed us to detect extra-Poisson variation in the allocation of copies to replicates. We extended our hierarchical model to accommodate a continuous effect of inhibitors and used our model to provide evidence for the inhibitor hypothesis and explore the potential implications. While our model is not a panacea for all challenges faced when quantifying low-concentration eDNA samples, it provides a framework for a more complete accounting of uncertainty.
","language":"English","publisher":"Springer","doi":"10.1007/s10651-024-00632-8","usgsCitation":"Augustine, B., Hutchins, P., Jones-Slobodian, D.N., Williams, J.R., Leinonen, E., and Sepulveda, A., 2025, A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples: Environmental and Ecological Statistics, v. 32, p. 21-56, https://doi.org/10.1007/s10651-024-00632-8.","productDescription":"36 p.","startPage":"21","endPage":"56","ipdsId":"IP-170289","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":466744,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2024.03.27.586987","text":"External Repository"},{"id":465331,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","noUsgsAuthors":false,"publicationDate":"2024-11-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Augustine, Ben 0000-0001-6935-6361","orcid":"https://orcid.org/0000-0001-6935-6361","contributorId":245736,"corporation":false,"usgs":true,"family":"Augustine","given":"Ben","email":"","affiliations":[{"id":49304,"text":"Department of Natural Resources, Cornell University","active":true,"usgs":false}],"preferred":false,"id":921530,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hutchins, Patrick Ross 0000-0001-5232-0821","orcid":"https://orcid.org/0000-0001-5232-0821","contributorId":256658,"corporation":false,"usgs":true,"family":"Hutchins","given":"Patrick Ross","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":921531,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones-Slobodian, Devin Nicole 0000-0001-9215-2930","orcid":"https://orcid.org/0000-0001-9215-2930","contributorId":305357,"corporation":false,"usgs":true,"family":"Jones-Slobodian","given":"Devin","middleInitial":"Nicole","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":921532,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Jacob R.","contributorId":288679,"corporation":false,"usgs":false,"family":"Williams","given":"Jacob","email":"","middleInitial":"R.","affiliations":[{"id":61825,"text":"Montana Fish","active":true,"usgs":false}],"preferred":false,"id":921533,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leinonen, Eric","contributorId":346482,"corporation":false,"usgs":false,"family":"Leinonen","given":"Eric","email":"","affiliations":[{"id":82874,"text":"Turner Enterprise Management","active":true,"usgs":false}],"preferred":false,"id":921534,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sepulveda, Adam 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":4187,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":921535,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70264135,"text":"70264135 - 2025 - Ecological and social drivers of Mexican wolf home range size across spatiotemporal scales","interactions":[],"lastModifiedDate":"2025-03-07T14:38:45.51395","indexId":"70264135","displayToPublicDate":"2024-11-24T08:35:33","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7153,"text":"Journal of Mammology","active":true,"publicationSubtype":{"id":10}},"title":"Ecological and social drivers of Mexican wolf home range size across spatiotemporal scales","docAbstract":"Elucidating factors influencing home range size is fundamental to the ecology and management of wildlife species, particularly those of conservation concern, because they can provide insight into how species utilize and interact with their environment. Variation in home range size can be related to intraspecific competition and social organization, energetic requirements in relation to habitat productivity, allometric relationships, and population density. The Mexican Gray Wolf (Canis lupus baileyi) is an endangered subspecies of the Gray Wolf whose home range size has not yet been studied. We examined ecological and social drivers of home range size of 22 Mexican Wolf packs between 2017 and 2021 across 4 biological time frames: annual; denning; post-denning; and non-denning. We used a 95% Brownian Bridge Movement Model home range estimator and generalized linear mixed-effect models to assess these relationships. Home range size was inversely correlated with estimated ungulate biomass, which was the most influential driver of home range size at annual and post-denning time frames. Larger packs utilized larger ranges during denning and post-denning time frames, while packs with larger litters had smaller ranges during the denning season. Snow depth was inversely related to home range size during the non-denning season. Our results indicate that both ecological and social factors are important and seasonally dependent in driving Mexican Wolf home range size. Use of a multiscale approach in future home range studies could discern relevant factors for species during time frames of interest.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyae110","usgsCitation":"Lichwa-Schneringer, E., Cain, J.W., Wan, H.Y., Fuller, G., Millberry, C., and Gunther, M.S., 2025, Ecological and social drivers of Mexican wolf home range size across spatiotemporal scales: Journal of Mammology, v. 106, no. 1, p. 105-117, https://doi.org/10.1093/jmammal/gyae110.","productDescription":"13 p.","startPage":"105","endPage":"117","ipdsId":"IP-159340","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":483043,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Lichwa-Schneringer, Evelyn","contributorId":352023,"corporation":false,"usgs":false,"family":"Lichwa-Schneringer","given":"Evelyn","affiliations":[{"id":81635,"text":"Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":929924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":929925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wan, Ho Yi","contributorId":209843,"corporation":false,"usgs":false,"family":"Wan","given":"Ho","email":"","middleInitial":"Yi","affiliations":[{"id":38007,"text":"3Northern Arizona University, School of Earth Sciences and Environmental Sustainability","active":true,"usgs":false}],"preferred":false,"id":929926,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuller, Genevieve","contributorId":352026,"corporation":false,"usgs":false,"family":"Fuller","given":"Genevieve","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":929927,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Millberry, Cyrenea","contributorId":352027,"corporation":false,"usgs":false,"family":"Millberry","given":"Cyrenea","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":929928,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gunther, Micaela Szykman","contributorId":265719,"corporation":false,"usgs":false,"family":"Gunther","given":"Micaela","email":"","middleInitial":"Szykman","affiliations":[{"id":54774,"text":"Department of Wildlife, Humboldt State University, Arcata, California, USA","active":true,"usgs":false}],"preferred":false,"id":929929,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271137,"text":"70271137 - 2025 - Declining ecological resilience and invasion resistance under climate change in the sagebrush region, United States","interactions":[],"lastModifiedDate":"2025-08-28T15:23:30.407508","indexId":"70271137","displayToPublicDate":"2024-11-24T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Declining ecological resilience and invasion resistance under climate change in the sagebrush region, United States","docAbstract":"In water-limited dryland ecosystems of the Western United States, climate change is intensifying the impacts of heat, drought, and wildfire. Disturbances often lead to increased abundance of invasive species, in part, because dryland restoration and rehabilitation are inhibited by limited moisture and infrequent plant recruitment events. Information on ecological resilience to disturbance (recovery potential) and resistance to invasive species can aid in addressing these challenges by informing long-term restoration and conservation planning. Here, we quantified the impacts of projected future climate on ecological resilience and invasion resistance (R&R) in the sagebrush region using novel algorithms based on ecologically relevant and climate-sensitive predictors of climate and ecological drought. We used a process-based ecohydrological model to project these predictor variables and resulting R&R indicators for two future climate scenarios and 20 climate models. Results suggested widespread future R&R decreases (24%–34% of the 1.16 million km2 study area) that are generally consistent among climate models. Variables related to rising temperatures were most strongly linked to decreases in R&R indicators. New continuous R&R indices quantified responses to climate change; particularly useful for areas without projected change in the R&R category but where R&R still may decrease, for example, some of the areas with a historically low R&R category. Additionally, we found that areas currently characterized as having high sagebrush ecological integrity had the largest areal percentage with expected declines in R&R in the future, suggesting continuing declines in sagebrush ecosystems. One limitation of these R&R projections was relatively novel future climatic conditions in particularly hot and dry areas that were underrepresented in the training data. Including more data from these areas in future updates could further improve the reliability of the projections. Overall, these projected future declines in R&R highlight a growing challenge for natural resource managers in the region, and the resulting spatially explicit datasets provide information that can improve long-term risk assessments, prioritizations, and climate adaptation efforts.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.3065","usgsCitation":"Schlaepfer, D.R., Chambers, J., Urza, A.K., Hanberry, B.B., Brown, J.L., Board, D.I., Campbell, S.B., Clause, K.J., Crist, M.R., and Bradford, J.B., 2025, Declining ecological resilience and invasion resistance under climate change in the sagebrush region, United States: Ecological Applications, v. 35, no. 1, e3065, 22 p., https://doi.org/10.1002/eap.3065.","productDescription":"e3065, 22 p.","ipdsId":"IP-158663","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":495009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 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0000-0001-6140-1260","orcid":"https://orcid.org/0000-0001-6140-1260","contributorId":360734,"corporation":false,"usgs":false,"family":"Board","given":"David","middleInitial":"I.","affiliations":[{"id":82408,"text":"USDA Forest Service, Rocky Mountain Research Station, Reno, Nevada U.S.A.","active":true,"usgs":false}],"preferred":false,"id":947555,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Campbell, Steven B. 0009-0002-9710-9688","orcid":"https://orcid.org/0009-0002-9710-9688","contributorId":360736,"corporation":false,"usgs":false,"family":"Campbell","given":"Steven","middleInitial":"B.","affiliations":[{"id":86091,"text":"USDA Natural Resources Conservation Service, West National Technology Support Center, Portland, Oregon U.S.A.","active":true,"usgs":false}],"preferred":false,"id":947556,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Clause, Karen 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jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":222784,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":947559,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70257548,"text":"70257548 - 2025 - High variability of migration strategies in a re-established Cygnus buccinator (Trumpeter Swan) population","interactions":[],"lastModifiedDate":"2025-06-12T15:24:51.105385","indexId":"70257548","displayToPublicDate":"2024-11-22T10:17:33","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10109,"text":"Ornithology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"High variability of migration strategies in a re-established Cygnus buccinator (Trumpeter Swan) population","title":"High variability of migration strategies in a re-established Cygnus buccinator (Trumpeter Swan) population","docAbstract":"The Interior Population (IP) of Cygnus buccinator (Trumpeter Swan), formerly extirpated by market hunting, was re-established in eastern North America by releasing individuals from both migratory and non-migratory populations. Their current annual movement patterns are largely unknown. We deployed 113 GPS-GSM transmitters on IP C. buccinator in 6 U.S. states and 1 Canadian province across the current IP breeding range. Using data from 252 “swan-years”, we estimated migration phenology using piecewise regression models fit to each yearly time-series of displacement from the breeding site. We fit a latent-state model to characterize population-level associations between breeding latitude and maximum extent of migration, and linear mixed models to quantify associations between individual characteristics (e.g., breeding status, sex) and migration phenology. At the individual level, 59% of swans moved to distant nonbreeding-period areas (long-distance migration, defined as moving >100 km from the breeding site), 16% exhibited regional migration (25–100 km from breeding site), 19% exhibited non-migratory but local movements (<25 km from breeding site), and 6% exhibited multiple migration strategies. Swans breeding at more-northern latitudes departed their territories earlier in autumn, returned later in the spring, and migrated farther from their breeding territories than those breeding at more southern latitudes. Although the population-level association between migration extent and breeding latitude was positive, some individuals remained close to the location of their breeding site during the nonbreeding period. Breeding swans departed later in the autumn than non-breeders, but breeding status did not have a strong association with arrival in the spring. IP C. buccinator are partial migrants, with a continuum of strategies that vary latitudinally, from local movements to long-distance migration. Much of the variability in movement patterns related to factors tied to natural history demands (e.g., breeding status) and response to environmental conditions (e.g., through associations with breeding latitude).
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithology/ukae059","usgsCitation":"Wolfson, D., Knapik, R., Buckardt Thomas, A., Harms, T., Kearns, L., Kiss, B., Poole, T., Fowler, D., Finger, T.A., Matteson, S.W., Moriarty, J., Mayo, T., Smith, M., Herwig, C., Andersen, D.E., and Fieberg, J.R., 2025, High variability of migration strategies in a re-established Cygnus buccinator (Trumpeter Swan) population: Ornithology, v. 142, no. 2, ukae059, 12 p., https://doi.org/10.1093/ornithology/ukae059.","productDescription":"ukae059, 12 p.","ipdsId":"IP-163003","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":465487,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":466748,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithology/ukae059","text":"Publisher Index Page"}],"volume":"142","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Wolfson, David W.","contributorId":244928,"corporation":false,"usgs":false,"family":"Wolfson","given":"David W.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":910783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knapik, Randall T.","contributorId":343307,"corporation":false,"usgs":false,"family":"Knapik","given":"Randall T.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":910784,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckardt Thomas, Anna","contributorId":343310,"corporation":false,"usgs":false,"family":"Buckardt Thomas","given":"Anna","affiliations":[{"id":24495,"text":"Iowa Department of Natural 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Atlantic","interactions":[],"lastModifiedDate":"2025-01-22T15:49:36.764574","indexId":"70261188","displayToPublicDate":"2024-11-21T09:05:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Projections of multiple climate-related coastal hazards for the US Southeast Atlantic","docAbstract":"Faced with accelerating sea level rise and changing ocean storm conditions, coastal communities require comprehensive assessments of climate-driven hazard impacts to inform adaptation measures. Previous studies have focused on flooding but rarely on other climate-related coastal hazards, such as subsidence, beach erosion and groundwater. Here, we project societal exposure to multiple hazards along the Southeast Atlantic coast of the United States. Assuming 1 m of sea level rise, more than 70% of the coastal residents and US \\$1 trillion in property are in areas projected to experience shallow and emerging groundwater, 15 times higher than daily flooding. Storms increase flooding exposure by an order of magnitude over daily flooding, which could impact up to ~50% of all coastal residents and US \\$770 billion in property value. The loss of up to ~80% of present-day beaches and high subsidence rates that currently affect over 1 million residents will exacerbate flooding and groundwater hazard risks.
","language":"English","publisher":"Nature","doi":"10.1038/s41558-024-02180-2","usgsCitation":"Barnard, P.L., Befus, K.M., Danielson, J.J., Engelstad, A.C., Erikson, L.H., Foxgrover, A.C., Hayden, M.K., Hoover, D.J., Leijnse, T., Massey, C., McCall, R.T., Nadal-Caraballo, N., Nederhoff, K., O'Neill, A., Parker, K.A., Shirzaei, M., Ohenhen, L.O., Swarzenski, P., Thomas, J.A., van Ormondt, M., Vitousek, S., Vos, K., Wood, N.J., Jones, J.M., and Jones, J., 2025, Projections of multiple climate-related coastal hazards for the US Southeast Atlantic: Nature Climate Change, v. 15, p. 101-109, https://doi.org/10.1038/s41558-024-02180-2.","productDescription":"9 p.","startPage":"101","endPage":"109","ipdsId":"IP-162659","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":489042,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/10919/123765","text":"External 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approach for quantifying benthic fish sizes and densities in annotated underwater images","docAbstract":"1. Benthic fishes are a common target of scientific monitoring but are difficult to quantify because of their close association to bottom habitats that are hard to access. Advances in image-acquisition technologies, machine vision, and deep learning have made capturing and quantifying fishes with cameras increasingly feasible. We present a method and open-source software called ‘FishScale’ to estimate benthic fish lengths, numeric abundance, and biomass density in underwater environments assessed with down-looking monocular images.
2. ‘FishScale’ estimates fish abundances and size frequencies from near-nadir monocular images where fish have already been semantically segmented. The software accounts for lens distortion, underwater magnification effects, and fish body curvature to automatically estimate fish lengths and the areas of images where they were captured. Numeric and biomass density are estimated through a deterministic machine vision algorithm that requires a user-provided length-weight relationship for species of interest and calibration images.
3. Results from validation studies show that lengths and weights can be estimated with high accuracy and precision for round goby (Neogobius melanostomus) captured in distorted action camera images, and from large-bodied lake trout (Salvelinus namaycush) imaged with a machine vision camera. The real-world utility of the approach is demonstrated in a case study estimating round goby abundances and size frequencies along a 10.7-km transect surveyed with an autonomous underwater vehicle in Lake Michigan, USA.
4. Our validation studies demonstrate that the approach estimates benthic and benthopelagic fish lengths and weights with little bias and good accuracy and precision for species with much different body shapes and sizes. The method is applicable to data collected using a variety of nadir imaging approaches with widespread applications to fisheries monitoring and quantification of any species or object for which nadir images and working distances between the camera and feature of interest are available.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.14453","usgsCitation":"Esselman, P.C., Moradi, S., Geisz, J.K., and Roussi, C., 2025, A transferable approach for quantifying benthic fish sizes and densities in annotated underwater images: Methods in Ecology and Evolution, v. 16, no. 1, p. 145-159, https://doi.org/10.1111/2041-210X.14453.","productDescription":"15 p.","startPage":"145","endPage":"159","ipdsId":"IP-132466","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":466686,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.14453","text":"Publisher Index Page"},{"id":466452,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13QVR2R","text":"USGS data release","linkHelpText":"FishScale"},{"id":464463,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Michigan, Wisconsin","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.44954986437058,\n 45.79365704611857\n ],\n [\n -88.27475541132564,\n 44.16814114178051\n ],\n [\n -88.0092703926447,\n 42.701569303239616\n ],\n [\n -87.68751722190896,\n 41.624028632419794\n ],\n [\n -86.36553765374144,\n 41.63295180048564\n ],\n [\n -85.83690337498572,\n 42.86335985317472\n ],\n [\n -86.0486664314116,\n 44.084867584867666\n ],\n [\n -84.79565964117464,\n 46.01898404311527\n ],\n [\n -85.98754537346298,\n 46.05276165976035\n ],\n [\n -87.44954986437058,\n 45.79365704611857\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Esselman, Peter C. 0000-0002-0085-903X pesselman@usgs.gov","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":346494,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter","email":"pesselman@usgs.gov","middleInitial":"C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":919341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moradi, Shadi 0000-0002-9120-8952","orcid":"https://orcid.org/0000-0002-9120-8952","contributorId":342265,"corporation":false,"usgs":false,"family":"Moradi","given":"Shadi","email":"","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":919342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Geisz, Joseph K. 0000-0001-6783-7057","orcid":"https://orcid.org/0000-0001-6783-7057","contributorId":342270,"corporation":false,"usgs":false,"family":"Geisz","given":"Joseph","email":"","middleInitial":"K.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":919343,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roussi, Christopher","contributorId":346495,"corporation":false,"usgs":false,"family":"Roussi","given":"Christopher","email":"","affiliations":[{"id":34530,"text":"Michigan Tech Research Institute","active":true,"usgs":false}],"preferred":false,"id":919344,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273041,"text":"70273041 - 2025 - Resource selection of the southern fox squirrel (Sciurus niger niger) in the coastal plain of Virginia","interactions":[],"lastModifiedDate":"2025-12-15T14:49:57.010841","indexId":"70273041","displayToPublicDate":"2024-11-20T11:12:13","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3694,"text":"Virginia Journal of Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Resource selection of the southern fox squirrel (Sciurus niger niger) in the coastal plain of Virginia","title":"Resource selection of the southern fox squirrel (Sciurus niger niger) in the coastal plain of Virginia","docAbstract":"The southern fox squirrel (Sciurus niger niger) is a subspecies of fox squirrel that ranges from southeastern Virginia to northern Florida. Throughout its Southeastern range, southern fox squirrel habitat of natural mixed pine-hardwood forests has been fragmented by agriculture and short-rotation pine plantations. In Virginia, remaining habitat has been transformed by fire suppression on the landscape and has in turn resulted in small, disjunct populations of southern fox squirrels. We sought to identify the home range and resource utilization of southern fox squirrels in the southern Coastal Plain of Virginia. From established nest boxes, we captured, radio collared and tracked four individuals at Big Woods Wildlife Management area and Piney Grove Complex in Sussex County in 2022. We observed an average male 95% and 50% adaptive kernel home range 173.49 ha (SE = 25.73, N = 2) and 40.62 ha (SE = 5.87, N = 2), respectively and an average female 95% and 50% adaptive kernel home range of 28.51 ha (SE = 0.49, N = 2) and 4.71 ha (SE = 0.34, N = 2), respectively. At both the second and third orders of habitat selection, squirrels selected for pine savanna cover types and short fire-return intervals.
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