Objective
Environmental DNA (eDNA) metabarcoding provides an attractive option for monitoring biodiversity in remote freshwater ecosystems, where the deployment of conventional gears encounters major logistical constraints. We evaluated eDNA metabarcoding for monitoring fish communities and early detection of nonnative species in three remote lakes on Isle Royale, Michigan, USA.
Methods
At each of the three lakes, we collected surface, midwater, and lake bottom samples from 10 sites during spring and fall sampling events. We performed metabarcoding on all the water samples, targeting the 12S region of all fish species.
Results
Despite a relatively small sample size (N = 60 samples per lake across two visits; 10 locations with three depths per location), we recovered 70% of all the species that were previously observed using conventional methods. We recovered several detections of putative Cisco Coregonus artedi, a vulnerable coldwater species, providing evidence that Cisco have persisted in these lakes. However, we found disentangling likely false positives from rare species challenging, which we overcame by employing multiple types of detection thresholds and a species-specific quantitative PCR assay.
Conclusions
Although we were able to successfully characterize the fish communities using eDNA metabarcoding, more attention needs to be given to the detection thresholds and communication protocols that provide guidance in interpretating new eDNA detections and using eDNA detections to inform management decisions. Although eDNA metabarcoding has limitations that should be accounted for at the outset of the project, the ease of sample collection makes eDNA metabarcoding an option for monitoring freshwater biodiversity in remote systems.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/najfmt/vqaf106","usgsCitation":"Iacaruso, N.J., Myers, J.T., Seider, M.J., and Davis, M.A., 2025, Environmental DNA metabarcoding for monitoring fish biodiversity in remote lakes: North American Journal of Fisheries Management, v. 46, no. 1, p. 84-100, https://doi.org/10.1093/najfmt/vqaf106.","productDescription":"17 p.","startPage":"84","endPage":"100","ipdsId":"IP-176505","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":499648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Isle Royale, Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.31231479627827,\n 48.18989928985803\n ],\n [\n -89.31231479627827,\n 47.823253980655494\n ],\n [\n -88.40909564980919,\n 47.823253980655494\n ],\n [\n -88.40909564980919,\n 48.18989928985803\n ],\n [\n -89.31231479627827,\n 48.18989928985803\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"46","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Iacaruso, Nicholas J. 0009-0004-0829-2252","orcid":"https://orcid.org/0009-0004-0829-2252","contributorId":366087,"corporation":false,"usgs":false,"family":"Iacaruso","given":"Nicholas","middleInitial":"J.","affiliations":[{"id":38021,"text":"University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":955227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Myers, Jared Thomas 0009-0004-9362-8792","orcid":"https://orcid.org/0009-0004-9362-8792","contributorId":363104,"corporation":false,"usgs":true,"family":"Myers","given":"Jared","middleInitial":"Thomas","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":955228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seider, Michael J. 0000-0002-6500-4710","orcid":"https://orcid.org/0000-0002-6500-4710","contributorId":366088,"corporation":false,"usgs":false,"family":"Seider","given":"Michael","middleInitial":"J.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":955229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Mark A. 0000-0001-9034-9430","orcid":"https://orcid.org/0000-0001-9034-9430","contributorId":366089,"corporation":false,"usgs":false,"family":"Davis","given":"Mark","middleInitial":"A.","affiliations":[{"id":38021,"text":"University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":955230,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272620,"text":"dr1217 - 2025 - Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2024","interactions":[],"lastModifiedDate":"2026-02-03T16:40:49.220576","indexId":"dr1217","displayToPublicDate":"2025-12-01T07:18:23","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1217","displayTitle":"Range-wide Population Trend Analysis for Greater Sage-Grouse (Centrocercus urophasianus)—Updated 1960–2024","title":"Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2024","docAbstract":"Greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) are at the center of State and national land-use policies largely because of their unique life-history traits as an ecological indicator for the health of sagebrush ecosystems. This updated population trend analysis provides State and Federal land and wildlife managers with the best available science to help guide management and conservation plans aimed at benefiting sage-grouse populations and the ecosystems they inhabit. This analysis relied on previously published population trend modeling methodology from Coates and others (2021, 2022a) and incorporates population lek count data for 1960–2024. Included in this report are methodological updates to lek count data aggregation, state-space model forecasting, and targeted annual warning system signals, which are detailed under individual Modification sections. State-space models estimated a 2.9-percent average annual decline in sage-grouse populations between 1966 and 2021 (Period 1, six population oscillations) across their geographical range. The average annual decline among climate clusters for the same number of oscillations ranged between 2.2 and 3.4 percent. Cumulative declines were 41.2, 64.1, and 78.8 percent range-wide in Period 5 (19 years), Period 3 (35 years), and Period 1 (55 years), respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1217","collaboration":"Prepared in cooperation with the Bureau of Land Management","programNote":"Ecosystems Mission Areas—Species Management Research Program and Land Management Research Program","usgsCitation":"Prochazka, B.G., Coates, P.S., Aldridge, C.L., O'Donnell, M.S., Edmunds, D.R., Monroe, A.P., Hanser, S.E., Wiechman, L.A., and Chenaille, M.P., 2025, Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2024: U.S. Geological Survey Data Report 1217, 22 p., https://doi.org/10.3133/dr1217.","productDescription":"Report: viii, 22 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-182475","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":496879,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1217/dr1217.XML"},{"id":496877,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OQWGIV","text":"USGS data release","description":"USGS data release","linkHelpText":"Trends and a targeted annual warning system for greater sage-grouse in the western United States (ver. 4.0, November 2025)"},{"id":496878,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1217/images"},{"id":496874,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1217/coverthb.jpg"},{"id":496875,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1217/dr1217.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1217"},{"id":496876,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1217/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1217"}],"country":"United States","state":"California, Colorado, Idaho, Montana, Nevada, North Dakota, Oregon, South Dakota, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.02726904687307,\n 37.11378745198651\n ],\n [\n -107.91246282672654,\n 39.23148053932573\n ],\n [\n -104.18656479624082,\n 42.68923879351195\n ],\n [\n -104.09712675152082,\n 44.90768367632023\n ],\n [\n -103.10713250018665,\n 45.28903162099806\n ],\n [\n -103.07124138706033,\n 46.81624492709619\n ],\n [\n -105.38823344586734,\n 48.94676636341262\n ],\n [\n -120.30657593063506,\n 48.87342393238805\n ],\n [\n -120.60087183124688,\n 42.81488245718879\n ],\n [\n -120.58608571052426,\n 38.32426094909158\n ],\n [\n -117.42786260245566,\n 36.55795546064512\n ],\n [\n -113.02726904687307,\n 37.11378745198651\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Knowledge of vital rates informs the conservation and management of threatened and endangered species. In the northern Great Plains, USA, the federally threatened Piping Plover Charadrius melodus uses a variety of nesting habitats including natural river sandbars and human-created sites in the lower Platte River system, Nebraska. In this area, off-river sandpit sites (i.e., active sand and gravel mines, transition sites, and lakeshore housing developments) are not managed to prioritize nesting and are often considered inferior habitat to sandbars. However, most Piping Plovers in the lower Platte River system nest off river, especially in years when sandbar habitat is limited. As the quantity of habitat provided at off-river sites is predicted to decline, evaluating vital rates among different off-river nesting habitats will inform future conservation efforts. We estimated annual survival and fidelity of adult (n = 165) and hatch-year (n = 671) Piping Plovers from 2008 to 2018 and within-season weekly survival of breeding adults (n = 271) from 2011 to 2024. Annual adult survival was 0.771 (95% CI = 0.733–0.804) and hatch-year survival was 0.394 (0.335–0.456). Fidelity to the study area was 0.737 (0.634–0.819) for adults and 0.261 (0.192–0.345) for hatch-years. Within-season apparent weekly survival was higher for Piping Plovers at lakeshore housing developments (0.946 [85% CI = 0.917–0.965]) than sand and gravel mines (0.909 [0.874–0.935]) and transition sites (0.881 [0.834–0.928]). Annual survival of adult and hatch-year birds were comparable to other studies and regions within the Northern Great Plains population, indicating no negative consequence of off-river nesting to survival. Considering that off-river habitats are important for the persistence of Piping Plovers in the lower Platte River system, continued monitoring of survival could help managers evaluate recovery implications under uncertain future habitat availability in the region.
","language":"English","publisher":"International Wader Study Group","doi":"10.18194/ws.00393","usgsCitation":"Forsberg, E., Powell, L., Swift, R.J., Jorgensen, J., and Vrtiska, M.P., 2025, Adult and hatch-year survival and fidelity of Piping Plovers Charadrius melodus in the lower Platte River system, Nebraska, USA: Wader Study, v. 132, no. 3, p. 210-222, https://doi.org/10.18194/ws.00393.","productDescription":"13 p.","startPage":"210","endPage":"222","ipdsId":"IP-175896","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":501476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"lower Platte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97.53013643892548,\n 41.848160677437875\n ],\n [\n -97.53013643892548,\n 40.86001959632918\n ],\n [\n -95.95197180336409,\n 40.86001959632918\n ],\n [\n -95.95197180336409,\n 41.848160677437875\n ],\n [\n -97.53013643892548,\n 41.848160677437875\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"132","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Forsberg, Elsa M.","contributorId":357514,"corporation":false,"usgs":false,"family":"Forsberg","given":"Elsa M.","affiliations":[{"id":16602,"text":"University of Nebraska, Lincoln","active":true,"usgs":false}],"preferred":false,"id":957558,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powell, Larkin A.","contributorId":352292,"corporation":false,"usgs":false,"family":"Powell","given":"Larkin A.","affiliations":[{"id":84162,"text":"School of Natural Resources, University of Nebraska-Lincoln, Lincoln, Nebraska USA","active":true,"usgs":false}],"preferred":false,"id":957559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swift, Rose J. 0000-0001-7044-6196","orcid":"https://orcid.org/0000-0001-7044-6196","contributorId":212082,"corporation":false,"usgs":true,"family":"Swift","given":"Rose","email":"","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":957560,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jorgensen, Joel G.","contributorId":169604,"corporation":false,"usgs":false,"family":"Jorgensen","given":"Joel G.","affiliations":[{"id":25564,"text":"Nongame Bird Program, Nebraska Game and Parks Commission, Lincoln, NE 68503","active":true,"usgs":false}],"preferred":false,"id":957561,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vrtiska, Mark P.","contributorId":201604,"corporation":false,"usgs":false,"family":"Vrtiska","given":"Mark","middleInitial":"P.","affiliations":[{"id":36216,"text":"NE Game & Parks","active":true,"usgs":false}],"preferred":false,"id":957562,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273001,"text":"70273001 - 2025 - A framework for analyzing wild turkey summer sighting data.","interactions":[],"lastModifiedDate":"2025-12-12T17:19:15.483358","indexId":"70273001","displayToPublicDate":"2025-11-30T10:04:01","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"A framework for analyzing wild turkey summer sighting data.","docAbstract":"Wildlife agencies collect data on productivity (e.g., proportion of hens with poults and number of poults per hen) of wild turkey (Meleagris gallopavo) to monitor population status and trends. However, sampling protocols to collect productivity data rely on opportunistic observations reported by wildlife agency personnel and the public and have changed over time and differed among agencies. A protocol to standardize data collection was adopted by most state wildlife agencies in 2019, but long-term historical datasets exist that cannot be analyzed readily to make inferences about spatial and temporal patterns in wild turkey productivity. We developed statistical models to allow comparisons and model trends in productivity among and within states even though data collection protocols changed over time and differed among states. We found greater spatial variation in the proportion of hens with poults than the number of poults per brood, which may reflect how environmental factors influence wild turkey productivity. Our models can also provide inferences about productivity when data are limited or temporally discontinuous for some spatial units. Additionally, we found that temporal and spatial variation in data collection, even under the new protocol, can affect inferences about trends in productivity. The statistical models we developed address the uncontrolled nature of when and where data are collected and offer the ability to investigate long-term patterns of productivity in relation to factors such as changing climate or habitat conditions.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1623","usgsCitation":"Diefenbach, D.R., Buderman, F.E., Casalena, M.J., Dye, M., Gates, R., Gigliotti, L., Long, C., Martin, K., Muthersbaugh, M., Peters, M.L., Sloan, J., Stiller, J., and Wiley, M., 2025, A framework for analyzing wild turkey summer sighting data.: Wildlife Society Bulletin, v. 49, no. 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Robert","contributorId":363855,"corporation":false,"usgs":false,"family":"Long","given":"C. Robert","affiliations":[],"preferred":false,"id":952073,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Martin, Katherine","contributorId":363856,"corporation":false,"usgs":false,"family":"Martin","given":"Katherine","affiliations":[],"preferred":false,"id":952074,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Muthersbaugh, Michael","contributorId":204945,"corporation":false,"usgs":false,"family":"Muthersbaugh","given":"Michael","affiliations":[],"preferred":false,"id":952075,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Peters, Michael L.","contributorId":363859,"corporation":false,"usgs":false,"family":"Peters","given":"Michael","middleInitial":"L.","affiliations":[],"preferred":false,"id":952076,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sloan, James","contributorId":354629,"corporation":false,"usgs":false,"family":"Sloan","given":"James","affiliations":[{"id":40718,"text":"New Jersey Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":952077,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Stiller, Joshua","contributorId":363864,"corporation":false,"usgs":false,"family":"Stiller","given":"Joshua","affiliations":[],"preferred":false,"id":952078,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wiley, Mark","contributorId":363866,"corporation":false,"usgs":false,"family":"Wiley","given":"Mark","affiliations":[],"preferred":false,"id":952079,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70274024,"text":"70274024 - 2025 - Predicted fish vulnerability to stream drying in the western U.S.A.","interactions":[],"lastModifiedDate":"2026-02-24T14:45:01.973166","indexId":"70274024","displayToPublicDate":"2025-11-30T09:17:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Predicted fish vulnerability to stream drying in the western U.S.A.","docAbstract":"The frequency, magnitude and extent of stream drying is increasing due to climate change and human water demand. Fish vulnerability to increased stream drying is a combination of sensitivity (innate tolerance to low streamflow) and exposure to stream drying. To understand fish tolerance to low flow and susceptibility to decline under changing streamflow conditions, we estimated species-specific measures of sensitivity to low streamflow, determined relationships to species traits and evaluated vulnerability to future reductions in streamflow for 60 species. We found that sensitivity varied across species, and some variation was explained by life history strategy, spawning strategy and body size. Periodic life history strategy, pelagic spawning and larger size corresponded to an increased sensitivity to stream drying. Under future projections of August streamflow, 90% of sites were predicted to decrease in flow magnitude. Vulnerability to changes in streamflow, the combination of sensitivity and exposure, varied slightly across the study species, with the percent of inhospitable sites under future climate scenarios increasing for 87% of the species. Despite being relatively insensitive to low streamflow, vulnerability was high for multiple species dominant in mountainous areas, driven by high levels of exposure to stream drying. Our results illustrate the potential for species traits to predict sensitivity to low streamflow and demonstrate that exposure may play a large role when defining species vulnerability to stream drying. The ability to predict species tolerances and susceptibility to decline will become increasingly important in prioritising conservation efforts under changing environmental conditions.
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The objectives of this study are to 1) provide a conceptual model to consider how differing spatial distributions and hydrologic timing of sediment sources, both upland and in-channel, can result in equifinal sediment transport outcomes, and 2) utilize analytical methods with widely available environmental datasets to infer sediment processes from stream gaging data. Hysteretic patterns of observed storm events were classified based on their direction and timing of peak sediment concentration, relative to streamflow, using records from 35 U.S. Geological Survey stream gages in the period between 2007 and 2023 within two different physiographic regions: the Mid-Atlantic Delaware River Basin (DRB) and the Midwestern Illinois River Basin (IRB). The DRB contains mixed forest, urban, suburban and agricultural watersheds over diverse topography, and the IRB is primarily an intensively managed agricultural watershed on flat terrain. We use principal component analysis and linear discriminant analysis to infer regional hydrologic relations with turbidity dynamics, and to identify the primary hydrologic and land surface characteristics most effective at distinguishing between hysteretic classes in each region. These analyses reveal underlying regional relations in storm event hydrodynamics and landscape characteristics that contribute to varying patterns in sediment dynamics. Incorporating these sediment dynamic relations with spatial distributions and hydrologic timing of sediment sources could help to improve process understanding and predictive capability of fine sediment transport in watersheds.
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2025 - Interspecific interactions moderate direct effects of vegetation change resulting from prescribed fires","interactions":[],"lastModifiedDate":"2026-02-02T21:34:17.940337","indexId":"70273803","displayToPublicDate":"2025-11-27T15:29:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Interspecific interactions moderate direct effects of vegetation change resulting from prescribed fires","docAbstract":"Savannas depend on frequent, low-intensity fires that shape animal and plant communities. These fires alter animal populations, movement, and habitat use. Here, we report on how fires in a longleaf pine (Pinus palustris) savanna affected small mammal microhabitat use via changes in competition and predation. We monitored small mammal populations and vegetation subjected to biennial prescribed fires and compared microhabitat use of three small mammal populations [hispid cotton rats (Sigmodon hispidus), cotton mice (Peromyscus gossypinus) and oldfield mice (Peromyscus polionotus)] in the presence and absence of mesocarnivores while accounting for changes in density and movement of each small mammal species. Densities of cotton rats varied greatly across years but were similar between predator exclosures and controls. However, frequency of use was greater in exclosures than in controls irrespective of vegetation characteristics, suggesting predation risk altered cotton rat microhabitat use. Conversely, higher relative abundance of cotton rats was associated with lower cotton mouse and oldfield mouse use, suggesting spatial separation in niche and indicating that cotton mice expand their realized niche following predation-induced declines of cotton rats associated with prescribed burn events. Our results contribute to a better understanding of pyrodiversity and how interspecific interactions can moderate effects of vegetation changes following prescribed fires.","language":"English","publisher":"Springer","doi":"10.1038/s41598-025-26529-5","usgsCitation":"Shastry, V., Conner, L.M., Morris, G., Royle, A., Smith, L., and Morin, D., 2025, Interspecific interactions moderate direct effects of vegetation change resulting from prescribed fires: Scientific Reports, v. 15, no. 1, 42385, 12 p., https://doi.org/10.1038/s41598-025-26529-5.","productDescription":"42385, 12 p.","ipdsId":"IP-181552","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":499616,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-26529-5","text":"Publisher Index Page"},{"id":499417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","county":"Baker County","otherGeospatial":"Jones Center at Ichauway","volume":"15","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Shastry, Varsha","contributorId":365822,"corporation":false,"usgs":false,"family":"Shastry","given":"Varsha","affiliations":[{"id":87229,"text":"Mississippi State University; The Jones Center at Ichauway","active":true,"usgs":false}],"preferred":false,"id":954876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conner, L. Mike","contributorId":365823,"corporation":false,"usgs":false,"family":"Conner","given":"L.","middleInitial":"Mike","affiliations":[{"id":56171,"text":"The Jones Center at Ichauway","active":true,"usgs":false}],"preferred":false,"id":954877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morris, Gail","contributorId":365824,"corporation":false,"usgs":false,"family":"Morris","given":"Gail","affiliations":[{"id":56171,"text":"The Jones Center at Ichauway","active":true,"usgs":false}],"preferred":false,"id":954878,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":954879,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Lora","contributorId":156438,"corporation":false,"usgs":false,"family":"Smith","given":"Lora","affiliations":[],"preferred":false,"id":954880,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morin, Dana","contributorId":264602,"corporation":false,"usgs":false,"family":"Morin","given":"Dana","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":954881,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273268,"text":"70273268 - 2025 - Rare milkvetch (Astragalus) persistence at a utility-scale solar energy facility in the Mojave Desert","interactions":[],"lastModifiedDate":"2025-12-29T15:38:48.704275","indexId":"70273268","displayToPublicDate":"2025-11-27T09:31:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Rare milkvetch (Astragalus) persistence at a utility-scale solar energy facility in the Mojave Desert","title":"Rare milkvetch (Astragalus) persistence at a utility-scale solar energy facility in the Mojave Desert","docAbstract":"Utility-scale solar energy (USSE) development is driving the projected growth in global renewable energy capacity but comes with environmental tradeoffs. New, alternative construction methods are promoted to minimize impacts to soils, vegetation, and hydrology; however, the disturbance created by these methods requires further investigation. We evaluated the population of a rare annual species, threecorner milkvetch (Astragalus geyeri var. triquetrus), at the Gemini Solar Project in the Mojave Desert, USA, two years after construction. Gemini was required to minimize disturbance in the threecorner milkvetch habitat, providing a unique opportunity to study the plant population and life history characteristics of a rare plant species under novel construction methods. Our objectives were to compare plant population characteristics of threecorner milkvetch inside and outside the Gemini footprint and in different photovoltaic (PV) panel microsites (interspace, panel dripline, under panel). We hypothesized that 1) threecorner milkvetch would have lower survival, reproduction, and growth, and a later phenology, inside compared to outside the facility, and 2) that these negative effects on plant demography and phenology would intensify with increasing proximity to photovoltaic panels in the solar array due to an increasing effect of disturbance and reduction of light and water availability. The results of this 1-year study during a favorable year of rainfall demonstrate the persistence of a rare Mojave annual plant species within an altered environment at a USSE facility. We found that threecorner milkvetch had an earlier phenology, grew larger, and had a higher fecundity at Gemini compared to plants off-site. Survivorship between the two populations, however, was not significantly different. Although growth and reproductive metrics were not correlated with distance to panel, minimal threecorner milkvetch emergence occurred directly under the PV panels and along their driplines, indicating a potential loss of suitable habitat if this pattern becomes more widespread in space or through time. Novel construction techniques for USSE could be considered moving forward to minimize impact on aboveground vegetation and maintain viable seed banks. The results of this study can assist land managers in making decisions about USSE development as the demand grows.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2025.1697878","usgsCitation":"Pereira, T.J., Karban, C.C., Kobelt, L., and Munson, S.M., 2025, Rare milkvetch (Astragalus) persistence at a utility-scale solar energy facility in the Mojave Desert: Frontiers in Ecology and Evolution, v. 13, 1697878, 12 p., https://doi.org/10.3389/fevo.2025.1697878.","productDescription":"1697878, 12 p.","ipdsId":"IP-182848","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":498294,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2025.1697878","text":"Publisher Index Page"},{"id":498143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.87877698144997,\n 36.55309391567229\n ],\n [\n -114.87877698144997,\n 36.398061936746544\n ],\n [\n -114.70717521419876,\n 36.398061936746544\n ],\n [\n -114.70717521419876,\n 36.55309391567229\n ],\n [\n -114.87877698144997,\n 36.55309391567229\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Pereira, Tiffany J.","contributorId":364633,"corporation":false,"usgs":false,"family":"Pereira","given":"Tiffany","middleInitial":"J.","affiliations":[{"id":86877,"text":"Desert Research Institute [DRI] Conservation Ecology Lab, Division of Earth and Ecosystem Sciences, DRI, Las Vegas, NV, US","active":true,"usgs":false}],"preferred":false,"id":952964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karban, Claire C 0000-0002-6157-031X","orcid":"https://orcid.org/0000-0002-6157-031X","contributorId":344987,"corporation":false,"usgs":true,"family":"Karban","given":"Claire","email":"","middleInitial":"C","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":952965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kobelt, Lara A.","contributorId":350355,"corporation":false,"usgs":false,"family":"Kobelt","given":"Lara A.","affiliations":[{"id":83722,"text":"Bureau of Land Management, Southern Nevada District Office, 4701 North Torrey Pines Dr., Las Vegas, NV 89130","active":true,"usgs":false}],"preferred":false,"id":952966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":220026,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":952967,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272631,"text":"70272631 - 2025 - The effects of carnivory and herbivory on the energy balance of Arctic grizzly bears","interactions":[],"lastModifiedDate":"2025-12-01T15:26:20.339626","indexId":"70272631","displayToPublicDate":"2025-11-27T09:18:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"The effects of carnivory and herbivory on the energy balance of Arctic grizzly bears","docAbstract":"Omnivores often face tradeoffs between selecting for spatially dispersed energy-dense vertebrate prey versus densely distributed herbivorous resources that have limited energetic value per unit intake. Arctic grizzly bears (Ursus arctos) are large omnivores within a resource-limited ecosystem that are known to exhibit smaller body masses and occur at lower densities than grizzly bears in other regions of North America. We evaluated the energy balance of Arctic grizzly bears during a portion of the fall hyperphagic period in two ecologically differing regions on Alaska’s northern Arctic coast by monitoring mass change, food intake, activity, and energy expenditure of 12 individuals over 17–22 days. Bears in coastal areas were more carnivorous than bears in the foothills that were predominantly herbivorous and frugivorous. Carnivory was associated with greater movement, body fat, and energy expenditure and two of four carnivorous bears lost mass. Overall, the mean body fat of the bears in this study was 34% lower than other grizzly bear populations in North America in the fall. Furthermore, the bears in this study exhibited relatively small changes in body mass (x̄= 3%, range =−2 to 11%) that were 60% lower than other grizzly bear populations which typically gain substantial mass in the fall in preparation for denning. Our results, while representing a snapshot from a small number of bears during the fall hyperphagic period, are consistent with previous studies and indicate limited availability of energy-dense food resources during this time for grizzly bears in this region of the Arctic.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00442-025-05830-0","usgsCitation":"Pagano, A.M., Rode, K.D., Nicholson, K.L., Leacock, W.B., Stricker, C.A., and Robbins, C.T., 2025, The effects of carnivory and herbivory on the energy balance of Arctic grizzly bears: Oecologia, v. 208, 2, 15 p., https://doi.org/10.1007/s00442-025-05830-0.","productDescription":"2, 15 p.","ipdsId":"IP-179627","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":496947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"North Slope","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -152,\n 70.5\n ],\n [\n -152,\n 69.5\n ],\n [\n -144,\n 69.5\n ],\n [\n -144,\n 70.5\n ],\n [\n -152,\n 70.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"208","noUsgsAuthors":false,"publicationDate":"2025-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":951049,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":951050,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nicholson, Kerry L.","contributorId":363061,"corporation":false,"usgs":false,"family":"Nicholson","given":"Kerry","middleInitial":"L.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":951051,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leacock, William B.","contributorId":363062,"corporation":false,"usgs":false,"family":"Leacock","given":"William","middleInitial":"B.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":951052,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":951053,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robbins, Charles T.","contributorId":363063,"corporation":false,"usgs":false,"family":"Robbins","given":"Charles","middleInitial":"T.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":951054,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70275282,"text":"70275282 - 2025 - Sentinel-1 SAR estimates of snowmelt onset coincide with SNOTEL soil moisture pulses across the western U.S.","interactions":[],"lastModifiedDate":"2026-04-27T15:12:58.559551","indexId":"70275282","displayToPublicDate":"2025-11-27T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Sentinel-1 SAR estimates of snowmelt onset coincide with SNOTEL soil moisture pulses across the western U.S.","docAbstract":"While there have been recent advancements in synthetic aperture radar (SAR)-based snow water equivalent (SWE) retrievals, obtaining accurate estimates of SWE requires knowledge of the amount of liquid water content (LWC) in the snowpack given its strong impact on radar velocity. Recent studies have utilised Sentinel-1 SAR to identify snowmelt runoff onset in complex, high-elevation terrain based on a seasonal minimum backscatter time-series; however, detailed investigations into the snowpack state before and after snowmelt runoff onset are lacking. In this study, we integrated repeat field measurements at five sites, SNOw TELemetry (SNOTEL) station data (n = 260) from across the Western United States, and paired Sentinel-1 SAR estimates of snowmelt runoff onset to (1) assess the snowpack state prior to and after Sentinel-1 SAR-derived runoff onset estimates, and (2) evaluate Sentinel-1 SAR estimates of runoff onset with SNOTEL-derived estimates of melt output via soil moisture ‘pulses’. We found that on the date of minimum backscatter, the snowpack was isothermal at three of the five field sites, and snow pit-measured LWC was increasing at all field sites relative to previous survey dates. SNOTEL soil moisture pulses preceded Sentinel-1 SAR estimates of snowmelt runoff onset by a median of 3 days (standard deviation = ±25.3 days) and post-dated peak SWE by a median of 3 days (standard deviation = ±18.2 days). Snow density and the number of positive degree days on soil moisture pulse date increased with latitude and longitude and decreased with elevation. Although satellite-based estimates of snowmelt runoff onset provide a promising approach for improving spaceborne retrievals of SWE, local climatological conditions exert significant influence on meltwater runoff onset signal clarity for both in situ and satellite-based estimates.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70341","usgsCitation":"Detre, A., McGrath, D., Gagliano, E., Bonnell, R.R., Webb, R., Marshall, H., and Shean, D., 2025, Sentinel-1 SAR estimates of snowmelt onset coincide with SNOTEL soil moisture pulses across the western U.S.: Hydrological Processes, v. 39, no. 12, e70341, 18 p., https://doi.org/10.1002/hyp.70341.","productDescription":"e70341, 18 p.","ipdsId":"IP-180871","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":503550,"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 -125.75873923043854,\n 48.828742030010915\n ],\n [\n -125.75873923043854,\n 34.45259906675574\n ],\n [\n -104.65537215897085,\n 34.45259906675574\n ],\n [\n -104.65537215897085,\n 48.828742030010915\n ],\n [\n -125.75873923043854,\n 48.828742030010915\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Detre, Ally 0009-0004-6977-9283","orcid":"https://orcid.org/0009-0004-6977-9283","contributorId":370422,"corporation":false,"usgs":false,"family":"Detre","given":"Ally","affiliations":[{"id":79077,"text":"Department of Geosciences, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":960331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGrath, Daniel 0000-0002-9462-6842","orcid":"https://orcid.org/0000-0002-9462-6842","contributorId":221142,"corporation":false,"usgs":false,"family":"McGrath","given":"Daniel","affiliations":[{"id":40333,"text":"Department of Geosciences, Colorado State University, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":960332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gagliano, Eric","contributorId":370423,"corporation":false,"usgs":false,"family":"Gagliano","given":"Eric","affiliations":[{"id":12994,"text":"Department of Civil and Environmental Engineering, University of Washington","active":true,"usgs":false}],"preferred":false,"id":960333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonnell, Randall Ray 0000-0002-8812-351X","orcid":"https://orcid.org/0000-0002-8812-351X","contributorId":365098,"corporation":false,"usgs":true,"family":"Bonnell","given":"Randall","middleInitial":"Ray","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":960334,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Webb, Ryan","contributorId":330966,"corporation":false,"usgs":false,"family":"Webb","given":"Ryan","email":"","affiliations":[{"id":79081,"text":"Department of Civil and Architectural Engineering and Construction Management, University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":960335,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marshall, Hans-Peter","contributorId":365100,"corporation":false,"usgs":false,"family":"Marshall","given":"Hans-Peter","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":960336,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shean, David","contributorId":299742,"corporation":false,"usgs":false,"family":"Shean","given":"David","affiliations":[],"preferred":false,"id":960337,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274577,"text":"70274577 - 2025 - From fences to roads: Changes in barrier behaviour of Mongolian gazelle across different types of linear infrastructure in Mongolia","interactions":[],"lastModifiedDate":"2026-04-06T15:48:16.485239","indexId":"70274577","displayToPublicDate":"2025-11-26T14:51:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3174,"text":"Proceedings of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"From fences to roads: Changes in barrier behaviour of Mongolian gazelle across different types of linear infrastructure in Mongolia","docAbstract":"Poorly designed linear infrastructure can reduce habitat connectivity and be major barriers for migratory wildlife. An important start at effective mitigation is understanding how individuals respond when barriers are encountered. This can be done via comparison of fine- and broad-scale behavioural responses to various anthropogenic barrier types. We classified fine-scale responses of 62 Mongolian gazelles (Procapra gutturosa) across different barrier types, seasons and times of day. We also investigated interactions at a broader scale by measuring the length of linear infrastructure traced, interaction duration and crossing success rate. We learned that gazelle behaviour varied according to barrier permeability, and that fences were major obstacles. Gazelles exhibited similar bouncing behaviour when confronted with paved roads as with fences, suggesting paved roads can act as semi-permeable barriers during high traffic volume. Broad-scale movement patterns revealed gazelles travelled considerable distances along fences—averaging 40.2 km, and up to 211.6 km—before moving away or crossing. Long-distance tracing movements can help identify areas with the strongest barrier effect and guide mitigation measures for current and future linear infrastructure. Designing infrastructure and implementing conservation strategies for ungulates in steppe ecosystems will benefit from taking into account behavioural responses at both fine and broad scales.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rspb.2025.2093","usgsCitation":"Sévêque, A., Mendgen, P., Freeman, I., Bayarbaatar, B., Kauffman, M.J., Olsen, K., Usukhjargal, D., Uuganbayar, G., Xu, W., Mueller, T., and Dejid, N., 2025, From fences to roads: Changes in barrier behaviour of Mongolian gazelle across different types of linear infrastructure in Mongolia: Proceedings of the Royal Society B: Biological Sciences, v. 292, no. 2059, 20252093, https://doi.org/10.1098/rspb.2025.2093.","productDescription":"20252093","ipdsId":"IP-180143","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":501972,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mongolia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 86.14815830860528,\n 52.011926051186464\n ],\n [\n 86.14815830860528,\n 41.82159331743961\n ],\n [\n 119.95403757641532,\n 41.82159331743961\n ],\n [\n 119.95403757641532,\n 52.011926051186464\n ],\n [\n 86.14815830860528,\n 52.011926051186464\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"292","issue":"2059","noUsgsAuthors":false,"publicationDate":"2025-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Sévêque, Anthony","contributorId":369043,"corporation":false,"usgs":false,"family":"Sévêque","given":"Anthony","affiliations":[{"id":27439,"text":"Senckenberg Biodiversity and Climate Research Centre","active":true,"usgs":false}],"preferred":false,"id":958345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mendgen, Philipp","contributorId":339036,"corporation":false,"usgs":false,"family":"Mendgen","given":"Philipp","email":"","affiliations":[{"id":81238,"text":"Goethe University","active":true,"usgs":false}],"preferred":false,"id":958346,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Ian","contributorId":335506,"corporation":false,"usgs":false,"family":"Freeman","given":"Ian","email":"","affiliations":[],"preferred":false,"id":958347,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bayarbaatar, Buuveibaatar","contributorId":287848,"corporation":false,"usgs":false,"family":"Bayarbaatar","given":"Buuveibaatar","affiliations":[{"id":61638,"text":"Wildlife Conservation Society, Mongolia Program, Ulaanbaatar, Mongolia","active":true,"usgs":false}],"preferred":false,"id":958348,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":958349,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Olsen, Kirk","contributorId":369044,"corporation":false,"usgs":false,"family":"Olsen","given":"Kirk","affiliations":[{"id":87706,"text":"Wildlife Conservation Society, Mongolia Program","active":true,"usgs":false}],"preferred":false,"id":958350,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Usukhjargal, Dorj","contributorId":287888,"corporation":false,"usgs":false,"family":"Usukhjargal","given":"Dorj","email":"","affiliations":[{"id":61645,"text":"Hustai National Park Trust, Mongolia","active":true,"usgs":false}],"preferred":false,"id":958351,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Uuganbayar, Ganbold","contributorId":287889,"corporation":false,"usgs":false,"family":"Uuganbayar","given":"Ganbold","email":"","affiliations":[{"id":61645,"text":"Hustai National Park Trust, Mongolia","active":true,"usgs":false}],"preferred":false,"id":958352,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Xu, Wenjing","contributorId":285005,"corporation":false,"usgs":false,"family":"Xu","given":"Wenjing","email":"","affiliations":[],"preferred":false,"id":958353,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mueller, Thomas","contributorId":337677,"corporation":false,"usgs":false,"family":"Mueller","given":"Thomas","affiliations":[{"id":81034,"text":"Goethe-University Frankfurt and Senckenberg Biodiversity and Climate Research Centre","active":true,"usgs":false}],"preferred":false,"id":958354,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Dejid, Nandintsetseg","contributorId":287854,"corporation":false,"usgs":false,"family":"Dejid","given":"Nandintsetseg","affiliations":[{"id":61644,"text":"Senckenberg Biodiversity and Climate Research Centre, Frankfurt (Main), Germany","active":true,"usgs":false}],"preferred":false,"id":958355,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70272619,"text":"ofr20251054 - 2025 - Comparisons of shoreline positions from satellite-derived and traditional field- and remote-sensing techniques","interactions":[],"lastModifiedDate":"2026-02-03T16:40:03.569804","indexId":"ofr20251054","displayToPublicDate":"2025-11-26T12:05:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1054","displayTitle":"Comparisons of Shoreline Positions from Satellite-Derived and Traditional Field- and Remote-Sensing Techniques","title":"Comparisons of shoreline positions from satellite-derived and traditional field- and remote-sensing techniques","docAbstract":"Satellite-derived shorelines (SDS) have the potential to help researchers answer critical coastal science questions and support work to predict coastal change by filling in the spatial and temporal gaps present in current field-based and remote-sensing data collection methods. The U.S. Geological Survey conducted comparison analyses of traditionally sourced shorelines and SDS in diverse coastal landscapes to determine how SDS could be used in ongoing and future work across varied coastal environments and provided some initial findings that could be used for implementation. Using CoastSeg, a browser-based program for SDS detection and mapping, SDS for the period 1984–2023 for multiple locations across the United States were compared to shoreline positions from traditionally sourced shoreline data. In this report, the authors present these comparisons alongside lessons learned and challenges encountered when building SDS workflows in different coastal locations. Results show that individual SDS have larger uncertainty and yet produced similar linear trends to sparser, traditionally sourced shoreline data; because SDS methods provide orders of magnitude more data than traditional shoreline-detection methods, they can be used to evaluate shoreline behaviors. Refining average scalar slopes used in tidal corrections did not result in substantial decreases in uncertainty. Using lessons from this work to outline needs for regional implementation, initial setup time would be considerable, being on the order of weeks. However, once complete, shoreline detections and analyses are fast (on the order of minutes to hours) and achievable using a desktop computer.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251054","programNote":"Coastal and Marine Hazards and Resources Program","usgsCitation":"O’Neill, A.C., Batiste, S.F., Buscombe, D.D., Burgess, J., Doran, K.S., Gibbs, A.E., Henderson, R.E., Heslin, J.L., Janda, C.N., Lundine, M.A., Terrano, J.F., Warrick, J.A., and Weber, K.M., 2025, Comparisons of shoreline positions from satellite-derived and traditional field- and remote-sensing techniques: U.S. Geological Survey Open-File Report 2025–1054, 41 p., https://doi.org/10.3133/ofr20251054.","productDescription":"viii, 41 p.","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-177965","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":496871,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251054/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1054 HTML"},{"id":496869,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1054/coverthb.jpg"},{"id":496873,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1054/images/"},{"id":496872,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1054/ofr20251054.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1054 XML"},{"id":496870,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1054/ofr20251054.pdf","text":"Report","size":"8.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1054 PDF"}],"country":"United States","state":"Alaska, Florida, Massachusetts, Washington","otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.23262232723678,\n 42.09708901142952\n ],\n [\n -70.23262232723678,\n 41.7296953201367\n ],\n [\n -69.88869105489118,\n 41.7296953201367\n ],\n [\n -69.88869105489118,\n 42.09708901142952\n ],\n [\n -70.23262232723678,\n 42.09708901142952\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.8586476385848,\n 27.855837758503966\n ],\n [\n -82.8586476385848,\n 27.73142586709062\n ],\n [\n -82.70953873940795,\n 27.73142586709062\n ],\n [\n -82.70953873940795,\n 27.855837758503966\n ],\n [\n -82.8586476385848,\n 27.855837758503966\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.6354762817767,\n 48.15958852423637\n ],\n [\n -123.6354762817767,\n 48.07700409405399\n ],\n [\n -123.49731286568142,\n 48.07700409405399\n ],\n [\n -123.49731286568142,\n 48.15958852423637\n ],\n [\n -123.6354762817767,\n 48.15958852423637\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -143.75227424150037,\n 70.14885784620938\n ],\n [\n -143.75227424150037,\n 70.08259373043822\n ],\n [\n -143.56394337243916,\n 70.08259373043822\n ],\n [\n -143.56394337243916,\n 70.14885784620938\n ],\n [\n -143.75227424150037,\n 70.14885784620938\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.26663872487647,\n 18.348796644288143\n ],\n [\n -67.26663872487647,\n 18.327492880601937\n ],\n [\n -67.24442657044659,\n 18.327492880601937\n ],\n [\n -67.24442657044659,\n 18.348796644288143\n ],\n [\n -67.26663872487647,\n 18.348796644288143\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission Street
Santa Cruz, California 95060
Sudden habitat loss associated with environmental disturbance can trigger animals to move from affected to undisturbed areas, where increases in local density may occur. Although pathogen transmission is strongly related to local density, how crowding after habitat loss affects infection dynamics in wild populations remains unclear. Here we conceptualize the Disturbance-Density-Disease hypothesis, which posits that disturbance-induced habitat loss results in increased pathogen prevalence via increases in local density at adjacent, undisturbed patches. We then used data from before, during, and after flooding disturbance to test this hypothesis in boreal toads Anaxyrus boreas boreas co-occurring with the pathogenic fungus Batrachochytrium dendrobatidis (Bd). We collected Bd samples from captured individuals during a 5-year (2015–2019) mark-recapture study of boreal toads (n = 1295) that breed in beaver ponds in western Wyoming, USA. During spring of 2017, an extreme flooding event destroyed several beaver dams, resulting in the loss of breeding habitat. We compared host density and pathogen prevalence pre- and post-disturbance at sites affected versus unaffected by flooding. At affected sites, population density and Bd prevalence increased at adjacent, undisturbed ponds following the sudden loss of habitat. Moreover, neither host density nor Bd prevalence increased at control sites in areas unaffected by flooding. Taken together, our results support hypothesized links between disturbance, adjacent increases in density, and subsequent increases in pathogen prevalence. Our study contributes to a growing body of ecological research leveraging natural experiments to extract insights from extreme disturbance events. By doing so, we demonstrate an important consequence of disturbance beyond proximate habitat loss and introduce a clear conceptual approach (the Disturbance-Density-Disease hypothesis) to understanding how pathogen transmission can be affected by disturbance via alterations to local density.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.70265","usgsCitation":"Barrile, G.M., Chalfoun, A.D., Walters, A.W., Merkle, J.A., 2025, Density as a mechanism linking habitat disturbance to increased pathogen prevalence: Evidence from a natural experiment: Ecology, v. 106, no. 11, e70265, 15 p., https://doi.org/10.1002/ecy.70265.","productDescription":"e70265, 15 p.","ipdsId":"IP-171436","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Bridger-Teton National Forest, northern Wyoming Range, Wind River Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.9701288311253,\n 44.01466129417253\n ],\n [\n -110.9701288311253,\n 41.8640098196185\n ],\n [\n -108.35885871498692,\n 41.8640098196185\n ],\n [\n -108.35885871498692,\n 44.01466129417253\n ],\n [\n -110.9701288311253,\n 44.01466129417253\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"106","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Barrile, Gabriel M.","contributorId":366853,"corporation":false,"usgs":false,"family":"Barrile","given":"Gabriel","middleInitial":"M.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":956316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":956317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956318,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Merkle, Jerod A.","contributorId":366854,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod","middleInitial":"A.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":956319,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272658,"text":"70272658 - 2025 - The acoustic-Doppler current profiler (ADCP): A comprehensive tool for river-reach hydromorphodynamics","interactions":[],"lastModifiedDate":"2025-12-03T17:19:25.259086","indexId":"70272658","displayToPublicDate":"2025-11-26T11:01:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"The acoustic-Doppler current profiler (ADCP): A comprehensive tool for river-reach hydromorphodynamics","docAbstract":"This paper introduces the use of acoustic Doppler current profiler (ADCP) measurements as input for the Acoustic Mapping Velocimetry (AMV) method, a technique for characterizing the dynamics of riverine bedforms. The performance of this new approach, ADCP-AMV, is compared with input from a multibeam echosounder through a field study conducted on the Mississippi River (USA). A virtual ADCP tool has been created to support the ADCP-AMV measurements with optimal data density predictions. To the authors’ knowledge, this is the first time ADCP measurements have been used in conjunction with the AMV dune-tracking method. Subsequently, the paper discusses the coupling of ADCP-AMV measurements with ancillary data extracted from the ADCP. These ancillary data are processed using previously developed protocols to characterize hydrodynamics and the suspended sediment distribution in the water column. This paper emphasizes the capability of ADCPs to characterize open-channel river hydromorphodynamic parameters with high spatiotemporal resolution. Recommendations to accurately and efficiently acquire these multi-variable measurements and derived datasets are discussed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2025.105180","usgsCitation":"Fleit, G., Muste, M., Baranya, S., Kim, D., Whaling, A., McAlpin, T., and You, H., 2025, The acoustic-Doppler current profiler (ADCP): A comprehensive tool for river-reach hydromorphodynamics: Advances in Water Resources, v. 206, 105180, 15 p., https://doi.org/10.1016/j.advwatres.2025.105180.","productDescription":"105180, 15 p.","ipdsId":"IP-177812","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":497092,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.advwatres.2025.105180","text":"Publisher Index Page"},{"id":497018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","city":"Memphis","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.08,\n 35.13\n ],\n [\n -90.08,\n 35.12\n ],\n [\n -90.07,\n 35.12\n ],\n [\n -90.07,\n 35.13\n ],\n [\n -90.08,\n 35.13\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"206","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fleit, Gábor","contributorId":363187,"corporation":false,"usgs":false,"family":"Fleit","given":"Gábor","affiliations":[{"id":86640,"text":"Research fellow at Budapest University of Technology and Economics","active":true,"usgs":false}],"preferred":false,"id":951233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muste, Marian 0000-0002-5975-462X","orcid":"https://orcid.org/0000-0002-5975-462X","contributorId":192136,"corporation":false,"usgs":false,"family":"Muste","given":"Marian","email":"","affiliations":[],"preferred":false,"id":951234,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baranya, Sándor","contributorId":363188,"corporation":false,"usgs":false,"family":"Baranya","given":"Sándor","affiliations":[{"id":86642,"text":"Professor (Associate) at Budapest University of Technology and Economics","active":true,"usgs":false}],"preferred":false,"id":951235,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kim, Dongsu","contributorId":363189,"corporation":false,"usgs":false,"family":"Kim","given":"Dongsu","affiliations":[{"id":86643,"text":"Professor at Dankook University","active":true,"usgs":false}],"preferred":false,"id":951236,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whaling, Amanda 0000-0003-1375-8323","orcid":"https://orcid.org/0000-0003-1375-8323","contributorId":213953,"corporation":false,"usgs":true,"family":"Whaling","given":"Amanda","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951237,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McAlpin, Tate","contributorId":363190,"corporation":false,"usgs":false,"family":"McAlpin","given":"Tate","affiliations":[{"id":86644,"text":"Coastal and Hydraulics Laboratory, U.S. Army Engineer Research and Development Center, Vicksburg, MS, USA.","active":true,"usgs":false}],"preferred":false,"id":951238,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"You, Hojun","contributorId":363191,"corporation":false,"usgs":false,"family":"You","given":"Hojun","affiliations":[{"id":86646,"text":"Senior Researcher at K-water Research Institute","active":true,"usgs":false}],"preferred":false,"id":951239,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70272640,"text":"70272640 - 2025 - Potential thiamine deficiency of phytoplankton across a productivity gradient and seasons in Ohio lakes","interactions":[],"lastModifiedDate":"2025-12-02T16:25:40.80763","indexId":"70272640","displayToPublicDate":"2025-11-26T10:21:30","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Potential thiamine deficiency of phytoplankton across a productivity gradient and seasons in Ohio lakes","docAbstract":"The depth level at which porphyry Cu–forming magmas fractionated and exsolved mineralizing fluids is actively debated. In the classic model, extensive magma fractionation occurs in large, upper crustal magma chambers, and concomitant fluid exsolution leads to forceful expulsion of residual magmas in the form of porphyry dikes, stocks, and breccia pipes, which subsequently serve as pathways for the mineralizing fluids. In contrast, some recent studies highlighting the role of deep crustal magma fractionation in the production of fertile magmas essentially deny the existence of upper crustal magma chambers at the time of mineralization. To address this, we conducted a detailed thermobarometric investigation of 13 intermediate to felsic, porphyritic intrusive rocks related to porphyry-skarn Cu mineralization at Santa Rita and Hanover-Fierro, New Mexico, United States, representing two premineralization magmas (61–60 Ma), seven synmineralization magmas (60–58 Ma), and four late- to postmineralization magmas (58–57 Ma).
For each sample, the pressure of last magma crystallization before final magma ascent to the current exposure level was reconstructed based on Al-in-hornblende barometry of small hornblende inclusions trapped within quartz phenocrysts and through titanium-in-quartz (TitaniQ) thermobarometry of the host quartz phenocrysts themselves. Since quartz is one of the last crystallizing magmatic minerals, and no significant phenocryst growth could have occurred in small dikes and stocks after final magma emplacement, quartz phenocrysts and their contained hornblende inclusions record the depth of last magma crystallization before final magma ascent. When present, hornblende phenocrysts and hornblende inclusions within other major phenocrysts were also analyzed. Both quartz and hornblende barometers return consistent average pressures of 3.2 ± 0.4 kbar for the entire suite of pre- to postmineralization magmas, corresponding to depths of 11 to 14 km. The synmineralization magmas return even more consistent average pressures of 3.1 ± 0.2 kbar, corresponding to a depth of 12 ± 1 km.
The volume of the mineralizing porphyry dikes and stocks at the emplacement level is far too small to have provided all the fluids and metals required to form the observed ore deposits. Therefore, the majority of the ore-forming fluids must have originated from the magmas that crystallized at 12 ± 1 km depth. The ore deposits, conversely, formed at ~5-km paleodepth. This implies that most of the mineralizing fluids traveled an average vertical distance of ~7 km from their magmatic source to the eventual site of ore precipitation. The relatively unaltered nature and low veining degree of deeper parts of mineralized porphyry dikes and stocks suggest that the fluid transport through these intrusive bodies occurred mostly at near-solidus conditions by means of fluid percolation along grain boundaries.
In summary, our results suggest that (1) a large, upper crustal pluton exists ~7 km beneath the Santa Rita and Hanover-Fierro deposits; (2) abundant phenocryst crystallization occurred at this depth level; and (3) this pluton was the main source for the exsolution of ore-forming fluids. However, the investigated rocks have elevated whole-rock Sr/Y ratios, indicating magma fractionation at deep crustal levels. As a result, our preferred model is a combination of the two end-member models introduced above, with most magma fractionation having occurred in the deep crust and with residual, intermediate to felsic melts having ascended and accumulated at 11 to 14 km paleodepth, where they continued to crystallize with comparatively little crystal-liquid separation, before some of these magmas ascended further to shallow levels and quenched to porphyries.
","language":"English","publisher":"Society of Economic Geology","doi":"10.5382/econgeo.5197","usgsCitation":"Audétat, A., Chang, J., and Gaynor, S.P., 2025, Depth of magma crystallization and fluid exsolution beneath the porphyry-skarn Cu deposits at Santa Rita and Hanover-Fierro, New Mexico, USA: Economic Geology, v. 120, no. 7, p. 1679-1699, https://doi.org/10.5382/econgeo.5197.","productDescription":"21 p.","startPage":"1679","endPage":"1699","ipdsId":"IP-174016","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":496982,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Hanover-Fierro deposit, Santa Rita mine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108,\n 32.875\n ],\n [\n -108.1667,\n 32.875\n ],\n [\n -108.1667,\n 32.75\n ],\n [\n -108,\n 32.75\n ],\n [\n -108,\n 32.875\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"120","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Audétat, Andreas","contributorId":363151,"corporation":false,"usgs":false,"family":"Audétat","given":"Andreas","affiliations":[{"id":83309,"text":"Bavarian Geoinstitute, University of Bayreuth","active":true,"usgs":false}],"preferred":false,"id":951173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chang, Jia","contributorId":363152,"corporation":false,"usgs":false,"family":"Chang","given":"Jia","affiliations":[{"id":83309,"text":"Bavarian Geoinstitute, University of Bayreuth","active":true,"usgs":false}],"preferred":false,"id":951174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gaynor, Sean Patrick 0000-0002-8353-511X","orcid":"https://orcid.org/0000-0002-8353-511X","contributorId":346264,"corporation":false,"usgs":true,"family":"Gaynor","given":"Sean","email":"","middleInitial":"Patrick","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":951175,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272618,"text":"sir20255099 - 2025 - Temporal changes in nutrient concentrations in the Lower Grand River and selected drainage basins, Missouri and Iowa, during the Mississippi River Basin Healthy Watersheds Initiative (2010–23)","interactions":[],"lastModifiedDate":"2026-02-03T16:39:07.258008","indexId":"sir20255099","displayToPublicDate":"2025-11-26T08:25:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5099","displayTitle":"Temporal Changes in Nutrient Concentrations in the Lower Grand River and Selected Drainage Basins, Missouri and Iowa, During the Mississippi River Basin Healthy Watersheds Initiative (2010–23)","title":"Temporal changes in nutrient concentrations in the Lower Grand River and selected drainage basins, Missouri and Iowa, during the Mississippi River Basin Healthy Watersheds Initiative (2010–23)","docAbstract":"This report describes a cooperative study by the U.S. Geological Survey and Missouri Department of Natural Resources that evaluated temporal changes in total nitrogen (TN) and total phosphorus (TP) concentrations in the Lower Grand River hydrologic unit. The study focused on trends since 2010, when the basin was designated as a priority drainage basin of the Mississippi River Basin Healthy Watersheds Initiative (MRBI). At three local drainage basins within the Lower Grand hydrological unit (MRBI sites), stream nutrient trends were evaluated using flow-adjusted (FA) TN and TP concentrations for water years 2011 through 2023. FATN concentration trends were not statistically significant for any MRBI site. One site (site 2) showed a statistically significant increasing trend in FATP concentration, indicating a possible increase in phosphorus sources in parts of the basin. Overall, streamflow variability appeared to be the dominant factor affecting nutrient concentrations at MRBI sites. At five regional drainage basins, including the Grand River and nearby rivers with data from 1994 through 2023 (long-term sites), annual flow-normalized (FN) TN and TP concentrations were evaluated for trends before (water years 2000–10) and during (water years 2010–23) the MRBI. For water years 2010 through 2023, annual FNTN and FNTP concentrations decreased in the Grand River, as well as in the Nodaway and Chariton Rivers, which were not targeted by the MRBI. The Grand River (site 9) reversed from increasing to decreasing FNTP concentrations after 2010, with a 26-percent reduction. Annual FNTN and FNTP concentrations also decreased at the Missouri River sites. While nutrient reductions in the Grand River may reflect the effects of implemented conservation practices, similar trends in nearby, nontargeted rivers and the absence of strong decreasing trends at MRBI sites suggest that broader regional factors, instead of or in addition to MRBI efforts, may have contributed to nutrient reductions in the Grand River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255099","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Kamrath, B.J.W., Lauderback, C.N., and Murphy, J.C., 2025, Temporal changes in nutrient concentrations in the Lower Grand River and selected drainage basins, Missouri and Iowa, during the Mississippi River Basin Healthy Watersheds Initiative (2010–23): U.S. Geological Survey Scientific Investigations Report 2025–5099, 19 p., https://doi.org/10.3133/sir20255099.","productDescription":"Report: vii, 19 p.; 5 Linked Tables; Data Release; Dataset","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-167198","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497801,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118990.htm"},{"id":496854,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":496853,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13FQ2YN","text":"USGS data release","linkHelpText":"Archive of the load estimation models used in the analyses of temporal changes in nutrient concentrations in the Lower Grand River and selected drainage basins, Missouri and Iowa (2010–23)"},{"id":496855,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255099/full"},{"id":496848,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5099/coverthb.jpg"},{"id":496852,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2025/5099/downloads/","text":"Tables 1.1 to 1.5","linkFileType":{"id":3,"text":"xlsx"}},{"id":496851,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5099/images/"},{"id":496849,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5099/sir20255099.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5099"},{"id":496850,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5099/sir20255099.XML"}],"country":"United States","state":"Iowa, Missouri","otherGeospatial":"Lower Grand River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.5,\n 41.5\n ],\n [\n -95.5,\n 38.5\n ],\n [\n -91.5,\n 38.5\n ],\n [\n -91.5,\n 41.5\n ],\n [\n -95.5,\n 41.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, estimated total nitrogen and total phosphorus concentrations at three local and five regional monitoring sites in Missouri. Temporal changes in total nitrogen and total phosphorus were quantified to evaluate whether instream nutrient concentrations have changed at local or regional scales. At the local scale sites, total phosphorus concentrations substantially increased at one site, which indicated a possible increase in phosphorus sources in the Lower Grand River hydrologic unit, while total nitrogen concentrations did not change substantially. At the regional site, annual total nitrogen and total phosphorus concentrations generally decreased. The regional decline in stream nutrients paired with the lack of nutrient reduction at the local sites indicated that nutrient reductions in the Grand River may have been driven by regional changes in nutrient export, instead of or in addition to conservation practices implemented as part of the Mississippi River Basin Healthy Watersheds Initiative.
","publicationDate":"2025-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Kamrath, Brock J.W. 0000-0001-7118-0537","orcid":"https://orcid.org/0000-0001-7118-0537","contributorId":347859,"corporation":false,"usgs":true,"family":"Kamrath","given":"Brock","middleInitial":"J.W.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lauderback, Courtney N. 0000-0002-6975-0331","orcid":"https://orcid.org/0000-0002-6975-0331","contributorId":363041,"corporation":false,"usgs":true,"family":"Lauderback","given":"Courtney","middleInitial":"N.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":4281,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950959,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272103,"text":"sir20255062 - 2025 - An evaluation of the effects of different deicing salt application rates on three watersheds in Essex County, New York","interactions":[],"lastModifiedDate":"2026-02-03T16:38:12.480343","indexId":"sir20255062","displayToPublicDate":"2025-11-25T15:50:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5062","displayTitle":"An Evaluation of the Effects of Different Deicing Salt Application Rates on Three Watersheds in Essex County, New York","title":"An evaluation of the effects of different deicing salt application rates on three watersheds in Essex County, New York","docAbstract":"The U.S. Geological Survey, in cooperation with the New York State Department of Transportation, evaluated the effects of different deicing salt application rates on surface water, groundwater, and highway runoff quality near State highways in northern New York. Three reaches of State highways were tested with different deicing treatments between October 2019 and November 2022: a salt-sand mixture (Treatment A), a salt mixture applied at a lower rate (Treatment B), and a control mixture consistent with typical deicing salt amounts and application rates. Data on pavement conditions and the quality of surface water, highway runoff, and groundwater were collected. Surface electromagnetic data were also collected. Surface-water and groundwater quality downgradient from the State highways were compared with water quality at upgradient locations. The percentage of snow or ice coverage was used to evaluate the effectiveness of the salt applications.
This report provides an overview of the transport of deicing salt. The Treatment B watershed had deicing mixture applied more frequently than other highway reaches, which caused it to have the highest annual total chloride application. Despite differences in chloride application, flow-weighted mean chloride concentrations in highway runoff were comparable across treatments. Chloride concentrations were elevated in surface water and groundwater downgradient from highways relative to chloride concentrations upgradient from highways. A chloride mass balance, calculated for one treatment watershed, indicated that groundwater affected by legacy deicing practices may be contributing additional chloride to surface water. Spatial patterns from electromagnetic surveys show a shallow saline plume alongside the highway in that area.
Differences in winter severity and pavement-surface conditions drove deicing salt applications in the treatment areas. This study found that several factors affect chloride loads in the watersheds, including variable winter conditions, adaptive snow and ice management, legacy management practices, and area-specific aquifer and groundwater conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255062","collaboration":"Prepared in cooperation with the New York State Department of Transportation","usgsCitation":"Gutchess, K., Scavotto, N., Dondero, A., Woda, J., Terry, N., Smith, K., and Williams, J., 2025, An evaluation of the effects of different deicing salt application rates on three watersheds in Essex County, New York: U.S. Geological Survey Scientific Investigations Report 2025–5062, 31 p., https://doi.org/10.3133/sir20255062.","productDescription":"Report: viii, 31 p.; 2 Data Releases","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-160931","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":497798,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118989.htm"},{"id":496533,"rank":7,"type":{"id":30,"text":"Data 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New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 1280–8349
Here, we present a first assessment of the US Department of Agriculture’s (USDA) “Grass-Cast Southwest,” which is a forecasting tool for rangeland aboveground net primary productivity (ANPP) for the southwest region of the United States. Our results show that ANPP forecasts in early April were relatively close to the observation-based ANPP estimates in late May for all years evaluated (R = 0.6–0.9). The relatively high predictability of spring rangeland productivity in this region is likely because it is strongly driven by antecedent winter/early spring precipitation. Conversely, the first summer forecasts produced in June did not consistently predict the final observation-based ANPP estimates in late August (R = −0.5–0.7), likely because summer rangeland productivity in this region is highly dependent on variable, less predictable precipitation from the North American Monsoon (NAM). Antecedent El Niño Southern Oscillation (ENSO) indices could be used to improve Grass-Cast Southwest performance in both the spring and summer. The ENSOJFM (January–March) index was significantly positively correlated with rangeland productivity during the spring season, whereas ENSOMAM (March–May) was significantly negatively correlated with rangeland productivity during the summer season.
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Introgression and genetic variation at the trailing edge of Quercus bicolor","interactions":[],"lastModifiedDate":"2026-01-05T17:01:51.876178","indexId":"70272654","displayToPublicDate":"2025-11-25T09:50:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evaluating the central–marginal hypothesis: Introgression and genetic variation at the trailing edge of Quercus bicolor","title":"Evaluating the central–marginal hypothesis: Introgression and genetic variation at the trailing edge of Quercus bicolor","docAbstract":"The central–marginal hypothesis (CMH) predicts reduced genetic diversity and increased differentiation in range-edge populations due to ecological marginality and limited gene flow. Deviations from this pattern, however, can result from historical demographic processes, variation in reproductive strategies or interspecific hybridization. The genus Quercus, known for hybridization and long-distance pollination, offers an excellent model to examine the spatial patterns of genetic diversity, structure and introgression across species distributions. Here, we investigate these dynamics in Quercus bicolor Willd., a widespread eastern North American oak. Using RADseq, we genotyped 142 individuals from 12 sites at the fragmented trailing range edge and nine sites from the range core. To detect introgression, we incorporated reference data from six sympatric white oak species. We reveal extensive introgression, particularly from Q. lyrata Walt., in nearly all southern edge populations, but none in core populations despite sympatry with closely related congeners. Southern populations also showed increased genetic structure and differentiation, but not reduced diversity or increased inbreeding, even when only examining non-admixed individuals. Regression analyses reveal relationships between introgressed ancestry and heterozygosity, inbreeding and differentiation, indicating that introgression may buffer range-edge populations against genetic erosion by introducing novel alleles. Hindcast, current and forecast ecological niche models demonstrate temporally changing degrees of overlap between the geographic range of Q. lyrata and Q. bicolor and suggest higher hybridization potential in the future. These findings offer mixed support for the CMH while underscoring the evolutionary relevance of introgression in shaping genetic landscapes at range margins with significant implications for conservation.
","language":"English","publisher":"Wiley","doi":"10.1111/mec.70185","usgsCitation":"Jesse B. Parker, Sean Hoban, Thompson, L., and Scott E. Schlarbaum, 2025, Evaluating the central–marginal hypothesis: Introgression and genetic variation at the trailing edge of Quercus bicolor: Molecular Ecology, v. 34, no. 24, e70185, 19 p., https://doi.org/10.1111/mec.70185.","productDescription":"e70185, 19 p.","ipdsId":"IP-182841","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":497082,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/mec.70185","text":"Publisher Index Page"},{"id":496986,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.7397874284601,\n 47.69010833548356\n ],\n [\n -96.50515645608941,\n 38.374728664216455\n ],\n [\n -94.46111669832068,\n 35.024323679813264\n ],\n [\n -75.54658793458438,\n 34.796796242513224\n ],\n [\n -73.9846649987043,\n 39.20135867583498\n ],\n [\n -69.38877471060589,\n 41.55065832321056\n ],\n [\n -66.75532196682867,\n 44.51664342888958\n ],\n [\n -66.71186067192609,\n 47.40639899204692\n ],\n [\n -76.96565391885454,\n 44.77224521173778\n ],\n [\n -85.96379061474377,\n 47.170718633297994\n ],\n [\n -96.7397874284601,\n 47.69010833548356\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"34","issue":"24","noUsgsAuthors":false,"publicationDate":"2025-11-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Jesse B. Parker","contributorId":363175,"corporation":false,"usgs":false,"family":"Jesse B. Parker","affiliations":[{"id":63836,"text":"University of Tennessee, Knoxville","active":true,"usgs":false}],"preferred":false,"id":951194,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sean Hoban","contributorId":363177,"corporation":false,"usgs":false,"family":"Sean Hoban","affiliations":[{"id":86637,"text":"Morton Arboretum","active":true,"usgs":false}],"preferred":false,"id":951195,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Laura 0000-0002-7884-6001","orcid":"https://orcid.org/0000-0002-7884-6001","contributorId":207364,"corporation":false,"usgs":true,"family":"Thompson","given":"Laura","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":951196,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scott E. Schlarbaum","contributorId":363179,"corporation":false,"usgs":false,"family":"Scott E. Schlarbaum","affiliations":[{"id":63836,"text":"University of Tennessee, Knoxville","active":true,"usgs":false}],"preferred":false,"id":951197,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273031,"text":"70273031 - 2025 - Spatial occupancy patterns of the endangered northern long‐eared bat in New England","interactions":[],"lastModifiedDate":"2025-12-12T16:38:07.189122","indexId":"70273031","displayToPublicDate":"2025-11-25T09:30:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Spatial occupancy patterns of the endangered northern long‐eared bat in New England","docAbstract":"Aim
White-nose syndrome has caused severe declines in eastern North American cave bats, leading to the federal listing of the northern long-eared bat (Myotis septentrionalis) as endangered in the United States and Canada. This has heightened the importance of long-term monitoring to inform species status assessments. We employed a combination of long-term repeated and single-season acoustic survey data to assess the regional presence, spatial distribution, occupancy, and detection probability of northern long-eared bats.
Location
New England, United States.
Methods
We analysed acoustic data from 2357 detector sites, aggregated by year, using Bayesian single-species occupancy models. We investigated the influence of habitat characteristics, climatic variables, and year (2015–2022) on occupancy and the effects of weather conditions and survey month (May to August) on detection probability. Spatial random effects were included to address residual spatial autocorrelation, with a 1-km resolution chosen based on significant positive autocorrelation observed in a non-spatial model.
Results
Occupancy was highest on steep, forested hillsides with minimal anthropogenic development, higher in warmer regions, particularly along coastlines and on offshore islands, and declined across survey years. Including a 1-km spatial random effect reduced residual autocorrelation and suggests northern long-eared bats utilise resources at small to medium landscape scales. Detection probability was highest earlier in the maternity season, but declined when monthly precipitation or temperature exceeded average conditions.
Conclusions
Conservation efforts that focus on steep, forested hillsides in warmer regions with low anthropogenic development could be beneficial. Our analysis supports the use of spatial random effects at a 1-km2 scale, highlighting the importance of survey designs that capture ecological variation at species-specific resolutions. Additionally, early-season acoustic surveys conducted during favourable weather conditions may improve monitoring effectiveness. Acoustic sampling and spatial occupancy modelling offer powerful tools for monitoring remnant populations of northern long-eared bats and guiding conservation practices.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.70122","usgsCitation":"De La Cruz, J.L., Deeley, S.M., Hunter, E.A., and Ford, W., 2025, Spatial occupancy patterns of the endangered northern long‐eared bat in New England: Diversity and Distributions, v. 31, no. 11, e70122, 14 p., https://doi.org/10.1111/ddi.70122.","productDescription":"e70122, 14 p.","ipdsId":"IP-173151","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497707,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.70122","text":"Publisher Index Page"},{"id":497482,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont","otherGeospatial":"New England","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -68.0467630667936,\n 47.51205906310295\n ],\n [\n -69.45031396213979,\n 47.35719130879998\n ],\n [\n -70.61580060874599,\n 45.750869986415296\n ],\n [\n -71.56018342332794,\n 45.25079633685677\n ],\n [\n -73.36997254667905,\n 44.93837726441758\n ],\n [\n -73.64279304233246,\n 41.439981251049005\n ],\n [\n -69.6894535963497,\n 41.37398252890503\n ],\n [\n -67.03254188469603,\n 44.57837534082219\n ],\n [\n -68.0467630667936,\n 47.51205906310295\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"31","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-11-25","publicationStatus":"PW","contributors":{"authors":[{"text":"De La Cruz, Jesse L","contributorId":363941,"corporation":false,"usgs":false,"family":"De La Cruz","given":"Jesse","middleInitial":"L","affiliations":[{"id":81893,"text":"Virginia Polytechnic and State University","active":true,"usgs":false}],"preferred":false,"id":952119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deeley, Sabrina M.","contributorId":363943,"corporation":false,"usgs":false,"family":"Deeley","given":"Sabrina","middleInitial":"M.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":952120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":952121,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":952122,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272800,"text":"70272800 - 2025 - Detection of viral, bacterial, and protozoan pathogens and microbial source tracking markers in paired large- and small-volume water samples","interactions":[],"lastModifiedDate":"2025-12-09T15:04:46.203031","indexId":"70272800","displayToPublicDate":"2025-11-25T07:58:59","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19118,"text":"ES&T Water","active":true,"publicationSubtype":{"id":10}},"title":"Detection of viral, bacterial, and protozoan pathogens and microbial source tracking markers in paired large- and small-volume water samples","docAbstract":"When sampling for waterborne microbes, researchers may need to diverge from recommended sample volumes due to logistical constraints, novel targets, or challenging matrices, with little guidance about the potential impact on results. In field studies, we measured bacteria, viruses, and protozoa (15 quantitative polymerase chain reaction assays) in paired large- and small-volume samples to evaluate method performance and relevant factors. Concordance between methods was low. Large-volume ultrafiltration yielded more detections than small-volume sampling, especially for pathogens in groundwater. Greater microbial concentrations were associated with more frequent detections in small-volume samples and greater concordance between paired samples. Large-volume samples appeared to be more susceptible to diminished sensitivity from complex sample matrices. In laboratory studies, recovery of microbes was poorer for large- than small-volume methods, although large-volume methods more reliably detected low-concentration targets. Large-volume samples were less stable than small-volume samples during storage. Overall, large-volume sampling was superior for detecting pathogens but may underestimate concentrations; small-volume sampling was more prone to false negatives but was adequate when concentrations were relatively high, like we observed for microbial source tracking in surface waters.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acsestwater.5c00639","usgsCitation":"Heffron, J., Stokdyk, J.P., Firnstahl, A.D., Cook, R.M., Hruby, C.E., and Borchardt, M.A., 2025, Detection of viral, bacterial, and protozoan pathogens and microbial source tracking markers in paired large- and small-volume water samples: ES&T Water, 12 p., https://doi.org/10.1021/acsestwater.5c00639.","productDescription":"12 p.","ipdsId":"IP-178626","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497409,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acsestwater.5c00639","text":"Publisher Index Page"},{"id":497277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"southwest Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.16854398405542,\n 43.724862035862486\n ],\n [\n -91.16854398405542,\n 42.528189766140656\n ],\n [\n -89.21470862754418,\n 42.528189766140656\n ],\n [\n -89.21470862754418,\n 43.724862035862486\n ],\n [\n -91.16854398405542,\n 43.724862035862486\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-11-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Heffron, Joe","contributorId":339799,"corporation":false,"usgs":false,"family":"Heffron","given":"Joe","email":"","affiliations":[],"preferred":false,"id":951808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stokdyk, Joel P. 0000-0003-2887-6277 jstokdyk@usgs.gov","orcid":"https://orcid.org/0000-0003-2887-6277","contributorId":193848,"corporation":false,"usgs":true,"family":"Stokdyk","given":"Joel","email":"jstokdyk@usgs.gov","middleInitial":"P.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Firnstahl, Aaron D. 0000-0003-2686-7596 afirnstahl@usgs.gov","orcid":"https://orcid.org/0000-0003-2686-7596","contributorId":168296,"corporation":false,"usgs":true,"family":"Firnstahl","given":"Aaron","email":"afirnstahl@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951810,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, Rachel M.","contributorId":300167,"corporation":false,"usgs":false,"family":"Cook","given":"Rachel","middleInitial":"M.","affiliations":[],"preferred":false,"id":951811,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hruby, Claire E.","contributorId":192690,"corporation":false,"usgs":false,"family":"Hruby","given":"Claire","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":951812,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Borchardt, Mark A. 0000-0002-6471-2627","orcid":"https://orcid.org/0000-0002-6471-2627","contributorId":151033,"corporation":false,"usgs":false,"family":"Borchardt","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":951813,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272503,"text":"sir20255088 - 2025 - Estimating flood discharges at selected annual exceedance probabilities for unregulated, rural streams in Vermont, 2023","interactions":[],"lastModifiedDate":"2026-04-27T14:54:35.900219","indexId":"sir20255088","displayToPublicDate":"2025-11-24T13:01:21","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5088","displayTitle":"Estimating Flood Discharges at Selected Annual Exceedance Probabilities for Unregulated, Rural Streams in Vermont, 2023","title":"Estimating flood discharges at selected annual exceedance probabilities for unregulated, rural streams in Vermont, 2023","docAbstract":"This report provides estimates of flood discharge at selected annual exceedance probabilities (AEPs) for streamgages in and adjacent to Vermont and equations for estimating flood discharges at AEPs of 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent (recurrence intervals of 2-, 5-, 10-, 25-, 50-, 100-, and 500-years, respectively) for ungaged, unregulated, rural streams in Vermont with drainage areas between 0.47 and 851 square miles. The equations were developed using generalized least-squares regression and flood-frequency and drainage-basin characteristics from 156 streamgages. Flood-frequency analyses were completed using data through the 2023 water year. The drainage-basin characteristics used as explanatory variables in the regression equations are drainage area, percentage of wetland area, and basin-wide mean of the average annual precipitation. The average standard errors of prediction used to estimate flood discharges at the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEP with these equations are 34.9, 37.1, 38.2, 41.6, 43.8, 46.0, 49.1, and 53.2 percent, respectively.
Flood discharges at selected AEPs for streamgages were computed using the Expected Moments Algorithm. Techniques used to adjust an AEP discharge computed from a streamgage record with results from the regression equations and to estimate flood discharge at a selected AEP for an ungaged site upstream or downstream from a streamgage using a drainage-area adjustment are both described. The final regression equations and the flood-discharge frequency data used in this study will be available in StreamStats. StreamStats is an internet-based application that provides automated regression-equation solutions for user-selected sites on streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255088","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Olson, S.A., 2025, Estimating flood discharges at selected annual exceedance probabilities for unregulated, rural \nstreams in Vermont, 2023: U.S. Geological Survey Scientific Investigations Report 2025–5088, 22 p., https://doi.org/10.3133/sir20255088.","productDescription":"Report: vii, 22 p.; Data Release; Appendix","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-175471","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":496788,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5088/images"},{"id":496787,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5088/sir20255088.XML","description":"SIR 2025-5088 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532