Ratings are used for several reasons in water-resources investigations. The simplest rating relates discharge to the stage of a river (the stage-discharge relation). From a pure hydrodynamics perspective, all rivers and streams have some form of hysteresis in the relation between stage and discharge because flow becomes unsteady as a flood wave passes. The stage-discharge relation is unable to represent hysteresis. However, a dynamic rating method can capture hysteresis, which is driven by the variable energy slope of a flood wave.
A dynamic rating method called DYNPOUND, which accommodates compact and compound channel geometry, was developed by simplifying the one-dimensional Saint-Venant equations. The DYNPOUND method was developed in the Python programming language and computes discharge from stage and stage from discharge. Stage and discharge time series computed with this dynamic rating method were compared to the U.S. Geological Survey (USGS) published stage and discharge time series. The results from the DYNPOUND method were also compared to in-person field measurements of stage and discharge made at 10 USGS streamgages.
DYNPOUND was calibrated for 10 USGS streamgages using published discharge time-series data computed with a simple rating method. The calibration objective was to minimize the mean squared logarithmic error (MSLE) of the DYNPOUND-computed discharge with respect to the discharge time series computed by a simple rating method. For each site, the calibration process also included comparing all field measurements within a selected water year to the corresponding DYNPOUND-computed discharge data points. The MSLE of the DYNPOUND-computed discharge time series for the 10 sites ranged from 8.51×10−4 to 1.36×10−1. For each site, an event-based period was selected to compare the discharge time series computed with the dynamic rating method to discharge field measurements made at the streamgages; the range of MSLE for the 10 DYNPOUND-computed discharge sites was from 4.79×10−4 to 2.30×10−2.
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U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
The umbrella species concept is often used as a tool to guide management decisions and focus efforts towards one focal species whose habitat needs overlap that of other species. We assessed this concept in the context of an agriculturally dominant landscape using one of the most well-studied avian species in North America as a target for conservation efforts: Northern Bobwhite (Colinus virginianus). This species is often viewed as an umbrella species for grassland and shrubland bird conservation throughout its native range due to its complex, year-round habitat requirements. We assessed the influence of Northern Bobwhite habitat management on six songbird species of conservation concern in Iowa by evaluating similarities and differences in habitat associations between each species. Our objectives were to (1) assess which vegetation characteristics were most strongly associated with Northern Bobwhite occupancy and (2) evaluate whether those characteristics were also associated with abundance of the focal songbird species. We used occupancy and N-mixture models to assess relationships between vegetation characteristics and Northern Bobwhite occupancy and songbird abundance, respectively. We found that the vegetation characteristics most strongly associated with Northern Bobwhite occupancy probability were the amounts of closed canopy forest, early successional woody vegetation, non-vegetated areas, and percent cover of bare ground. We found that for some of these covariates, including the amounts of forest and non-vegetated area, the effect on focal songbird species abundance aligned with Northern Bobwhite occupancy. For others, including the amount of early successional woody vegetation, the effects differed. This assessment of overlap and variability in habitat associations suggests that Northern Bobwhite-targeted management can provide benefits to other grassland and shrubland birds, but may also come with some trade-offs. This work adds to existing literature, further highlighting the nuances of the umbrella species concept in that land management benefits from the assessment of trade-offs and inclusion of local community dynamics.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2025.113310","usgsCitation":"Ford, J., Tucker, A.M., Janke, A., Harms, T., and Wilson, R., 2025, Effects of northern bobwhite habitat management on avian species of conservation concern: Ecological Indicators, v. 172, 113310, 11 p., https://doi.org/10.1016/j.ecolind.2025.113310.","productDescription":"113310, 11 p.","ipdsId":"IP-170818","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493804,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2025.113310","text":"Publisher Index Page"},{"id":493722,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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H.","contributorId":342498,"corporation":false,"usgs":false,"family":"Ford","given":"Johanna M. H.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":945117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, Anna Maureen 0000-0002-1473-2048 amtucker@usgs.gov","orcid":"https://orcid.org/0000-0002-1473-2048","contributorId":257906,"corporation":false,"usgs":true,"family":"Tucker","given":"Anna","email":"amtucker@usgs.gov","middleInitial":"Maureen","affiliations":[],"preferred":true,"id":945118,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Janke, Adam K.","contributorId":359281,"corporation":false,"usgs":false,"family":"Janke","given":"Adam K.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":945119,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harms, Tyler M.","contributorId":343314,"corporation":false,"usgs":false,"family":"Harms","given":"Tyler M.","affiliations":[{"id":24495,"text":"Iowa Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":945120,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Riggs O.","contributorId":359283,"corporation":false,"usgs":false,"family":"Wilson","given":"Riggs O.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":945121,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70264293,"text":"sir20255021 - 2025 - World minerals outlook—Cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium through 2029","interactions":[],"lastModifiedDate":"2025-07-23T16:44:58.484068","indexId":"sir20255021","displayToPublicDate":"2025-03-11T10:50:00","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":"2025-5021","displayTitle":"World Minerals Outlook—Cobalt, Gallium, Helium, Lithium, Magnesium, Palladium, Platinum, and Titanium Through 2029","title":"World minerals outlook—Cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium through 2029","docAbstract":"Given the rapid expansion in the demand for mineral commodities that underpin worldwide economic growth and technological advancement, information regarding expected country-level mine production and production capacity is becoming increasingly important to industry stakeholders, end users, and policymakers. Production capacity can limit future supply, depending on how rapidly that capacity is able to expand. Current capacity can be evaluated on the basis of past production. Decreases to future capacity can be taken into account from announcements of planned shutdowns of mines or processing facilities, which are frequently publicized well in advance of such closures. Likewise, capacity expansions, which usually involve multiple stages—such as permitting, financing, and construction (all of which take time)—can also be estimated. As such, it is possible to evaluate midterm future capacity based on estimates of today’s capacities along with consideration of future investment plans. This World Minerals Outlook provides estimated capacities for cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium for 2025 through 2029.
The results of this analysis indicate that two mineral commodities important to the manufacture of lithium-ion batteries—cobalt and lithium—are expected to have large capacity growth in the next few years, likely owing to expectations for increased demand for these batteries. For gallium, helium, palladium, and platinum, capacity is expected to remain stable or exhibit moderate growth. Still, these expected capacity levels are higher than current production, allowing for future production growth. The production capacity outlook is opaque for magnesium and titanium metal, which have a significant fraction of current production in nonmarket economies, such as China and Russia. Ultimately, though, where free market conditions prevail, full utilization of capacity potential for those commodities is likely to depend on supply deficits and prices that are above production costs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255021","usgsCitation":"Alonso, E., Brioche, A.S., Schulte, R.F., Trimmer, L.M., Kim, J.-E., Gulley, A.L., and Pineault, D.G., 2025, World minerals outlook—Cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium through 2029 (ver. 1.1, March 14, 2025): U.S. Geological Survey Scientific Investigations Report 2025–5021, 19 p., https://doi.org/10.3133/sir20255021.","productDescription":"Report: vi, 19 p.; Data Release","numberOfPages":"19","onlineOnly":"Y","ipdsId":"IP-173545","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":483354,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2025/5021/versionHist.txt","size":"4.64 KB","linkFileType":{"id":2,"text":"txt"}},{"id":483159,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1HTTCWN","text":"USGS data release","linkHelpText":"World minerals outlook to 2029—Cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium data"},{"id":483408,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5021//images/"},{"id":483406,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255021/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5021 HTML"},{"id":492776,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118478.htm","linkFileType":{"id":5,"text":"html"}},{"id":483407,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5021/sir20255021.XML","description":"SIR 2025-5021 XML"},{"id":483145,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5021/sir20255021.pdf","text":"Report","size":"2.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5021 PDF"},{"id":483144,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5021/coverthb2.jpg"}],"edition":"Version 1.0: March 11, 2025; Version 1.1: March 14, 2025","contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
","tableOfContents":"Understanding mine production and potential capacity growth can help inform the growing need for the minerals that support economic growth, technological change, and national security for businesses and policy makers. How much a mine can produce affects future supply, especially as capacities can change over time. This report estimates production capacities for cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium through 2029. The results of the analysis suggest that cobalt and lithium, which are key for lithium-ion batteries, are likely to see significant increases in production capacity owing to rising demand, whereas gallium and platinum are expected to see stable or moderate growth, exceeding current production levels. However, the future for magnesium and titanium is less clear because much of their production comes from countries with nonmarket economies, like China and Russia. In free markets, using full production capacity is likely to depend on supply shortages and prices being above production costs.
","publicationDate":"2025-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Alonso, Elisa 0000-0002-0090-8284","orcid":"https://orcid.org/0000-0002-0090-8284","contributorId":223015,"corporation":false,"usgs":true,"family":"Alonso","given":"Elisa","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":930300,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brioche, Amanda Sarah 0000-0002-9650-2456","orcid":"https://orcid.org/0000-0002-9650-2456","contributorId":332784,"corporation":false,"usgs":true,"family":"Brioche","given":"Amanda Sarah","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":930301,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schulte, Ruth 0000-0003-4724-5905","orcid":"https://orcid.org/0000-0003-4724-5905","contributorId":201973,"corporation":false,"usgs":true,"family":"Schulte","given":"Ruth","email":"","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":930302,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Trimmer, Loyd M. III 0000-0003-4121-7874 ltrimmer@usgs.gov","orcid":"https://orcid.org/0000-0003-4121-7874","contributorId":194120,"corporation":false,"usgs":true,"family":"Trimmer","given":"Loyd","suffix":"III","email":"ltrimmer@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":930303,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kim, Ji-Eun 0000-0002-7668-5072","orcid":"https://orcid.org/0000-0002-7668-5072","contributorId":331665,"corporation":false,"usgs":true,"family":"Kim","given":"Ji-Eun","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":930304,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gulley, Andrew L. 0000-0003-4717-2080","orcid":"https://orcid.org/0000-0003-4717-2080","contributorId":203953,"corporation":false,"usgs":true,"family":"Gulley","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":930305,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pineault, David 0009-0001-6801-4711","orcid":"https://orcid.org/0009-0001-6801-4711","contributorId":352217,"corporation":false,"usgs":true,"family":"Pineault","given":"David","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":930306,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70270419,"text":"70270419 - 2025 - Evidence for size‐based predation risk during Atlantic salmon (Salmo salar) smolt migration.","interactions":[],"lastModifiedDate":"2025-08-19T14:52:48.36751","indexId":"70270419","displayToPublicDate":"2025-03-11T09:48:40","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evidence for size-based predation risk during Atlantic salmon (Salmo salar) smolt migration","title":"Evidence for size‐based predation risk during Atlantic salmon (Salmo salar) smolt migration.","docAbstract":"Hatchery supplementation is frequently employed during the conservation and recovery of imperilled salmon populations. At the smolt stage, hatchery rearing practices often produce individuals that are larger than wild conspecifics. Under this ‘bigger is better’ strategy, it is assumed that larger fish are less susceptible to predation during migration. We tested this hypothesis on hatchery-reared Atlantic salmon (Salmo salar) smolts with fork lengths representative of those of natural and hatchery origins, allowing us to isolate the influence of size from rearing history. From May to June 2023 we characterized predation risk for acoustic-tagged (n = 50) and tethered (n = 192) smolts of various sizes through a mostly free-flowing section of the Penobscot River, Maine, USA. Across both methods, more than 50% of smolts were predated, with the majority of predation events being attributed to smallmouth bass (Micropterus dolomieu). Tethered smolts of all sizes experienced similar predation risk. In the acoustic telemetry component of this study, smaller, wild-sized smolts incurred greater overall mortality relative to standard hatchery sizes (95% vs. 75%), the majority of which occurred within 3 km of the release site. Collectively, these results allude to a strong predation influence imposed by smallmouth bass on smolts in freshwater sections of the Penobscot River and small-bodied migrants may incur greater predation risk, particularly near stocking sites.
","language":"English","publisher":"Wiley","doi":"10.1111/jfb.70011","usgsCitation":"Mensinger, M., Mortelliti, A., and Zydlewski, J.D., 2025, Evidence for size‐based predation risk during Atlantic salmon (Salmo salar) smolt migration.: Journal of Fish Biology, https://doi.org/10.1111/jfb.70011.","ipdsId":"IP-167997","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":496392,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jfb.70011","text":"Publisher Index Page"},{"id":494310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Mensinger, Matthew A.","contributorId":287641,"corporation":false,"usgs":false,"family":"Mensinger","given":"Matthew A.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":946384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mortelliti, Alessio","contributorId":342757,"corporation":false,"usgs":false,"family":"Mortelliti","given":"Alessio","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":946385,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":946386,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70264584,"text":"70264584 - 2025 - Deposits of volcanic wet flows","interactions":[],"lastModifiedDate":"2025-03-17T14:12:23.109691","indexId":"70264584","displayToPublicDate":"2025-03-11T09:10:49","publicationYear":"2025","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":15,"text":"Monograph"},"title":"Deposits of volcanic wet flows","docAbstract":"No abstract available.
","language":"English","publisher":"Springer","doi":"10.1007/978-3-031-66574-5","usgsCitation":"Pierson, T., Siebert, L., and Scott, K., 2025, Deposits of volcanic wet flows, 486 p., https://doi.org/10.1007/978-3-031-66574-5.","productDescription":"486 p.","ipdsId":"IP-132474","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":498286,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/978-3-031-66574-5","text":"Publisher Index Page"},{"id":483446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pierson, T.C. 0000-0001-9002-4273","orcid":"https://orcid.org/0000-0001-9002-4273","contributorId":41855,"corporation":false,"usgs":true,"family":"Pierson","given":"T.C.","affiliations":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":930818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siebert, Lee","contributorId":20475,"corporation":false,"usgs":false,"family":"Siebert","given":"Lee","affiliations":[{"id":12865,"text":"Smithsonian Institute","active":true,"usgs":false}],"preferred":false,"id":930819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scott, Kevin M.","contributorId":352333,"corporation":false,"usgs":false,"family":"Scott","given":"Kevin M.","affiliations":[{"id":84172,"text":"USGS CVO, emeritus","active":true,"usgs":false}],"preferred":false,"id":930820,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70264079,"text":"sir20245096 - 2025 - Determining low-flow conditions at select streams to Barnegat Bay-Little Egg Harbor as the first step towards the development of ecological-flow targets","interactions":[],"lastModifiedDate":"2025-07-23T16:43:49.357537","indexId":"sir20245096","displayToPublicDate":"2025-03-11T09:00:00","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":"2024-5096","displayTitle":"Determining Low-Flow Conditions at Select Streams to Barnegat Bay-Little Egg Harbor as the First Step Towards the Development of Ecological-Flow Targets","title":"Determining low-flow conditions at select streams to Barnegat Bay-Little Egg Harbor as the first step towards the development of ecological-flow targets","docAbstract":"Maintaining streamflow to support human water needs and ecosystem services requires a fundamental understanding of the relations between changes in streamflow processes and ecosystem responses. Changes in the natural patterns in flow, geology, and topography alter the habitats that aquatic organisms rely on for food, shelter, and reproduction. The U.S. Geological Survey (USGS) implemented an ecological-flow framework that encapsulates the basic principles of the Ecological Limits of Hydrologic Alteration (ELOHA) to compare the relations between hydrologic metrics and stream conditions and estimate ecological flow needs in the Barnegat Bay-Little Egg Harbor watershed. As a first step in the ELOHA process, streamflow from two historical time periods (occurring between 1933 and 1988) was compared to streamflow for a recent time period (from 2004-2020) for four major streams in the Barnegat Bay-Little Egg Harbor watershed (North Branch Metedeconk River, Toms River, Cedar Creek, and Westecunk Creek), to evaluate if there were statistically significant differences in streamflow metrics. Analysis of monthly, seasonal, and annual low-flow metrics; patterns in the streamflow record; and general land-use changes were used to develop a better understanding of flow conditions in the watershed.
The comparative streamflow analysis indicated that notable changes in flow processes for the study streams occurred between the three periods of record (PORs) evaluated in this study: period of record 1 (POR1, from water years 1933–1958), period of record 2 (POR2, from water years 1974–1988), and period of record 3 (POR3, from water years 2004–2020). For example, the mean of the daily streamflow decreased between the historical POR to the current POR in Cedar Creek but increased in North Branch Metedeconk and Toms Rivers. Larger and more significant changes (p-value <0.10) occurred during specific months or were related to the variability or seasonality of flow. North Branch Metedeconk River and Toms River, the two northern and most developed sites, exhibited changes in low-flow metrics and decreases in minimum n-day moving averages. Decreases in the normalized 75th-percentile exceedance flows were evident at three of the four study sub-basins during POR2 and POR3. In comparison, there was little to no evidence of negative changes to low-flow metrics at Westecunk Creek, the southernmost and least developed site, where all low-flow duration metrics increased as well as seasonal minimum consecutive 7-day average flows. Significant increases in monthly minimums (p-value <0.05) at Cedar Creek for spring months (April, May, and June) also were observed.
Natural and anthropogenic processes can alter the landscape resulting in concomitant changes in the streamflow regime. There is a need to assess these changes and synthesize the results into a scientifically defensible set of goals and standards that help support the management of environmental flows. This study represents the initial steps in building the hydrologic foundation to inform management and develop future ecological flow targets that balance water availability for human and ecosystem needs in the Barnegat Bay-Little Egg Harbor watershed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245096","collaboration":"Prepared in cooperation with the Barnegat Bay Partnership","usgsCitation":"Wieben, C.M., Kennen, J.G., and Suro, T.P., 2025, Determining low-flow conditions at select streams to Barnegat Bay-Little Egg Harbor as the first step towards the development of ecological-flow targets: U.S. Geological Survey Scientific Investigations Report 2024–5096, 39 p., https://doi.org/10.3133/sir20245096.","productDescription":"vii, 39 p.","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-149405","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":492774,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118479.htm","linkFileType":{"id":5,"text":"html"}},{"id":482893,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5096/coverthb.jpg"},{"id":482897,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5096/images/"},{"id":482896,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5096/sir20245096.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5096 XML"},{"id":482895,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245096/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5096 HTML"},{"id":482894,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5096/sir20245096.pdf","text":"Report","size":"7.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5096 PDF"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay-Little Egg Harbor watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.5,\n 40.1667\n ],\n [\n -74.5,\n 39.5\n ],\n [\n -73.8333,\n 39.5\n ],\n [\n -73.8333,\n 40.1667\n ],\n [\n -74.5,\n 40.1667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
Birds are vital to our economy, ecosystems, and cultural heritage. Investing in bird conservation benefits communities, businesses, and working lands while reinforcing our nation’s legacy of stewardship and biodiversity. By valuing birds, we ensure a richer, healthier, and more vibrant future for all Americans. The USGS leads two national bird monitoring programs Thriving bird populations contribute over $100 billion in related purchases to the U.S. economy annually, helping to support 1.4 million jobs and $90 billion in labor-related income. Across our nation, Federal and State wildlife agencies, Flyway Councils, non-governmental organizations, and more consider data from the U.S. Geological Survey’s (USGS) Bird Banding Laboratory (BBL) and Breeding Bird Survey (BBS) to be critical to meeting their mandates to set healthy harvest levels and in identifying species of conservation need. However, without stable and sufficient resources for the BBL and BBS, the capacity to monitor and address the rapidly evolving needs of migratory bird populations is at risk, jeopardizing the foundation of collaborative conservation efforts across North America.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253011","programNote":"Species Management Research Program","usgsCitation":"Ziolkowski, D., Celis-Murillo, A., Malpass, J., Pardieck, K., Martin, J., and Walker, L., 2025, Foundational science in flight—USGS bird programs support conservation, culture, and a thriving U.S. economy: U.S. Geological Survey Fact Sheet 2025–3011, 4 p., https://doi.org/10.3133/fs202533011.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-175892","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":483152,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3011/fs20253011_print.pdf","text":"Report","size":"3.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3011 PDF","linkHelpText":"Printer-friendly version"},{"id":483073,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3011/images"},{"id":483072,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3011/fs20253011.XML","description":"FS 2025-3011 XML"},{"id":483070,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3011/fs20253011.pdf","text":"Report","size":"2.61 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3011 PDF"},{"id":483069,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3011/coverthb2.jpg"}],"country":"Canada, Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.02943301109039,\n 15.410306981738572\n ],\n [\n -86.44265063211188,\n 21.842039182358832\n ],\n [\n -79.453241061223,\n 26.64186789245565\n ],\n [\n -78.50306906661305,\n 32.979705227993094\n ],\n [\n -50.77847439442888,\n 48.892922136315434\n ],\n [\n -66.2635829932419,\n 75.41047680539205\n ],\n [\n -74.57496425238357,\n 78.3457781585499\n ],\n [\n -58.13072469895427,\n 83.1029782866932\n ],\n [\n -168.32855790630842,\n 70.40594475176928\n ],\n [\n -166.93127284689004,\n 55.679378483117404\n ],\n [\n -121.64076199951083,\n 32.65515564988158\n ],\n [\n -109.15060725080741,\n 19.965527030937324\n ],\n [\n -93.8127347824803,\n 12.893183633264144\n ],\n [\n -92.02943301109039,\n 15.410306981738572\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Rd.
Kearneysville, WV 25430
Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Freshwater megafishes are among some of the most commercially and ecologically important aquatic organisms yet are disproportionately threatened with range and population reduction. Anthropogenic alterations of rivers influencing migrations are among the most significant causes for these declines. However, migratory fishes do not always respond similarly to movement barriers and thus it is necessary to develop models to predict movements of freshwater migratory fishes in the face of anthropogenic alteration. Predicting movement of freshwater fishes is often investigated using statistical packages. However, empirical studies assessing these packages have led to mixed results, questioning its applicability to all taxa. We argue that spatial, temporal, and environmental attributes are more influential for movement of a migratory megafish, the Alligator Gar (Atractosteus spatula), than the current parameters explored in a globally relevant fish movement model.
This study explored two independent mobile telemetry datasets investigating Alligator Gar movement on the Brazos and Trinity rivers. Environmental associations were investigated to predict Alligator Gar displacement and dispersal using generalized additive models, generalized linear models, and model selection. Leptokurtosis of Alligator Gar populations was also assessed. Predictability of the movement model was tested by comparing observed to model derived stationary and mobile components making up a leptokurtic movement distribution.
Our study suggests that current and antecedent measures of discharge and water temperature are positively correlated with Alligator Gar displacement and dispersal. However, these patterns are only detectable when monthly relocation intervals are explored rather than seasonal scales. Leptokurtosis was observed in both Alligator Gar populations. However, movement was normally distributed (i.e., mesokurtic) under tracking events following high flood pulses. Additionally, predicted Alligator Gar movement was significantly farther under modeled values compared to observed values, in part because the species undergoes cyclical migrations for reproduction that are sensitive to water temperature and discharge.
In conclusion, this study provides an alternative framework to assess the movement patterns of migratory fishes, which could be tested on additional freshwater fishes, and suggests that assessing spatial, environmental, and temporal processes simultaneously are necessary to capture the complexities of fish movement which currently are unavailable for the movement model we investigated.
","language":"English","publisher":"BMC","doi":"10.1186/s40462-025-00544-7","usgsCitation":"Roberts, H.C., Kappen, F., Acre, M.R., Daugherty, D.J., Smith, N.G., and Perkin, J., 2025, Meta-analysis of a megafish: Assessing patterns and predictors of Alligator Gar movement across multiple populations: Movement Ecology, v. 13, no. 1, 15, 18 p., https://doi.org/10.1186/s40462-025-00544-7.","productDescription":"15, 18 p.","ipdsId":"IP-172438","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":488371,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-025-00544-7","text":"Publisher Index Page"},{"id":483713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.70591756751243,\n 30.894440659055704\n ],\n [\n -96.70591756751243,\n 29.622760974861365\n ],\n [\n -94.82999949548378,\n 29.622760974861365\n ],\n [\n -94.82999949548378,\n 30.894440659055704\n ],\n [\n -96.70591756751243,\n 30.894440659055704\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts, Hayden C.","contributorId":335083,"corporation":false,"usgs":false,"family":"Roberts","given":"Hayden","email":"","middleInitial":"C.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":931580,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kappen, Florian","contributorId":352518,"corporation":false,"usgs":false,"family":"Kappen","given":"Florian","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":931581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Acre, Matthew Ross 0000-0002-5417-9523","orcid":"https://orcid.org/0000-0002-5417-9523","contributorId":268034,"corporation":false,"usgs":true,"family":"Acre","given":"Matthew","email":"","middleInitial":"Ross","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":931582,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daugherty, Daniel J.","contributorId":335084,"corporation":false,"usgs":false,"family":"Daugherty","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":931583,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Nathan G.","contributorId":268036,"corporation":false,"usgs":false,"family":"Smith","given":"Nathan","email":"","middleInitial":"G.","affiliations":[{"id":55541,"text":"Heart of the Hills Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":931584,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Perkin, Joshuah S.","contributorId":238286,"corporation":false,"usgs":false,"family":"Perkin","given":"Joshuah S.","affiliations":[{"id":47708,"text":"Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station, TX","active":true,"usgs":false}],"preferred":false,"id":931585,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70264306,"text":"70264306 - 2025 - 6PPD-quinone in water from the San Francisco-San Joaquin Delta, California, 2018-2024","interactions":[],"lastModifiedDate":"2025-03-11T14:21:30.245946","indexId":"70264306","displayToPublicDate":"2025-03-10T09:15:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"6PPD-quinone in water from the San Francisco-San Joaquin Delta, California, 2018-2024","docAbstract":"The Sacramento-San Joaquin Delta (Delta) is an expansive river delta supplying a large portion of California’s fresh water for agriculture and residential use, and it is also an area of critical habitat for numerous state and federally listed species of concern. In many locations, urban stormwater flows directly into the Delta. 6PPD-quinone (6PPD-Q), an ozonation byproduct of a tire antiozonant 6PPD, has been shown to enter surface water via these pathways and can cause various toxicological effects, including acute urban mortality syndrome to coho salmon (Oncorhynchus kisutch) at low levels (LC50 = 41 and 95 ng/L for juveniles and adults, respectively). Here, we quantified 6PPD-Q in 61 archived Delta water extracts collected between 2018 and 2024 and found concentrations up to 21 ng/L. Currently, no 6PPD-Q presence and/or quantitative data is available for this complex and diverse ecosystem. Little is known regarding long-term storage of 6PPD-quinone in solvent extracts, so 6PPD-Q observations document its presence in the study area and provide evidence that further sampling may be warranted to better quantify environmental concentrations. Consistent with the general understanding of 6PPD-Q transport, all detections observed were in samples collected during or immediately after a precipitation event. This work provides environmentally relevant concentration data to complement ongoing toxicological investigations of 6PPD-Q in Delta organisms and suggests there are research opportunities for a more robust survey of 6PPD-Q inputs into the Delta.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-025-13757-5","usgsCitation":"Black, G.P., De Parsia, M., Uychutin, M., Lane, R.F., Orlando, J., and Hladik, M.L., 2025, 6PPD-quinone in water from the San Francisco-San Joaquin Delta, California, 2018-2024: Environmental Monitoring and Assessment, v. 197, no. 4, 369, 9 p., https://doi.org/10.1007/s10661-025-13757-5.","productDescription":"369, 9 p.","ipdsId":"IP-169662","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":483195,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco‑San Joaquin delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.4615589600206,\n 38.89855420973035\n ],\n [\n -122.4156538354604,\n 37.57763045605546\n ],\n [\n -120.7611068337572,\n 37.57763045605546\n ],\n [\n -120.7611068337572,\n 38.92128311603909\n ],\n [\n -122.4615589600206,\n 38.89855420973035\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"197","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Black, Gabrielle Pecora 0000-0002-1578-742X","orcid":"https://orcid.org/0000-0002-1578-742X","contributorId":303108,"corporation":false,"usgs":true,"family":"Black","given":"Gabrielle","email":"","middleInitial":"Pecora","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930372,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Parsia, Matthew D. 0000-0001-5806-5403","orcid":"https://orcid.org/0000-0001-5806-5403","contributorId":204707,"corporation":false,"usgs":true,"family":"De Parsia","given":"Matthew D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930373,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Uychutin, Matthew 0000-0003-2677-7902","orcid":"https://orcid.org/0000-0003-2677-7902","contributorId":339824,"corporation":false,"usgs":true,"family":"Uychutin","given":"Matthew","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930374,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lane, Rachael F. 0000-0001-9202-0612","orcid":"https://orcid.org/0000-0001-9202-0612","contributorId":222471,"corporation":false,"usgs":true,"family":"Lane","given":"Rachael","email":"","middleInitial":"F.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":930375,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orlando, James 0000-0002-0099-7221","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":208413,"corporation":false,"usgs":true,"family":"Orlando","given":"James","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930376,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221087,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930377,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70264193,"text":"sir20255004 - 2025 - Assessment of effects of channelization mitigation alternatives of Stoney Brook, Carlton and St. Louis Counties, Minnesota","interactions":[],"lastModifiedDate":"2025-07-23T16:37:17.642571","indexId":"sir20255004","displayToPublicDate":"2025-03-10T08:26:00","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":"2025-5004","displayTitle":"Assessment of Effects of Channelization Mitigation Alternatives of Stoney Brook, Carlton and St. Louis Counties, Minnesota","title":"Assessment of effects of channelization mitigation alternatives of Stoney Brook, Carlton and St. Louis Counties, Minnesota","docAbstract":"The U.S. Geological Survey, in cooperation with the Fond du Lac Band of Lake Superior Chippewa (FDLB), studied the effects of channel modification alternatives on lake levels and floodplain inundation in the Stoney Brook watershed in northeast Minnesota. Northern wild rice (Zizania palustris), also referred to as manoomin by the Ojibwe/Chippewa people, is a natural and cultural resource to the FDLB and is sensitive to water levels and rates of water-level changes, particularly during the early stages of growth. Drainage ditches constructed in the early 1900s in the Stoney Brook watershed lowered lake-water levels, caused greater fluctuations in the lakes, and created a loss in wetland coverage. The FDLB is committed to minimizing large fluctuations of the lakes with natural wild rice production in the Stoney Brook watershed and restoring a more natural hydrology to Stoney Brook. The hydrologic response of these lakes and floodplain storage to simulated channel modification alternatives were examined.
Hydrologic and hydraulic models were developed for the watershed and calibrated to historical rainfall events. The models used probabilistic frequency rainfall events of 24-hour duration for 1-, 2-, 5-, and 10-year annual recurrence intervals (100-, 50-, 20-, and 10-percent annual exceedance probability) to simulate watershed management scenarios with existing and alternative conditions. The hydraulic model outputs for peak flows, volume accumulation, water levels, and inundation duration and depths were assessed to quantify the effects of the channel modification alternatives. The channel modification alternatives were simulated with four different terrain conditions: existing conditions, bank spoil breach, original channel reconnection, and original channel reconnection with bank spoil breach. Hydrologic characteristics from six distinct areas were used in the model to evaluate the effects from the channel modification alternatives.
The simulated results of two lakes in which wild rice was planted demonstrated that the lakes would take longer to draw down following an event with the channel modification alternatives compared to existing conditions with little change to peak water-surface elevations. The alternatives provided minor to no increases in flows or conveyances at the downstream reference location at Pine Drive bridge. The restored floodplain locations had increased flows and conveyances for the channel modification alternatives that could be considered substantial when compared to flows with existing conditions. The inundation extent, duration, and water-depth distribution were assessed within selected floodplain areas. Generally, the channel modification alternatives produced increases in the higher depth (3–4 and greater than 4 feet) and duration (10–14 and greater than 14 days) categories for these areas, which may be beneficial to increases in wetland coverage and floodplain storage.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255004","collaboration":"Prepared in cooperation with the Fond du Lac Band of Lake Superior Chippewa","usgsCitation":"Cigrand, C.V., 2025, Assessment of effects of channelization mitigation alternatives of Stoney Brook, Carlton and St. Louis Counties, Minnesota: U.S. Geological Survey Scientific Investigations Report 2025–5004, 44 p., https://doi.org/10.3133/sir20255004.","productDescription":"Report: ix, 44 p.; Data Release; Dataset","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-132433","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":483061,"rank":5,"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":483062,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13KFQSL","text":"USGS data release","linkHelpText":"Archive of hydraulic and hydrologic models used in the Stoney Brook watershed in Carlton and St. Louis Counties, Minnesota, 2008–2024"},{"id":483057,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5004/coverthb.jpg"},{"id":483058,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5004/sir20255004.pdf","text":"Report","size":"9.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025–5004"},{"id":483059,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5004/sir20255004.XML"},{"id":483060,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5004/images/"},{"id":483063,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255004/full"},{"id":492770,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118476.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Minnesota","county":"Carlton County, St. Louis County","otherGeospatial":"Stoney Brook watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.4667,\n 46.8667\n ],\n [\n -92.8,\n 46.8667\n ],\n [\n -92.8,\n 46.633\n ],\n [\n -92.4667,\n 46.633\n ],\n [\n -92.4667,\n 46.8667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
In the United States, wildlife managers are entrusted with preserving culturally and economically important ungulate populations in the face of the ongoing spread of chronic wasting disease (CWD). The U.S. Fish and Wildlife Service established an adaptive management plan to reduce the reliance of elk (Cervus canadensis) on supplemental winter feeding on the National Elk Refuge. The end goal of reducing the unnaturally high aggregation of elk during the winter is to mitigate the threat of disease outbreaks and to meet the objectives of sustainable populations of elk on the refuge. In this case study, we evaluated 6 years (2017–2022) of data from GPS-collared elk to determine the efficacy of shortening the length of the annual feeding period on the refuge to reduce elk aggregation. We measured aggregation using proximity rates, based on pairwise interactions over time, in both raw form as an index as well as predicted proximity as a function of other abiotic influences. We created a new R package, wildagg, to help with the process of computing the metrics from our study and to increase reproducibility in the future. Aggregation declined in years with less feeding on the refuge according to raw aggregation metrics when examined in isolation and dependent on the baseline feeding year used for comparison. However, accounting for abiotic factors while modeling proximity rates suggested in some years the decision to shorten the feeding period had less influence on aggregation than predicted. Our results underscore the complexity of measuring management outcomes and the usefulness of multiple approaches to evaluation.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1574","usgsCitation":"Janousek, W.M., Cole, E., Dewey, S.R., and Graves, T., 2025, Informing adaptive management to reduce ungulate aggregations: A case study involving winter feeding of elk: Wildlife Society Bulletin, v. 49, no. 1, e1574, 12 p., https://doi.org/10.1002/wsb.1574.","productDescription":"e1574, 12 p.","ipdsId":"IP-153310","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":488309,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wsb.1574","text":"Publisher Index Page"},{"id":483356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"National Elk Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.7137912687953,\n 43.57693522181455\n ],\n [\n -110.7137912687953,\n 43.5282857345309\n ],\n [\n -110.63727861874892,\n 43.5282857345309\n ],\n [\n -110.63727861874892,\n 43.57693522181455\n ],\n [\n -110.7137912687953,\n 43.57693522181455\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Janousek, William Michael 0000-0003-3978-1775","orcid":"https://orcid.org/0000-0003-3978-1775","contributorId":237980,"corporation":false,"usgs":true,"family":"Janousek","given":"William","email":"","middleInitial":"Michael","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":930720,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cole, Eric K. 0000-0002-2229-5853","orcid":"https://orcid.org/0000-0002-2229-5853","contributorId":145755,"corporation":false,"usgs":false,"family":"Cole","given":"Eric K.","affiliations":[{"id":16228,"text":"U.S. Fish and Wildlife Service, National Elk Refuge, PO Box 510, Jackson, WY 83001 USA","active":true,"usgs":false}],"preferred":false,"id":930721,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dewey, Sarah R.","contributorId":264423,"corporation":false,"usgs":false,"family":"Dewey","given":"Sarah","email":"","middleInitial":"R.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":930722,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":930723,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265878,"text":"70265878 - 2025 - Population trends of native and non-native forest birds on the island of Molokai, Hawaii","interactions":[],"lastModifiedDate":"2025-04-17T15:11:55.20767","indexId":"70265878","displayToPublicDate":"2025-03-10T08:06:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7509,"text":"The Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Population trends of native and non-native forest birds on the island of Molokai, Hawaii","docAbstract":"Hawaiʻi’s avifauna has undergone profound changes over the past 1,000 years, with many endemic bird species driven to extinction and non-native introductions reshaping forest ecosystems. On the island of Molokaʻi, habitat degradation and the introduction of mosquito-borne disease, mainly avian malaria (Plasmodium relictum), have caused extinctions and severe declines in native forest bird populations. To assess these changes, point-transect distance sampling surveys were initiated in 1979 and 1980 and repeated six times, most recently in 2021, covering a 3,527 ha area. This study analyzes species composition, population densities, abundances, and long-term trends for species with sufficient detections using log-linear regression. Since 1979–1980, a total of 17 non-native and 3 native species were detected across all six surveys. The non-native Warbling White-eye (Zosterops japonicus) had the highest density and abundance in every survey, while abundance of Red-billed Leiothrix (Leiothrix lutea) significantly trended upward. The Japanese Bush Warbler (Horornis diphone) irrupted in the survey area, increasing in abundance by more than 99% since 1979–1980. Among native species, ʻApapane (Himatione sanguinea) populations increased by 33%, while Hawaiʻi ʻAmakihi (Chlorodrepanis virens) declined by 78% from their peak in 1995. Federally threatened ʻIʻiwi (Drepanis coccinea), highly susceptible to avian malaria, have not been recorded on Molokaʻi since 2010, and the endemic Olomaʻo (Myadestes lanaiensis) has not been detected since 1980 and is possibly extinct. Our results underscore the ongoing conservation crisis for Molokaʻi’s forest birds and the continued vulnerability of native birds to disease and habitat loss.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15594491.2024.2444022","usgsCitation":"Smith, L., Judge, S., Genz, A., Berry, L., Berthold, L.K., Mounce, H., and Camp, R.J., 2025, Population trends of native and non-native forest birds on the island of Molokai, Hawaii: The Wilson Journal of Ornithology, v. 137, no. 1, p. 51-64, https://doi.org/10.1080/15594491.2024.2444022.","productDescription":"14 p.","startPage":"51","endPage":"64","ipdsId":"IP-153478","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":488281,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/15594491.2024.2444022","text":"Publisher Index Page"},{"id":484680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Molokai","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -157.28873231120195,\n 21.241518704959404\n ],\n [\n -157.3259292153299,\n 21.127451352654802\n ],\n [\n -157.28873231120195,\n 21.03800311764543\n ],\n [\n -156.71002845991853,\n 21.03800311764543\n ],\n [\n -156.71002845991853,\n 21.241518704959404\n ],\n [\n -157.28873231120195,\n 21.241518704959404\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"137","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Lauren K. 0000-0003-1783-715X","orcid":"https://orcid.org/0000-0003-1783-715X","contributorId":353538,"corporation":false,"usgs":false,"family":"Smith","given":"Lauren K.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":933792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Judge, Seth 0000-0003-3832-3246","orcid":"https://orcid.org/0000-0003-3832-3246","contributorId":189965,"corporation":false,"usgs":false,"family":"Judge","given":"Seth","email":"","affiliations":[],"preferred":false,"id":933793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Genz, Ayesha 0000-0002-2916-1436","orcid":"https://orcid.org/0000-0002-2916-1436","contributorId":196671,"corporation":false,"usgs":false,"family":"Genz","given":"Ayesha","email":"","affiliations":[],"preferred":false,"id":933794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Berry, Lainie","contributorId":272646,"corporation":false,"usgs":false,"family":"Berry","given":"Lainie","email":"","affiliations":[{"id":56397,"text":"State of Hawai‘i, Division of Forestry and Wildlife","active":true,"usgs":false}],"preferred":false,"id":933795,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berthold, Laura K","contributorId":264666,"corporation":false,"usgs":false,"family":"Berthold","given":"Laura","email":"","middleInitial":"K","affiliations":[{"id":54533,"text":"Maui Forest Bird Recovery Project, Pacific Cooperative Studies Unit, University of Hawai‘i at Manoa","active":true,"usgs":false}],"preferred":false,"id":933796,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mounce, Hanna L.","contributorId":253154,"corporation":false,"usgs":false,"family":"Mounce","given":"Hanna L.","affiliations":[{"id":13352,"text":"Maui Forest Bird Recovery Project","active":true,"usgs":false}],"preferred":false,"id":933797,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":933798,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70269684,"text":"70269684 - 2025 - Characterizing the scale of regional landslide triggering from storm hydrometeorology","interactions":[],"lastModifiedDate":"2025-07-30T14:49:56.57927","indexId":"70269684","displayToPublicDate":"2025-03-10T07:42:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17114,"text":"Natural Hazards and Earth Systems Sciences (NHESS)","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing the scale of regional landslide triggering from storm hydrometeorology","docAbstract":"Rainfall strongly affects landslide triggering; however, understanding how storm characteristics relate to the severity of landslides at the regional scale has thus far remained unclear, despite the societal benefits that would result from defining this relationship. As mapped landslide inventories typically cover a small region relative to a storm system, here we develop a dimensionless index for landslide-inducing rainfall, A*, based on extremes of modeled soil water relative to its local climatology. We calibrate A* using four landslide inventories, comprising over 11 000 individual landslides over four unique storm events, and find that a common threshold can be applied to estimate regional shallow-landslide-triggering potential across diverse climatic regimes in California (USA). We then use the spatial distribution of A*, along with topography, to calculate the landslide potential area (LPA) for nine landslide-inducing storm events over the past 20 years, and we test whether atmospheric metrics describing the strength of landfalling storms, such as integrated water vapor transport, correlate with the magnitude of hazardous landslide-inducing rainfall. We find that although the events with the largest LPA do occur during exceptional atmospheric river (AR) storms, the strength of landfalling atmospheric rivers does not scale neatly with landslide potential area, and even exceptionally strong ARs may yield minimal landslide impacts. Other factors, such as antecedent soil moisture driven by storm frequency and mesoscale precipitation features within storms, are instead more likely to dictate the patterns of landslide-generating rainfall throughout the state.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/nhess-25-1037-2025","usgsCitation":"Perkins, J.P., Oakley, N.S., Collins, B.D., Corbett, S.C., and Burgess, W.P., 2025, Characterizing the scale of regional landslide triggering from storm hydrometeorology: Natural Hazards and Earth Systems Sciences (NHESS), v. 25, no. 3, p. 1037-1056, https://doi.org/10.5194/nhess-25-1037-2025.","productDescription":"20 p.","startPage":"1037","endPage":"1056","ipdsId":"IP-144518","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":493301,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-25-1037-2025","text":"Publisher Index Page"},{"id":493184,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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For long-lived animals and those with boom-and-bust life histories, perspective across time contributes to discerning temporal trends in occupancy and persistence, and potentially in identifying mechanisms affecting those parameters. Long-term data are particularly useful in protected areas to quantify indicators of change that may be less obvious or occur more slowly. We used long-term amphibian data from Rocky Mountain National Park (RMNP) in a Bayesian occupancy modeling framework to estimate changes in occupancy, colonization, and persistence of amphibians over three decades and to explore the effects of climate, landscape change, and visitor use as mechanisms behind observed changes. Our results indicate that colonization and persistence are low and/or declining for Pseudacris maculata, Lithobates sylvaticus, and Ambystoma mavortium, and that occupied catchments are increasingly isolated. 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","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70210","usgsCitation":"Kissel, A.M., Watry, M., Evan Bredeweg, and Muths, E., 2025, Assessing the effects of climate and visitor use on amphibian occupancy in a protected landscape with long-term data: Ecosphere, v. 16, no. 3, e70210, 18 p., https://doi.org/10.1002/ecs2.70210.","productDescription":"e70210, 18 p.","ipdsId":"IP-159475","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":493784,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70210","text":"Publisher Index Page"},{"id":493569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Mountain National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.8238828687088,\n 40.47056779384607\n ],\n [\n -105.8238828687088,\n 40.178502721775686\n ],\n [\n -105.49527410941528,\n 40.178502721775686\n ],\n [\n -105.49527410941528,\n 40.47056779384607\n ],\n [\n -105.8238828687088,\n 40.47056779384607\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Kissel, Amanda Marie 0000-0002-6346-7455","orcid":"https://orcid.org/0000-0002-6346-7455","contributorId":334356,"corporation":false,"usgs":true,"family":"Kissel","given":"Amanda","email":"","middleInitial":"Marie","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":944877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watry, Mary Kay","contributorId":359046,"corporation":false,"usgs":false,"family":"Watry","given":"Mary Kay","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":944878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evan Bredeweg","contributorId":359047,"corporation":false,"usgs":false,"family":"Evan Bredeweg","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":944879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muths, Erin L. 0000-0002-5498-3132","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":245922,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":944880,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70264310,"text":"70264310 - 2025 - Decadal-scale effects of a dam removal on channel geomorphology, sediment and large wood on the Elwha River, Washington, USA","interactions":[],"lastModifiedDate":"2025-03-11T14:40:43.1934","indexId":"70264310","displayToPublicDate":"2025-03-08T09:33:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Decadal-scale effects of a dam removal on channel geomorphology, sediment and large wood on the Elwha River, Washington, USA","docAbstract":"The removal of Glines Canyon Dam on the Elwha River in western Washington, USA, from 2011 to 2014 introduced a 20-Mt pulse of stored sediment and logs into the downstream channel. We used terrestrial laser scanning, high-resolution orthoimages, and surveys of large wood (LW) and sediment grain-size distribution to quantify changes to the channel and LW in four different geomorphic settings spanning a 16-year period before, during, and after dam removal. The results provide insights into the role of site-specific geomorphology on the interplay among sediment size and supply, wood, and channel form in the aftermath of a dam removal. Sediment-size distribution, braiding index, and number of log jams rapidly reached new steady states. Other factors, such as channel sinuosity and log jam area, were still evolving six years after the dam was removed. The rate and type of river response was partially dictated by the geomorphic setting and the accumulation of LW. Complex reaches trapped more sediment and LW, initiating immediate changes in the channel count, position and lateral migration that continued to evolve through positive feedbacks. Single-channel sites experienced less initial erosion and deposition, but channel migration continued for years once it was underway. The post-dam sediment composition progressively shifted to a mixed size distribution midway between the armored cobbles when the dam was in place and the influx of primarily sand and fine gravel during dam removal. Reworking of sediment was most rapid in the first year after dam removal, especially at the site with the greatest channel complexity. The relation between log jams and channel divisions fundamentally changed. There were 11 log jams in the middle reach of the Elwha River downstream of Glines Canyon Dam, and all log jams associated with channel divisions occurred at the heads of stable, vegetated islands. During dam removal, the number of log jams rapidly increased to 86 and stabilized near that level in the post-dam period. While log jams on stable islands persisted, more were added at divisions around transient sediment bars, scattered across gravel bars, or outside of the active channel. Following a brief spike during dam removal, there was a net long-term increase of ∼10 % in the number of channel divisions associated with log jams. The sediment deposits, LW, vegetation, channel morphology and river discharge continued to cause adjustments within the fluvial system a decade after the start of dam removal. This state of greater variability could be the new equilibrium for years to come.
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12201 Sunrise Valley Drive, Mail Stop 303
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Satellite-derived maps of vegetation cover provide detailed information about vegetation spatiotemporal patterns and are increasingly used to better understand and manage rangelands. Despite their utility, questions remain regarding the regional and site level accuracy for these maps, especially compared to field-collected data. We conducted an accuracy assessment of the Rangeland Analysis Platform (RAP), using over 17,000 field plots sampled through nationwide rangeland vegetation monitoring programs in the continental U.S. We observed higher overall nationwide map error compared to previous validations of RAP, and absolute error (Mean Absolute Error [MAE] and Root Mean Square Error [RMSE]) was highest for perennial herbaceous and bare ground and lowest for trees (MAE range = 2.98 –10.22 %). There were also differences in map agreement with field data across ecoregions. Generally, map agreement was highest in the Great Basin and lowest in the Great Plains and Desert Southwest. Additionally, we assessed the suitability of using RAP in riparian and wetland areas, which are absent in the current version’s training. Errors for bare ground in riparian areas were lower than errors of upland accuracy assessments (upland MAE = 10.22 %, riparian MAE = 7.22 %), but for all other functional groups, riparian error was higher (ΔMAE range: 0.21 – 20.49 %). We examine how our results could inform regional applications of fractional cover data while considering error and uncertainty and identify areas for potential model improvement. Our findings inform the use of RAP regionally and provide a technique for evaluating other vegetation mapping products for use in rangeland management.
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such as salt marshes requires an understanding of the complex stressors influencing their continued threat of drowning. However, efforts to determine the effects of one potential stressor, ditches, have produced diverging results complicating management efforts. Ditches (linear trenches dug to drain salt marshes for agriculture and mosquito control) alter salt marsh hydrology, but their effects on widescale marsh function and degradation are poorly understood. We created a dataset of visible ditches and summarized ditch densities (length of ditches over area) for salt marshes of the Northeast U.S. to evaluate ditching against vulnerability metrics, including elevation and the unvegetated to vegetated marsh ratio (UVVR). We identified a scale dependency in which the larger/coarser the spatial scale of analysis, the greater the fraction of ditched salt marshes. Scale dependence explains discrepancies between previously determined ditch indices. In terms of effects on marsh vulnerability, relative elevation was not influenced by visible ditch presence. Ditch densities affected UVVR, exhibiting a multiple threshold behavior. When present at low densities, ditches have little effect on ponding; yet as ditch densities increase, UVVR (i.e., ponding) increases. The relationship between ditching and UVVR reverses at the highest ditch densities, with ponding substantially decreasing. The multiple threshold vulnerability response of Northeast salt marshes to the hydrologic influences imposed by ditching suggests restoration strategies should consider the degree of ditching rather than simply ditching presence.
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Woods Hole, MA 02543.","active":true,"usgs":false}],"preferred":false,"id":931995,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":931996,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":931997,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hartley, Mitch","contributorId":272059,"corporation":false,"usgs":false,"family":"Hartley","given":"Mitch","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":931998,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Johnson, Catherine","contributorId":306165,"corporation":false,"usgs":false,"family":"Johnson","given":"Catherine","affiliations":[{"id":66380,"text":"National Park Service, University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":931999,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mercer, Jason J","contributorId":219802,"corporation":false,"usgs":false,"family":"Mercer","given":"Jason","email":"","middleInitial":"J","affiliations":[{"id":34987,"text":"University of Wyoming, Laramie, WY","active":true,"usgs":false}],"preferred":false,"id":932000,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ruskin, Katharine J.","contributorId":352685,"corporation":false,"usgs":false,"family":"Ruskin","given":"Katharine J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":932001,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Woodruff, Jonathan D.","contributorId":192777,"corporation":false,"usgs":false,"family":"Woodruff","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":932002,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Yellen, Brian","contributorId":198491,"corporation":false,"usgs":false,"family":"Yellen","given":"Brian","email":"","affiliations":[{"id":33278,"text":"Department of Geosciences, University of Massachusetts, Amherst, MA","active":true,"usgs":false}],"preferred":false,"id":932003,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70263876,"text":"70263876 - 2025 - Population vulnerability of residents, employees, and cruise-ship passengers to tsunami hazards of islands in complex seismic regions: A case study of the U.S. Virgin Islands","interactions":[],"lastModifiedDate":"2025-04-30T15:22:09.702835","indexId":"70263876","displayToPublicDate":"2025-03-07T08:15:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2036,"text":"International Journal of Disaster Risk Reduction","active":true,"publicationSubtype":{"id":10}},"title":"Population vulnerability of residents, employees, and cruise-ship passengers to tsunami hazards of islands in complex seismic regions: A case study of the U.S. Virgin Islands","docAbstract":"Reducing the potential for loss of life from tsunamis is challenging on islands located in complex seismic regions given the multiple sources that surround islands, differences among islands in the amount of time needed to evacuate before wave arrival, and the high number of residents, employees, and tourists in tsunami-hazard zones. We examine variations in population vulnerability in island communities to multiple tsunami threats and use the United States territory of the U.S. Virgin Islands (USVI), including St. Thomas Island, St. John Island, and St. Croix Island, as our case study. We estimate the tsunami-hazard exposure of residents, employees, and cruise-ship passengers on vessels docking at USVI maritime facilities, as well as model pedestrian travel times out of inundation zones for 13 credible tsunami scenarios. Results indicate that the threat to life safety in USVI posed by tsunamis is not equal among the three islands, both in terms of the magnitude of people in hazard zones and the amount of time available to evacuate for the various scenarios. The number of employees and cruise-ship passengers in tsunami-hazard zones is orders of magnitude higher than the number of residents, suggesting that risk assessments that only account for residents are under-estimating threats to life safety from tsunamis. Finally, reducing departure delays has a greater impact than increasing pedestrian travel speeds on reducing the number of people that may have insufficient time to evacuate hazard zones before wave arrival.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijdrr.2025.105289","usgsCitation":"Wood, N.J., Peters, J., and Moore, C., 2025, Population vulnerability of residents, employees, and cruise-ship passengers to tsunami hazards of islands in complex seismic regions: A case study of the U.S. Virgin Islands: International Journal of Disaster Risk Reduction, v. 119, 105289, 15 p., https://doi.org/10.1016/j.ijdrr.2025.105289.","productDescription":"105289, 15 p.","ipdsId":"IP-172610","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":487887,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijdrr.2025.105289","text":"Publisher Index Page"},{"id":482556,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"U.S. Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -65.10271729681736,\n 18.453483664421626\n ],\n [\n -65.10271729681736,\n 18.217661626050017\n ],\n [\n -64.66350061715465,\n 18.217661626050017\n ],\n [\n -64.66350061715465,\n 18.453483664421626\n ],\n [\n -65.10271729681736,\n 18.453483664421626\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"119","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":928795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peters, Jeff 0000-0003-4312-0590 jpeters@usgs.gov","orcid":"https://orcid.org/0000-0003-4312-0590","contributorId":4711,"corporation":false,"usgs":true,"family":"Peters","given":"Jeff","email":"jpeters@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":928796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Christopher","contributorId":202056,"corporation":false,"usgs":false,"family":"Moore","given":"Christopher","affiliations":[{"id":33877,"text":"CNTS","active":true,"usgs":false}],"preferred":false,"id":928797,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271427,"text":"70271427 - 2025 - UAV-derived models of vegetation characteristics do not transfer to extreme drought and wet conditions across a northern Arizona landscape","interactions":[],"lastModifiedDate":"2025-09-15T13:19:09.227483","indexId":"70271427","displayToPublicDate":"2025-03-07T07:46:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"UAV-derived models of vegetation characteristics do not transfer to extreme drought and wet conditions across a northern Arizona landscape","docAbstract":"Context
Shifts in precipitation regimes due to climate change are significantly impacting dryland ecosystems, including vegetation composition and structure. Unoccupied aerial vehicles (UAVs) are widely used to monitor vegetation, but whether models built to predict changes in these characteristics are robust under extreme precipitation regimes is unclear.
Objectives
We aimed to predict key vegetation characteristics under three precipitation regimes (ambient, drought, and water addition) and assess model performance across these moisture conditions. We also evaluated how models built under ambient conditions predicted vegetation characteristics under extreme precipitation regimes.
Methods
UAV surveys were conducted at five sites subject to long-term precipitation manipulation along an elevation gradient in northern Arizona, United States (U.S.). Twenty-one vegetation indices and point cloud data from the UAV imagery were used to develop models to predict vegetation structure and composition characteristics. Model performance and transferability were assessed via error and directional bias within each treatment (i.e., in situ) and from ambient to precipitation treatments (i.e., model transfer).
Results
UAV-based models accurately measured vegetation characteristics across all regimes, but maximum height showed significantly higher error under drought conditions. Models developed under ambient precipitation and applied to extreme precipitation treatments exhibited significant differences in the error and directional bias, indicating they may not be suitable under climate change.
Conclusions
UAV-based models are effective for monitoring vegetation characteristics but may lose accuracy under extreme precipitation regimes expected under climate change. This study emphasizes the need to improve model transferability and suggests refining landscape monitoring approaches to consider extreme changes in precipitation and associated vegetation responses.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10980-025-02064-6","usgsCitation":"Blackburn, R.C., Allington, G.R., Motzer, N., Munson, S.M., and Huang, Q., 2025, UAV-derived models of vegetation characteristics do not transfer to extreme drought and wet conditions across a northern Arizona landscape: Landscape Ecology, v. 40, 59, 17 p., https://doi.org/10.1007/s10980-025-02064-6.","productDescription":"59, 17 p.","ipdsId":"IP-171149","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":496414,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-025-02064-6","text":"Publisher Index Page"},{"id":495407,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"northern Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.00885151827934,\n 35.49924603762916\n ],\n [\n -112.00885151827934,\n 34.90066874429827\n ],\n [\n -111.00177522680366,\n 34.90066874429827\n ],\n [\n -111.00177522680366,\n 35.49924603762916\n ],\n [\n -112.00885151827934,\n 35.49924603762916\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationDate":"2025-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Blackburn, Ryan C. 0000-0002-2952-0865","orcid":"https://orcid.org/0000-0002-2952-0865","contributorId":361388,"corporation":false,"usgs":false,"family":"Blackburn","given":"Ryan","middleInitial":"C.","affiliations":[{"id":86267,"text":"Smithsonian Conservation Biology Institute, Front Royal, Virginia, USA","active":true,"usgs":false}],"preferred":false,"id":948728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allington, Ginger R. H. 0000-0003-0446-0576","orcid":"https://orcid.org/0000-0003-0446-0576","contributorId":213452,"corporation":false,"usgs":false,"family":"Allington","given":"Ginger","email":"","middleInitial":"R. H.","affiliations":[{"id":34680,"text":"George Washington University","active":true,"usgs":false}],"preferred":false,"id":948729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Motzer, Nicole","contributorId":361389,"corporation":false,"usgs":false,"family":"Motzer","given":"Nicole","affiliations":[{"id":86268,"text":"Office of Research Development, Montana State University, Bozeman, MT, USA","active":true,"usgs":false}],"preferred":false,"id":948730,"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":948731,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huang, Qiongyu","contributorId":298920,"corporation":false,"usgs":false,"family":"Huang","given":"Qiongyu","affiliations":[{"id":37784,"text":"Smithsonian Conservation Biology Institute","active":true,"usgs":false}],"preferred":false,"id":948732,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70264080,"text":"tm11E1 - 2025 - Lunar grid systems, coordinate systems, and map projections for the Artemis missions and lunar surface navigation","interactions":[],"lastModifiedDate":"2025-03-07T14:34:26.559588","indexId":"tm11E1","displayToPublicDate":"2025-03-06T14:33:35","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"11-E1","displayTitle":"Lunar Grid Systems, Coordinate Systems, and Map Projections for the Artemis Missions and Lunar Surface Navigation","title":"Lunar grid systems, coordinate systems, and map projections for the Artemis missions and lunar surface navigation","docAbstract":"This document contains design specifications of a navigational standard for the Moon, including a Lunar Transverse Mercator system, a Lunar Polar Stereographic system, a Lunar Grid Reference System, and a unique coordinate structure, Artemis Condensed Coordinates, for Artemis mission navigation and lunar surface science.
The National Aeronautics and Space Administration (NASA) Artemis campaign seeks to place humans on the Moon for the first time since the Apollo missions. Early Artemis missions are heavily focused on the lunar south pole, which promises to return valuable data on the Moon’s geologic record, amongst other mission objectives. Coordinate systems in use today for the lunar south pole provides crew members on the surface neither an efficient nor intuitive means to communicate their position and orientation. A novel grid coordinate system, the Lunar Grid Reference System, is proposed to address these concerns for use in real-time extravehicular activity operations on the lunar surface.
The many stakeholders involved in the Artemis missions will need a common system to communicate position and orientation while astronauts are operating on the lunar surface. To that end, Artemis crew members will need that system to be efficient and intuitive to promote efficient extravehicular activity timelines and reduce confusion. In the context of this document, these characteristics are addressed on the design of lunar coordinate systems:
Technological systems are currently being investigated to supplement the crew members’ ability to locate and orient themselves and other assets on the lunar surface; however, it is unlikely that those systems will be fully operational for the first few landed missions. Even with future positional aids, crew members will still need an efficient and intuitive means to communicate position and orientation. In addition, if technological systems fail, the crews will require land navigation skills and have maps available, thus providing further motivation for a crew-centric coordinate system.
The contents of this U.S. Geological Survey (USGS) document detail a comprehensive framework for standardizing lunar crewed surface navigation within NASA and outlines the protocols, methods, and designs necessary for achieving consistency and interoperability across relevant space mission teams and lunar surface navigators. Key components of this document include designs of map projections, projected coordinate reference systems (Lunar Transverse Mercator and Lunar Polar Stereographic systems), and a grid system (Lunar Grid Reference System and Artemis Condensed Coordinates) for the Moon.
The work proposed in this document seeks to accomplish something similar to the National Geospatial-Intelligence Agency (NGA) document SIG 0012 (NGA, 2014a), but for using grid systems for the Moon. This report incorporates initial feedback and input from NASA’s Artemis Geospatial Data Team, NASA’s Flight Operations Directorate, National Geodetic Survey, USGS Astrogeology Science Center, and NGA and is intended to serve as a resource for all involved with the Artemis missions, as well as for engineers designing and operating lunar infrastructure.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm11E1","collaboration":"Prepared in cooperation with the National Aeronautics and Space Administration and with support from the National Geodetic Survey","usgsCitation":"McClernan, M.T., Dennis, M.L., Theriot, I.H., Hare, T.M., Archinal, B.A., Ostrach, L.R., Hunter, M.A., Miller, M.J., Beyer, R.A., Annex, A.M., and Lawrence, S.J., 2025, Lunar grid systems, coordinate systems, and map projections for the Artemis missions and lunar surface navigation: U.S. Geological Survey Techniques and Methods, book 11, chap. E1, 308 p., https://doi.org/10.3133/tm11E1.","productDescription":"Report: xi, 308 p.; Software Release","onlineOnly":"Y","ipdsId":"IP-164069","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":482939,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/11/e1/coverthb.jpg"},{"id":482940,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/11/e1/tm11E1.pdf","text":"Report","size":"8.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM11E1 PDF"},{"id":482941,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://astrogeology.usgs.gov/search/map//lunar-map-projections-and-grid-reference-system-for-artemis-astronaut-surface-navigation","text":"Software Release","description":"McClernan, M.T., Dennis, M.L., Theriot, I.H., Hare, T.M., Archinal, B.A., Ostrach, L.R., Hunter, M.A., Miller, M.J., Beyer, R.A., Annex, A.M., and Lawrence, S.J., 2024, Lunar map projections and grid reference system for Artemis astronaut surface navigation: U.S. Geological Survey, Astropedia Lunar and Planetary Cartographic Catalog, https://astrogeology.usgs.gov/search/map//lunar-map-projections-and-grid-reference-system-for-artemis-astronaut-surface-navigation.","linkHelpText":"— Lunar map projections and grid reference system for Artemis astronaut surface navigation"}],"otherGeospatial":"Moon","contact":"Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
Reports of declining insect populations have received widespread media attention, but evidence for declines has been variable across regions and taxonomic groups. Edwards et al. examined trends in the most surveyed taxon: butterflies (see the Perspective by Inouye). Combining data from 35 citizen science programs across the continental US, the authors found declines in overall butterfly abundance over the past 20 years across almost all major regions. Two-thirds of studied species showed declines of more than 10%. Many insects have the potential for rapid population growth and recovery, but habitat restoration, species-specific interventions, and reducing pesticide use are all likely needed to curb population declines.
","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/science.adp4671","usgsCitation":"Edwards, C., Zipkin, E., Henry, E., Haddad, N.M., Forister, M.L., Burls, K., Campbell, S., Crone, E., Diffendorfer, J., Douglas, M.R., Drum, R., Fallon, C.E., Glassberg, J., Grames, E., Hatfield, R.G., Hershcovich, S.V., Hoffman-Black, S., Larsen, E., Leuenberger, W., Linders, M., Longcore, T., Marschalek, D., Michielini, J., Neupane, N., Ries, L., Shapiro, A.M., Swengel, A., Swengel, S., Taron, D., Van Deynze, B., Wiedmann, J., Thogmartin, W.E., and Schultz, C., 2025, Rapid butterfly declines across the United States during the 21st century: Science, v. 387, no. 6738, p. 1090-1094, https://doi.org/10.1126/science.adp4671.","productDescription":"5 p.","startPage":"1090","endPage":"1094","ipdsId":"IP-163739","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences 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