1. Population ecology and biogeography applications often necessitate the transfer of models across spatial and/or temporal dimensions to make predictions outside the bounds of the data used for model fitting. However, ecological data are often spatiotemporally unbalanced such that the spatial or the temporal dimension tends to contain more data than the other. This unbalance frequently leads model transfers to become substitutions, which are predictions to a different dimension than the predictive model was built on. Despite the prevalence of substitutions in ecology, studies validating their performance and their underlying assumptions are scarce.
2. Here, we present a successful case study demonstrating both space-for-time and time-for-space substitutions using emperor penguins (Aptenodytes forsteri) as the focal species. Using abundance-based species distribution models (aSDM) of adult emperor penguins in attendance during spring across 50 colonies, we predict long-term annual fluctuations in fledgling abundance and breeding success at a single colony, Pointe Géologie. Subsequently, we construct statistical models from time series of extended counts on Pointe Géologie to predict average fledgling abundance across 50 colonies.
3. Our analysis reveals that distance to nearest open water (NOW) exhibits the strongest association with both temporal and spatial data. aSDM’s space-for-time substitution performance, as measured by Pearson correlation coefficient was 0.63 and 0.56 when predicting breeding success and fledgling abundance time series, respectively. Linear regression of fledgling abundance on NOW yields similar time-for-space substitution performance when predicting abundance distribution of emperor penguin colonies with a correlation coefficient of 0.58.
4. We posit that such space-time equivalence arises because: 1) emperor penguins colonies conform to their existing fundamental niche; 2) there is not yet any environmental novelty when comparing the spatial vs temporal variation of distance to nearest open water; and 3) models of more specific components of life histories, such as fledgling abundance, rather than occurrence or total population abundance, are more transferable. Identifying these conditions empirically can enhance the qualitative validation of substitutions in cases where direct validation data are lacking.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2656.70025","usgsCitation":"Şen, B., Che-Castaldo, C., LaRue, M., Krumhardt, K., Landrum, L., Holland, M., Lynch, H., Delord, K., Barbraud, C., and Jenouvrier, S., 2025, Temporal and spatial equivalence in demographic responses of emperor penguins (Aptenodytes forsteri) to environmental change: Journal of Animal Ecology, v. 94, no. 5, p. 932-942, https://doi.org/10.1111/1365-2656.70025.","productDescription":"11 p.","startPage":"932","endPage":"942","ipdsId":"IP-170330","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":496436,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.70025","text":"Publisher Index Page"},{"id":493730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, Pointe Géologie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 154.44140675588028,\n -67.88310899484881\n ],\n [\n 154.44140675588028,\n -70.08242540623479\n ],\n [\n 161.81002372233837,\n -70.08242540623479\n ],\n [\n 161.81002372233837,\n -67.88310899484881\n ],\n [\n 154.44140675588028,\n -67.88310899484881\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"94","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Şen, Bilgecan","contributorId":359058,"corporation":false,"usgs":false,"family":"Şen","given":"Bilgecan","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":false,"id":944928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Che-Castaldo, Christian Joseph 0000-0002-7670-2178","orcid":"https://orcid.org/0000-0002-7670-2178","contributorId":347906,"corporation":false,"usgs":true,"family":"Che-Castaldo","given":"Christian Joseph","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":944929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaRue, Michelle A.","contributorId":348627,"corporation":false,"usgs":false,"family":"LaRue","given":"Michelle A.","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":944930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krumhardt, Kristen M.","contributorId":359059,"corporation":false,"usgs":false,"family":"Krumhardt","given":"Kristen M.","affiliations":[{"id":85742,"text":"NSF National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":944931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Landrum, Laura","contributorId":359060,"corporation":false,"usgs":false,"family":"Landrum","given":"Laura","affiliations":[{"id":85742,"text":"NSF National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":944932,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holland, Marika M.","contributorId":359062,"corporation":false,"usgs":false,"family":"Holland","given":"Marika M.","affiliations":[{"id":85742,"text":"NSF National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":944933,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lynch, Heather J.","contributorId":347911,"corporation":false,"usgs":false,"family":"Lynch","given":"Heather J.","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":944934,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Delord, Karine 0000-0001-6720-951X","orcid":"https://orcid.org/0000-0001-6720-951X","contributorId":197702,"corporation":false,"usgs":false,"family":"Delord","given":"Karine","email":"","affiliations":[],"preferred":false,"id":944935,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barbraud, Christophe","contributorId":197701,"corporation":false,"usgs":false,"family":"Barbraud","given":"Christophe","email":"","affiliations":[],"preferred":false,"id":944936,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jenouvrier, Stéphanie","contributorId":359063,"corporation":false,"usgs":false,"family":"Jenouvrier","given":"Stéphanie","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":944937,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70264400,"text":"70264400 - 2025 - MTAB 111, March 2025","interactions":[],"lastModifiedDate":"2025-03-14T14:08:10.828956","indexId":"70264400","displayToPublicDate":"2025-03-13T09:05:42","publicationYear":"2025","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":13451,"text":"Memo to All Banders (MTAB)","active":true,"publicationSubtype":{"id":30}},"title":"MTAB 111, March 2025","docAbstract":"This Memo to All Banders (MTAB 111) was released in March 2025. Subjects in this this memo are 1. The Chief’s Chirp; 2. Alerts – Highly Pathogenic Avian Influenza; 3. Staff updates – celebrating Karen Jone’s remarkable career and retirement, meeting reports and a field trip; 4. News – BandIt end of life! (starting February 1st, 2025 the BBL will no longer be accepting BandIt files), Notes From the Field: Black-bellied Whistling Ducks, Longevity records update, ABA Bird of the Year the Common Loon, EESC signs partnership with Audubon Society, and what 100 years of USGS bird monitoring data tells us about hummingbirds; 5. A note from the permitting shelves – changes to the application process for new master personal or station permits and don’t wait to submit authorization requests; 6. A note from the supply room – best practices for band supply; 7. Data management – banding data submission for birds released from rehabilitation; 8. Frequently asked questions – I had to replace a federal metal band or auxiliary marker, how should I submit this data to the BBL? 9. Banding and encounter highlights; 10. Message to the Flyways; 11. Recent literature; 12. Moments in history; 13. Upcoming events; and 14. Request for information.
","language":"English","publisher":"U.S. Geological Survey","usgsCitation":"Harvey, K., and McKay, J.L., 2025, MTAB 111, March 2025: Memo to All Banders (MTAB), 14 p.","productDescription":"14 p.","ipdsId":"IP-176859","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":483335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":483311,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.usgs.gov/media/files/mtab-111-march-2025"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harvey, Kyra 0000-0003-4781-1874","orcid":"https://orcid.org/0000-0003-4781-1874","contributorId":296250,"corporation":false,"usgs":true,"family":"Harvey","given":"Kyra","email":"","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":930646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKay, Jennifer L. 0000-0002-8893-0231","orcid":"https://orcid.org/0000-0002-8893-0231","contributorId":296562,"corporation":false,"usgs":true,"family":"McKay","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":930751,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70266046,"text":"70266046 - 2025 - Movements and habitat use of Silver Carp in the Arkansas and White rivers","interactions":[],"lastModifiedDate":"2025-04-24T14:57:58.143549","indexId":"70266046","displayToPublicDate":"2025-03-13T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Movements and habitat use of Silver Carp in the Arkansas and White rivers","docAbstract":"Silver Carp Hypophthalmichthys molitrix is an invasive species found throughout the Mississippi River basin. Efforts have been made to control Silver Carp populations through removal programs and movement barrier implementation. Up to date information on diel, seasonal, and annual movements and habitat use by Silver Carp will benefit these efforts. Studies of Silver Carp movement are prevalent in the upper Mississippi River, Ohio River, and tributaries, but rare in tributaries of the lower Mississippi River. Between June 2021 and May 2022, we quantified average movement rates and residency periods of 48 Silver Carp in the free-flowing lower White River and lock-and-dam fragmented lower Arkansas River using passive acoustic telemetry arrays and internal implant acoustic transmitters. We also manually tracked Silver Carp in the two rivers during the four seasons to estimate diel movement rates and use of different habitats. On an annual scale, Silver Carp in the White River moved at faster rates than Silver Carp in the Arkansas River and were recorded more times by acoustic receivers. Diel movement rates varied by season in both rivers but were low overall. Silver Carp used lentic habitats more often than lotic habitats. Overall, results suggest the numerous locks and dams of the McClellan-Kerr Arkansas River Navigation System may limit large-scale, annual movement of Silver Carp in the Arkansas River compared to the White River. Low hourly diel movement rates and high occupancy of lentic habitats also should enable effective harvest of Silver Carp using active gears in those lentic habitats.
","language":"English","publisher":"Allen Press","doi":"10.3996/jfwm-23-066","usgsCitation":"Althoff, A., Kindschuh, J., Lochmann, S., Owens, D., Spurgeon, J.J., and Stevens, J., 2025, Movements and habitat use of Silver Carp in the Arkansas and White rivers: Journal of Fish and Wildlife Management, v. 15, no. 2, p. 493-509, https://doi.org/10.3996/jfwm-23-066.","productDescription":"17 p.","startPage":"493","endPage":"509","ipdsId":"IP-155044","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":490100,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-23-066","text":"Publisher Index Page"},{"id":484978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Arkansas River, White 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Bluff","active":true,"usgs":false}],"preferred":false,"id":934448,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Owens, Derek K.","contributorId":353748,"corporation":false,"usgs":false,"family":"Owens","given":"Derek K.","affiliations":[{"id":81661,"text":"University of Arkansas at Pine Bluff","active":true,"usgs":false}],"preferred":false,"id":934449,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spurgeon, Jonathan J. 0000-0002-6888-5867","orcid":"https://orcid.org/0000-0002-6888-5867","contributorId":304259,"corporation":false,"usgs":true,"family":"Spurgeon","given":"Jonathan","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":934450,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stevens, Jeffery N.","contributorId":353752,"corporation":false,"usgs":false,"family":"Stevens","given":"Jeffery N.","affiliations":[{"id":81661,"text":"University of Arkansas at Pine Bluff","active":true,"usgs":false}],"preferred":false,"id":934451,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70264367,"text":"ofr20211104F - 2025 - Potential effects of sea level rise and high tide flooding on Laterallus jamaicensis jamaicensis (eastern black rail) coastal breeding areas","interactions":[{"subject":{"id":70264367,"text":"ofr20211104F - 2025 - Potential effects of sea level rise and high tide flooding on Laterallus jamaicensis jamaicensis (eastern black rail) coastal breeding areas","indexId":"ofr20211104F","publicationYear":"2025","noYear":false,"chapter":"F","displayTitle":"Potential Effects of Sea Level Rise and High Tide Flooding on Laterallus jamaicensis jamaicensis (Eastern Black Rail) Coastal Breeding Areas","title":"Potential effects of sea level rise and high tide flooding on Laterallus jamaicensis jamaicensis (eastern black rail) coastal breeding areas"},"predicate":"IS_PART_OF","object":{"id":70228323,"text":"ofr20211104 - 2022 - Effects of climate change on fish and wildlife species in the United States","indexId":"ofr20211104","publicationYear":"2022","noYear":false,"title":"Effects of climate change on fish and wildlife species in the United States"},"id":1}],"isPartOf":{"id":70228323,"text":"ofr20211104 - 2022 - Effects of climate change on fish and wildlife species in the United States","indexId":"ofr20211104","publicationYear":"2022","noYear":false,"title":"Effects of climate change on fish and wildlife species in the United States"},"lastModifiedDate":"2025-07-23T16:56:40.604898","indexId":"ofr20211104F","displayToPublicDate":"2025-03-12T15:03:12","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1104","chapter":"F","displayTitle":"Potential Effects of Sea Level Rise and High Tide Flooding on Laterallus jamaicensis jamaicensis (Eastern Black Rail) Coastal Breeding Areas","title":"Potential effects of sea level rise and high tide flooding on Laterallus jamaicensis jamaicensis (eastern black rail) coastal breeding areas","docAbstract":"Laterallus jamaicensis jamaicensis (eastern black rails; Gmelin, 1789) are facing increasing risk from flooding in coastal breeding habitats because of rising sea levels combined with standard high tide flooding. In this report, we examine regional differences in relative rates of sea level rise, days in the breeding season above historical high tide flooding thresholds, future inundation of current (2021) emergent wetlands, and potential marsh resiliency for the breeding distribution of the eastern black rail across the Atlantic and U.S. Gulf coasts. By midcentury (2050), two sea level rise scenarios (intermediate low and intermediate) indicate that areas analyzed in Texas and the Mid-Atlantic will experience at least minor flood levels for more than half of the breeding season. By the end of the century (2100), all tidal gages in the Atlantic and U.S. Gulf coasts are projected to experience at least moderate flood levels for most of the current (April–September) eastern black rail breeding season. In some areas like New Jersey, this translates to inundation for most of the emergent wetlands in the representative parishes and counties analyzed in this report. In other parts of the coastal distribution, estimates of increases in inundation are lower or more variable, stemming from differences in the elevation of existing emergent marsh, especially at the herbaceous wetland/woody wetland transition zone. Sea level rise and tidal flooding are not projected to pose an equal risk across the coastal distribution of the eastern black rail, leading to variation in risk of nest loss because of flooding. The degree to which these wetlands and birds will adapt to changing sea level and salinity depends on a range of factors including future expansion of developed areas and the ability of marsh areas to move inland. Restoration and active management of coastal wetland areas may be necessary to maintain appropriate breeding habitat.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211104F","usgsCitation":"Nikiel, C.A., and Lyons, M.P., 2025, Potential effects of sea level rise and high tide flooding on Laterallus jamaicensis jamaicensis (eastern black rail) coastal breeding areas: U.S. Geological Survey Open-File Report 2021–1104–F, 40 p., https://doi.org/10.3133/ofr20211104F.","productDescription":"vii, 40 p.","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-172341","costCenters":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":483246,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211104F/full"},{"id":483244,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1104/f/ofr20211104f.XML"},{"id":483243,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1104/f/ofr20211104f.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1104-F"},{"id":483242,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1104/f/coverthb.jpg"},{"id":483245,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1104/f/images/"},{"id":492780,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118482.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Atlantic Coast, Gulf Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -66.73369411465748,\n 44.87861692762931\n ],\n [\n -67.9395715369188,\n 45.91302389167819\n ],\n [\n -68.52891205677287,\n 46.14233382856975\n ],\n [\n -69.66609739851674,\n 44.904840367756236\n ],\n [\n -71.8455845133013,\n 43.01632555370077\n ],\n [\n -75.76042364090121,\n 40.73258218965182\n ],\n [\n -77.41422284991526,\n 39.32302567933269\n ],\n [\n -77.11953264135055,\n 36.58955309284522\n ],\n [\n -79.0153316043617,\n 34.430624116007294\n ],\n [\n -82.3380440342791,\n 31.342877305678\n ],\n [\n -87.14213042595998,\n 31.473505392669267\n ],\n [\n -87.74548189802837,\n 32.39195075385649\n ],\n [\n -89.00813665013129,\n 32.354083649747\n ],\n [\n -89.30755056658234,\n 31.271920212222028\n ],\n [\n -92.00443786768639,\n 31.222304379727817\n ],\n [\n -95.98918412828937,\n 30.505582509882984\n ],\n [\n -98.19210772787893,\n 28.060885389466677\n ],\n [\n -98.10578570219339,\n 26.094479941263742\n ],\n [\n -97.05626247225148,\n 25.880720528127156\n ],\n [\n -97.21103649173618,\n 27.232424454623654\n ],\n [\n -95.67794712232511,\n 28.598718054492764\n ],\n [\n -93.37262411904577,\n 29.53246193068931\n ],\n [\n -90.09201823404798,\n 28.868540112379208\n ],\n [\n -88.84955647397418,\n 28.787680093703898\n ],\n [\n -88.58294319870708,\n 29.755309328858473\n ],\n [\n -86.26626920949336,\n 30.023219777079703\n ],\n [\n -84.98796116952035,\n 29.29748111241001\n ],\n [\n -83.97817016398578,\n 29.677155423717906\n ],\n [\n -82.92684471060598,\n 28.711279338050616\n ],\n [\n -83.33453111961292,\n 28.007674975959418\n ],\n [\n -81.38398690858428,\n 24.942184191892167\n ],\n [\n -81.48743115456318,\n 24.146104924998653\n ],\n [\n -79.34128084180263,\n 25.993764942081356\n ],\n [\n -81.14405051637162,\n 30.851402909345737\n ],\n [\n -74.95193417969506,\n 35.431852837245344\n ],\n [\n -75.10789103469754,\n 37.38614632113877\n ],\n [\n -73.3440560833726,\n 40.10806605773732\n ],\n [\n -69.15888557248354,\n 41.691566830140545\n ],\n [\n -70.25945555475435,\n 43.01474979449651\n ],\n [\n -66.73369411465748,\n 44.87861692762931\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Midwest Climate Adaptation Science Center
U.S. Geological Survey
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Drought and its effect on streamflow are important to understand because of the potential to adversely affect water supply, agricultural production, and ecological conditions. The Red River of the North Basin in north-central United States and central Canada is susceptible to dry conditions. During an extended drought, streamflow conditions in the Red River of the North may become inadequate to support existing water supply needs in the basin for agriculture, industry, human use, and aquatic life. To understand potential future low-streamflow conditions in the Red River of the North Basin, the U.S. Geological Survey, in cooperation with the International Joint Commission, North Dakota Department of Water Resources, Red River Joint Water Resource District, and Red River Watershed Management Board, developed a water-balance model of the Red River of the North Basin upstream from Emerson, Manitoba, Canada, and coupled the model with stochastic weather inputs to simulate possible future low-streamflow conditions.
Historical changes in low-streamflow conditions were characterized across the Red River of the North Basin using multiple change-point analysis for 12 streamgages. Across these stations, significant change-point years in 1943 and 1994 marked increases in the magnitude of low-streamflow conditions. During 1920–2015, conversion of primary land (not affected by human use) to agricultural and secondary land was followed by a conversion from smalls grains to corn and soybeans as the dominant crop type. From land-use analysis, 1940–2000 was determined to have relatively stable land use and therefore was used as the calibration period for the water-balance model.
A deterministic water-balance model was developed for the Red River of the North Basin upstream from Emerson, Manitoba. The water-balance model was calibrated with data from 37 U.S. Geological Survey streamgages for 1940–2000 and verified using data for 2001–15. The calibrated water-balance model simulated streamflow distributions that mirrored the seasonal patterns of the observed mean monthly streamflow and the standard deviation of the monthly streamflow data, especially during the fall and winter months when streamflow was lowest. For the verification period, during the low-streamflow months of December through January, the difference between simulated and observed data was similar to the calibration comparison and successfully reproduced seasonal trends in the distribution of streamflow, even when using weather data that were outside the calibration period.
To determine the future risk of low-streamflow conditions in the Red River of the North Basin, a block-bootstrap method was used to generate multiple possible future climates. These stochastically generated weather time series were then input to a water-balance model to simulate a distribution of possible streamflows. Three sets of experiments were performed, with each experiment containing a set of scenarios. The first set of experiments from the stochastic streamflow model were designed to investigate how changes in reservoir management would affect the distribution of low streamflow. Relative to scenario 1 (present-day [2023] reservoir operation), scenario 2 (no reservoir operation) shifted the low-streamflow frequency curves downward, reducing the annual minimum monthly streamflow for the Emerson subbasin. Subbasins were defined by the contributing area upstream from a selected streamgage station. Relative to scenario 1, scenario 3 (regulated streamflow with an increased reservoir capacity of 10 percent) shifted the low-streamflow frequency curves upward for the Emerson subbasin. The magnitude of this upward shift, caused by increased reservoir capacity, was lower than the magnitude of the shift caused by the absence of the reservoirs, which indicates that the streamflow was most affected when the reservoirs were first constructed.
The second set of experiments from the stochastic streamflow model included two scenarios that were performed to better understand how the Red River of the North Basin responds to long periods of low or high precipitation. The results indicate that the model consistently overestimated streamflow, but the relative change between a wet and dry climate state of simulated streamflow distribution reasonably matched the relative change of historical streamflow. Across the subbasins, the model was most accurate for low-streamflow conditions associated with nonexceedance probabilities between 20 and 40 percent.
The third set of experiments from the stochastic streamflow model were done to investigate low-streamflow response across the basin to several drought events. Low-end streamflow was reduced when the basin was exposed to a drought, and the magnitude of the reduction increased with longer or more intense droughts. Compared to the low-intensity drought scenarios, the range of percent reductions (as indicated by the interquartile range) was larger for the high-intensity drought scenarios for all subbasins, and the subbasins of Grand Forks and Emerson had a smaller range of reductions compared to the other three subbasins. The larger drainage area—combined with the large contribution of the Red Lake River and several other Minnesota tributaries that generally experience wetter climate conditions—upstream from the Emerson and Grand Forks subbasins may contribute to the smaller range in reductions under the high intensity scenarios. Comparison of the percent reduction in low-end streamflow among subbasins also indicated that the effects of drought duration and intensity could be cumulative. Combining factors of time and intensity produced a larger reduction in streamflow than when each effect was isolated. The array of drought scenarios can be used to determine how a subbasin would respond to multiple possible future conditions. Based on climate predictions, the drought scenario that best matches a future anticipated drought scenario can be used to estimate a low streamflow response for a given subbasin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255002","collaboration":"Prepared in cooperation with the International Joint Commission, North Dakota Department of Water Resources, Red River Joint Water Resource District, and Red River Watershed Management Board","usgsCitation":"Redoloza, F.S., Glas, R.L., Nustad, R.A., and Ryberg, K.R., 2025, Evaluating drought risk of the Red River of the North Basin using historical and stochastic streamflow upstream from Emerson, Manitoba: U.S. Geological Survey Scientific Investigations Report 2025–5002, 58 p., https://doi.org/10.3133/sir20255002.","productDescription":"Report: viii, 58 p.; Data Release; Dataset","numberOfPages":"70","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-160450","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":492779,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118481.htm","linkFileType":{"id":5,"text":"html"}},{"id":483206,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13XEN8U","text":"USGS data release","linkHelpText":"Red River of the North low flow water-balance model and supporting data"},{"id":483203,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5002/sir20255002.XML"},{"id":483202,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5002/sir20255002.pdf","text":"Report","size":"9.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5002"},{"id":483201,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5002/coverthb.jpg"},{"id":483204,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5002/images/"},{"id":483207,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":483205,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255002/full"}],"country":"Canada, United States","state":"Manitoba, Minnesota, North Dakota","otherGeospatial":"Red River of the North Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97.08881710576394,\n 49.037592614274644\n ],\n [\n -97.61189514667993,\n 49.237246321777064\n ],\n [\n -97.98430773681044,\n 49.25792746144549\n ],\n [\n -98.47156466708684,\n 49.30311814027007\n ],\n [\n -98.18869515177104,\n 48.806510092341696\n ],\n [\n -98.92510212635796,\n 48.563256003263746\n ],\n [\n -98.41426650704827,\n 48.10818045779425\n ],\n [\n -97.49283622534884,\n 48.05240253638604\n ],\n [\n -97.3523048621935,\n 47.017146908752025\n ],\n [\n -97.10429716720503,\n 45.72316825195222\n ],\n [\n -95.52291599413297,\n 45.59412827523792\n ],\n [\n -94.77240339220764,\n 46.995377381657505\n ],\n [\n -94.76454577568065,\n 47.45566932791883\n ],\n [\n -93.68493211560182,\n 47.83688445747143\n ],\n [\n -94.11770692662546,\n 48.33322840096503\n ],\n [\n -95.73784376997673,\n 48.92757937919353\n ],\n [\n -97.08881710576394,\n 49.037592614274644\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
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This report addresses system characterization of the Environmental Mapping and Analysis Program hyperspectral sensor by the DLR (German Aerospace Center, ground segment project management), GFZ (Deutsches Geoforschungszentrum, science lead) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the EnMAP hyperspectral sensor; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), and radiometric performances of the EnMAP hyperspectral sensor. Results of these analyses indicate that the Environmental Mapping and Analysis Program has a band-to-band geometric performance in the range of −0.135 to 0.15 pixel, geometric performance relative to the Operational Land Imager in the range of −27.716 meters (−0.92 pixel) to 32.892 meters (1.09 pixels) offset in comparison to Landsat 8 Operational Land Imager, offset of a radiometric comparison in the range of −0.012 to 0.020, slope of a radiometric comparison in the range of 0.947 to 1.031.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030S","usgsCitation":"Kim, M., Park, S., and Anderson, C., 2025, System characterization report on the Environmental Mapping and Analysis Program (EnMAP), chap. S of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors:U.S. Geological Survey Open-File Report 2021–1030, 28 p., https://doi.org/10.3133/ofr20211030S.","productDescription":"vi, 28 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-167720","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":483138,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/s/coverthb.jpg"},{"id":483141,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/s/images/"},{"id":483142,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211030S/full"},{"id":483139,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/s/ofr20211030s.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030–S"},{"id":483140,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/s/ofr20211030s.XML"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
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1. Patterns of migratory connectivity are increasingly used to understand and manage threats throughout the annual cycle of migratory species. Strong migratory connectivity refers to when individuals from different populations remain spatially separated across the annual cycle, which may expose populations to unique sets of threats and conditions that cause differential population trends. However, the populations or groups used for species’ management are often defined a priori based on expert knowledge and/or management units, which may mask important population segregation and obscure differential population trends and their drivers.
2. We compared three approaches to defining management groups of a declining shorebird, the long-billed curlew (Numenius americanus), for annual cycle management: by expert-opinion, according to management flyways, and with unsupervised clustering of satellite tracking data that maximizes the strength of migratory connectivity.
3. Despite the curlews having a continuous breeding range and a pattern of parallel migration, all three approaches identified groups with different population trends, movement behaviours and habitat selection across the annual cycle, suggesting these are meaningful ecological groups. The expert and clustering approaches resulted in similar group structure, strong estimates of migratory connectivity (measured as MC = 0.64 across seasons), movement behaviour and habitat selection; however, the expert approach identified an additional divide between the easternmost grouping, which revealed strongly negative population trends in the group occupying the Chihuahuan desert during the stationary nonbreeding season. In contrast, the flyway delineation resulted in weaker estimates of migratory connectivity, marginal differences in population trends and less between-group differences in movement behaviour and habitat selection.
4. Synthesis and applications. Using measurements of migratory connectivity in concert with expert opinion can define ecologically distinct groups for wildlife management that differ in the environmental conditions they experience across seasons of the annual cycle, which is a key component for understanding and reversing declines of migratory species.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.14885","usgsCitation":"Knight, E., Carlisle, J.D., Boyce, A., Bradley, D., Cimprich, P., Coates, S., Dinsmore, S., Gregory, C., Jorgensen, J., Kelly, J., Newstead, D., Olalla, A., Powell, L., Scarpignato, A., Tibbitts, T., Warnock, N., Wehtje, W., Marra, P., and Harrison, A., 2025, Delineating ecologically-distinct groups for annual cycle management of a declining shorebird: Journal of Applied Ecology, v. 62, no. 5, p. 1152-1165, https://doi.org/10.1111/1365-2664.14885.","productDescription":"14 p.","startPage":"1152","endPage":"1165","ipdsId":"IP-162500","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":488308,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.14885","text":"Publisher Index Page"},{"id":483352,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.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 -130.61742203243398,\n 55.06220192129385\n ],\n [\n -125.78642691212771,\n 37.96714257094378\n ],\n [\n -112.79332255145798,\n 19.6607075263222\n ],\n [\n -96.55986873218092,\n 19.42104945978697\n ],\n [\n -98.16768517783267,\n 27.617354166317778\n ],\n [\n -93.88189635105832,\n 30.28935268993333\n ],\n [\n -80.97632580516836,\n 30.315920278541377\n ],\n [\n -95.50678240297971,\n 43.55365071845705\n ],\n [\n -100.13328021048312,\n 54.69226523920972\n ],\n [\n -130.61742203243398,\n 55.06220192129385\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"62","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-03-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Knight, Elly C.","contributorId":352283,"corporation":false,"usgs":false,"family":"Knight","given":"Elly C.","affiliations":[{"id":84154,"text":"Migratory Bird Center, Smithsonian’s National Zoo and Conservation Biology Institute, Washington, DC, USA","active":true,"usgs":false}],"preferred":false,"id":930653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlisle, J. 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The U.S. Geological Survey has a new decadal-scale coastal change assessment product that synthesizes nearly two dozen coastal datasets. A supervised machine-learning framework is used to combine existing datasets that describe the landscape and the hazards that affect it to determine the coastal change likelihood (CCL) in the coming decade at a resolution of 10 m per pixel for the NE United States from Maine to Virginia. Here, results from a series of statistical tests conducted on source data, the supervised classification, and the CCL outcomes as compared with historical land-cover change are presented. The overall accuracy of the aggregated land-cover dataset that serves as the foundation to which other source datasets are appended is 94%. The supervised learning classification that determines the final CCL output has an overall accuracy of 92%. The CCL predictions of high expected coastal change were consistent with 95% of the coastal and low-elevation landscape change in the last 20 years, as recorded by the Coastal Change Analysis Program land-cover change atlas. Results suggest that CCL provides accurate estimates of coastal landscape change in the next decade that are consistent with recent observed change. Additionally, best practices for applying CCL for planning purposes are outlined, and citing limitations, knowledge gaps, and opportunities for improved accuracy and further investigation are considered.
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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.
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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":432,"text":"National Minerals Information Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science 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":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":432,"text":"National Minerals Information Center","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":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","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. We found visitor use to have a consistently negative effect on occupancy and persistence of amphibians in RMNP, and that all species are more likely to occupy catchments with more complex habitat and a higher proportion of wetlands. While these results are sobering, they also provide a way forward where mitigation efforts can target identified drivers of change.
","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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