Spawning phenology and associated migrations of fishes are often regulated by factors such as temperature and stream discharge, but flow regulation of mainstem rivers coupled with climate change might disrupt these cues and affect fitness. Flannelmouth sucker (Catostomus latipinnis) persisting in heavily modified river networks are known to spawn in tributaries that might provide better spawning habitat than neighboring mainstem rivers subject to habitat degradation (e.g., embedded sediments, altered thermal regimes, and disconnected floodplains). Passive integrative transponder (PIT) tag data and radio telemetry were used to quantify the timing and duration of flannelmouth sucker tributary spawning migrations in relation to environmental cues in McElmo Creek, a tributary to the San Juan River in the American Southwest. We also tested the extent of the tributary migration and assessed mainstem movements prior to and following tributary migrations. Additionally, multi-year datasets of PIT detections from other tributaries in the Colorado River basin were used to quantify interannual and cross-site variation in the timing of flannelmouth sucker spawning migrations in relation to environmental cues. The arrival and residence times of fish spawning in McElmo Creek varied among years with earlier migration and a three-week increase in residence time in relatively wet years compared to drier years. Classification tree analysis suggested a combination of discharge and temperature determined arrival timing. Of fish PIT tagged in the fall, 56% tagged within 10 km of McElmo Creek spawned in the tributary the following spring, as did 60% of radio-tagged fish, with a decline in its use corresponding to increased distance of tagging location. A broader analysis of four tributaries in the Colorado River basin, including McElmo Creek, found photoperiod and temperature of tributary and mainstem rivers were the most important variables in determining migration timing, but tributary and mainstem discharge also aided in classification success. The largest tributary, the Little Colorado River, had more residential fish or fish that stayed for longer periods (median = 30 days), while McElmo Creek fish stayed an average of just 10 days in 2022. Our results generally suggest that higher discharge, across years or across sites, results in extended use of tributaries by flannelmouth suckers. Conservation actions that limit water extraction and maintain natural flow regimes in tributaries, while maintaining open connection with mainstem rivers may benefit migratory species including flannelmouth suckers.
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Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
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Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 3.8 billion barrels of oil and 20.7 trillion cubic feet of gas offshore of Morocco.
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Box 25046, MS-939
Denver, CO 80225-0046
We investigate the utility of towed underwater camera systems with tightly coupled Global Navigation Satellite System (GNSS) positions to provide reef-scale bathymetric models with millimeter to centimeter resolutions and accuracies with Structure-from-Motion (SfM) photogrammetry. Successful development of these techniques would allow for detailed assessments of benthic conditions, including the accretion and erosion of reefs and adjacent sediment deposits, without the need for ground control points. We use a multi-camera system towed by a small vessel to map over 70,000 m2 of complex shallow (2–8 m water depth) bedrock reef, boulder fields, and fine (sand and gravel) sediments of Lake Tahoe, California. We find that multiple synchronized cameras increase overall mapping coverage and allow for wider survey line spacing. The accuracy of the techniques was sub-millimeter for local length measurements less than a meter, and the bathymetric reproducibility was found to scale with the accuracy of GNSS (3–5 cm), although this could be improved to sub-centimeter with the inclusion of one or more co-registered, but unsurveyed, control points. For future applications, we provide guidance on conducting field operations, correcting underwater image color, and optimizing the SfM workflows. We conclude that a GNSS-coupled underwater camera array is a promising technique to map shallow reefs at high accuracy and resolution without ground control.
","language":"English","publisher":"MDPI","doi":"10.3390/rs15153727","usgsCitation":"Hatcher, G., Warrick, J.A., Kranenburg, C.J., and Ritchie, A.C., 2023, Accurate maps of reef-scale bathymetry with synchronized underwater cameras and GNSS: Remote Sensing, v. 15, no. 15, 3727, 21 p., https://doi.org/10.3390/rs15153727.","productDescription":"3727, 21 p.","ipdsId":"IP-153460","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":442635,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs15153727","text":"Publisher Index Page"},{"id":419399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Lake Tahoe","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.0917,\n 39.1875\n ],\n [\n -120.1047,\n 39.1875\n ],\n [\n -120.1047,\n 39.175\n ],\n [\n -120.0917,\n 39.175\n ],\n [\n -120.0917,\n 39.1875\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"15","noUsgsAuthors":false,"publicationDate":"2023-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Hatcher, Gerald A. 0000-0001-7705-1509","orcid":"https://orcid.org/0000-0001-7705-1509","contributorId":67586,"corporation":false,"usgs":true,"family":"Hatcher","given":"Gerald A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":879227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":879228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kranenburg, Christine J. 0000-0002-2955-0167 ckranenburg@usgs.gov","orcid":"https://orcid.org/0000-0002-2955-0167","contributorId":169234,"corporation":false,"usgs":true,"family":"Kranenburg","given":"Christine","email":"ckranenburg@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":879229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ritchie, Andrew C. aritchie@usgs.gov","contributorId":4984,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew","email":"aritchie@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":879230,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70247391,"text":"70247391 - 2023 - Movement and behavioral states of common carp (Cyprinus carpio) in response to a behavioral deterrent in a navigational lock","interactions":[],"lastModifiedDate":"2023-08-02T14:53:36.421758","indexId":"70247391","displayToPublicDate":"2023-07-26T09:43:09","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Movement and behavioral states of common carp (Cyprinus carpio) in response to a behavioral deterrent in a navigational lock","title":"Movement and behavioral states of common carp (Cyprinus carpio) in response to a behavioral deterrent in a navigational lock","docAbstract":"Freshwater ecosystems are some of the most affected by biological invasions due, in part, to the introduction of invasive carp worldwide. Where carp have become established, management programs often seek to limit further range expansion into new areas by reducing their movement through interconnected rivers and waterways. Lock and dams are important locations for non-physical deterrents, such as carbon dioxide (CO2), to reduce unwanted fish passage without disrupting human use. The purpose of this study was to evaluate the behavioral responses of common carp (Cyprinus carpio) to non-physical deterrents within a navigation structure on the Fox River, Wisconsin. Acoustic telemetry combined with hidden Markov models (HMMs) was used to analyze variation in carp responses to treatments. Outcomes may inform CO2 effectiveness at preventing invasive carp movement through movement pinch-points.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s40462-023-00396-z","usgsCitation":"Raboin, M.J., Plumb, J., Sholtis, M.D., Smith, D., Jackson, P.R., Rivera, J., Suski, C., and Cupp, A.R., 2023, Movement and behavioral states of common carp (Cyprinus carpio) in response to a behavioral deterrent in a navigational lock: Movement Ecology, v. 11, 42, 16 p., https://doi.org/10.1186/s40462-023-00396-z.","productDescription":"42, 16 p.","ipdsId":"IP-148214","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":442636,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-023-00396-z","text":"Publisher Index Page"},{"id":435240,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B8SRMW","text":"USGS data release","linkHelpText":"Acoustic Telemetry Evaluation of Invasive Carp in Kaukauna, Wisconsin (Summer 2019)"},{"id":419500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Fox River, Kaukauna locks","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.2903788929823,\n 44.27679879835844\n ],\n [\n -88.30570324899331,\n 44.27679879835844\n ],\n [\n -88.30570324899331,\n 44.270866037921394\n ],\n [\n -88.2903788929823,\n 44.270866037921394\n ],\n [\n -88.2903788929823,\n 44.27679879835844\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Raboin, Maggie Jo 0000-0002-1475-7253","orcid":"https://orcid.org/0000-0002-1475-7253","contributorId":317839,"corporation":false,"usgs":true,"family":"Raboin","given":"Maggie","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":879428,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":223236,"corporation":false,"usgs":true,"family":"Plumb","given":"John","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":879429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sholtis, Matthew D. 0000-0003-1904-8250","orcid":"https://orcid.org/0000-0003-1904-8250","contributorId":317840,"corporation":false,"usgs":true,"family":"Sholtis","given":"Matthew","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":879430,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, David","contributorId":261251,"corporation":false,"usgs":false,"family":"Smith","given":"David","affiliations":[{"id":52784,"text":"U.S. Department of Agriculture, Economic Research Service","active":true,"usgs":false}],"preferred":false,"id":879431,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879432,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rivera, Jose 0000-0003-3756-6860 jrivera@usgs.gov","orcid":"https://orcid.org/0000-0003-3756-6860","contributorId":201064,"corporation":false,"usgs":true,"family":"Rivera","given":"Jose","email":"jrivera@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":879433,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Suski, C. D.","contributorId":190151,"corporation":false,"usgs":false,"family":"Suski","given":"C.","middleInitial":"D.","affiliations":[],"preferred":false,"id":879434,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":879435,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70249842,"text":"70249842 - 2023 - A one-dimensional volcanic plume model for predicting ash aggregation","interactions":[],"lastModifiedDate":"2023-11-02T14:38:16.632909","indexId":"70249842","displayToPublicDate":"2023-07-26T09:34:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"A one-dimensional volcanic plume model for predicting ash aggregation","docAbstract":"During explosive volcanic eruptions, volcanic ash is ejected into the atmosphere, impacting aircraft safety and downwind communities. These volcanic clouds tend to be dominated by fine ash (<63 μm in diameter), permitting transport over hundreds to thousands of kilometers. However, field observations show that much of this fine ash aggregates into clusters or pellets with faster settling velocities than individual particles. Models of ash transport and deposition require an understanding of aggregation processes, which depend on factors like moisture content and local particle collision rates. In this study, we develop a Plume Model for Aggregate Prediction, a one-dimensional (1D) volcanic plume model that predicts the plume rise height, concentration of water phases, and size distribution of resulting ash aggregates from a set of eruption source parameters. The plume model uses a control volume approach to solve mass, momentum, and energy equations along the direction of the plume axis. The aggregation equation is solved using a fixed pivot technique and incorporates a sticking efficiency model developed from analog laboratory experiments of particle aggregation within a novel turbulence tower. When applied to the 2009 eruption of Redoubt Volcano, Alaska, the 1D model predicts that the majority of the plume is over-saturated with water, leading to a high rate of aggregation. Although the mean grain size of the computed Redoubt aggregates is larger than the measured deposits, with a peak at 1 mm rather than 500 μm, the present results provide a quantitative estimate for the magnitude of aggregation in an eruption.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JB027002","usgsCitation":"Hoffman, D.W., Mastin, L.G., Van Eaton, A.R., Solovitz, S.A., Cal, R., and Eaton, J.K., 2023, A one-dimensional volcanic plume model for predicting ash aggregation: JGR Solid Earth, v. 128, no. 9, e2023JB027002, 26 p., https://doi.org/10.1029/2023JB027002.","productDescription":"e2023JB027002, 26 p.","ipdsId":"IP-151689","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":442639,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jb027002","text":"Publisher Index Page"},{"id":435241,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UFXP7T","text":"USGS data release","linkHelpText":"plumeria PMAP software release 1.0.3"},{"id":422335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"128","issue":"9","noUsgsAuthors":false,"publicationDate":"2023-08-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Hoffman, Davis W. 0000-0002-2621-0570","orcid":"https://orcid.org/0000-0002-2621-0570","contributorId":331319,"corporation":false,"usgs":false,"family":"Hoffman","given":"Davis","email":"","middleInitial":"W.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":887338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mastin, Larry G. 0000-0002-4795-1992","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":265985,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":887339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":887340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Solovitz, Stephen A. 0000-0001-7019-2958","orcid":"https://orcid.org/0000-0001-7019-2958","contributorId":257659,"corporation":false,"usgs":false,"family":"Solovitz","given":"Stephen","email":"","middleInitial":"A.","affiliations":[{"id":52077,"text":"Washington State University, Vancouver","active":true,"usgs":false}],"preferred":false,"id":887341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cal, Raul B.","contributorId":257658,"corporation":false,"usgs":false,"family":"Cal","given":"Raul B.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":887342,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eaton, John K. 0000-0001-6241-4266","orcid":"https://orcid.org/0000-0001-6241-4266","contributorId":331320,"corporation":false,"usgs":false,"family":"Eaton","given":"John","email":"","middleInitial":"K.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":887343,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70247431,"text":"70247431 - 2023 - Soil salinity and water level interact to generate tipping points in low salinity tidal wetlands responding to climate change","interactions":[],"lastModifiedDate":"2023-10-23T16:01:53.14607","indexId":"70247431","displayToPublicDate":"2023-07-26T07:21:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Soil salinity and water level interact to generate tipping points in low salinity tidal wetlands responding to climate change","docAbstract":"Low salinity tidal wetlands (LSTW) are vulnerable to sea level rise and saltwater intrusion, thus their carbon sequestration capacity is threatened. However, the thresholds of rapid changes in carbon dynamics and biogeochemical processes in LSTW due to changes in hydroperiod and salinity regime remain unclear. In this study, we examined the effects of soil porewater salinity and water level on changes in net primary productivity (NPP) and greenhouse gas fluxes [GHG: methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2)] in LSTW using a wetland biogeochemistry model, Tidal Freshwater Wetland Denitrification and Decomposition (TFW-DNDC). TFW-DNDC was run with a series of combinations of soil salinities (0.1, 0.5, 1, 2, 4, 6, 8, 10 psu) and water levels relative to soil surface (-30, -20, -10, -5, 0, 5, 10, 20, 30 cm) for tidal forest and oligohaline marsh sites along the Savannah River and Waccamaw River, USA. Our results indicate that soil salinity and water level have antagonistic effects on CH4 emissions and synergistic effects on CO2 release. A soil salinity of 2-3 psu is the tipping point for the ecosystem level functional changes (e.g., NPP and CH4 emissions) in LSTW. There are negative and nonlinear responses (NPP and CH4 emission) to soil salinity. Furthermore, a soil water level from 10 cm below to 10 cm above the surface is a critical range in which biogeochemical processes respond strongly to hydrological changes. The presence of nonlinear tipping points in LSTW has large implications for understanding and predicting the effects of climate change on coastal wetland blue carbon storage and ecosystem dynamics.
Brownlee Reservoir is a mercury (Hg)-impaired hydroelectric reservoir that exhibits dynamic hydrological and geochemical conditions and is located within the Hells Canyon Complex in Idaho, USA. Methylmercury (MeHg) contamination in fish is a concern in the reservoir. While MeHg production has historically been attributed to sulfate-reducing bacteria and methanogenic archaea, microorganisms carrying the hgcA gene are taxonomically and metabolically diverse and the major biogeochemical cycles driving mercury (Hg) methylation are not well understood. In this study, Hg speciation and redox-active compounds were measured throughout Brownlee Reservoir across the stratified period in four consecutive years (2016–2019) to identify the location where and redox conditions under which MeHg is produced. Metagenomic sequencing was performed on a subset of samples to characterize the microbial community with hgcA and identify possible links between biogeochemical cycles and MeHg production. Biogeochemical profiles suggested in situ water column Hg methylation was the major source of MeHg. These profiles, combined with genome-resolved metagenomics focused on hgcA-carrying microbes, indicated that MeHg production occurs in this system under nitrate- or manganese-reducing conditions, which were previously thought to preclude Hg-methylation. Using this multidisciplinary approach, we identified the cascading effects of interannual variability in hydrology on the redox status, microbial metabolic strategies, abundance and metabolic diversity of Hg methylators, and ultimately MeHg concentrations throughout the reservoir. This work expands the known conditions conducive to producing MeHg and suggests that the Hg-methylation mitigation efforts by nitrate or manganese amendment may be unsuccessful in some locations.
","language":"English","publisher":"Nature","doi":"10.1038/s41396-023-01482-1","usgsCitation":"Peterson, B.D., Poulin, B., Krabbenhoft, D.P., Tate, M., Baldwin, A.K., Naymik, J., Gastelecutto, N., and McMahon, K.D., 2023, Metabolically diverse microorganisms mediate methylmercury formation under nitrate-reducing conditions in a dynamic hydroelectric reservoir: International Society for Microbial Ecology Journal, v. 17, p. 1705-1718, https://doi.org/10.1038/s41396-023-01482-1.","productDescription":"14 p.","startPage":"1705","endPage":"1718","ipdsId":"IP-152265","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":442645,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41396-023-01482-1","text":"Publisher Index Page"},{"id":419879,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Brownlee Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.82386599883054,\n 44.927005686412485\n ],\n [\n -117.32902035469117,\n 44.927005686412485\n ],\n [\n -117.32902035469117,\n 44.33306182839914\n ],\n [\n -116.82386599883054,\n 44.33306182839914\n ],\n [\n -116.82386599883054,\n 44.927005686412485\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","noUsgsAuthors":false,"publicationDate":"2023-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Peterson, Benjamin D.","contributorId":328487,"corporation":false,"usgs":false,"family":"Peterson","given":"Benjamin","email":"","middleInitial":"D.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":880305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poulin, Brett A.","contributorId":328488,"corporation":false,"usgs":false,"family":"Poulin","given":"Brett A.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":880306,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":880307,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tate, Michael T. 0000-0003-1525-1219 mttate@usgs.gov","orcid":"https://orcid.org/0000-0003-1525-1219","contributorId":3144,"corporation":false,"usgs":true,"family":"Tate","given":"Michael T.","email":"mttate@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":880308,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":880309,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Naymik, Jesse","contributorId":229386,"corporation":false,"usgs":false,"family":"Naymik","given":"Jesse","affiliations":[{"id":41632,"text":"Idaho Power Company","active":true,"usgs":false}],"preferred":false,"id":880310,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gastelecutto, Nick","contributorId":296597,"corporation":false,"usgs":false,"family":"Gastelecutto","given":"Nick","email":"","affiliations":[{"id":41632,"text":"Idaho Power Company","active":true,"usgs":false}],"preferred":false,"id":880311,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McMahon, Katherine D.","contributorId":194624,"corporation":false,"usgs":false,"family":"McMahon","given":"Katherine","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":880312,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70250118,"text":"70250118 - 2023 - A genome assembly for the southern Pacific rattlesnake, Crotalus oreganus helleri, in the western rattlesnake species complex","interactions":[],"lastModifiedDate":"2023-11-21T12:40:57.336466","indexId":"70250118","displayToPublicDate":"2023-07-26T06:39:36","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2333,"text":"Journal of Heredity","active":true,"publicationSubtype":{"id":10}},"title":"A genome assembly for the southern Pacific rattlesnake, Crotalus oreganus helleri, in the western rattlesnake species complex","docAbstract":"Rattlesnakes play important roles in their ecosystems by regulating prey populations, are involved in complex coevolutionary dynamics with their prey, and exhibit a variety of unusual adaptations, including maternal care, heat-sensing pit organs, hinged fangs, and medically-significant venoms. The western rattlesnake (Crotalus oreganus) is one of the widest ranging rattlesnake species, with a distribution from British Columbia, where it is listed as threatened, to Baja California and east across the Great Basin to western Wyoming, Colorado and New Mexico. Here, we report a new reference genome assembly for one of six currently recognized subspecies, C. oreganus helleri, as part of the California Conservation Genomics Project (CCGP). Consistent with the reference genomic sequencing strategy of the CCGP, we used Pacific Biosciences HiFi long reads and Hi-C chromatin-proximity sequencing technology to produce a de novo assembled genome. The assembly comprises a total of 698 scaffolds spanning 1,564,812,557 base pairs, has a contig N50 of 64.7 Mb, a scaffold N50 of 110.8 Mb, and BUSCO complete score of 90.5%. This reference genome will be valuable for studies on the genomic basis of venom evolution and variation within Crotalus, in resolving the taxonomy of C. oreganus and its relatives, and for the conservation and management of rattlesnakes in general.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jhered/esad045","usgsCitation":"Westeen, E.P., Escalona, M., Holding, M., Beraut, E., Fairbairn, C., Marimuthu, M.P., Nguyen, O., Perri, R., Fisher, R., Toffelmier, E., Shaffer, H., and Wang, I.J., 2023, A genome assembly for the southern Pacific rattlesnake, Crotalus oreganus helleri, in the western rattlesnake species complex: Journal of Heredity, v. 114, no. 6, p. 681-689, https://doi.org/10.1093/jhered/esad045.","productDescription":"9 p.","startPage":"681","endPage":"689","ipdsId":"IP-153896","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442647,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jhered/esad045","text":"Publisher Index Page"},{"id":422778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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The CBLCM simulates infill development, residential and commercial development, natural land and agricultural land conversion, and growth served by sewer or septic wastewater treatment. The CBLCM is unique among land change models by simulating multiple types of development and explicitly accounting for infill development and the spatial patterns of development densities. The CBLCM was used to simulate five future land use scenarios, holding population constant, for all counties within and adjacent to the Chesapeake Bay watershed from 2013 to 2055. Results are presented here for the state of Maryland over the period 2013–2025 to illustrate model functionality and validation. The growth management (GM) scenario achieved the least development and potential impacts to natural and agricultural lands while accommodating the same amount of population growth as the other four scenarios. Scenarios focusing exclusively on natural or agricultural land protection shifted development to unprotected areas resulting in unforeseen water quality consequences. Simultaneously achieving more compact development while protecting the most valued natural and agricultural lands requires a combination of GM and land conservation policies and actions.
","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.13131","usgsCitation":"Claggett, P., Ahmed, L., Irani, F., McDonald, S., and Thompson, R., 2023, The Chesapeake Bay Land Change Model (CBLCM): Simulating future land use scenarios and potential impacts on water quality: Journal of the American Water Resources Association, 21-0151, 26 p., https://doi.org/10.1111/1752-1688.13131.","productDescription":"21-0151, 26 p.","ipdsId":"IP-134156","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":442650,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.13131","text":"Publisher Index Page"},{"id":419413,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","noUsgsAuthors":false,"publicationDate":"2023-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Claggett, Peter 0000-0002-5335-2857","orcid":"https://orcid.org/0000-0002-5335-2857","contributorId":238920,"corporation":false,"usgs":true,"family":"Claggett","given":"Peter","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":879320,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ahmed, Labeeb 0000-0003-4524-9611","orcid":"https://orcid.org/0000-0003-4524-9611","contributorId":303117,"corporation":false,"usgs":true,"family":"Ahmed","given":"Labeeb","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879321,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irani, Frederick 0000-0002-2424-0135 firani@usgs.gov","orcid":"https://orcid.org/0000-0002-2424-0135","contributorId":303119,"corporation":false,"usgs":true,"family":"Irani","given":"Frederick","email":"firani@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDonald, Sarah 0000-0003-3534-325X","orcid":"https://orcid.org/0000-0003-3534-325X","contributorId":303116,"corporation":false,"usgs":true,"family":"McDonald","given":"Sarah","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879323,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Renee 0000-0003-1463-5173 rthompson1@usgs.gov","orcid":"https://orcid.org/0000-0003-1463-5173","contributorId":303115,"corporation":false,"usgs":true,"family":"Thompson","given":"Renee","email":"rthompson1@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879324,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70247192,"text":"ofr20231052 - 2023 - Status of spectacled eiders (Somateria fischeri) on the Yukon-Kuskokwim Delta, Alaska, 2022—Testing and updating predictive models","interactions":[],"lastModifiedDate":"2023-09-18T19:45:02.263947","indexId":"ofr20231052","displayToPublicDate":"2023-07-25T12:03:50","publicationYear":"2023","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":"2023-1052","displayTitle":"Status of Spectacled Eiders (Somateria fischeri) on the Yukon-Kuskokwim Delta, Alaska, 2022—Testing and Updating Predictive Models","title":"Status of spectacled eiders (Somateria fischeri) on the Yukon-Kuskokwim Delta, Alaska, 2022—Testing and updating predictive models","docAbstract":"The nesting biology and demography of spectacled eiders (Somateria fischeri) along the lower Kashunuk River on the Yukon-Kuskokwim Delta, Alaska, were studied from 1993 to 2002. This previous work demonstrated that the breeding population on the study area was declining, and demographic modeling predicted that the population would continue to decline from 2002 forward. The predicted decline was primarily because of lead shot in tundra wetlands in the area, exposure of nesting females to lead, resulting in low adult female survival. The model predicted that lead pellets already in wetlands would slowly settle beyond the foraging depth of eiders, and that, lead exposure rates would decline. The goal of this project was to test this prediction by revisiting the lower Kashunuk River study area in 2022 to (1) update previous datasets regarding demographic parameters and (2) validate (or refute) existing models relative to lead exposure rates and the effects of lead on population dynamics. In the summer of 2022, a total of 37 nests were found in a sub-area of the historical study area. Comparing to past efforts in this same sub-area, more nests were found than predicted but the proportion of nesting female spectacled eiders exposed to lead in 2022 (24.3 percent) was still similar to levels of exposure observed between 1994 and 2002 (28.5 percent). Thus, data from the 2022 survey suggests that the earlier decline in numbers of nesting spectacled eiders has reversed, but there has been little decrease in lead exposure over time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231052","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Flint, P.L., 2023, Status of spectacled eiders (Somateria fischeri) on the Yukon-Kuskokwim Delta, Alaska, 2022—Testing and updating predictive models: U.S. Geological Survey Open-File Report 2023–1052, 5 p., https://doi.org/10.3133/ofr20231052.","productDescription":"vi, 5 p.","onlineOnly":"Y","ipdsId":"IP-151770","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":419316,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1052/ofr20231052.XML"},{"id":419315,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1052/images"},{"id":419314,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231052/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1052"},{"id":419313,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1052/ofr20231052.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1052"},{"id":419312,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1052/coverthb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon-Kuskokwim Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -166.06721221943172,\n 61.59887493914758\n ],\n [\n -166.06721221943172,\n 60.1670676261173\n ],\n [\n -162.86058022136012,\n 60.1670676261173\n ],\n [\n -162.86058022136012,\n 61.59887493914758\n ],\n [\n -166.06721221943172,\n 61.59887493914758\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
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Anchorage, Alaska 99508
Annual peak-flow data collected at U.S. Geological Survey streamgages in Minnesota and adjacent areas of neighboring states of Iowa and South Dakota were analyzed to develop and update regional regression equations that can be used to estimate the magnitude and frequency of peak streamflow for ungaged streams in Minnesota, excluding the Lake of the Woods-Rainy River Basin upstream from Kenora, Ontario, Canada. Hydraulic engineers use peak-flow frequency estimates to inform designs of bridges, culverts, and dams, and water managers use the estimates for regulation and planning activities. Peak-flow estimates are provided for the 66.7-, 50-, 20-, 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probabilities (AEPs), which are equivalent to annual flood-frequency recurrence intervals of 1.5-, 2-, 5-, 10-, 25-, 50-, 100-, and 500-years, respectively. The estimates were computed by applying the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak flows for 298 streamgages based on annual peak-flow data collected through water year 2019. The study area is represented by six hydrologic regions delineated on the basis of a pattern of residuals of statewide regressions, using basin characteristics such as drainage area, main-channel slope, lake area, storage area, and mean annual runoff as explanatory variables. The concept and principles of hydrologic landscape units was used to validate the regions. Residual analysis of the regional regression equations was used to subsequently develop equations relating the peak flow estimates for selected AEPs using 17 characteristics tested as explanatory variables in the regression analysis.
The equations developed in this study can be used to produce AEPs within the six regions and to update equations developed in earlier, similar studies in Minnesota. Furthermore, updating the equations in StreamStats, a web-based geographic information system tool developed by the U.S. Geological Survey, will allow hydraulic engineers and water managers to obtain AEPs and basin characteristics for user-selected locations on streams through an interactive map.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235079","collaboration":"Prepared in cooperation with the Minnesota Department of Transportation","usgsCitation":"Sanocki, C.A., and Levin, S.B., 2023, Techniques for estimating the magnitude and frequency of peak flows on small streams in Minnesota, excluding the Rainy River Basin, based on data through water year 2019: U.S. Geological Survey Scientific Investigations Report 2023–5079, 15 p., https://doi.org/10.3133/sir20235079.","productDescription":"Report: v, 15 p.; 2 Data Releases; Dataset","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-127955","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":419307,"rank":7,"type":{"id":39,"text":"HTML 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\"}}]}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
This report outlines quality assurance (QA) processes, including radiometric and geometric calibration guidelines, and guidelines for data acquisition and quality control to be followed by U.S. Geological Survey (USGS) researchers for acquiring and processing uncrewed aircraft systems (UAS) data. These QA processes ensure that UAS data can be used for quantitative analysis and are comparable with other standard geospatial data.
Remote sensing data play a critical role in monitoring Earth’s resources. Traditionally, the USGS and Department of the Interior have used well calibrated metric sensors mounted on satellite or aircraft platforms to collect these data. These sensors and platforms are stable, and data have been processed using standard pipelines. These processes ensured that the data are generally consistent with each other and benefitted a diverse group of users. These data are shared among multiple researchers around the world through the internet and other means, using standard formats and metadata.
In the last few years, UAS platforms have democratized the remote sensing data collection further, bringing an unparalleled level of control of time, sensors, and processes to individual researchers. Together with the development of cheaper and lighter sensors and relaxation of prohibitions against UAS operation in the National Airspace System by the Federal Aviation Authority, researchers can collect remote sensing data using UAS platforms. Researchers often customize the sensors on these UAS systems based on their specific requirements and use ad hoc processing steps to generate data.
A challenge is that these data are often produced by a wide array of sensors and processes that render them potentially inconsistent with each other. Therefore, unlike data collected from metric sensors, UAS-based data are designed to benefit only specific user groups. The data thus generated often lack traceability to known standards, making them difficult to use with other geospatial data.
This report provides radiometric and geometric calibration guidelines, as well as guidelines for data acquisition and quality control, that can be followed by USGS researchers in acquiring and processing UAS data. Instead of calibrating sensors, researchers collecting UAS data can focus on calibrating the data. Various radiometric calibration processes are provided, and the two panel empirical line method is highlighted for radiometric calibration.
For geometric calibration, USGS and Department of the Interior researchers are experienced in following standard calibration procedures provided by standard UAS data processing software. However, researchers may be aided in paying attention to the tie points and the accuracy of the ground control points used for geometric calibration and data production. The accuracy of ground control points are related to the requirements of the project. The ground control points and the quality of tie points directly contribute to the geometric accuracy of the data, regardless of the ground sample distance of the imagery.
The guidelines outlined in this report are intended to ensure that the data are in common units and are quantifiable and comparable with other data. These QA and calibration processes can be critical in ensuring that these datasets are used to the maximum extent possible. Including the calibration parameters (and their uncertainties) as part of metadata can allow for easier data discovery and analytical filters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231033","usgsCitation":"Sampath, A., Shrestha, M., While, M., and Scholl, V.M., 2023, Guidelines for calibration of uncrewed aircraft systems imagery: U.S. Geological Survey Open-File Report 2023–1033, 23 p., https://doi.org/10.3133/ofr20231033.","productDescription":"v, 23 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-146359","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":419305,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231033/full"},{"id":419252,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1033/images/"},{"id":419251,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1033/ofr20231033.XML"},{"id":419250,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1033/ofr20231033.pdf","text":"Report","size":"3.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1033"},{"id":419249,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1033/coverthb.jpg"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Herbivorous animals tend to seek out plants at intermediate phenological states to improve energy intake while minimizing consumption of fibrous material. In some ecosystems, the timing of green-up is heterogeneous and propagates across space in a wave-like pattern, known as the green wave. Tracking the green wave allows individuals to prolong access to higher-quality forage. While there is a plethora of empirical support for such behavior in herbivorous taxa, the green wave hypothesis (GWH) is nuanced based on factors such as body morphometrics and digestive capacity. Furthermore, little is known about whether other taxa, such as omnivores, track the green wave. Our objective was to assess whether the GWH can be extended to explain the movements of omnivores. Using GPS collar data from seven populations (n = 127 individuals) of brown bears Ursus arctos across their entire North American range, we first tested whether bears tracked the green wave. Using conditional resource selection functions (RSFs), we found that variation in proxies of vegetative forage quality better explained movement and habitat selection than proxies of forage biomass in over half of the bears in our study, providing evidence of green wave tracking. Second, we assess factors that explained variation in green wave tracking using linear mixed effects models. Green wave tracking in brown bears was explained by the variation in availability of green-up within spring home ranges, and how green-up transitioned across those home ranges. Our results demonstrate that the GWH can partially explain movement of a non-migratory omnivorous species, extending the generality of the GWH as a broad predictor of animal space use. The green wave is another resource wave brown bears track, and our findings help predict brown bear space use, which can be used to guide conservation and habitat restoration efforts.
","language":"English","publisher":"Wiley","doi":"10.1111/ecog.06549","usgsCitation":"Bowersock, N.R., Ciarniello, L.M., Deacy, W.W., Heard, D.C., Joly, K., Lamb, C.T., Leacock, W.B., Mclellan, B., Mowat, G., Sorum, M.S., van Manen, F.T., and Merkle, J., 2023, A test of the green wave hypothesis in omnivorous brown bears across North America: Ecography, v. 2023, no. 10, e06549, 12 p., https://doi.org/10.1111/ecog.06549.","productDescription":"e06549, 12 p.","ipdsId":"IP-142801","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":442652,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ecog.06549","text":"Publisher Index Page"},{"id":419350,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, British Columbia, Idaho, Montana, Wyoming","otherGeospatial":"Elk Valley, Flathead Valley, Gates of the Arctic, Greater Yellowstone ecosystem, Kodiak Island, Parsnip Mountain, Parsnip Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.58270702767695,\n 43.58074880621092\n ],\n [\n -114.86203363678416,\n 50.16374484994262\n ],\n [\n -122.08539027157664,\n 55.91094145040341\n ],\n [\n -144.08820653499708,\n 68.6311238737492\n ],\n [\n -152.21192576584002,\n 69.43288028347476\n ],\n [\n -161.02170588000897,\n 68.55829959585586\n ],\n [\n -155.54559520650918,\n 56.09696676721251\n ],\n [\n -150.40416182908686,\n 57.307524490103276\n ],\n [\n -144.85601862056535,\n 61.07891762933866\n ],\n [\n -130.33415600545123,\n 54.54538997683014\n ],\n [\n -121.6241105920378,\n 49.020537277214885\n ],\n [\n -111.72137354906724,\n 44.96531210384342\n ],\n [\n -111.36242529627467,\n 42.9172213366808\n ],\n [\n -106.9583587691117,\n 42.788416970678725\n ],\n [\n -107.58270702767695,\n 43.58074880621092\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2023","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Bowersock, Nathaniel R.","contributorId":268804,"corporation":false,"usgs":false,"family":"Bowersock","given":"Nathaniel","email":"","middleInitial":"R.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":879090,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ciarniello, L. 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C.","contributorId":317706,"corporation":false,"usgs":false,"family":"Heard","given":"D.","email":"","middleInitial":"C.","affiliations":[{"id":69134,"text":"BC Ministry of Forests, Lands and Natural Resource Operations","active":true,"usgs":false}],"preferred":false,"id":879093,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Joly, Kyle","contributorId":53117,"corporation":false,"usgs":false,"family":"Joly","given":"Kyle","email":"","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":879094,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lamb, Clayton T.","contributorId":216009,"corporation":false,"usgs":false,"family":"Lamb","given":"Clayton","email":"","middleInitial":"T.","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":879095,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leacock, William B.","contributorId":211732,"corporation":false,"usgs":false,"family":"Leacock","given":"William","email":"","middleInitial":"B.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":879096,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mclellan, Bruce","contributorId":167051,"corporation":false,"usgs":false,"family":"Mclellan","given":"Bruce","email":"","affiliations":[{"id":24603,"text":"British Columbia Ministry of Forests Research Branch","active":true,"usgs":false}],"preferred":false,"id":879097,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mowat, Garth","contributorId":216012,"corporation":false,"usgs":false,"family":"Mowat","given":"Garth","email":"","affiliations":[{"id":13452,"text":"Univ. British Columbia","active":true,"usgs":false}],"preferred":false,"id":879098,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sorum, Mathew S","contributorId":243500,"corporation":false,"usgs":false,"family":"Sorum","given":"Mathew","email":"","middleInitial":"S","affiliations":[],"preferred":false,"id":879099,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":879100,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Merkle, Jerod A.","contributorId":270421,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod A.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":879101,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70247277,"text":"70247277 - 2023 - The relation between decadal droughts and eruptions of Steamboat Geyser in Yellowstone National Park, USA","interactions":[],"lastModifiedDate":"2023-07-26T13:47:46.688774","indexId":"70247277","displayToPublicDate":"2023-07-25T08:36:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"The relation between decadal droughts and eruptions of Steamboat Geyser in Yellowstone National Park, USA","docAbstract":"In the past century, most eruptions of Steamboat Geyser in Yellowstone National Park's Norris Geyser Basin were mainly clustered in three episodes: 1961–1969, 1982–1984, and ongoing since 2018. These eruptive episodes resulted in extensive disturbance to surrounding trees. To characterize tree response over time as an indicator of geyser activity adjustments to climate variability, aerial and ground images were analyzed to document changes in tree coverage around the geyser since 1954. Radiocarbon dating of silicified tree remnants from within 14 m of the geyser vent was used to examine geyser response to possible variations in decadal to centennial precipitation patterns. We searched for atypical or absent growth rings in cores from live trees in years associated with large geyser eruptions. Photographs indicate that active eruptive phases have adversely affected trees up to 30 m from the vent, primarily in the dominant downwind direction. Radiocarbon dates indicate that the geyser formed before 1878, in contrast to the birthdate reported in historical documents. Further, the ages of the silicified trees cluster within three episodes that are temporally correlated with periods of relative drought in the Yellowstone region during the 15th–17th centuries. The discontinuous growth of trees around the geyser suggests that changes in eruptive patterns occur in response to decadal to multidecadal droughts. This inference is supported by the lack of silicified specimens with more than 20 annual rings and by the existence of atypical or missing rings in live trees during periods of extended geyser activity.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023GC010988","usgsCitation":"Hurwitz, S., King, J., Pederson, G.T., Reed, M.H., Harrison, L.N., Hungerford, J., Vaughan, R.G., and Manga, M., 2023, The relation between decadal droughts and eruptions of Steamboat Geyser in Yellowstone National Park, USA: Geochemistry, Geophysics, Geosystems, v. 24, no. 7, e2023GC010988, 16 p., https://doi.org/10.1029/2023GC010988.","productDescription":"e2023GC010988, 16 p.","ipdsId":"IP-151989","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":442655,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023gc010988","text":"Publisher Index Page"},{"id":435243,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NG2TF4","text":"USGS data release","linkHelpText":"Radiocarbon dating of silicified wood from around Steamboat Geyser in Norris Geyser Basin, Yellowstone National Park, 2021-2022"},{"id":419346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Steamboat Geyser, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.70737958606496,\n 44.726071382948504\n ],\n [\n -110.70737958606496,\n 44.720452350460704\n ],\n [\n -110.69905051930982,\n 44.720452350460704\n ],\n [\n -110.69905051930982,\n 44.726071382948504\n ],\n [\n -110.70737958606496,\n 44.726071382948504\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"24","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":879082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, John C.","contributorId":225237,"corporation":false,"usgs":false,"family":"King","given":"John C.","affiliations":[{"id":41082,"text":"Lone Pine Research","active":true,"usgs":false}],"preferred":false,"id":879083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":879084,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reed, Mara H.","contributorId":317700,"corporation":false,"usgs":false,"family":"Reed","given":"Mara","email":"","middleInitial":"H.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":879085,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harrison, Lauren N 0000-0002-6621-5958","orcid":"https://orcid.org/0000-0002-6621-5958","contributorId":300066,"corporation":false,"usgs":true,"family":"Harrison","given":"Lauren","email":"","middleInitial":"N","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":879086,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hungerford, Jefferson","contributorId":243584,"corporation":false,"usgs":false,"family":"Hungerford","given":"Jefferson","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":879087,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vaughan, R. Greg 0000-0002-0850-6669","orcid":"https://orcid.org/0000-0002-0850-6669","contributorId":69030,"corporation":false,"usgs":true,"family":"Vaughan","given":"R.","email":"","middleInitial":"Greg","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":879088,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Manga, Michael 0000-0003-3286-4682","orcid":"https://orcid.org/0000-0003-3286-4682","contributorId":265640,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":879089,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70248461,"text":"70248461 - 2023 - Ecosystem resilience to invasion and drought: Insights after 24 years in a rare never-grazed grassland","interactions":[],"lastModifiedDate":"2023-09-20T16:28:46.57569","indexId":"70248461","displayToPublicDate":"2023-07-25T08:26:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem resilience to invasion and drought: Insights after 24 years in a rare never-grazed grassland","docAbstract":"Understanding the resilience of ecosystems globally is hampered by the complex and interacting drivers of change characteristic of the Anthropocene. This is true for drylands of the western US, where widespread alteration of disturbance regimes and spread of invasive non-native species occurred with westward expansion during the 1800s, including the introduction of domestic livestock and spread of Bromus tectorum, an invasive non-native annual grass. In addition, this region has experienced a multi-decadal drought not seen for at least 1200 years with potentially large and interacting impacts on native plant communities. Here, we present 24 years of twice-annual plant cover monitoring (1997–2021) from a semiarid grassland never grazed by domestic livestock but subject to a patchy invasion of B. tectorum beginning in ~1994, compare our findings to surveys done in 1967, and examine potential climate drivers of plant community changes. We found a significant warming trend in the study area, with more than 75% of study year temperatures being warmer than average (1966–2021). We observed a native perennial grass community with high resilience to climate forcings with cover values like those in 1967. In invaded patches, B. tectorum cover was greatest in the early years of this study (1997–2001; ~20%–40%) but was subsequently constrained by climate and subtle variation in soils, with limited evidence of long-term impacts to native vegetation, contradicting earlier studies. Our ability to predict year-to-year variation in functional group and species cover with climate metrics varied, with a 12-month integrated index and fall and winter patterns appearing most important. However, declines to near zero live cover in recent years in response to regional drought intensification leave questions regarding the resiliency of intact grasslands to ongoing aridification and whether the vegetation observations reported here may be a leading indicator of impending change in this protected ecosystem.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16882","usgsCitation":"Duniway, M.C., Finger-Higgens, R.A., Geiger, E.L., Hoover, D.L., Pfennigwerth, A., Knight, A.C., Van Scoyoc, M., Miller, M.E., and Belnap, J., 2023, Ecosystem resilience to invasion and drought: Insights after 24 years in a rare never-grazed grassland: Global Change Biology, v. 29, no. 20, p. 5866-5880, https://doi.org/10.1111/gcb.16882.","productDescription":"15 p.","startPage":"5866","endPage":"5880","ipdsId":"IP-150102","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":420786,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Canyonlands National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 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0000-0002-7645-504X","orcid":"https://orcid.org/0000-0002-7645-504X","contributorId":290211,"corporation":false,"usgs":true,"family":"Finger-Higgens","given":"Rebecca","email":"","middleInitial":"A","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":882998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Geiger, Erika L. 0000-0003-4546-3503","orcid":"https://orcid.org/0000-0003-4546-3503","contributorId":207502,"corporation":false,"usgs":true,"family":"Geiger","given":"Erika","email":"","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":882999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoover, David L. 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0000-0002-9455-2855","orcid":"https://orcid.org/0000-0002-9455-2855","contributorId":255113,"corporation":false,"usgs":true,"family":"Knight","given":"Anna","email":"","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":883002,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Van Scoyoc, M.","contributorId":329694,"corporation":false,"usgs":false,"family":"Van Scoyoc","given":"M.","affiliations":[{"id":78691,"text":"National Park Service, Southeast Utah Group Parks, Moab, UT","active":true,"usgs":false}],"preferred":false,"id":883003,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Mark E.","contributorId":91580,"corporation":false,"usgs":false,"family":"Miller","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":883004,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":883005,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70247926,"text":"70247926 - 2023 - Spatio-temporal variability in the strength, directionality, and relative importance of climate on occupancy and population densities in a philopatric mammal, the American pika (Ochotona princeps)","interactions":[],"lastModifiedDate":"2023-08-24T13:18:36.766188","indexId":"70247926","displayToPublicDate":"2023-07-25T08:09:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatio-temporal variability in the strength, directionality, and relative importance of climate on occupancy and population densities in a philopatric mammal, the American pika (Ochotona princeps)","title":"Spatio-temporal variability in the strength, directionality, and relative importance of climate on occupancy and population densities in a philopatric mammal, the American pika (Ochotona princeps)","docAbstract":"Species distribution models (SDMs) have been widely employed to evaluate species–environment relationships. However, when extrapolated over broad spatial scales or through time, these models decline in their predictive ability due to variation in how species respond to their environment. Many models assume species–environment relationships remain constant over space and time, hindering their ability to accurately forecast distributions. Therefore, there is growing recognition that models could be improved by accounting for spatio-temporal nonstationarity – a phenomenon wherein the factors governing ecological processes change over space or time. Here, we investigated nonstationarity in American pika (Ochotona princeps) relationships with climatic variables in the Rocky Mountains (USA). We first compared broad-scale differences in pika–climate patterns for occupancy and population density across the Southern, Central, and Northern Rockies. Next, we investigated within-ecoregion variation across four mountain ranges nested within the Northern Rockies. Lastly, we tested whether species–climate relationships changed over time within the Central Rockies ecoregion. Across all analyses, we found varying levels of nonstationarity among the climate metrics for both occupancy and density. Although we found general congruence in temperature metrics, which consistently had negative coefficients, and moisture metrics (e.g., relative humidity), which had positive coefficients, nonstationarity was greatest for summer and winter precipitation over both space and time. These results suggest that interpretations from one ecoregion should not be applied to other regions universally – especially when using precipitation metrics. The within-ecoregion analysis found much greater variation in the strength-of-relationship coefficients among the four mountain ranges, relative to the inter-regional analysis, possibly attributable to smaller sample sizes per mountain range. Lastly, the importance of several variables shifted through time from significant to insignificant in the temporal analysis. Our results collectively reveal the overall complexity underlying species–environment relationships. With rapidly shifting conditions globally, this work adds to the growing body of literature highlighting how issues of spatio-temporal nonstationarity can limit the accuracy, transferability, and reliability of models and that interpretations will likely be most robust at local to regional scales. Diagnosing, describing, and incorporating nonstationarity of species–climate relationships into models over space and time could serve as a pivotal step in creating more informative models.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2023.1202610","usgsCitation":"Billman, P.D., Beever, E.A., Westover, M.L., and Ryals, D., 2023, Spatio-temporal variability in the strength, directionality, and relative importance of climate on occupancy and population densities in a philopatric mammal, the American pika (Ochotona princeps): Frontiers in Ecology and Evolution, v. 11, 1202610, 13 p., https://doi.org/10.3389/fevo.2023.1202610.","productDescription":"1202610, 13 p.","ipdsId":"IP-152205","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":442659,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1202610","text":"Publisher Index Page"},{"id":435244,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WB1EWC","text":"USGS data release","linkHelpText":"Climatic data associated with American-pika survey (2011-2021) locations in 3 regions of the Rocky Mountains"},{"id":420114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Billman, Peter D.","contributorId":311242,"corporation":false,"usgs":false,"family":"Billman","given":"Peter","email":"","middleInitial":"D.","affiliations":[{"id":67370,"text":"University of Connecticut, Dept. of Ecology and Evolution","active":true,"usgs":false}],"preferred":false,"id":881024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beever, Erik A. 0000-0002-9369-486X ebeever@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-486X","contributorId":2934,"corporation":false,"usgs":true,"family":"Beever","given":"Erik","email":"ebeever@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":881025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Westover, Marie L.","contributorId":274853,"corporation":false,"usgs":false,"family":"Westover","given":"Marie","email":"","middleInitial":"L.","affiliations":[{"id":48790,"text":"Dept. of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":881026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ryals, Dylan K.","contributorId":328675,"corporation":false,"usgs":false,"family":"Ryals","given":"Dylan K.","affiliations":[{"id":78450,"text":"Dept. of Entomology, Purdue University, West Lafayette, IN","active":true,"usgs":false}],"preferred":false,"id":881027,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70247704,"text":"70247704 - 2023 - Accuracy of finite fault slip estimates in subduction zone regions with topographic Green's functions and seafloor geodesy","interactions":[],"lastModifiedDate":"2023-08-14T12:25:52.922387","indexId":"70247704","displayToPublicDate":"2023-07-25T07:24:37","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Accuracy of finite fault slip estimates in subduction zone regions with topographic Green's functions and seafloor geodesy","docAbstract":"Until recently, the lack of seafloor geodetic instrumentation and the use of unrealistically simple, half-space based forward models have resulted in poor resolution of near-trench slip in subduction zone settings. Here, we use a synthetic framework to investigate the impact of topography and geodetic data distribution on coseismic slip estimates in various subduction zone settings. We calculate surface displacements in two synthetic topographic domains that have topography similar to that of Chile and Japan, respectively. We then attempt to image target slip distributions by using a Bayesian approach to solve for slip with two sets of Green's functions—one that accounts for topography and one that does not—and five sets of 50 or more observation points selected from the synthetic surface displacements. Three of these sets of observation points are entirely onland, and two include 5–10 seafloor geodetic sites. We find that the use of topographic Green's functions always improves inferred slip models, and with seafloor geodetic data, it enables an almost perfect recovery of a target slip model, even in the near-trench region. Critically, our results demonstrate that it would be impossible for non-topographic Green's functions to properly recover the true slip distribution, particularly in the near-trench region. We also perform a parameter study with approximately 4,000 slip models estimated using a least-square approach, and find that topographic Green's functions yield significantly more accurate slip models in cases where good data (well distributed and reasonably dense) are available, even in the absence of seafloor geodetic sites.
The Harney Basin is Oregon's largest internally draining basin and contains a unique native fish assemblage. The first and only comprehensive study of the origin and distribution of Harney Basin fishes occurred in 1971. Here, we update this study and identify potential threats to the basin's native fishes a half century later. Our assessment documents that all species of native fishes are still present, and with some exceptions distributed as originally reported. The distinctive fish assemblages in each of the 3 major subbasins within the Harney Basin (Silvies River, Silver Creek, and Donner und Blitzen River) support the hypothesis that terminal lakes in the Harney Basin (Malheur, Mud, and Harney Lakes) act as dispersal barriers, at least for native species. More than half of the fish species in the basin at present are introduced, primarily inhabiting low-elevation sites. We suggest that native non-salmonid species cohabiting these sites face the most immediate threats from climate change, water demands, and impacts from introduced fishes. Overall, our results show that native fish are still relatively widespread across the Harney Basin, but also face increasing threats despite the basin having experienced less development than many other areas in the Pacific Northwest. Improved understanding of the unique fishes of the Harney Basin, along with more detailed assessments of likely future trajectories of environmental risks are proactive measures that could improve conservation outcomes.
Climate warming threatens to destabilize vast northern permafrost areas, potentially releasing large quantities of organic carbon that could further disrupt the climate. Here we synthesize paleorecords of past permafrost-carbon dynamics to contextualize future permafrost stability and carbon feedbacks. We identify key landscape differences between the last deglaciation and today that influence the response of permafrost to atmospheric warming, as well as landscape-level differences that limit subsequent carbon uptake. We show that the current magnitude of thaw has not yet exceeded that of previous deglaciations, but that permafrost carbon release has the potential to exert a strong feedback on future Arctic climate as temperatures exceed those of the Pleistocene. Better constraints on the extent of subsea permafrost and its carbon pool, and on carbon dynamics from a range of permafrost thaw processes, including blowout craters and megaslumps, are needed to help quantify the future permafrost-carbon-climate feedbacks.
Introduced fungal pathogens have caused declines and extinctions of naïve wildlife populations across vertebrate classes. Consequences of introduced pathogens to hosts with small ranges might be especially severe because of limited redundancy to rescue populations and lower abundance that may limit the resilience of populations to perturbations like disease introduction. As a complement to biosecurity measures to prevent the spread of pathogens, surveillance programs may enable early detection of pathogens, when management actions to limit the effects of pathogens on naïve hosts might be most beneficial. We analyzed surveillance data for the endangered and narrowly endemic Dixie Valley toad (Anaxyrus [= Bufo] williamsi) from two time periods (2011–2014 and 2019–2021) to estimate the minimum detectable prevalence of the amphibian fungal pathogen Batrachochytrium dendrobatidis (Bd). We assessed if detection efficiency could be improved by using samples from both Dixie Valley toads and co-occurring introduced American bullfrogs (Lithobates catesbeianus) and literature-derived surveillance weights. We further evaluated a weighted surveillance design to increase the efficiency of surveillance efforts for Bd within the toad’s small (<6 km2) range. We found that monitoring adult and larval American bullfrogs would probably detect Bd more efficiently than monitoring Dixie Valley toads alone. Given that no Bd was detected, minimum detectable prevalence of Bd was <3% in 2011–2014, and <5% (Dixie Valley toads only) and <10% (American bullfrogs only) in 2019–2021. Optimal management for Bd depends on the mechanisms underlying its apparent absence from the range of Dixie Valley toads, but a balanced surveillance scheme that includes sampling American bullfrogs to increase the likelihood of detecting Bd, and adult Dixie Valley toads to ensure broad spatial coverage where American bullfrogs do not occur, would probably result in efficient surveillance, which might permit timely management of Bd if it is detected.
Breccia pipe deposits of the Grand Canyon region contain ore grade copper and uranium. Horn Creek is located near the Orphan Mine mineralized breccia pipe deposit and groundwater emerging from the bedrock in the headwaters of Horn Creek has the highest uranium concentrations in the region. Uranium decreases an order of magnitude between the groundwater at the top of the watershed and the groundwater emerging from the alluvial material lower in the watershed. Horn Creek water has low sulfur and uranium isotopic ratios which may suggest interaction with sulfide and uranium minerals found in mineralized breccia pipe deposits. Per- and polyfluoroalkyl substances (PFBA and PFBS) were found in low concentrations in groundwater from the bedrock and may be related to mining process materials or other anthropogenic activities. PHREEQC modeling suggests that water that is elevated in uranium emerging from the bedrock in the upper watershed may mix with other groundwater and atmospheric precipitation infiltrated into the alluvial material in the lower watershed. Tritium is elevated in Horn Creek groundwaters suggesting a component of modern water, some of which may have interacted with Orphan Mine workings. Additional studies could build on this understanding of chemistry changes in waters of Horn Creek to provide more direct evidence of contribution of water moving through the Orphan Mine.
","language":"English","publisher":"Geological Society of London","doi":"10.1144/geochem2023-007","usgsCitation":"Beisner, K.R., Davidson, C., and Tillman, F.D., 2023, Anthropogenic influence on groundwater geochemistry in Horn Creek Watershed near the Orphan Mine in Grand Canyon National Park, Arizona, USA: Geochemistry: Exploration, Environment, Analysis, v. 23, no. 3, geochem2023-007, 14 p., https://doi.org/10.1144/geochem2023-007.","productDescription":"geochem2023-007, 14 p.","ipdsId":"IP-148025","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":442670,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1144/geochem2023-007","text":"Publisher Index Page"},{"id":435245,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X17FKG","text":"USGS data release","linkHelpText":"PHREEQC files for geochemical simulations in Horn Creek, Grand Canyon, AZ"},{"id":419348,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park, Horn Creek Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.20894969063656,\n 36.094735674145454\n ],\n [\n -112.21000073958996,\n 36.06653388307063\n ],\n [\n -112.13348437577403,\n 36.06653388307063\n ],\n [\n -112.13768857158801,\n 36.110530696949866\n ],\n [\n -112.20894969063656,\n 36.094735674145454\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-09-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Beisner, Kimberly R. 0000-0002-2077-6899 kbeisner@usgs.gov","orcid":"https://orcid.org/0000-0002-2077-6899","contributorId":2733,"corporation":false,"usgs":true,"family":"Beisner","given":"Kimberly","email":"kbeisner@usgs.gov","middleInitial":"R.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davidson, Collin","contributorId":317722,"corporation":false,"usgs":false,"family":"Davidson","given":"Collin","email":"","affiliations":[{"id":40182,"text":"University of Nevada Las Vegas","active":true,"usgs":false}],"preferred":false,"id":879134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879135,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70247123,"text":"70247123 - 2023 - Patterns, drivers, and a predictive model of dam removal cost in the United States","interactions":[],"lastModifiedDate":"2023-12-01T21:14:06.647209","indexId":"70247123","displayToPublicDate":"2023-07-24T08:36:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Patterns, drivers, and a predictive model of dam removal cost in the United States","docAbstract":"Given the burgeoning dam removal movement and the large number of dams approaching obsolescence in the United States, cost estimating data and tools are needed for dam removal prioritization, planning, and execution. We used the list of removed dams compiled by American Rivers to search for publicly available reported costs for dam removal projects. Total cost information could include component costs related to project planning, dam deconstruction, monitoring, and several categories of mitigation activities. We compiled reported costs from 455 unique sources for 668 dams removed in the United States from 1965 to 2020. The dam removals occurred within 571 unique projects involving 1–18 dams. When adjusted for inflation into 2020 USD, cost of these projects totaled \\$1.522 billion, with per-dam costs ranging from $1 thousand (k) to \\$268.8 million (M). The median cost for dam removals was \\$157k, \\$823k, and \\$6.2M for dams that were< 5 m, between 5–10 m, and > 10 m in height, respectively. Geographic differences in total costs showed that northern states in general, and the Pacific Northwest in particular, spent the most on dam removal. The Midwest and the Northeast spent proportionally more on removal of dams less than 5 m in height, whereas the Northwest and Southwest spent the most on larger dam removals > 10 m tall. We used stochastic gradient boosting with quantile regression to model dam removal cost against potential predictor variables including dam characteristics (dam height and material), hydrography (average annual discharge and drainage area), project complexity (inferred from construction and sediment management, mitigation, and post-removal cost drivers), and geographic region. Dam height, annual average discharge at the dam site, and project complexity were the predominant drivers of removal cost. The final model had an R2 of 57% and when applied to a test dataset model predictions had a root mean squared error of $5.09M and a mean absolute error of \\$1.45M, indicating its potential utility to predict estimated costs of dam removal. We developed a R shiny application for estimating dam removal costs using customized model inputs for exploratory analyses and potential dam removal planning.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2023.1215471","usgsCitation":"Duda, J.J., Jumani, S., Wieferich, D.J., Tullos, D.D., McKay, S.K., Randle, T.J., Jansen, A., Bailey, S., Jensen, B.L., Johnson, R.C., Wagner, E.J., Richards, K.B., Wenger, S., Walther, E.J., and Bountry, J.A., 2023, Patterns, drivers, and a predictive model of dam removal cost in the United States: Frontiers in Ecology and Evolution, v. 11, 1215471. 16 p., https://doi.org/10.3389/fevo.2023.1215471.","productDescription":"1215471. 16 p.","ipdsId":"IP-153157","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":442673,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1215471","text":"Publisher Index Page"},{"id":435246,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G8V371","text":"USGS data release","linkHelpText":"Compilation of cost estimates for dam removal projects in the United States"},{"id":419297,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-07-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":878956,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jumani, Suman 0000-0002-2292-7996","orcid":"https://orcid.org/0000-0002-2292-7996","contributorId":305995,"corporation":false,"usgs":false,"family":"Jumani","given":"Suman","email":"","affiliations":[{"id":66338,"text":"Network for Engineering with Nature, Georgia, USA","active":true,"usgs":false}],"preferred":false,"id":878957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wieferich, Daniel J. 0000-0003-1554-7992 dwieferich@usgs.gov","orcid":"https://orcid.org/0000-0003-1554-7992","contributorId":176205,"corporation":false,"usgs":true,"family":"Wieferich","given":"Daniel","email":"dwieferich@usgs.gov","middleInitial":"J.","affiliations":[{"id":5069,"text":"Office of the AD Core Science Systems","active":true,"usgs":true},{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":878958,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tullos, Desiree D.","contributorId":176667,"corporation":false,"usgs":false,"family":"Tullos","given":"Desiree","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":878959,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKay, S. Kyle","contributorId":169086,"corporation":false,"usgs":false,"family":"McKay","given":"S.","email":"","middleInitial":"Kyle","affiliations":[],"preferred":false,"id":878960,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Randle, Timothy J.","contributorId":90994,"corporation":false,"usgs":false,"family":"Randle","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":878961,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jansen, Alvin","contributorId":317292,"corporation":false,"usgs":false,"family":"Jansen","given":"Alvin","email":"","affiliations":[{"id":68995,"text":"Technical Service Center, Bureau of Reclamation, Denver, Colorado, USA","active":true,"usgs":false}],"preferred":false,"id":878962,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bailey, Susan","contributorId":317293,"corporation":false,"usgs":false,"family":"Bailey","given":"Susan","email":"","affiliations":[{"id":68996,"text":"Engineer Research and Development Center - Environmental Laboratory, U.S. Army Corps of Engineers, Vicksburg, Mississippi, USA","active":true,"usgs":false}],"preferred":false,"id":878963,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jensen, Benjamin Lorenz 0000-0003-1199-973X","orcid":"https://orcid.org/0000-0003-1199-973X","contributorId":306036,"corporation":false,"usgs":true,"family":"Jensen","given":"Benjamin","email":"","middleInitial":"Lorenz","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":878964,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Johnson, Rachelle Carina 0000-0003-1480-4088","orcid":"https://orcid.org/0000-0003-1480-4088","contributorId":241962,"corporation":false,"usgs":true,"family":"Johnson","given":"Rachelle","email":"","middleInitial":"Carina","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":878965,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wagner, Ella J.","contributorId":306038,"corporation":false,"usgs":false,"family":"Wagner","given":"Ella","email":"","middleInitial":"J.","affiliations":[{"id":66358,"text":"Previously USGS, WFRC, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":878966,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Richards, Kyla Breanne 0000-0001-7504-6239","orcid":"https://orcid.org/0000-0001-7504-6239","contributorId":306039,"corporation":false,"usgs":true,"family":"Richards","given":"Kyla","email":"","middleInitial":"Breanne","affiliations":[{"id":5069,"text":"Office of the AD Core Science Systems","active":true,"usgs":true}],"preferred":true,"id":878967,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":878968,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Walther, Eric J.","contributorId":304288,"corporation":false,"usgs":false,"family":"Walther","given":"Eric","email":"","middleInitial":"J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":878969,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Bountry, Jennifer A.","contributorId":30114,"corporation":false,"usgs":false,"family":"Bountry","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":878970,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ]}