One of the most prominent challenges related to legacy seismic data is determining how these data can be appropriately used in modern research applications. The wide variety of instrumentation used in the analog era, the format of recording on paper wrapped around a helicorder drum, and limited metadata information introduces ambiguities that are not typical of modern digital data. Therefore, techniques must be developed to help characterize uncertainties in legacy data. This article presents an analysis that compares corecorded signals from two instruments—a Trillium Compact or Press‐Ewing (PE) seismometer for sensing ground motion and two recording systems: a modern Q330 digitizer or heated‐stylus system. Analyses of the recordings in both time and frequency domains indicate time uncertainty on the order of one second, identify a flat response in a 10–60 s band for the PE and drum recorder, and highlight how specific features of scans and paper seismograms (e.g., repeated portions of scans and line thickness) can cause timing jumps or reduced trace amplitude.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220230129","usgsCitation":"Lee, T., Ringler, A.T., Anthony, R.E., and Ishii, M., 2023, Comparison of co-recorded analog and digital systems for characterization of responses and uncertainties: Seismological Research Letters, v. 94, no. 5, p. 2301-2312, https://doi.org/10.1785/0220230129.","productDescription":"12 p.","startPage":"2301","endPage":"2312","ipdsId":"IP-154154","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":420230,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-07-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Lee, Thomas A.","contributorId":328830,"corporation":false,"usgs":false,"family":"Lee","given":"Thomas A.","affiliations":[],"preferred":false,"id":881246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":3946,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":881247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":881248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ishii, Miaki","contributorId":140929,"corporation":false,"usgs":false,"family":"Ishii","given":"Miaki","email":"","affiliations":[{"id":13619,"text":"Department of Earth & Planetary Sciences, Harvard University, Cambridge, MA","active":true,"usgs":false}],"preferred":false,"id":881249,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249589,"text":"70249589 - 2023 - Tree-ring derived avalanche frequency and climate associations in a high-latitude, maritime climate","interactions":[],"lastModifiedDate":"2023-10-18T12:09:25.06511","indexId":"70249589","displayToPublicDate":"2023-07-28T07:07:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6454,"text":"Journal of Geophysical Research - Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Tree-ring derived avalanche frequency and climate associations in a high-latitude, maritime climate","docAbstract":"Snow avalanches are a natural hazard in mountainous areas worldwide with severe impacts that include fatalities, damage to infrastructure, disruption to commerce, and landscape disturbance. Understanding long-term avalanche frequency patterns, and associated climate and weather influences, improves our understanding of how climate change may affect avalanche activity. We used dendrochronological techniques to evaluate the historical frequency of large magnitude avalanches (LMAs) in the high-latitude climate of southeast Alaska, United States. We collected 434 cross sections throughout six avalanche paths near Juneau, Alaska. This resulted in 2706 identified avalanche growth disturbances between 1720 and 2018, which allowed us to reconstruct 82 years with LMA activity across three sub-regions. By combining this tree-ring-derived avalanche data set with a suite of climate and atmospheric variables and applying a generalized linear model to fit a binomial regression, we found that February and March precipitation and the Oceanic Niño Index (ONI) were significant predictors of LMA activity in the study area. Specifically, LMA activity occurred during winters with substantial February and March precipitation and neutral or negative (cold) ONI values, while years not characterized by LMAs occur more frequently during warm winters (positive ONI values). Our examination of the climate-avalanche relationship in southeast Alaska sheds light on important climate variables and physical processes associated with LMA years. These results can be used to inform long-term infrastructure planning and avalanche mitigation operations in an urban area, such as Juneau, where critical infrastructure is subject to substantial avalanche hazard.
The decline in salmon and steelhead populations in the Columbia River Basin has been well documented, as have the decades-long, $9 billion restoration spending efforts by federal and state agencies. These efforts are mainly tied to Endangered Species Act (ESA) mandates for recovery of wild, naturally-spawning threatened or endangered fish species. The impact of these efforts remains poorly understood; many observers, including the federal courts, have long been concerned by the lack of evidence of recovery. Most studies evaluating restoration efforts have examined individual projects for specific species, reaches, or life stages, which limits the ability to make broad inferences at the basin level. There is a need to ask: is there evidence of an overall increase in wild fish abundance associated with the totality of these recovery efforts? To that end, the current study estimates fixed-effects panel regression models of adult returns of four species. Results indicate that restoration spending combined with hatchery production are associated with substantial increases in returning adult fish. Evidence of benefits to wild fish alone, however, require indirect approaches given the commingling of restoration spending with spending on hatchery releases, the impacts of spending on hatchery fish survival, and the density dependence effects of hatchery releases. To accomplish this, the models’ predicted adult returns (both hatchery and wild fish) attributed to both spending and hatchery releases are compared to independent estimates of returning hatchery fish based on hatchery survival estimates (smolt-to-adult ratios). The comparison finds the model-predicted levels of adult returns due to spending and hatchery releases do not exceed the survival-rate based estimates for hatcheries alone, so that we are unable to reject the hypothesis of no benefits to wild fish from the restoration spending.
Uncovering relationships between landscape diversity and species interactions is crucial for predicting how ongoing land-use change and homogenization will impact the stability and persistence of communities. However, such connections have rarely been quantified in nature. We coupled high-resolution river sonar imaging with annualized energetic food webs to quantify relationships among habitat diversity, energy flux, and trophic interaction strengths in large-river food-web modules that support the endangered Pallid Sturgeon. Our results demonstrate a clear relationship between habitat diversity and species interaction strengths, with more diverse foraging landscapes containing higher production of prey and a greater proportion of weak and potentially stabilizing interactions. Additionally, rare patches of large and relatively stable river sediments intensified these effects and further reduced interaction strengths by increasing prey diversity. Our findings highlight the importance of landscape characteristics in promoting stabilizing food-web architectures and provide direct relevance for future management of imperilled species in a simplified and rapidly changing world.
In the Lower Missouri River, extensive channel modifications have altered hydraulic and morphologic conditions and reduced the river's ecological integrity. One species that has been adversely affected by these changes is the pallid sturgeon (Scaphirhynchus albus). Mainstem dams on the Missouri River restrict the upstream migration of adults and limit the downstream dispersal of larvae. Channelization to facilitate commercial barge traffic has also simplified the river. The self-dredging navigation channel is a highly efficient conduit for transporting sand, which has resulted in diminished rearing habitat along the lower river. Recently, a series of experimental projects was implemented to reengineer selected bends of the Lower Missouri River with the goal of increasing the interception and retention of passively drifting age-0 sturgeon into habitats more conducive to rearing. Here, we evaluate the hydraulic performance of one of these rehabilitation projects to gain insight on the implications of these interventions for age-0 pallid sturgeon dispersal. We conducted a dye-trace experiment and complementary hydraulic and particle-tracking modeling to examine the spatial and temporal patterns of passive dispersal in and around the rehabilitated study reach. Results from both the dye-trace experiment and particle-tracking model highlight the presence of several interception pathways from the navigation channel into more suitable rearing habitat on channel margins. Moreover, our results indicate that residence times within the rearing habitat are increased in comparison to the main channel. Although we cannot provide biological evaluation at this time to assess whether the rehabilitated study bend intercepts passively drifting age-0 pallid sturgeon, our analysis shows that hydraulic conditions within the rehabilitated bend would favor interception and retention of passively drifting particles (or, presumably, larvae) from the navigation channel and into slower moving, shallow-water habitat. Moreover, our particle-tracking model provides a new capability to explore important biological transport processes across a range of flows, organisms, and river environments.
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.
","language":"English","publisher":"Wiley","doi":"10.1111/jfb.15509","usgsCitation":"Bonjour, S.M., Gido, K.B., McKinstry, M.C., Cathcart, C.N., Bogaard, M.R., Dzul, M.C., Healy, B.D., Hooley-Underwood, Z.E., Rogowski, D.L., and Yackulic, C., 2023, Migration timing and tributary use of spawning flannelmouth sucker (Catostomus latipinnis): Journal of Fish Biology, v. 103, no. 5, p. 1144-1162, https://doi.org/10.1111/jfb.15509.","productDescription":"19 p.","startPage":"1144","endPage":"1162","ipdsId":"IP-148081","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":419436,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"103","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-08-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Bonjour, Sophia M.","contributorId":317812,"corporation":false,"usgs":false,"family":"Bonjour","given":"Sophia","email":"","middleInitial":"M.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":879348,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gido, Keith B.","contributorId":317813,"corporation":false,"usgs":false,"family":"Gido","given":"Keith","email":"","middleInitial":"B.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":879349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKinstry, Mark C.","contributorId":301155,"corporation":false,"usgs":false,"family":"McKinstry","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":65322,"text":"Upper Colorado Regional Office","active":true,"usgs":false}],"preferred":false,"id":879350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cathcart, Charles N.","contributorId":317814,"corporation":false,"usgs":false,"family":"Cathcart","given":"Charles","email":"","middleInitial":"N.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":879351,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bogaard, Matthew R.","contributorId":317815,"corporation":false,"usgs":false,"family":"Bogaard","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":879352,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dzul, Maria C. 0000-0002-4798-5930 mdzul@usgs.gov","orcid":"https://orcid.org/0000-0002-4798-5930","contributorId":5469,"corporation":false,"usgs":true,"family":"Dzul","given":"Maria","email":"mdzul@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":879353,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Healy, Brian D. 0000-0002-4402-638X","orcid":"https://orcid.org/0000-0002-4402-638X","contributorId":304257,"corporation":false,"usgs":true,"family":"Healy","given":"Brian","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":879354,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hooley-Underwood, Zachary E.","contributorId":317816,"corporation":false,"usgs":false,"family":"Hooley-Underwood","given":"Zachary","email":"","middleInitial":"E.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":879355,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rogowski, David L.","contributorId":175084,"corporation":false,"usgs":false,"family":"Rogowski","given":"David","email":"","middleInitial":"L.","affiliations":[{"id":27527,"text":"AZ Game and FIsh Department","active":true,"usgs":false}],"preferred":false,"id":879356,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":879357,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70247328,"text":"70247328 - 2023 - Accurate maps of reef-scale bathymetry with synchronized underwater cameras and GNSS","interactions":[],"lastModifiedDate":"2023-07-27T16:21:43.136065","indexId":"70247328","displayToPublicDate":"2023-07-26T11:14:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Accurate maps of reef-scale bathymetry with synchronized underwater cameras and GNSS","docAbstract":"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":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois 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.
The Chesapeake Bay Land Change Model (CBLCM) is an open-source pseudo-cellular automata land change model tailored for loose coupling with watershed models. 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.
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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
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
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. M.","contributorId":317704,"corporation":false,"usgs":false,"family":"Ciarniello","given":"L.","email":"","middleInitial":"M.","affiliations":[{"id":69132,"text":"Aklak Wildlife Consulting","active":true,"usgs":false}],"preferred":false,"id":879091,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deacy, William W.","contributorId":287298,"corporation":false,"usgs":false,"family":"Deacy","given":"William","email":"","middleInitial":"W.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":879092,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heard, D. 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":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.
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":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico 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":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":5069,"text":"Office of the AD Core Science Systems","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}]}} ,{"id":70255163,"text":"70255163 - 2023 - Conserving habitat for migratory ungulates: How wide is a migration corridor?","interactions":[],"lastModifiedDate":"2024-06-14T13:32:12.209183","indexId":"70255163","displayToPublicDate":"2023-07-23T08:23:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Conserving habitat for migratory ungulates: How wide is a migration corridor?","docAbstract":"Climate-driven permafrost thaw can release ancient carbon to the atmosphere, begetting further warming in a positive feedback loop. Polar ice core data and young radiocarbon ages of dissolved methane in thermokarst lakes have challenged the importance of this feedback, but field studies did not adequately account for older methane released from permafrost through bubbling. We synthesized panarctic isotope and emissions datasets to derive integrated ages of panarctic lake methane fluxes. Methane age in modern thermokarst lakes (3132 ± 731 years before present) reflects remobilization of ancient carbon. Thermokarst-lake methane emissions fit within the constraints imposed by polar ice core data. Younger, albeit ultimately larger sources of methane from glacial lakes, estimated here, lagged those from thermokarst lakes. Our results imply that panarctic lake methane release was a small positive feedback to climate warming, comprising up to 17% of total northern hemisphere sources during the deglacial period.
Habitat and corridor mapping are key components of many conservation programs. Grizzly bear populations in the continental US are fragmented and connectivity among federal recovery areas is a conservation goal. Building on recent work, we modeled movements to predict areas of connectivity, using integrated step selection functions (iSSFs) developed from GPS-collared grizzly bears (F = 46, M = 19) in the Northern Continental Divide Ecosystem (NCDE). We applied iSSFs in a >300,000 km2 area including the NCDE, Cabinet–Yaak (CYE), Bitterroot (BE), and Greater Yellowstone (GYE) Ecosystems. First, we simulated directed movements (randomized shortest paths with 3 levels of exploration) between start and end nodes across populations. Second, we simulated undirected movements from start nodes in the NCDE, CYE, or GYE (no predetermined end nodes). We summarized and binned results as classes 1 (lowest relative predicted use) – 10 (highest relative predicted use) and evaluated predictions using 127 outlier grizzly bear locations. Connectivity pathways were primarily associated with mountainous areas and secondarily with river and stream courses in open valleys. Values at outlier locations indicated good model fit and mean classes at outlier locations (≥7.4) and Spearman rank correlations (≥0.87) were highest for undirected simulations and directed simulations with the highest level of exploration. Our resulting predictive maps can facilitate on-the-ground application of this research for prioritizing habitat conservation, human-bear conflict mitigation, and transportation planning. Additionally, our overall modeling approach has utility for myriad species and conservation applications.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2023.110199","usgsCitation":"Sells, S.N., Costello, C., Lukacs, P., Roberts, L., and Vinks, M., 2023, Predicted connectivity pathways between grizzly bear ecosystems in western Montana: Biological Conservation, v. 284, 110199, 14 p., https://doi.org/10.1016/j.biocon.2023.110199.","productDescription":"110199, 14 p.","ipdsId":"IP-147522","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":442688,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2023.110199","text":"Publisher Index Page"},{"id":429885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.95053391508199,\n 44.43718455079485\n ],\n [\n -111.00373928161369,\n 44.654761054970265\n ],\n [\n -111.03818726935785,\n 45.07387870212517\n ],\n [\n -108.85212263919709,\n 45.04832534471231\n ],\n [\n -108.66626782395645,\n 49.03152143147685\n ],\n [\n -116.13232385049233,\n 48.92723714245324\n ],\n [\n -116.03762573536355,\n 47.98615190263325\n ],\n [\n -115.57692588139909,\n 47.339026847952084\n ],\n [\n -114.54184801583628,\n 46.55145022278339\n ],\n [\n -114.48564988684791,\n 45.576847377601254\n ],\n [\n -113.90424702051097,\n 45.6284093642955\n ],\n [\n -112.95053391508199,\n 44.43718455079485\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"284","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sells, Sarah Nelson 0000-0003-4859-7160","orcid":"https://orcid.org/0000-0003-4859-7160","contributorId":302377,"corporation":false,"usgs":true,"family":"Sells","given":"Sarah","email":"","middleInitial":"Nelson","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costello, C.M.","contributorId":338295,"corporation":false,"usgs":false,"family":"Costello","given":"C.M.","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":903097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lukacs, P.M.","contributorId":338298,"corporation":false,"usgs":false,"family":"Lukacs","given":"P.M.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":903098,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roberts, L.L.","contributorId":338301,"corporation":false,"usgs":false,"family":"Roberts","given":"L.L.","email":"","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":903099,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vinks, M.A.","contributorId":338305,"corporation":false,"usgs":false,"family":"Vinks","given":"M.A.","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":903100,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70247092,"text":"70247092 - 2023 - Prolonged drought in a northern California coastal region suppresses wildfire impacts on hydrology","interactions":[],"lastModifiedDate":"2024-09-16T16:43:11.061729","indexId":"70247092","displayToPublicDate":"2023-07-21T09:31:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Prolonged drought in a northern California coastal region suppresses wildfire impacts on hydrology","docAbstract":"Wildfires naturally occur in many landscapes, however they are undergoing rapid regime shifts. Despite the emphasis in the literature on the most severe hydrological responses to wildfire, there remains a knowledge gap on the thresholds of wildfire (i.e. burned area/drainage area ratio, BAR) required to initiate hydrological responses. We investigated hydrological changes in the Russian River Watershed (RRW) in California, a coastal, Mediterranean, drought-prone, wildfire-adapted ecosystem, following ten wildfires that burned 30% of the watershed. Our findings suggest that sub-watersheds of the RRW have not burned beyond an intrinsic, unknown, threshold required to initiate change. Using paired watersheds, we examined spatiotemporal patterns of pre-and-post wildfire hydrology with a rainfall-runoff hydrological model. Even though these successive wildfires burned 1-50% of each sub-watershed (1-30% at moderate/high severity), we found little evidence of wildfire-related shifts in hydrology. As a function of BAR, wildfire imposed limited effects on runoff ratios (runoff/precipitation) and runoff residuals (observations - model simulations). Our findings that post-wildfire runoff enhancements asymptote beyond 30% burn indicate that when a watershed is burned beyond a certain threshold, the magnitude of the hydrologic response no longer increases. Drought and storm conditions explained much of the variability observed in streamflow, whereas wildfire explained only moderate variability in streamflow even when wildfire accounted for >45% BAR. While the BAR in the RRW was sufficiently beyond previously reported minimum disturbance thresholds (>20% burned forest), the lack of hydrological response is attributed to buffering effects of wildfire adaptation and drought factors that are unique to Mediterranean ecoregions.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR034206","usgsCitation":"Newcomer, M.E., Underwood, J.C., Murphy, S.F., Ulrich, C., Schram, T., Maples, S.R., Pena, J., Siirila-Woodburn, E.R., Trotta, M., Jasperse, J., Seymour, D., and Hubbard, S., 2023, Prolonged drought in a northern California coastal region suppresses wildfire impacts on hydrology: Water Resources Research, v. 59, no. 8, e2022WR034206, 23 p., https://doi.org/10.1029/2022WR034206.","productDescription":"e2022WR034206, 23 p.","ipdsId":"IP-147415","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":442702,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022wr034206","text":"Publisher Index Page"},{"id":419247,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Russian River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.58166191175413,\n 39.66438164966229\n ],\n [\n -123.52362681286694,\n 38.86220749551856\n ],\n [\n -122.91949120418995,\n 38.952501194302044\n ],\n [\n -123.01324021008476,\n 39.6265634050871\n ],\n [\n -123.58166191175413,\n 39.66438164966229\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"59","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Newcomer, Michelle E.","contributorId":317249,"corporation":false,"usgs":false,"family":"Newcomer","given":"Michelle","email":"","middleInitial":"E.","affiliations":[{"id":68983,"text":"Lawrence Berkeley National Laboratory, Earth & Environmental Sciences Area","active":true,"usgs":false}],"preferred":false,"id":878842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Underwood, Jennifer C. 0000-0002-2702-0410 jcunder@usgs.gov","orcid":"https://orcid.org/0000-0002-2702-0410","contributorId":294555,"corporation":false,"usgs":true,"family":"Underwood","given":"Jennifer","email":"jcunder@usgs.gov","middleInitial":"C.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":878843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":878844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ulrich, Craig","contributorId":317250,"corporation":false,"usgs":false,"family":"Ulrich","given":"Craig","affiliations":[{"id":68983,"text":"Lawrence Berkeley National Laboratory, Earth & Environmental Sciences Area","active":true,"usgs":false}],"preferred":false,"id":878845,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schram, Todd","contributorId":317251,"corporation":false,"usgs":false,"family":"Schram","given":"Todd","email":"","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878846,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maples, Stephen R.","contributorId":317252,"corporation":false,"usgs":false,"family":"Maples","given":"Stephen","email":"","middleInitial":"R.","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878847,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pena, Jasquelin","contributorId":317253,"corporation":false,"usgs":false,"family":"Pena","given":"Jasquelin","email":"","affiliations":[{"id":68983,"text":"Lawrence Berkeley National Laboratory, Earth & Environmental Sciences Area","active":true,"usgs":false}],"preferred":false,"id":878848,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Siirila-Woodburn, Erica R.","contributorId":317254,"corporation":false,"usgs":false,"family":"Siirila-Woodburn","given":"Erica","email":"","middleInitial":"R.","affiliations":[{"id":68983,"text":"Lawrence Berkeley National Laboratory, Earth & Environmental Sciences Area","active":true,"usgs":false}],"preferred":false,"id":878849,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Trotta, Marcus","contributorId":317255,"corporation":false,"usgs":false,"family":"Trotta","given":"Marcus","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878850,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jasperse, Jay","contributorId":317256,"corporation":false,"usgs":false,"family":"Jasperse","given":"Jay","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878851,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Seymour, Donald","contributorId":317257,"corporation":false,"usgs":false,"family":"Seymour","given":"Donald","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878852,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hubbard, Susan S.","contributorId":317258,"corporation":false,"usgs":false,"family":"Hubbard","given":"Susan S.","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":878853,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70246679,"text":"sir20235042 - 2023 - Selenium hazards in the Salton Sea environment—Summary of current knowledge to inform future wetland management","interactions":[],"lastModifiedDate":"2026-03-06T21:38:07.222047","indexId":"sir20235042","displayToPublicDate":"2023-07-20T14:20:47","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5042","displayTitle":"Selenium Hazards in the Salton Sea Environment—Summary of Current Knowledge to Inform Future Wetland Management","title":"Selenium hazards in the Salton Sea environment—Summary of current knowledge to inform future wetland management","docAbstract":"Quaternary marine and continental shales in the western United States are sources of selenium that can be loaded into the aquatic environment through mining, agricultural, and energy production processes. The mobilization of selenium from shales through agricultural irrigation has been recognized since the 1930s; however, discovery of deformities in birds and other wildlife using agricultural habitats during the 1980s spurred studies to determine the extent and effects of the contamination. Through these early studies, researchers determined that biota in the Salton Sea drainage basin was at risk from legacy selenium contamination in the Colorado River watershed.
The Salton Sea and its surrounding managed and unmanaged wetlands provide vital inland habitat and trophic support for diverse assemblages of resident and migratory wildlife, and understanding regional selenium hazards for these trust species is a priority for many Federal and State agencies. The modern Salton Sea is a shallow, landlocked saline lake in Riverside and Imperial Counties (not shown) of California that is sustained by irrigation return and perennial river inflow. Changes in water transfer agreements under the 2003 Quantification Settlement Agreement (QSA) have resulted in reduced irrigation flow, declining lake levels, and the evolution of unmanaged wetlands in areas where drains and rivers no longer reach the Salton Sea. These wetlands provide additional habitat for some species of concern, but their potential to increase selenium hazards for trust species is largely unknown.
From the 1980s to 2020, efforts to document selenium contamination and effects throughout the region have resulted in a considerable amount of selenium data from the Salton Sea and its surrounding drainage basin; however, no long-term (greater than 20 years), consistent sampling program has been established, and all data have been collected by different entities using a variety of protocols and analytical techniques. This lack of coordination has been previously documented in regional management plans and has led to difficulty in reliably assessing selenium hazards in the Salton Sea environment. This report provides a summary of the available disparate selenium information collected from water, sediment, and biota in the Salton Sea region since the 1980s and to identify data gaps that need to be filled to understand the potential effects of selenium on species of concern, including federally endangered desert pupfish (Cyprinodon macularius) and Yuma Ridgway’s Rail (Rallus obsoletus yumanensis; formerly Yuma Clapper Rail, Rallus longirostris yumanensis).
Available data from the Salton Sea drainage basin show that water from the Colorado River has the lowest selenium concentration of all surface water sources. All other surface water flowing into the Salton Sea has elevated selenium concentrations due to evaporation and evapotranspiration that occurs in agricultural fields and associated water delivery infrastructure or leaching of selenium from irrigated farmland soils. The Salton Sea has lower selenium concentrations because of various biogeochemical processes that recycle selenium into the sediment or volatilize it to the atmosphere; however, these mechanisms are not well defined, and it is not clear if selenium cycling will change in response to possible changes in the oxidation state of the Salton Sea bottom waters as water levels decline. Agricultural drains have the highest average selenium concentrations, but few drains have been sampled since changes in irrigation practices have occurred (due to the 2003 QSA). Groundwater selenium concentrations are variable; some wells south of the Salton Sea have selenium concentrations as high as 300 micrograms per liter (µg/L), whereas selenium concentrations are below detection in other wells. Groundwater and surface-water geothermal discharge zones around the margins of the Salton Sea and in unmanaged wetlands have not been studied in detail, and published selenium measurements are not available for these surface features.
Selenium concentrations in the sediment of the Salton Sea drainage basin are highest in wetland particulate organic matter and the Salton Sea lakebed, indicating that removal of selenium from the water to the sediment has been a primary mechanism for keeping selenium concentrations low in the water column. Sediment selenium concentrations in wetlands are lower than in the Salton Sea but higher than inflowing drains and rivers, indicating the lentic wetland sites also may be important sinks for selenium because of biogeochemical processes. Sediment selenium data have not been collected in agricultural drains since changes in irrigation practices occurred (due to the 2003 QSA), and it is unknown if selenium sequestration from the water column has changed in these systems.
We divided biological data into broad taxonomic categories, including primary producers, invertebrates, herpetofauna, mammals, fishes, and birds to facilitate evaluation of selenium concentrations and spatiotemporal trends observed in the Salton Sea. Overall, selenium concentrations were substantially greater in algae samples compared to all vascular plant samples combined. Median selenium concentrations in several invertebrate taxa (Chironomidae, Formicidae, Corixidae, Corbiculidae and Nereididae, and Decapoda) exceeded the maximum suggested dietary threshold of 3.0–4.0 micrograms per gram (µg/g) dry weight (dw) for predators consuming invertebrates in aquatic food webs. The greatest number of samples were collected from fish, and selenium distributions among species and locations showed that the range for most samples was lower than the U.S. Environmental Protection Agency selenium criterion for aquatic life (8.5 µg/g dw whole body, 11.3 µg/g dw fillets). The median selenium concentrations for whole body fish were below the selenium criterion in most locations, except for bairdiella (Bairdiella icistia) from the Salton Sea and irrigation drains, a few individual tilapia spp. (family Cichlidae, including genera Tilapia, Oreochromis, and their hybrids) from the river and river outlets, and several western mosquitofish (Gambusia affinis) and sailfin molly (Poecilia latipinna) from irrigation drain outlets. For avian samples combined among years and locations, median selenium concentrations in livers from all families except waders and Ibis (family Threskiornithidae) were higher than levels expected to cause selenium toxicosis (10–20 µg/g dw), and all median egg concentrations were above or near 6.0 μg/g dw, which is a conservative threshold value for reproductive impairment.
Most knowledge gaps we identified for water, sediment, and biota were interrelated, and the use of integrated approaches to address knowledge gaps can provide greater insight into the drivers behind selenium hazards. Integrated water, sediment, and biota studies could help identify cost-effective management solutions that serve multiple purposes. A comprehensive analysis of the hydrology, biogeochemistry, and food-web processes in wetlands and other habitats can inform predictive models to identify drivers of selenium bioavailability, uptake from the environment and subsequent trophic transfer, ultimately forming the basis for experimental habitat management manipulations to minimize selenium hazards to wildlife. Furthermore, a comprehensive, long-term sampling and analytical laboratory plan would enable comparison of data among different entities that are sampling at the Salton Sea. Such efforts are well suited to help fill knowledge gaps that preclude understanding of selenium hazards and future management options for biota using Salton Sea habitats, including newly formed wetlands throughout the region.
All data compiled for this report are available in two U.S. Geological Survey data releases: Groover and others (2022) for water and sediment samples and De La Cruz and others (2022) for biological samples. The data releases include all publicly available data for selenium concentrations in water, sediment, and biological samples collected in and around the Salton Sea, including the Coachella and Imperial Valleys. The data releases also include previously unpublished data.
Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Riverbank groundwater discharge faces are spatially extensive areas of preferential seepage that are exposed to air at low river flow. Some conceptual hydrologic models indicate discharge faces represent the spatial convergence of highly variable age and length groundwater flowpaths, while others indicate greater consistency in source groundwater characteristics. Our detailed field investigation of preferential discharge points nested across mainstem riverbank discharge faces was accomplished by: (1) leveraging new temperature-based recursive estimation (extended Kalman Filter) modelling methodology to evaluate seasonal, diurnal, and event-driven groundwater flux patterns, (2) developing a multi-parameter toolkit based on readily measured attributes to classify the general source groundwater flowpath depth and flowpath length scale, and, (3) assessing whether preferential flow points across discharge faces tend to represent common or convergent groundwater sources. Five major groundwater discharge faces were mapped along the Farmington River, CT, United States using thermal infrared imagery. We then installed vertical temperature profilers directly into 39 preferential discharge points for 4.5 months to track vertical discharge flux patterns. Monthly water chemistry was also collected at the discharge points along with one spatial synoptic of stable isotopes of water and dissolved radon gas. We found pervasive evidence of shallow groundwater sources at the upstream discharge faces along a wide valley section with deep bedrock, as primarily evidenced by pronounced diurnal discharge flux patterns. Discharge flux seasonal trends and bank storage transitions during large river flow events provided further indication of shallow, local sources. In contrast, downstream discharge faces associated with near surface cross cutting bedrock exhibited deep and regional source flowpath characteristics such as more stable discharge patterns and temperatures. However, many neighbouring points across discharge faces had similar discharge flux patterns that differed in chloride and radon concentrations, indicating the additional effects of localized flowpath heterogeneity overprinting on larger scale flowpath characteristics.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14939","usgsCitation":"Haynes, A., Briggs, M., Moore, E., Jackson, K., Knighton, J., Rey, D., and Helton, A., 2023, Shallow and local or deep and regional? Inferring source groundwater characteristics across mainstem riverbank discharge faces: Hydrological Processes, v. 37, no. 7, e14939, 19 p., https://doi.org/10.1002/hyp.14939.","productDescription":"e14939, 19 p.","ipdsId":"IP-151076","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":442704,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.14939","text":"Publisher Index Page"},{"id":419349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut","otherGeospatial":"Farmington River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.716667,\n 41.933\n ],\n [\n -72.8333,\n 41.933\n ],\n [\n -72.8333,\n 41.7833\n ],\n [\n -72.716667,\n 41.7833\n ],\n [\n -72.716667,\n 41.933\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"37","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Haynes, Adam","contributorId":216657,"corporation":false,"usgs":false,"family":"Haynes","given":"Adam","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":222759,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":879121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Eric","contributorId":216658,"corporation":false,"usgs":false,"family":"Moore","given":"Eric","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Kevin","contributorId":317715,"corporation":false,"usgs":false,"family":"Jackson","given":"Kevin","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879123,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knighton, James","contributorId":317716,"corporation":false,"usgs":false,"family":"Knighton","given":"James","email":"","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879124,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rey, David M. 0000-0003-2629-365X","orcid":"https://orcid.org/0000-0003-2629-365X","contributorId":211848,"corporation":false,"usgs":true,"family":"Rey","given":"David M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":879125,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Helton, Ashley","contributorId":219741,"corporation":false,"usgs":false,"family":"Helton","given":"Ashley","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879126,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}