To refine the use of graptolite and solid bitumen as thermal proxies at overmature conditions, we evaluated their evolution via Raman and infrared (IR) spectroscopies, reflectance, and geochemical screening using high-temperature pyrolysis experiments in comparison to naturally matured samples. Naturally matured samples included marine shales from the overmature Upper Ordovician Wufeng-Lower Silurian Longmaxi Formations (herein referred to as Wufeng-Longmaxi) of the Sichuan Basin, China. Immature samples for pyrolysis experiments included Mesoproterozoic (Ectasian) Xiamaling marine shale from Hebei, China (graptolite absent) and graptolite-bearing Ordovician (Tremadocian) Alum marine shale from Grönhögen, Sweden. Pyrolysis experiments at 360 °C for 10 days and 27 days (hydrous conditions), and 450 °C 3 days, 550 °C 3 days, and 550 °C 10 days (all anhydrous) created Xiamaling and Alum residues with solid bitumen and graptolite, respectively, of similar and higher maturity compared to the naturally matured Wufeng-Longmaxi samples. Compositional proxies from IR spectroscopy were inconclusive. Raman spectral properties including Raman band separation (RBS) and the full-width at half-maximum of the G-band (G-FWHM) exhibited robust positive and inverse relationships with increasing reflectance in pyrolysis residues, respectively. RBS values were systematically lower in artificially matured samples versus naturally matured samples with equivalent reflectance values, whereas G-FWHM values were systematically higher. This observation indicates that the limited duration or low internal reactor pressure of pyrolysis experiments is insufficient to allow alignment or ordering of aromatic carbon arrays in both organic matter types, relative to natural maturation occurring at geologic time scales. Reflectance of graptolite was typically higher than co-occurring solid bitumen in Wufeng-Longmaxi samples and the untreated Alum sample, suggesting inherently higher aromaticity. However, aromaticity in pyrolysis residues was systematically higher in solid bitumen compared to graptolite with equivalent reflectance values, indicating a higher kinetic barrier to molecular rearrangement in graptolite versus solid bitumen. These data further clarify differences in the molecular evolution of sedimentary organic matter in natural versus analogue laboratory environments and distinguish the properties of individual organic matter types in response to thermal stress.
Dam removals are occurring more frequently with the rising cost of maintaining aging infrastructure, public safety concerns, and growing interest in river restoration. So far, most dam-removals have been unsystematic in their approach. Given the several thousand dam removals expected over the coming decades, a systematic approach to plan future dam removals holds potential for aligning and delivering multiple benefits. Despite multi-sector factors driving decision-making, most existing prioritization frameworks tend to operate within single or related disciplines. Here we present a hierarchical, multi-disciplinary decision-support framework to prioritize dam removals based on opportunistic factors (Tier 1), hydro-ecological variables (Tier 2), and socio-cultural considerations (Tier 3). This framework integrates multiple decision criteria under data availability constraints, incorporates value-driven weights, and can be applied to a portfolio of dams at various spatial scales. The final output facilitates the identification of dam removal projects that align opportunistic, environmental, and social benefits. We recommend the application of this framework as a critical first step to identifying high-priority candidates for removal, recognizing that removal decisions will ultimately require detailed feasibility studies and stakeholder engagement. To illustrate its utility, we apply this framework to California's North Coast region and identify a small number of “good” candidates to be considered for removal. We conclude with recommendations for filling critical knowledge gaps and advancing systematic dam removal planning in the United States and beyond.
","language":"English","publisher":"Springer","doi":"10.1016/j.envc.2023.100731","usgsCitation":"Jumani, S., Andrews, L., Grantham, T., McKay, S.K., Duda, J.J., and Howard, J., 2023, A decision-support framework for dam removal planning and its application in northern California: Environmental Challenges, v. 12, 100731, 12 p., https://doi.org/10.1016/j.envc.2023.100731.","productDescription":"100731, 12 p.","ipdsId":"IP-148476","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":443247,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envc.2023.100731","text":"Publisher Index Page"},{"id":417640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.77091855129396,\n 36.7466893389355\n ],\n [\n -116.9691520832261,\n 36.776141248769136\n ],\n [\n -119.98785211712357,\n 39.006796288474135\n ],\n [\n -119.95653836939476,\n 42.05461941906097\n ],\n [\n -124.38794543960415,\n 42.0261045664181\n ],\n [\n -124.4642262183686,\n 41.804019222742454\n ],\n [\n -124.32721924215684,\n 41.633585678003044\n ],\n [\n -124.17850589546725,\n 41.49840485955721\n ],\n [\n -124.27747182589826,\n 41.15089716990744\n ],\n [\n -124.27104710057688,\n 40.82986818953012\n ],\n [\n -124.56779043285218,\n 40.4901547526143\n ],\n [\n -124.43691360782503,\n 40.11700972954404\n ],\n [\n -124.12543123329115,\n 39.94332674949021\n ],\n [\n -123.89676200625902,\n 39.585584296391346\n ],\n [\n -123.97016648621855,\n 39.277039146418616\n ],\n [\n -123.83772283002048,\n 38.98565895430556\n ],\n [\n -123.79848226911275,\n 38.77121252330733\n ],\n [\n -123.16760955324685,\n 38.33406661818478\n ],\n [\n -123.04572722537378,\n 38.155575864615116\n ],\n [\n -123.10923482050586,\n 37.87049270762934\n ],\n [\n -122.65845531971604,\n 37.72170323809223\n ],\n [\n -122.44361749477085,\n 37.06649531483684\n ],\n [\n -122.16970344342997,\n 36.866248324182635\n ],\n [\n -121.77091855129396,\n 36.7466893389355\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":874355,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andrews, Lucy","contributorId":305996,"corporation":false,"usgs":false,"family":"Andrews","given":"Lucy","email":"","affiliations":[{"id":66340,"text":"University of California Berkeley, Berkeley, California, USA","active":true,"usgs":false}],"preferred":false,"id":874356,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grantham, Theodore E.","contributorId":198855,"corporation":false,"usgs":false,"family":"Grantham","given":"Theodore E.","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":874357,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKay, S. Kyle","contributorId":169086,"corporation":false,"usgs":false,"family":"McKay","given":"S.","email":"","middleInitial":"Kyle","affiliations":[],"preferred":false,"id":874358,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":874359,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Howard, Jeanette K.","contributorId":297483,"corporation":false,"usgs":false,"family":"Howard","given":"Jeanette K.","affiliations":[{"id":27697,"text":"The Nature Conservency","active":true,"usgs":false}],"preferred":false,"id":874360,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70245117,"text":"70245117 - 2023 - Living with wildfire in Emigration Canyon, Utah: 2022 data report","interactions":[],"lastModifiedDate":"2023-06-16T12:17:31.168159","indexId":"70245117","displayToPublicDate":"2023-06-01T07:14:58","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Living with wildfire in Emigration Canyon, Utah: 2022 data report","docAbstract":"Located in North Central Utah, Emigration Canyon is a prominent and historic canyon that runs northeast from Salt Lake City into the higher elevations of the Wasatch Mountains. The Wasatch Range is characterized by steep, rocky slopes and 26-44 millimeters of annual rainfall, both of which contribute to a high threat of wildfire. The area’s landscape is diverse with oak woodland at the lower elevations up to a conifer forest type including ponderosa pine, Douglas-fir, and subalpine fir. The Utah Wildfire Risk Assessment Portal (UWRAP) rates the fire danger in Emigration Canyon as “Extreme.” Resultantly, the Utah Division of Forestry, Fire & State Lands, as well as adjacent land management agencies, have identified this wildland-urban interface (WUI) zone as a high priority. The Utah Division of Forestry, Fire & State Lands website describes WUI as “the zone where structures and other human development meet and intermingle with undeveloped wildland or vegetative fuels.”
","language":"English","publisher":"USDA Forest Service","doi":"10.2737/RMRS-RN-98","usgsCitation":"Goolsby, J., Brenkert-Smith, H., Reid, D., Meldrum, J., Champ, P.A., Barth, C.M., Donovan, C., and Wagner, C., 2023, Living with wildfire in Emigration Canyon, Utah: 2022 data report, 144 p., https://doi.org/10.2737/RMRS-RN-98.","productDescription":"144 p.","ipdsId":"IP-146796","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":443250,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2737/rmrs-rn-98","text":"Publisher Index Page"},{"id":418157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Emigration Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.83999933907488,\n 40.79599357420403\n ],\n [\n -111.83999933907488,\n 40.723990571002446\n ],\n [\n -111.69346339481368,\n 40.723990571002446\n ],\n [\n -111.69346339481368,\n 40.79599357420403\n ],\n [\n -111.83999933907488,\n 40.79599357420403\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Goolsby, Julia 0000-0002-2229-5685","orcid":"https://orcid.org/0000-0002-2229-5685","contributorId":295471,"corporation":false,"usgs":false,"family":"Goolsby","given":"Julia","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":875559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brenkert-Smith, Hannah 0000-0001-6117-8863","orcid":"https://orcid.org/0000-0001-6117-8863","contributorId":195485,"corporation":false,"usgs":false,"family":"Brenkert-Smith","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":875560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reid, Dax","contributorId":310416,"corporation":false,"usgs":false,"family":"Reid","given":"Dax","email":"","affiliations":[{"id":67180,"text":"Utah Division of Forestry, Fire and State Lands","active":true,"usgs":false}],"preferred":false,"id":875561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":875562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Champ, Patricia A.","contributorId":195486,"corporation":false,"usgs":false,"family":"Champ","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":875563,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barth, Christopher M.","contributorId":195487,"corporation":false,"usgs":false,"family":"Barth","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":875564,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Donovan, Colleen","contributorId":240586,"corporation":false,"usgs":false,"family":"Donovan","given":"Colleen","email":"","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":875565,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wagner, Carolyn","contributorId":240587,"corporation":false,"usgs":false,"family":"Wagner","given":"Carolyn","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":875566,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70244124,"text":"70244124 - 2023 - Estimating streamflow permanence with the watershed erosion prediction project model: Implications for surface water presence modeling and data collection","interactions":[],"lastModifiedDate":"2023-06-09T15:27:22.153327","indexId":"70244124","displayToPublicDate":"2023-06-01T07:01:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating streamflow permanence with the watershed erosion prediction project model: Implications for surface water presence modeling and data collection","docAbstract":"Many data collection efforts and modeling studies have focused on providing accurate estimates of streamflow while fewer efforts have sought to identify when and where surface water is present and the duration of surface water presence in stream channels, hereafter referred to as streamflow permanence. While physically-based hydrological models are frequently used to explore how water quantity may be influenced by various climatic and basin characteristics at local, regional, national, and global extents they are less often used to explore streamflow permanence. Herein, the Watershed Erosion Prediction Project (WEPP) hydrological model is applied to watersheds in the humid H. J. Andrews Experimental Forest (HJA) and watersheds of the arid Willow and Whitehorse creeks (WW), both in Oregon, to simulate daily (WW) and annual (HJA and WW) streamflow permanence. One thousand parameter combinations were tested to calibrate WEPP to observed streamflow in the HJA watersheds and one hundred parameter combinations were tested to calibrate WEPP to observed surface water presence time series data in WW watersheds. When calibrated to observed streamflow, WEPP correctly classified annual streamflow permanence for 83% of HJA stream reaches. In the WW, WEPP simulations correctly classified 63–93% of daily streamflow permanence observations and 59-87% of annual streamflow permanence classifications. Inclusion of a dry-day threshold (the maximum number of days a stream reach could be modeled ‘dry’ but still classified as permanent for the year) improved annual accuracy in three WW watersheds from 2-10%. Parameter sets that produced the best daily accuracies in WW resulted in poor annual accuracies. Results highlight the importance of evaluating physically-based streamflow permanence models on both permanent and nonpermanent streams at daily and annual time scales to ensure evaluation metrics are appropriate for interpretation purposes. Additionally, results suggest that strategic collection of surface water presence observations and streamflow observations may support robust calibration of physically based models to simulate streamflow permanence moving forward.
Two decades of drought in the southwestern USA are spurring concerns about increases in wind erosion, dust emissions, and associated impacts on ecosystems, agriculture, human health, and water supply. Different avenues of investigation into primary drivers of wind erosion and dust have yielded mixed results depending on the spatial and temporal sensitivity of the evidence. We monitored passive aeolian sediment traps from 2017 to 2020 across eighty-one sites near Moab UT to understand patterns of sediment flux. At measurement sites we collated climate, soil, topography and vegetation spatial layers to better understand the context of wind erosion and then combine these data with field observations of land use in models to characterize the influence of cattle grazing, oil and gas well pads, and vehicle/heavy equipment disturbance that potentially drive both exposure of bare soil and increases in erodible sediment supply that increase vulnerability to erosion. Disturbed areas with low soil calcium carbonate content yielded high sediment transport in dry years, but notably areas with little disturbance and low bare soil exposure had much less activity. Cattle grazing had the largest land use association with erosional activity with analyses suggesting that both herbivory and trampling from cattle could be drivers. The amount and distribution of bare soil exposure from new sub-annual fractional cover remote sensing products proved very helpful in mapping erosion, and new predictive maps informed by field data are presented to help depict spatial patterns of wind erosion activity. Our results suggest that despite the magnitude of current droughts, minimizing surface disturbance in vulnerable soils can mitigate a large portion of dust emissions. Results can help managers identify eroding areas where disturbance reduction and soil surface protection measures can be prioritized.
Deep Springs Valley (DSV) is a hydrologically isolated valley between the White and Inyo mountains that is commonly excluded from regional paleohydrology and paleoclimatology. Previous studies showed that uplift of Deep Springs ridge (informal name) by the Deep Springs fault defeated streams crossing DSV and hydrologically isolated the valley sometime after eruption of the Pleistocene Bishop Tuff (0.772 Ma). Here, we present tephrochronology and clast counts that reaffirms interruption of the Pliocene–Pleistocene hydrology and formation of DSV during the Pleistocene. Paleontology and infrared stimulated luminescence (IRSL) dates indicate a freshwater lake inundated Deep Springs Valley from ca. 83–61 ka or during Late Pleistocene Marine Isotope Stages 5a (MIS 5a; ca. 82 ka peak) and 4 (MIS 4; ca. 71–57 ka). The age of pluvial Deep Springs Lake coincides with pluvial lakes in Owens Valley and Columbus Salt Marsh and documents greater effective precipitation in southwestern North America during MIS 5a and MIS 4. In addition, we hypothesize that Deep Springs Lake was a balanced-fill lake that overflowed into Eureka Valley via the Soldier Pass wind gap during MIS 5a and MIS 4. DSV hydrology has implications for dispersal and endemism of the Deep Springs black toad (Anaxyrus exsul).
ABSTRACT: Thermal refuges are habitats used by species for behavioral thermoregulation. These habitats can be highly dynamic and are often influenced by fluctuations in local climate. When protected species require thermal refuges, it is necessary to identify stable and high-quality areas by evaluating species use in response to variation in thermal refuge quality. Here, we assessed behavioral thermoregulation in the Florida manatee Trichechus manatus latirostris, a cold-intolerant marine mammal. Using metrics from ectotherm physiology, we evaluated thermal quality of 2 refuge types (passive thermal basins, natural springs) in 2 areas of their distribution. Thermal refuge quality was assessed with respect to the lower critical threshold of the manatee (20°C) and the surrounding ambient temperatures and compared between refuge types. We used GPS locations of manatees to quantify visits to refuges and calculated total visit duration in each refuge by individual manatees. At natural springs, we found a negative correlation between visit duration and ambient temperature during cold weather; visit duration also increased with the temperature differential between the spring and the lower critical thermal threshold. Visit duration at passive thermal basins was negatively correlated with the thermal differential between the refuge and the lower critical thermal threshold. The relationship between thermal refuge quality and time-use metrics sheds light on the potential implications of habitat degradation on animal energetics and behavior. Given these results, focusing on potential key refuges in each system may inform targeted management and habitat restoration efforts to maintain adequate thermal refuge environments for this listed species.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01245","usgsCitation":"Haase, C.G., Fletcher, R.J., Slone, D., Reid, J.P., and Butler, S.M., 2023, Quality of thermal refuges influences use by the cold-intolerant Florida manatee: Endangered Species Research, v. 51, p. 89-101, https://doi.org/10.3354/esr01245.","productDescription":"13 p.; 3 Data Releases","startPage":"89","endPage":"101","ipdsId":"IP-139369","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":443261,"rank":5,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01245","text":"Publisher Index Page"},{"id":417958,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":419357,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A6YY9G","text":"GPS Telemetry and other data sets of Florida manatees from Crystal River, FL 2006-2018","linkFileType":{"id":5,"text":"html"}},{"id":419356,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98C25SK","text":"Manatee tracking, sighting and environmental data from the Northern Gulf of Mexico, 2013-2019","linkFileType":{"id":5,"text":"html"}},{"id":419355,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QT5VC1","text":"GPS telemetry of Florida manatees and riverine water temperatures from southwest Florida 2002-2015","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.45336286015565,\n 30.458124251618187\n ],\n [\n -84.45336286015565,\n 29.08554912434488\n ],\n [\n -82.58648806675804,\n 29.08554912434488\n ],\n [\n -82.58648806675804,\n 30.458124251618187\n ],\n [\n -84.45336286015565,\n 30.458124251618187\n ]\n ]\n ],\n \"type\": \"Polygon\"\n },\n \"id\": 0\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.94955431371608,\n 26.167155569976586\n ],\n [\n -81.94955431371608,\n 25.097882739812448\n ],\n [\n -80.543907410452,\n 25.097882739812448\n ],\n [\n -80.543907410452,\n 26.167155569976586\n ],\n [\n -81.94955431371608,\n 26.167155569976586\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Haase, Catherine G.","contributorId":306088,"corporation":false,"usgs":false,"family":"Haase","given":"Catherine","email":"","middleInitial":"G.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":875057,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fletcher, Robert J. Jr.","contributorId":300712,"corporation":false,"usgs":false,"family":"Fletcher","given":"Robert","suffix":"Jr.","middleInitial":"J.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":875058,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Slone, Daniel 0000-0002-9903-9727","orcid":"https://orcid.org/0000-0002-9903-9727","contributorId":213747,"corporation":false,"usgs":true,"family":"Slone","given":"Daniel","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":875059,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reid, James P. 0000-0002-8497-1132","orcid":"https://orcid.org/0000-0002-8497-1132","contributorId":206849,"corporation":false,"usgs":true,"family":"Reid","given":"James","email":"","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":875060,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Butler, Susan M. 0000-0003-3676-9332 sbutler@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-9332","contributorId":195796,"corporation":false,"usgs":true,"family":"Butler","given":"Susan","email":"sbutler@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":875061,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70244117,"text":"70244117 - 2023 - Evidence for density-dependent effects on body composition of a large omnivore in a changing Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2023-07-24T16:56:26.505999","indexId":"70244117","displayToPublicDate":"2023-06-01T06:38:41","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for density-dependent effects on body composition of a large omnivore in a changing Greater Yellowstone Ecosystem","docAbstract":"Understanding the density-dependent processes that drive population demography in a changing world is critical in ecology, yet measuring performance–density relationships in long-lived mammalian species demands long-term data, limiting scientists' ability to observe such mechanisms. We tested performance–density relationships for an opportunistic omnivore, grizzly bears (Ursus arctos, Linnaeus, 1758) in the Greater Yellowstone Ecosystem, with estimates of body composition (lean body mass and percent body fat) serving as indicators of individual performance over two decades (2000–2020) during which time pronounced environmental changes have occurred. Several high-calorie foods for grizzly bears have mostly declined in recent decades (e.g., whitebark pine [Pinus albicaulis, Engelm, 1863]), while increasing human impacts from recreation, development, and long-term shifts in temperatures and precipitation are altering the ecosystem. We hypothesized that individual lean body mass declines as population density increases (H1), and that this effect would be more pronounced among growing individuals (H2). We also hypothesized that omnivory helps grizzly bears buffer energy intake from changing foods, with body fat levels being independent from population density and environmental changes (H3). Our analyses showed that individual lean body mass was negatively related to population density, particularly among growing-age females, supporting H1 and partially H2. In contrast, population density or sex had little effect on body fat levels and rate of accumulation, indicating that sufficient food resources were available on the landscape to accommodate successful use of shifting food sources, supporting H3. Our results offer important insights into ecological feedback mechanisms driving individual performances within a population undergoing demographic and ecosystem-level changes. However, synergistic effects of continued climate change and increased human impacts could lead to more extreme changes in food availability and affect observed population resilience mechanisms. Our findings underscore the importance of long-term studies in protected areas when investigating complex ecological relationships in an increasingly anthropogenic world.
The Taurus porphyry Cu-Mo district contains four mineralized porphyry centers in the eastern interior of Alaska. All four centers were emplaced during a magmatic episode that spanned from ca. 72 to 67 Ma, with seven distinct igneous suites. Each igneous suite resulted in hydrothermal alteration and mineralization, with younger pulses overprinting older pulses. Each magmatic-hydrothermal system is not present at all four mineralized centers. Apart from the Dennison occurrence, each mineralized center records pulses of repeated intermediate-silicic magmatism and associated alteration and mineralization.
Laser ablation-inductively coupled plasma-mass spectrometry U-Pb zircon crystallization ages indicate that an early quartz porphyry dike swarm ranges in age from ca. 71 to 70 Ma and is associated with potassic, sericitic, and propylitic alteration. Quartz latite intrusions were emplaced at ca. 69 Ma and exhibit early sodiccalcic alteration overprinted by potassic, sericitic, and propylitic alteration. The Taurus monzonite suite is cut by quartz latite but yielded an ca. 70 Ma emplacement age and exhibits the largest footprint of potassic and sericitic alteration. Feldspar porphyry dikes were emplaced ca. 69 Ma and have significant tourmaline-bearing potassic and sericitic alteration. This suite was followed by development of an igneous breccia with a monzonitic igneous matrix. Sodic-calcic alteration was associated with the igneous brecciation. A small stock of monzonite was emplaced at ca. 68 Ma causing locally pervasive sericite-tourmaline-pyrite alteration. The youngest suite of magmatism dated in the district is a series of granodiorite porphyry dikes with weak sodic-calcic and propylitic alteration that truncates earlier alteration assemblages.
Mineralization in the district consists of chalcopyrite and molybdenite associated with sugary quartz veins with potassium feldspar and biotite alteration envelopes (A veins). Less common banded quartz-molybdenite veins (B veins) occur with potassium feldspar envelopes. Gold occurs throughout the district and is strongly correlated with copper grade. Sericitic alteration contains lower copper contents and is predominantly associated with quartz-pyrite veins with sericite envelopes (D veins). Pyrrhotite and local arsenopyrite are present in sericitic assemblages. Pyrrhotite also occurs as inclusions in pyrite within D veins.
Magmas across the district exhibit oxidized characteristics, evidenced by the presence of abundant magnetite, rare titanite, and elevated Eu/Eu* and Ce/Ce* in zircon. Zircon Th/U and Yb/Gd compositions suggest a fractionation path controlled by apatite, titanite, and hornblende. Zircon rare earth element ratios and trace element data indicate two distinct batches of magma evolved from mafic parental compositions to monzonite and granodioritic compositions via fractional crystallization. In the early pulse of magma (ca. 72–69 Ma), fractional crystallization was key to ore formation. Earlier, better mineralized suites evolve to less negative Eu anomalies (Eu/Eu* > 0.7), indicating more oxidized and higher-water-pressure conditions evidenced by the suppression of plagioclase crystallization, compared to later, more poorly mineralized suites.
The temporal and spatial evolution of the district was determined from mapping and U-Pb and Re-Os geochronology. Mapping of igneous and hydrothermal assemblages indicates that the locus of the intrusive suites and hydrothermal systems shifted spatially over time, based on the presence of high-temperature (K-silicate–dominant) alteration, which is coincident with the highest Cu and Au grades. The earliest hydrothermal system was centered at Bluff and East Taurus and transitioned to West Taurus during emplacement of the second magmatic suite. Emplacement of the third magmatic suite was centered back at East Taurus, and the fourth and fifth suites were centered at West Taurus. The latest suites were widespread without a core of high-temperature alteration marking a central locus. East Taurus contains the overlap of six of the seven magmatic and hydrothermal suites and has the highest intersected grades and tonnages in the district. The Bluff and Dennison occurrences exhibit fewer igneous suites and hydrothermal assemblages with weak mineralization. Sodic-calcic alteration, common on the deep and distal flanks of porphyry systems, is only present at West Taurus and is indicative of a localized source of high-salinity nonmagmatic fluids.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.4999","usgsCitation":"Kreiner, D.C., Holm-Denoma, C., Pianowski, L., Flood, Z., Stevenson, D.J., Graham, G.E., Vazquez, J.A., and Creaser, R.A., 2023, Geochronology and mapping constraints on the time-space evolution of the igneous and hydrothermal systems in the Taurus Cu-Mo district, eastern Alaska: Economic Geology, v. 118, no. 4, p. 745-778, https://doi.org/10.5382/econgeo.4999.","productDescription":"34 p.","startPage":"745","endPage":"778","ipdsId":"IP-136126","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":435302,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RANVXY","text":"USGS data release","linkHelpText":"U-Pb zircon data for igneous units related to mineralization in the eastern 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Alberta","active":true,"usgs":false}],"preferred":false,"id":870931,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70244145,"text":"70244145 - 2023 - HyWaves: Hybrid downscaling of multimodal wave spectra to nearshore areas","interactions":[],"lastModifiedDate":"2023-06-05T11:25:46.025191","indexId":"70244145","displayToPublicDate":"2023-06-01T06:21:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5979,"text":"Ocean Modeling","active":true,"publicationSubtype":{"id":10}},"title":"HyWaves: Hybrid downscaling of multimodal wave spectra to nearshore areas","docAbstract":"Long-term and accurate wave hindcast databases are often required in different coastal engineering projects. The assessment of the nearshore wave climate is often accomplished by using downscaling techniques to translate offshore waves to coastal areas. However, dynamical downscaling approaches may incur huge computational cost. Additionally, the common use of bulk parameterizations are often not accurate for multidimensional waves. To overcome these limitations, we present a hybrid downscaling approach that combines mathematical algorithms (statistical downscaling) and numerical modeling (dynamical downscaling) over the individual spectral partitions. Every wave partition is downscaled and aggregated afterward by using principles of wave linear theory. By assuming linearity in the propagation of the wave celerity, the application of the method is limited from offshore to intermediate water depths. In addition, the method proposed uses a technique to simplify the spectral boundary conditions in complex domains. The methodology has been applied and validated in the island states of Samoa, American Samoa, Majuro, and Kwajalein, showing good skill at reproducing the spectral hourly time series of significant wave height, peak period, and peak direction. Moreover, an accurate representation of the observed energy spectrum was achieved. This study provides insight into the numerical approximation of the combined sea-swell states while improving the quality of fast spectral forecasting and early warning systems.
1. Conversion of land for settlements and agriculture is increasing globally and can influence wildlife space use. However, there is limited research to identify the thresholds of land-use change that incur wildlife avoidance and how these thresh-olds might vary across levels of selection.
2. We evaluated multi-level avoidance thresholds of elk Cervus canadensis impacted by residential development and irrigated agriculture across the Greater Yellowstone Ecosystem in Idaho, Montana and Wyoming. Using GPS data from765 elk in 21 herds, we estimated habitat selection in relation to development and agriculture at three levels (home range selection, within home range selection and movement path selection). Next, using individual selection covariates and as-sociated measures of land-use availability, we used functional-response models to evaluate how selection varied based on availability, and in turn, to estimate avoidance thresholds.
3. We found individual and level-specific variation in elk responses to environmental factors. Elk exhibited stronger responses (either selection or avoidance) when selecting home range locations (i.e. second-order selection) than when selecting areas within home ranges (i.e. third-order selection) or selecting movement paths (i.e. fourth-order selection). Importantly, elk avoidance of development and agriculture changed as the amount of land in these categories changed. Across all levels of selection elk exhibited neutral selection for human development at low levels of availability (<1.1%–2.2% developed) but avoided areas that were >1.1%–2.2% developed. Conversely, elk selected positively for irrigated agriculture at low to moderate levels of availability (<52.0%–66.2% agriculture) but exhibited neutral selection in areas that were >52.0%–66.2% agriculture.
4. Synthesis and applications. Elk avoidance of low levels of human development suggests conservation efforts such as restrictions on future development or conservation easements could focus on areas that are still below 2% developed. Additionally, because elk selection was strongest at the landscape scale, conservation actions that are based on information about the overall landscape structure may be most impactful. Our results highlight the importance of under-standing variability in wildlife habitat selection at multiple levels, particularly in relation to land-use change, and highlight how functional response modelling can help inform landscape conservation.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.14401","usgsCitation":"Gigliotti, L., Atwood, M., Cole, E.K., Courtemanche, A., Dewey, S., Gude, J., Hurley, M., Kauffman, M., Kroetz, K., Leonard, B., MacNulty, D., Maichak, E., McWhirter, D., Mong, T., Proffitt, K., Scurlock, B., Stahler, D., and Middleton, A., 2023, Multi-level thresholds of residential and agricultural land use for elk avoidance across the Greater Yellowstone Ecosystem: Journal of Applied Ecology, v. 60, no. 6, p. 1089-1099, https://doi.org/10.1111/1365-2664.14401.","productDescription":"11 p.","startPage":"1089","endPage":"1099","ipdsId":"IP-145333","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467109,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.14401","text":"Publisher Index Page"},{"id":466426,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.49834976413001,\n 45.26023090682858\n ],\n [\n -111.49834976413001,\n 43.83379000138524\n ],\n [\n -108.63921958902552,\n 43.83379000138524\n ],\n [\n -108.63921958902552,\n 45.26023090682858\n ],\n [\n -111.49834976413001,\n 45.26023090682858\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"60","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-04-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Gigliotti, Laura Christine 0000-0002-6390-4133","orcid":"https://orcid.org/0000-0002-6390-4133","contributorId":348259,"corporation":false,"usgs":true,"family":"Gigliotti","given":"Laura Christine","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Atwood, M. 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WY 82414","active":true,"usgs":false}],"preferred":false,"id":923326,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Proffitt, Kelly","contributorId":348289,"corporation":false,"usgs":false,"family":"Proffitt","given":"Kelly","affiliations":[{"id":81193,"text":"Montana Department of Fish","active":true,"usgs":false}],"preferred":false,"id":923327,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Scurlock, Brandon","contributorId":348292,"corporation":false,"usgs":false,"family":"Scurlock","given":"Brandon","affiliations":[{"id":36596,"text":"Wyoming Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":923328,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Stahler, Daniel","contributorId":348295,"corporation":false,"usgs":false,"family":"Stahler","given":"Daniel","affiliations":[{"id":79152,"text":"Yellowstone Center for 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necessity to model animal population size from point counts with imperfect detection of individuals, where capture-recapture methods are infeasible. Initially developed for applications where population size was assumed constant, N-mixture models were extended in 2011 to include population dynamics, allowing application to populations whose size fluctuates during the study. A further extension in 2014 accommodates populations with multiple “states” such as age class or sex. More recent extensions model spatial movement of animals among habitat patches or the spatial spread of infectious disease in a human population. The core idea underlying this class of models is a hierarchical structure, where the observation model is defined conditional on the model for true abundance. This hierarchy allows researchers to incorporate information about observation and abundance processes, while permitting distinct inferences about elements affecting detection and those affecting abundance. Another benefit of the hierarchical approach is the ability to accommodate many existing sampling protocols such as removal sampling and distance sampling. One drawback to N-mixture models is that since they estimate both abundance and detection from replicated but unmarked counts, model parameters may not be clearly identifiable. A second drawback is that when observed counts are large, calculating the N-mixture likelihood is computationally infeasible. This difficulty motivated an approximate likelihood based on the normal approximation to the binomial. The normal approximation provides a diagnostic of parameter estimability based on the closed-form expression of the Fisher information matrix for a multivariate normal likelihood.
","language":"English","publisher":"Wiley","doi":"10.1002/wics.1625","usgsCitation":"Madsen, L., and Royle, J., 2023, A review of N-mixture models: WIREs Computational Statistics, v. 15, no. 6, e1625, 15 p., https://doi.org/10.1002/wics.1625.","productDescription":"e1625, 15 p.","ipdsId":"IP-147184","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":502082,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wics.1625","text":"Publisher Index Page"},{"id":502005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Madsen, Lisa","contributorId":369194,"corporation":false,"usgs":false,"family":"Madsen","given":"Lisa","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":958596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":958597,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70244057,"text":"sir20235056 - 2023 - Source contributions to suspended sediment and particulate selenium export from the Loutsenhizer Arroyo and Sunflower Drain watersheds in Colorado","interactions":[],"lastModifiedDate":"2026-03-09T16:27:43.171892","indexId":"sir20235056","displayToPublicDate":"2023-05-31T17:25:00","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":"2023-5056","displayTitle":"Source Contributions to Suspended Sediment and Particulate Selenium Export from the Loutsenhizer Arroyo and Sunflower Drain Watersheds in Colorado","title":"Source contributions to suspended sediment and particulate selenium export from the Loutsenhizer Arroyo and Sunflower Drain watersheds in Colorado","docAbstract":"Selenium in aquatic ecosystems of the lower Gunnison River Basin in Colorado is affecting the recovery of populations of endangered, native fish species. Dietary exposure is the primary pathway for bioaccumulation of selenium in fish, and particulate selenium can be consumed directly by fish or by the invertebrates on which fish feed. Although selenium can be incorporated into particulate matter via biogeochemical processes, particulate selenium can also enter aquatic ecosystems of the lower Gunnison River Basin from sediments derived from the selenium-rich Mancos Shale. The U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board, conducted this study during 2018–19 to identify sources of selenium-rich suspended sediments from two watersheds underlain by Mancos Shale: Loutsenhizer Arroyo and Sunflower Drain, which is a locally known agricultural drainage near the municipality of Delta, Colorado.
A multipronged approach (fieldwork, laboratory work, and computer modeling) referred to as “sediment fingerprinting” was used to evaluate sources of suspended sediments in the streams flowing out of the two studied watersheds. Four potential source types for suspended sediments were identified and sampled (using soil plugs) within the watersheds: rangelands, agricultural fields, arroyo walls, and streambanks. The sediment fingerprinting approach used elemental concentrations and naturally occurring fallout radionuclides as tracers to apportion percent contributions from the four source types of suspended sediments found in streamflow from both watersheds.
To determine the dominant sources of suspended sediment in streamflow from both watersheds, a mathematical “unmixing” model was used. Unmixing models apportion source percentages to samples of material in which those sources are mixed. These models used elemental and isotopic data in the suspended sediments to unmix them into proportional contributions from source types. The results indicated that arroyo walls and streambanks generally dominated as sources of the suspended sediment. Arroyo walls and streambanks were channel-adjacent sources, with sediments mobilized by water flowing within the stream channel. These sources accounted for greater than 50 percent of suspended sediment in all but one sample and accounted for 100 percent of suspended sediment in 5 of the 11 samples collected. Rangeland and agricultural field sources were located in uplands outside of stream channels and were detected more often during the non-irrigation season. Rangeland and agricultural field sources each were found in 5 of the 11 samples collected. Concentrations of selenium in sediment-source samples were comparatively greater in streambanks and lower in rangelands, with agricultural fields and arroyo walls being intermediate. As a result, source apportionments for particulate selenium skewed towards sources adjacent to stream channels more than for suspended sediments. Water imports for irrigation have changed the hydrology of the watersheds, and a notable fraction of imported water passes through the watersheds rapidly. The rapid flowthrough water during the irrigation season likely contributes heavily to sediment erosion and transport in Loutsenhizer Arroyo and Sunflower Drain, particularly from channel-adjacent sources of sediment. Decreases in irrigation season streamflow, at least in Loutsenhizer Arroyo, may have decreased sediment erosion and transport during the 2018–20 irrigation seasons compared to the 2015–17 seasons.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235056","collaboration":"Prepared in cooperation with the Colorado Water Conservation Board","usgsCitation":"Bern, C.R., Williams, C.A., and Smith, C.G., 2023, Source contributions to suspended sediment and particulate selenium export from the Loutsenhizer Arroyo and Sunflower Drain watersheds in Colorado: U.S. Geological Survey Scientific Investigations Report 2023–5056, 32 p., https://doi.org/10.3133/sir20235056.","productDescription":"Report: vii, 32 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-132717","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":485917,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114745.htm","linkFileType":{"id":5,"text":"html"}},{"id":417883,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235056/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5056"},{"id":417619,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5056/sir20235056.xml"},{"id":417618,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5056/images"},{"id":417612,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99EZZJK","text":"USGS data release","linkHelpText":"Geochemical and fallout radionuclide data for sediment source fingerprinting studies of the Loutsenhizer Arroyo and Sunflower Drain watersheds in western Colorado"},{"id":417611,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5056/sir20235056.pdf","text":"Report","size":"3.49 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5056"},{"id":417610,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5056/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Loutsenhizer Arroyo Watershed, Sunflower Drain Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.2032088457371,\n 38.871468271392075\n ],\n [\n -108.2032088457371,\n 38.38029358037457\n ],\n [\n -107.27351004163626,\n 38.38029358037457\n ],\n [\n -107.27351004163626,\n 38.871468271392075\n ],\n [\n -108.2032088457371,\n 38.871468271392075\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, Colorado 80225
Planets are expected to conclude their growth through a series of giant impacts: energetic, global events that significantly alter planetary composition and evolution. Computer models and theory have elucidated the diverse outcomes of giant impacts in detail, improving our ability to interpret collision conditions from observations of their remnants. However, many open questions remain, as even the formation of the Moon—a widely suspected giant-impact product for which we have the most information—is still debated. We review giant-impact theory, the diverse nature of giant-impact outcomes, and the governing physical processes. We discuss the importance of computer simulations, informed by experiments, for accurately modeling the impact process. Finally, we outline how the application of probability theory and computational advancements can assist in inferring collision histories from observations, and we identify promising opportunities for advancing giant-impact theory in the future.
We surveyed for Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) at five survey areas within the City of Carlsbad Preserve, Carlsbad, California, in 2022. Three flycatcher surveys were completed between May 18 and June 29, 2022. Territorial or transient flycatchers were not observed at the City of Carlsbad Preserve in 2022.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1172","collaboration":"Prepared in cooperation with the Center for Natural Lands Management; City of Carlsbad, California; and the U.S. Fish and Wildlife Service","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Allen, L.D., and Kus, B.E., 2023, Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys at the city of Carlsbad Preserve, San Diego County, California—2022 data summary: U.S. Geological Survey Data Report 1172, 9 p., https://doi.org/10.3133/dr1172.","productDescription":"v, 9 p.","numberOfPages":"9","onlineOnly":"Y","ipdsId":"IP-147281","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":417445,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1172/covrthb.jpg"},{"id":417446,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1172/dr1172.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":417447,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1172/dr1172.xml"},{"id":417448,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1172/images"},{"id":417449,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1172/full"}],"country":"United States","state":"California","county":"San Diego County","city":"Carlsbad","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.30898827684368,\n 33.08036562033729\n ],\n [\n -117.29802485908556,\n 33.08535233373509\n ],\n [\n -117.28549523879045,\n 33.08508988218436\n ],\n [\n -117.27045969443618,\n 33.085877234486176\n ],\n [\n -117.26388164378125,\n 33.07196630606006\n ],\n [\n -117.25072554247134,\n 33.06566629410253\n ],\n [\n -117.21658232716703,\n 33.072491286696504\n ],\n [\n -117.20342622585716,\n 33.101097993292996\n ],\n [\n -117.20906455498991,\n 33.150416126261035\n ],\n [\n -117.22911194746214,\n 33.1934156973948\n ],\n [\n -117.25072554247134,\n 33.22774775677978\n ],\n [\n -117.29708513756337,\n 33.22827180597483\n ],\n [\n -117.33060187185288,\n 33.219624592759175\n ],\n [\n -117.38541896064392,\n 33.19787176320091\n ],\n [\n -117.35660083396529,\n 33.15985686343487\n ],\n [\n -117.3346739984487,\n 33.128646110454724\n ],\n [\n -117.31807225155748,\n 33.09742425830902\n ],\n [\n -117.30898827684368,\n 33.08036562033729\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
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Bathymetric data were collected at 10 water-supply lakes in north-central and west-central Missouri by the U.S. Geological Survey (USGS) in cooperation with the Missouri Department of Natural Resources and in collaboration with various local agencies, as part of a multiyear effort to establish or update the surface area and capacity tables for the surveyed lakes. The lakes were surveyed in June and July 2020. Seven of the lakes had been surveyed by the USGS between 2002 and 2007, and the recent surveys were compared to the earlier surveys to document changes in the bathymetric surface and capacity of the lake and produce a bathymetric change map.
Bathymetric data were collected using a high-resolution multibeam mapping system mounted on a boat. Supplemental depth data at two of the lakes were collected in shallow areas with an acoustic Doppler current profiler on a remote-controlled boat. Data points from the various sources were exported at a gridded data resolution appropriate to each lake, either 0.82 foot or 1.64 feet. Data outside the multibeam survey extent and greater than the surveyed water-surface elevation generally were obtained from data collected using aerial light detection and ranging (lidar) point cloud data, except at Holden City Lake. A linear enforcement technique was used to add points to the dataset in areas of sparse data (the upper ends of coves where the water was shallow or aquatic vegetation precluded data acquisition) based on surrounding multibeam and upland data values. The various point datasets were used to produce a three-dimensional triangulated irregular network surface of lake-bottom elevations for each lake. A surface area and capacity table was produced from the three-dimensional surface for each lake showing surface area and capacity at specified lake water-surface elevations. Various quality-assurance tests were conducted to ensure quality data were collected with the multibeam, including beam angle checks and patch tests. Additional quality-assurance tests were conducted on the gridded bathymetric data from the survey, the bathymetric surface created from the gridded data, and the contours created from the bathymetric survey.
If data from a previous bathymetric survey existed at a given lake, a bathymetric change map was generated from the elevation difference between the previous survey and the 2020 bathymetric survey data points. After reconciling any vertical datum disagreement between the previous survey and the 2020 survey, coincident points between the surveys were identified, and a bathymetric change map was generated using the coincident point data.
A decrease in capacity was observed at nearly all the lakes for which a previous survey existed, and the mean bathymetric change between the surveys was positive at all the lakes. The decrease in capacity at the primary spillway elevation ranged from –0.4 percent at Edwin A Pape Lake to 9.4 percent at upper Higginsville Reservoir. The mean bathymetric change ranged from 0.03 foot at Garden City New Lake to 1.75 feet at Harrisonville City Lake, which corresponds to a time-averaged mean bathymetric change ranging from 0.002 foot per year at Garden City New Lake to 0.132 foot per year at Harrisonville City Lake. The computed volumetric sedimentation rate generally ranged from 0.04 to 4.91 acre-feet per year at Garden City New Lake and Holden City Lake, respectively; however, Harrisonville City Lake had a substantially larger volumetric sedimentation rate of 42.7 acre-feet per year, corresponding to the substantial mean bathymetric change of 1.75 feet and combined with the relatively shorter interval between surveys. Harrisonville City Lake also had the second-largest decrease in capacity at the spillway elevation of 5.9 percent. As with the 2019 surveys, some changes observed in the bathymetric change maps likely result from the difference in data collection equipment and techniques between the surveys. Certain apparent erosional features around the perimeter of certain lakes may be the result of wave action or compaction of sediments exposed to air during low-water years, or may indicate an unidentified but systemic error in the older singlebeam echosounder survey data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235046","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Huizinga, R.J., Rivers, B.C., Richards, J.M., and Waite, G.J., 2023, Bathymetric contour maps, surface area and capacity tables, and bathymetric change maps for selected water-supply lakes in north-central and west-central Missouri, 2020: U.S. Geological Survey Scientific Investigations Report 2023–5046, 52 p., https://doi.org/10.3133/sir20235046.","productDescription":"Report: vii, 52 p.; 9 Plates: 24.00 x 24.00 inches; 2 Data Releases; Dataset","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-137680","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":417113,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BV1H0S","text":"USGS data release","linkHelpText":"Bathymetric and supporting data for various water supply lakes in north-central and west-central Missouri, 2020"},{"id":417114,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5f7784b182ce1d74e7d6c99a","text":"USGS data release","linkHelpText":"USGS 13 arc-second n39w095 1 x 1 degree"},{"id":417109,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5046/sir20235046.pdf","text":"Report","size":"9.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5046"},{"id":417108,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5046/coverthb.jpg"},{"id":417590,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235046/full"},{"id":417110,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5046/sir20235046.XML"},{"id":500923,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114744.htm","linkFileType":{"id":5,"text":"html"}},{"id":417116,"rank":8,"type":{"id":28,"text":"Dataset"},"url":"https://www.sciencebase.gov/catalog/item/4f70ab64e4b058caae3f8def","text":"USGS dataset","linkHelpText":"—Lidar Point Cloud—USGS National Map 3DEP downloadable data collection"},{"id":417112,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2023/5046/downloads","text":"Plates 1–9"},{"id":417111,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5046/images"}],"country":"United States","state":"Missouri","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.5,\n 40.5\n ],\n [\n -94.5,\n 38.6\n ],\n [\n -93,\n 38.6\n ],\n [\n -93,\n 40.5\n ],\n [\n -94.5,\n 40.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
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Molecular methods including metabarcoding and quantitative polymerase chain reaction have shown promise for estimating species abundance by quantifying the concentration of genetic material in field samples. However, the relationship between specimen abundance and detectable concentrations of genetic material is often variable in practice. DNA mixture analysis represents an alternative approach to quantify specimen abundance based on the presence of unique alleles in a sample. The DNA mixture approach provides novel opportunities to inform ecology and conservation by estimating the absolute abundance of target taxa through molecular methods; yet, the challenges associated with genotyping many highly variable markers in mixed-DNA samples have prevented its widespread use. To advance molecular approaches for abundance estimation, we explored the utility of microhaplotypes for DNA mixture analysis by applying a 125-marker panel to 1179 Chinook salmon (Oncorhynchus tshawytscha) smolts from the Sacramento-San Joaquin Delta, California, USA. We assessed the accuracy of DNA mixture analysis through a combination of mock mixtures containing DNA from up to 20 smolts and a trophic ecological application enumerating smolts in predator diets. Mock DNA mixtures of up to 10 smolts could reliably be resolved using microhaplotypes, and increasing the panel size would likely facilitate the identification of more individuals. However, while analysis of predator gastrointestinal tract contents indicated DNA mixture analysis could discern the presence of multiple prey items, poor and variable DNA quality prevented accurate genotyping and abundance estimation. Our results indicate that DNA mixture analysis can perform well with high-quality DNA, but methodological improvements in genotyping degraded DNA are necessary before this approach can be used on marginal-quality samples.
","language":"English","publisher":"Wiley","doi":"10.1111/1755-0998.13816","usgsCitation":"Shi, Y., Dick, C., Karpan, K., Baetscher, D., Henderson, M., Sethi, S.A., McPhee, M.V., and Larson, W., 2023, Toward absolute abundance for conservation applications: Estimating the number of contributors via microhaplotype genotyping of mixed-DNA sample: Molecular Ecology Resources, v. 00, p. 1-13, https://doi.org/10.1111/1755-0998.13816.","productDescription":"13 p.","startPage":"1","endPage":"13","ipdsId":"IP-148129","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":443274,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/1755-0998.13816","text":"External Repository"},{"id":433117,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.26086948103463,\n 38.478699734733226\n ],\n [\n -122.26086948103463,\n 37.77218409560264\n ],\n [\n -121.28033969587833,\n 37.77218409560264\n ],\n [\n -121.28033969587833,\n 38.478699734733226\n ],\n [\n -122.26086948103463,\n 38.478699734733226\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"00","noUsgsAuthors":false,"publicationDate":"2023-05-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Shi, Yue","contributorId":342417,"corporation":false,"usgs":false,"family":"Shi","given":"Yue","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":910092,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dick, Cory","contributorId":342431,"corporation":false,"usgs":false,"family":"Dick","given":"Cory","email":"","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":910093,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karpan, Kirby","contributorId":342435,"corporation":false,"usgs":false,"family":"Karpan","given":"Kirby","email":"","affiliations":[{"id":37482,"text":"National Oceanographic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":910094,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baetscher, Diana S.","contributorId":288056,"corporation":false,"usgs":false,"family":"Baetscher","given":"Diana S.","affiliations":[{"id":61691,"text":"University of California Santa Cruz and NOAA Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":910095,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henderson, Mark J. 0000-0002-2861-8668 mhenderson@usgs.gov","orcid":"https://orcid.org/0000-0002-2861-8668","contributorId":198609,"corporation":false,"usgs":true,"family":"Henderson","given":"Mark J.","email":"mhenderson@usgs.gov","affiliations":[],"preferred":false,"id":910096,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sethi, Suresh A","contributorId":171843,"corporation":false,"usgs":false,"family":"Sethi","given":"Suresh","email":"","middleInitial":"A","affiliations":[{"id":26952,"text":"U.S. Fish and Wildlife Service, Anchorage, AK; Fisheries, Aquatic Science and Technology Lab, Alaska Pacific University, Anchorage, AK and U.S. Geological Survey New York Cooperative Fish and Wildlife Research Unit, Cornell University, Ithaca, NY","active":true,"usgs":false}],"preferred":false,"id":910097,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McPhee, Megan V.","contributorId":149335,"corporation":false,"usgs":false,"family":"McPhee","given":"Megan","email":"","middleInitial":"V.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":910098,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Larson, Wesley A.","contributorId":342433,"corporation":false,"usgs":false,"family":"Larson","given":"Wesley A.","affiliations":[{"id":37482,"text":"National Oceanographic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":910099,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70246271,"text":"70246271 - 2023 - Effects of a large flood on sediment and turbidity reduction projects in the Esopus Creek watershed, NY","interactions":[],"lastModifiedDate":"2023-06-29T12:27:02.208792","indexId":"70246271","displayToPublicDate":"2023-05-31T07:23:29","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Effects of a large flood on sediment and turbidity reduction projects in the Esopus Creek watershed, NY","docAbstract":"On December 24-25, 2020, 7.3 to 14.6 cm of rain fell on a large snowpack in the upper Esopus Creek (UEC) watershed in the Catskill Mountains of New York. The resulting flood had an annual exceedance probability (AEP) of 4 to 20% (recurrence intervals of 25 to 5 years) in streams across the watershed, resulted in substantial geomorphic adjustments in some stream channels, and transported the highest sediment concentrations observed since stream restoration projects in the UEC began in 2012. The largest flooding occurred in the Stony Clove Creek subbasin of the UEC which contains 8 sediment and turbidity reduction projects.
The UEC is the primary water source for the Ashokan Reservoir, part of New York City’s unfiltered water-supply system. A network of 16 turbidity-only and 13 suspended sediment and turbidity monitoring stations has been in operation within the UEC since October 2016. One of the primary purposes of this monitoring network is to investigate changes in suspended-sediment concentrations (SSC) and turbidity resulting from sediment and turbidity reduction projects (STRPs) implemented in tributaries to the UEC between 2012 and 2018. During the 2 to 8 years following the installation of the projects and prior to the 2020 flooding, declines in SSC and turbidity were measured at all monitoring sites although there were no flows that exceeded a 50% AEP flood. The flood of December 2020 had a 4-percent AEP at the subbasin outlet (Stony Clove Creek below Ox Clove at Chichester NY, USGS station number 01362370) and provided an opportunity to assess the effectiveness of the STRP following a large flood.
An order of magnitude increase in suspended-sediment concentration per unit discharge was measured at the outlet of the Stony Clove Creek subbasin following the flood. Increased SSC persisted for 3 months throughout the range in discharge and for at least 1 year at high discharges following the flood. The concentration-discharge relation returned to near pre-flood levels at low discharges but continued to remain above pre-flood levels at high discharges for more than 1 year. Mapped bank erosion increased in all Stony Clove subbasins following the flood and increases in stream contact with clay-rich glacial till and lacustrine sediments were greater relative to increases in contact with alluvium. Large increases in sediment concentration were observed where contact with glacial lacustrine material also increased. Minor increases in sediment concentration per unit discharge were measured from stream reaches where STRP were constructed and substantially less erosion was noted within those reaches relative to non-STRP reaches, though some breaches in revetments were noted.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD","conferenceDate":"May 8-12, 2023","conferenceLocation":"St. Louis, MO","language":"English","publisher":"SEDHYD","collaboration":"New York City Department of Environmental Protection","usgsCitation":"Siemion, J., Davis, W., and Bonville, D.B., 2023, Effects of a large flood on sediment and turbidity reduction projects in the Esopus Creek watershed, NY, in Proceedings of SEDHYD2023, St. Louis, MO, May 8-12, 2023, 16 p.","productDescription":"16 p.","ipdsId":"IP-151422","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":418614,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/past/2023Proceedings/100.pdf"},{"id":418621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Esopus Creek watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.25100517394345,\n 42.21443069112155\n ],\n [\n -74.25100517394345,\n 42.052331211522414\n ],\n [\n -74.0569800004709,\n 42.052331211522414\n ],\n [\n -74.0569800004709,\n 42.21443069112155\n ],\n [\n -74.25100517394345,\n 42.21443069112155\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Siemion, Jason 0000-0001-5635-6469 jsiemion@usgs.gov","orcid":"https://orcid.org/0000-0001-5635-6469","contributorId":127562,"corporation":false,"usgs":true,"family":"Siemion","given":"Jason","email":"jsiemion@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Wae D.","contributorId":315430,"corporation":false,"usgs":false,"family":"Davis","given":"Wae D.","affiliations":[{"id":68316,"text":"New York City Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":876540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonville, Donald B. 0000-0003-4480-9381","orcid":"https://orcid.org/0000-0003-4480-9381","contributorId":248849,"corporation":false,"usgs":true,"family":"Bonville","given":"Donald","email":"","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876541,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70247803,"text":"70247803 - 2023 - Knowledge gaps, uncertainties, and opportunities regarding the response of the Chesapeake Bay estuary to restoration efforts","interactions":[],"lastModifiedDate":"2023-08-18T12:18:04.306608","indexId":"70247803","displayToPublicDate":"2023-05-31T07:16:15","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Knowledge gaps, uncertainties, and opportunities regarding the response of the Chesapeake Bay estuary to restoration efforts","docAbstract":"As part of the Chesapeake Bay Program's (CBP's) Science and Technical Advisory Committee (STAC) initiative \"Achieving Water Quality Goals in the Chesapeake Bay: An Evaluation of System Response\", an Estuary Working Group was formed to generate an assessment of scientific knowledge gaps, uncertainties, and recent ecosystem changes to consider in light of CBP's impending goal of full implementation of management measures (Total Maximum Daily Load [TMDL] agreements and associated necessary stakeholder actions) that are being finalized and designed to achieve living resource-based nutrient targets by 2025. \n\nThis document summarizes aspects of the knowledge gaps, uncertainties, and associated needs and opportunities relating to our understanding of how the Chesapeake Bay estuary has responded to previously implemented management plans, and what features of the ecosystem may slow or enhance its response to future management actions in the face of expected continuations of climatic change.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Scientific and Technical Advisory Committee Report","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Chesapeake Bay Science and Technical Advisory Committee","collaboration":"University of Maryland Center for Environmental Science; Johns Hopkins University; University of Maryland Eastern Shore; U.S. Environmental Protection Agency; Foundation for Food and Agriculture Research","usgsCitation":"Testa, J.M., Dennison, W., Ball, W.P., Boomer, K., Gibson, D.M., Linker, L.C., Runge, M.C., and Sanford, L., 2023, Knowledge gaps, uncertainties, and opportunities regarding the response of the Chesapeake Bay estuary to restoration efforts, 61 p.","productDescription":"61 p.","ipdsId":"IP-146985","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":419926,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":419915,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.chesapeake.org/stac/wp-content/uploads/2023/05/23-004_Estuary-updated.pdf"}],"country":"United States","otherGeospatial":"Chesapeake Bay estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.63835995141072,\n 40.258031063896965\n ],\n [\n -77.63835995141072,\n 36.5239575992841\n ],\n [\n -75.22240433642538,\n 36.5239575992841\n ],\n [\n -75.22240433642538,\n 40.258031063896965\n ],\n [\n -77.63835995141072,\n 40.258031063896965\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Testa, Jeremy M.","contributorId":244524,"corporation":false,"usgs":false,"family":"Testa","given":"Jeremy","email":"","middleInitial":"M.","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":false,"id":880515,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dennison, William C.","contributorId":248356,"corporation":false,"usgs":false,"family":"Dennison","given":"William C.","affiliations":[{"id":38802,"text":"University of Maryland Center for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":880516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ball, William P.","contributorId":174394,"corporation":false,"usgs":false,"family":"Ball","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":27446,"text":"Johns Hopkins University, Department of Geography and Environmental Engineering","active":true,"usgs":false}],"preferred":false,"id":880517,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boomer, Kathleen","contributorId":328534,"corporation":false,"usgs":false,"family":"Boomer","given":"Kathleen","email":"","affiliations":[{"id":78388,"text":"Foundation for Food and Agriculture Research","active":true,"usgs":false}],"preferred":false,"id":880518,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gibson, Deirdre M","contributorId":328535,"corporation":false,"usgs":false,"family":"Gibson","given":"Deirdre","email":"","middleInitial":"M","affiliations":[{"id":78389,"text":"University of Maryland Eastern Shore","active":true,"usgs":false}],"preferred":false,"id":880519,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Linker, Lewis C. 0000-0002-3456-3659","orcid":"https://orcid.org/0000-0002-3456-3659","contributorId":252964,"corporation":false,"usgs":false,"family":"Linker","given":"Lewis","email":"","middleInitial":"C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":880520,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":880521,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sanford, Lawrence","contributorId":328536,"corporation":false,"usgs":false,"family":"Sanford","given":"Lawrence","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":false,"id":880522,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70245770,"text":"70245770 - 2023 - Viewing river corridors through the lens of critical zone science","interactions":[],"lastModifiedDate":"2023-06-27T12:04:16.335511","indexId":"70245770","displayToPublicDate":"2023-05-31T07:01:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7170,"text":"Frontiers in Water","active":true,"publicationSubtype":{"id":10}},"title":"Viewing river corridors through the lens of critical zone science","docAbstract":"River corridors integrate the active channels, geomorphic floodplain and riparian areas, and hyporheic zone while receiving inputs from the uplands and groundwater and exchanging mass and energy with the atmosphere. Here, we trace the development of the contemporary understanding of river corridors from the perspectives of geomorphology, hydrology, ecology, and biogeochemistry. We then summarize contemporary models of the river corridor along multiple axes including dimensions of space and time, disturbance regimes, connectivity, hydrochemical exchange flows, and legacy effects of humans. We explore how river corridor science can be advanced with a critical zone framework by moving beyond a primary focus on discharge-based controls toward multi-factor models that identify dominant processes and thresholds that make predictions that serve society. We then identify opportunities to investigate relationships between large-scale spatial gradients and local-scale processes, embrace that riverine processes are temporally variable and interacting, acknowledge that river corridor processes and services do not respect disciplinary boundaries and increasingly need integrated multidisciplinary investigations, and explicitly integrate humans and their management actions as part of the river corridor. We intend our review to stimulate cross-disciplinary research while recognizing that river corridors occupy a unique position on the Earth's surface.
No abstract available.
","conferenceTitle":"SEDHYD-2023, Sedimentation and Hydrologic Modeling Conference","conferenceDate":"May 8-12, 2023","conferenceLocation":"St. Louis, MO","language":"English","usgsCitation":"Keith, M.K., Wallick, J., Stratton Garvin, L.E., and Gordon, G., 2023, Coupled upstream-downstream geomorphic responses to deep reservoir drawdowns at Fall Creek Dam, Oregon, SEDHYD-2023, Sedimentation and Hydrologic Modeling Conference, St. Louis, MO, May 8-12, 2023, 14 p.","productDescription":"14 p.","ipdsId":"IP-147088","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":418000,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417999,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.sedhyd.org/2023Program/1/248.pdf"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.4250067091849,\n 46.136623316749194\n ],\n [\n -123.4250067091849,\n 43.631784058558026\n ],\n [\n -121.36046282001558,\n 43.631784058558026\n ],\n [\n -121.36046282001558,\n 46.136623316749194\n ],\n [\n -123.4250067091849,\n 46.136623316749194\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Keith, Mackenzie K. 0000-0002-7239-0576 mkeith@usgs.gov","orcid":"https://orcid.org/0000-0002-7239-0576","contributorId":196963,"corporation":false,"usgs":true,"family":"Keith","given":"Mackenzie","email":"mkeith@usgs.gov","middleInitial":"K.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wallick, J. Rose 0000-0002-9392-272X rosewall@usgs.gov","orcid":"https://orcid.org/0000-0002-9392-272X","contributorId":3583,"corporation":false,"usgs":true,"family":"Wallick","given":"J. Rose","email":"rosewall@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875130,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stratton Garvin, Laurel E. 0000-0001-8567-8619 lstratton@usgs.gov","orcid":"https://orcid.org/0000-0001-8567-8619","contributorId":270182,"corporation":false,"usgs":true,"family":"Stratton Garvin","given":"Laurel","email":"lstratton@usgs.gov","middleInitial":"E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875131,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gordon, Gabriel W. 0000-0001-6866-0302 ggordon@usgs.gov","orcid":"https://orcid.org/0000-0001-6866-0302","contributorId":269773,"corporation":false,"usgs":true,"family":"Gordon","given":"Gabriel W.","email":"ggordon@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875132,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248822,"text":"70248822 - 2023 - Applying decision analysis to diverse domains: An introduction to the special issue","interactions":[],"lastModifiedDate":"2023-09-22T11:45:33.044483","indexId":"70248822","displayToPublicDate":"2023-05-31T06:42:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13279,"text":"INFORMS Journal on Applied Analytics","active":true,"publicationSubtype":{"id":10}},"title":"Applying decision analysis to diverse domains: An introduction to the special issue","docAbstract":"No abstract available.
","language":"English","publisher":"INFORMS","doi":"10.1287/inte.2023.1163","usgsCitation":"Bansal, S., Siebert, J.U., Keisler, J.M., and Jenni, K., 2023, Applying decision analysis to diverse domains: An introduction to the special issue: INFORMS Journal on Applied Analytics, v. 53, no. 3, p. 173-177, https://doi.org/10.1287/inte.2023.1163.","productDescription":"5 p.","startPage":"173","endPage":"177","ipdsId":"IP-151038","costCenters":[{"id":78761,"text":"Office of the AD Energy and Minerals","active":true,"usgs":true}],"links":[{"id":421061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bansal, Saurabh","contributorId":329992,"corporation":false,"usgs":false,"family":"Bansal","given":"Saurabh","email":"","affiliations":[{"id":78758,"text":"Smeal College of Business, Penn State University","active":true,"usgs":false}],"preferred":false,"id":883790,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siebert, Johannes Ulrich 0000-0003-1623-308X","orcid":"https://orcid.org/0000-0003-1623-308X","contributorId":329993,"corporation":false,"usgs":false,"family":"Siebert","given":"Johannes","email":"","middleInitial":"Ulrich","affiliations":[{"id":78759,"text":"Management Center Innsbruck","active":true,"usgs":false}],"preferred":false,"id":883791,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keisler, Jeffrey M. 0000-0002-9267-2327","orcid":"https://orcid.org/0000-0002-9267-2327","contributorId":329994,"corporation":false,"usgs":false,"family":"Keisler","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[{"id":78760,"text":"University of Massachussetts at Boston","active":true,"usgs":false}],"preferred":false,"id":883792,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jenni, Karen 0000-0001-9927-7509","orcid":"https://orcid.org/0000-0001-9927-7509","contributorId":219401,"corporation":false,"usgs":true,"family":"Jenni","given":"Karen","email":"","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":883793,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70244252,"text":"70244252 - 2023 - Wildlife health surveillance: Gaps, needs and opportunities","interactions":[],"lastModifiedDate":"2023-06-09T11:40:28.762688","indexId":"70244252","displayToPublicDate":"2023-05-31T06:38:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5043,"text":"Scientific and Technical Review","active":true,"publicationSubtype":{"id":10}},"title":"Wildlife health surveillance: Gaps, needs and opportunities","docAbstract":"Disease emergence represent a global threat for public health, economy, and biological conservation and most of the emerging diseases have zoonotic origin from wildlife. To prevent their spread and to support the implementation of control measures, disease surveillance and reporting systems are needed, and due to globalisation, these activities should be carried at world level. To define the main gaps affecting the performances of wildlife health surveillance and reporting systems at word level, we analysed the Wildlife Disease Surveillance Survey submitted to all Members of World Organisation for Animal Health which inquire on structure and limits of surveillance and reporting systems. The response from 103 Members, covering all world areas, showed that 54.4% of them have a wildlife disease surveillance programme and 66% implemented a strategy to manage their spread. The lack of dedicated budget affected the possibility of outbreak investigations, sampling collection and diagnostic testing. Although most Members maintain records relating to wildlife mortality or morbidity events in centralised databases, data analyses and disease risk assessment are reported as main needs. Our evaluation of surveillance capacity showed an overall low level associated to great variability between Members not restricted to specific geographical area. A better recognition of the value of wildlife disease surveillance resulting in allocation of adequate resources by governments would make wildlife disease surveillance systems more functional. Moreover, the future comprehension of the influence of socio-economic, cultural and biodiversity aspects will be essential to increase better disease surveillance under One Health approach.","language":"English","publisher":"World Organisation for Animal Health","doi":"10.20506/rst.42.3359","usgsCitation":"Delgado, M., Ferrari, N., Fanelli, A., Muset, S., Thompson, L., Sleeman, J.M., White, C.L., Walsh, D.P., Wannous, C., and Tizzani, P., 2023, Wildlife health surveillance: Gaps, needs and opportunities: Scientific and Technical Review, p. 161-172, https://doi.org/10.20506/rst.42.3359.","productDescription":"12 p.","startPage":"161","endPage":"172","ipdsId":"IP-146472","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":497993,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.20506/rst.42.3359","text":"Publisher Index Page"},{"id":417957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Delgado, M.","contributorId":306198,"corporation":false,"usgs":false,"family":"Delgado","given":"M.","email":"","affiliations":[{"id":66384,"text":"World Organisation for Animal Health, 12 Rue de Prony, 75017 Paris, France","active":true,"usgs":false}],"preferred":false,"id":875018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferrari, N.","contributorId":306199,"corporation":false,"usgs":false,"family":"Ferrari","given":"N.","email":"","affiliations":[{"id":66386,"text":"Department of Veterinary Medicine and Animal Sciences- Università degli Studi di Milano (Italy)","active":true,"usgs":false}],"preferred":false,"id":875019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fanelli, A.","contributorId":306200,"corporation":false,"usgs":false,"family":"Fanelli","given":"A.","email":"","affiliations":[{"id":66387,"text":"University of Bari","active":true,"usgs":false}],"preferred":false,"id":875020,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muset, S.","contributorId":306201,"corporation":false,"usgs":false,"family":"Muset","given":"S.","email":"","affiliations":[{"id":66384,"text":"World Organisation for Animal Health, 12 Rue de Prony, 75017 Paris, France","active":true,"usgs":false}],"preferred":false,"id":875021,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, L.","contributorId":306202,"corporation":false,"usgs":false,"family":"Thompson","given":"L.","email":"","affiliations":[{"id":66384,"text":"World Organisation for Animal Health, 12 Rue de Prony, 75017 Paris, France","active":true,"usgs":false}],"preferred":false,"id":875022,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":875023,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"White, C. LeAnn 0000-0002-5004-5165 clwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-5004-5165","contributorId":4315,"corporation":false,"usgs":true,"family":"White","given":"C.","email":"clwhite@usgs.gov","middleInitial":"LeAnn","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":875024,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":875025,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wannous, C.","contributorId":306203,"corporation":false,"usgs":false,"family":"Wannous","given":"C.","email":"","affiliations":[{"id":66384,"text":"World Organisation for Animal Health, 12 Rue de Prony, 75017 Paris, France","active":true,"usgs":false}],"preferred":false,"id":875026,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tizzani, P.","contributorId":306204,"corporation":false,"usgs":false,"family":"Tizzani","given":"P.","affiliations":[{"id":66384,"text":"World Organisation for Animal Health, 12 Rue de Prony, 75017 Paris, France","active":true,"usgs":false}],"preferred":false,"id":875027,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70245186,"text":"70245186 - 2023 - Water quality at Chaco Culture National Historical Park and the potential effects of hydrocarbon extraction","interactions":[],"lastModifiedDate":"2023-06-21T11:42:56.490152","indexId":"70245186","displayToPublicDate":"2023-05-31T06:37:50","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Water quality at Chaco Culture National Historical Park and the potential effects of hydrocarbon extraction","docAbstract":"Chaco Culture National Historical Park (CCNHP) is in the San Juan Basin of northwestern New Mexico, U.S.A. Its only water supply is in Gallup Sandstone aquifer, stratigraphically surrounded by layers long targeted for oil and natural gas extraction.
To assess groundwater flow direction, age, mixing between aquifers, and whether hydrocarbons extraction may affect water quality, we completed a geochemical groundwater sampling campaign. Groundwater at 11 sites was analyzed for major ions, hydrocarbon associated volatile organic carbon (VOC) compounds, noble gases, and the isotope systems δ2H, δ18O, 87Sr/86Sr, δ13C, and 14C.
Results demonstrate that all sampled groundwaters are exceedingly old and geochemically evolved, with a median 14C age of ∼41,000 years before present and a north flowing path. Three lines of evidence suggest mixing between aquifers through relatively impermeable shale units and mixing with hydrocarbons: 1) noble gases are fractionated likely through mixing with connate water expelled during hydrocarbon genesis; 2) several wells—including the park’s main supply well—contained trace amounts of hydrocarbon related VOC compounds; and 3) major ion analysis shows mixing trends between aquifers. We hypothesize that cross-aquifer mixing may be facilitated through the region’s numerous hydrocarbon related boreholes. Whether our findings are the result of oil and gas extraction or represent the natural state of the aquifers will require more research.