Birds are used as bioindicators of environmental mercury (Hg) contamination, and toxicity reference values are needed for injury assessments. We conducted a comprehensive review, summarized data from 168 studies, performed a series of Bayesian hierarchical meta-analyses, and developed new toxicity reference values for the effects of methylmercury (MeHg) on birds using a benchmark dose analysis framework. Lethal and sublethal effects of MeHg on birds were categorized into nine biologically relevant endpoint categories and three age classes. Effective Hg concentrations where there was a 10% reduction (EC10) in the production of juvenile offspring (0.55 µg/g wet wt adult blood-equivalent Hg concentrations, 80% credible interval: [0.33, 0.85]), histology endpoints (0.49 [0.15, 0.96] and 0.61 [0.09, 2.48]), and biochemical markers (0.77 [<0.25, 2.12] and 0.57 [0.35, 0.92]) were substantially lower than those for survival (2.97 [2.10, 4.73] and 5.24 [3.30, 9.55]) and behavior (6.23 [1.84, >13.42] and 3.11 [2.10, 4.64]) of juveniles and adults, respectively. Within the egg age class, survival was the most sensitive endpoint (EC10 = 2.02 µg/g wet wt adult blood-equivalent Hg concentrations [1.39, 2.94] or 1.17 µg/g fresh wet wt egg-equivalent Hg concentrations [0.80, 1.70]). Body morphology was not particularly sensitive to Hg. We developed toxicity reference values using a combined survival and reproduction endpoints category for juveniles, because juveniles were more sensitive to Hg toxicity than eggs or adults. Adult blood-equivalent Hg concentrations (µg/g wet wt) and egg-equivalent Hg concentrations (µg/g fresh wet wt) caused low injury to birds (EC1) at 0.09 [0.04, 0.17] and 0.04 [0.01, 0.08], moderate injury (EC5) at 0.6 [0.37, 0.84] and 0.3 [0.17, 0.44], high injury (EC10) at 1.3 [0.94, 1.89] and 0.7 [0.49, 1.02], and severe injury (EC20) at 3.2 [2.24, 4.78] and 1.8 [1.28, 2.79], respectively. Maternal dietary Hg (µg/g dry wt) caused low injury to juveniles at 0.16 [0.05, 0.38], moderate injury at 0.6 [0.29, 1.03], high injury at 1.1 [0.63, 1.87], and severe injury at 2.4 [1.42, 4.13]. We found few substantial differences in Hg toxicity among avian taxonomic orders, including for controlled laboratory studies that injected Hg into eggs. Our results can be used to quantify injury to birds caused by Hg pollution.
This study focuses on understanding the association of rare earth elements (REE; lanthanides + yttrium + scandium) with organic matter from the Middle Devonian black shales of the Appalachian Basin. Developing a better understanding of the role of organic matter (OM) and thermal maturity in REE partitioning may help improve current geochemical models of REE enrichment in a wide range of black shales. We studied relationships between whole rock REE content and total organic carbon (TOC) and compared the correlations with a suite of global oil shales that contain TOC as high as 60 wt.%. The sequential leaching of the Appalachian shale samples was conducted to evaluate the REE content associated with carbonates, Fe–Mn oxyhydroxides, sulfides, and organics. Finally, the residue from the leaching experiment was analyzed to assess the mineralogical changes and REE extraction efficiency. Our results show that heavier REE (HREE) have a positive correlation with TOC in our Appalachian core samples. However, data from the global oil shales display an opposite trend. We propose that although TOC controls REE enrichment, thermal maturation likely plays a critical role in HREE partitioning into refractory organic phases, such as pyrobitumen. The REE inventory from a core in the Appalachian Basin shows that (1) the total REE ranges between 180 and 270 ppm and the OM-rich samples tend to contain more REE than the calcareous shales; (2) there is a relatively higher abundance of middle REE (MREE) to HREE than lighter REE (LREE); (3) there is a disproportionate increase in Y and Tb with TOC likely due to the rocks being over-mature; and (4) the REE extraction demonstrates that although the OM has higher HREE concentration, the organic leachates contain more LREE, suggesting it is more challenging to extract HREE from OM than using traditional leaching techniques.
","language":"English","publisher":"MDPI","doi":"10.3390/en17092107","usgsCitation":"Bhattacharya, S., Sharma, S., Agrawal, V., Dix, M.C., Zanoni, G., Birdwell, J.E., Wylie, A.S., and Wagner, T., 2024, Influence of organic matter thermal maturity on rare earth element distribution: A study of Middle Devonian black shales from the Appalachian Basin, USA: Energies, v. 17, no. 9, 2107, 23 p., https://doi.org/10.3390/en17092107.","productDescription":"2107, 23 p.","ipdsId":"IP-160281","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":439736,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/en17092107","text":"Publisher Index Page"},{"id":428357,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Middle Devonian Appalachian Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.019722212101,\n 35.09354117626262\n ],\n [\n -80.0893868493873,\n 35.83616426236574\n ],\n [\n -75.48876301910367,\n 41.23650512855389\n ],\n [\n -74.6944038739024,\n 43.48785346597265\n ],\n [\n -79.3043542917768,\n 42.997887934674736\n ],\n [\n -83.72355980871455,\n 37.83971543304291\n ],\n [\n -85.019722212101,\n 35.09354117626262\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"9","noUsgsAuthors":false,"publicationDate":"2024-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Bhattacharya, Shailee","contributorId":336153,"corporation":false,"usgs":false,"family":"Bhattacharya","given":"Shailee","email":"","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":900057,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sharma, Shikha","contributorId":336154,"corporation":false,"usgs":false,"family":"Sharma","given":"Shikha","email":"","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":900058,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Agrawal, Vikas","contributorId":336156,"corporation":false,"usgs":false,"family":"Agrawal","given":"Vikas","email":"","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":900059,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dix, Michael C.","contributorId":336159,"corporation":false,"usgs":false,"family":"Dix","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":80761,"text":"Consultant (formerly with PremierCorex)","active":true,"usgs":false}],"preferred":false,"id":900060,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zanoni, Giovanni","contributorId":336160,"corporation":false,"usgs":false,"family":"Zanoni","given":"Giovanni","email":"","affiliations":[{"id":80763,"text":"RohmTek, Houston, TX","active":true,"usgs":false}],"preferred":false,"id":900061,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":900062,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wylie, Albert S. Jr.","contributorId":336282,"corporation":false,"usgs":false,"family":"Wylie","given":"Albert","suffix":"Jr.","email":"","middleInitial":"S.","affiliations":[{"id":80764,"text":"Independent researcher, Mohawk, MI","active":true,"usgs":false}],"preferred":false,"id":900063,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wagner, Tom","contributorId":336283,"corporation":false,"usgs":false,"family":"Wagner","given":"Tom","email":"","affiliations":[],"preferred":false,"id":900064,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70257516,"text":"70257516 - 2024 - Prion forensics: A multidisciplinary approach to investigate CWD at an illegal deer carcass disposal site","interactions":[],"lastModifiedDate":"2024-08-30T16:56:00.350095","indexId":"70257516","displayToPublicDate":"2024-04-26T11:45:42","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3121,"text":"Prion","onlineIssn":"1933-690X","printIssn":"1933-6896","active":true,"publicationSubtype":{"id":10}},"title":"Prion forensics: A multidisciplinary approach to investigate CWD at an illegal deer carcass disposal site","docAbstract":"Infectious prions are resistant to degradation and remain infectious in the environment for several years. Chronic wasting disease (CWD) has been detected in cervids inhabiting North America, the Nordic countries, and South Korea. CWD-prion spread is partially attributed to carcass transport and disposal. We employed a forensic approach to investigate an illegal carcass dump site connected with a CWD-positive herd. We integrated anatomic, genetic, and prion amplification methods to discover CWD-positive remains from six white-tailed deer (Odocoileus virginianus) and, using microsatellite markers, confirmed a portion originated from the CWD-infected herd. This approach provides a foundation for future studies of carcass prion transmission risk.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/19336896.2024.2343298","usgsCitation":"Schwabenlander, M.D., Bartz, J.C., Carstensen, M., Fameli, A., Glaser, L., Larsen, R.J., Li, M., Shoemaker, R.L., Rowden, G., Stone, S., Walter, W., Wolf, T.M., and Larsen, P.A., 2024, Prion forensics: A multidisciplinary approach to investigate CWD at an illegal deer carcass disposal site: Prion, v. 18, no. 1, p. 72-86, https://doi.org/10.1080/19336896.2024.2343298.","productDescription":"15 p.","startPage":"72","endPage":"86","ipdsId":"IP-148949","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":439738,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/19336896.2024.2343298","text":"Publisher Index Page"},{"id":433385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","county":"Beltrami 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","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241021","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Doyle, H.F., and Domanski, M.M., 2024, Special Contributing Area Loading Program user’s manual: U.S. Geological Survey Open-File Report 2024–1021, 15 p., https://doi.org/10.3133/ofr20241021.","productDescription":"Report: vi, 15 p.; Software Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-137188","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":427858,"rank":6,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9EE0614","text":"USGS software release","linkHelpText":"—SCALP (Special Contributing Area Loading Program, ver. 1.0.0)"},{"id":427857,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241021/full"},{"id":427856,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1021/images/"},{"id":427855,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1021/ofr20241021.XML"},{"id":427854,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1021/ofr20241021.pdf","text":"Report","size":"4.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1021"},{"id":427853,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1021/coverthb.jpg"}],"contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
An increase in volcanic thermal emissions can indicate subsurface and surface processes that precede, or coincide with, volcanic eruptions. Space-borne infrared sensors can detect hotspots—defined here as localized volcanic thermal emissions—in near-real-time. However, automatic hotspot detection systems are needed to efficiently analyze the large quantities of data produced. While hotspots have been automatically detected for over 20 years with simple thresholding algorithms, new computer vision technologies, such as convolutional neural networks (CNNs), can enable improved detection capabilities. Here we introduce HotLINK: the Hotspot Learning and Identification Network, a CNN trained to detect hotspots with a dataset of −3,800 satellite-based, Visible Infrared Imaging Radiometer Suite (VIIRS) images from Mount Veniaminof and Mount Cleveland volcanoes, Alaska. We find that our model achieves an accuracy of 96% (F1-score 0.92) when evaluated on −1,700 unseen images from the same volcanoes, and 95% (F1-score 0.67) when evaluated on −3,000 images from six additional Alaska volcanoes (Augustine Volcano, Bogoslof Island, Okmok Caldera, Pavlof Volcano, Redoubt Volcano, Shishaldin Volcano). In comparison with an existing threshold-based hotspot detection algorithm, MIROVA (Coppola et al., Geological Society, London, Special Publications, 2016, 426, 181–205), our model detects 22% more hotspots and produces 12% fewer false positives. Additional testing on −700 labeled Moderate Resolution Imaging Spectroradiometer (MODIS) images from Mount Veniaminof demonstrates that our model is applicable to this sensor’s data as well, achieving an accuracy of 98% (F1-score 0.95). We apply HotLINK to 10 years of VIIRS data and 22 years of MODIS data for the eight aforementioned Alaska volcanoes and calculate the radiative power of detected hotspots. From these time series we find that HotLINK accurately characterizes background and eruptive periods, similar to MIROVA, but also detects more subtle warming signals, potentially related to volcanic unrest. We identify three advantages to our model over its predecessors: 1) the ability to detect more subtle volcanic hotspots and produce fewer false positives, especially in daytime images; 2) probabilistic predictions provide a measure of detection confidence; and 3) its transferability, i.e., the successful application to multiple sensors and multiple volcanoes without the need for threshold tuning, suggesting the potential for global application.
Many forests globally are experiencing increases in large, high-severity wildfires, often with increasingly inadequate post-fire tree regeneration. To identify areas that might need post-fire planting, forest managers have a growing need for seedling reference densities – the natural seedling densities expected to be adequate to regenerate a forest – to compare with observed post-fire seedling densities. The most useful reference densities will meet five criteria: they will (1) be specific to natural post-fire reproduction rather than planted seedlings (because planted seedlings can have substantially greater survival than natural seedlings, thus underestimating adequate natural reproduction), (2) apply to the first few years following fire (when management decisions and actions are most likely), (3) be specific to each of those post-fire years (because post-fire seedling densities can change rapidly with time since fire), (4) be associated with estimates of uncertainty, and (5) include consideration of novel environmental conditions during management applications (because most reference densities will be based on data collected under more environmentally benign conditions). The world’s most massive tree species, the giant sequoia (Sequoiadendron giganteum) of California’s Sierra Nevada, recently experienced historically unprecedented wildfires that killed an estimated 13–19% of mature sequoias across their native range. Seedlings germinating after these fires then experienced exceptional summer heat and the two most severe summer droughts of the 121-year historical record. To help inform management responses to these events, we used seedling censuses from past fires (mostly prescribed fires) to calculate sequoia seedling reference densities meeting the five criteria. The reference densities had three striking features, which are partly attributable to giant sequoia’s status as a pioneer species. First, despite being inherently conservative, the reference densities were quite high. For example, mean first-year reference density was 172,599 seedlings ha−1. Second, reference densities declined precipitously with time since fire: the mean fifth-year reference density was only 5% of the mean first-year density. Third, the reference densities were associated with relatively substantial uncertainty, a consequence of density variations among seedling plots; for example, the 95% credible interval for first-year reference density was 64,377 to 313,438 seedlings ha−1. Despite this uncertainty, a case-study sequoia grove that recently burned in a high-severity wildfire had second-year post-fire seedling densities that were significantly (and dramatically) lower than the corresponding second-year reference density, suggesting inadequate post-fire reproduction. Our results highlight the value of the five criteria for reference densities – criteria that, in current practice, are rarely all met.
The spatiotemporal distribution of harmful algal blooms (HABs) in rivers remains poorly understood, and there is an urgent need to develop a consistent set of metrics to better document HAB occurrences and forecast future events. Using data from seven sites in the Illinois River Basin, we computed metrics focused on HAB conditions related to excess algal growth and hypoxia. Daily mean chlorophyll and dissolved oxygen (DO) concentrations, gross primary productivity (GPP), and net ecosystem productivity (NEP) rates, focused on water quality status, identifying the timing of the transition from a clear-water to an algal dominated state. Early warning indicators (EWIs), the first-order autoregressive process (Ar1) and standard deviation (SD) of chlorophyll concentrations, focused on future events, forecasting blooms. Metrics were compared to either literature-derived or statistical-based thresholds and were normalized by total number of daily samples for an exceedance rate. Exceedances of a daily mean chlorophyll concentration averaged 50 % across all sites using a 10 µg L−1 threshold but increasing the threshold to 50 μg L−1 reduced the average exceedance rate to 5 %. The average exceedance rate for GPP (∼8 g O2 m2d−1 threshold) was 15 %, similar to the daily amplitude DO concentration (∼3 mg L−1 threshold), but the average for NEP (0 g O2 m2 d−1 threshold) was higher, at 28 %. The number of days with at least 1 continuous DO concentration below the threshold of 5, 3, or 2 mg L−1, had basin wide exceedance rates of 9 %, 3 %, and 2 %, respectively. Thresholds for EWIs, Ar1 and SD, were exceeded at 5 of the 7 sites with high chlorophyll concentrations and GPP rates. The correlation between proxies for algal biomass (chlorophyll concentration) and productivity (GPP) was strongest for sites in the middle region of the basin, with R2 values between 0.54 and 0.74. Although, cyanotoxin concentrations are the most commonly used metrics by states to define an inland water HAB, there is a paucity of publicly available data. The wider availability of chlorophyll and oxygen data combined with the results from this study suggest that biomass and productivity state and event-based metrics may be a promising way to assess and predict the vulnerability of rivers to some of the deleterious effects of HABs at broad spatial scales.
In response to recent shifts towards open science that emphasize transparency, reproducibility, and access to research data, the US Geological Survey (USGS) conducted a study to assess the degree to which USGS data assets meet the FAIR data principles (Findable, Accessible, Interoperable, and Reusable). The USGS designed and applied a methodology for quantitative analysis of FAIR characteristics. A new rubric was derived from a crosswalk of existing FAIR evaluation frameworks and customized for the USGS. The rubric, consisting of 62 yes/no questions, was applied to 392 metadata records of USGS data products published between 1987 and 2022. Results were analyzed to show which FAIR characteristics were most and least present in the metadata and how these scores changed after the implementation of data policy requirements in 2016. Aggregated scores showed specific areas of strength and needed improvements. The greatest increases in FAIR scores over time were for elements that were required by new data policies, especially in the ‘Findable’ category. Based on the results, this paper presents strategies to further improve USGS alignment with FAIR. The suggested strategies are organized in four key areas: USGS data repository characteristics, training and communities of practice, data management policy considerations, and metadata standards, tools, and best practices.
","language":"English","publisher":"CODATA","doi":"10.5334/dsj-2024-022","usgsCitation":"Hutchison, V.B., Norkin, T., Zolly, L., and Hsu, L., 2024, State of the data: Assessing the FAIRness of USGS data: Data Science Journal, v. 23, 20 p., https://doi.org/10.5334/dsj-2024-022.","productDescription":"20 p.","ipdsId":"IP-155592","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":439743,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.5334/dsj-2024-022","text":"Publisher Index Page"},{"id":428533,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","noUsgsAuthors":false,"publicationDate":"2024-04-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Hutchison, Vivian B. 0000-0001-5301-3698 vhutchison@usgs.gov","orcid":"https://orcid.org/0000-0001-5301-3698","contributorId":173674,"corporation":false,"usgs":true,"family":"Hutchison","given":"Vivian","email":"vhutchison@usgs.gov","middleInitial":"B.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":900358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norkin, Tamar 0000-0003-0797-3940 tnorkin@usgs.gov","orcid":"https://orcid.org/0000-0003-0797-3940","contributorId":5882,"corporation":false,"usgs":true,"family":"Norkin","given":"Tamar","email":"tnorkin@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":900359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zolly, Lisa 0000-0003-3595-7809 lisa_zolly@usgs.gov","orcid":"https://orcid.org/0000-0003-3595-7809","contributorId":484,"corporation":false,"usgs":true,"family":"Zolly","given":"Lisa","email":"lisa_zolly@usgs.gov","affiliations":[],"preferred":true,"id":900360,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hsu, Leslie 0000-0002-5353-807X lhsu@usgs.gov","orcid":"https://orcid.org/0000-0002-5353-807X","contributorId":191745,"corporation":false,"usgs":true,"family":"Hsu","given":"Leslie","email":"lhsu@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":900361,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70253191,"text":"sir20245009 - 2024 - Status of water quality in groundwater resources used for drinking-water supply in the southeastern San Joaquin Valley, 2013–15—California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2025-08-07T20:31:29.798566","indexId":"sir20245009","displayToPublicDate":"2024-04-25T13:17:53","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5009","displayTitle":"Status of Water Quality in Groundwater Resources Used for Drinking-Water Supply in the Southeastern San Joaquin Valley, 2013–15: California GAMA Priority Basin Project","title":"Status of water quality in groundwater resources used for drinking-water supply in the southeastern San Joaquin Valley, 2013–15—California GAMA Priority Basin Project","docAbstract":"The California Groundwater Ambient Monitoring and Assessment Program Priority Basin Project (GAMA-PBP) investigated water quality of groundwater resources used for drinking-water supplies in the Madera-Chowchilla, Kings, Kaweah, Tule, and Tulare Lake groundwater subbasins of the southeastern San Joaquin Valley during 2013–15. The study focused primarily on groundwater resources used for domestic-supply wells in the southeastern San Joaquin Valley (SESJV-D), which correspond mostly to shallower parts of aquifer systems, compared to the groundwater resources used for public-supply wells in the southeastern San Joaquin Valley (SESJV-P). The investigation had three components: (1) characterization of the status of water quality in the SESJV-D, (2) comparison between water quality in the SESJV-D and SESJV-P, and (3) identification of natural and anthropogenic factors that potentially could affect water quality in these resources.
The characterization of water quality in the SESJV-D was based on data collected from 198 domestic wells sampled during 2013–15 by the U.S. Geological Survey (USGS); characterization of water quality in the SESJV-P was based on data collected from 124 wells sampled by the USGS during 2005–18 and an additional 1,577 wells with publicly available data reported to the California State Water Resources Control Board Division of Drinking Water (SWRCB-DDW). Measured concentrations were compared to regulatory and non-regulatory drinking-water quality benchmarks. A grid-based method was used to estimate the areal proportions of each study area and the whole southeastern San Joaquin Valley with high (greater than benchmark concentration), moderate (greater than half of the benchmark for inorganic and one-tenth of the benchmark for organic), and low concentrations relative to those benchmarks.
Natural and anthropogenic factors that could affect groundwater quality for the SESJV-D were identified in the context of the hydrogeologic setting of the southeastern San Joaquin Valley. The considered factors represented hydrologic conditions and position in the groundwater flow system (well depth, lateral position, presence of hydric soils, percentage of coarse-grained sediment, and aridity index), land-use characteristics (percentages of agricultural, urban, and natural land use, percentage of orchard or vineyard land use, and densities of septic tanks and underground storage tanks near the wells), and geochemical conditions (groundwater age class, oxidation-reduction class, pH, and dissolved oxygen and bicarbonate concentrations). Factors are compared between SESJV-D and SESJV-P at the scale of the five study areas.
One or more inorganic constituents with U.S. Environmental Protection Agency (EPA) or California maximum contaminant levels (MCLs) were detected at high concentrations in 47 percent of the SESJV-D and in 32 percent of the SESJV-P. The inorganic constituents most commonly present at high concentrations in the SESJV-D were nitrate, uranium, and arsenic. Within the SESJV-D, the proportion of the study area with high concentrations of inorganic constituents ranged from 19 percent in Madera-Chowchilla to 60 percent in Kings and Tulare Lake. One or more inorganic constituents with California State Water Resources Control Board Division of Drinking Water secondary maximum contaminant levels (SMCL-CAs) were detected at high concentrations in 14 percent of the SESJV-D and in 19 percent of the SESJV-P. The constituents most commonly present at high concentrations were manganese, iron, and total dissolved solids (TDS). Although the proportion of SESJV-D and SESJV-P with high concentrations of TDS greater than the upper SMCL were similar at 4 percent, the proportion of the SESJV-D with moderate concentrations (between the recommended and upper SMCL-CA), 30 percent, was greater than the proportion of the SESJV-P with moderate concentrations, 12 percent.
One or more organic constituents with MCLs were present at high concentrations in 19 percent of the SESJV-D and in 12 percent of the SESJV-P. All the constituents detected at high concentrations in the SESJV-D were fumigants, primarily 1,2,3-trichloropropane (1,2,3-TCP) and 1,2-dibromo-3-chloropropane (DBCP). Fumigants also were the constituents most commonly detected at high concentrations in the SESJV-P, although high concentrations of solvents also were detected. The SESJV-D dataset included analysis of many organic constituents without MCL benchmarks and with detection levels far below drinking water benchmark concentrations; detections at these low concentrations can be used as tracers of anthropogenic influence on groundwater. Pesticides and degradates of pesticides were detected in 60 percent of the SESJV-D; the most frequently detected pesticides were the herbicides simazine, didealkylatrazine (CAAT, a degradate of simazine and atrazine), diuron, and bromacil.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245009","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","programNote":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program","usgsCitation":"Burow, K.R., Shelton, J.L., and Fram, M.S., 2024, Status of water quality in groundwater resources used for drinking-water supply in the southeastern San Joaquin Valley, 2013–15—California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2024–5009, 135 p., https://doi.org/10.3133/sir20245009.","productDescription":"Report: xiii, 135 p.; Data Release","numberOfPages":"136","onlineOnly":"Y","ipdsId":"IP-094434","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":428122,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245009/full"},{"id":493742,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116370.htm","linkFileType":{"id":5,"text":"html"}},{"id":428123,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DCTLXV","text":"USGS Data Release","description":"Balkan, M., Burow, K.R., and Shelton, J.L., and Fram, M.S., 2024, Data sets for: Status of water quality in groundwater resources used for drinking water supply in the southeast San Joaquin Valley, 2013–2015—California GAMA Priority Basin Project: U.S. Geological Survey data release, accessed January, 22, 2024, at https://doi.org/10.5066/P9DCTLXV","linkHelpText":"Data sets for: Status of water quality in groundwater resources used for drinking water supply in the southeast San Joaquin Valley, 2013–2015—California GAMA Priority Basin Project"},{"id":428120,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5009/sir20245009.xml"},{"id":428118,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5009/covrthb.jpg"},{"id":428121,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5009/images"},{"id":428119,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5009/sir20245009.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.36728753741212,\n 37.719936264455484\n ],\n [\n -121.36728753741212,\n 35.78355104851377\n ],\n [\n -118.20322503741215,\n 35.78355104851377\n ],\n [\n -118.20322503741215,\n 37.719936264455484\n ],\n [\n -121.36728753741212,\n 37.719936264455484\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Conservation propagation facilities in the upper basin of the Missouri River are currently experiencing inconsistent survival of first-feeding larval Pallid Sturgeon Scaphirhynchus albus among genetic families (i.e., distinct male–female pairings). The inconsistent survival can have unintended negative consequences for genetic representation of Pallid Sturgeon that are returned to the Missouri and Yellowstone rivers. We conducted a laboratory study designed to determine whether a live diet improves survival and growth of first-feeding larval Pallid Sturgeon.
First-feeding larval Pallid Sturgeon from three distinct genetic families were assigned to one of the following diets: live first instar brine shrimp (Artemia franciscana) nauplii, an Otohime dry diet, a 50–50% combination of Otohime and live first instar brine shrimp nauplii, or food restricted (no food). Mortality was evaluated at the end of each day and at the end of the trial (21 days after the onset of exogenous feeding), and individual weight (g) was measured at the end of the trial.
Pallid Sturgeon larvae that received a live diet (either solely live first instar brine shrimp nauplii or the combined diet) experienced higher survival than larvae that were fed solely Otohime. Furthermore, there was statistical evidence that larvae receiving solely live first instar brine shrimp nauplii were heavier at 21 days postexogenous feeding than larvae that were fed either solely Otohime or the combined diet.
Our results suggest that a live diet can improve survival and growth of first-feeding larval Pallid Sturgeon at conservation propagation facilities.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/naaq.10340","usgsCitation":"Treanor, H.B., Guy, C.S., Ilgen, J., Sealey, W., Dove, A.T., and Webb, M., 2024, Survival and growth of larval Pallid Sturgeon are improved by a live diet: North American Journal of Aquaculture, v. 86, no. 3, p. 332-339, https://doi.org/10.1002/naaq.10340.","productDescription":"8 p.","startPage":"332","endPage":"339","ipdsId":"IP-158440","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":439745,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/naaq.10340","text":"Publisher Index Page"},{"id":429649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Treanor, Hilary B.","contributorId":200249,"corporation":false,"usgs":false,"family":"Treanor","given":"Hilary","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":902500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":902501,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ilgen, Jason E.","contributorId":276361,"corporation":false,"usgs":false,"family":"Ilgen","given":"Jason E.","affiliations":[{"id":56967,"text":"cct","active":true,"usgs":false}],"preferred":false,"id":902502,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sealey, Wendy M.","contributorId":337561,"corporation":false,"usgs":false,"family":"Sealey","given":"Wendy M.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902503,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dove, Addison T.","contributorId":337563,"corporation":false,"usgs":false,"family":"Dove","given":"Addison","email":"","middleInitial":"T.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":902504,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Webb, Molly A. H.","contributorId":193590,"corporation":false,"usgs":false,"family":"Webb","given":"Molly A. H.","affiliations":[],"preferred":false,"id":902505,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70254841,"text":"70254841 - 2024 - Genetic evidence for the presence of wild-caught sturgeons in commercial markets in Georgia","interactions":[],"lastModifiedDate":"2024-06-10T14:36:30.852808","indexId":"70254841","displayToPublicDate":"2024-04-25T09:32:13","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Genetic evidence for the presence of wild-caught sturgeons in commercial markets in Georgia","docAbstract":"Sturgeons (Family: Acipenseridae) are among the most endangered taxa worldwide. Significant resources have been invested into the conservation of global sturgeon populations, including the development of commercial aquaculture programs. These programs are intended to improve conservation outcomes by reducing the harvest of wild populations while still meeting commercial demand for sturgeon products. However, there is growing concern that commercial aquaculture programs may contribute to wild population declines through continued, illegal harvest and the escape and/or release of captive individuals into wild environments. These concerns may be particularly acute in the country of Georgia which, despite its small territory and altered landscape, is a globally significant hotspot for sturgeon diversity. In order to understand the potential threat of captive culture on wild sturgeon populations in Georgia, we used mitochondrial DNA sequencing and microsatellite analyses to identify the species and origin of sturgeons encountered in commercial settings. Microsatellite analyses showed significant differentiation between wild and commercial Russian sturgeon populations and highlighted the potential for wild-caught individuals to be present in coastal markets in Georgia. The analyses of mitochondrial haplotypes also suggested that commercial markets may contain sturgeon species that are not native to the region. Overall, our results suggest that wild sturgeon populations may still be exploited to support captive aquaculture programs and commercial sales.
","language":"English","publisher":"MDPI","doi":"10.3390/d16050274","usgsCitation":"Beridze, T., White, S.L., Kazyak, D.C., Ninua, L., Fox, D.A., Sethuraman, A., Edisherashvili, T., Roberts, B., Potskhishvili, M., Klailova, M., and Anderson, C., 2024, Genetic evidence for the presence of wild-caught sturgeons in commercial markets in Georgia: Diversity, v. 16, no. 5, 274, 13 p., https://doi.org/10.3390/d16050274.","productDescription":"274, 13 p.","ipdsId":"IP-158954","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":439747,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d16050274","text":"Publisher Index Page"},{"id":429750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Georgia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[41.55408,41.53566],[41.70317,41.96294],[41.45347,42.64512],[40.87547,43.01363],[40.32139,43.12863],[39.95501,43.435],[40.07696,43.5531],[40.92218,43.38216],[42.39439,43.22031],[43.75602,42.74083],[43.9312,42.55497],[44.53762,42.71199],[45.47028,42.50278],[45.77641,42.09244],[46.40495,41.86068],[46.14543,41.7228],[46.63791,41.18167],[46.50164,41.06444],[45.9626,41.12387],[45.21743,41.41145],[44.97248,41.24813],[43.58275,41.09214],[42.61955,41.58317],[41.55408,41.53566]]]},\"properties\":{\"name\":\"Georgia\"}}]}","volume":"16","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Beridze, Tamar","contributorId":299977,"corporation":false,"usgs":false,"family":"Beridze","given":"Tamar","email":"","affiliations":[{"id":63351,"text":"Ilia State University","active":true,"usgs":false}],"preferred":false,"id":902686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Shannon L. 0000-0003-4687-6596","orcid":"https://orcid.org/0000-0003-4687-6596","contributorId":263424,"corporation":false,"usgs":true,"family":"White","given":"Shannon","email":"","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":902687,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":140409,"corporation":false,"usgs":true,"family":"Kazyak","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":902688,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ninua, Levan","contributorId":337799,"corporation":false,"usgs":false,"family":"Ninua","given":"Levan","email":"","affiliations":[{"id":81045,"text":"Faculty of Natural Sciences and Medicine, Ilia State University, Georgia","active":true,"usgs":false}],"preferred":false,"id":902689,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fox, Dewayne A.","contributorId":117052,"corporation":false,"usgs":false,"family":"Fox","given":"Dewayne","email":"","middleInitial":"A.","affiliations":[{"id":12970,"text":"Department of Agriculture and Natural Resources, Delaware State University","active":true,"usgs":false}],"preferred":false,"id":902690,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sethuraman, Arun","contributorId":337800,"corporation":false,"usgs":false,"family":"Sethuraman","given":"Arun","email":"","affiliations":[],"preferred":false,"id":902691,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Edisherashvili, Tamar","contributorId":337801,"corporation":false,"usgs":false,"family":"Edisherashvili","given":"Tamar","email":"","affiliations":[{"id":81045,"text":"Faculty of Natural Sciences and Medicine, Ilia State University, Georgia","active":true,"usgs":false}],"preferred":false,"id":902692,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roberts, Bianca","contributorId":337802,"corporation":false,"usgs":false,"family":"Roberts","given":"Bianca","email":"","affiliations":[{"id":81048,"text":"Fauna & Flora, Caucasus Programme, Georgia","active":true,"usgs":false}],"preferred":false,"id":902693,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Potskhishvili, Mikheil","contributorId":337803,"corporation":false,"usgs":false,"family":"Potskhishvili","given":"Mikheil","email":"","affiliations":[{"id":81048,"text":"Fauna & Flora, Caucasus Programme, Georgia","active":true,"usgs":false}],"preferred":false,"id":902694,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Klailova, Michelle","contributorId":337804,"corporation":false,"usgs":false,"family":"Klailova","given":"Michelle","email":"","affiliations":[{"id":81048,"text":"Fauna & Flora, Caucasus Programme, Georgia","active":true,"usgs":false}],"preferred":false,"id":902695,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Anderson, Cort","contributorId":337805,"corporation":false,"usgs":false,"family":"Anderson","given":"Cort","email":"","affiliations":[{"id":81045,"text":"Faculty of Natural Sciences and Medicine, Ilia State University, Georgia","active":true,"usgs":false}],"preferred":false,"id":902696,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70263482,"text":"70263482 - 2024 - Cytology in cnidaria using Exaiptasia as a model","interactions":[],"lastModifiedDate":"2025-02-12T14:24:23.745139","indexId":"70263482","displayToPublicDate":"2024-04-25T08:21:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Cytology in cnidaria using Exaiptasia as a model","title":"Cytology in cnidaria using Exaiptasia as a model","docAbstract":"A need exists for additional methods to examine cnidaria at the cellular level to aid our understanding of health, anatomy, and physiology of this important group of organisms. This need is particularly acute given that disease is emerging as a major factor in declines of ecologically important functional groups such as corals. Here we describe a simple method to process cnidarian cells for microscopic examination using the model organism Exaiptasia. We show that this organism has at least 18 cell types or structures that can be readily distinguished based on defined morphological features. Some of these cells can be related back to anatomic features of the animal both at the light microscope and ultrastructural level. The cnidome of Exaiptasia may be more complex than what is currently understood. Moreover, cnidarian cells, including some types of cnidocytes, phagocytize cells other than endosymbionts. Finally, our findings shed light on morphologic complexity of cell-associated microbial aggregates and their intimate intracellular associations. The tools described here could be useful for other cnidaria.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/dao03781","usgsCitation":"Work, T.M., Singarkhan, C., and Weatherby, T., 2024, Cytology in cnidaria using Exaiptasia as a model: Diseases of Aquatic Organisms, v. 158, p. 37-53, https://doi.org/10.3354/dao03781.","productDescription":"17 p.","startPage":"37","endPage":"53","ipdsId":"IP-159594","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":487639,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/dao03781","text":"Publisher Index Page"},{"id":481970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"158","noUsgsAuthors":false,"publicationDate":"2024-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":927130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Singarkhan, Chutimon","contributorId":335063,"corporation":false,"usgs":false,"family":"Singarkhan","given":"Chutimon","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":927131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weatherby, Tina","contributorId":193516,"corporation":false,"usgs":false,"family":"Weatherby","given":"Tina","affiliations":[],"preferred":false,"id":927132,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70253192,"text":"70253192 - 2024 - Atmospheric river activity during the late Holocene exceeds modern range of variability in California","interactions":[],"lastModifiedDate":"2024-04-26T12:03:49.92142","indexId":"70253192","displayToPublicDate":"2024-04-25T06:59:17","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13795,"text":"Nature Communications Earth and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Atmospheric river activity during the late Holocene exceeds modern range of variability in California","docAbstract":"Atmospheric rivers are associated with some of the largest flood-producing precipitation events in western North America, particularly California. Insight into past extreme precipitation can be reconstructed from sedimentary archives on millennial timescales. Here we document atmospheric river activity near Leonard Lake, California, over 3,200 years, using a key metric of atmospheric river intensity, that is silicon/aluminum enriched layers that are highly correlated with modern records of integrated vapor transport. The late twentieth century had the highest median integrated vapor transport since the onset of the Medieval Climate Anomaly, with integrated vapor transport increasing during the Little Ice Age. The reconstruction suggests California has experienced pluvial episodes that exceeded any in the meteorologic instrumental era, with the largest episodes occurring two and three millennia ago. These results provide critical data to help avoid underestimation of potential risks and aid future planning scenarios.
Wildlife species confront threats from climate and land use change, exacerbating the influence of extreme climatic events on populations and biodiversity. Migratory waterbirds are especially vulnerable to hydrological drought via reduced availability of surface water habitats. We assessed how whooping cranes (Grus americana) modified habitat use and migration strategies during drought to evaluate their resilience to changing conditions and adaptive capacity. We categorized >8000 night-roost sites used by 146 cranes from 2010 to 2022 and examined relative use during non-drought, moderate drought, and extreme drought conditions. We found cultivated and uncultivated palustrine and lacustrine wetlands were generally used less during droughts than non-drought conditions. Conversely, impounded palustrine and lacustrine systems and rivers served more frequently as drought refugia (i.e., used more during drought than non-drought conditions). Night roosts occurred primarily on private lands (86% overall); public land use decreased with latitude and increased with drought severity, with greatest use (56%) occurring during severe autumn drought in the southern Great Plains. Quantifying use of identified critical habitats in the United States indicated that Cheyenne Bottoms State Waterfowl Management Area and Quivira National Wildlife Refuge were used less during drought, and the Central Platte River and Salt Plains National Wildlife Refuge received similar use during drought compared to non-drought conditions. Our findings provide insights into compensatory use of habitats, where impounded surface water may function in a complementary fashion with natural wetlands. Collectively, these and other types of wetlands distributed across the migration corridor provided a reliable network of habitat available across the Great Plains. A diversity of wetlands available during variable environmental conditions would be useful in supporting continued recovery of whooping cranes and likely have benefits for a wide array of migratory birds.
Bighead carp (Hypophthalmichthys nobilis), silver carp (H. molitrix), black carp (Mylopharyngodon piceus), and grass carp (Ctenopharyngodon idella), are invasive species in North America. However, they hold significant economic importance as food sources in China. The drifting stage of carp eggs has received great attention because egg survival rate is strongly affected by river hydrodynamics. In this study, we explored egg-drift dynamics using computational fluid dynamics (CFD) models to infer potential egg settling zones based on mechanistic criteria from simulated turbulence in the Lower Missouri River. Using an 8-km reach, we simulated flow characteristics with four different discharges, representing 45–3% daily flow exceedance. The CFD results elucidate the highly heterogeneous spatial distribution of flow velocity, flow depth, turbulence kinetic energy (TKE), and the dissipation rate of TKE. The river hydrodynamics were used to determine potential egg settling zones using criteria based on shear velocity, vertical turbulence intensity, and Rouse number. Importantly, we examined the difference between hydrodynamic-inferred settling zones and settling zones predicted using an egg-drift transport model. The results indicate that hydrodynamic inference is useful in determining the ‘potential’ of egg settling, however, egg drifting paths should be taken into account to improve prediction. Our simulation results also indicate that the river turbulence does not surpass the laboratory-identified threshold to pose a threat to carp eggs.
Bathymetric and velocimetric data were collected by the U.S. Geological Survey, in cooperation with the Missouri Department of Transportation, near seven bridges at six highway crossings of the Missouri and Mississippi Rivers on the periphery of Missouri from June 13–22, 2022. A multibeam echosounder mapping system was used to obtain channel-bed elevations for river reaches about 1,640 feet longitudinally and generally extending laterally across the active channel from bank to bank during minor flood-flow conditions. These surveys provided channel geometry and hydraulic conditions at the time of the surveys and provided characteristics of scour holes that may be useful in developing or verifying predictive guidelines or equations for computing potential scour depth. These data also may be useful to the Missouri Department of Transportation as a minor flood-flow assessment of the bridges for stability and integrity issues with respect to bridge scour during floods.
Bathymetric data were collected around every in-channel pier. Scour holes were present at most piers for which bathymetry could be obtained, except those on banks or surrounded by riprap. Occasionally, scour holes were minor and difficult to discern from nearby dunes and ripples. All bridge sites in this study were surveyed and documented in previous studies. Although partial exposure of substructural support elements was observed at several piers, at most sites the exposure most likely is minimal compared to the overall substructure that remains buried in bed material at these piers. The notable exceptions are piers 12 and 13 at structure L0135 on State Highway 51 at Chester, Illinois, where the bedrock material was fully exposed around the piers.
The average difference between the bathymetric surfaces between 2022 and 2018 varied from 0.41 foot higher to 1.86 feet lower. Between 2022 and 2014, the average difference between the bathymetric surfaces varied from 1.02 feet higher to 4.69 feet lower. Only the two sites on the Missouri River and the Caruthersville site were surveyed in 2011; for those sites, the average difference between the bathymetric surfaces varied from 5.83 feet higher to 1.34 feet lower. The most substantial overall net gain of sediment in a reach was between 2011 and 2022 at structure A1700 near Caruthersville, Mo. (site 38). This result was expected because structure A1700 is downstream from the confluences of the Missouri and Ohio Rivers, and therefore subject to the largest streamflows, the largest streamflow fluctuations, and the most substantial sediment flux, as has historically been observed at this site.
The presence of riprap blankets, pier size and nose shape, and alignment to flow had a substantial effect on the size of the scour hole observed for a given pier. Piers that were surrounded by riprap blankets had scour holes that were substantially smaller (to nonexistent) compared to piers at which no rock or riprap were present. New riprap blankets were surveyed at pier 3 of structure L0098 at Brownville, Nebraska, and at piers 15–18 of structure A1700 near Caruthersville, Mo., that effectively mitigated the scour holes historically observed at these piers. Narrow piers having round or sharp noses that were aligned with flow often had scour holes that were difficult to discern from nearby bed features, whereas piers having wide or blunt noses resulted in larger, deeper scour holes. Several of the structures had piers that were skewed to primary approach flow. Scour holes near these piers consistently displayed greater depth on the side of the pier with impinging flow and deposition on the leeward side of the pier.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245032","collaboration":"Prepared in cooperation with Missouri Department of Transportation","usgsCitation":"Huizinga, R.J., 2024, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri and Mississippi Rivers on the periphery of Missouri, June 13–22, 2022: U.S. Geological Survey Scientific Investigations Report 2024–5032, 82 p., https://doi.org/10.3133/sir20245032.","productDescription":"Report: x, 82 p.; Data Release; Dataset","numberOfPages":"96","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-151591","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":428058,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245032/full"},{"id":428056,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5032/sir20245032.XML"},{"id":428054,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5032/coverthb.jpg"},{"id":428055,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5032/sir20245032.pdf","text":"Report","size":"36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024–5032"},{"id":499459,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116369.htm","linkFileType":{"id":5,"text":"html"}},{"id":428060,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":428059,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K66GYC","text":"USGS data release","linkHelpText":"Bathymetry and velocity data from surveys at highway bridges crossing the Missouri and Mississippi Rivers on the periphery of Missouri, June 13–22, 2022"},{"id":428057,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5032/images/"}],"country":"United States","state":"Missouri","otherGeospatial":"Mississippi River, Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.91926710848416,\n 39.14873660952682\n ],\n [\n -90.91926710848416,\n 38.25709077908323\n ],\n [\n -89.90852492098409,\n 38.25709077908323\n ],\n [\n -89.90852492098409,\n 39.14873660952682\n ],\n [\n -90.91926710848416,\n 39.14873660952682\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.85237257723388,\n 39.36990790433225\n ],\n [\n -94.85237257723388,\n 38.70430347732409\n ],\n [\n -94.14924757723371,\n 38.70430347732409\n ],\n [\n -94.14924757723371,\n 39.36990790433225\n ],\n [\n -94.85237257723388,\n 39.36990790433225\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Environmental DNA (eDNA) sampling is an increasingly important tool for answering ecological questions and informing aquatic species management; however, several factors currently limit the reliability of ecological inference from eDNA sampling. Two particular challenges are 1) determining species source location(s) and 2) accurately and precisely measuring low concentration eDNA samples in the presence of multiple sources of ecological and measurement variability. The recently introduced eDNA Integrating Transport and Hydrology (eDITH) model provides a framework for relating eDNA measurements to source locations in riverine networks, but little empirical work has been done to test and refine model assumptions or accommodate low concentration samples, that can be systematically undermeasured. To better understand eDNA fate and transport dynamics and our ability to reliably quantify low concentration samples, we developed a hierarchical model and used it to evaluate a fate and transport experiment. Our model addresses several low concentration challenges by modeling the number of copies in each PCR replicate as a latent variable with a count distribution and conditioning detection and quantification on replicate copy number. We provide evidence that the eDNA removal rate declined through time, estimating that over 80% of eDNA was removed over the first 10 meters, traversed in 41 seconds. After this initial period of rapid decay, eDNA decayed slowly with consistent detection through our farthest site 1km from the release location, traversed in 250 seconds. Our model further allowed us to detect extra-Poisson variation in the allocation of copies to replicates. We extended our hierarchical model to accommodate a continuous effect of inhibitors and used our model to provide evidence for the inhibitor hypothesis and explore the potential implications. While our model is not a panacea for all challenges faced when quantifying low-concentration eDNA samples, it provides a framework for a more complete accounting of uncertainty.
","language":"English","publisher":"BiorXiv","doi":"10.1101/2024.03.27.586987","usgsCitation":"Augustine, B., Hutchins, P., Jones-Slobodian, D.N., Williams, J., Leinonen, E., and Sepulveda, A., 2024, A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples: BioRxiv, https://doi.org/10.1101/2024.03.27.586987.","productDescription":"61 p.","ipdsId":"IP-161502","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":459969,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2024.03.27.586987","text":"External Repository"},{"id":465483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Augustine, Ben 0000-0001-6935-6361","orcid":"https://orcid.org/0000-0001-6935-6361","contributorId":245736,"corporation":false,"usgs":true,"family":"Augustine","given":"Ben","email":"","affiliations":[{"id":49304,"text":"Department of Natural Resources, Cornell University","active":true,"usgs":false}],"preferred":false,"id":912510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hutchins, Patrick Ross 0000-0001-5232-0821","orcid":"https://orcid.org/0000-0001-5232-0821","contributorId":256658,"corporation":false,"usgs":true,"family":"Hutchins","given":"Patrick Ross","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":912511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones-Slobodian, Devin Nicole 0000-0001-9215-2930","orcid":"https://orcid.org/0000-0001-9215-2930","contributorId":305357,"corporation":false,"usgs":true,"family":"Jones-Slobodian","given":"Devin","middleInitial":"Nicole","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":912512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Jacob R.","contributorId":343977,"corporation":false,"usgs":false,"family":"Williams","given":"Jacob R.","affiliations":[{"id":82269,"text":"Turner Institute of Ecoagriculture","active":true,"usgs":false}],"preferred":false,"id":912513,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leinonen, Eric","contributorId":343978,"corporation":false,"usgs":false,"family":"Leinonen","given":"Eric","affiliations":[{"id":82269,"text":"Turner Institute of Ecoagriculture","active":true,"usgs":false}],"preferred":false,"id":912514,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sepulveda, Adam 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":4187,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":912515,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70253898,"text":"70253898 - 2024 - Genetic structure of restored Brook Trout populations in the Southern Appalachian Mountains indicates successful reintroductions","interactions":[],"lastModifiedDate":"2024-07-15T15:03:38.550959","indexId":"70253898","displayToPublicDate":"2024-04-24T08:48:15","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Genetic structure of restored Brook Trout populations in the Southern Appalachian Mountains indicates successful reintroductions","docAbstract":"Wildlife reintroduction is an important conservation tool for threatened species, yet identifying appropriate source populations poses a challenge. In particular, the possibility of outbreeding depression is cited as a constraint limiting the range of candidate source populations for translocation. When multiple source lineages are mixed during reintroduction, genetic monitoring is necessary to evaluate whether sources contribute equally to subsequent generations and whether they are interbreeding as expected. Moreover, statistical analysis of genetic data should account for complex life histories that might affect the timescale of admixture and genetic drift. Here, we use samples collected over a 23-year period and a stochastic age-structured model to analyze the genetic mixing process in reintroduced Brook Trout (Salvelinus fontinalis) populations in the Southern Appalachians. Each restored population was seeded with two to three source populations. Previous research inferred reproductive isolation between source populations leading to a proposal of splitting the species into multiple taxa. In contrast, we found patterns of ancestry that were consistent with random mating and no advantage for one source lineage over any other. Brook Trout from different source streams are mixing as expected in the restoration sites. This result does not support the hypothesis that Brook Trout in the Southern Appalachian Mountains includes several distinct species. Mixing different sources from the same watershed seems to be an effective way to increase genetic diversity of reintroduced populations while minimizing risk to source populations.
","language":"English","publisher":"Springer","doi":"10.1007/s10592-024-01620-y","usgsCitation":"Smith, R.J., Kazyak, D.C., Kulp, M.A., Lubinski, B.A., and Fitzpatrick, B.M., 2024, Genetic structure of restored Brook Trout populations in the Southern Appalachian Mountains indicates successful reintroductions: Conservation Genetics, v. 25, p. 1007-1020, https://doi.org/10.1007/s10592-024-01620-y.","productDescription":"14 p.","startPage":"1007","endPage":"1020","ipdsId":"IP-158952","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":428350,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Tennessee","otherGeospatial":"Great Smoky Mountains National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.90629478474587,\n 35.85116809750147\n ],\n [\n -84.21639200734252,\n 35.85116809750147\n ],\n [\n -84.21639200734252,\n 35.2665417042201\n ],\n [\n -82.90629478474587,\n 35.2665417042201\n ],\n [\n -82.90629478474587,\n 35.85116809750147\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","noUsgsAuthors":false,"publicationDate":"2024-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Rebecca J.","contributorId":229064,"corporation":false,"usgs":false,"family":"Smith","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":41574,"text":"National Park Service, Yellowstone National Park, PO Box 168, 22 Stable Street, Yellowstone National Park, WY, 82190, USA","active":true,"usgs":false}],"preferred":false,"id":900031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":140409,"corporation":false,"usgs":true,"family":"Kazyak","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":900032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kulp, Matt A.","contributorId":196801,"corporation":false,"usgs":false,"family":"Kulp","given":"Matt","email":"","middleInitial":"A.","affiliations":[{"id":35484,"text":"National Park Service, Great Smoky Mountains National Park","active":true,"usgs":false}],"preferred":false,"id":900033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lubinski, Barbara A. 0000-0003-3568-2569","orcid":"https://orcid.org/0000-0003-3568-2569","contributorId":202483,"corporation":false,"usgs":true,"family":"Lubinski","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":900034,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitzpatrick, Benjamin M.","contributorId":336140,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Benjamin","email":"","middleInitial":"M.","affiliations":[{"id":80760,"text":"1. Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, Tennessee","active":true,"usgs":false}],"preferred":false,"id":900035,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70264784,"text":"70264784 - 2024 - Environmental DNA dynamics of three species of unionid freshwater mussels","interactions":[],"lastModifiedDate":"2025-03-24T15:21:21.274494","indexId":"70264784","displayToPublicDate":"2024-04-24T08:17:43","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5840,"text":"Environmental DNA","active":true,"publicationSubtype":{"id":10}},"title":"Environmental DNA dynamics of three species of unionid freshwater mussels","docAbstract":"North American freshwater mussels are of special conservation concern due to their high endemism and the multiple anthropogenic stressors affecting them. Of the over 300 species in North America, nearly one third of these species are federally listed as threatened or endangered. Environmental DNA (eDNA) analysis has been successful in detecting freshwater mussels and could aid in monitoring their populations. Production and degradation rates of eDNA for the species of interest are needed to inform interpretation of eDNA detections, allow possible modeling of relative abundance and population location, and aid in mussel conservation through population identification. Here, we designed and tested qPCR assays for three freshwater mussel species, mucket (Ortmanniana ligamentina), fatmucket (Lampsilis siliquoidea), and the federally endangered spectaclecase (Cumberlandia monodonta). We performed laboratory experiments under controlled conditions to measure eDNA shedding and degradation rates for each species. Different biomasses, temperatures, and food regimens were tested independently to determine if these factors influence the amount of DNA produced by the mussels. Degradation rates of eDNA were measured from experimental tank water after mussels were removed. Overall, we observed low eDNA shedding rates for freshwater mussels compared to previous studies of fish eDNA shedding rates. Furthermore, temperature and feeding showed limited or no significant effects in the species studied. Environmental DNA degradation rates were consistent with those reported in the literature for other taxa. Collectively, our results will be useful for designing eDNA monitoring studies, modeling eDNA dispersal, and interpreting eDNA results to help inform freshwater mussel conservation efforts.
","language":"English","publisher":"Wiley","doi":"10.1002/edn3.543","usgsCitation":"Ruiz-Ramos, D., Thompson, N., Richter, C.A., Voshage, M., Schreier, T.M., Merkes, C.M., and Klymus, K.E., 2024, Environmental DNA dynamics of three species of unionid freshwater mussels: Environmental DNA, v. 6, no. 2, e543, 15 p., https://doi.org/10.1002/edn3.543.","productDescription":"e543, 15 p.","ipdsId":"IP-157659","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":488376,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/edn3.543","text":"Publisher Index Page"},{"id":483719,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruiz-Ramos, Dannise","contributorId":332474,"corporation":false,"usgs":false,"family":"Ruiz-Ramos","given":"Dannise","affiliations":[{"id":78382,"text":"formerly Columbia Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":931669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Nathan 0000-0002-1372-6340 nthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-1372-6340","contributorId":196133,"corporation":false,"usgs":true,"family":"Thompson","given":"Nathan","email":"nthompson@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":931670,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richter, Catherine A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":138994,"corporation":false,"usgs":true,"family":"Richter","given":"Catherine","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":931671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voshage, Megan C.","contributorId":332475,"corporation":false,"usgs":false,"family":"Voshage","given":"Megan C.","affiliations":[{"id":78382,"text":"formerly Columbia Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":931672,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schreier, Theresa M. 0000-0001-7722-6292 tschreier@usgs.gov","orcid":"https://orcid.org/0000-0001-7722-6292","contributorId":3344,"corporation":false,"usgs":true,"family":"Schreier","given":"Theresa","email":"tschreier@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":931673,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Merkes, Christopher M. 0000-0001-8191-627X cmerkes@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-627X","contributorId":139516,"corporation":false,"usgs":true,"family":"Merkes","given":"Christopher","email":"cmerkes@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":931674,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Klymus, Katy E. 0000-0002-8843-6241 kklymus@usgs.gov","orcid":"https://orcid.org/0000-0002-8843-6241","contributorId":5043,"corporation":false,"usgs":true,"family":"Klymus","given":"Katy","email":"kklymus@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":931675,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70253193,"text":"70253193 - 2024 - Spatiotemporal patterns in habitat use of natal and non-natal adult Atlantic sturgeon in two spawning rivers","interactions":[],"lastModifiedDate":"2024-04-26T12:11:30.607528","indexId":"70253193","displayToPublicDate":"2024-04-24T07:07:17","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal patterns in habitat use of natal and non-natal adult Atlantic sturgeon in two spawning rivers","docAbstract":"Monitoring movement across an organism’s ontogeny is often challenging, particularly for long-lived or wide-ranging species. When empirical data are unavailable, general knowledge about species’ ecology may be used to make assumptions about habitat use across space or time. However, inferences about habitat use based on population-level ecology may overlook important eco-evolutionary contributions from individuals with heterogenous ethologies and could diminish the efficacy of conservation and management.
We analyzed over a decade of acoustic telemetry data to understand individual differences in habitat use of federally endangered adult Atlantic sturgeon (Acipenser o. oxyrinchus) in the Delaware and Hudson rivers during spawning season. In particular, we sought to understand whether sex or natal origin could predict patterns in habitat use, as there is a long-held assumption that adult Atlantic sturgeon seldom stray into non-natal rivers.
In both rivers, migration timing, spawning habitat occupancy, and maximum upstream migration distance were similar between natal and non-natal individuals. While non-natal individuals represented only 13% of fish detected in the Hudson River, nearly half of all tagged fish detected in the Delaware River were non-natal and generally occupied freshwater habitats longer than natal individuals. In both systems males had more heterogenous patterns of habitat use and longer duration of occupancy than did females.
This study demonstrates the importance of non-natal rivers for fulfilling ontogenetic habitat requirements in Atlantic sturgeon. Our results may also highlight an opportunity to improve conservation and management by extending habitat designations to account for more heterogenous patterns in individual habitat use in non-natal freshwater environments.
Moderate- or high-severity fires promote increases in runoff and erosion, leading to a greater likelihood of extreme geomorphic responses, including debris flows. In the first several years following fire, the majority of debris flows initiate when runoff rapidly entrains sediment on steep slopes. From a hazard perspective, it is important to be able to anticipate when and where watershed responses will be dominated by debris flows rather than flood flows. Rainfall intensity averaged over a 15 min duration, I15, in particular, has been identified as a key predictor of debris flow likelihood. Developing effective warning systems and predictive models for post-fire debris flow hazards therefore relies on high-temporal resolution rainfall data at the time debris flows initiate. In this study, we documented the geomorphic response of a series of watersheds following a wildfire in western New Mexico, USA, with an emphasis on constraining debris flow timing within rainstorms to better characterize debris-flow-triggering rainfall intensities. We estimated temporal changes in soil hydraulic properties and ground cover in areas burned at different severities over >2 years to offer explanations for observed differences in spatial and temporal patterns in debris flow activity. We observed 16 debris flows, all of which initiated during the first several months following the fire. The average recurrence interval of the debris-flow-triggering I15 is 1.3 years, which highlights the susceptibility of recently burned watersheds to runoff-generated debris flows in this region. All but one of the debris flows initiated in watersheds burned primarily at moderate or high soil burn severity. Since soil hydraulic properties appeared to be relatively resilient to burning, we attribute reduced debris flow activity at later times to decreases in the fraction of bare ground. Results provide additional constraints on the rainfall characteristics that promote post-fire debris flow initiation in a region where fire size and severity have been increasing.
Carotenoid-dependent ornaments can reflect animals’ diet and foraging behaviors. However, this association should be spatially flexible and variable among populations to account for geographic variation in optimal foraging behaviors. We tested this hypothesis using populations of a marine predator (the brown booby, Sula leucogaster) that forage across a gradient in ocean depth in and near the Gulf of California. Specifically, we quantified green chroma for two skin traits (foot and gular color) and their relationship to foraging location and diet of males, as measured via global positioning system tracking and stable carbon isotope analysis of blood plasma. Our three focal colonies varied in which foraging attributes were linked to carotenoid-rich ornaments. For gular skin, our data showed a shift from a benthic prey-green skin association in the shallow waters in the north to a pelagic prey-green skin association in the deepest waters to the south. Mean foraging trip duration and distance of foraging site from coast also predicted skin coloration in some colonies. Finally, brown booby colonies varied in which trait (foot versus gular skin color) was associated with foraging metrics. Overall, our results indicate that male ornaments reflect quality of diet and foraging–information that may help females select mates who are adapted to local foraging conditions and therefore, are likely to provide better parental care. More broadly, our results stress that diet-dependent ornaments are closely linked to animals’ environments and that we cannot assume ornaments or ornament signal content are ubiquitous within species, even when ornaments appear similar among populations.
Eggshell thickness can be an indicator of environmental pollution in wild birds and shell quality in wild and domestic birds, but it is difficult to measure calcite eggshell thickness due to the presence of the adherent outer eggshell membrane. Eggshells of 13 waterbird species were divided in half longitudinally and the outer membrane was removed from one of the halves. Subsequently, we measured eggshell thickness, both with and without the outer eggshell membrane, using a Hall-effect thickness gauge to the nearest 0.001 mm along the equator of each eggshell half. Outer eggshell membrane thicknesses ranged from 0.014 to 0.073 mm. Caspian Tern (Hydroprogne caspia) and California Gull (Larus californicus) had the thickest eggshell membranes (0.056 and 0.073 mm, respectively), and Green Heron (Butorides virescens) and Killdeer (Charadrius vociferus) had the thinnest membranes (0.014 and 0.022 mm, respectively). The eggshell membrane, as a percent of the total eggshell and membrane thickness, varied among the 13 species and ranged among species from 7.9% to 20.6%. The outer membrane comprised a greater percent of the total eggshell and membrane thickness for Black Skimmer (19.3%; Rynchops niger), California Gull (20.5%), and Forster's Tern (20.6%; Sterna forsteri) than for Green Heron (7.9%), Double-crested Cormorant (10.4%; Phalacrocorax auritus), and Western Grebe (10.6%; Aechmophorus occidentalis). Within species, the outer membrane thickness was not correlated with egg morphometrics but, for a subset of species, there was some indication that the calcite eggshell thickness decreases with embryo development (age). We discuss several reasons for conducting future eggshell thickness measurements without removing the membrane.
","language":"English","publisher":"Wilson Ornithological Society","doi":"10.1676/23-00017","usgsCitation":"Santolo, G.M., Peterson, S.H., Cooney, B., Hartman, C.A., Herzog, M.P., and Ackerman, J.T., 2024, Eggshell membrane thickness and its contribution to total eggshell thickness for 13 waterbird species: The Wilson Journal of Ornithology, v. 136, no. 1, p. 62-76, https://doi.org/10.1676/23-00017.","productDescription":"15 p.","startPage":"62","endPage":"76","ipdsId":"IP-159812","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":434977,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HJJ07G","text":"USGS data release","linkHelpText":"Egg Membrane Thickness in 13 Waterbird Species"},{"id":428729,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"136","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Santolo, Gary M.","contributorId":336702,"corporation":false,"usgs":false,"family":"Santolo","given":"Gary","email":"","middleInitial":"M.","affiliations":[{"id":80834,"text":"Jacobs","active":true,"usgs":false}],"preferred":false,"id":900818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":900819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cooney, Breanne","contributorId":336703,"corporation":false,"usgs":false,"family":"Cooney","given":"Breanne","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":900820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":900821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":900822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":900823,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70254125,"text":"70254125 - 2024 - Wetland creation and reforestation of legacy surface mines in the Central Appalachian Region (USA): A potential climate-adaptation approach for pond-breeding amphibians?","interactions":[],"lastModifiedDate":"2024-05-08T11:48:29.128139","indexId":"70254125","displayToPublicDate":"2024-04-24T06:45:15","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Wetland creation and reforestation of legacy surface mines in the Central Appalachian Region (USA): A potential climate-adaptation approach for pond-breeding amphibians?","docAbstract":"This study uses a one-dimensional steady-state hydraulic model and the Fluvial Egg Drift Simulator (FluEgg) to model the drift and dispersion of grass carp eggs and larvae in the Maumee River, Ohio, for 180 scenarios representing different combinations of 10 river flows, 6 water temperatures, and 3 spawning locations. The FluEgg simulations were used to quantify in-river suspended hatching rates (the percentage of eggs that hatch within the river and in suspension) and in-river larval retention rates (the percentage of larvae that reach the gas bladder inflation stage within the river after hatching in suspension), and identify which scenarios produce the highest likelihood of recruitment. The simulations indicate that at low flows, in-river suspended hatching and larval retention rates in the Maumee River are limited by the capacity of the flow to keep fertilized eggs in suspension, whereas at high flows, the limiting factor is the distance available for the eggs/larvae to drift in the river. A wide range of scenarios result in eggs hatching within the river, but all larvae drift into Maumee Bay prior to the gas bladder inflation stage when flows exceed the mean annual flow. The simulations were assessed in the context of the hydraulic conditions that trigger spawning and maximize egg fertilization and the nursery habitat requirements for larval grass carp. The results indicate that the Maumee River, although suitable for grass carp spawning, may not be an ideal setting for recruitment unless Maumee Bay provides adequate nursery habitat for larvae.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2024.102345","usgsCitation":"LeRoy, J.Z., Doyle, H.F., Jackson, P.R., and Cigrand, C.V., 2024, Reproduction of grass carp (Ctenopharyngodon idella) in the Maumee River, Ohio: Part 2—Optimal river conditions for egg and larval drift: Journal of Great Lakes Research, v. 50, 102345, 18 p., https://doi.org/10.1016/j.jglr.2024.102345.","productDescription":"102345, 18 p.","ipdsId":"IP-137490","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":439771,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1016/j.jglr.2024.102345","text":"Publisher Index Page"},{"id":428354,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Maumee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.38518414361491,\n 41.68593497191691\n ],\n [\n -83.45979759899954,\n 41.74305978003929\n ],\n [\n -83.66454217332985,\n 41.60155527334871\n ],\n [\n -83.8481872826162,\n 41.471249401310274\n ],\n [\n -84.12554495228478,\n 41.444009750259625\n ],\n [\n -84.20397403397705,\n 41.37227829616401\n ],\n [\n -84.41243215532246,\n 41.2918512649257\n ],\n [\n -84.35316138453301,\n 41.241526198376704\n ],\n [\n -84.09303055462573,\n 41.30190322738565\n ],\n [\n -84.060513011197,\n 41.379455129599705\n ],\n [\n -83.7812377285593,\n 41.39524150503729\n ],\n [\n -83.38518414361491,\n 41.68593497191691\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"50","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"LeRoy, Jessica Z. 0000-0003-4035-6872 jzinger@usgs.gov","orcid":"https://orcid.org/0000-0003-4035-6872","contributorId":174534,"corporation":false,"usgs":true,"family":"LeRoy","given":"Jessica","email":"jzinger@usgs.gov","middleInitial":"Z.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":900027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doyle, Henry F. 0000-0001-9942-8602 hfdoyle@usgs.gov","orcid":"https://orcid.org/0000-0001-9942-8602","contributorId":243432,"corporation":false,"usgs":true,"family":"Doyle","given":"Henry","email":"hfdoyle@usgs.gov","middleInitial":"F.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":900028,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":900029,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cigrand, Charles V. 0000-0002-4177-7583","orcid":"https://orcid.org/0000-0002-4177-7583","contributorId":201575,"corporation":false,"usgs":true,"family":"Cigrand","given":"Charles","email":"","middleInitial":"V.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":900030,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}