Plague, caused by Yersinia pestis, is a widespread threat to endangered black-footed ferrets (Mustela nigripes) and their primary prey, prairie dogs (Cynomys spp.). Wildlife biologists most commonly manage plague using insecticides to control fleas, the primary vectors of Y. pestis. We tested edible baits containing the insecticides lufenuron and/or nitenpyram in prairie dogs. During a laboratory study, we treated 26 white-tailed prairie dogs (Cynomys leucurus) with lufenuron at 300 mg/kg body mass. All animals remained clinically healthy over the 9 wk monitoring period. Although serum lufenuron concentrations were >130 ppb in two treatment groups at week 1, concentrations declined to ≤60 ppb after 3 wk in non-torpid prairie dogs and after 7 wk in torpid prairie dogs. In a field experiment, we tested baits containing a combination of 75 mg lufenuron and 6 mg nitenpyram, respectively, in black-tailed prairie dogs (Cynomys ludovicianus). We uniformly distributed baits at 125 baits/ha on two plots (treated once) and 250 baits/ha on two plots (each treated twice 4.4 wk apart). Following treatments, flea abundance increased on prairie dogs and remained stable in burrows. Our findings indicate that baits containing lufenuron and nitenpyram, at the reported treatment rates, are ineffective tools for flea control on prairie dogs. Future experiments might evaluate efficacy of higher doses of lufenuron and nitenpyram, and repetitive treatments at differing intervals over time to evaluate potentially therapeutic treatments.
The primary ingredients on the hazard side of the equation include the rapid characterization of the earthquake source and quantifying the spatial distribution of the shaking, plus any secondary hazards an earthquake may have triggered. On the earthquake impact side, loss calculations require the aforementioned hazard assessments—and their uncertainties—as input, plus the quantification of the exposure and vulnerability of structures, infrastructure, and the affected inhabitants. Lastly, effectively communicating uncertain estimates of the resulting impacts on society requires careful consideration of its function and form. All these aspects of rapid earthquake information delivery entailed wide-ranging collaborative research and development among seismologists, earthquake engineers, geographers, social scientists, Information Technology professionals, and communication experts, leveraging diverse components and ingredients not achievable without extensive collaboration. I was very fortunate to be able to work on interesting and useful projects with many colleagues who got involved with them. Advances in content, its rapid delivery, and our ability to better communicate uncertain loss estimates greatly expanded the range of users and critical decision-makers who could directly benefit from rapid post-earthquake information. Moreover, in the critical user–developer feedback loop, we have intently followed requests from users to develop new ways of delivering the most-requested post-earthquake information within the limitations of the science and technology. Such new avenues and tools then motivated and prioritized additional research directions and developments.
Bank- and boat-angler efforts are logistically difficult and costly to estimate, preventing landscape-scale estimates that are required to address current and future challenges (e.g., climate change, invasive species) for inland recreational fisheries. Using a large Nebraska, USA, recreational fishery dataset (N = 67 waterbodies), we demonstrate that waterbody size can be used to predict bank- and boat-angler efforts across a heterogeneous landscape of extra small (< 104 ha) and large (> 647 ha) waterbodies. Bank and boat anglers respond to waterbody size, however these relationships appear to be unique between the two angler types. Boat-angler efforts increased as a function of waterbody size, whereas bank-angler efforts increased as a function of waterbody size for extra small waterbodies but not for large waterbodies. The ability to connect waterbody size and angler effort will be important for continued effective inland fisheries management.
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\"}}]}","volume":"267,","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kanee, D.S.","contributorId":340845,"corporation":false,"usgs":false,"family":"Kanee","given":"D.S.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":907602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koupal, Keith D.","contributorId":340847,"corporation":false,"usgs":false,"family":"Koupal","given":"Keith D.","affiliations":[{"id":17640,"text":"Nebraska Game and Parks Commission","active":true,"usgs":false}],"preferred":false,"id":907604,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pegg, M.A.","contributorId":274523,"corporation":false,"usgs":false,"family":"Pegg","given":"M.A.","affiliations":[{"id":16602,"text":"University of Nebraska, Lincoln","active":true,"usgs":false}],"preferred":false,"id":907605,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chizinski, C.J.","contributorId":340849,"corporation":false,"usgs":false,"family":"Chizinski","given":"C.J.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":907606,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kaemingk, M.A.","contributorId":340850,"corporation":false,"usgs":false,"family":"Kaemingk","given":"M.A.","email":"","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":907607,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70255163,"text":"70255163 - 2023 - Conserving habitat for migratory ungulates: How wide is a migration corridor?","interactions":[],"lastModifiedDate":"2024-06-14T13:32:12.209183","indexId":"70255163","displayToPublicDate":"2023-07-23T08:23:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Conserving habitat for migratory ungulates: How wide is a migration corridor?","docAbstract":"Climate-driven permafrost thaw can release ancient carbon to the atmosphere, begetting further warming in a positive feedback loop. Polar ice core data and young radiocarbon ages of dissolved methane in thermokarst lakes have challenged the importance of this feedback, but field studies did not adequately account for older methane released from permafrost through bubbling. We synthesized panarctic isotope and emissions datasets to derive integrated ages of panarctic lake methane fluxes. Methane age in modern thermokarst lakes (3132 ± 731 years before present) reflects remobilization of ancient carbon. Thermokarst-lake methane emissions fit within the constraints imposed by polar ice core data. Younger, albeit ultimately larger sources of methane from glacial lakes, estimated here, lagged those from thermokarst lakes. Our results imply that panarctic lake methane release was a small positive feedback to climate warming, comprising up to 17% of total northern hemisphere sources during the deglacial period.
Habitat and corridor mapping are key components of many conservation programs. Grizzly bear populations in the continental US are fragmented and connectivity among federal recovery areas is a conservation goal. Building on recent work, we modeled movements to predict areas of connectivity, using integrated step selection functions (iSSFs) developed from GPS-collared grizzly bears (F = 46, M = 19) in the Northern Continental Divide Ecosystem (NCDE). We applied iSSFs in a >300,000 km2 area including the NCDE, Cabinet–Yaak (CYE), Bitterroot (BE), and Greater Yellowstone (GYE) Ecosystems. First, we simulated directed movements (randomized shortest paths with 3 levels of exploration) between start and end nodes across populations. Second, we simulated undirected movements from start nodes in the NCDE, CYE, or GYE (no predetermined end nodes). We summarized and binned results as classes 1 (lowest relative predicted use) – 10 (highest relative predicted use) and evaluated predictions using 127 outlier grizzly bear locations. Connectivity pathways were primarily associated with mountainous areas and secondarily with river and stream courses in open valleys. Values at outlier locations indicated good model fit and mean classes at outlier locations (≥7.4) and Spearman rank correlations (≥0.87) were highest for undirected simulations and directed simulations with the highest level of exploration. Our resulting predictive maps can facilitate on-the-ground application of this research for prioritizing habitat conservation, human-bear conflict mitigation, and transportation planning. Additionally, our overall modeling approach has utility for myriad species and conservation applications.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2023.110199","usgsCitation":"Sells, S.N., Costello, C., Lukacs, P., Roberts, L., and Vinks, M., 2023, Predicted connectivity pathways between grizzly bear ecosystems in western Montana: Biological Conservation, v. 284, 110199, 14 p., https://doi.org/10.1016/j.biocon.2023.110199.","productDescription":"110199, 14 p.","ipdsId":"IP-147522","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":442688,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2023.110199","text":"Publisher Index Page"},{"id":429885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.95053391508199,\n 44.43718455079485\n ],\n [\n -111.00373928161369,\n 44.654761054970265\n ],\n [\n -111.03818726935785,\n 45.07387870212517\n ],\n [\n -108.85212263919709,\n 45.04832534471231\n ],\n [\n -108.66626782395645,\n 49.03152143147685\n ],\n [\n -116.13232385049233,\n 48.92723714245324\n ],\n [\n -116.03762573536355,\n 47.98615190263325\n ],\n [\n -115.57692588139909,\n 47.339026847952084\n ],\n [\n -114.54184801583628,\n 46.55145022278339\n ],\n [\n -114.48564988684791,\n 45.576847377601254\n ],\n [\n -113.90424702051097,\n 45.6284093642955\n ],\n [\n -112.95053391508199,\n 44.43718455079485\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"284","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sells, Sarah Nelson 0000-0003-4859-7160","orcid":"https://orcid.org/0000-0003-4859-7160","contributorId":302377,"corporation":false,"usgs":true,"family":"Sells","given":"Sarah","email":"","middleInitial":"Nelson","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costello, C.M.","contributorId":338295,"corporation":false,"usgs":false,"family":"Costello","given":"C.M.","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":903097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lukacs, P.M.","contributorId":338298,"corporation":false,"usgs":false,"family":"Lukacs","given":"P.M.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":903098,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roberts, L.L.","contributorId":338301,"corporation":false,"usgs":false,"family":"Roberts","given":"L.L.","email":"","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":903099,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vinks, M.A.","contributorId":338305,"corporation":false,"usgs":false,"family":"Vinks","given":"M.A.","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":903100,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70247358,"text":"70247358 - 2023 - Amino acid variation at the mitochondrial binding site of Antimycin A is proposed to reflect sensitivity and toxicity differences among fish species","interactions":[],"lastModifiedDate":"2023-07-31T11:04:51.823706","indexId":"70247358","displayToPublicDate":"2023-07-22T09:52:32","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6476,"text":"Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Amino acid variation at the mitochondrial binding site of Antimycin A is proposed to reflect sensitivity and toxicity differences among fish species","docAbstract":"To better understand differential sensitivities among fish species to the piscicidal compound Antimycin-A (ANT-A), we hypothesized that variations in amino acids at the ANT-A binding site may reflect toxicity differences. Protein sequences for six motifs comprising the ANT-A binding site were obtained and compared for invasive carp species (N = 515) and seven non-target species (N = 277); a consensus was delineated from each species. The carp species, Common Carp (Cyprinus carpio), Silver Carp (Hypophthalmichthys molitrix), Bighead Carp (Hypophthalmichthys nobilis), Grass Carp (Ctenopharyngodon idella), and Black Carp (Mylopharyngodon piceus), showed the same amino acids at the site; thus, it was termed the carp consensus motif sequence (CCM). Channel Catfish (Ictalurus punctatus) showed the most amino acid polymorphisms, with three motifs 96–100% different from CCM. Within a species, Bluegill (Lepomis macrochirus) and Fathead Minnow (Pimephales promelas) variation per motif was most dissimilar (46.7% and 21.6%, respectively). Organismal mortality data from the literature indicated Yellow Perch (Perca flavescens), Walleye (Sander vitreus), and American Gizzard Shad (Dorosoma cepedianum) to be most sensitive to the piscicide, Catfish least sensitive, and all others intermediate. The protein sequence variations of the binding site appeared to be in accord with organismal sensitivity categories when they differed from the CCM; the motifs in Gizzard Shad and Walleye were the same as in CCM. The physical/chemical nature of ANT-A is important to consider in organismal response comparisons. This cellular approach of studying ANT-A binding at its target enzyme is a non-destructive way to predict piscicidal efficacy of ANT-A against fishes of interest, informs management decisions in control efforts for invasives, and can be used to forecast effects on sympatric species.
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and volcanic lithologies. NWA 15507 is a microgabbroic specimen (mean grainsize ~1.4 mm) composed predominantly of zoned Al-Ti-augite, Ca-bearing olivine and anorthite together with accessory kirschsteinite, rhönite, hercynite, low-Ni kamacite, merrillite, magnetite and troilite. Upon initial investigation, the anorthite was found to exhibit a cathodoluminescence (CL) response which revealed a complex history of crystallization. Hyperspectral cathodoluminescence, quantitative electron probe microanalysis mapping, laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), and electron back scattered diffraction (EBSD) were used to determine the CL emitter to better unravel the crystallization history of NWA 15507.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2023 Proceedings microscopy and microanalysis","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Microscopy and Microanalysis","conferenceDate":"July 23-27, 2023","conferenceLocation":"Minneapolis, MN","language":"English","publisher":"Oxford Academic","doi":"10.1093/micmic/ozad067.415","usgsCitation":"Lowers, H.A., Thompson, J.M., Carpenter, P.K., Wilbur, Z., and Irving, A., 2023, Hyperspectral cathodoluminescence and quantitative EPMA mapping of angrite northwest Africa 15507, in 2023 Proceedings microscopy and microanalysis, v. 29, no. Supplement 1, Minneapolis, MN, July 23-27, 2023, p. 836-837, https://doi.org/10.1093/micmic/ozad067.415.","productDescription":"2 p.","startPage":"836","endPage":"837","ipdsId":"IP-150202","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":442695,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1093/micmic/ozad067.415","text":"Publisher Index Page"},{"id":423624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"Supplement 1","noUsgsAuthors":false,"publicationDate":"2023-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Lowers, Heather A. 0000-0001-5360-9264 hlowers@usgs.gov","orcid":"https://orcid.org/0000-0001-5360-9264","contributorId":191307,"corporation":false,"usgs":true,"family":"Lowers","given":"Heather","email":"hlowers@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":890285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Jay M. 0000-0003-3322-0870","orcid":"https://orcid.org/0000-0003-3322-0870","contributorId":329664,"corporation":false,"usgs":true,"family":"Thompson","given":"Jay","middleInitial":"M.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":890286,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carpenter, Paul K.","contributorId":295353,"corporation":false,"usgs":false,"family":"Carpenter","given":"Paul","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":890287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilbur, Zoe","contributorId":332495,"corporation":false,"usgs":false,"family":"Wilbur","given":"Zoe","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":890288,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Irving, Anthony","contributorId":332496,"corporation":false,"usgs":false,"family":"Irving","given":"Anthony","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":890289,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70256531,"text":"70256531 - 2023 - Occupancy and activity patterns of nine-banded Armadillos (Dasypus novemcinctus) in a suburban environment","interactions":[],"lastModifiedDate":"2024-08-16T17:04:07.88155","indexId":"70256531","displayToPublicDate":"2023-07-21T09:45:46","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Occupancy and activity patterns of nine-banded Armadillos (Dasypus novemcinctus) in a suburban environment","docAbstract":"The geographic range of the nine-banded armadillo (Dasypus novemcinctus) has rapidly been expanding within the United States for the last 150 years. One of the factors contributing to this astounding range expansion is the species’ ability to survive in and colonize human-dominated areas. Despite the fact that armadillos live alongside humans in numerous towns and cities across the Southeastern, Southcentral, and now Midwestern United States, we know relatively little about the behavior and ecology of armadillos in human-developed areas. Here, we used motion-triggered game cameras in over 115 residential yards in the rapidly developing Northwest corner of Arkansas to survey armadillos in a largely suburban environment. Our objectives were to explore trends in armadillo occupancy and daily activity patterns in a suburban setting. We documented armadillos in approximately 84% of the yards surveyed indicating that the species was widespread throughout the environment. We found that the species was more likely to occupy yards surrounded by a high proportion of forest cover. We found no relationship between armadillo occupancy and other land cover or development covariates. Only 2% of nearly 2000 armadillo detections occurred during the day indicating that the species is almost exclusively nocturnal during the summer months when living near humans in the suburban environment, which we suggest is likely an adaptation to avoid contact with humans and their dogs. As the armadillo continues to expand its geographic range to areas where it has not previously occurred, understanding how human development supports and facilitates the spread of this species can elucidate areas where conflict between humans and armadillos might occur allowing for preemptive management or education to mitigate conflict.
","language":"English","publisher":"MDPI","doi":"10.3390/d15080907","usgsCitation":"DeGregorio, B.A., McElroy, M.R., and Johansson, E.P., 2023, Occupancy and activity patterns of nine-banded Armadillos (Dasypus novemcinctus) in a suburban environment: Diversity, v. 15, no. 8, p. 907-915, https://doi.org/10.3390/d15080907.","productDescription":"9 p.","startPage":"907","endPage":"915","ipdsId":"IP-153925","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":467100,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d15080907","text":"Publisher Index Page"},{"id":432869,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"northwest Arkansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.63362649934824,\n 36.51285511036747\n ],\n [\n -94.63362649934824,\n 35.53149848763729\n ],\n [\n -92.91995398236419,\n 35.53149848763729\n ],\n [\n -92.91995398236419,\n 36.51285511036747\n ],\n [\n -94.63362649934824,\n 36.51285511036747\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-07-31","publicationStatus":"PW","contributors":{"authors":[{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":910828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McElroy, Matthew R.","contributorId":341036,"corporation":false,"usgs":false,"family":"McElroy","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":81694,"text":"Northeastern State University","active":true,"usgs":false}],"preferred":false,"id":907838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johansson, Emily P.","contributorId":328877,"corporation":false,"usgs":false,"family":"Johansson","given":"Emily","email":"","middleInitial":"P.","affiliations":[{"id":78513,"text":"University of Arkansas, Dept of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":907839,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70247092,"text":"70247092 - 2023 - Prolonged drought in a northern California coastal region suppresses wildfire impacts on hydrology","interactions":[],"lastModifiedDate":"2024-09-16T16:43:11.061729","indexId":"70247092","displayToPublicDate":"2023-07-21T09:31:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Prolonged drought in a northern California coastal region suppresses wildfire impacts on hydrology","docAbstract":"Wildfires naturally occur in many landscapes, however they are undergoing rapid regime shifts. Despite the emphasis in the literature on the most severe hydrological responses to wildfire, there remains a knowledge gap on the thresholds of wildfire (i.e. burned area/drainage area ratio, BAR) required to initiate hydrological responses. We investigated hydrological changes in the Russian River Watershed (RRW) in California, a coastal, Mediterranean, drought-prone, wildfire-adapted ecosystem, following ten wildfires that burned 30% of the watershed. Our findings suggest that sub-watersheds of the RRW have not burned beyond an intrinsic, unknown, threshold required to initiate change. Using paired watersheds, we examined spatiotemporal patterns of pre-and-post wildfire hydrology with a rainfall-runoff hydrological model. Even though these successive wildfires burned 1-50% of each sub-watershed (1-30% at moderate/high severity), we found little evidence of wildfire-related shifts in hydrology. As a function of BAR, wildfire imposed limited effects on runoff ratios (runoff/precipitation) and runoff residuals (observations - model simulations). Our findings that post-wildfire runoff enhancements asymptote beyond 30% burn indicate that when a watershed is burned beyond a certain threshold, the magnitude of the hydrologic response no longer increases. Drought and storm conditions explained much of the variability observed in streamflow, whereas wildfire explained only moderate variability in streamflow even when wildfire accounted for >45% BAR. While the BAR in the RRW was sufficiently beyond previously reported minimum disturbance thresholds (>20% burned forest), the lack of hydrological response is attributed to buffering effects of wildfire adaptation and drought factors that are unique to Mediterranean ecoregions.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR034206","usgsCitation":"Newcomer, M.E., Underwood, J.C., Murphy, S.F., Ulrich, C., Schram, T., Maples, S.R., Pena, J., Siirila-Woodburn, E.R., Trotta, M., Jasperse, J., Seymour, D., and Hubbard, S., 2023, Prolonged drought in a northern California coastal region suppresses wildfire impacts on hydrology: Water Resources Research, v. 59, no. 8, e2022WR034206, 23 p., https://doi.org/10.1029/2022WR034206.","productDescription":"e2022WR034206, 23 p.","ipdsId":"IP-147415","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":442702,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022wr034206","text":"Publisher Index Page"},{"id":419247,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Russian River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.58166191175413,\n 39.66438164966229\n ],\n [\n -123.52362681286694,\n 38.86220749551856\n ],\n [\n -122.91949120418995,\n 38.952501194302044\n ],\n [\n -123.01324021008476,\n 39.6265634050871\n ],\n [\n -123.58166191175413,\n 39.66438164966229\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"59","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Newcomer, Michelle E.","contributorId":317249,"corporation":false,"usgs":false,"family":"Newcomer","given":"Michelle","email":"","middleInitial":"E.","affiliations":[{"id":68983,"text":"Lawrence Berkeley National Laboratory, Earth & Environmental Sciences Area","active":true,"usgs":false}],"preferred":false,"id":878842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Underwood, Jennifer C. 0000-0002-2702-0410 jcunder@usgs.gov","orcid":"https://orcid.org/0000-0002-2702-0410","contributorId":294555,"corporation":false,"usgs":true,"family":"Underwood","given":"Jennifer","email":"jcunder@usgs.gov","middleInitial":"C.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":878843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":878844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ulrich, Craig","contributorId":317250,"corporation":false,"usgs":false,"family":"Ulrich","given":"Craig","affiliations":[{"id":68983,"text":"Lawrence Berkeley National Laboratory, Earth & Environmental Sciences Area","active":true,"usgs":false}],"preferred":false,"id":878845,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schram, Todd","contributorId":317251,"corporation":false,"usgs":false,"family":"Schram","given":"Todd","email":"","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878846,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maples, Stephen R.","contributorId":317252,"corporation":false,"usgs":false,"family":"Maples","given":"Stephen","email":"","middleInitial":"R.","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878847,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pena, Jasquelin","contributorId":317253,"corporation":false,"usgs":false,"family":"Pena","given":"Jasquelin","email":"","affiliations":[{"id":68983,"text":"Lawrence Berkeley National Laboratory, Earth & Environmental Sciences Area","active":true,"usgs":false}],"preferred":false,"id":878848,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Siirila-Woodburn, Erica R.","contributorId":317254,"corporation":false,"usgs":false,"family":"Siirila-Woodburn","given":"Erica","email":"","middleInitial":"R.","affiliations":[{"id":68983,"text":"Lawrence Berkeley National Laboratory, Earth & Environmental Sciences Area","active":true,"usgs":false}],"preferred":false,"id":878849,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Trotta, Marcus","contributorId":317255,"corporation":false,"usgs":false,"family":"Trotta","given":"Marcus","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878850,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jasperse, Jay","contributorId":317256,"corporation":false,"usgs":false,"family":"Jasperse","given":"Jay","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878851,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Seymour, Donald","contributorId":317257,"corporation":false,"usgs":false,"family":"Seymour","given":"Donald","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878852,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hubbard, Susan S.","contributorId":317258,"corporation":false,"usgs":false,"family":"Hubbard","given":"Susan S.","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":878853,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70266268,"text":"70266268 - 2023 - Climatic drivers of estuarine sediment dynamics","interactions":[],"lastModifiedDate":"2025-05-02T14:16:41.321072","indexId":"70266268","displayToPublicDate":"2023-07-21T09:14:15","publicationYear":"2023","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"13","title":"Climatic drivers of estuarine sediment dynamics","docAbstract":"Estuarine sediment dynamics are controlled by myriad physical processes that operate across broad spatiotemporal scales. On the smallest scales, interactions between turbulence and individual particles control mobilization and settling, while interactions across larger scales between freshwater and marine inflow can control decadal timescale geomorphic change. Climate change, through the combined effects of sea-level rise, precipitation intensity, atmospheric variability, and anthropogenic intervention will affect sediment dynamics, geomorphology, and ultimately estuarine function. Therefore, it is imperative to understand the influence of these effects on sediment dynamics to assess the future evolution of estuaries. In this chapter we address the basic tidal, non-tidal, and geologic timescale concepts of estuarine sediment transport, then we illustrate how these concepts may be affected by future climate change. While sea-level rise alone will tend to favor sediment trapping and landward movement of estuaries, human influences within the watershed and estuary, including shoreline stabilization and dredging, may be of similar magnitude. The overarching goal of this chapter is to provide the reader with a basic framework of estuarine sediment transport so they can apply these general concepts to a specific system, under a predicted future state of climate, and develop testable hypotheses on future estuarine geomorphology and function.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Climate Change and Estuaries","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Taylor & Francis","doi":"10.1201/9781003126096","usgsCitation":"Ganju, N., 2023, Climatic drivers of estuarine sediment dynamics, chap. 13 of Climate Change and Estuaries, p. 231-248, https://doi.org/10.1201/9781003126096.","productDescription":"18 p.","startPage":"231","endPage":"248","ipdsId":"IP-134121","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":485322,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2023-07-21","publicationStatus":"PW","contributors":{"editors":[{"text":"Kennish, Michael J.","contributorId":111903,"corporation":false,"usgs":true,"family":"Kennish","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":935628,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Paerl, Hans W.","contributorId":172724,"corporation":false,"usgs":false,"family":"Paerl","given":"Hans","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":935629,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Crosswell, Joseph","contributorId":217003,"corporation":false,"usgs":false,"family":"Crosswell","given":"Joseph","email":"","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":935630,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":935345,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70247696,"text":"70247696 - 2023 - Seed banks of rare Physostegia correllii (Lamiaceae) in Lady Bird Lake, Austin, Texas, U.S.A.","interactions":[],"lastModifiedDate":"2023-08-11T14:13:55.203954","indexId":"70247696","displayToPublicDate":"2023-07-21T09:09:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2535,"text":"Journal of the Botanical Research Institute of Texas","active":true,"publicationSubtype":{"id":10}},"title":"Seed banks of rare Physostegia correllii (Lamiaceae) in Lady Bird Lake, Austin, Texas, U.S.A.","docAbstract":"Rare species threatened by climate and land-use change may harbor seeds in soil seed banks for periods of time even if adults have disappeared from the site. Soil samples were collected from sites with current Phyostegia correllii populations and from sites with former populations in Lady Bird Lake (a reservoir of the Colorado River, Austin, Texas. A seedling emergence study was conducted under greenhouse conditions, and the presence/absence of seedling emergence was recorded for two years. Seeds germinated from the seed banks of all current and former colonies tested. The presence of seed banks in a historical site (Blunn Creek) of Physostegia correllii suggests that management to encourage the germination of seeds might help to encourage the establishment of populations of this species. The re-establishment of disturbance fugitives might be facilitated by removing overhanging ground vegetation or imposing water management regimes that mimic natural floodplain dynamics.
","language":"English","publisher":"Botanical Research Institute of Texas","doi":"10.17348/jbrit.v17.i1.1301","usgsCitation":"Middleton, B., and Williams, C.R., 2023, Seed banks of rare Physostegia correllii (Lamiaceae) in Lady Bird Lake, Austin, Texas, U.S.A.: Journal of the Botanical Research Institute of Texas, v. 17, no. 1, p. 363-368, https://doi.org/10.17348/jbrit.v17.i1.1301.","productDescription":"6 p.","startPage":"363","endPage":"368","ipdsId":"IP-140260","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":442703,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.17348/jbrit.v17.i1.1301","text":"Publisher Index Page"},{"id":435248,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z2KNGL","text":"USGS data release","linkHelpText":"Data Release: Seed banks of rare Physostegia correllii in Lady Bird Johnson Lake, Austin, Texas"},{"id":419744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","city":"Austin","otherGeospatial":"Lady Bird Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97.71632409287069,\n 30.24098994873829\n ],\n [\n -97.70560523792001,\n 30.252833646807105\n ],\n [\n -97.72355308807003,\n 30.251757005975477\n ],\n [\n -97.73152991035897,\n 30.25218766372423\n ],\n [\n -97.74249804100634,\n 30.264675917120925\n ],\n [\n -97.78188360105861,\n 30.286849418007208\n ],\n [\n -97.79010969904377,\n 30.284051097058665\n ],\n [\n -97.76244009672892,\n 30.264460615860244\n ],\n [\n -97.74972703620615,\n 30.259293243994193\n ],\n [\n -97.73427194302117,\n 30.245942941599353\n ],\n [\n -97.71632409287069,\n 30.24098994873829\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":222689,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Casey R.","contributorId":299854,"corporation":false,"usgs":false,"family":"Williams","given":"Casey","email":"","middleInitial":"R.","affiliations":[{"id":64965,"text":"BIO-WEST, Inc.","active":true,"usgs":false}],"preferred":false,"id":880075,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70246987,"text":"fs20233030 - 2023 - Streamflow—Water year 2022","interactions":[],"lastModifiedDate":"2026-02-09T17:33:21.25708","indexId":"fs20233030","displayToPublicDate":"2023-07-20T14:30:50","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3030","displayTitle":"Streamflow—Water Year 2022","title":"Streamflow—Water year 2022","docAbstract":"The maps and graphs describe national streamflow conditions for water year 2022 (October 1, 2021, to September 30, 2022) in the context of streamflow ranks relative to the 93-year period of water years 1930–2022. Annual runoff in the Nation’s rivers and streams during water year 2022 (8.97 inches) was a slighter smaller than the long-term (1930–2022) mean annual runoff of 9.39 inches for the contiguous United States. Nationwide, the 2022 streamflow ranked the 60th highest out of the 93 years.
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415 National Center
Reston, Virginia 20192
Quaternary marine and continental shales in the western United States are sources of selenium that can be loaded into the aquatic environment through mining, agricultural, and energy production processes. The mobilization of selenium from shales through agricultural irrigation has been recognized since the 1930s; however, discovery of deformities in birds and other wildlife using agricultural habitats during the 1980s spurred studies to determine the extent and effects of the contamination. Through these early studies, researchers determined that biota in the Salton Sea drainage basin was at risk from legacy selenium contamination in the Colorado River watershed.
The Salton Sea and its surrounding managed and unmanaged wetlands provide vital inland habitat and trophic support for diverse assemblages of resident and migratory wildlife, and understanding regional selenium hazards for these trust species is a priority for many Federal and State agencies. The modern Salton Sea is a shallow, landlocked saline lake in Riverside and Imperial Counties (not shown) of California that is sustained by irrigation return and perennial river inflow. Changes in water transfer agreements under the 2003 Quantification Settlement Agreement (QSA) have resulted in reduced irrigation flow, declining lake levels, and the evolution of unmanaged wetlands in areas where drains and rivers no longer reach the Salton Sea. These wetlands provide additional habitat for some species of concern, but their potential to increase selenium hazards for trust species is largely unknown.
From the 1980s to 2020, efforts to document selenium contamination and effects throughout the region have resulted in a considerable amount of selenium data from the Salton Sea and its surrounding drainage basin; however, no long-term (greater than 20 years), consistent sampling program has been established, and all data have been collected by different entities using a variety of protocols and analytical techniques. This lack of coordination has been previously documented in regional management plans and has led to difficulty in reliably assessing selenium hazards in the Salton Sea environment. This report provides a summary of the available disparate selenium information collected from water, sediment, and biota in the Salton Sea region since the 1980s and to identify data gaps that need to be filled to understand the potential effects of selenium on species of concern, including federally endangered desert pupfish (Cyprinodon macularius) and Yuma Ridgway’s Rail (Rallus obsoletus yumanensis; formerly Yuma Clapper Rail, Rallus longirostris yumanensis).
Available data from the Salton Sea drainage basin show that water from the Colorado River has the lowest selenium concentration of all surface water sources. All other surface water flowing into the Salton Sea has elevated selenium concentrations due to evaporation and evapotranspiration that occurs in agricultural fields and associated water delivery infrastructure or leaching of selenium from irrigated farmland soils. The Salton Sea has lower selenium concentrations because of various biogeochemical processes that recycle selenium into the sediment or volatilize it to the atmosphere; however, these mechanisms are not well defined, and it is not clear if selenium cycling will change in response to possible changes in the oxidation state of the Salton Sea bottom waters as water levels decline. Agricultural drains have the highest average selenium concentrations, but few drains have been sampled since changes in irrigation practices have occurred (due to the 2003 QSA). Groundwater selenium concentrations are variable; some wells south of the Salton Sea have selenium concentrations as high as 300 micrograms per liter (µg/L), whereas selenium concentrations are below detection in other wells. Groundwater and surface-water geothermal discharge zones around the margins of the Salton Sea and in unmanaged wetlands have not been studied in detail, and published selenium measurements are not available for these surface features.
Selenium concentrations in the sediment of the Salton Sea drainage basin are highest in wetland particulate organic matter and the Salton Sea lakebed, indicating that removal of selenium from the water to the sediment has been a primary mechanism for keeping selenium concentrations low in the water column. Sediment selenium concentrations in wetlands are lower than in the Salton Sea but higher than inflowing drains and rivers, indicating the lentic wetland sites also may be important sinks for selenium because of biogeochemical processes. Sediment selenium data have not been collected in agricultural drains since changes in irrigation practices occurred (due to the 2003 QSA), and it is unknown if selenium sequestration from the water column has changed in these systems.
We divided biological data into broad taxonomic categories, including primary producers, invertebrates, herpetofauna, mammals, fishes, and birds to facilitate evaluation of selenium concentrations and spatiotemporal trends observed in the Salton Sea. Overall, selenium concentrations were substantially greater in algae samples compared to all vascular plant samples combined. Median selenium concentrations in several invertebrate taxa (Chironomidae, Formicidae, Corixidae, Corbiculidae and Nereididae, and Decapoda) exceeded the maximum suggested dietary threshold of 3.0–4.0 micrograms per gram (µg/g) dry weight (dw) for predators consuming invertebrates in aquatic food webs. The greatest number of samples were collected from fish, and selenium distributions among species and locations showed that the range for most samples was lower than the U.S. Environmental Protection Agency selenium criterion for aquatic life (8.5 µg/g dw whole body, 11.3 µg/g dw fillets). The median selenium concentrations for whole body fish were below the selenium criterion in most locations, except for bairdiella (Bairdiella icistia) from the Salton Sea and irrigation drains, a few individual tilapia spp. (family Cichlidae, including genera Tilapia, Oreochromis, and their hybrids) from the river and river outlets, and several western mosquitofish (Gambusia affinis) and sailfin molly (Poecilia latipinna) from irrigation drain outlets. For avian samples combined among years and locations, median selenium concentrations in livers from all families except waders and Ibis (family Threskiornithidae) were higher than levels expected to cause selenium toxicosis (10–20 µg/g dw), and all median egg concentrations were above or near 6.0 μg/g dw, which is a conservative threshold value for reproductive impairment.
Most knowledge gaps we identified for water, sediment, and biota were interrelated, and the use of integrated approaches to address knowledge gaps can provide greater insight into the drivers behind selenium hazards. Integrated water, sediment, and biota studies could help identify cost-effective management solutions that serve multiple purposes. A comprehensive analysis of the hydrology, biogeochemistry, and food-web processes in wetlands and other habitats can inform predictive models to identify drivers of selenium bioavailability, uptake from the environment and subsequent trophic transfer, ultimately forming the basis for experimental habitat management manipulations to minimize selenium hazards to wildlife. Furthermore, a comprehensive, long-term sampling and analytical laboratory plan would enable comparison of data among different entities that are sampling at the Salton Sea. Such efforts are well suited to help fill knowledge gaps that preclude understanding of selenium hazards and future management options for biota using Salton Sea habitats, including newly formed wetlands throughout the region.
All data compiled for this report are available in two U.S. Geological Survey data releases: Groover and others (2022) for water and sediment samples and De La Cruz and others (2022) for biological samples. The data releases include all publicly available data for selenium concentrations in water, sediment, and biological samples collected in and around the Salton Sea, including the Coachella and Imperial Valleys. The data releases also include previously unpublished data.
Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Polychlorinated biphenyls (PCBs), some of the earliest “forever chemicals,” were used for decades in the United States before 1979 when PCB manufacturing was banned. High PCB concentrations were found recently in the lower Clinton River in the Great Lakes drainage. To determine the possible existence, location, and significance of a current source of PCBs, the U.S. Geological Survey (USGS) deployed passive water samplers (SPMDs, semipermeable membrane devices) in the river at 15 sites for 1 month in 2019 near outfalls of interest and other locations. USGS also deployed passive stream sediment samplers at a subset of four sites during the same period and collected bank sediment samples at a subset of four sites. Sediment from nearby catch basins was also collected. Samples were assayed for 209 individual PCB congeners, and patterns in total and individual congeners were evaluated; ancillary sediment data included grain size, total organic carbon, and moisture. U.S. Army Corps of Engineers (USACE) data for total PCBs and 209 PCB congeners in surficial sediment samples collected in 2019 were also evaluated. In general, total PCBs were highest in streambed sediment, followed by catch basin sediment, bank sediment, and then water as estimated from SPMDs. Total PCBs in sediment were low in all catch basins but one (sample CB19–02) that drains from an historical landfill area to one of two adjacent outfalls of interest: the outfall for a nearby wastewater treatment plant and adjacent outfall MTC–R–060, where the highest total PCBs in USGS stream sediment samples were found (site 14, sample 14STRM; 1,260,000 picograms per gram). Also, the SPMD at site 14 was the only water sample with more “light” (three or fewer chlorine atoms) than “heavy” (four or more chlorine atoms) PCB congeners, and the passive sediment sample had the highest proportion of light PCBs in USGS sediment samples. Light PCB congeners degrade more quickly than heavy PCB congeners and results may indicate that one or more current sources of PCBs are contributing to total PCBs in sediment at four river sites. Of 209 possible PCB congeners assayed, 117 congeners were detected in water samples; 155 and 154 congeners were detected in USGS and USACE sediment samples, respectively. PCBs 28, 73, 31, and 18 (highest to lowest) contributed most toward total PCBs in water samples overall; PCBs 20/28, 31, 52, and 44/47/65 contributed most toward total PCBs for sediment in USGS stream samples overall and USACE samples overall; these rankings were also true for catch basins overall except for PCB–31. After omitting coeluting congeners to allow further comparison, 5 key PCB congeners are in the top 20 congeners across all assay groups: 17, 31, 52, 95, and 118. The importance of these congeners in multiple assays aligns with their importance as components of certain Aroclors. Sediment from the high PCB catch basin (sample CB19–02) had a different pattern of top congeners than the other catch basins, and multivariate analyses indicated a high degree of similarity in its overall congener pattern with that of the highest PCB sediment sample (sample 14STRM) collected by the outfalls for the catch basin and the wastewater treatment plant. Similarities in overall congener patterns across sample media as determined by multivariate analyses confirmed some site linkages and the possibility of more than one source of PCBs to the reach. Furthermore, equilibrium partitioning calculations indicated that water concentrations as estimated by SPMDs were high enough to result in the PCB concentrations measured in USGS passive sediment samples but not USACE surficial sediment samples when normalized by organic carbon. However, the SPMDs and passive sediment samples reflect only one month of contribution to the river and higher concentrations would be expected to result with years of PCB accumulation. PCBs contributed to the river water by outfalls could eventually partition to sediment in the reach. Thus, the river could have a current source or sources of PCBs, perhaps one or more outfalls near four sites. Additional investigation is needed to better define the relative significance of each outfall and areas in nearby drainage systems that may be contributing PCBs to outfalls and the river.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235030","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency and the U.S. Army Corps of Engineers","usgsCitation":"Scudder Eikenberry, B.C., Olds, H.T., Stefaniak, O.M., and Alvarez, D.A., 2023, PCB source assessment in the lower Clinton River, Clinton River Area of Concern, Mount Clemens, Michigan: U.S. Geological Survey Scientific Investigations Report 2023–5030, 37 p., https://doi.org/10.3133/sir20235030.","productDescription":"Report: viii, 37 p.; Data Release; Database","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-133016","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":500892,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115014.htm","linkFileType":{"id":5,"text":"html"}},{"id":419191,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235030/full"},{"id":419073,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5030/sir20235030.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023–5030"},{"id":419065,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M870XM","text":"USGS data release","linkHelpText":"Polychlorinated biphenyl (PCB) data from instream water and sediment passive samplers, stream bank sediment, and catch basin sediment in the Clinton River Area of Concern, Michigan, USA, 2019 (Under Revision)"},{"id":419066,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":419064,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5030/sir20235030.pdf","text":"Report","size":"4.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5030"},{"id":419072,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5030/images/"},{"id":419063,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5030/coverthb.jpg"}],"country":"United States","state":"Michigan","city":"Mount Clemens","otherGeospatial":"lower Clinton River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.87419476806319,\n 42.602\n ],\n [\n -82.87419476806319,\n 42.596\n ],\n [\n -82.86189203439089,\n 42.596\n ],\n [\n -82.86189203439089,\n 42.602\n ],\n [\n -82.87419476806319,\n 42.602\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
Gifford Pinchot Drive
Madison, WI 53726
Riverbank groundwater discharge faces are spatially extensive areas of preferential seepage that are exposed to air at low river flow. Some conceptual hydrologic models indicate discharge faces represent the spatial convergence of highly variable age and length groundwater flowpaths, while others indicate greater consistency in source groundwater characteristics. Our detailed field investigation of preferential discharge points nested across mainstem riverbank discharge faces was accomplished by: (1) leveraging new temperature-based recursive estimation (extended Kalman Filter) modelling methodology to evaluate seasonal, diurnal, and event-driven groundwater flux patterns, (2) developing a multi-parameter toolkit based on readily measured attributes to classify the general source groundwater flowpath depth and flowpath length scale, and, (3) assessing whether preferential flow points across discharge faces tend to represent common or convergent groundwater sources. Five major groundwater discharge faces were mapped along the Farmington River, CT, United States using thermal infrared imagery. We then installed vertical temperature profilers directly into 39 preferential discharge points for 4.5 months to track vertical discharge flux patterns. Monthly water chemistry was also collected at the discharge points along with one spatial synoptic of stable isotopes of water and dissolved radon gas. We found pervasive evidence of shallow groundwater sources at the upstream discharge faces along a wide valley section with deep bedrock, as primarily evidenced by pronounced diurnal discharge flux patterns. Discharge flux seasonal trends and bank storage transitions during large river flow events provided further indication of shallow, local sources. In contrast, downstream discharge faces associated with near surface cross cutting bedrock exhibited deep and regional source flowpath characteristics such as more stable discharge patterns and temperatures. However, many neighbouring points across discharge faces had similar discharge flux patterns that differed in chloride and radon concentrations, indicating the additional effects of localized flowpath heterogeneity overprinting on larger scale flowpath characteristics.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14939","usgsCitation":"Haynes, A., Briggs, M., Moore, E., Jackson, K., Knighton, J., Rey, D., and Helton, A., 2023, Shallow and local or deep and regional? Inferring source groundwater characteristics across mainstem riverbank discharge faces: Hydrological Processes, v. 37, no. 7, e14939, 19 p., https://doi.org/10.1002/hyp.14939.","productDescription":"e14939, 19 p.","ipdsId":"IP-151076","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":442704,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.14939","text":"Publisher Index Page"},{"id":419349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut","otherGeospatial":"Farmington River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.716667,\n 41.933\n ],\n [\n -72.8333,\n 41.933\n ],\n [\n -72.8333,\n 41.7833\n ],\n [\n -72.716667,\n 41.7833\n ],\n [\n -72.716667,\n 41.933\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"37","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Haynes, Adam","contributorId":216657,"corporation":false,"usgs":false,"family":"Haynes","given":"Adam","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":222759,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":879121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Eric","contributorId":216658,"corporation":false,"usgs":false,"family":"Moore","given":"Eric","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Kevin","contributorId":317715,"corporation":false,"usgs":false,"family":"Jackson","given":"Kevin","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879123,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knighton, James","contributorId":317716,"corporation":false,"usgs":false,"family":"Knighton","given":"James","email":"","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879124,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rey, David M. 0000-0003-2629-365X","orcid":"https://orcid.org/0000-0003-2629-365X","contributorId":211848,"corporation":false,"usgs":true,"family":"Rey","given":"David M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":879125,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Helton, Ashley","contributorId":219741,"corporation":false,"usgs":false,"family":"Helton","given":"Ashley","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879126,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70247091,"text":"70247091 - 2023 - Ocean current patterns drive the worldwide colonization of eelgrass (Zostera marina)","interactions":[],"lastModifiedDate":"2023-08-23T16:47:30.13571","indexId":"70247091","displayToPublicDate":"2023-07-20T08:39:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5201,"text":"Nature Plants","onlineIssn":"2055-0278","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Ocean current patterns drive the worldwide colonization of eelgrass (Zostera marina)","title":"Ocean current patterns drive the worldwide colonization of eelgrass (Zostera marina)","docAbstract":"Currents are unique drivers of oceanic phylogeography and thus determine the distribution of marine coastal species, along with past glaciations and sea-level changes. Here we reconstruct the worldwide colonization history of eelgrass (Zostera marina L.), the most widely distributed marine flowering plant or seagrass from its origin in the Northwest Pacific, based on nuclear and chloroplast genomes. We identified two divergent Pacific clades with evidence for admixture along the East Pacific coast. Two west-to-east (trans-Pacific) colonization events support the key role of the North Pacific Current. Time-calibrated nuclear and chloroplast phylogenies yielded concordant estimates of the arrival of Z. marina in the Atlantic through the Canadian Arctic, suggesting that eelgrass-based ecosystems, hotspots of biodiversity and carbon sequestration, have only been present there for ~243 ky (thousand years). Mediterranean populations were founded ~44 kya, while extant distributions along western and eastern Atlantic shores were founded at the end of the Last Glacial Maximum (~19 kya), with at least one major refuge being the North Carolina region. The recent colonization and five- to sevenfold lower genomic diversity of the Atlantic compared to the Pacific populations raises concern and opportunity about how Atlantic eelgrass might respond to rapidly warming coastal oceans.
","language":"English","publisher":"Nature","doi":"10.1038/s41477-023-01464-3","usgsCitation":"Yu, L., Khachaturyan, M., Matschiner, M., Healey, A., Bauer, D., Cameron, B., Cusson, M., Duffy, J., Fodrie, F.J., Gill, D., Grimwood, J., Hori, M., Hovel, K., Hughes, A.R., Jahnke, M., Jenkins, J., Keymanesh, K., Kruschel, C., Mamidi, S., Menning, D.M., Moksnes, P., Nakaoka, M., Pennacchio, C., Reiss, K., Rossi, F., Ruesink, J., Schultz, S., Talbott, S., Unsworth, R., Ward, D.H., Dagan, T., Schmutz, J., Eisen, J.A., Stachowicz, J., Van de Peer, Y., Olsen, J.L., and Reusch, T.B., 2023, Ocean current patterns drive the worldwide colonization of eelgrass (Zostera marina): Nature Plants, v. 9, p. 1207-1220, https://doi.org/10.1038/s41477-023-01464-3.","productDescription":"14 p.","startPage":"1207","endPage":"1220","ipdsId":"IP-147613","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":442706,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41477-023-01464-3","text":"Publisher Index Page"},{"id":419244,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2023-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Yu, Lei","contributorId":317220,"corporation":false,"usgs":false,"family":"Yu","given":"Lei","email":"","affiliations":[],"preferred":false,"id":878806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Khachaturyan, Marina","contributorId":317221,"corporation":false,"usgs":false,"family":"Khachaturyan","given":"Marina","email":"","affiliations":[],"preferred":false,"id":878807,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matschiner, Michael","contributorId":317222,"corporation":false,"usgs":false,"family":"Matschiner","given":"Michael","email":"","affiliations":[],"preferred":false,"id":878808,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Healey, Adam","contributorId":317223,"corporation":false,"usgs":false,"family":"Healey","given":"Adam","email":"","affiliations":[],"preferred":false,"id":878809,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bauer, Diane","contributorId":317224,"corporation":false,"usgs":false,"family":"Bauer","given":"Diane","email":"","affiliations":[],"preferred":false,"id":878810,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cameron, Brenda","contributorId":317225,"corporation":false,"usgs":false,"family":"Cameron","given":"Brenda","email":"","affiliations":[],"preferred":false,"id":878811,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cusson, Mathieu","contributorId":317226,"corporation":false,"usgs":false,"family":"Cusson","given":"Mathieu","email":"","affiliations":[],"preferred":false,"id":878812,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Duffy, J. Emmett","contributorId":270555,"corporation":false,"usgs":false,"family":"Duffy","given":"J. Emmett","affiliations":[],"preferred":false,"id":878813,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fodrie, F. Joel","contributorId":317227,"corporation":false,"usgs":false,"family":"Fodrie","given":"F.","email":"","middleInitial":"Joel","affiliations":[],"preferred":false,"id":878814,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gill, Diana","contributorId":317228,"corporation":false,"usgs":false,"family":"Gill","given":"Diana","email":"","affiliations":[],"preferred":false,"id":878815,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Grimwood, Jane","contributorId":317229,"corporation":false,"usgs":false,"family":"Grimwood","given":"Jane","email":"","affiliations":[],"preferred":false,"id":878816,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hori, Masakazu","contributorId":317230,"corporation":false,"usgs":false,"family":"Hori","given":"Masakazu","email":"","affiliations":[],"preferred":false,"id":878817,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hovel, Kevin","contributorId":317231,"corporation":false,"usgs":false,"family":"Hovel","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":878818,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hughes, A. Randall","contributorId":177827,"corporation":false,"usgs":false,"family":"Hughes","given":"A.","email":"","middleInitial":"Randall","affiliations":[],"preferred":false,"id":878819,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Jahnke, Marlene","contributorId":317232,"corporation":false,"usgs":false,"family":"Jahnke","given":"Marlene","email":"","affiliations":[],"preferred":false,"id":878820,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Jenkins, J.","contributorId":317233,"corporation":false,"usgs":false,"family":"Jenkins","given":"J.","email":"","affiliations":[],"preferred":false,"id":878821,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Keymanesh, K.","contributorId":317234,"corporation":false,"usgs":false,"family":"Keymanesh","given":"K.","email":"","affiliations":[],"preferred":false,"id":878822,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Kruschel, C.","contributorId":317235,"corporation":false,"usgs":false,"family":"Kruschel","given":"C.","email":"","affiliations":[],"preferred":false,"id":878823,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Mamidi, S.","contributorId":317236,"corporation":false,"usgs":false,"family":"Mamidi","given":"S.","email":"","affiliations":[],"preferred":false,"id":878824,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Menning, Damian M. 0000-0003-3547-3062 dmenning@usgs.gov","orcid":"https://orcid.org/0000-0003-3547-3062","contributorId":205131,"corporation":false,"usgs":true,"family":"Menning","given":"Damian","email":"dmenning@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":878825,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Moksnes, P.","contributorId":317237,"corporation":false,"usgs":false,"family":"Moksnes","given":"P.","email":"","affiliations":[],"preferred":false,"id":878826,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Nakaoka, M.","contributorId":317238,"corporation":false,"usgs":false,"family":"Nakaoka","given":"M.","email":"","affiliations":[],"preferred":false,"id":878827,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Pennacchio, C.","contributorId":317239,"corporation":false,"usgs":false,"family":"Pennacchio","given":"C.","email":"","affiliations":[],"preferred":false,"id":878828,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Reiss, K.","contributorId":317240,"corporation":false,"usgs":false,"family":"Reiss","given":"K.","email":"","affiliations":[],"preferred":false,"id":878829,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Rossi, F.","contributorId":317241,"corporation":false,"usgs":false,"family":"Rossi","given":"F.","affiliations":[],"preferred":false,"id":878830,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Ruesink, J.","contributorId":317242,"corporation":false,"usgs":false,"family":"Ruesink","given":"J.","affiliations":[],"preferred":false,"id":878831,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Schultz, S.","contributorId":317243,"corporation":false,"usgs":false,"family":"Schultz","given":"S.","email":"","affiliations":[],"preferred":false,"id":878832,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Talbott, S.","contributorId":54327,"corporation":false,"usgs":false,"family":"Talbott","given":"S.","email":"","affiliations":[],"preferred":false,"id":878833,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Unsworth, R.","contributorId":317244,"corporation":false,"usgs":false,"family":"Unsworth","given":"R.","email":"","affiliations":[],"preferred":false,"id":878834,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":878835,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Dagan, T.","contributorId":317245,"corporation":false,"usgs":false,"family":"Dagan","given":"T.","email":"","affiliations":[],"preferred":false,"id":878836,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Schmutz, J.","contributorId":317246,"corporation":false,"usgs":false,"family":"Schmutz","given":"J.","email":"","affiliations":[],"preferred":false,"id":878837,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Eisen, J. A.","contributorId":317266,"corporation":false,"usgs":false,"family":"Eisen","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":878876,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Stachowicz, J.","contributorId":317247,"corporation":false,"usgs":false,"family":"Stachowicz","given":"J.","email":"","affiliations":[],"preferred":false,"id":878838,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Van de Peer, Y.","contributorId":317248,"corporation":false,"usgs":false,"family":"Van de Peer","given":"Y.","email":"","affiliations":[],"preferred":false,"id":878839,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Olsen, J. L.","contributorId":317267,"corporation":false,"usgs":false,"family":"Olsen","given":"J.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":878840,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Reusch, T. B. H.","contributorId":317268,"corporation":false,"usgs":false,"family":"Reusch","given":"T.","email":"","middleInitial":"B. H.","affiliations":[],"preferred":false,"id":878841,"contributorType":{"id":1,"text":"Authors"},"rank":37}]}} ,{"id":70247423,"text":"70247423 - 2023 - Adjacent and downstream effects of forest harvest on the distribution and abundance of larval headwater stream amphibians in the Oregon Coast Range","interactions":[],"lastModifiedDate":"2023-08-04T12:27:36.129329","indexId":"70247423","displayToPublicDate":"2023-07-20T07:25:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Adjacent and downstream effects of forest harvest on the distribution and abundance of larval headwater stream amphibians in the Oregon Coast Range","docAbstract":"Forest harvest is a primary landscape-scale management action affecting riparian forests. Although concerns about impacts of forest harvest on stream amphibians is generally limited to areas adjacent to harvest, there is a paucity of information regarding potential downstream effects of forest harvest on these species. We designed a before-after, control-impact (BACI) experiment to quantify potential impacts of clearcut logging that included 12-m buffers or smaller variable-width buffers on the distribution and abundance of headwater stream amphibians in adjacent and downstream areas. We sampled larval coastal tailed frogs (Ascaphus truei), coastal giant salamanders (Dicamptodon tenebrosus), and Columbia torrent salamanders (Rhyacotriton kezeri) across 3,915 sampling occasions that spanned 13 study reaches in 2008–2011 (pre-harvest) and 2013–2016 (post-harvest) as part of the Trask River Watershed Study in the Oregon Coast Range, U.S.A. We analyzed these data using occupancy models to estimate occupancy and (when possible) relative abundance, while accounting for various sources of imperfect detection. All species exhibited reduced occupancy adjacent to clearcuts with variable-width buffers (odds ratios [ORs] ranged = 0.24–0.48), and these negative impacts were not always diminished when increasing the buffer size to 12 m (ORs ranged = 0.20–3.56). Dicamptodon tenebrosus was the only species to have occupancy impacted in downstream areas, and this negative impact was related to clearcut logging with uniform 12-m buffers (OR = 0.60). This species was also the only species to have abundance negatively impacted by forest harvest in downstream areas (OR = 0.41 with uniform 12-m buffers, OR = 0.38 with variable-width buffers), albeit impacts to abundance were not evaluated for R. kezeri. Ascaphus truei abundance increased in areas downstream of clearcut logging with uniform 12-m buffers (OR = 2.92). Although we found the direction and magnitude of responses varied by species, our study confirms that clearcut logging can have negative impacts on amphibians that inhabit the adjacent stream areas. Perhaps more importantly, we also found that forest harvest can have negative effects on stream amphibians downstream of the harvested area and that increasing the buffer size to 12 m did not necessarily diminish these impacts in adjacent and downstream areas. Altogether, our study provides a nuanced picture of adjacent and downstream effects of forest harvest on three endemic headwater stream amphibians, and our findings demonstrate that forest management practices should consider downstream effects on aquatic taxa when assessing the impact of harvesting trees near headwater streams.
Animal movement is the mechanism connecting landscapes to fitness, and understanding variation in seasonal animal movements has benefited from the analysis and categorization of animal displacement. However, seasonal movement patterns can defy classification when movements are highly variable. Hidden Markov movement models (HMMs) are a class of latent-state models well-suited to modeling movement data. Here, we used HMMs to assess seasonal patterns of variation in the movement of pronghorn (Antilocapra americana), a species known for variable seasonal movements that challenge analytical approaches, while using a population of mule deer (Odocoileus hemionus), for whom seasonal movements are well-documented, as a comparison. We used population-level HMMs in a Bayesian framework to estimate a seasonal trend in the daily probability of transitioning between a short-distance local movement state and a long-distance movement state. The estimated seasonal patterns of movements in mule deer closely aligned with prior work based on indices of animal displacement: a short period of long-distance movements in the fall season and again in the spring, consistent with migrations to and from seasonal ranges. We found seasonal movement patterns for pronghorn were more variable, as a period of long-distance movements in the fall was followed by a winter period in which pronghorn were much more likely to further initiate and remain in a long-distance movement pattern compared with the movement patterns of mule deer. Overall, pronghorn were simply more likely to be in a long-distance movement pattern throughout the year. Hidden Markov movement models provide inference on seasonal movements similar to other methods, while providing a robust framework to understand movement patterns on shorter timescales and for more challenging movement patterns. Hidden Markov movement models can allow a rigorous assessment of the drivers of changes in movement patterns such as extreme weather events and land development, important for management and conservation.
In recent decades the habitat of North American beaver (Castor canadensis) has expanded from boreal forests into Arctic tundra ecosystems. Beaver ponds in Arctic watersheds are known to alter stream biogeochemistry, which is likely coupled with changes in the activity and composition of microbial communities inhabiting beaver pond sediments. We investigated bacterial, archaeal, and fungal communities in beaver pond sediments along tundra streams in northwestern Alaska (AK), USA and compared them to those of tundra lakes and streams in north-central Alaska that are unimpacted by beavers. β-glucosidase activity assays indicated higher cellulose degradation potential in beaver ponds than in unimpacted streams and lakes within a watershed absent of beavers. Beta diversity analyses showed that dominant lineages of bacteria and archaea in beaver ponds differed from those in tundra lakes and streams, but dominant fungal lineages did not differ between these sample types. Beaver pond sediments displayed lower relative abundances of Crenarchaeota and Euryarchaeota archaea and of bacteria from typically anaerobic taxonomic groups, suggesting differences in rates of fermentative organic matter (OM) breakdown, syntrophy, and methane generation. Beaver ponds also displayed low relative abundances of Chytridiomycota (putative non-symbiotic) fungi and high relative abundances of ectomycorrhizal (plant symbionts) Basidiomycota fungi, suggesting differences in the occurrence of plant and fungi mutualistic interactions. Beaver ponds also featured microbes with taxonomic identities typically associated with the cycling of nitrogen and sulfur compounds in higher relative abundances than tundra lakes and streams. These findings help clarify the microbiological implications of beavers expanding into high latitude regions.
Compressional-wave seismic velocity (velocity) and bulk density (density) data were compiled from published sources for rock suites and earth materials that are significant for geophysical modeling of the Mesoproterozoic Midcontinent Rift System in the Lake Superior region. The data include laboratory measurements of outcrop and drill core samples, seismic refraction studies, and a sonic log from a 1.5-kilometer-deep exploration well. Rock suites of the Midcontinent Rift System include basalts of the Mesoproterozoic Keweenawan Supergroup, Oronto Group sedimentary rocks (divided into arenaceous versus argillaceous units), and several sedimentary formations overlying the Oronto Group that have been correlated across the area. Intrusive units include diabase, gabbro, and felsic igneous rocks. Other geologic units important for geophysical modeling in the Lake Superior region include Archean crystalline crust, Paleoproterozoic metasedimentary and crystalline rocks, lower Mesoproterozoic sedimentary rocks, and Holocene to Pleistocene surficial deposits.
Empirical velocity-density relations for each rock suite were determined by comparing the compiled data to published relations, such as the Nafe-Drake curve, Gardner’s relation, and best-fit equations developed for different rock types from laboratory studies. Graphical representations of these velocity-density relations provide a way to easily understand how velocity and density differ between tectonic settings and by rock type. Overlaps in velocity and density ranges for different geologic units are significant and have especially important implications for geologic interpretation of seismic data. Important examples include similar velocities but differing densities for argillaceous Oronto Group versus units overlying the Oronto Group and arenaceous Oronto Group versus basalt of the Keweenawan Supergroup. Similar densities but differing velocities were found for diabase versus gabbro. In addition, expected velocity ranges by rock type show that high-velocity intervals (6.9–7.1 kilometers per second) interpreted as basalt in previous seismic-reflection studies more likely indicate diabase or gabbro, suggesting that these interpretations may warrant additional consideration.
Center Director, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, Mail Stop 973
Denver, CO 80225
The wildland–urban interface (WUI) is where buildings and wildland vegetation meet or intermingle. It is where human–environmental conflicts and risks can be concentrated, including the loss of houses and lives to wildfire, habitat loss and fragmentation and the spread of zoonotic diseases. However, a global analysis of the WUI has been lacking. Here, we present a global map of the 2020 WUI at 10 m resolution using a globally consistent and validated approach based on remote sensing-derived datasets of building area and wildland vegetation. We show that the WUI is a global phenomenon, identify many previously undocumented WUI hotspots and highlight the wide range of population density, land cover types and biomass levels in different parts of the global WUI. The WUI covers only 4.7% of the land surface but is home to nearly half its population (3.5 billion). The WUI is especially widespread in Europe (15% of the land area) and the temperate broadleaf and mixed forests biome (18%). Of all people living near 2003–2020 wildfires (0.4 billion), two thirds have their home in the WUI, most of them in Africa (150 million). Given that wildfire activity is predicted to increase because of climate change in many regions, there is a need to understand housing growth and vegetation patterns as drivers of WUI change.
","language":"English","publisher":"Springer","doi":"10.1038/s41586-023-06320-0","usgsCitation":"Schug, F., Bar-Massada, A., Carlson, A.R., Cox, H., Hawbaker, T., Helmers, D., Hostert, P., Kaim, D., Kasraee, N., Martinuzzi, S., Mockrin, M.H., Pfoch, K.A., and Radeloff, V., 2023, The global wildland-urban interface: Nature, v. 621, p. 94-99, https://doi.org/10.1038/s41586-023-06320-0.","productDescription":"18 p.","startPage":"94","endPage":"99","ipdsId":"IP-147006","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":442714,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41586-023-06320-0","text":"Publisher Index Page"},{"id":421684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Earth","volume":"621","noUsgsAuthors":false,"publicationDate":"2023-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Schug, F.","contributorId":330629,"corporation":false,"usgs":false,"family":"Schug","given":"F.","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":885469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bar-Massada, Avi","contributorId":176995,"corporation":false,"usgs":false,"family":"Bar-Massada","given":"Avi","affiliations":[],"preferred":false,"id":885470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlson, Amanda Renee 0000-0002-0450-2636","orcid":"https://orcid.org/0000-0002-0450-2636","contributorId":303685,"corporation":false,"usgs":true,"family":"Carlson","given":"Amanda","email":"","middleInitial":"Renee","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":885471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cox, H.","contributorId":330630,"corporation":false,"usgs":false,"family":"Cox","given":"H.","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":885472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":885473,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Helmers, D.","contributorId":211616,"corporation":false,"usgs":false,"family":"Helmers","given":"D.","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":885474,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hostert, Patrick","contributorId":294426,"corporation":false,"usgs":false,"family":"Hostert","given":"Patrick","affiliations":[{"id":63572,"text":"Humboldt University of Berlin","active":true,"usgs":false}],"preferred":false,"id":885475,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kaim, D.","contributorId":330634,"corporation":false,"usgs":false,"family":"Kaim","given":"D.","email":"","affiliations":[{"id":78943,"text":"Jagiellonian University","active":true,"usgs":false}],"preferred":false,"id":885476,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kasraee, Neda K.","contributorId":330635,"corporation":false,"usgs":false,"family":"Kasraee","given":"Neda K.","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":885477,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Martinuzzi, S.","contributorId":211621,"corporation":false,"usgs":false,"family":"Martinuzzi","given":"S.","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":885478,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mockrin, Miranda H.","contributorId":296768,"corporation":false,"usgs":false,"family":"Mockrin","given":"Miranda","email":"","middleInitial":"H.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":885479,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Pfoch, Kira A.","contributorId":330637,"corporation":false,"usgs":false,"family":"Pfoch","given":"Kira","email":"","middleInitial":"A.","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":885480,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Radeloff, Volker C.","contributorId":296767,"corporation":false,"usgs":false,"family":"Radeloff","given":"Volker C.","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":885481,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70246879,"text":"ofr20231050 - 2023 - ECCOE Landsat quarterly Calibration and Validation report—Quarter 1, 2023","interactions":[],"lastModifiedDate":"2023-07-20T13:40:55.659896","indexId":"ofr20231050","displayToPublicDate":"2023-07-19T08:10:12","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1050","displayTitle":"ECCOE Landsat Quarterly Calibration and Validation Report—Quarter 1, 2023","title":"ECCOE Landsat quarterly Calibration and Validation report—Quarter 1, 2023","docAbstract":"The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level.
This report provides observed geometric and radiometric analysis results for Landsats 7–8 for quarter 1 (January–March) of 2023. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov.
One specific activity that the ECCOE Landsat Cal/Val Team closely monitored was a Landsat 8 safehold anomaly. On January 26, 2023, the Global Positioning System (GPS) onboard Landsat 8 became invalid because the GPS fault tripped. Later that same day, the GPS was reinitialized, but a Field of View 1 fault trip occurred early the next morning, causing the observatory to go into Earth Point Safe mode, which put the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) into safehold. Once it was safe to reactivate the sensors, the OLI was transitioned to operational status late on January 27 and TIRS was reactivated early on January 28. Additional information about the Landsat 8 safehold anomaly is here: https://www.usgs.gov/landsat-missions/news/landsat-8-recovers-safehold.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231050","usgsCitation":"Haque, M.O., Rengarajan, R., Lubke, M., Hasan, M.N., Shrestha, A., Tuli, F.T.Z., Shaw, J.L., Denevan, A., Franks, S., Micijevic, E., Choate, M.J., Anderson, C., Thome, K., Kaita, E., Barsi, J., Levy, R., and Miller, J., 2023, ECCOE Landsat quarterly Calibration and Validation report—Quarter 1, 2023: U.S. Geological Survey Open-File Report 2023–1050, 39 p., https://doi.org/10.3133/ofr20231050.","productDescription":"Report: vii, 39 p.; Dataset","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-152817","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":419162,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov","text":"USGS database","linkHelpText":"—EarthExplorer"},{"id":419161,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1050/images/"},{"id":419158,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1050/coverthb.jpg"},{"id":419181,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231050/full"},{"id":419160,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1050/ofr20231050.XML"},{"id":419159,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1050/ofr20231050.pdf","text":"Report","size":"4.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1050"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
River turbulence is spatially variable due to interactions between morphology of rivers and physical mechanics of flowing water. Understanding the variation of turbulence in rivers is important for characterizing transport processes of soluble and particulate materials in these systems. We present an exploratory effort to understand ecologically relevant flow patterns using measurements of mean flow and turbulence in a highly engineered river channel around an island in the lower Missouri River. Specifically, the profiles of mean river velocities were investigated to examine the logarithmic relation and associated parameters, including shear velocity and bed roughness. Turbulence intensity and Reynolds shear stress were compared with classic open-channel profiles and previously reported river data in the hydraulics literature. With the capability of pulse-to-pulse coherent Doppler velocity profiling in high spatial resolution, we estimated the profiles of turbulence dissipation rate using resolved one-dimensional velocity spectra. These measurement data allow us to examine the validity of turbulence production-dissipation balance and the classic open-channel profiles of turbulence statistics, including turbulence intensity, Reynolds shear stress, dissipation rate, and eddy viscosity. The field data show a strong variation of turbulence profiles in close vicinity of the river island. In shallow water depths close to the island, turbulence is substantially enhanced in comparison with classic open-channel profiles. Such turbulence enhancement is likely attributed to non-uniformity of the flow structures.