Management of a widely distributed species can be a challenge when management priorities, resource status, and assessment methods vary across jurisdictions. For example, restoration and preservation of coregonine species diversity is a goal of management agencies across the Laurentian Great Lakes. However, management goals and the amount of information available varies across management units, making the focus for management efforts challenging to determine. Genetic data provide a spatially consistent means to assess diversity. Therefore, we examined the genetic stock structure of cisco (Coregonus artedi) in the Great Lakes where the species is still extant. Using genotype data from 17 microsatellite DNA loci, we observed low levels of population structure among collections with most contributions to overall diversity occurring among lakes. Cisco from lakes Superior, Michigan, Ontario, and the St. Marys River could be considered single genetic populations while distinct genetic populations were observed among samples from northern Lake Huron. Significant within-lake diversity in Lake Huron is supported by populations found in embayments in northern Lake Huron. The Grand Traverse Bay population in Lake Michigan represents a distinct population with reduced levels of genetic variation when compared to other lakes. The different levels of within lake population structure we observed will be important to consider as future lake-specific management plans are developed.
It is important to routinely estimate loads from an entire watershed to describe current conditions and evaluate how watershed-wide management efforts have affected the nutrient and sediment export that affect downstream water quality. However, monitoring in most areas, including the Great Lakes watershed, consists of sampling at a limited number of sites that are only periodically used to estimate total watershed loading. Here, we describe a technique to extrapolate loads measured at a limited number of reference sites to the total load from a large watershed using load ratios between monitored sites and unmonitored areas obtained from a watershed model (i.e., model load ratio, MLR, approach). In this study, modeled nonpoint-source load ratios between monitored tributaries (reference sites) and nearby unmonitored areas and point-source delivery factors for all areas were obtained from a Spatially Referenced Regression On Watershed attributes (SPARROW) model and used to extrapolate the measured loads from an ongoing monitoring program (Great Lakes Restoration Initiative Tributary monitoring program) to the entire Great Lakes watershed. The MLR approach incorporates spatial variability in nonpoint- and point-source delivery, watershed characteristics, and hydrology that are often not considered when estimating loads from unmonitored areas, such as using the unit area load (UAL) extrapolation approach. The MLR approach provided smaller watershed loads than the UAL approach because yields from monitored sites, in general, were larger than from unmonitored areas. When both approaches were used to estimate loads at adjacent monitored sites, the MLR approach provided more accurate estimates than the UAL approach.
Stable hydrogen, carbon, nitrogen, oxygen and sulfur (HCNOS) isotope compositions expressed as isotope-delta values are typically reported relative to international standards such as Vienna Standard Mean Ocean Water (VSMOW), Vienna Peedee belemnite (VPDB) or Vienna Cañon Diablo Troilite (VCDT). These international standards are chosen by convention and the calibration methods used to realise them in practice undergo occasional changes. To ensure longevity and reusability of published data, a comprehensive description of (1) analytical procedure, (2) traceability, (3) data processing, and (4) uncertainty evaluation is required. Following earlier International Union of Pure and Applied Chemistry documents on terminology and notations, this paper proposes minimum requirements for publishing HCNOS stable-isotope delta results. Each of the requirements are presented with illustrative examples.
","language":"English","publisher":"De Gruyter","doi":"10.1515/pac-2021-1108","usgsCitation":"Skrzypek, G., Allison, C., Bohlke, J., Bontempo, L., Brewer, P., Camin, F., Carter, J.F., Chartrand, M.M., Coplen, T.B., Groning, M., Helie, J., Esquivel-Hernandez, G., Kraft, R., Magdas, D.A., Mann, J.L., Meija, J., Meijer, H.A., Moossen, H., Ogrinc, N., Perini, M., Possolo, A., Rogers, K., Schimmelmann, A., Shemesh, A., Soto, D.X., Thomas, F., Wielgosz, R., Winchester, M.R., Yan, Z., and Dunn, P.J., 2022, Minimum requirements for publishing hydrogen, carbon, nitrogen, oxygen and sulfur stable-isotope delta results (IUPAC Technical Report): Pure and Applied Chemistry, v. 94, no. 11-12, p. 1249-1255, https://doi.org/10.1515/pac-2021-1108.","productDescription":"7 p.","startPage":"1249","endPage":"1255","ipdsId":"IP-135649","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":445800,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1515/pac-2021-1108","text":"Publisher Index Page"},{"id":418125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","issue":"11-12","noUsgsAuthors":false,"publicationDate":"2022-11-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Skrzypek, Grzegorz 0000-0002-5686-2393","orcid":"https://orcid.org/0000-0002-5686-2393","contributorId":310369,"corporation":false,"usgs":false,"family":"Skrzypek","given":"Grzegorz","email":"","affiliations":[{"id":67153,"text":"West Australian Biogeochemistry Centre, School of Biological Sciences, The University of Western Australia, Crawley, Western Australia, Australia","active":true,"usgs":false}],"preferred":false,"id":875480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allison, Colin 0000-0002-3942-827X","orcid":"https://orcid.org/0000-0002-3942-827X","contributorId":310370,"corporation":false,"usgs":false,"family":"Allison","given":"Colin","email":"","affiliations":[{"id":67154,"text":"Commonwealth Scientific and Industrial Research Organisation, Oceans and Atmosphere, Aspendale, Victoria, Australia","active":true,"usgs":false}],"preferred":false,"id":875481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":37277,"text":"WMA - 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In 2020 ∼70% of global tantalum supply originated in Africa, with 40% produced in the Democratic Republic of Congo alone. The United States has relied entirely on imports since the 1950s. However, quantifying total domestic consumption is problematic because refined tantalum compounds do not have unique tariff codes resulting in significant trade volumes not properly documented. Furthermore, tantalum incorporated into finished goods is not tracked as tantalum. Thus, estimates only capture a fraction of total consumption. We performed a material flow analysis to quantify total domestic tantalum consumption from 2002 to 2020. Our results indicate that consumption may be up to 250% more than previously estimated. Our detailed results allow quantification of tantalum stocks in-use as well as coming out of use any year, providing valuable insight to industry and policymakers for addressing potential supply security issues.
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Center","active":true,"usgs":true}],"preferred":true,"id":858133,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238712,"text":"70238712 - 2022 - An assessment of future tidal marsh resilience in the San Francisco Estuary through modeling and quantifiable metrics of sustainability","interactions":[],"lastModifiedDate":"2022-12-06T12:42:29.067786","indexId":"70238712","displayToPublicDate":"2022-11-25T06:34:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"An assessment of future tidal marsh resilience in the San Francisco Estuary through modeling and quantifiable metrics of sustainability","docAbstract":"Quantitative, broadly applicable metrics of resilience are needed to effectively manage tidal marshes into the future. Here we quantified three metrics of temporal marsh resilience: time to marsh drowning, time to marsh tipping point, and the probability of a regime shift, defined as the conditional probability of a transition to an alternative super-optimal, suboptimal, or drowned state. We used organic matter content (loss on ignition, LOI) and peat age combined with the Coastal Wetland Equilibrium Model (CWEM) to track wetland development and resilience under different sea-level rise scenarios in the Sacramento-San Joaquin Delta (Delta) of California. A 100-year hindcast of the model showed excellent agreement (R2 = 0.96) between observed (2.86 mm/year) and predicted vertical accretion rates (2.98 mm/year) and correctly predicted a recovery in LOI (R2 = 0.76) after the California Gold Rush. Vertical accretion in the tidal freshwater marshes of the Delta is dominated by organic production. The large elevation range of the vegetation combined with high relative marsh elevation provides Delta marshes with resilience and elevation capital sufficiently great to tolerate centenary sea-level rise (CLSR) as high as 200 cm. The initial relative elevation of a marsh was a strong determinant of marsh survival time and tipping point. For a Delta marsh of average elevation, the tipping point at which vertical accretion no longer keeps up with the rate of sea-level rise is 50 years or more. Simulated, triennial additions of 6 mm of sediment via episodic atmospheric rivers increased the proportion of marshes surviving from 51% to 72% and decreased the proportion drowning from 49% to 28%. Our temporal metrics provide critical time frames for adaptively managing marshes, restoring marshes with the best chance of survival, and seizing opportunities for establishing migration corridors, which are all essential for safeguarding future habitats for sensitive species.
Grazing represents the most extensive use of land worldwide. Yet its impacts on ecosystem services remain uncertain because pervasive interactions between grazing pressure, climate, soil properties, and biodiversity may occur but have never been addressed simultaneously. Using a standardized survey at 98 sites across six continents, we show that interactions between grazing pressure, climate, soil, and biodiversity are critical to explain the delivery of fundamental ecosystem services across drylands worldwide. Increasing grazing pressure reduced ecosystem service delivery in warmer and species-poor drylands, whereas positive effects of grazing were observed in colder and species-rich areas. Considering interactions between grazing and local abiotic and biotic factors is key for understanding the fate of dryland ecosystems under climate change and increasing human pressure.
","language":"English","publisher":"American Association for the Advancement of Science (AAAS)","doi":"10.1126/science.abq4062","usgsCitation":"Maestre, F.T., Le Bagousse-Pinguet, Y., Delgado-Baquerizo, M., Eldridge, D., Saiz, H., Berdugo, M., Gozalo, B., Ochoa, V., Guirado, E., García-Gómez, M., Valencia, E., Gaitan, J.J., Asensio, S., Mendoza, B.J., Plaza, C., Diaz-Martinez, P., Rey, A., Hu, H., He, J., Wang, J., Lehmann, A., Rillig, M., Cesarz, S., Eisenhauer, N., Martinez-Valderrama, J., Moreno-Jimenez, E., Sala, O.E., Abedi, M., Ahmadian, N., Alados, C.L., Aramayo, V., Amghar, F., Arredondo, T., Ahumada, R.J., Bahalkeh, K., Ben Salem, F., Blaum, N., Boldgiv, B., Bowker, M., Bran, D., Bu, C., Canessa, R., Castillo-Monroy, A.P., Castro, H., Castro, I., Castro-Quezada, P., Chibani, R., Conceição, A., Currier, C.M., Darrouzet-Nardi, A., Deak, B., Donoso, D.A., Dougill, A.J., Duran, J., Erdenetsetseg, B., Espinosa, C., Fajardo, A., Farzam, M., Ferrante, D., Frank, A.S., Fraser, L.H., Gherardi, L.A., Greenville, A.C., Guerra, C., Gusmán-Montalvan, E., Hernández-Hernández, R., Holzel, N., Huber-Sannwald, E., Hughes, F., Jadan-Maza, O., Jeltsch, F., Jentsch, A., Kaseke, K.F., Kobel, M., Koopman, J.E., Leder, C.V., Linstadter, A., le Roux, P.C., Li, X., Liancourt, P., Liu, J., Louw, M.A., Maggs-Kolling, G., Makhalanyane, T.P., Malam Issa, O., Manzaneda, A.J., Marais, E., Mora, J.P., Moreno, G., Munson, S.M., Nunes, A., Oliva, G., Oñatibia, G., Peter, G., Pivari, M.O., Pueyo, Y., Quiroga, R., Rahmanian, S., Reed, S., Rey, P.J., Richard, B., Rodriguez, A., Rolo, V., Rubalcaba, J.G., Puppert, J.C., Salah, A., Schuchardt, M.A., Spann, S., Stavi, I., Stephens, C.R., Swemmer, A.M., Teixido, A.L., Thomas, A.D., Throop, H.L., Tielborger, K., Travers, S.K., Val, J., Valko, O., van den Brink, L., Velasco Ayuso, S., Velbert, F., Wamiti, W., Wang, D., Wang, L., Wardle, G., Yahdjian, L., Zaady, E., Zhang, Y., Zhou, X., Singh, B.K., and Gross, N., 2022, Grazing and ecosystem service delivery in global drylands: Science, v. 378, no. 6622, p. 915-920, https://doi.org/10.1126/science.abq4062.","productDescription":"6 p.","startPage":"915","endPage":"920","ipdsId":"IP-131591","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":445813,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10486/716905","text":"External Repository"},{"id":411285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"378","issue":"6622","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maestre, Fernando T.","contributorId":207297,"corporation":false,"usgs":false,"family":"Maestre","given":"Fernando","email":"","middleInitial":"T.","affiliations":[{"id":37513,"text":"Departamento de Biología y Geología, Física y Química Inorgánica, ESCET, Universidad Rey Juan Carlos, c/ Tulipán s/n, 28933 Móstoles, Spain","active":true,"usgs":false}],"preferred":false,"id":860364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Le Bagousse-Pinguet, Yoann","contributorId":300372,"corporation":false,"usgs":false,"family":"Le Bagousse-Pinguet","given":"Yoann","email":"","affiliations":[{"id":65094,"text":"Aix Marseille Univ, CNRS, Avignon Université, IRD, IMBE, Aix-en-Provence, France.","active":true,"usgs":false}],"preferred":false,"id":860365,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Delgado-Baquerizo, Manuel","contributorId":214645,"corporation":false,"usgs":false,"family":"Delgado-Baquerizo","given":"Manuel","email":"","affiliations":[{"id":39101,"text":"Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USA","active":true,"usgs":false}],"preferred":false,"id":860366,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eldridge, David J. 0000-0002-2191-486X","orcid":"https://orcid.org/0000-0002-2191-486X","contributorId":66535,"corporation":false,"usgs":false,"family":"Eldridge","given":"David J.","affiliations":[{"id":27407,"text":"Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia","active":true,"usgs":false}],"preferred":false,"id":860367,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Saiz, Hugo","contributorId":300373,"corporation":false,"usgs":false,"family":"Saiz","given":"Hugo","email":"","affiliations":[{"id":65095,"text":"Dept. de Ciencias Agrarias y Medio Natural, Escuela Politécnica Superior, Instituto Universitario de Investigación en Ciencias Ambientales de Aragón, Universidad de Zaragoza, Huesca, Spain","active":true,"usgs":false}],"preferred":false,"id":860368,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Berdugo, 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Universidad de Alicante, Alicante, Spain. 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Box 40658-00100, Nairobi, Kenya","active":true,"usgs":false}],"preferred":false,"id":860485,"contributorType":{"id":1,"text":"Authors"},"rank":122},{"text":"Wang, Deli","contributorId":214265,"corporation":false,"usgs":false,"family":"Wang","given":"Deli","email":"","affiliations":[{"id":39004,"text":"Northeast Normal University","active":true,"usgs":false}],"preferred":false,"id":860486,"contributorType":{"id":1,"text":"Authors"},"rank":123},{"text":"Wang, Lixin","contributorId":300466,"corporation":false,"usgs":false,"family":"Wang","given":"Lixin","affiliations":[{"id":65165,"text":"Department of Earth Sciences, Indiana University–Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA.","active":true,"usgs":false}],"preferred":false,"id":860487,"contributorType":{"id":1,"text":"Authors"},"rank":124},{"text":"Wardle, Glenda M.","contributorId":300467,"corporation":false,"usgs":false,"family":"Wardle","given":"Glenda M.","affiliations":[{"id":65131,"text":"Desert Ecology Research Group, School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia.","active":true,"usgs":false}],"preferred":false,"id":860488,"contributorType":{"id":1,"text":"Authors"},"rank":125},{"text":"Yahdjian, Laura","contributorId":187584,"corporation":false,"usgs":false,"family":"Yahdjian","given":"Laura","email":"","affiliations":[],"preferred":false,"id":860489,"contributorType":{"id":1,"text":"Authors"},"rank":126},{"text":"Zaady, Eli","contributorId":300468,"corporation":false,"usgs":false,"family":"Zaady","given":"Eli","affiliations":[{"id":65166,"text":"Department of Natural Resources, Agricultural Research Organization, Institute of Plant Sciences, Gilat Research Center, Mobile Post Negev, Israel.","active":true,"usgs":false}],"preferred":false,"id":860490,"contributorType":{"id":1,"text":"Authors"},"rank":127},{"text":"Zhang, Yuanming","contributorId":173232,"corporation":false,"usgs":false,"family":"Zhang","given":"Yuanming","email":"","affiliations":[{"id":27200,"text":"Key Laboratory of Biogeography and Bioresource in Arid Land, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China","active":true,"usgs":false}],"preferred":false,"id":860491,"contributorType":{"id":1,"text":"Authors"},"rank":128},{"text":"Zhou, Xiaobing","contributorId":181757,"corporation":false,"usgs":false,"family":"Zhou","given":"Xiaobing","email":"","affiliations":[],"preferred":false,"id":860492,"contributorType":{"id":1,"text":"Authors"},"rank":129},{"text":"Singh, Brajesh K.","contributorId":240762,"corporation":false,"usgs":false,"family":"Singh","given":"Brajesh","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":860493,"contributorType":{"id":1,"text":"Authors"},"rank":130},{"text":"Gross, Nicolas","contributorId":300469,"corporation":false,"usgs":false,"family":"Gross","given":"Nicolas","email":"","affiliations":[{"id":65167,"text":"Université Clermont Auvergne, INRAE, VetAgro Sup, Unité Mixte de Recherche Ecosystème Prairial, Clermont-Ferrand, France.","active":true,"usgs":false}],"preferred":false,"id":860494,"contributorType":{"id":1,"text":"Authors"},"rank":131}]}} ,{"id":70259410,"text":"70259410 - 2022 - Lava fountain jet noise during the 2018 eruption of fissure 8 of Kīlauea volcano","interactions":[],"lastModifiedDate":"2024-10-07T14:47:49.850068","indexId":"70259410","displayToPublicDate":"2022-11-24T09:40:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9121,"text":"Frontiers Earth Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"Lava fountain jet noise during the 2018 eruption of fissure 8 of Kīlauea volcano","docAbstract":"Real-time monitoring is crucial to assess hazards and mitigate risks of sustained volcanic eruptions that last hours to months or more. Sustained eruptions have been shown to produce a low frequency (infrasonic) form of jet noise. We analyze the lava fountaining at fissure 8 during the 2018 Lower East Rift Zone eruption of Kīlauea volcano, Hawaii, and connect changes in fountain properties with recorded infrasound signals from an array about 500 m from the fountain using jet noise scaling laws and visual imagery. Video footage from the eruption reveals a change in lava fountain dynamics from a tall, distinct fountain at the beginning of June to a low fountain with a turbulent, out-pouring lava pond surrounded by a tephra cone by mid-June. During mid-June, the sound pressure level reaches a maximum, and peak frequency drops. We develop a model that uses jet noise scaling relationships to estimate changes in volcanic jet diameter and jet velocity from infrasound sound pressure levels and peak frequencies. The results of this model indicate a decrease in velocity in mid-June which coincides with the decrease in fountain height. Furthermore, the model results suggest an increase in jet diameter, which can be explained by the larger width of the fountain that resembles a turbulent lava pond compared to the distinct fountain at the beginning of June. The agreement between the infrasound-derived and visually observed changes in fountain dynamics suggests that jet noise scaling relationships can be used to monitor lava fountain dynamics using infrasound recordings.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2022.1027408","usgsCitation":"Gestrich, J., Fee, D., Matoza, R., Lyons, J.J., Dietterich, H., Cigala, V., Kueppers, U., Patrick, M.R., and Parcheta, C., 2022, Lava fountain jet noise during the 2018 eruption of fissure 8 of Kīlauea volcano: Frontiers Earth Science Journal, v. 10, 1027408, 18 p., https://doi.org/10.3389/feart.2022.1027408.","productDescription":"1027408, 18 p.","ipdsId":"IP-144544","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467142,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2022.1027408","text":"Publisher Index Page"},{"id":462663,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.40616179843389,\n 19.510647106982844\n ],\n [\n -155.40616179843389,\n 19.352324463279487\n ],\n [\n -155.20934216439622,\n 19.352324463279487\n ],\n [\n -155.20934216439622,\n 19.510647106982844\n ],\n [\n -155.40616179843389,\n 19.510647106982844\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2022-11-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Gestrich, Julia","contributorId":268787,"corporation":false,"usgs":false,"family":"Gestrich","given":"Julia","affiliations":[{"id":50446,"text":"UAF-GI","active":true,"usgs":false}],"preferred":false,"id":915202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fee, David 0000-0002-0936-9977","orcid":"https://orcid.org/0000-0002-0936-9977","contributorId":267231,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":13097,"text":"Geophysical Institute, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":915203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matoza, Robin","contributorId":268788,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":915204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":915205,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915206,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cigala, Valerie","contributorId":344976,"corporation":false,"usgs":false,"family":"Cigala","given":"Valerie","affiliations":[{"id":62362,"text":"LMU","active":true,"usgs":false}],"preferred":false,"id":915207,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kueppers, Ulrich","contributorId":178534,"corporation":false,"usgs":false,"family":"Kueppers","given":"Ulrich","affiliations":[],"preferred":false,"id":915208,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915209,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Parcheta, Carolyn 0000-0001-6556-4630 cparcheta@usgs.gov","orcid":"https://orcid.org/0000-0001-6556-4630","contributorId":215617,"corporation":false,"usgs":true,"family":"Parcheta","given":"Carolyn","email":"cparcheta@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915210,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70238659,"text":"70238659 - 2022 - Editorial: Plant phenology shifts and their ecological and climatic consequences","interactions":[],"lastModifiedDate":"2022-12-02T13:04:45.016779","indexId":"70238659","displayToPublicDate":"2022-11-24T07:02:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5725,"text":"Frontiers in Plant Science","active":true,"publicationSubtype":{"id":10}},"title":"Editorial: Plant phenology shifts and their ecological and climatic consequences","docAbstract":"Climate change is causing plant phenology to shift, with consequences for ecosystems and the Earth’s climate. Over the last decades, the timing of many important phenological events has advanced in spring, such as leaf emergence and flowering, or been delayed in fall, such as leaf coloration and leaf fall. The consequences of such phenological shifts are still largely unknown, but are hypothesized to have cascading effects on ecosystems, carbon and water cycles, and Earths’ climate. With this research topic, we aimed to synthesize and inspire innovative research in plant phenology to address research questions and challenges on the consequences of phenological shifts on ecosystem function and local hydrology. The articles presented here improve our understanding of the physiological mechanisms responsible for the current phenological changes in spring and fall and provide insight into some of the consequences of these changes on hydrological cycles and ecosystem functioning.","language":"English","publisher":"Frontiers","doi":"10.3389/fpls.2022.1071266","usgsCitation":"Fu, Y.H., Prevey, J.S., and Vitasse, Y., 2022, Editorial: Plant phenology shifts and their ecological and climatic consequences: Frontiers in Plant Science, v. 13, 1071266, 3 p., https://doi.org/10.3389/fpls.2022.1071266.","productDescription":"1071266, 3 p.","ipdsId":"IP-146273","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":445816,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fpls.2022.1071266","text":"Publisher Index Page"},{"id":409982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2022-11-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Fu, Yongshuo H.","contributorId":299608,"corporation":false,"usgs":false,"family":"Fu","given":"Yongshuo","email":"","middleInitial":"H.","affiliations":[{"id":64905,"text":"1. College of Water Science, Beijing Normal University, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":858215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prevey, Janet S. 0000-0003-2879-6453","orcid":"https://orcid.org/0000-0003-2879-6453","contributorId":222702,"corporation":false,"usgs":true,"family":"Prevey","given":"Janet","email":"","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vitasse, Yann","contributorId":299609,"corporation":false,"usgs":false,"family":"Vitasse","given":"Yann","email":"","affiliations":[{"id":64907,"text":"3. Swiss Federal Institute for Forest, Snow and Landscape Research, Forest Dynamics, Birmensdorf, Switzerland","active":true,"usgs":false}],"preferred":false,"id":858217,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70246258,"text":"70246258 - 2022 - A reappraisal of explosive–effusive silicic eruption dynamics: Syn-eruptive assembly of lava from the products of cryptic fragmentation","interactions":[],"lastModifiedDate":"2023-06-28T11:47:35.561379","indexId":"70246258","displayToPublicDate":"2022-11-24T06:46:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"A reappraisal of explosive–effusive silicic eruption dynamics: Syn-eruptive assembly of lava from the products of cryptic fragmentation","docAbstract":"Silicic volcanic eruptions range in style from gently effusive to highly explosive, and may switch style unpredictably during a single eruption. Direct observations of subaerial rhyolitic eruptions (Chaiten 2008, Cordón Caulle 2011–2012, Chile) challenged long-standing paradigms of explosive and effusive eruptive styles and led to the formulation of new models of hybrid activity. However, the processes that govern such hybrid explosive–effusive activity remain poorly understood. Here, we bring together observations of the well-studied 2011–2012 Cordón Caulle eruption with new textural and petrologic data on erupted products, and video and still imagery of the eruption. We infer that all of the activity – explosive, effusive, and hybrid – was fed by explosive fragmentation at depth, and that effusive behaviour arose from sticking and sintering, in the shallow vent region, of the clastic products of deeper, cryptic fragmentation. We use a scaling approach to determine that there is sufficient time available, during emplacement, for diffusive pyroclast degassing and sintering to produce a degassed plug that occludes the shallow conduit, feeding clastogenic, apparently effusive, lava-like deposits. Based on evidence from Cordón Caulle, and from other similar eruptions, we further argue that hybrid explosive–effusive activity is driven by episodic gas-fracking of the occluding lava plug, fed by the underlying pressurized ash- and pyroclast-laden region. The presence of a pressurized pocket of ash-laden gas within the conduit provides a mechanism for generation of harmonic tremor, and for syn-eruptive laccolith intrusion, both of which were features of the Cordón Caulle eruption. We conclude that the cryptic fragmentation models is more consistent with available evidence than the prevailing model for effusion of silicic lava that assume coherent non-fragmental rise of magma from depth to the surface without wholesale explosive fragmentation.
The increased risk of coastal flooding associated with climate-change driven sea level rise threatens to displace communities and cause substantial damage to infrastructure. Site-specific adaptation planning is necessary to mitigate the negative impacts of flooding on coastal residents and the built environment. Cost-benefit analyses used to evaluate coastal adaption strategies have traditionally focused on economic considerations, often overlooking potential demographic impacts that can directly influence vulnerability in coastal communities. Here, we present a transferable framework that couples hydrodynamic modeling of flooding driven by sea level rise and storm scenarios with site-specific building stock and census block-level demographic data. We assess the efficacy of multiple coastal adaptation strategies at reducing flooding, economic damages, and impacts to the local population. We apply this framework to evaluate a range of engineered, nature-based, and hybrid adaptation strategies for a portion of Santa Monica Bay, California. Overall, we find that dual approaches that provide protection along beaches using dunes or seawalls and along inlets using sluice gates perform best at reducing or eliminating flooding, damages, and population impacts. Adaptation strategies that include a sluice gate and partial or no protection along the beach are effective at reducing flooding around inlets but can exacerbate flooding elsewhere, leading to unintended impacts on residents. Our results also indicate trade-offs between economic and social risk-reduction priorities. The proposed framework allows for a comprehensive evaluation of coastal protection strategies across multiple objectives. Understanding how coastal adaptation strategies affect hydrodynamic, economic, and social factors at a local scale can enable more effective and equitable planning approaches.
Nest site selection has consequences for hatching success by mediating the temperature and moisture conditions that eggs experience during the incubation period. Understanding the potentially complex pathways by which nest placement influences these abiotic mediators, and therefore hatching success, is important for predicting which nests will be successful and which may require management action. We studied the effects of loggerhead sea turtle (Caretta caretta) nest site selection on hatching success by linking nest placement characteristics to hatching success through a structural equation model. We monitored 170 nests on Ossabaw Island, Georgia, during the summers of 2017 and 2018 and tracked nest conditions throughout the incubation period. Temperature had a complex effect on hatching success—nests had higher hatching rates if they were exposed to higher mean temperatures but also if they experienced both extremely high (>34°C) and extremely low (<26.5°C) temperatures, suggesting that temperature variability plays a role in determining nest outcomes beyond the mean temperature. Likewise, hatching success declined with a higher incidence of nests being inundated by tides. We found that nests placed at the highest elevations had the highest hatching success rates, likely because those nests had a much lower chance of being washed over by high tides and had higher mean temperatures. Nests were also more successful when placed in greater amounts of vegetation, again because vegetated nests were generally warmer and were associated with fewer washover events. These results shed light on the mechanisms behind selection for certain nest site characteristics and can guide the relocation of nests as a conservation action.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps14197","usgsCitation":"Whitesell, M., Hunter, E.A., Rostal, D., and Carroll, J., 2022, Direct and indirect pathways for environmental drivers of hatching success in the loggerhead sea turtle: Marine Ecology Progress Series, v. 701, p. 119-132, https://doi.org/10.3354/meps14197.","productDescription":"14 p.","startPage":"119","endPage":"132","ipdsId":"IP-139067","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481071,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.3354/meps14197","text":"External Repository"},{"id":480923,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Ossabaw Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.16544988349773,\n 31.87085846584084\n ],\n [\n -81.16544988349773,\n 31.71610084390467\n ],\n [\n -81.03274894641083,\n 31.71610084390467\n ],\n [\n -81.03274894641083,\n 31.87085846584084\n ],\n [\n -81.16544988349773,\n 31.87085846584084\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"701","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Whitesell, Mattie J.","contributorId":348695,"corporation":false,"usgs":false,"family":"Whitesell","given":"Mattie J.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":923704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rostal, David C.","contributorId":348698,"corporation":false,"usgs":false,"family":"Rostal","given":"David C.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":923706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carroll, John M.","contributorId":348701,"corporation":false,"usgs":false,"family":"Carroll","given":"John M.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":923707,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70256614,"text":"70256614 - 2022 - Natural resource system size can be used for managing recreational use","interactions":[],"lastModifiedDate":"2024-08-26T16:58:03.87962","indexId":"70256614","displayToPublicDate":"2022-11-23T11:52:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Natural resource system size can be used for managing recreational use","docAbstract":"Outdoor recreation provides societal benefits that are often measured by the amount of use natural resource systems receive. Still, the amount of resource use natural resource systems receive is often unknown or unstudied. Monitoring and quantifying resource use is often logistically difficult and costly but is paramount to optimize societal benefits. Identifying a simple and readily available metric that can indicate the quantity of recreational use of natural resource systems would benefit natural resource management. Using recreational angler participation data during an 11-year study period from 73 public waterbodies in Nebraska, USA, we developed a resource size-use model that demonstrates the ability of natural resource system size to indicate the quantity of recreational use they receive. We demonstrate how resource size-use models can estimate use for unsampled systems, produce broad-scale estimations of use, guide the allocation of resources, and predict how changes in resource system size may affect use. Resource size-use models provide opportunities to manage recreational use, which has been previously elusive for social-ecological systems.
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important controls over global nitrogen (N) cycles. However, C and N concentrations are known to vary among peatlands contributing to the uncertainty of global C inventories, but there are few global studies that relate peatland classification to peat chemistry. We analyzed 436 peat cores sampled in 24 countries across six continents and measured C, N, and organic matter (OM) content at three depths down to 70 cm. Sites were distinguished between northern (387) and tropical (49) peatlands and assigned to one of six distinct broadly recognized peatland categories that vary primarily along a pH gradient. Peat C and N concentrations, OM content, and C:N ratios differed significantly among peatland categories, but few differences in chemistry with depth were found within each category. Across all peatlands C and N concentrations in the 10–20 cm layer, were 440 ± 85.1 g kg-1 and 13.9 ± 7.4 g kg-1, with an average C:N ratio of 30.1 ± 20.8. Among peatland categories, median C concentrations were highest in bogs, poor fens and tropical swamps (446–532 g kg-1) and lowest in intermediate and extremely rich fens (375–414 g kg-1). The C:OM ratio in peat was similar across most peatland categories, except in deeper samples from ombrotrophic tropical peat swamps that were higher than other peatlands categories. Peat N concentrations and C:N ratios varied approximately two-fold among peatland categories and N concentrations tended to be higher (and C:N lower) in intermediate fens compared with other peatland types. This study reports on a unique data set and demonstrates that differences in peat C and OM concentrations among broadly classified peatland categories are predictable, which can aid future studies that use land cover assessments to refine global peatland C and N stocks.
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Geoff","contributorId":346757,"corporation":false,"usgs":false,"family":"Zahn","given":"Geoff","email":"","affiliations":[{"id":40367,"text":"Utah Valley University","active":true,"usgs":false}],"preferred":false,"id":919841,"contributorType":{"id":1,"text":"Authors"},"rank":63}]}} ,{"id":70238431,"text":"sir20225111 - 2022 - Stormwater quantity and quality in selected urban watersheds in Hampton Roads, Virginia, 2016–2020","interactions":[],"lastModifiedDate":"2022-11-23T15:12:52.022733","indexId":"sir20225111","displayToPublicDate":"2022-11-23T09:15:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5111","displayTitle":"Stormwater Quantity and Quality in Selected Urban Watersheds in Hampton Roads, Virginia, 2016–2020","title":"Stormwater quantity and quality in selected urban watersheds in Hampton Roads, Virginia, 2016–2020","docAbstract":"Urbanization can substantially alter sediment and nutrient loadings to streams. Although a growing body of literature has documented these processes, conditions may vary widely by region and physiographic province (PP). Substantial investments are made by localities to meet federal, state, and local water-quality goals and locally relevant monitoring data are needed to appropriately set standards and track progress. In 2016, a long-term stormwater monitoring program was initiated to characterize water-quality and streamflow conditions and compute average annual nutrient- and sediment-loading rates across the three dominant land-use types—commercial (COM), high-density residential, and single-family residential (SFR)—in the Hampton Roads metropolitan region within the Coastal Plain PP in southeastern Virginia. This report summarizes the first five years of data collection to (1) assess patterns in streamflow and water chemistry across the three major land-use types in the region; (2) compute annual sediment and nutrient loads; and (3) compare annual loading rates to those in other urbanized regions.
Patterns in watershed hydrology characteristics and conditions were similar to those observed in other urban monitoring studies. Base-flow indices were lower and stream flashiness indices were higher in the study watersheds compared to those in less developed reference watersheds. These patterns reflect a decrease in infiltration and consequent increase in storm runoff as a result of urbanization. Stream flashiness was strongly positively related to degree of impervious land cover and negatively to watershed area. Hydrologic metrics varied across the land-use gradient, reflecting greater and more rapid runoff in the COM watersheds than in SFR watersheds. Event-based analyses conducted exclusively on periods of runoff highlight longer duration events, longer time-to-peak streamflow, and a longer lag between peak precipitation and peak streamflow in SFR watersheds, and higher stormflow yields, runoff ratios, and peak flows in COM watersheds. Event-based metrics varied seasonally because of regional meteorological patterns.
Concentrations of total suspended solids (TSS) and total phosphorus (TP) were positively correlated to streamflow, whereas concentrations of total nitrogen (TN) varied little across the hydrologic regime. Phosphorus composition varied spatially and seasonally—the proportion of orthophosphate (PO43-) was highest in samples collected from stations draining residential land-use types and was elevated in summer and fall. Nitrogen composition varied with hydrologic condition: nitrate plus nitrite (NO3-) dominance during base flow shifted to total organic nitrogen (TON) dominance during periods of runoff. For all three major constituents (TSS, TP, and TN), concentrations were highest in SFR watersheds, whereas yields were greatest in COM watersheds. This seeming contradiction in concentration and yield across land-use types occurred because of spatial differences in streamflow yield.
The network average TSS yield in Hampton Roads was lower than that in comparable networks in Fairfax County, Virginia, and Gwinnett County, Georgia, a difference that may reflect dissimilarities in the topographic and soil characteristics of the Coastal Plain versus those in Piedmont PPs, as well as differences in engineered concrete stormwater conveyances versus earthen streams. The average annual TP yield in Hampton Roads was higher than averages reported in comparison studies and was primarily driven by elevated PO43-. Elevated PO43- yields may be related to unique soil and geological features of the Coastal Plain PP that limit phosphorus retention. Total nitrogen yields in the Hampton Roads and Fairfax County networks were similar; however, composition did vary, with greater total organic nitrogen yields in Hampton Roads and greater NO3- yields in Fairfax County.
Cross-correlation analyses and mass-volume curves were used to assess the timing of sediment and nutrient loadings. The majority of TSS and TP was typically transported during the initial phase of a storm-runoff event, a phenomenon commonly termed the “first flush.” Although TN concentrations typically peaked within an hour of peak streamflow, reflecting the particulate dominance of TN during stormflows, and loadings were greater during the early phase of most storm events, the stricter first-flush criterion was rarely met. This suggests that the most abundant sources of TN in these watersheds are not as directly connected to the stormwater-conveyance system as are TSS and TP.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225111","isbn":"978-1-4113-4488-4","collaboration":"Prepared in cooperation with the Hampton Roads Planning District Commission","usgsCitation":"Porter, A.J., 2022, Stormwater quantity and quality in selected urban watersheds in Hampton Roads, Virginia, 2016–2020: U.S. Geological Survey Scientific Investigations Report 2022–5111, 77 p., https://doi.org/10.3133/sir20225111.","productDescription":"Report: xi, 77 p.; Data Release","numberOfPages":"77","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-140434","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":409552,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225111/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5111"},{"id":409543,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XMPEND","text":"USGS data release","linkHelpText":"Inputs and selected outputs used to assess stormwater quality and quantity in twelve urban watersheds in Hampton Roads, Virginia, 2016–2020"},{"id":409542,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5111/images/"},{"id":409539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5111/sir20225111.pdf","text":"Report","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5111"},{"id":409541,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5111/sir20225111.XML"},{"id":409538,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5111/coverthb.jpg"}],"country":"United States","state":"Virginia","city":"Hampton Roads","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.14335620670732,\n 36.90313369880009\n ],\n [\n -76.31812685340054,\n 37.07905097755574\n ],\n [\n -76.51786473533596,\n 37.10821243098252\n ],\n [\n -76.55620727517176,\n 37.13025388344366\n ],\n [\n -76.59365716752067,\n 37.16650105362895\n ],\n [\n -76.62219115065432,\n 37.1295423598058\n ],\n [\n -76.47773786104024,\n 37.03208397181615\n ],\n [\n -76.4179948338545,\n 36.95587973488442\n ],\n [\n -76.23519900440459,\n 36.804670263024434\n ],\n [\n -76.11036282819533,\n 36.821803342395526\n ],\n [\n -76.14335620670732,\n 36.90313369880009\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Virginia and West Virginia Water Science Center
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In this report, we consider evolutionary and ecological connectivity for westslope cutthroat trout (Oncorhynchus clarkii lewisi) and mountain whitefish (Prosopium williamsoni) within the Pend Oreille River in northeastern Washington State, northern Idaho, and adjacent portions of southeastern British Columbia, Canada. Specifically, we focused on the rationale for active translocation of individuals of these species upstream from Boundary Dam both in the context of natural patterns of pre-dam evolutionary connectivity as well as preserving contemporary ecological and evolutionary characteristics of local extant populations. Boundary Dam impounds the Pend Oreille River (called the Pend d’Oreille River in Canada) with the resulting reservoir inundating two historical barriers to upstream movement of fish (Metaline Falls and Z Canyon). Historically, it was thought these barriers impeded the upstream movement of westslope cutthroat trout and mountain whitefish, as well as Pacific salmon (Oncorhynchus spp.), steelhead trout (O. mykiss), and other resident species such as bull trout (Salvelinus confluentus). To address connectivity, we consider historical and contemporary processes and features. This review includes an assessment of postglacial processes within the Pend Oreille River and systems upstream that include Priest Lake, Lake Pend Oreille, the Clark Fork River, features of Boundary Reservoir and its tributaries, and areas downstream in the Pend Oreille River such as the Salmo River. Based on this information, we then give a more detailed review of existing genetic and ecological data to summarize what is known about connectivity for westslope cutthroat trout and mountain whitefish. Our assessment of the collective evidence leads us to conclude that moving fish upstream over Boundary Dam is not warranted if the management objective is to maintain natural patterns of evolutionary and ecological connectivity or to conserve unique ecological and evolutionary characteristics of extant local populations of these species in the system. These findings parallel that of a previous analysis of bull trout. Although we were able to arrive at well-supported conclusions in relation to Boundary Dam, we suggest that more work on connectivity further upstream in the Pend Oreille River would help to better understand the role of historical processes and dams further up in the system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221084","collaboration":"Prepared in cooperation with the University of British Columbia, Biodiversity Research Centre and Beaty Biodiversity Museum, and Idaho State University, Department of Biological Sciences, Fish Ecology Laboratory","usgsCitation":"Dunham, J.B., Taylor, E.B., and Keeley, E.R., 2022, Evolutionary and ecological connectivity in westslope cutthroat\ntrout (Oncorhynchus clarkii lewisi) and mountain whitefish (Prosopium williamsoni) in relation to the potential\ninfluences of Boundary Dam, Washington, Idaho, and parts of British Columbia: U.S. Geological Survey Open-File\nReport 2022–1084, 22 p., https://doi.org/10.3133/ofr20221084.","productDescription":"vii, 22 p.","onlineOnly":"Y","ipdsId":"IP-137003","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":409558,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1084/coverthb.jpg"},{"id":409559,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1084/ofr20221084.pdf","text":"Report","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1084"},{"id":409561,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1084/images"},{"id":409562,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1084/ofr20221084.XML"}],"country":"Canada, United States","state":"British Columbia, Idaho, Washington","otherGeospatial":"Boundary Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.81638376433206,\n 49.098372085467105\n ],\n [\n -117.81638376433206,\n 47.528691502768\n ],\n [\n -113.48236882623914,\n 47.528691502768\n ],\n [\n -113.48236882623914,\n 49.098372085467105\n ],\n [\n -117.81638376433206,\n 49.098372085467105\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
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Freshwater mussels (Unionida) are among the world’s most imperiled taxa, but the relationship between freshwater mussel mortality events and infectious disease is largely unstudied. We surveyed viromes of a widespread and abundant species (mucket, Actinonaias ligamentina; syn: Ortmanniana ligamentina) experiencing a mortality event of unknown etiology in the Huron River, Michigan, in 2019–2020 and compared them to viromes from mucket in a healthy population in the St. Croix River, Wisconsin and a population from the Clinch River, Virginia and Tennessee, where a mortality event was affecting the congeneric pheasantshell (Actinonaias pectorosa; syn: Ortmanniana pectorosa) population. We identified 38 viruses, most of which were associated with mussels collected during the Huron River mortality event. Viral richness and cumulative viral read depths were significantly higher in moribund mussels from the Huron River than in healthy controls from each of the three populations. Our results demonstrate significant increases in the number and intensity of viral infections for freshwater mussels experiencing mortality events, whereas individuals from healthy populations have a substantially reduced virome comprising a limited number of species at low viral read depths.
","language":"English","publisher":"MDPI","doi":"10.3390/v14122603","usgsCitation":"Richard, J., Leis, E., Dunn, C.D., Harris, C., Agbalog, R., Campbell, L., Knowles, S., Waller, D.L., Putnam, J.G., and Goldberg, T., 2022, Freshwater mussels show elevated viral richness and intensity during a mortality event: Viruses, v. 14, no. 12, 2603, 13 p., https://doi.org/10.3390/v14122603.","productDescription":"2603, 13 p.","ipdsId":"IP-141265","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":445829,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/v14122603","text":"Publisher Index Page"},{"id":411718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Tennessee, Virginia, Wisconsin","otherGeospatial":"Clinch River, Huron River, Saint Croix River","geographicExtents":"{\n \"type\": 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0000-0002-6104-810X dwaller@usgs.gov","orcid":"https://orcid.org/0000-0002-6104-810X","contributorId":5272,"corporation":false,"usgs":true,"family":"Waller","given":"Diane","email":"dwaller@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":861331,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Putnam, Joel G. 0000-0002-5464-4587 jgputnam@usgs.gov","orcid":"https://orcid.org/0000-0002-5464-4587","contributorId":5783,"corporation":false,"usgs":true,"family":"Putnam","given":"Joel","email":"jgputnam@usgs.gov","middleInitial":"G.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":861332,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Goldberg, Tony","contributorId":211788,"corporation":false,"usgs":false,"family":"Goldberg","given":"Tony","affiliations":[{"id":38319,"text":"UW Madison","active":true,"usgs":false}],"preferred":false,"id":861333,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70238871,"text":"70238871 - 2022 - Violent groundwater eruption triggered by a distant earthquake","interactions":[],"lastModifiedDate":"2022-12-14T14:58:13.560529","indexId":"70238871","displayToPublicDate":"2022-11-23T08:35:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Violent groundwater eruption triggered by a distant earthquake","docAbstract":"It is now well established that earthquakes cause various hydrogeological responses at distances thousands of kilometers from the epicenter. What remains unexplained is the large amplitude and intensity of some responses. Following the 2004 Mw 9.1 Sumatra earthquake, groundwater 3,200 km from the epicenter erupted violently from a well and formed a water fountain reaching a height exceeding 60 m. We model the relevant processes by combining tidal analysis of groundwater level with numerical simulations using a two-dimensional finite-element model. We suggest that the eruption resulted from a combination of factors, including a rapid increase of crustal permeability and runaway CO2 exsolution and bubble nucleation induced by the passage of seismic waves. Our results may have implications for some engineering applications such as oil production and CO2 sequestration, and the eruption of hydrothermal features such as geysers.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022GL101239","usgsCitation":"Yan, X., Shi, Z., Wang, C., Ingebritsen, S.E., and Manga, M., 2022, Violent groundwater eruption triggered by a distant earthquake: Geophysical Research Letters, v. 49, no. 23, e2022GL101239, 10 p., https://doi.org/10.1029/2022GL101239.","productDescription":"e2022GL101239, 10 p.","ipdsId":"IP-141694","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":445834,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022gl101239","text":"Publisher Index Page"},{"id":410471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 115.816667,\n 24.916667\n ],\n [\n 115.816667,\n 24.75\n ],\n [\n 116.033333,\n 24.75\n ],\n [\n 116.033333,\n 24.916667\n ],\n [\n 115.816667,\n 24.916667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"23","noUsgsAuthors":false,"publicationDate":"2022-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Yan, Xin","contributorId":299915,"corporation":false,"usgs":false,"family":"Yan","given":"Xin","email":"","affiliations":[],"preferred":false,"id":859007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shi, Zheming","contributorId":299913,"corporation":false,"usgs":false,"family":"Shi","given":"Zheming","email":"","affiliations":[{"id":64978,"text":"China University of Geosciences - Beijing","active":true,"usgs":false}],"preferred":false,"id":859008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Chi-Yuen","contributorId":131171,"corporation":false,"usgs":false,"family":"Wang","given":"Chi-Yuen","email":"","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":859009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":859010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Manga, Michael 0000-0003-3286-4682","orcid":"https://orcid.org/0000-0003-3286-4682","contributorId":265640,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":859011,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70238463,"text":"70238463 - 2022 - Size distribution and reproductive phenology of the invasive Burmese python (Python molurus bivittatus) in the Greater Everglades Ecosystem, Florida, USA","interactions":[],"lastModifiedDate":"2022-11-28T13:46:02.465368","indexId":"70238463","displayToPublicDate":"2022-11-23T07:39:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5071,"text":"NeoBiota","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Size distribution and reproductive phenology of the invasive Burmese python (Python molurus bivittatus) in the Greater Everglades Ecosystem, Florida, USA","title":"Size distribution and reproductive phenology of the invasive Burmese python (Python molurus bivittatus) in the Greater Everglades Ecosystem, Florida, USA","docAbstract":"The design of successful invasive species control programs is often hindered by the absence of basic demographic data on the targeted population. Establishment of invasive Burmese pythons (Python molurus bivittatus) in the Greater Everglades Ecosystem, Florida USA has led to local precipitous declines (> 90%) of mesomammal populations and is also a major threat to native populations of reptiles and birds. Efforts to control this species are ongoing but are hampered by the lack of access to and information on the expected biological patterns of pythons in southern Florida. We present data from more than 4,000 wild Burmese pythons that were removed in southern Florida over 26 years (1995–2021), the most robust dataset representing this invasive population to date. We used these data to characterize Burmese python size distribution, size at maturity, clutch size, and seasonal demographic and reproductive trends. We broadened the previously described size ranges by sex and, based on our newly defined size-stage classes, showed that males are smaller than females at sexual maturity, confirmed a positive correlation between maternal body size and potential clutch size, and developed predictive equations to facilitate demographic predictions. We also refined the annual breeding season (approx.100 days December into March), oviposition timing (May), and hatchling emergence and dispersal period (July through October) using correlations of capture morphometrics with observations of seasonal gonadal recrudescence (resurgence) and regression. Determination of reproductive output and timing can inform population models and help managers arrest population growth by targeting key aspects of python life history. These results define characteristics of the species in Florida and provide an enhanced understanding of the ecology and reproductive biology of Burmese pythons in their invasive Everglades range.
","language":"English","publisher":"Pensoft","doi":"10.3897/neobiota.78.93788","usgsCitation":"Currylow, A.F., Falk, B., Yackel Adams, A.A., Romagosa, C., Josimovich, J., Rochford, M., Cherkiss, M., Nafus, M., Hart, K., Mazzotti, F., Snow, R.W., and Reed, R., 2022, Size distribution and reproductive phenology of the invasive Burmese python (Python molurus bivittatus) in the Greater Everglades Ecosystem, Florida, USA: NeoBiota, v. 78, p. 129-158, https://doi.org/10.3897/neobiota.78.93788.","productDescription":"30 p.","startPage":"129","endPage":"158","ipdsId":"IP-144474","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":445837,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/neobiota.78.93788","text":"Publisher Index Page"},{"id":409686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.05393175290448,\n 26.86978990604409\n ],\n [\n -82.2443372550706,\n 26.86978990604409\n ],\n [\n -82.2443372550706,\n 24.285980539160136\n ],\n [\n -80.05393175290448,\n 24.285980539160136\n ],\n [\n -80.05393175290448,\n 26.86978990604409\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"78","noUsgsAuthors":false,"publicationDate":"2022-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Currylow, Andrea Faye 0000-0003-1631-8964","orcid":"https://orcid.org/0000-0003-1631-8964","contributorId":257055,"corporation":false,"usgs":true,"family":"Currylow","given":"Andrea","email":"","middleInitial":"Faye","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":857542,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falk, Bryan 0000-0002-9690-5626 bfalk@usgs.gov","orcid":"https://orcid.org/0000-0002-9690-5626","contributorId":150075,"corporation":false,"usgs":true,"family":"Falk","given":"Bryan","email":"bfalk@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":857543,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":857544,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Romagosa, Christina M.","contributorId":39661,"corporation":false,"usgs":true,"family":"Romagosa","given":"Christina M.","affiliations":[],"preferred":false,"id":857545,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Josimovich, Jillian jjosimovich@usgs.gov","contributorId":173092,"corporation":false,"usgs":true,"family":"Josimovich","given":"Jillian","email":"jjosimovich@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":857546,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rochford, Michael R.","contributorId":6574,"corporation":false,"usgs":true,"family":"Rochford","given":"Michael R.","affiliations":[],"preferred":false,"id":857547,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cherkiss, Michael 0000-0002-7802-6791","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":222180,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":857548,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nafus, Melia Gail 0000-0002-7325-3055","orcid":"https://orcid.org/0000-0002-7325-3055","contributorId":245717,"corporation":false,"usgs":true,"family":"Nafus","given":"Melia Gail","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":857549,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":220333,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":857550,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mazzotti, Frank J.","contributorId":12358,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12604,"text":"Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, 3205 College Avenue, University of Florida, Davie, FL 33314, USA","active":true,"usgs":false}],"preferred":false,"id":857551,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Snow, Ray W.","contributorId":76449,"corporation":false,"usgs":false,"family":"Snow","given":"Ray","email":"","middleInitial":"W.","affiliations":[{"id":13415,"text":"Everglades National Park","active":true,"usgs":false}],"preferred":false,"id":857552,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Reed, Robert 0000-0001-8349-6168","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":267796,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":857553,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70238560,"text":"70238560 - 2022 - A review of current capabilities and science gaps in water supply data, modeling, and trends for water availability assessments in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2022-11-29T13:18:15.018564","indexId":"70238560","displayToPublicDate":"2022-11-23T07:12:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"A review of current capabilities and science gaps in water supply data, modeling, and trends for water availability assessments in the Upper Colorado River Basin","docAbstract":"Over the past century, piñon and juniper trees have encroached into sagebrush steppe lands of the interior United States, and managers have for many years removed trees to stimulate the favored understory. While consistent understory response to tree removal in these semiarid lands suggests that trees outcompete other plants for water, no studies have linked increased soil water to understory response after tree removal. We tested the hypothesis that tree removal at six sagebrush steppe sites increased soil water, leading to increased understory plant cover. Using a structural equation model, we found that before tree removal, trees suppressed shrubs (standardized coefficient [SC] = −0.87), perennial deep-rooted (SC = −0.50) and shallow-rooted bunchgrasses (SC = −0.36), but had no influence on cheatgrass. The model explained between 2% (cheatgrass) and 40% (shrubs) of pretreatment cover variation. Measurement of the same plots six years post-treatment showed that most cover variation was due directly to plant growth, with standardized coefficients between 0.51 (perennial shallow-rooted grasses) and 0.72 (cheatgrass). Competition between cheatgrass and perennial deep-rooted grasses was evident, with perennials having twice the influence on cheatgrass than vice-versa (SC = −0.24 vs. −0.11). Spring soil water (wet-degree days) increased significantly after tree removal, measured as cumulative over 6 years (SC = 0.30), and in the early Spring of year six (SC = 0.16). Treatment-induced increase of cumulative Spring wet degree-days explained variation in shrub cover at year 6 (SC = 0.12) and the increase of early Spring wet degree-days at year 6 led to increases in perennial deep-rooted grasses (SC = 0.24) and cheatgrass (SC = 0.23). We detected no influence of Spring wet degree-days on perennial shallow-rooted grasses. The post-treatment model explained between 34% (shallow-rooted perennial grasses) and 69% (deep-rooted perennial grasses) of variation in understory cover. Most variation was explained by re-measurement of the same populations, followed by treatment effects mediated through increased soil water availability, soil factors, and direct effects of the treatment itself. In conclusion, our model is consistent with the a priori hypothesis that additional wet degree-days due to tree removal is a significant mechanism behind observed increases in understory cover.
Gila trout (Oncorhynchus gilae) represent an iconic species of the American Southwest. The salmonid has survived extensive logging, livestock grazing, and mining, and is currently threatened by climate change, wildfire, and extended drought. Long-term conservation and recovery of the species and its unique lineages rely on stocking and translocation into historically inhabited streams. Thus, the fish's thermal tolerance is essential in determining suitable habitat and potential vulnerability to a warming climate. We compared a laboratory-derived temperature metric, critical thermal maximum (CTMax), in hatchery-reared Gila trout from three lineages (Main Diamond, South Diamond, and Whiskey Creek) to determine if CTMax differed among the lineages. The average initial (28.9°C, SD = 0.81°C) and final (29.2°C, SD = 0.74°C) temperature at loss of righting responses did not differ across the lineages. We compared the CTMax values with stream temperatures across three drainages representative of extant Gila trout populations from spring 2015 to fall 2018. The East Fork Gila River drainage was represented by more extreme stream temperatures. The maximum daily maximum temperature (i.e., single highest temperature) varied from 24.1 to 33.4°C, exceeding CTMax in four of the five streams. The maximum daily temperature varied from 12.1 to 28.6°C, and the mean weekly maximum temperature varied from 19.9 to 31.1°C. Mean weekly maximum temperature in Lower Diamond Creek exceeded CTMax on 11 occasions. Stream temperatures were cooler within the Middle and the West Fork Gila River drainages and did not exceed CTMax. Intermittency loggers within the East Fork Gila River drainage, which supports Main Diamond and South Diamond lineages of Gila trout, recorded over 300 days of intermittency during a drought. Continued long-term monitoring of stream temperature and comparison with CTMax of Gila trout could assist with decisions of which streams in the Gila Drainage are suitable for Gila trout recovery, stocking, and translocation.
Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 13,929 million (13.9 billion) barrels of oil and 193,721 billion (193.7 trillion) cubic feet of gas within the Senegal Basin Province of northwest Africa.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20223080","usgsCitation":"Schenk, C.J., Mercier, T.J., Woodall, C.A., Le, P.A., Cicero, A.D., Drake, R.M., II, Ellis G.S., Finn, T.M., Gardner, M.H., Gelman, S.E., Hearon, J.S., Johnson, B.G., Lagesse, J.H., Leathers-Miller, H.M., Marra, K.R., Timm, K.K., and Young, S.S., 2022, Assessment of undiscovered conventional oil and gas resources of the Senegal Basin Province of northwest Africa, 2021: U.S. Geological Survey Fact Sheet 2022–3080, 2 p., https://doi.org/10.3133/fs20223080.","productDescription":"Report: 2 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-133002","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":409553,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20223080/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2022-3069"},{"id":409534,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3080/fs20223080.xml"},{"id":409533,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3080/images"},{"id":409421,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QN4RG5","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project–Senegal Basin Province: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":409420,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3080/fs20223080.pdf","text":"Report","size":"700.0 kB","description":"FS 2022-3080"},{"id":409419,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3080/coverthb2.jpg"}],"otherGeospatial":"Senegal Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -12,\n 24\n ],\n [\n -24,\n 24\n ],\n [\n -24,\n 8\n ],\n [\n -12,\n 8\n ],\n [\n -12,\n 24\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Flat Creek, a tributary to the Snake River in northwestern Wyoming, is an important source of irrigation water, fish and wildlife habitat, and local recreation. Since 1996, a section of Flat Creek within the town of Jackson has failed to meet Wyoming Department of Environmental Quality’s surface-water-quality standards for total suspended solids and turbidity required by its State water-use classification. Wyoming Department of Environmental Quality water-quality standards prohibit increases of greater than 10 nephelometric turbidity units (NTU) because of human activities in streambodies of Wyoming. Sediment loading from urban stormwater runoff is hypothesized in previous publications to be the primary cause of impairment, but the relative fine sediment contributions from various sources have not been quantified.
In cooperation with the Teton Conservation District, the U.S. Geological Survey began a pilot study in the Flat Creek drainage basin to investigate the use of continuous turbidity measurements to predict suspended-sediment concentrations, loads, and sources through the town of Jackson, Wyoming. The predictions were based on turbidity measurements collected every 15 minutes during parts of water years 2019 and 2020. Analysis of differences in the more than 15,000 turbidity measurements coincident between upstream and downstream streamgages indicated that differences of 10 formazin nephelometric units (FNU) or greater composed about 1 percent of the total accepted measurements during the 2019 and 2020 measurement periods. The median difference in measured turbidity between coincident records at the upstream and downstream streamgages in 2019 was 0.20 FNU and the median difference in 2020 was 0.0 FNU.
Calculations of mean total sediment loads in Flat Creek during 2019 and 2020 indicate substantially more suspended-sediment was in Flat Creek below the town of Jackson than above town. Mean total calculated suspended-sediment loads at the upstream streamgage were 26 percent in 2019 and 21 percent in 2020 of the mean total suspended-sediment loads at the downstream streamgage. For measurements occurring at the same time (coincident), mean calculated suspended-sediment loads entering the town of Jackson from Flat Creek were 39 percent in 2019 and 35 percent in 2020 of those loads exiting town in Flat Creek. Incorporating statistical model uncertainty, mean differences between predicted suspended-sediment loads could potentially be zero. The annual period of operations of the South Park Supply Ditch, which diverts water into Flat Creek from the Gros Ventre River, constituted between 91 and 90 percent of the total calculated suspended-sediment load at the upstream streamgage, and between 88 and 87 percent of the loads at the downstream streamgage for coincident periods of record in 2019 and 2020, respectively. However, in the absence of simultaneous continuous monitoring and resulting measurements at the outlet of the South Park Supply Ditch, no robust method was available to quantify suspended-sediment loads from the ditch.
A moving average filter was used to identify and isolate short-duration (minutes to hours) spikes in turbidity at the downstream streamgage that were likely caused by overland flow and urban runoff. Suspended-sediment loads during urban runoff constituted about 8 and 10 percent of the total calculated suspended-sediment loads at the downstream streamgage (Flat Creek below Cache Creek, near Jackson, Wyoming; U.S. Geological Survey streamgage 13018350), and 6 and 4 percent of the loads calculated for the record coincident with the upstream streamgage in 2019 and 2020, respectively. Estimated suspended-sediment loads at the upstream streamgage during urban runoff events for the coincident period of record constitute 32 and 40 percent of the total estimated suspended-sediment loads at the downstream streamgage in 2019 and 2020, respectively, indicating sediment loads from urban runoff may contribute less than 10 percent, even as little as 5 percent, of the total sediment load exiting the town of Jackson on Flat Creek. Estimation of the proportion of suspended-sediment loads at the upstream site that originate from the South Park Supply Ditch or Cache Creek can only be done with assumptions but have the potential to be equivalent to or greater than calculated suspended-sediment loads associated with urban runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221103","collaboration":"Prepared in cooperation with the Teton Conservation District","programNote":"Water Mission Area","usgsCitation":"Alexander, J.S., Girard, C., Campbell, J., Ellison, C., Gosselin, E., and Smith, E., 2022, Using continuous measurements of turbidity to predict suspended-sediment concentrations, loads, and sources in Flat Creek through the town of Jackson, Wyoming, 2019−20 — A pilot study: U.S. Geological Survey Open-File Report 2022–1103, 29 p., https://doi.org/10.3133/ofr20221103.","productDescription":"Report: viii, 29 p.; Dataset","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-136294","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":409367,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":409366,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1103/images"},{"id":409364,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1103/ofr20221103.pdf","text":"Report","size":"2.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1103"},{"id":409365,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1103/ofr20221103.XML"},{"id":409363,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1103/coverthb.jpg"},{"id":501840,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113833.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","city":"Jackson","otherGeospatial":"Flat Creek drainage basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.72880406891166,\n 43.5011735765672\n ],\n [\n -110.8241704639435,\n 43.5011735765672\n ],\n [\n -110.8241704639435,\n 43.42146497765464\n ],\n [\n -110.72880406891166,\n 43.42146497765464\n ],\n [\n -110.72880406891166,\n 43.5011735765672\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
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Diel migrations of zooplanktons occur in marine and freshwater systems and can complicate inferences from studies. If populations perform vertical or horizontal diel migrations, daytime-only sampling can mischaracterize distributions and abundances. Zooplanktons also often display reduced capture avoidance at night and occupy areas easier to sample near the surface and away from littoral structure and the benthos. We examined zooplankton abundance, water column position and taxonomic composition during daytime and nighttime new moon periods using discrete depth sampling in oligo-mesotrophic reservoirs in Oregon, USA. These reservoirs have limited littoral structures, but support populations of zooplanktivorous fishes that we expected to drive diel vertical migrations. Contrary to our expectations, at night, most zooplankton taxa were within 2 m of their daytime distributional peak and did not display differences in abundance from day to night sampling. We consider factors that may help predict whether diel vertical migration occurs in a system. Where daytime sampling is sufficient to characterize zooplankton densities and distributions, costs and risks specific to nighttime sampling may be avoided. Improving our knowledge of zooplankton dynamics, particularly in ecosystems with limited diurnal variability, is an important part of understanding lake and reservoir food webs and can optimize the efforts of future studies.
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