Highly pathogenic avian influenza viruses (HPAIVs) of the A/goose/Guangdong/1/1996 lineage H5 clade 2.3.4.4b continue to have a devastating effect on domestic and wild birds. Full genome sequence analyses using 1369 H5N1 HPAIVs detected in the United States (U.S.) in wild birds, commercial poultry, and backyard flocks from December 2021 to April 2022, showed three phylogenetically distinct H5N1 virus introductions in the U.S. by wild birds. Unreassorted Eurasian genotypes A1 and A2 entered the Northeast Atlantic states, whereas a genetically distinct A3 genotype was detected in Alaska. The A1 genotype spread westward via wild bird migration and reassorted with North American wild bird avian influenza viruses. Reassortments of up to five internal genes generated a total of 21 distinct clusters; of these, six genotypes represented 92% of the HPAIVs examined. By phylodynamic analyses, most detections in domestic birds were shown to be point-source transmissions from wild birds, with limited farm-to-farm spread.
The goal of this paper was to review the evidence of population-level impacts of the Deepwater Horizon Oil Spill (DWH) on Gulf of Mexico (GOM) continental shelf taxa, as well as evidence of resiliency following the DWH. There is considerable environmental and biological evidence that GOM shelf taxa were exposed to and suffered direct and indirect impacts of the DWH. Numerous assessments, from mesocosm studies to analysis of biopsied tissue or tissue samples from necropsied animals, revealed a constellation of physiological effects related to DWH impacts on GOM biota, some of which clearly or likely resulted in mortality. While the estimated concentrations of hydrocarbons in shelf waters and sediments were orders of magnitude lower than measured in inshore or deep GOM environments, the level of mortality observed or predicted was substantial for many shelf taxa. In some cases, such as for zooplankton, community shifts following the spill were ephemeral, likely reflecting high rates of population turnover and productivity. In other taxa, such as GOM reef fishes, impacts of the spill are confounded with other stressors, such as fishing mortality or the appearance and rapid population growth of invasive lionfish (Pterois spp.). In yet others, such as cetaceans, modeling efforts to predict population-level effects of the DWH made conservative assumptions given the species’ protected status, which post-DWH population assessments either failed to detect or population increases were estimated. A persistent theme that emerged was the lack of precise population-level data or assessments prior to the DWH for many taxa, but even when data or assessments did exist, examining evidence of population resiliency was confounded by other stressors impacting GOM biota. Unless efforts are made to increase the resolution of the data or precision of population assessments, difficulties will likely remain in estimating the scale of population-level effects or resiliency in the case of future large-scale environmental catastrophes.
Anthrax is a lethal bacterial zoonosis primarily affecting herbivorous wildlife and livestock. Upon host death Bacillus anthracis vegetative cells form spores capable of surviving for years in soil. Anthrax transmission requires host exposure to large spore doses. Thus, conditions that facilitate higher spore concentrations or promote spore survival will increase the probability that a pathogen reservoir infects future hosts. We investigated abiotic and pathogen genomic variation in relation to spore concentrations in surface soils (0e1 cm depth) at 40 plains zebra (Equus quagga) anthrax carcass sites in Namibia. Specifically, how initial spore concentrations and spore survival were affected by seasonality associated with the timing of host mortality, local soil characteristics, and pathogen genomic variation. Zebras dying of anthrax in wet seasons-the peak season for anthrax in Etosha National Park-had soil spore concentrations 1.36 orders of magnitude higher than those that died in dry seasons. No other variables considered affected spore concentrations, and spore survival rates did not differ among sites. Surface soils at these pathogen reservoirs remained culture positive for a range of 3.8e10.4 years after host death. Future research could evaluate if seasonal patterns in spore concentrations are driven by differences in sporulation success or levels of terminal bacteremia.
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2023 - Tool 3: Suggested coproduction steps and practices","interactions":[],"lastModifiedDate":"2024-05-01T15:31:23.787416","indexId":"70248119","displayToPublicDate":"2023-08-01T11:00:50","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Tool 3: Suggested coproduction steps and practices","docAbstract":"An information sheet provided as part of a toolkit for researchers and practitioners\nwith an interest in coproducing actionable science to support public land management","language":"English","publisher":"Bureau of Land Management","usgsCitation":"Selby, L.B., Carter, S.K., Haby, T., Wood, D.J., Bamzai-Dodson, A., Anderson, P.J., Herrick, J.E., Samuel, E., and Tull, J.C., 2023, Tool 3: Suggested coproduction steps and practices (Revised 2024), 2 p.","productDescription":"2 p.","ipdsId":"IP-146728","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":420495,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://www.blm.gov/sites/default/files/docs/2024-02/CASSPLM-Tool3-SuggestedCoproductionStepsAndPractices.pdf"},{"id":420496,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Revised 2024","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Selby, Lea B. 0000-0001-7260-5576","orcid":"https://orcid.org/0000-0001-7260-5576","contributorId":329037,"corporation":false,"usgs":true,"family":"Selby","given":"Lea","email":"","middleInitial":"B.","affiliations":[{"id":66310,"text":"Student Service Contractor","active":true,"usgs":false}],"preferred":true,"id":881973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, Sarah K. 0000-0003-3778-8615","orcid":"https://orcid.org/0000-0003-3778-8615","contributorId":192418,"corporation":false,"usgs":true,"family":"Carter","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haby, Travis","contributorId":202409,"corporation":false,"usgs":false,"family":"Haby","given":"Travis","affiliations":[{"id":36421,"text":"Bureau of Land Management National Operations Center","active":true,"usgs":false}],"preferred":false,"id":881975,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, D. 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We demonstrate that under the piecewise constant hazard function, the likelihood for uncensored or right-censored subjects is proportional to the likelihood of multiple conditionally independent Poisson random variables. To address left- or interval-censored subjects, we propose to impute the exact event times and convert them into uncensored subjects, enabling the application of the integrated nested Laplace approximation to update model parameters using the imputed data. We introduce an iterative algorithm that alternates between imputing event times for left- and interval-censored subjects and re-estimating model parameters. The proposed method is assessed through a simulation study and applied to analyze a spatio-temporal survival dataset in a wildlife disease study investigating bovine tuberculosis in white-tailed deer in Michigan.
","language":"English","publisher":"Wiley","doi":"10.1002/env.2823","usgsCitation":"Yao, K., Zhu, J., O'Brien, D., and Walsh, D.P., 2023, Bayesian spatio-temporal survival analysis for all types of censoring with application to a wildlife disease study: Environmetrics, v. 34, no. 8, e2823, 13 p., https://doi.org/10.1002/env.2823.","productDescription":"e2823, 13 p.","ipdsId":"IP-146224","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":442561,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1002/env.2823","text":"Publisher Index Page"},{"id":430134,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Yao, Kehui","contributorId":339161,"corporation":false,"usgs":false,"family":"Yao","given":"Kehui","email":"","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":903822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhu, Jun","contributorId":73485,"corporation":false,"usgs":true,"family":"Zhu","given":"Jun","email":"","affiliations":[],"preferred":false,"id":903823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Brien, Daniel J.","contributorId":339164,"corporation":false,"usgs":false,"family":"O'Brien","given":"Daniel J.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":903824,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":903825,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248303,"text":"70248303 - 2023 - Sacramento River nutrient change study","interactions":[],"lastModifiedDate":"2023-09-07T14:19:16.52086","indexId":"70248303","displayToPublicDate":"2023-08-01T09:12:55","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":251,"text":"Final Report","active":false,"publicationSubtype":{"id":4}},"title":"Sacramento River nutrient change study","docAbstract":"The Sacramento River Nutrient Change Study (SRiNCS) was developed with input from multiple stakeholders in the Delta Regional Monitoring Program, as well as the State Water Contractors. We tracked the effects of changes in nutrient loading resulting from a short-term wastewater hold at the Sacramento River Wastewater Treatment Plant (SRWTP). In the summer of 2019, scheduled wastewater effluent holds occurred during the Effluent Valve Replacement (EVR) project, part of the EchoWater Project upgrade at the SRWTP. During an EVR hold in early September 2019, no treated effluent entered the Sacramento River for 48 hours, creating a parcel of “without-wastewater” river water approximately 20 miles (32 km) long. We observed the magnitudes and impacts of short-term changes in nutrient loading in water with wastewater (WW+, September 10) and without wastewater (WW-, September 11 and 12) in the Sacramento River and three downstream channels: Georgiana Slough, the North Fork Mokelumne River, and the South Fork Mokelumne River","language":"English","publisher":"Delta Regional Monitoring Program","usgsCitation":"Thompson, L., Mussen, T.D., Cook, M., Nordin, J., Noss, J., Bigler, U., Ramamoorthy, S., Berg, G.M., Driscoll, S., Herrmann, C., Kimmerer, W.J., Ignoffo, T., Kraus, T.E., Fackrell, J.K., Bergamaschi, B., Guerin, M., and Rachiele, R., 2023, Sacramento River nutrient change study: Final Report, 361 p.","productDescription":"361 p.","ipdsId":"IP-141332","costCenters":[{"id":154,"text":"California Water Science 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C. 0000-0002-5187-8644 tkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":147560,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara","email":"tkraus@usgs.gov","middleInitial":"E. C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882368,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Fackrell, Joseph K. 0000-0001-8148-3734","orcid":"https://orcid.org/0000-0001-8148-3734","contributorId":225515,"corporation":false,"usgs":true,"family":"Fackrell","given":"Joseph","email":"","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882369,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Bergamaschi, Brian 0000-0003-2876-0485 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0003-2876-0485","contributorId":329470,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882370,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Guerin, Marianne","contributorId":147561,"corporation":false,"usgs":false,"family":"Guerin","given":"Marianne","email":"","affiliations":[{"id":16871,"text":"Resource Management Associates","active":true,"usgs":false}],"preferred":false,"id":882371,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Rachiele, Richard","contributorId":329471,"corporation":false,"usgs":false,"family":"Rachiele","given":"Richard","email":"","affiliations":[{"id":16871,"text":"Resource Management Associates","active":true,"usgs":false}],"preferred":false,"id":882372,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70257347,"text":"70257347 - 2023 - Understanding drivers of mercury in lake trout (Salvelinus namaycush), a top-predator fish in southwest Alaska's parklands","interactions":[],"lastModifiedDate":"2024-08-28T16:23:55.197568","indexId":"70257347","displayToPublicDate":"2023-08-01T09:11:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Understanding drivers of mercury in lake trout (Salvelinus namaycush), a top-predator fish in southwest Alaska's parklands","docAbstract":"Mercury (Hg) is a widespread element and persistent pollutant, harmful to fish, wildlife, and humans in its organic, methylated form. The risk of Hg contamination is driven by factors that regulate Hg loading, methylation, bioaccumulation, and biomagnification. In remote locations, with infrequent access and limited data, understanding the relative importance of these factors can pose a challenge. Here, we assessed Hg concentrations in an apex predator fish species, lake trout (Salvelinus namaycush), collected from 14 lakes spanning two National Parks in southwest Alaska, U.S.A. We then examined factors associated with the variation in fish Hg concentrations using a Bayesian hierarchical model. We found that total Hg concentrations in water were consistently low among lakes (0.11–0.50 ng L− 1). Conversely, total Hg concentrations in lake trout spanned a thirty-fold range (101–3046 ng g− 1 dry weight), with median values at 7 lakes exceeding Alaska’s human consumption threshold. Model results showed that fish age and, to a lesser extent, body condition best explained variation in Hg concentration among fish within a lake, with Hg elevated in older, thinner lake trout. Other factors, including plankton methyl Hg content, fish species richness, volcano proximity, and glacier loss, best explained variation in lake trout Hg concentration among lakes. Collectively, these results provide evidence that multiple, hierarchically nested factors control fish Hg levels in these lakes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2023.121678","usgsCitation":"Bartz, K.K., Hannam, M.P., Wilson, T.L., Lepak, R., Ogorek, J.M., Young, D.B., Eagles-Smith, C., and Krabbenhoft, D.P., 2023, Understanding drivers of mercury in lake trout (Salvelinus namaycush), a top-predator fish in southwest Alaska's parklands: Environmental Pollution, v. 330, 121678, 11 p., https://doi.org/10.1016/j.envpol.2023.121678.","productDescription":"121678, 11 p.","ipdsId":"IP-149237","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":442564,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2023.121678","text":"Publisher Index Page"},{"id":433253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Katmai National Park and Preserve, Lake Clark National Park and Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.59006149445355,\n 60.857310763857726\n ],\n [\n -155.59006149445355,\n 58.42599213711503\n ],\n [\n -152.59863331288238,\n 58.42599213711503\n ],\n [\n -152.59863331288238,\n 60.857310763857726\n ],\n [\n -155.59006149445355,\n 60.857310763857726\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"330","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bartz, Krista K.","contributorId":200705,"corporation":false,"usgs":false,"family":"Bartz","given":"Krista","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":910037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hannam, Michael P.","contributorId":199775,"corporation":false,"usgs":false,"family":"Hannam","given":"Michael","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":910038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Tammy L. 0000-0002-3672-8277","orcid":"https://orcid.org/0000-0002-3672-8277","contributorId":293684,"corporation":false,"usgs":true,"family":"Wilson","given":"Tammy","email":"","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lepak, Ryan F. 0000-0003-2806-1895","orcid":"https://orcid.org/0000-0003-2806-1895","contributorId":210990,"corporation":false,"usgs":false,"family":"Lepak","given":"Ryan F.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":910040,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ogorek, Jacob M. 0000-0002-6327-0740 jmogorek@usgs.gov","orcid":"https://orcid.org/0000-0002-6327-0740","contributorId":4960,"corporation":false,"usgs":true,"family":"Ogorek","given":"Jacob","email":"jmogorek@usgs.gov","middleInitial":"M.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":910041,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Young, Daniel","contributorId":58468,"corporation":false,"usgs":false,"family":"Young","given":"Daniel","affiliations":[{"id":35763,"text":"National Park Service, Lake Clark National Park and Preserve, Port Alsworth, AK","active":true,"usgs":false}],"preferred":false,"id":910042,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":910043,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - 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In particular, there is a growing need for high performance rare earth permanent magnets for motors and generators used to convert electrical energy to mechanical energy, and vice versa. Current trends in rare earth demand are reviewed and discussed as the specific rare earth metal demand can influence the choice of feed material and process selection. Australia has the potential to increase the supply of these metals. Rare earth sources in Australia are briefly reviewed, with some discussion on the Mary Kathleen Uranium Tailings opportunity. Much of the cost of recovering rare earths is in the challenging chemical separations, some examples are provided using equilibrium chemical thermodynamic diagrams to explain the specific leaching and precipitation reactions.
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GFPD serves a community of approximately 1,500 homes and 3,600 residents. The community borders the south side of I-70 and runs south up varied topography with varied vegetation to approximately 8,000 feet of elevation and is considered to be at extremely high risk of wildfire. In 2020, GFPD worked with the Forest Stewards Guild to update their Community Wildfire Protection Plan (CWPP). GFPD and WiRē collaborated to collect household-level data in an effort that is complementary to the insights provided by the CWPP. A series of scoping meetings that included the GFR Fire Board helped to build a shared understanding of GFPD’s goals, the setting, and the community.
","language":"English","publisher":"U.S. Forest Service","doi":"10.2737/RMRS-RN-99","usgsCitation":"Brenkert-Smith, H., Dalton, D., Puffett, J., Champ, P.A., Barth, C.M., Meldrum, J., Donovan, C., Wagner, C., Goolsby, J., and Forrester, C., 2023, Living with wildfire in Genesee Fire Protection District, Jefferson County, Colorado: 2022 data report: Research Note RMRS-RN-99, 123 p., https://doi.org/10.2737/RMRS-RN-99.","productDescription":"123 p.","ipdsId":"IP-147946","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":442566,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2737/rmrs-rn-99","text":"Publisher Index Page"},{"id":420072,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Genesee Fire Protection District","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.30847810777267,\n 39.713783190976784\n ],\n [\n -105.30847810777267,\n 39.664454606211564\n ],\n [\n -105.24895390154236,\n 39.664454606211564\n ],\n [\n -105.24895390154236,\n 39.713783190976784\n ],\n [\n -105.30847810777267,\n 39.713783190976784\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brenkert-Smith, Hannah 0000-0001-6117-8863","orcid":"https://orcid.org/0000-0001-6117-8863","contributorId":195485,"corporation":false,"usgs":false,"family":"Brenkert-Smith","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":880928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dalton, Dorie","contributorId":328658,"corporation":false,"usgs":false,"family":"Dalton","given":"Dorie","email":"","affiliations":[{"id":78446,"text":"Genesee Fire Rescue","active":true,"usgs":false}],"preferred":false,"id":880929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Puffett, Jason","contributorId":328659,"corporation":false,"usgs":false,"family":"Puffett","given":"Jason","email":"","affiliations":[{"id":78446,"text":"Genesee Fire Rescue","active":true,"usgs":false}],"preferred":false,"id":880930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Champ, Patricia A.","contributorId":195486,"corporation":false,"usgs":false,"family":"Champ","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":880931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barth, Christopher M.","contributorId":195487,"corporation":false,"usgs":false,"family":"Barth","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":880932,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":880933,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Donovan, Colleen","contributorId":240586,"corporation":false,"usgs":false,"family":"Donovan","given":"Colleen","email":"","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":880934,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wagner, Carolyn","contributorId":240587,"corporation":false,"usgs":false,"family":"Wagner","given":"Carolyn","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":880935,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Goolsby, Julia 0000-0002-2229-5685","orcid":"https://orcid.org/0000-0002-2229-5685","contributorId":295471,"corporation":false,"usgs":false,"family":"Goolsby","given":"Julia","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":880936,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Forrester, Chiara","contributorId":328660,"corporation":false,"usgs":false,"family":"Forrester","given":"Chiara","email":"","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":880937,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70248244,"text":"70248244 - 2023 - The During Nearshore Event Experiment (DUNEX): A collaborative coastal community experiment to address coastal resilience","interactions":[],"lastModifiedDate":"2023-09-06T13:41:07.461467","indexId":"70248244","displayToPublicDate":"2023-08-01T08:40:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3385,"text":"Shore & Beach","printIssn":"0037-4237","active":true,"publicationSubtype":{"id":10}},"title":"The During Nearshore Event Experiment (DUNEX): A collaborative coastal community experiment to address coastal resilience","docAbstract":"The During Nearshore Event Experiment (DUNEX) was a large-scale coastal field effort focused on improving understanding of during-storm nearshore processes to ultimately develop predictive technologies, engineering solutions, and actions to enhance coastal resilience. The experiments were conducted on the North Carolina coast by a multidisciplinary group of over 30 research scientists from 18 academic and federal institutions supporting over 30 graduate students and deploying over 300 instruments from 2019 to 2021. The overarching goal of DUNEX was to gather information collaboratively to improve understanding of the interactions of coastal water levels, waves, currents, beach and dune evolution, soil behavior, vegetation, and groundwater during major coastal storms that affect infrastructure, habitats, and communities. In the short term, these high-quality field measurements will lead to better understanding of during-storm processes and impacts and will enhance U.S. academic coastal research programs by providing opportunities for students to learn about field data collection and to potentially analyze data as part of their studies. Longer-term, DUNEX data and outcomes will improve the ability to predict extreme event physical processes and impacts, validate coastal processes numerical models, and improve coastal resilience strategies and communication methods for coastal communities impacted by storms. The purpose of this paper is to describe the motivation for and science goals of the experiment, how stakeholder needs led to these goals, collaborations amongst researchers, and the knowledge gained that will lead to tools to improve coastal resilience. Herein, we first describe how researchers worked with stakeholders to structure their community-driven needs into science-based requirements. Next, we summarize how federal, academic, and stakeholder researchers worked together to design and execute a multi-organizational experiment aligned with those requirements. Finally, we articulate early findings and lessons learned from the experiment. This paper does not summarize all the research findings from DUNEX, as analyses are still ongoing. An American Geophysical Union (AGU) Special Collection on Coastal Storm Research will be published in 2025 including outcomes from DUNEX research.
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Advances in liquefaction hazard analysis in practice have largely stagnated in recent years; the state of practice remains rooted in simplified procedures that ignore considerable uncertainties in liquefaction phenomena, and are largely conditional on single-return period ground motions. As a result, they lack any sort of liquefaction-specific design criteria or performance objective. Presented herein is a roadmap for using probabilistic liquefaction hazard analysis (PLHA) to address many of these limitations and improve liquefaction design guidelines. PLHA incorporates hazard contributions from the full ground motion hazard space in conjunction with probabilistic liquefaction models, to produce hazard curves for various types of liquefaction-related demands. In this study, PLHA is utilized to assess the current, implied liquefaction design levels at 76 study sites throughout the U.S. using ASCE 7 guidelines, by computing effective return periods of liquefaction factor of safety FSL, and liquefaction potential index LPI. The results indicate broad inconsistencies in these design levels across different parts of the U.S, with return periods varying from about 300 years in deterministically-capped parts of California, to nearly 3,000 years on the Pacific Northwest coast and in the Charleston Fault zone region. These results are also used to inform potential strategies for establishing consistent, liquefaction-specific design objectives in the future, based on return period averaging methods that weight the importance of a study site according to both the population and relative liquefaction hazard level.
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Populations along geographical range limits are often exposed to unsuitable climate and low resource availability relative to core populations. As such, there has been a renewed focus on understanding the factors that determine range limits to better predict how species will respond to global change. Using recent theory on range limits and classical understanding of density dependence, we evaluated the influence of resource availability on the snowshoe hare Lepus americanus along its trailing range edge. We estimated variation in population density, habitat use, survival, and parasite loads to test the Great Escape Hypothesis (GEH), i.e. that density dependence determines, in part, a species' persistence along trailing edges. We found that variability in resource availability affected density and population fluctuations and led to trade-offs in survival for snowshoe hare populations in the northeastern USA. Hares living in resource-limited environments had lower and less variable population density, yet higher survival and lower parasitism compared to populations living in resource-rich environments. We suggest that density-dependent dynamics, elicited by resource availability, provide hares a unique survival advantage and partly explain persistence along their trailing edge. We hypothesize that this low-density escape from predation and parasitism occurs for other prey species along trailing edges, but the extent to which it occurs is likely conditional on the quality of matrix habitat. Our work indicates that biotic factors play an important role in shaping species' trailing edges and more detailed examination of non-climatic factors is warranted to better inform conservation and management decisions.
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The pond is hydraulically connected to the surrounding groundwater-flow system, and water levels in the pond fluctuate in response to recharge to the aquifer from precipitation and wastewater return flows through septic systems, to withdrawals from the aquifer at nearby wells, and to precipitation directly on the pond surface. Concerns about the effects of withdrawals on water levels in the pond prompted an investigation to better understand the hydrology of Kingsbury Pond and its response to groundwater withdrawals and to determine if withdrawals from wells in Franklin, Mass., can be modified to simultaneously reduce the effect on water levels in the pond and yet meet the water-supply demands of the Town of Franklin.
An existing, transient groundwater-flow model of the Upper Charles River Basin was modified for this study in the area near Kingsbury Pond to improve representation of the hydrologic system near the pond. The mean annual water-level altitude simulated for the pond for nonpumping conditions using the modified model is 136 feet (ft), which falls within the range of likely annual pond-altitude fluctuations of 135 to 140 ft estimated for average hydrologic conditions before the beginning of withdrawals at two nearby wells operated by the Town of Franklin (wells FR–04 and FR–05). The mean annual water-level altitude at the pond decreased by 3.8 ft to 132.2 ft for simulated mean monthly withdrawal rates at all wells within the Upper Charles River Basin from 2010 to 2019 (referred to as the baseline withdrawal condition).
A groundwater management model that links the groundwater-flow model with a mathematical optimization method was developed to evaluate the effects of three alternative groundwater-withdrawal scenarios for the Franklin public-water system on water levels in Kingsbury Pond. In the first scenario, monthly withdrawal rates at wells FR–04 and FR–05 were increased from the baseline withdrawal rates to their maximum authorized rates for all months of the year; all other Franklin wells were specified at their baseline withdrawal rates. This scenario resulted in a mean annual water-level altitude at the pond of 129.3 ft, or a mean annual decline of 6.7 ft compared with nonpumping conditions and a decline of 2.9 ft compared with baseline conditions.
The results of the second scenario showed that water levels in the pond can be increased relative to 2010–19 conditions while meeting Franklin’s 2010–19 monthly water-supply demands if withdrawals at wells FR–04 and FR–05 were shifted to other Franklin wells. In this scenario, monthly withdrawal rates at wells FR–04 and FR–05 were decreased from their baseline rates to one-third their maximum practical rates for all months of the year; increased withdrawal rates at other Franklin wells were determined by the management model. The decrease in withdrawal rates at wells FR–04 and FR–05 resulted in a mean water-level altitude at the pond of 134.1 ft, which was equivalent to a 51 percent increase (improvement) in the mean annual water level of the pond relative to the baseline condition.
A third scenario was done to determine if Franklin’s existing water-supply system has the capacity to meet the mean annual maximum permitted withdrawal rate of the system of 3.45 million gallons per day while maintaining monthly withdrawal rates at wells FR–04 and FR–05 at their 2010–19 rates and water levels in Kingsbury Pond at baseline conditions. The analysis indicated that the capacity of the system cannot meet the increased demand during some months of the year with withdrawal rates at the two wells fixed at their monthly 2010–19 rates; however, the existing system is capable of meeting about 90 percent of the maximum permitted rate (3.10 million gallons per day) by increasing withdrawal rates at other Franklin wells above their 2010–19 rates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235083","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Barlow, P.M., Friesz, P.J., and Barbaro, J.R., 2023, Evaluation of alternative groundwater-withdrawal scenarios on water levels in Kingsbury Pond, upper Charles River Basin, eastern Massachusetts: U.S. Geological Survey Scientific Investigations Report 2023–5083, 36 p., https://doi.org/10.3133/sir20235083.","productDescription":"Report: viii, 36 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-141684","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501046,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115124.htm","linkFileType":{"id":5,"text":"html"}},{"id":419446,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V49N3R","text":"USGS data release","linkHelpText":"MODFLOW–2000 and management-optimization models used to evaluate alternative groundwater-withdrawal scenarios on water levels in Kingsbury Pond, upper Charles River Basin, eastern Massachusetts"},{"id":419445,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5083/images/"},{"id":419444,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5083/sir20235083.XML"},{"id":419442,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5083/sir20235083.pdf","text":"Report","size":"3.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5083"},{"id":419441,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5083/coverthb.jpg"},{"id":419443,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235083/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5083"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Upper Charles River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.61642753245717,\n 42.29469041974528\n ],\n [\n -71.61642753245717,\n 41.90357856449015\n ],\n [\n -71.16069045053953,\n 41.90357856449015\n ],\n [\n -71.16069045053953,\n 42.29469041974528\n ],\n [\n -71.61642753245717,\n 42.29469041974528\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532