In streams supporting Pacific salmon (Oncorhynchus spp.) within the southern Puget Lowland, high water temperatures during late summer are a primary water-quality concern. The metabolic rates of fish and other ectothermic (in other words, cold-blooded) species are regulated by water temperature; salmon and other cold-water fish have specific thermal tolerances outside of which they are susceptible to infection, disease, increased predation, and decreased reproductive success. Mill and Gosnell Creeks, which collectively drain a 30-square mile area of the Puget Lowland in Mason County, Washington, support several species of anadromous salmonids. Whereas previous studies documented relatively cool water temperatures in Gosnell Creek, which drains the watershed upstream from Lake Isabella, water temperatures in Mill Creek, which heads at the outlet of Lake Isabella, regularly exceed thermal tolerances for cold-water fish. The occurrence and distribution of cold-water anomalies in less-than-ambient water temperatures in Mill Creek, however, have not been assessed. In this report, we present spatially and temporally continuous measurements of near-streambed water temperature measured using fiber-optic distributed temperature sensing for three reaches of Mill Creek during August–September 2020 when the water temperatures of streams in western Washington were near their annual maximum. Water temperature was collected every hour and averaged spatially over 1.015-meter sections of the fiber-optic cable deployed at the streambed of Mill Creek. The lengths of the fiber-optic cables deployed in Reaches A, B, and C were 883, 270, and 1,014 meters, respectively. Daily maximum water temperature and daily temperature variability, as measured by standard deviation of water temperature during the deployment, progressively decreased downstream as distance from Lake Isabella increased. However, no abrupt decreases in daily maximum or standard deviation of water temperature were detected in longitudinal temperature profiles of any of the three reaches. Collectively, these results suggest that warm water discharged from Lake Isabella was progressively buffered downstream as it equilibrated with downstream heat fluxes mediated by physical processes including riparian shading and diffuse groundwater input. Although parts of the surveyed reaches associated with deep pools were cooler than other locations, no large (less than 2 °C) water-temperature anomalies characteristic of discrete sources of cold groundwater or surface-water inputs were measured in any of the three surveyed reaches.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225063","collaboration":"Prepared in cooperation with Squaxin Island Tribe","usgsCitation":"Gendaszek, A.S., Sheibley, R.W., Marbet, E., Puhn, J., and Seguin, C., 2022, Longitudinal water-temperature profiles in Mill Creek, Mason County, Washington: U.S. Geological Survey Scientific Investigations Report 2022–5063, 11 p., https://doi.org/10.3133/sir20225063.","productDescription":"Report: v, 11 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-132795","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":404673,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RP12RQ","text":"USGS data release","description":"USGS data release","linkHelpText":"Longitudinal profiles of water temperature in Mill Creek, Mason County, Washington, measured using fiber-optic distributed temperature sensing (FO-DTS)"},{"id":404671,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5063/sir20225063.pdf","text":"Report","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5063"},{"id":404675,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5063/sir20225063.XML"},{"id":404674,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5063/images"},{"id":404670,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5063/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mill Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.29750061035155,\n 47.09490289688982\n ],\n [\n -122.9425048828125,\n 47.09490289688982\n ],\n [\n -122.9425048828125,\n 47.22656309922327\n ],\n [\n -123.29750061035155,\n 47.22656309922327\n ],\n [\n -123.29750061035155,\n 47.09490289688982\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
In 2019, the U.S. Geological Survey conducted a reconnaissance survey of concentrations of 41 trace elements present in bed sediment in the reservoir on the Similkameen River upstream from Enloe Dam, near Oroville, Washington. The Similkameen River drains a watershed containing highly mineralized geologic deposits with current (2019) and historical mining activity. Results of this survey indicated that surface and subsurface sediment are substantially enriched in element concentrations of silver (Ag), arsenic (As), gold (Au), bismuth (Bi), cadmium (Cd), copper (Cu), manganese (Mn), antimony (Sb), selenium (Se), tin (Sn), and tellurium (Te) relative to average concentrations found in upper continental-crustal material. Conversely, concentrations of mercury (Hg) and lead (Pb) in sediment above Enloe Dam (Enloe Reservoir) were generally less than average concentrations in upper continental-crustal material (Hg = 0.05 milligrams per kilogram [mg/kg]; Pb =17 mg/kg). Concentrations of most trace elements were higher in the less than 63-micrometer fraction (silt) and tended to be higher in subsurface than in surface sediment. The concentrations of trace elements were compared to consensus-based aquatic toxicity reference concentrations, Washington State Department of Ecology sediment management standards, and average concentrations of upper continental-crustal material. Arsenic concentrations were consistently elevated above these criteria among samples and often exceeded sediment management standards and aquatic toxicity reference values (both threshold effects and probable effects concentrations). High concentrations of As were measured in sediment with proportionally more material in the less than 63-micrometer size fraction; this result may be related to the presence of ore-processing waste material that has entered the aquatic system from approximately 125 years of mining operations in the basin. Elevated concentrations of chromium and copper that exceed the same criteria as arsenic (As) were measured less consistently and predominantly in the fine-grain size fraction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225073","collaboration":"Prepared in cooperation with Grant County Public Utility District","usgsCitation":"Cox, S.E., Curran, C.A., Spanjer, A.R., Opatz, C.C., Takesue, R.K., and Bell, J.L., 2022, Element concentrations and grain size of sediment from the Similkameen River above Enloe Dam (Enloe Reservoir) near Oroville, Washington, 2019: U.S. Geological Survey Scientific Investigations Report 2022–5073, 47 p., https://doi.org/10.3133/sir20225073.","productDescription":"Report: x, 47 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-120573","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":404705,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225073/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5073"},{"id":404708,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5073/sir20225073.XML"},{"id":404707,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5073/images"},{"id":404704,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5073/sir20225073.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5073"},{"id":404703,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5073/coverthb.jpg"},{"id":404706,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9593V04","text":"USGS data release","description":"USGS data release","linkHelpText":"Sediment chemistry and characteristics of samples collected in 2019 from the Similkameen River above Enloe Dam, Okanogan County, Washington (ver. 3.0, March 2022):"}],"country":"United States","state":"Washington","otherGeospatial":"Enloe Dam, Enloe Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.520263671875,\n 48.96218736991556\n ],\n [\n -119.49554443359376,\n 48.96218736991556\n ],\n [\n -119.49554443359376,\n 48.98652581047831\n ],\n [\n -119.520263671875,\n 48.98652581047831\n ],\n [\n -119.520263671875,\n 48.96218736991556\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Land subsidence is a settling, sinking, or collapse of the land surface. In the southeastern United States, subsidence is frequently observed as sinkhole collapse in karst environments, wetland degradation and loss in coastal and other low-lying areas, and inundation of coastal urban communities. Human activities such as fluid extraction, mining, and overburden alteration can cause or exacerbate subsidence, which can result in damage to infrastructure and resources. Subsidence is a hazard that takes place throughout the United States; however, a systematic approach to recognize and develop informed responses to the drivers of subsidence has not yet been fully established. To address this problem, the U.S. Geological Survey (USGS) Southeast Region (SER) funded the gathering of a team of interdisciplinary USGS scientists to promote scientific collaboration. Southeast Region scientists welcomed scientists from other regions (see table 1.1 in Appendix 1) in September 2018 at the St. Petersburg Coastal and Marine Science Center (SPCMSC) in Florida for the first workshop of the Subsidence Flex Team (SFT) (see Appendix 2 for agenda). The SFT set out to review subsidence-related research and technology and develop a unifying framework for describing the processes and hazards associated with land subsidence. A more comprehensive understanding of subsidence hazards could help to inform regional vulnerability assessments that would prove invaluable to the public, community developers, policy makers, and resource managers in both inland and coastal states. The SFT analyzed USGS strengths and weaknesses to identify existing infrastructure and capabilities that could be leveraged to create a comprehensive and far-reaching subsidence-monitoring and mitigation program. Over the course of the 2-day workshop, interdisciplinary understandings of the processes and hazards related to subsidence were explored through individual presentations and group discussion. With all perspectives considered, the SFT recommended that subsidence-related research develop scientific approaches and metrics by which the subsidence component can be isolated and quantified in order to protect both the environment and human infrastructure from harm.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221064","usgsCitation":"Flocks, J., McGraw, E., Barras, J., Bernier, J., Bradley, M., Galloway, D., Landmeyer, J., McBride, W.S., Smith, C., Smith, K., Swarzenski, C., and Toth, L., 2022, Documenting the multiple facets of a subsiding landscape from coastal cities and wetlands to the continental shelf: U.S. Geological Survey Open-File Report 2022–1064, 22 p., https://doi.org/10.3133/ofr20221064.","productDescription":"viii, 22 p.","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-106940","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":501871,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113357.htm","linkFileType":{"id":5,"text":"html"}},{"id":404582,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1064/covrthb.jpg"},{"id":404583,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1064/ofr20221064.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1064"}],"country":"United States","state":"Alabama, Florida, Louisiana, Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.603515625,\n 24.5271348225978\n ],\n [\n -79.7607421875,\n 24.5271348225978\n ],\n [\n -79.7607421875,\n 31.16580958786196\n ],\n [\n -93.603515625,\n 31.16580958786196\n ],\n [\n -93.603515625,\n 24.5271348225978\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
The brown treesnake (BTS) (Boiga irregularis) invasion on Guåhan (in English, Guam) led to the extirpation of nearly all native forest birds. In recent years, methods have been developed to reduce BTS abundance on a landscape scale. To help assess the prospects for the successful reintroduction of native birds to Guåhan following BTS suppression, we modeled bird population persistence based on their life history characteristics and relative sensitivity to BTS predation. We constructed individual-based models and simulated BTS predation in hypothetical founding populations for each of seven candidate bird species. We represented BTS predation risk in two steps: risk of being encountered and risk of mortality if encountered. We link encounter risk from the bird's perspective to snake contact rates at camera traps with live animal lures, the most direct practical means of estimating BTS predation risk. Our simulations support the well-documented fact that Guåhan's birds cannot persist with an uncontrolled population of BTS but do indicate that bird persistence in Guåhan's forests is possible with suppression short of total eradication. We estimate threshold BTS contact rates would need to be below 0.0002–0.0006 snake contacts per bird per night for these birds to persist on the landscape, which translates to an annual encounter probability of 0.07–0.20. We simulated the effects of snake-proof nest boxes for Sihek (Todiramphus cinnamominus) and Såli (Aplonis opaca), but the benefits were small relative to the overall variation in contact rate thresholds among species. This variation among focal bird species in sustainable predation levels can be used to prioritize species for reintroduction in a BTS-suppressed landscape, but variation among these species is narrow relative to the required reduction from current BTS levels, which may be four orders of magnitude higher (>0.18). Our modeling indicates that the required predation thresholds may need to be lower than have yet been demonstrated with current BTS management. Our predation threshold metric provides an important management tool to help estimate target BTS suppression levels that can be used to determine when bird reintroduction campaigns might begin and serves as a model for other systems to match predator control with reintroduction efforts.
","language":"English","publisher":"Wiley","doi":"10.1002/eap.2716","usgsCitation":"McElderry, R., Paxton, E.H., Nguyen, A.V., and Siers, S.R., 2022, Predation thresholds for reintroduction of native avifauna following suppression of invasive brown treesnakes on Guam: Ecological Applications, v. 32, no. 8, e2716, 19 p., https://doi.org/10.1002/eap.2716.","productDescription":"e2716, 19 p.","ipdsId":"IP-130719","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":446952,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2716","text":"Publisher Index Page"},{"id":412025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 144.97077826134404,\n 13.59091065759955\n ],\n [\n 144.85095546721982,\n 13.663691679762252\n ],\n [\n 144.77392652814024,\n 13.509785599826927\n ],\n [\n 144.6134495717218,\n 13.445281650900142\n ],\n [\n 144.6284274209881,\n 13.332878728890421\n ],\n [\n 144.6797800470419,\n 13.235003984055268\n ],\n [\n 144.726853287589,\n 13.224589457355279\n ],\n [\n 144.78890437740444,\n 13.272492591536036\n ],\n [\n 144.7931837629091,\n 13.401575642368869\n ],\n [\n 144.93226379180425,\n 13.509785472844925\n ],\n [\n 144.97077826134404,\n 13.59091065759955\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"32","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"McElderry, Robert","contributorId":265185,"corporation":false,"usgs":false,"family":"McElderry","given":"Robert","email":"","affiliations":[{"id":54632,"text":"Research Corporation of the University of Guam","active":true,"usgs":false}],"preferred":false,"id":861792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paxton, Eben H. 0000-0001-5578-7689","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":19640,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben","email":"","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":861793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nguyen, Andre Van 0000-0001-5917-0360","orcid":"https://orcid.org/0000-0001-5917-0360","contributorId":301028,"corporation":false,"usgs":true,"family":"Nguyen","given":"Andre","email":"","middleInitial":"Van","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":861794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Siers, Shane R.","contributorId":152305,"corporation":false,"usgs":false,"family":"Siers","given":"Shane","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":861795,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70234147,"text":"70234147 - 2022 - Reproducibility and variability of earthquake subsidence estimates from saltmarshes of a Cascadia estuary","interactions":[],"lastModifiedDate":"2022-10-31T14:29:19.249559","indexId":"70234147","displayToPublicDate":"2022-08-02T08:26:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2437,"text":"Journal of Quaternary Science","active":true,"publicationSubtype":{"id":10}},"title":"Reproducibility and variability of earthquake subsidence estimates from saltmarshes of a Cascadia estuary","docAbstract":"We examine fossil foraminiferal assemblages from 20 sediment cores to assess sudden relative sea-level (RSL) changes across three mud-over-peat contacts at three salt marshes in northern Humboldt Bay, California (~44.8°N, -124.2°W). We use a validated foraminiferal-based Bayesian transfer function to evaluate the variability of subsidence stratigraphy at a range of 30-6000 m across an estuary. We use the consistency in RSL reconstructions to support estimates of coseismic subsidence from megathrust earthquakes. To assess the variability of subsidence estimates, we analyzed: nine examples of the 1700 CE earthquake (average of 0.64 ±0.14 m subsidence; range of 0.24 ±0.27 to 1.00 ±0.44 m), five examples of the ca. 875 cal a BP earthquake (average of 0.43 ±0.16 m; range of 0.41 ±0.36 to 0.48 ±0.39 m), and six examples of the ca. 1120 cal a BP earthquake (average of 0.70±0.18 m; range of 0.47 ±0.36 to 0.80 ±0.49 m). Our subsidence estimate results suggest ~±0.3 m of within-site (intra-site) variability, which is consistent with previous research. We also identify inconsistencies between sites (inter-site) at northern Humboldt Bay greater than one-sigma uncertainties, driven by variable foraminiferal assemblages in the mud overlying the 1700 CE subsidence contact. Therefore, we recommend at least two quantitative microfossil reconstructions across the same stratigraphic sequence from different marsh sites within an estuary to account for estimate variability and provide increased confidence in vertical coseismic deformation estimates. Our results have broad implications for quantitative, microfossil-based reconstructions of coseismic subsidence at temperate coastlines globally.","language":"English","publisher":"Wiley","doi":"10.1002/jqs.3446","usgsCitation":"Padgett, J.S., Engelhart, S.E., Kelsey, H., Witter, R., and Cahill, N., 2022, Reproducibility and variability of earthquake subsidence estimates from saltmarshes of a Cascadia estuary: Journal of Quaternary Science, v. 37, no. 7, p. 1294-1312, https://doi.org/10.1002/jqs.3446.","productDescription":"19 p.","startPage":"1294","endPage":"1312","ipdsId":"IP-137254","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446956,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/jqs.3446","text":"External Repository"},{"id":404650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Humboldt Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.22721862792969,\n 40.764421348741976\n ],\n [\n -124.19013977050781,\n 40.75271883902363\n ],\n [\n -124.1891098022461,\n 40.77898159474759\n ],\n [\n -124.18224334716797,\n 40.78574062435701\n ],\n [\n -124.17469024658203,\n 40.80133575979201\n ],\n [\n -124.13692474365234,\n 40.804454347291006\n ],\n [\n -124.12559509277342,\n 40.804454347291006\n ],\n [\n -124.08473968505858,\n 40.824201998489904\n ],\n [\n -124.08267974853514,\n 40.82991732677595\n ],\n [\n -124.08130645751953,\n 40.84809918505204\n ],\n [\n -124.08473968505858,\n 40.85770758108904\n ],\n [\n -124.09194946289061,\n 40.87043006899356\n ],\n [\n -124.11632537841795,\n 40.86835309505014\n ],\n [\n -124.11872863769531,\n 40.85822691415107\n ],\n [\n -124.12799835205078,\n 40.86212178233553\n ],\n [\n -124.13383483886719,\n 40.867833841384936\n ],\n [\n -124.15752410888672,\n 40.86705495325258\n ],\n [\n -124.17915344238281,\n 40.82705972420505\n ],\n [\n -124.19528961181639,\n 40.81121078417314\n ],\n [\n -124.20318603515624,\n 40.78834006798032\n ],\n [\n -124.22721862792969,\n 40.764421348741976\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Padgett, Jason Scott 0000-0003-1157-8716","orcid":"https://orcid.org/0000-0003-1157-8716","contributorId":294391,"corporation":false,"usgs":true,"family":"Padgett","given":"Jason","email":"","middleInitial":"Scott","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":847975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engelhart, Simon E.","contributorId":60104,"corporation":false,"usgs":false,"family":"Engelhart","given":"Simon","email":"","middleInitial":"E.","affiliations":[{"id":6923,"text":"University of Rhode Island, Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":847976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelsey, Harvey M.","contributorId":206893,"corporation":false,"usgs":false,"family":"Kelsey","given":"Harvey M.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":847977,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":847978,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cahill, Niamh","contributorId":150754,"corporation":false,"usgs":false,"family":"Cahill","given":"Niamh","email":"","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false},{"id":18091,"text":"University College Dublin","active":true,"usgs":false}],"preferred":false,"id":847979,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237685,"text":"70237685 - 2022 - Hydrological and lock operation conditions associated with paddlefish and bigheaded carp dam passage on a large and small scale in the Upper Mississippi River (Pools 14–18)","interactions":[],"lastModifiedDate":"2022-10-19T13:19:44.062612","indexId":"70237685","displayToPublicDate":"2022-08-02T08:11:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Hydrological and lock operation conditions associated with paddlefish and bigheaded carp dam passage on a large and small scale in the Upper Mississippi River (Pools 14–18)","docAbstract":"Movement and dispersal of migratory fish species is an important life-history characteristics that can be impeded by navigation dams. Although habitat fragmentation may be detrimental to native fish species, it might act as an effective and economical barrier for controlling the spread of invasive species in riverine systems. Various technologies have been proposed as potential fish deterrents at locks and dams to reduce bigheaded carp (i.e., silver carp and bighead carp (Hypophthalmichthys spp.)) range expansion in the Upper Mississippi River (UMR). Lock and Dam (LD) 15 is infrequently at open-river condition (spillway gates completely open; hydraulic head across the dam <0.4 m) and has been identified as a potential location for fish deterrent implementation. We used acoustic telemetry to evaluate paddlefish passage at UMR dams and to evaluate seasonal and diel movement of paddlefish and bigheaded carp relative to environmental conditions and lock operations at LD 15. We observed successful paddlefish passage at all dams, with the highest number of passages occurring at LDs 17 and 16. Paddlefish residency events in the downstream lock approach of LD 15 occurred more frequently and for longer durations than residency events of bigheaded carp. We documented upstream passages completed by two individual paddlefish through the lock chamber at LD 15, and a single bighead carp completed upstream passage through the lock chamber during two separate years of this study. We identified four bigheaded carp and 19 paddlefish that made upstream passages through the spillway gates at LD 15 during this study. The majority of the upstream passages through the spillway gates for both species occurred during open river conditions. When hydraulic head was approximately 1-m or greater, we observed these taxa opt for upstream passage through the lock chamber more often than the dam gates. In years with infrequent open-river condition, a deterrent placed in the downstream lock approach may assist in meeting the management goal of reducing upstream passage of bigheaded carps but could also potentially affect paddlefish residency and passage. Continued study to understand the effects of deterrents on native fish could be beneficial for implementing an integrated bigheaded carp control strategy. Understanding fish behavior at UMR dams is a critical information need for river managers as they evaluate potential tools or technologies to control upstream expansion of bigheaded carp in the UMR.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.13822","usgsCitation":"Turney, D.D., Fritts, A.K., Knights, B.C., Vallazza, J.M., Appel, D., and Lamar, J.T., 2022, Hydrological and lock operation conditions associated with paddlefish and bigheaded carp dam passage on a large and small scale in the Upper Mississippi River (Pools 14–18): PeerJ, v. 10, e13822, 31 p., https://doi.org/10.7717/peerj.13822.","productDescription":"e13822, 31 p.","ipdsId":"IP-135535","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":446958,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.13822","text":"Publisher Index Page"},{"id":435747,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CHJ8OG","text":"USGS data release","linkHelpText":"2017-2019 Telemetry data for invasive carp and paddlefish surrounding Lock and Dam 15 in the Upper Mississippi River Basin"},{"id":408536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.7138671875,\n 40.41767833585549\n ],\n [\n -89.8736572265625,\n 40.41767833585549\n ],\n [\n -89.8736572265625,\n 41.9921602333763\n ],\n [\n -91.7138671875,\n 41.9921602333763\n ],\n [\n -91.7138671875,\n 40.41767833585549\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2022-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Turney, Dominique D.","contributorId":298069,"corporation":false,"usgs":false,"family":"Turney","given":"Dominique","email":"","middleInitial":"D.","affiliations":[{"id":49637,"text":"Western Illinois University","active":true,"usgs":false}],"preferred":false,"id":855012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fritts, Andrea K. 0000-0003-2142-3339","orcid":"https://orcid.org/0000-0003-2142-3339","contributorId":204594,"corporation":false,"usgs":true,"family":"Fritts","given":"Andrea","email":"","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":855013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":855014,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vallazza, Jonathan M. 0000-0003-2367-4887 jvallazza@usgs.gov","orcid":"https://orcid.org/0000-0003-2367-4887","contributorId":149362,"corporation":false,"usgs":true,"family":"Vallazza","given":"Jonathan","email":"jvallazza@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":855015,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Appel, Douglas 0000-0001-8775-1058","orcid":"https://orcid.org/0000-0001-8775-1058","contributorId":268159,"corporation":false,"usgs":true,"family":"Appel","given":"Douglas","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":855016,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lamar, James T.","contributorId":298070,"corporation":false,"usgs":false,"family":"Lamar","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":855017,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70234212,"text":"70234212 - 2022 - Sclerochronological records of environmental variability and bivalve growth in the Pacific Arctic","interactions":[],"lastModifiedDate":"2022-08-15T14:03:40.905011","indexId":"70234212","displayToPublicDate":"2022-08-02T06:54:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3194,"text":"Progress in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Sclerochronological records of environmental variability and bivalve growth in the Pacific Arctic","docAbstract":"The Pacific Arctic region has experienced, and is projected to continue experiencing, rapid climate change. Large uncertainties exist in our understanding of the impact these physical changes have on the region’s ecology. This is, in part, due to the lack of long-term data. Here we investigate bivalve mollusc growth increment width chronologies (sclerochronologies) to develop a long-term biological data series in an Arctic species and address the hypothesis that benthic production in the Pacific Arctic region is in decline with implications for predators (e.g., walrus, whales, seals, and sea ducks). Growth increments formed in the shells of two bivalve mollusc species, Astarte borealis and Liocyma fluctuosa, were examined using conventional sclerochronological techniques. The A. borealis and L. fluctuosa samples exhibited measured longevities of >148 and >18 years, respectively, in the coastal waters of Alaska’s Chukchi Sea. Dendrochronology crossdating techniques facilitated the development of two robust (expressed population signal >0.85) independent growth increment width chronologies. These chronologies provide evidence of the growth conditions through time for each species (1985-2015 for A. borealis and 1997-2014 for L. fluctuosa). Linear regression analyses identified that both species grew more rapidly in years with warmer sea surface temperature and lower sea ice concentration. The results provide evidence that benthic ecosystems are benefiting from the warmer conditions and reduced sea ice that have accompanied recent Arctic climate trends. This result is encouraging for benthic predators in the eastern Chukchi Sea as it alleviates the concern that their benthic prey has already become food limited by weakened pelagic-benthic coupling. More broadly, this initial A. borealis chronology is among the longest biological data series for any Arctic species and highlights the feasibility of multicentennial biological data for the Arctic.
The 2018 eruption of Mount Veniaminof occurred from September 3–4 to December 27, lasting about 114 days. This report summarizes the types of volcanic unrest that accompanied the eruption and provides a chronology of events and observations. Information about the 2018 eruption was derived from geophysical instrumentation on or near the volcano that included an eight-station seismic network and regional infrasound sensors. Other observations came from frequent satellite images of the eruption, occasional aerial photographs and videos contributed by passing pilots, and web-camera views of the volcano from Perryville, Alaska, about 35 kilometers (km) south of the volcano. Eruptive activity involved small vents on the upper south flank of a cinder cone (cone A) within the ice-filled caldera that characterizes Mount Veniaminof. The 2018 eruption consisted of occasional explosive emissions of ash and gas (reaching up to 6,000 meters above sea level), episodes of low-level lava fountaining, Strombolian explosive activity, and effusion of lava flows. By the end of the eruption, lava covered an area of about 600,000 square meters (m2) on the lower south flank of cone A. The lava flows melted into ice and snow, slowly creating melt depressions around the flow margins. No unusual outflows of water were observed exiting the caldera through the main drainage northwest of the cone. Minor ash emissions were generated throughout the eruptive period, and trace amounts of ash fell on Perryville on October 25 and November 21–22. There were no reports of aircraft encounters with ash clouds. The amount of lava and ash erupted from early September to late December 2018 resulted in the generation of about 1,200,000 cubic meters (m3) of lava and 20,000–30,000 m3 of ash, which would characterize the 2018 activity as having an eruption magnitude of 1–2 on the Volcanic Explosivity Index (VEI) scale.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225075","usgsCitation":"Waythomas, C.F., Dietterich, H.R., Tepp, G.M., Lopez, T.M., and Loewen, M.W., 2022, The 2018 eruption of Mount Veniaminof, Alaska: U.S. Geological Survey Scientific Investigations Report 2022-5075, 32 p., https://doi.org/10.3133/sir20225075.","productDescription":"vii, 32 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-120282","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":404574,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5075/covrthb.jpg"},{"id":404575,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5075/sir20225075.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Alaska","otherGeospatial":"Mount Veniaminof","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160.3399658203125,\n 55.83522882231773\n ],\n [\n -158.1866455078125,\n 55.83522882231773\n ],\n [\n -158.1866455078125,\n 56.48676175249086\n ],\n [\n -160.3399658203125,\n 56.48676175249086\n ],\n [\n -160.3399658203125,\n 55.83522882231773\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Volcano Observatory
U.S. Geological Survey
4210 University Drive
Anchorage, AK 99508
This paper proposes a graph-based meta learning approach to separately predict water quantity and quality variables for river segments in stream networks. Given the heterogeneous water dynamic patterns in large-scale basins, we introduce an additional meta-learning condition based on physical characteristics of stream segments, which allows learning different sets of initial parameters for different stream segments. Specifically, we develop a representation learning method that leverages physical simulations to embed the physical characteristics of each segment. The obtained embeddings are then used to cluster river segments and add the condition for the meta-learning process. We have tested the performance of the proposed method for predicting daily water temperature and streamflow for the Delaware River Basin (DRB) over a 14 year period. The results confirm the effectiveness of our method in predicting target variables even using sparse training samples. We also show that our method can achieve robust performance with different numbers of clusterings.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and data mining","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","conferenceDate":"August 14-18, 2022","conferenceLocation":"Washington DC","language":"English","publisher":"ACM Digital Library","doi":"10.1145/3534678.3539115","usgsCitation":"Chen, S., Zwart, J.A., and Jia, X., 2022, Physics-guided graph meta learning for predicting water temperature and streamflow in stream networks, in Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and data mining, Washington DC, August 14-18, 2022, p. 2752-2761, https://doi.org/10.1145/3534678.3539115.","productDescription":"10 p.","startPage":"2752","endPage":"2761","ipdsId":"IP-138051","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":420911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Chen, Shengyu","contributorId":297452,"corporation":false,"usgs":false,"family":"Chen","given":"Shengyu","email":"","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":883313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":883314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":883315,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70237270,"text":"70237270 - 2022 - Floodplains and climate change","interactions":[],"lastModifiedDate":"2022-10-06T15:00:23.931708","indexId":"70237270","displayToPublicDate":"2022-08-01T11:35:37","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":12617,"text":"IEP Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"99","chapter":"4","title":"Floodplains and climate change","docAbstract":"Floodplains are landscape features that are periodically inundated by water from adjacent rivers (Opperman et al. 2010). Ecologically, functional floodplains are characterized by three primary elements: connectivity, flow regime, and spatial scale. Water quantity flowing over floodplains can vary greatly. Based on a flood’s effects on the floodplain, three flood categories have been defined: floodplain-activation floods, floodplain-maintenance floods, and floodplainresetting floods (Box 1). Several physical parameters determine the types of ecosystems on floodplains and the species they will support; these include temperature, water depth, water velocity, and hydrologic connectivity (Opperman et al. 2010). Natural ecosystems commonly found on floodplains include annual vegetation, forests, seasonal wetlands, and permanent ponds or wetlands (Whipple et al. 2012). Floodplains provide many valuable ecosystem services: attenuation of flood flows which reduces flood risk, filtration of surface water, recreation, fisheries, agriculture, biodiversity, food availability, and groundwater recharge, which contributes to more-sustained and cooler dry-season flows (Opperman et al. 2010).
--------------------------------------------------------------------------------------------------------------
Box 1
Floodplain-activation flood
A small magnitude flood that occurs relatively frequently and produces characteristic ecological benefits such as food-web productivity and habitat creation for native fish spawning and rearing.
Floodplain-maintenance flood
A higher magnitude flood that, in addition to providing ecological benefits, results in geomorphic changes including bank erosion and deposition on the floodplain.
Floodplain-resetting flood
A very high-magnitude flood that occurs rarely and results in extensive geomorphic changes, such as the scouring of floodplain surfaces and changes in channel location due to avulsion.
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","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Synthesis of data and studies related to the effect of climate change on the ecosystems and biota of the Upper San Francisco Estuary Year 2022","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"Interagency Ecological Program","usgsCitation":"Keeley, A., Khanna, S., Kwan, N., Matthias, B.G., Pien, C., and Wulff, M.L., 2022, Floodplains and climate change: IEP Technical Report 99, 51 p.","productDescription":"51 p.","startPage":"188","endPage":"238","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":408038,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":407971,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://iep.ca.gov/Publications/Library","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Cosumnes River floodplain, Yolo Bypass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.9317626953125,\n 37.709899354855125\n ],\n [\n -120.3936767578125,\n 37.709899354855125\n ],\n [\n -120.3936767578125,\n 39.21523130910491\n ],\n [\n -121.9317626953125,\n 39.21523130910491\n ],\n [\n -121.9317626953125,\n 37.709899354855125\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Bashevkin, Samuel M.","contributorId":288941,"corporation":false,"usgs":false,"family":"Bashevkin","given":"Samuel M.","affiliations":[{"id":61910,"text":"Delta Science Program, Delta Stewardship Council","active":true,"usgs":false}],"preferred":false,"id":854020,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854021,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Bush, Eva","contributorId":297190,"corporation":false,"usgs":false,"family":"Bush","given":"Eva","email":"","affiliations":[{"id":64315,"text":"Delta Stewardship Council Delta Science Program","active":true,"usgs":false}],"preferred":false,"id":854022,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Castillo, Gonzalo","contributorId":269408,"corporation":false,"usgs":false,"family":"Castillo","given":"Gonzalo","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife 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Shruti","contributorId":74287,"corporation":false,"usgs":true,"family":"Khanna","given":"Shruti","affiliations":[],"preferred":false,"id":854027,"contributorType":{"id":2,"text":"Editors"},"rank":8},{"text":"Keeley, Annika","contributorId":297191,"corporation":false,"usgs":false,"family":"Keeley","given":"Annika","email":"","affiliations":[{"id":64315,"text":"Delta Stewardship Council Delta Science Program","active":true,"usgs":false}],"preferred":false,"id":854028,"contributorType":{"id":2,"text":"Editors"},"rank":9},{"text":"Kwan, Nicole","contributorId":297192,"corporation":false,"usgs":false,"family":"Kwan","given":"Nicole","email":"","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":854029,"contributorType":{"id":2,"text":"Editors"},"rank":10},{"text":"Lehman, Peggy W.","contributorId":96168,"corporation":false,"usgs":false,"family":"Lehman","given":"Peggy","email":"","middleInitial":"W.","affiliations":[{"id":7101,"text":"California Department of Water Resources, Geodetic Branch","active":true,"usgs":false}],"preferred":false,"id":854030,"contributorType":{"id":2,"text":"Editors"},"rank":11},{"text":"Mahardja, Brian","contributorId":174645,"corporation":false,"usgs":false,"family":"Mahardja","given":"Brian","email":"","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":854031,"contributorType":{"id":2,"text":"Editors"},"rank":12},{"text":"Malinich, Timothy D.","contributorId":7583,"corporation":false,"usgs":true,"family":"Malinich","given":"Timothy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":854032,"contributorType":{"id":2,"text":"Editors"},"rank":13},{"text":"McKenzie, Ryan","contributorId":297366,"corporation":false,"usgs":false,"family":"McKenzie","given":"Ryan","email":"","affiliations":[],"preferred":false,"id":854033,"contributorType":{"id":2,"text":"Editors"},"rank":14},{"text":"Matthias, Bryan G.","contributorId":240763,"corporation":false,"usgs":false,"family":"Matthias","given":"Bryan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":854034,"contributorType":{"id":2,"text":"Editors"},"rank":15},{"text":"Pien, Catarina","contributorId":297193,"corporation":false,"usgs":false,"family":"Pien","given":"Catarina","email":"","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":854035,"contributorType":{"id":2,"text":"Editors"},"rank":16},{"text":"Wulff, Marissa L. 0000-0003-0121-9066 mwulff@usgs.gov","orcid":"https://orcid.org/0000-0003-0121-9066","contributorId":1719,"corporation":false,"usgs":true,"family":"Wulff","given":"Marissa","email":"mwulff@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854036,"contributorType":{"id":2,"text":"Editors"},"rank":17}],"authors":[{"text":"Keeley, Annika","contributorId":297191,"corporation":false,"usgs":false,"family":"Keeley","given":"Annika","email":"","affiliations":[{"id":64315,"text":"Delta Stewardship Council Delta Science Program","active":true,"usgs":false}],"preferred":false,"id":854014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Khanna, Shruti","contributorId":74287,"corporation":false,"usgs":true,"family":"Khanna","given":"Shruti","affiliations":[],"preferred":false,"id":854015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kwan, Nicole","contributorId":297192,"corporation":false,"usgs":false,"family":"Kwan","given":"Nicole","email":"","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":854016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matthias, Bryan G.","contributorId":240763,"corporation":false,"usgs":false,"family":"Matthias","given":"Bryan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":854017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pien, Catarina","contributorId":297193,"corporation":false,"usgs":false,"family":"Pien","given":"Catarina","email":"","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":854018,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wulff, Marissa L. 0000-0003-0121-9066 mwulff@usgs.gov","orcid":"https://orcid.org/0000-0003-0121-9066","contributorId":1719,"corporation":false,"usgs":true,"family":"Wulff","given":"Marissa","email":"mwulff@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854019,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70237209,"text":"70237209 - 2022 - Chapter 1: General conceptual model for climate change in the Upper San Francisco Estuary","interactions":[],"lastModifiedDate":"2022-10-05T20:04:24.970765","indexId":"70237209","displayToPublicDate":"2022-08-01T11:35:25","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":12617,"text":"IEP Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"99","chapter":"1","title":"Chapter 1: General conceptual model for climate change in the Upper San Francisco Estuary","docAbstract":"This report is a collaboration by many state and federal agencies working in the Upper San Francisco Estuary to analyze the potential impacts of climate change to different ecosystems found here. Management stategies for ecological values in the face of climate change require reliable and focused information. In this technical report, our focus is on the Upper San Francisco Estuary (SFE), which contains the Sacramento-San Joaquin Delta and Suisun Bay. This area is home to three interconnected ecosystems: open water, floodplain, and tidal marsh. For this geographical area, we have decades of in-depth monitoring information and scientific investigations that have been successfully used to address a number of management needs. In 2019, the Interagency Ecological Program established a diverse work team to improve our ability to anticipate and respond to climate change impacts. The charge to the group was to:
• synthesize science relevant to climate change,
• determine important knowledge gaps, and
• identify ecosystem metrics for climate change.
We focus our analyses on the likely impacts of climate change on interconnected aquatic habitats. We illustrate how changes in habitats are likely to affect diverse species.
In this report we describe ecological trends attributable to climate change and likely future impacts. We address four principal questions:
1. How have the habitats and biotic communities changed due to climatic trends and events?
2. How are estuarine habitats, flora, and fauna likely to change as climate change trends continue?
3. What are key metrics to document ecosystem change as a result of climate change?
4. How should our monitoring change to improve information value?
Our work builds on the similar work of the San Francisco Baylands Goals Project (Goals Project 2015), which addressed climate change impacts to wetlands downstream of the confluence of the Sacramento and San Joaquin Rivers. We aim to contribute to an integrated baseline understanding of climate change impacts for the entire San Francisco Estuary.
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Moreover, the automotive manufacturing industries are reliant on complex and sometimes opaque multi-tiered global supply chains. Among the many industries on which automotive supply chains depend are the electronics and semiconductor industries, which are themselves material-intensive and reliant on opaque global supply chains. A linear programming model built on mineral end-use data and input-output tables provides a tool for investigating inter-industry relationships between the two sets of industry sectors and industrial vulnerability to mineral commodity supply disruptions. Supply disruptions in aluminum, magnesium metal, and zinc—metals used in the body-in-white, wheels and other parts—have significant potential to disrupt the automotive industries. On the other hand, supply disruptions in gallium, tellurium, and indium for example—semiconductor elements used in power electronics, screen coatings and other parts—have significant potential to impact the electronics and computer industries. More interestingly, case studies of the automotive and electronics industries show how supply disruptions in mineral commodities that are generally considered semiconductor materials, such as gallium, can significantly impact the automotive sector.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.resourpol.2022.102894","usgsCitation":"Manley, R., Alonso, E., and Nassar, N.T., 2022, Examining industry vulnerability: A focus on mineral commodities used in the automotive and electronics industries: Resources Policy, v. 78, 102894, 8 p., https://doi.org/10.1016/j.resourpol.2022.102894.","productDescription":"102894, 8 p.","ipdsId":"IP-135107","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":487793,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.resourpol.2022.102894","text":"Publisher Index Page"},{"id":408492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Manley, Ross 0000-0002-3341-4766","orcid":"https://orcid.org/0000-0002-3341-4766","contributorId":223012,"corporation":false,"usgs":true,"family":"Manley","given":"Ross","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":854894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alonso, Elisa 0000-0002-0090-8284","orcid":"https://orcid.org/0000-0002-0090-8284","contributorId":223015,"corporation":false,"usgs":true,"family":"Alonso","given":"Elisa","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":854895,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":197864,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","middleInitial":"T.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":854896,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70237283,"text":"70237283 - 2022 - Influence of surface- and ground-water hydrology on riparian tree growth and mortality in the Limitrophe segment of the Colorado River","interactions":[],"lastModifiedDate":"2022-11-29T16:53:40.800191","indexId":"70237283","displayToPublicDate":"2022-08-01T10:03:14","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":12975,"text":"Biennial Report","active":true,"publicationSubtype":{"id":4}},"chapter":"4","title":"Influence of surface- and ground-water hydrology on riparian tree growth and mortality in the Limitrophe segment of the Colorado River","docAbstract":"Branch sections and cores of cottonwood and willow trees were collected from two sites in the Limitrophe. Tree-ring analyses may reveal the relationships among tree growth, streamflow and groundwater.
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This report chapter summarizes 2018 results from the restoration and control sites and compares restoration site results between 2017 and 2018.
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This study was conducted before the devastating 2020 East Troublesome Fire1, which spread across 193,812 acres and resulted in two lives lost and 366 homes and 214 other structures burned. The fire’s dramatic run threatened over 7,000 structures and led to a mandatory evacuation of over 35,000 people in Grand and Larimer Counties. The data reported here serve as baseline data to aid in understanding the parcel and social conditions before the fire. This report presents results from WiRē Rapid Wildfire Risk Assessment (WiRē RA) data, collected from 1,162 private residential properties in six communities in five fire protection districts (FPDs), the majority (72%) of which were characterized as high, very high, or extreme risk.
This report also presents results from household surveys sent to homeowners in the study area. Household survey respondents underestimated their risk compared to the conditions observed through the professional risk assessment. Respondents consistently overestimated the amount of defensible space and the distance from their homes to nonvegetative combustibles. Respondents also overestimated the availability of driveway clearance that would enable access for response vehicles and for safe passing of residents evacuating and responders arriving to their homes.
Structure from motion (SfM) photogrammetry is an increasingly common technique for measuring landscape change over time by deriving 3D point clouds and surface models from overlapping photographs. Traditional change detection approaches require photos that are geotagged with a differential GPS (DGPS) location, which requires expensive equipment that can limit the ability of communities and researchers to perform frequent (i.e. daily, weekly, and/or monthly) surveys. Crowd-sourced photos can lower the barrier to entry and substantially increase the frequency of surveys, although such photos often lack accurate location information and can vary in quality. This paper presents a SfM approach for monitoring environmental change in high relief coastal environments that does not require all photos have DGPS location information and does not require field survey data. A 1.5 km section of coastal bluffs near the Elwha River Delta (Washington state) is used to demonstrate the efficacy of this approach. Photos of the bluff were collected with a digital SLR camera or phone camera while either on foot along the beach or from a boat as part of monitoring following removal of two large dams along the Elwha River during 2011–2013. Only 33% of photos had DGPS location information, whereas most photos had no location information or locations that were accurate to a couple of meters. All photos were processed using 3D, 4D, and fixed-floating (FF) SfM alignment methods and the resulting dense point clouds are used to compare the different alignment approaches with crowd-sourced photo sets. Results demonstrate that 4D and FF approaches are more likely to reconstruct and are more accurate than the 3D approach. While the 4D and FF have comparable accuracies, the FF approach is several orders of magnitude more efficient, as this method can leverage camera location information from relatively few photos to improve the accuracy of all aligned and derived products. Effectively utilizing crowd-sourced photos in SfM change detection can improve the frequency of surveying a landscape in a more cost-effective approach that also has potential for citizen-science engagement and communication. This is especially important for data-poor environments such as high-relief coastal cliffs and bluffs, where near-nadir imagery and LIDAR may fail to accurately capture near-vertical cliffs or bluff faces. Based on the analysis of different photo alignment and filtering approaches, we present suggested best practices for engaging citizen scientists in coastal cliff and bluff monitoring efforts through collecting photos amenable for SfM reconstruction.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2022.104799","usgsCitation":"Wernette, P., Miller, I.M., Ritchie, A.C., and Warrick, J.A., 2022, Crowd-sourced SfM: Best practices for high resolution monitoring of coastal cliffs and bluffs: Continental Shelf Research, v. 245, 104799, 12 p., https://doi.org/10.1016/j.csr.2022.104799.","productDescription":"104799, 12 p.","ipdsId":"IP-129225","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446968,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.5061/dryad.63xsj3v4s","text":"External Repository"},{"id":404570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.54572296142578,\n 48.146846885734256\n ],\n [\n -123.52460861206055,\n 48.12805945422104\n ],\n [\n -123.51877212524414,\n 48.13413175409871\n ],\n [\n -123.52632522583006,\n 48.13963057588326\n ],\n [\n -123.53284835815428,\n 48.146846885734256\n ],\n [\n -123.54537963867186,\n 48.150970035875766\n ],\n [\n -123.54572296142578,\n 48.146846885734256\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"245","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wernette, Phillipe Alan 0000-0002-8902-5575","orcid":"https://orcid.org/0000-0002-8902-5575","contributorId":259274,"corporation":false,"usgs":true,"family":"Wernette","given":"Phillipe Alan","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":847869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Ian M. 0000-0002-3289-6337","orcid":"https://orcid.org/0000-0002-3289-6337","contributorId":41951,"corporation":false,"usgs":false,"family":"Miller","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":847870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ritchie, Andrew C. aritchie@usgs.gov","contributorId":4984,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew","email":"aritchie@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":847871,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":847872,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237091,"text":"70237091 - 2022 - Section 5: Remote sensing of vegetation in the riparian corridor of the Colorado River’s delta 2013-2018","interactions":[],"lastModifiedDate":"2026-01-12T16:42:05.865776","indexId":"70237091","displayToPublicDate":"2022-08-01T09:21:50","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Section 5: Remote sensing of vegetation in the riparian corridor of the Colorado River’s delta 2013-2018","docAbstract":"This remote sensing section is based on Nagler et al. (in preparation for the journal Hydrological Processes) and is a summary of the USGS preliminary findings to date.
This report documents the changes in green foliage density (greenness) as measured by satellite vegetation index (VI) data and corresponding evapotranspiration (ET) in the riparian corridor of the Colorado River delta associated with the Minutes 319 and 323 environmental water deliveries using time-series data from 2013 through 2018. The report focuses on what happened only within the riparian corridor’s seven reaches since the 2014 flows, and despite being a continuation of measuring greenness and ET after the 2017 end of Minute 319, this study continued the tracking of these two variables, greenness and ET, in these original riparian corridor focal areas. Two spatial scales are used here: (1) Landsat satellite imagery at 30 m pixels and (2) the EOS-1 satellite sensor the Moderate Resolution Imaging Spectrometer (MODIS) with a resolution of 250 m pixels. The focal period includes 2013 (prepulse flow) and the years 2014-2018, with a focus on imagery collected from the Summer growing seasons 2014 through 2018 (one-year, pre-pulse and several post-pulse years, respectively).
This report re-creates the 2013-2017 Landsat-based results from Jarchow et al. (2017a, b) by using the same region of interest (ROI). The report now provides revised and re-created results using all new imagery acquisition and processing techniques, as well as extraction code, created by the Vegetation Index and Phenology (VIP) Lab of the Biosystems Engineering Department of the University of Arizona (UofA). In 2018, methods employed by the VIP lab (and not ArcGIS) were used. ArcGIS was only used in the newly processed data to display the final difference maps. The entire spatial tile data from NASA was downloaded and processed at the VIP Lab using satellite imagery at two resolutions: 250 m MODIS and 30 m Landsat using three sensors, Landsat 5, Landsat 7 ETM+ and Landsat 8 Operational Land Imager (OLI), with added scenes for each year based on new clear atmosphere requirements. The VIP lab clipped the river boundary and seven riparian reaches from the previously existing ROI used in Jarchow et al. (2017 a, b) for the analyses done under Minute 319. The NASA image datasets for this riparian corridor ROI in seven reaches were re-processed to produce additional vegetation index (VI) information for years 2013 to 2018 for this report. At the same time, the report acquired and processed imagery from 2000- 2018 (data outside the scope of this report and data not shown here). The additional VIs (NDVI, scaled NDVI, EVI, EVI2) were analyzed so that new assessments of greenness and ET could be produced from the imagery datasets following methods in Nagler et al. (2013). These VI choices were based on previous performance comparisons between biophysical ground-based data and radiometric satellite-based data collected from this riparian ecosystem (Nagler et al., 2001) as well as performance related to ET estimation (Nagler et al., 2005a, b) and current advancements in VIs such as EVI2.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Minute 323: Colorado River limitrophe and delta environmental flows monitoring interim report for 2018","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"International Boundary and Water Commission United States and Mexico","usgsCitation":"Nagler, P.L., Barreto-Munoz, A., Jarchow, C., and Didan, K., 2022, Section 5: Remote sensing of vegetation in the riparian corridor of the Colorado River’s delta 2013-2018, 10 p.","productDescription":"10 p.","startPage":"39","endPage":"48","ipdsId":"IP-114755","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":407594,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Colorado River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.17517089843749,\n 31.587894464070395\n ],\n [\n -114.3621826171875,\n 31.587894464070395\n ],\n [\n -114.3621826171875,\n 32.99484290420988\n ],\n [\n -115.17517089843749,\n 32.99484290420988\n ],\n [\n -115.17517089843749,\n 31.587894464070395\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barreto-Munoz, Armando","contributorId":131000,"corporation":false,"usgs":false,"family":"Barreto-Munoz","given":"Armando","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":853314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jarchow, Christopher J. 0000-0002-0424-4104","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":211737,"corporation":false,"usgs":false,"family":"Jarchow","given":"Christopher J.","affiliations":[{"id":38314,"text":"USGS Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":853315,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Didan, Kamel","contributorId":292780,"corporation":false,"usgs":false,"family":"Didan","given":"Kamel","affiliations":[{"id":62999,"text":"Biosystems Engineering, University of Arizona, Tucson, AZ, 85721 USA","active":true,"usgs":false}],"preferred":false,"id":853316,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70241555,"text":"70241555 - 2022 - Editorial: Fire regimes in desert ecosystems: Drivers, impacts and changes","interactions":[],"lastModifiedDate":"2023-03-23T13:59:45.335315","indexId":"70241555","displayToPublicDate":"2022-08-01T08:56:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Editorial: Fire regimes in desert ecosystems: Drivers, impacts and changes","docAbstract":"Although not commonly associated with fire, many desert ecosystems across the globe do occasionally burn, and there is evidence that fire incidences are increasing, leading to altered fire regimes in this biome. The increased prevalence of megafires (wildfires >10,000 ha in size and typically damaging) in most global biomes is linked to climate change, although those occurring in deserts have received far less attention, from both a research and policy perspective, than that of forested ecosystems (Linley et al., 2022). Understanding the drivers of desert fires, from climate to landscape patterns of hydrology and soil, and how these may be changing in the face of anthropogenic pressures, such as invasive species, livestock grazing, and global climate change, is imperative. This Research Topic has published nine papers addressing these drivers, how they have changed, and their impacts on desert biodiversity.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2022.968031","usgsCitation":"van Etten, E.J., Brooks, M.L., Greenville, A.C., and Wardel, G.M., 2022, Editorial: Fire regimes in desert ecosystems: Drivers, impacts and changes: Frontiers in Ecology and Evolution, v. 10, 968031, 3 p., https://doi.org/10.3389/fevo.2022.968031.","productDescription":"968031, 3 p.","ipdsId":"IP-143374","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":446971,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2022.968031","text":"Publisher Index Page"},{"id":414611,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-08-01","publicationStatus":"PW","contributors":{"authors":[{"text":"van Etten, Eddie J. B.","contributorId":303343,"corporation":false,"usgs":false,"family":"van Etten","given":"Eddie","email":"","middleInitial":"J. B.","affiliations":[{"id":65770,"text":"Edith Cowan University, Australia","active":true,"usgs":false}],"preferred":false,"id":867294,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brooks, Matthew L. 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":393,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":867295,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Greenville, Aaron C.","contributorId":300416,"corporation":false,"usgs":false,"family":"Greenville","given":"Aaron","email":"","middleInitial":"C.","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":867296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wardel, Glenda M.","contributorId":303344,"corporation":false,"usgs":false,"family":"Wardel","given":"Glenda","email":"","middleInitial":"M.","affiliations":[{"id":33318,"text":"University of Sydney, Australia","active":true,"usgs":false}],"preferred":false,"id":867297,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70234150,"text":"70234150 - 2022 - Defining fine-scaled population structure among continuously distributed populations","interactions":[],"lastModifiedDate":"2022-10-17T15:47:18.330622","indexId":"70234150","displayToPublicDate":"2022-08-01T08:27:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Defining fine-scaled population structure among continuously distributed populations","docAbstract":"Climate change is a significant threat to people living in mountainous regions. It is essential to understand how montane communities currently depend especially on the provisioning ecosystem services (ES) and the ways in which climate change will impact these services, so that people can develop relevant adaptation strategies. The ES in the Gurez Valley, in the Western Himalayas of Pakistan, provide a unique opportunity to explore these questions. This understudied area is increasingly exposed not only to climate change but also to the overexploitation of resources. Hence, this study aimed to (a) identify and value provisioning ES in the region; (b) delineate indigenous communities’ reliance on ES based on valuation; and (c) measure the perceptions of indigenous communities of the impact of climate change on the ES in Gurez Valley. Semi-structured interviews and focus group discussions were used to classify the provisioning ES by using the ‘Common International Classification on Ecosystem Services’ (CICES) table and applying the ‘Total Economic Valuation (TEV)’ Framework. Results indicate that the indigenous communities are highly dependent on ES, worth 6730 ± 520 USD/Household (HH)/yr, and perceive climate change as a looming threat to water, crops, and rearing livestock ESS in the Gurez Valley. The total economic value of the provisioning ES is 3.1 times higher than a household’s average income. Medicinal plant collection is a significant source of revenue in the Valley for some households, i.e., worth 766 ± 134.8 USD/HH/yr. The benefits of the sustainable use of ES and of climate change adaptation and mitigation, are culturally, economically, and ecologically substantial for the Western Himalayans.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoser.2022.101453","usgsCitation":"Saeed, U., Arshad, M., Hayat, S., Morelli, T.L., and Nawaz, M.A., 2022, Analysis of provisioning ecosystem services and perceptions of climate change for indigenous communities in the Western Himalayan Gurez Valley, Pakistan: Ecosystem Services, v. 56, 101453, 12 p., https://doi.org/10.1016/j.ecoser.2022.101453.","productDescription":"101453, 12 p.","ipdsId":"IP-142004","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":410705,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Pakistan","otherGeospatial":"Gurez Valley, Himalaya","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 74.30402879968273,\n 34.79872407583629\n ],\n [\n 74.33003022612647,\n 34.803218980915204\n ],\n [\n 74.35671590063629,\n 34.78973353043585\n ],\n [\n 74.40392901707412,\n 34.80546634154311\n ],\n [\n 74.41419273803945,\n 34.78973353043585\n ],\n [\n 74.44156266061273,\n 34.793667014669126\n ],\n [\n 74.46893258318607,\n 34.78186599911395\n ],\n [\n 74.52025118801137,\n 34.772873615881096\n ],\n [\n 74.57430678509314,\n 34.76725287869074\n ],\n [\n 74.60715069218222,\n 34.74476610231628\n ],\n [\n 74.64683707991256,\n 34.72452276850544\n ],\n [\n 74.68515497151597,\n 34.711024458004616\n ],\n [\n 74.71663038247542,\n 34.69077286128618\n ],\n [\n 74.80147714245189,\n 34.689647627252725\n ],\n [\n 74.86901926888083,\n 34.68683447525103\n ],\n [\n 74.87791449371787,\n 34.70877452537363\n ],\n [\n 74.856018555659,\n 34.731271097417476\n ],\n [\n 74.87996723791093,\n 34.75825890299676\n ],\n [\n 74.8792829898461,\n 34.8077136408957\n ],\n [\n 74.79512047793315,\n 34.8352380842708\n ],\n [\n 74.74380187310788,\n 34.82568982952914\n ],\n [\n 74.6733243224815,\n 34.86668332685447\n ],\n [\n 74.60900500443444,\n 34.90260602860445\n ],\n [\n 74.57273985702543,\n 34.89362682537012\n ],\n [\n 74.52820462141244,\n 34.853769770789015\n ],\n [\n 74.49399221819647,\n 34.86050753124755\n ],\n [\n 74.42830440401977,\n 34.84029259441431\n ],\n [\n 74.37424880693797,\n 34.834676452877076\n ],\n [\n 74.29556027953936,\n 34.830183263796556\n ],\n [\n 74.30402879968273,\n 34.79872407583629\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"56","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Saeed, Uzma","contributorId":300021,"corporation":false,"usgs":false,"family":"Saeed","given":"Uzma","email":"","affiliations":[{"id":65001,"text":"Quaid I Azam University, Department of Animal Sciences","active":true,"usgs":false}],"preferred":false,"id":859279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arshad, Muhammad","contributorId":300022,"corporation":false,"usgs":false,"family":"Arshad","given":"Muhammad","affiliations":[{"id":49180,"text":"Snow Leopard Trust","active":true,"usgs":false}],"preferred":false,"id":859280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayat, Shakeel","contributorId":300023,"corporation":false,"usgs":false,"family":"Hayat","given":"Shakeel","email":"","affiliations":[{"id":65002,"text":"Institute of Management Sciences","active":true,"usgs":false}],"preferred":false,"id":859281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":859282,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nawaz, Muhammad Ali","contributorId":300024,"corporation":false,"usgs":false,"family":"Nawaz","given":"Muhammad","email":"","middleInitial":"Ali","affiliations":[{"id":65003,"text":"Department of Biological and Environmental Sciences, Qatar University","active":true,"usgs":false}],"preferred":false,"id":859283,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239005,"text":"70239005 - 2022 - Volcano, earthquake, and tsunami hazards of the Cascadia Subduction Zone","interactions":[],"lastModifiedDate":"2022-12-20T14:12:08.240749","indexId":"70239005","displayToPublicDate":"2022-08-01T08:08:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1490,"text":"Elements","active":true,"publicationSubtype":{"id":10}},"title":"Volcano, earthquake, and tsunami hazards of the Cascadia Subduction Zone","docAbstract":"Subduction zones produce some of Earth’s most devastating geological events. Recent eruptions of Mount St. Helens and great earthquakes and tsunamis in Japan and Sumatra provide stark examples of the destructive power of subduction-related hazards. In the Cascadia subduction zone, large earthquakes, tsunamis, and volcanic eruptions have occurred in the past and geologic records imply that these events will occur in the future. As the population and infrastructure increase in the region, resilience to these natural hazards requires a detailed scientific understanding of the geologic forces and processes involved, combined with a society motivated to mitigate risks.
","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/gselements.18.4.251","usgsCitation":"Westby, E.G., Meigs, A.J., and Goldfinger, C., 2022, Volcano, earthquake, and tsunami hazards of the Cascadia Subduction Zone: Elements, v. 18, no. 4, p. 251-256, https://doi.org/10.2138/gselements.18.4.251.","productDescription":"6 p.","startPage":"251","endPage":"256","ipdsId":"IP-140163","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":410795,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Cascadia Subduction Zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.39974102578327,\n 48.661637439847425\n ],\n [\n -128.38903776575108,\n 48.661637439847425\n ],\n [\n -128.38903776575108,\n 38.3148639052869\n ],\n [\n -121.39974102578327,\n 38.3148639052869\n ],\n [\n -121.39974102578327,\n 48.661637439847425\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Westby, Elizabeth G. 0000-0003-3494-8353","orcid":"https://orcid.org/0000-0003-3494-8353","contributorId":214674,"corporation":false,"usgs":true,"family":"Westby","given":"Elizabeth","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":859663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meigs, Andrew J","contributorId":300037,"corporation":false,"usgs":false,"family":"Meigs","given":"Andrew","email":"","middleInitial":"J","affiliations":[{"id":65004,"text":"College of Earth, Ocean and Atmospheric Sciences Oregon State University","active":true,"usgs":false}],"preferred":false,"id":859664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldfinger, Chris","contributorId":195634,"corporation":false,"usgs":false,"family":"Goldfinger","given":"Chris","email":"","affiliations":[],"preferred":false,"id":859665,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70234354,"text":"70234354 - 2022 - Rural turtles: Estimating the occupancy of Northwestern Pond Turtles and non-native red-eared sliders in agricultural habitats in California's Sacramento Valley and Sacramento-San Joaquin River Delta","interactions":[],"lastModifiedDate":"2022-08-09T12:19:57.100101","indexId":"70234354","displayToPublicDate":"2022-08-01T07:16:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2901,"text":"Northwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Rural turtles: Estimating the occupancy of Northwestern Pond Turtles and non-native red-eared sliders in agricultural habitats in California's Sacramento Valley and Sacramento-San Joaquin River Delta","docAbstract":"The Northwestern Pond Turtle (Actinemys marmorata; WPT) was once widespread throughout the Sacramento Valley and the Sacramento-San Joaquin River Delta. Much of its historical range has been converted into agricultural land, reducing and altering aquatic habitat and surrounding uplands. Red-eared Sliders (Trachemys scripta elegans; RES) have been introduced throughout much of the existing WPT range, particularly near urban centers, potentially competing with WPT for resources. Previous surveys for turtles in central California have primarily focused on rivers, lakes, and protected wetlands. Little is known about where WPT and RES occur in the vast expanses of agricultural land across the Sacramento Valley and Sacramento-San Joaquin River Delta. Using aquatic hoop nets, we surveyed 142 locations (102 irrigation canal sites, 39 wetlands, 1 tidally influenced slough) across 8 counties during the summers of 2018 and 2019. Both species were detected in agricultural habitats. Using occupancy modeling, we estimated that WPT occur at 44 (95% CRI = 38–53) of our trapping sites and RES occur at 51 (41–66) sampled sites. Co-occurrence of these 2 species was rare; the species were found together at only 6 sites. RES were primarily found in restored wetlands near major roads and the Sacramento metropolitan area, whereas WPT were more commonly found farther from urban areas in wider canals. Our work provides a picture of how WPT and RES occupy this modified agroecosystem that can inform future conservation efforts.