System-wide survival of hatchery-reared Atlantic salmon (Salmo salar) smolts was evaluated (2017–2019) in the Penobscot River and compared to survival estimates from previous years that spanned major changes (2005–2016). This system was transformed through two dam removals in 2012 and construction of a nature-like passage structure at a third. The main stem had three dams (five prior to 2012), while the main tributary had four dams (one with the new nature-like passage). We estimated survival using acoustic telemetry mark–recapture (n = 1482) from 2017 to 2019. Six release sites and two release dates were included to assess system-wide survival. Survival from 2017 to 2019 was higher than previous years, with total cumulative survival > 0.75, independently of year and release sites, compared to survival < 0.5 in previous years. These years coincided with exceptional high flows not seen previously. We found an effect of delays on survival, longer delays associated with lower survival. Overall, survival in these years increased in all reaches relative to previous years except for one dam, Weldon Dam, which was a site of sustained high mortality.
","language":"English","publisher":"Canadian Scientific Publishing","doi":"10.1139/cjfas-2022-0055","usgsCitation":"Molina-Moctezuma, A., Stich, D., and Zydlewski, J.D., 2022, Effects of dam-induced delays on system-wide survival of Atlantic salmon smolts during high-flow, high-survival years in the Penobscot River, Maine, USA: Canadian Journal of Fisheries and Aquatic Sciences, v. 79, no. 12, p. 2237-2250, https://doi.org/10.1139/cjfas-2022-0055.","productDescription":"14 p.","startPage":"2237","endPage":"2250","ipdsId":"IP-129261","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Penobscot River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -68.3833,\n 45.5667\n ],\n [\n -69.4,\n 45.5667\n ],\n [\n -69.4,\n 44.5667\n ],\n [\n -68.3833,\n 44.5667\n ],\n [\n -68.3833,\n 45.5667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"79","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Molina-Moctezuma, Alejandro","contributorId":275649,"corporation":false,"usgs":false,"family":"Molina-Moctezuma","given":"Alejandro","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":926390,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stich, Daniel S.","contributorId":350601,"corporation":false,"usgs":false,"family":"Stich","given":"Daniel S.","affiliations":[{"id":33660,"text":"SUNY Oneonta","active":true,"usgs":false}],"preferred":false,"id":926391,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":926392,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238398,"text":"70238398 - 2022 - Apophis specific action team report","interactions":[],"lastModifiedDate":"2022-11-23T15:26:20.317426","indexId":"70238398","displayToPublicDate":"2022-11-11T09:24:09","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Apophis specific action team report","docAbstract":"This report about Asteroid (99942) Apophis's Earth close approach on April 13, 2029 was generated by a Specific Action Team (SAT) formed by the Small Body Assessment Group (SBAG) at the request of NASAs Planetary Science Division (PSD). The SAT assessed the current predictions for the effects that may occur due to the close encounter, evaluated observing capabilities, and identified possible investigations then sorted them into priority categories. In addition, the SAT evaluated whether or not a spacecraft sent to Apophis could increase the risk of a future Earth impact.
","language":"English","publisher":"Lunar Planetary Institute","usgsCitation":"Dotson, J.L., Brozovic, M., Chesley, S., Jarmak, S., Moskovitz, N., Rivkin, A., Sanchez, P., Souami, D., and Titus, T.N., 2022, Apophis specific action team report, 59 p.","productDescription":"59 p.","ipdsId":"IP-146012","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":409586,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":409492,"type":{"id":15,"text":"Index Page"},"url":"https://www.lpi.usra.edu/sbag/documents/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dotson, J. L.","contributorId":299232,"corporation":false,"usgs":false,"family":"Dotson","given":"J.","email":"","middleInitial":"L.","affiliations":[{"id":24796,"text":"NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":857378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brozovic, M.","contributorId":299233,"corporation":false,"usgs":false,"family":"Brozovic","given":"M.","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":857379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chesley, S.","contributorId":299235,"corporation":false,"usgs":false,"family":"Chesley","given":"S.","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":857380,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jarmak, S.","contributorId":299237,"corporation":false,"usgs":false,"family":"Jarmak","given":"S.","email":"","affiliations":[{"id":36712,"text":"Southwest Research Institute","active":true,"usgs":false}],"preferred":false,"id":857381,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moskovitz, N.","contributorId":299240,"corporation":false,"usgs":false,"family":"Moskovitz","given":"N.","affiliations":[{"id":33218,"text":"Lowell Observatory","active":true,"usgs":false}],"preferred":false,"id":857382,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rivkin, A.","contributorId":299243,"corporation":false,"usgs":false,"family":"Rivkin","given":"A.","email":"","affiliations":[{"id":64793,"text":"John Hopkins Applied Physics Laboratory","active":true,"usgs":false}],"preferred":false,"id":857383,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sanchez, P.","contributorId":299246,"corporation":false,"usgs":false,"family":"Sanchez","given":"P.","email":"","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":857384,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Souami, D.","contributorId":299249,"corporation":false,"usgs":false,"family":"Souami","given":"D.","email":"","affiliations":[{"id":64795,"text":"Observatoire de la Cˆote d’Azur, Nice, France","active":true,"usgs":false}],"preferred":false,"id":857385,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":857386,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70240241,"text":"70240241 - 2022 - Interaction between transect design and animal distribution in distance sampling of deer","interactions":[],"lastModifiedDate":"2023-02-02T13:21:55.250028","indexId":"70240241","displayToPublicDate":"2022-11-11T07:18:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Interaction between transect design and animal distribution in distance sampling of deer","docAbstract":"We conducted a simulation study to evaluate the consequences of violating statistical assumptions of distance sampling (DS) on the bias and precision of population estimates of white-tailed deer (Odocoileus virginianus). Distance sampling is a method for estimating the density of organisms using a distribution of observed distances to individuals. A key assumption of DS is that sampling transects are randomly located with respect to the population being sampled. Most DS transects used in National Parks follow roads and trails, which are not positioned randomly. We constructed spatially explicit simulations of surveys using 7 different types of deer spatial distributions and 3 survey designs. A significant interaction between survey type and deer distribution type explained most of the variation in population estimates across simulations and this interaction was also a significant predictor of the coefficient of variation (CV) of population estimates. Simulation results suggested that 1) non-road surveys were more robust to bias than were road surveys, 2) effectiveness of each of 3 survey types was dependent on the way deer were distributed across the landscape, and 3) non-road surveys produced unbiased estimates of populations affected by roads, whereas road surveys did not. The results of our study suggest that DS surveys using pre-existing roads and trails have potential biases resulting from study design, something that could be considered by land managers when constructing surveys.
In most birds, parental incubation of eggs is necessary for embryo development and survival. Using a combination of weekly nest visits, temperature dataloggers, infrared video cameras, and GPS tracking of hens, we documented several instances of duck eggs hatching after being abandoned by the incubating female. Of 2826 Mallard (Anas platyrhynchos) and Gadwall (Mareca strepera) nests monitored 2015–2019 in Suisun Marsh, California, 48 (1.7%) were abandoned during late incubation (≥ 20 days). Of these, we identified six (12.5%) where at least one egg hatched 2–9 days after abandonment. In all six cases, eggshell membranes were found in the nest (indicating hatch), and ducklings were observed at three nests. Abandoned nests were unattended for an average of 5.9 days before eggs hatched; during this time, mean nest temperatures (23.6°C–29.0°C) were substantially lower than before nest abandonment (31.7°C–36.4°C). We estimated that abandonment resulted in a 9% longer time period between clutch completion and hatch (0–4 days longer) and a lower rate of egg hatching success (36%). Our results provide evidence that some older embryos (≥ 20 days) in mild climates can survive without parental incubation for several days and continue to develop (at a reduced rate) to the point of successfully hatching.
Sea otters were extirpated throughout much of their range by the maritime fur trade in the 18th and 19th centuries, including the coast of Katmai National Park and Preserve in southcentral Alaska. Brown bears are an important component of the Katmai ecosystem where they are the focus of a thriving ecotourism bear-viewing industry as they forage in sedge meadows and dig clams in the extensive tidal flats that exist there. Sea otters began reoccupying Katmai in the 1970s where their use of intertidal clam resources overlapped that of brown bears. By 2008, the Katmai sea otter population had grown to an estimated 7,000 animals and was likely near carrying capacity; however, in 2006–2015, the age-at-death distribution (AADD) of sea otter carcasses collected at Katmai included a higher-than-expected proportion of prime-age animals compared to most other sea otter populations in Alaska. The unusual AADD warranted scientific investigation, particularly because the Katmai population is part of the Threatened southwest sea otter stock. Brown bears in Katmai are known to prey on marine mammals and sea otters, but depredation rates are unknown; thus, we investigated carnivore predation, especially by brown bears, as a potential explanation for abnormally high prime-age otter mortality. We installed camera traps at two island-based marine mammal haulout sites within Katmai to gather direct evidence that brown bears prey on seals and sea otters. Over a period of two summers, we gathered photo evidence of brown bears making 22 attempts to prey on sea otters of which nine (41%) were successful and 12 attempts to prey on harbor seals of which one (8%) was successful. We also developed a population model based on the AADD to determine if the living population is declining, as suggested by the high proportion of prime-age animals in the AADD. We found that the population trend predicted by the modeled AADDs was contradictory to aerial population surveys that indicated the population was not in steep decline but was consistent with otter predation. Future work should focus on the direct and indirect effects these top-level predators have on each other and the coastal community that connects them.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyac095","usgsCitation":"Monson, D., Taylor, R.L., Hilderbrand, G., Erlenbach, J., Coletti, H., and Bodkin, J.L., 2022, Brown bear–sea otter interactions along the Katmai coast: Terrestrial and nearshore communities linked by predation: Journal of Mammalogy, gyac095, 13 p., https://doi.org/10.1093/jmammal/gyac095.","productDescription":"gyac095, 13 p.","ipdsId":"IP-109601","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":445905,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyac095","text":"Publisher Index Page"},{"id":409348,"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","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.9563357076709,\n 59.34074602972433\n ],\n [\n -156.9563357076709,\n 57.706193986474744\n ],\n [\n -153.1440798482959,\n 57.706193986474744\n ],\n [\n -153.1440798482959,\n 59.34074602972433\n ],\n [\n -156.9563357076709,\n 59.34074602972433\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Monson, Daniel 0000-0002-4593-5673 dmonson@usgs.gov","orcid":"https://orcid.org/0000-0002-4593-5673","contributorId":196670,"corporation":false,"usgs":true,"family":"Monson","given":"Daniel","email":"dmonson@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":857010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":857011,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hilderbrand, Grant 0000-0002-0051-8315 ghilderbrand@usgs.gov","orcid":"https://orcid.org/0000-0002-0051-8315","contributorId":297939,"corporation":false,"usgs":false,"family":"Hilderbrand","given":"Grant","email":"ghilderbrand@usgs.gov","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":857012,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erlenbach, Joy","contributorId":200750,"corporation":false,"usgs":false,"family":"Erlenbach","given":"Joy","affiliations":[],"preferred":false,"id":857013,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coletti, Heather","contributorId":258849,"corporation":false,"usgs":false,"family":"Coletti","given":"Heather","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":857014,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bodkin, James L. 0000-0003-1641-4438 jbodkin@usgs.gov","orcid":"https://orcid.org/0000-0003-1641-4438","contributorId":748,"corporation":false,"usgs":true,"family":"Bodkin","given":"James","email":"jbodkin@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":857015,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256723,"text":"70256723 - 2022 - Reproductive success of Red-Billed Tropicbirds (Phaethon aethereus) on St. Eustatius, Caribbean Netherlands","interactions":[],"lastModifiedDate":"2024-08-15T11:12:13.575616","indexId":"70256723","displayToPublicDate":"2022-11-11T06:09:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Reproductive success of Red-Billed Tropicbirds (Phaethon aethereus) on St. Eustatius, Caribbean Netherlands","docAbstract":"The daily nest-survival rates of Red-billed Tropicbirds (Phaethon aethereus) were estimated over six breeding seasons on St. Eustatius in the Caribbean. We analyzed 338 nesting attempts between 2013 and 2020. The daily survival rate (DSR) of tropicbird nests was modeled as a function of nest initiation date, sea surface temperature (SST), elevation, vegetation in front of the nest, and year. Yearly nest survival rates (± SE) of the best fitting models ranged from 0.21 ± 0.06–0.74 ± 0.13 (n = 338 nests). DSR of the most parsimonious models averaged 0.39 ± 0.04 during the incubation period, 0.83 ± 0.05 during the chick-rearing period, and 0.30 ± 0.04 during the nesting period (incubation through fledging) when data were pooled across all years. Models with linear and quadratic trends of nest initiation date combined with SST and elevation received strong support in the incubation and nesting periods. Nests initiated in peak nesting season, when SSTs were lower, had higher DSR estimates than nests initiated early or late in the season. Compared to studies of the same species from Saba and the Gulf of California, survival probability on St. Eustatius was lower during the incubation stage but higher during the chick-rearing period. Similar to populations in the Gulf of California, tropicbird reproduction differed and laying date varied among years, and survival was influenced by SST. Our results are consistent with a study on White-tailed Tropicbirds (Phaethon lepturus) in Bermuda which found that survival was affected by temporal factors rather than physical site characteristics. Our study contributes to a better understanding of the factors that influence Red-billed Tropicbird survival on a small Caribbean island.
The research described in this report was conducted as part of the Natural Resource Damage Assessment and Restoration process in the Big River. Our purpose was to compare habitat features and landscape factors that may be important for the establishment and persistence of mussel concentrations between the Big River and the adjacent Bourbeuse and Meramec rivers, thereby testing their appropriateness as reference systems for establishing baseline expectations of mussel populations in the absence of mining impacts for the Big River. Based on these comparisons and a published model dileneating suitable habitat for freshwater mussels, we establish expected baseline conditions related to suitable freshwater mussel habitat in the Big River to assist injury determination for mining-related impacts in the Southeast Missouri Lead Mining District Natural Resource Damage Assessment case.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Rosenberger, A.E., and Lindner, G.A., 2022, Use of a riverscape-scale model of fundamental physical habitat requirements for freshwater mussels to quantify mussel declines in a mining-contaminated stream: The Big River, Old Lead Belt, Southeast Missouri: Cooperator Science Series FWS/CSS-147-2022, ii, 32 p.","productDescription":"ii, 32 p.","ipdsId":"IP-132994","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":431949,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/media/use-riverscape-scale-model-fundamental-physical-habitat-requirements-freshwater-mussels"},{"id":433629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Big River watershed, Bourbeuse River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.34550598548627,\n 38.669645646671654\n ],\n [\n -91.90534506180033,\n 38.65386249841083\n ],\n [\n -91.86155171390972,\n 37.44368900102869\n ],\n [\n -90.22760081808802,\n 37.470421694633586\n ],\n [\n -90.34550598548627,\n 38.669645646671654\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lindner, Garth A.","contributorId":201828,"corporation":false,"usgs":false,"family":"Lindner","given":"Garth","email":"","middleInitial":"A.","affiliations":[{"id":36266,"text":"University of Missouri Cooperative Research Unit","active":true,"usgs":false}],"preferred":false,"id":908323,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238114,"text":"sir20175022A - 2022 - Geologic field-trip guide to volcanism and its interaction with snow and ice at Mount Rainier, Washington","interactions":[{"subject":{"id":70238114,"text":"sir20175022A - 2022 - Geologic field-trip guide to volcanism and its interaction with snow and ice at Mount Rainier, Washington","indexId":"sir20175022A","publicationYear":"2022","noYear":false,"chapter":"A","displayTitle":"Geologic Field-Trip Guide to Volcanism and its Interaction with Snow and Ice at Mount Rainier, Washington","title":"Geologic field-trip guide to volcanism and its interaction with snow and ice at Mount Rainier, Washington"},"predicate":"IS_PART_OF","object":{"id":70188710,"text":"sir20175022 - 2017 - Field-trip guides to selected volcanoes and volcanic landscapes of the western United States","indexId":"sir20175022","publicationYear":"2017","noYear":false,"title":"Field-trip guides to selected volcanoes and volcanic landscapes of the western United States"},"id":1}],"isPartOf":{"id":70188710,"text":"sir20175022 - 2017 - Field-trip guides to selected volcanoes and volcanic landscapes of the western United States","indexId":"sir20175022","publicationYear":"2017","noYear":false,"title":"Field-trip guides to selected volcanoes and volcanic landscapes of the western United States"},"lastModifiedDate":"2026-04-01T15:37:52.320114","indexId":"sir20175022A","displayToPublicDate":"2022-11-10T08:55:32","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5022","chapter":"A","displayTitle":"Geologic Field-Trip Guide to Volcanism and its Interaction with Snow and Ice at Mount Rainier, Washington","title":"Geologic field-trip guide to volcanism and its interaction with snow and ice at Mount Rainier, Washington","docAbstract":"Mount Rainier is the Pacific Northwest’s iconic volcano. At 4,393 meters and situated in the south-central Cascade Range of Washington State, it towers over cities of the Puget Lowland. As the highest summit in the Cascade Range, Mount Rainier hosts 26 glaciers and numerous permanent snow fields covering 87 square kilometers and having a snow and ice volume of about 3.8 cubic kilometers. It remains by far the most heavily glacier-clad mountain in the conterminous United States despite having lost about 14 percent of its ice volume between 1970 and 2008.
Five major rivers head at Mount Rainier—the White, Carbon, Puyallup, Nisqually, and Cowlitz Rivers. Because Mount Rainier is situated west of the Cascade Range crest, all of these rivers eventually turn and drain westward. The Puget Lowland, situated west to northwest of Mount Rainier, is the Pacific Northwest’s most densely populated area, including Seattle, Tacoma, and Olympia. The Puget Lowland is now home to a population of more than 4.5 million and a vibrant economy.
Mount Rainier is one of the most hazardous volcanoes in the United States, not so much because of its explosivity, but rather because of its frequent eruptions, its propensity to produce voluminous far-traveled lahars, and its proximity to large population centers of the Puget Lowland. Steep-sided, glacially carved valleys serve as lahar conduits, and even mild eruptions commonly produced large lahars that traveled into areas now populated by hundreds of thousands of people.
This guide describes a five-day field trip to view the geology of Mount Rainier as it relates to volcanism and its interaction with snow and ice. Day 1 will focus on lahars in the White River valley. We will drive to Enumclaw, Washington, to begin the day then work our way back upvalley toward Mount Rainier. Day 2 concentrates on geology of the Sunrise-Glacier Basin area within Mount Rainier National Park. As part of day 2 activities, we will hike about 10 miles from Sunrise to the top of Burroughs Mountain, down into Glacier Basin, and be picked up at White River Campground. On day 3 we will pack up and move to Paradise, stopping to examine geology along Stevens Canyon Road. We will hike from Paradise along the Golden Gate Trail and eventually eastward to the former Paradise Ice Caves area (the ice caves have melted out). Day 4 involves hiking from Comet Falls trailhead to Mildred Point and return (~7 miles; 11 km), examining geology along the way. During the first half of day 5, we will visit sites on the south side of Mount Rainier to study lahar deposits, then return to the tour origin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175022A","usgsCitation":"Vallance, J.W., and Sisson, T.W., 2022, Geologic field-trip guide to volcanism and its interaction with snow and ice at Mount Rainier, Washington: U.S. Geological Survey Scientific Investigations Report 2017–5022–A, 76 p., https://doi.org/10.3133/sir20175022A.","productDescription":"xi, 76 p.","numberOfPages":"76","onlineOnly":"Y","ipdsId":"IP-098758","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":501941,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113827.htm","linkFileType":{"id":5,"text":"html"}},{"id":409296,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/a/sir20175022a.pdf","text":"Report","size":"45 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":409295,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5022/a/covrthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Rainier","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.71753266545278,\n 46.79677402550709\n ],\n [\n -121.65639469361994,\n 46.82263284533062\n ],\n [\n -121.65158608909377,\n 46.84659991518495\n ],\n [\n -121.66738578967957,\n 46.890746508867124\n ],\n [\n -121.72577598749758,\n 46.927351224979105\n ],\n [\n -121.79447033787142,\n 46.95033371096099\n ],\n [\n -121.82194807802095,\n 46.92828947873738\n ],\n [\n -121.82675668254714,\n 46.908113401053384\n ],\n [\n -121.8377477786071,\n 46.890746508867124\n ],\n [\n -121.854234422697,\n 46.852237672335264\n ],\n [\n -121.84324332663707,\n 46.82780311745222\n ],\n [\n -121.80546143393136,\n 46.798655086153445\n ],\n [\n -121.74913206662472,\n 46.78830843882821\n ],\n [\n -121.71753266545278,\n 46.79677402550709\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Volcano Science Center
Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court
Vancouver, WA, 98683
Offshore wind energy development (OWED) is rapidly expanding globally and has the potential to contribute significantly to renewable energy portfolios. However, development of infrastructure in the marine environment presents risks to wildlife. Marine birds in particular have life history traits that amplify population impacts from displacement and collision with offshore wind infrastructure. Here, we present a broadly applicable framework to assess and mitigate the impacts of OWED on marine birds. We outline existing techniques to quantify impact via monitoring and modeling (e.g., collision risk models, population viability analysis), and present a robust mitigation framework to avoid, minimize, or compensate for OWED impacts. Our framework addresses impacts within the context of multiple stressors across multiple wind energy developments. We also present technological and methodological approaches that can improve impact estimation and mitigation. We highlight compensatory mitigation as a tool that can be incorporated into regulatory frameworks to mitigate impacts that cannot be avoided or minimized via siting decisions or alterations to OWED infrastructure or operation. Our framework is intended as a globally-relevant approach for assessing and mitigating OWED impacts on marine birds that may be adapted to existing regulatory frameworks in regions with existing or planned OWED.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2022.109795","usgsCitation":"Croll, D.A., Ellis, A.A., Adams, J., Cook, A.S., Garthe, S., Wing Goodale, M., Hall, C.S., Hazen, E.L., Keitt, B.S., Kelsey, E.C., Leirness, J.B., Lyons, D.E., McKown, M., Potiek, A., Searle, K.R., Soudjin, F.H., Rockwood, R.C., Tershy, B.R., Tinker, M., Vanderwerf, E.A., Williams, K.A., Young, L.C., and Zilliacus, K., 2022, Framework for assessing and mitigating the impacts of offshore wind energy development on marine birds: Biological Conservation, v. 276, 109795, 15 p., https://doi.org/10.1016/j.biocon.2022.109795.","productDescription":"109795, 15 p.","ipdsId":"IP-142666","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445913,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2022.109795","text":"Publisher Index Page"},{"id":409690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"276","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Croll, Donald A","contributorId":299391,"corporation":false,"usgs":false,"family":"Croll","given":"Donald","email":"","middleInitial":"A","affiliations":[{"id":64830,"text":"UC Santa Cruz, Ocean Health Building, 115 McAllister Way, Santa Cruz, CA 95060, United States","active":true,"usgs":false}],"preferred":false,"id":857691,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellis, Aspen A","contributorId":299392,"corporation":false,"usgs":false,"family":"Ellis","given":"Aspen","email":"","middleInitial":"A","affiliations":[{"id":64830,"text":"UC Santa Cruz, Ocean Health Building, 115 McAllister Way, Santa Cruz, CA 95060, United States","active":true,"usgs":false}],"preferred":false,"id":857692,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Josh 0000-0003-3056-925X","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":213442,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857693,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, Aonghais S. C. P.","contributorId":299393,"corporation":false,"usgs":false,"family":"Cook","given":"Aonghais","email":"","middleInitial":"S. C. P.","affiliations":[{"id":64832,"text":"British Trust for Ornithology, The Nunnery, Thetford, Norfolk IP26 4BG, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":857694,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garthe, Stefan","contributorId":243464,"corporation":false,"usgs":false,"family":"Garthe","given":"Stefan","affiliations":[],"preferred":false,"id":857695,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wing Goodale, Morgan","contributorId":299394,"corporation":false,"usgs":false,"family":"Wing Goodale","given":"Morgan","email":"","affiliations":[{"id":64834,"text":"Biodiversity Research Institute, 276 Canco Road, Portland, ME 04103, United States","active":true,"usgs":false}],"preferred":false,"id":857696,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hall, C. Scott","contributorId":299395,"corporation":false,"usgs":false,"family":"Hall","given":"C.","email":"","middleInitial":"Scott","affiliations":[{"id":64835,"text":"National Fish and Wildlife Foundation, 1133 15thSt. N.W., Suite 1000, Washington, DC 20005, United States","active":true,"usgs":false}],"preferred":false,"id":857697,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hazen, Elliott L.","contributorId":217590,"corporation":false,"usgs":false,"family":"Hazen","given":"Elliott","email":"","middleInitial":"L.","affiliations":[{"id":39677,"text":"National Marine Fisheries Service, National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":857698,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Keitt, Bradford S.","contributorId":299396,"corporation":false,"usgs":false,"family":"Keitt","given":"Bradford","email":"","middleInitial":"S.","affiliations":[{"id":64836,"text":"American Bird Conservancy, Santa Cruz, CA, United States","active":true,"usgs":false}],"preferred":false,"id":857699,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kelsey, Emily C. 0000-0002-0107-3530 ekelsey@usgs.gov","orcid":"https://orcid.org/0000-0002-0107-3530","contributorId":206505,"corporation":false,"usgs":true,"family":"Kelsey","given":"Emily","email":"ekelsey@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857700,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Leirness, Jeffery B","contributorId":299397,"corporation":false,"usgs":false,"family":"Leirness","given":"Jeffery","email":"","middleInitial":"B","affiliations":[{"id":64837,"text":"CSS Inc., 2750 Prosperity Avenue, Suite 220, Fairfax, VA 22031, United States","active":true,"usgs":false}],"preferred":false,"id":857701,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lyons, Don E","contributorId":299398,"corporation":false,"usgs":false,"family":"Lyons","given":"Don","email":"","middleInitial":"E","affiliations":[{"id":64838,"text":"Audubon Seabird Institute, National Audubon Society, 12 Audubon Road, Bremen, ME 04551, United States","active":true,"usgs":false}],"preferred":false,"id":857702,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McKown, Matthew W.","contributorId":298878,"corporation":false,"usgs":false,"family":"McKown","given":"Matthew W.","affiliations":[{"id":64717,"text":"Conservation Metrics, Inc., Santa Cruz, CA, USA","active":true,"usgs":false}],"preferred":false,"id":857703,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Potiek, Astrid","contributorId":299399,"corporation":false,"usgs":false,"family":"Potiek","given":"Astrid","email":"","affiliations":[{"id":64839,"text":"Waardenburg Ecology, Varkensmarkt 9, 4101 CK Culemborg, the Netherlands","active":true,"usgs":false}],"preferred":false,"id":857704,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Searle, Kate R","contributorId":299400,"corporation":false,"usgs":false,"family":"Searle","given":"Kate","email":"","middleInitial":"R","affiliations":[{"id":64840,"text":"UK Centre for Ecology & Hydrology, Bush Estate, Penicuik EH26 0QB, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":857705,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Soudjin, Floor H.","contributorId":299401,"corporation":false,"usgs":false,"family":"Soudjin","given":"Floor","email":"","middleInitial":"H.","affiliations":[{"id":64841,"text":"Ecological Dynamics Group, Wageningen Marine Research, 1976 CP Ijmuiden, the Netherlands","active":true,"usgs":false}],"preferred":false,"id":857706,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Rockwood, R. Cotton","contributorId":299402,"corporation":false,"usgs":false,"family":"Rockwood","given":"R.","email":"","middleInitial":"Cotton","affiliations":[{"id":64842,"text":"Point Blue Conservation Science, 3820 Cypress Drive, Suite 11, Petaluma, CA 94954, United States","active":true,"usgs":false}],"preferred":false,"id":857707,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Tershy, Bernie R.","contributorId":299403,"corporation":false,"usgs":false,"family":"Tershy","given":"Bernie","email":"","middleInitial":"R.","affiliations":[{"id":64830,"text":"UC Santa Cruz, Ocean Health Building, 115 McAllister Way, Santa Cruz, CA 95060, United States","active":true,"usgs":false}],"preferred":false,"id":857708,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Tinker, Martin","contributorId":299404,"corporation":false,"usgs":false,"family":"Tinker","given":"Martin","email":"","affiliations":[{"id":64843,"text":"Nhydra Ecological, Head of St Margarets Bay, Nova Scotia, Canada","active":true,"usgs":false}],"preferred":false,"id":857709,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Vanderwerf, Eric A.","contributorId":104689,"corporation":false,"usgs":false,"family":"Vanderwerf","given":"Eric","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":857710,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Williams, Kathryn A","contributorId":299405,"corporation":false,"usgs":false,"family":"Williams","given":"Kathryn","email":"","middleInitial":"A","affiliations":[{"id":64834,"text":"Biodiversity Research Institute, 276 Canco Road, Portland, ME 04103, United States","active":true,"usgs":false}],"preferred":false,"id":857711,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Young, Lindsay C.","contributorId":149044,"corporation":false,"usgs":false,"family":"Young","given":"Lindsay","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":857712,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Zilliacus, Kelly","contributorId":299406,"corporation":false,"usgs":false,"family":"Zilliacus","given":"Kelly","email":"","affiliations":[{"id":64830,"text":"UC Santa Cruz, Ocean Health Building, 115 McAllister Way, Santa Cruz, CA 95060, United States","active":true,"usgs":false}],"preferred":false,"id":857713,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70231792,"text":"70231792 - 2022 - Trends in vegetation and height of the topographic surface in a tidal freshwater swamp experiencing rooting zone saltwater intrusion","interactions":[],"lastModifiedDate":"2022-12-02T14:03:31.584539","indexId":"70231792","displayToPublicDate":"2022-11-10T07:56:42","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Trends in vegetation and height of the topographic surface in a tidal freshwater swamp experiencing rooting zone saltwater intrusion","docAbstract":"A decrease in the ground surface height of coastal wetlands is of worldwide concern because of its relationship to peat loss, coastal carbon, and biodiversity in freshwater wetlands. We asked if it is possible to determine indicators of impending transitions of freshwater swamps to other coastal types by examining long-term changes in the environment and vegetation. In a tidal Taxodium distichum swamp in Hickory Point State Forest, Maryland, the topographic surface height (ground surface height) decreased by as much as 25.6 ± 2.2 to 50.8 ± 3.8 cm at two Surface Elevation Tables from 2015 to 2021 following salinity intrusion events related to hurricanes and offshore storms (e.g., Hurricane Melissa). In 2019, rooting zone salinity exceeded 5 ppt for >24.9 % of the time, with a maximum salinity level of 12.5 ppt. Tree growth of T. distichum trees declined and 60 % of these trees died along a 4 m wide × 125 m transect in 2014–2016. Root biomass and ground surface height decreased roughly in conjunction with a salinity pulse in the rooting zone during Hurricane Melissa in 2019. Saplings survived but T. distichum seedlings were uncommon and did not survive in the study area. Typha × glauca increased in cover (0.2 to 5.6 % cover plot−1) from 2014 to 2016 so a vegetation shift toward T. × glauca was apparent by 2021. This work captures a multi-year trend of decreasing ground surface height, tree growth and health, and freshwater status in the rooting zone that may be an indicator of impending vegetation transition.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.109637","usgsCitation":"Middleton, B., and David, J.L., 2022, Trends in vegetation and height of the topographic surface in a tidal freshwater swamp experiencing rooting zone saltwater intrusion: Ecological Applications, v. 145, 109637, 11 p., https://doi.org/10.1016/j.ecolind.2022.109637.","productDescription":"109637, 11 p.","ipdsId":"IP-126845","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":489206,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2022.109637","text":"Publisher Index Page"},{"id":435623,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99LLMXQ","text":"USGS data release","linkHelpText":"Peat collapse and vegetation shift at Hickory Point"},{"id":435622,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UITS3D","text":"USGS data release","linkHelpText":"Data Release: Peat collapse and vegetation shift after storm-driven saltwater surge in a tidal freshwater swamp, Taxodium distichum growth"},{"id":435621,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V1N524","text":"USGS data release","linkHelpText":"Data Release: Peat collapse and vegetation shift after storm-driven saltwater surge in a tidal freshwater swamp, tree height and density 2021"},{"id":435620,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JDOY24","text":"USGS data release","linkHelpText":"Data Release: Peat collapse and vegetation shift after storm-driven saltwater surge in a tidal freshwater swamp, CTD Diver data"},{"id":435619,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P997WSVS","text":"USGS data release","linkHelpText":"Data Release: Peat collapse and vegetation shift after storm-driven saltwater surge in a tidal freshwater swamp, vegetation"},{"id":435618,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O3U8A9","text":"USGS data release","linkHelpText":"Data Release: Peat collapse and vegetation shift after storm-driven saltwater surge in a tidal freshwater swamp, roots"},{"id":435617,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P928FLVR","text":"USGS data release","linkHelpText":"Data Release: Peat collapse and vegetation shift after storm-driven saltwater surge in a tidal freshwater swamp, SET"},{"id":409994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Hickory Point State Forest, Pocomoke River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.59867363122336,\n 38.06239155638218\n ],\n [\n -75.66797775370112,\n 38.06239155638218\n ],\n [\n -75.66797775370112,\n 38.00946004126109\n ],\n [\n -75.59867363122336,\n 38.00946004126109\n ],\n [\n -75.59867363122336,\n 38.06239155638218\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"145","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":206922,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":843840,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"David, John L. 0000-0002-9254-5299","orcid":"https://orcid.org/0000-0002-9254-5299","contributorId":299294,"corporation":false,"usgs":false,"family":"David","given":"John","email":"","middleInitial":"L.","affiliations":[{"id":37174,"text":"Volunteer","active":true,"usgs":false}],"preferred":false,"id":858229,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238049,"text":"sir20225102 - 2022 - Effect of uncertainty of discharge data on uncertainty of discharge simulation for the Lake Michigan Diversion, northeastern Illinois and northwestern Indiana","interactions":[],"lastModifiedDate":"2022-11-11T17:47:08.905958","indexId":"sir20225102","displayToPublicDate":"2022-11-10T07:15:06","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5102","displayTitle":"Effect of Uncertainty of Discharge Data on Uncertainty of Discharge Simulation for the Lake Michigan Diversion, Northeastern Illinois and Northwestern Indiana","title":"Effect of uncertainty of discharge data on uncertainty of discharge simulation for the Lake Michigan Diversion, northeastern Illinois and northwestern Indiana","docAbstract":"Simulation models of watershed hydrology (also referred to as “rainfall-runoff models”) are calibrated to the best available streamflow data, which are typically published discharge time series at the outlet of the watershed. Even after calibration, the model generally cannot replicate the published discharges because of simplifications of the physical system embedded in the model structure and uncertainties of the input data and of the estimated model parameters, which, although optimized for the given calibration data, remain uncertain. The input data errors are caused by uncertainties in the forcing data, such as precipitation and other climatological data, and in the published discharges used for calibration. In the numerical algorithms used for calibration, the published discharges are often assumed to be without error, but they are themselves uncertain, typically having been computed using ratings, which are models fitted to uncertain discharge measurements.
In this study, uncertainty of published daily discharge data and how the discharge uncertainty is transmitted to the parameter values of the Hydrological Simulation Program–FORTRAN (HSPF) rainfall-runoff model and to the simulated discharge at both calibration and prediction locations were investigated for the Lake Michigan diversion in northeastern Illinois and northwestern Indiana. The HSPF model used in this study is used by the U.S. Army Corps of Engineers as part of quantifying the diversion of water from Lake Michigan by the State of Illinois. In this study, the model is calibrated jointly at two watersheds in the study area; the resulting model is considered the base model in this study. Seven other gaged watersheds in the study area are used for testing predictive simulations. A Bayesian rating curve estimation (BaRatin) approach, the BaRatin stage-period-discharge (SPD) method, was used to estimate the uncertainty of the published discharge from the calibration watersheds. To characterize the effect of the discharge uncertainty on parameter values, the HSPF model parameters were recalibrated to 17 nonrandomly selected pairs of discharge series from the BaRatin SPD analysis. To provide an indicator of the effect of parameter uncertainty to compare to the effect of discharge uncertainty, 1,000 parameter sets also were randomly generated from the estimated parameter covariance matrix of the base model. The recalibrated and random parameter sets were then used in HSPF simulations of discharge at the two calibration watersheds and at the seven prediction watersheds. Selected discharge summary statistics—the period-of-study (POS, water years 1997 to 2015) mean discharge, selected flow-duration curve (FDC) quantiles, and water year mean discharges—are used to characterize the variability between simulated and published discharge.
A normalized variability index (VN) is used as a measure of the uncertainty of flow statistics arising from the uncertainty of the sources considered in this study. When this index is at least 1, the variability of the simulations is large enough to explain the median error between simulated and published values, although offsetting errors from other sources are also likely. When the index is appreciably less than 1, the variability of the simulations is clearly insufficient to explain the median error between simulated and published values. At the two calibration watersheds and for results of the two simulation sets considered together, the VN values ranged from 0.2 to 0.8 for POS mean discharge, from 0.3 to 0.6 in the median for a set of FDC quantiles, and from 0.1 to 0.2 in the median for water year mean discharges. These values indicate that substantial uncertainty remains unexplained. Even though two watersheds were used in calibration, that calibration was highly constrained because it was applied to the watersheds simultaneously and was subject to parameter regularization that constrained the adjustment of the parameters from their initial values. These constraints were applied to avoid overfitting to the calibration watersheds and thus to increase the likelihood that the resulting parameters would give accurate results at watersheds not used in the calibration, but they created a parameter transfer error in the calibration watershed results shown by the balancing of errors between the two watersheds. Additional remaining error sources include model structural error and meteorological forcing error to the degree that the calibration was unable to adjust the parameters to account for these errors. At the prediction watersheds, the corresponding VN values were almost always substantially lower than those values at the calibration watersheds. This result is expected because the prediction watersheds have additional uncertainty, including parameter transfer error.
The work described in this report provides preliminary estimates of a limited range of sources of error in predicted discharge uncertainty. Future work would be beneficial to obtain a better statistical characterization of the effect of the uncertainty of calibration discharge series and to address additional sources of uncertainty, such as from precipitation input data used in calibration and prediction and from structural (model) errors.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225102","collaboration":"Prepared in cooperation with U.S. Army Corps of Engineers, Chicago District","usgsCitation":"Soong, D.T., and Over, T.M., 2022, Effect of uncertainty of discharge data on uncertainty of discharge simulation for the Lake Michigan Diversion, northeastern Illinois and northwestern Indiana: U.S. Geological Survey Scientific Investigations Report 2022–5102, 54 p., https://doi.org/10.3133/sir20225102.","productDescription":"Report: ix, 54 p.; 2 Data releases; Dataset","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-120412","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":409202,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97S2IID","text":"USGS data release","linkHelpText":"National Land Cover Database (NLCD) 2011 Land Cover Conterminous United States"},{"id":409201,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UC21B0","text":"USGS data release","linkHelpText":"Models, inputs, and outputs for estimating the uncertainty of discharge simulations for the Lake Michigan Diversion using the Hydrological Simulation Program – FORTRAN model"},{"id":409196,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5102/coverthb.jpg"},{"id":409197,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5102/sir20225102.pdf","text":"Report","size":"8.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5102"},{"id":409198,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5102/sir20225102.XML"},{"id":409199,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5102/images"},{"id":409200,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"}],"country":"United States","state":"Illinois, Indiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.34881814497747,\n 42.492126793048925\n ],\n [\n -88.34881814497747,\n 41.20266079763215\n ],\n [\n -87.22772634687415,\n 41.20266079763215\n ],\n [\n -87.22772634687415,\n 42.492126793048925\n ],\n [\n -88.34881814497747,\n 42.492126793048925\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
Swarms are bursts of earthquakes without an obvious mainshock. Some have been observed to be associated with transient aseismic fault slip, while others are thought to be related to fluids. However, the association is rarely quantitative due to insufficient data quality. We use high-quality GPS/GNSS, InSAR, and relocated seismicity to study a swarm of >2,000 earthquakes which occurred between 30 September and 6 October 2020, near Westmorland, California. Using 5 min sampled Global Positioning System (GPS) supplemented with InSAR, we document a spontaneous shallow Mw 5.2 slow slip event that preceded the swarm by 2–15 hr. The earthquakes in the early phase were predominantly non-interacting and driven primarily by the slow slip event resulting in a nonlinear expansion. A stress-driven model based on the rate-and-state friction successfully explains the overall spatial and temporal evolution of earthquakes, including the time lag between the onset of the slow slip event and the swarm. Later, a distinct back front and a square root of time expansion of clustered seismicity on en-echelon fault structures suggest that fluids helped sustain the swarm. Static stress triggering analysis using Coulomb stress and statistics of interevent times suggest that 45%–65% of seismicity was driven by the slow slip event, 10%–35% by inter-earthquake interactions, and 10%–30% by fluids. Our model also provides constraints on the friction parameter and the pore pressure and suggests that this swarm behaved like an aftershock sequence but with the mainshock replaced by the slow slip event.
Billions of people living in poverty are at risk of environmentally mediated infectious diseases—that is, pathogens with environmental reservoirs that affect disease persistence and control and where environmental control of pathogens can reduce human risk. The complex ecology of these diseases creates a global health problem not easily solved with medical treatment alone.
We quantified the current global disease burden caused by environmentally mediated infectious diseases and used a structural equation model to explore environmental and socioeconomic factors associated with the human burden of environmentally mediated pathogens across all countries.
We found that around 80% (455 of 560) of WHO-tracked pathogen species known to infect humans are environmentally mediated, causing about 40% (129 488 of 359 341 disability-adjusted life years) of contemporary infectious disease burden (global loss of 130 million years of healthy life annually). The majority of this environmentally mediated disease burden occurs in tropical countries, and the poorest countries carry the highest burdens across all latitudes. We found weak associations between disease burden and biodiversity or agricultural land use at the global scale. In contrast, the proportion of people with rural poor livelihoods in a country was a strong proximate indicator of environmentally mediated infectious disease burden. Political stability and wealth were associated with improved sanitation, better health care, and lower proportions of rural poverty, indirectly resulting in lower burdens of environmentally mediated infections. Rarely, environmentally mediated pathogens can evolve into global pandemics (eg, HIV, COVID-19) affecting even the wealthiest communities.
The high and uneven burden of environmentally mediated infections highlights the need for innovative social and ecological interventions to complement biomedical advances in the pursuit of global health and sustainability goals.
Bill & Melinda Gates Foundation, National Institutes of Health, National Science Foundation, Alfred P. Sloan Foundation, National Institute for Mathematical and Biological Synthesis, Stanford University, and the US Defense Advanced Research Projects Agency.
Invasive marine species are well documented but options to manage them are limited. At Palmyra Atoll National Wildlife Refuge (Central North Pacific), native invasive corallimorpharians, Rhodactis howesii, have smothered live native corals since 2007. Laboratory and field trials were conducted evaluating two control methods to remove R. howesii overgrowing the benthos at Palmyra Atoll (Palmyra): 1) paste mixed with chlorine, citric acid, or sodium hydroxide (NaOH), and 2) hot water. Paste mixed with NaOH had the most efficacious kill in mesocosm trials and resulted in > 90% kill over a 98 m² area three days after treatment. Hot water at 82°C was most effective in mesocosms; in the field hot water was less effective than paste but still resulted in a kill of ca. 75% over 100 m² three days after treatment. Costs of paste and heat (excluding capital equipment and costs of regulatory approval should this method be deployed large scale) were $70/m² and $59/m² respectively. Invasive R. howesii currently occupy ca 5,800,000 m² of reef at Palmyra with ca. 276,000 m² comprising heavily infested areas. Several potential management strategies are discussed based on costs of treatment, area covered, and the biology of the invasion. The methods described here expand the set of tools available to manage invasive species in complex marine habitats.
","language":"English","publisher":"REABIC","doi":"10.3391/mbi.2022.13.4.02","usgsCitation":"Work, T.M., Breeden, R., Rameyer, R., Born, V., Clark, T., Rainal, J., Gillies, C., Rose, J., Wegmann, A., and Kropidlowski, S., 2022, Invasive corallimorpharians at Palmyra Atoll National Wildlife Refuge are no match for lye and heat: Management of Biological Invasions, v. 13, no. 4, p. 609-630, https://doi.org/10.3391/mbi.2022.13.4.02.","productDescription":"22 p.","startPage":"609","endPage":"630","ipdsId":"IP-142696","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":445923,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2022.13.4.02","text":"Publisher Index Page"},{"id":435624,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QF4XDF","text":"USGS data release","linkHelpText":"Data on invasive corallimorphs Palmyra"},{"id":409416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Palmyra Atoll National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.11434364318848,\n 5.865525058703975\n ],\n [\n -162.04078674316406,\n 5.865525058703975\n ],\n [\n -162.04078674316406,\n 5.896261485744235\n ],\n [\n -162.11434364318848,\n 5.896261485744235\n ],\n [\n -162.11434364318848,\n 5.865525058703975\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Work, Thierry M. 0000-0002-4426-9090 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Alex","contributorId":299151,"corporation":false,"usgs":false,"family":"Wegmann","given":"Alex","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":857182,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kropidlowski, Stefan","contributorId":299153,"corporation":false,"usgs":false,"family":"Kropidlowski","given":"Stefan","affiliations":[{"id":25470,"text":"U.S. Fish & Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":857183,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70238101,"text":"ofr20221099 - 2022 - Growth, survival, and cohort formation of juvenile Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2020 monitoring report","interactions":[],"lastModifiedDate":"2022-12-08T18:08:44.657985","indexId":"ofr20221099","displayToPublicDate":"2022-11-09T14:46:26","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1099","displayTitle":"Growth, Survival, and Cohort Formation of Juvenile Lost River (Deltistes luxatus) and Shortnose Suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2020 Monitoring Report","title":"Growth, survival, and cohort formation of juvenile Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2020 monitoring report","docAbstract":"Populations of federally endangered Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir (hereinafter, Clear Lake), California, are experiencing long-term decreases in abundance. Upper Klamath Lake populations are decreasing not only because of adult mortality, which is relatively low, but also because they are not being balanced by recruitment of young adult suckers into known adult spawning aggregations.
Long-term monitoring of juvenile sucker populations is conducted to (1) determine if there are annual and species-specific differences in production, survival, and growth, (2) better understand when juvenile sucker mortality is greatest, and (3) help identify potential causes of high juvenile sucker mortality particularly in Upper Klamath Lake. The U.S. Geological Survey (USGS) monitoring program, begun in 2015, tracks cohorts through summer months and among years in Upper Klamath and Clear Lakes. Data on juvenile suckers captured in trap nets are used to provide information on annual variability in age-0 sucker apparent production, juvenile sucker apparent survival, apparent growth, species composition, and health.
Upper Klamath Lake indices of year-class strength suggest that the 2020 age-0 cohort is one of the lowest since standardized monitoring began. Despite apparently low over-winter survival, the relatively large 2019 cohort persisted in our 2020 samples and continues to contribute to the populations. Although the 2019 cohort age-0 suckers were composed mainly of Lost River suckers, the age-1 suckers from the 2019 cohort were mainly shortnose suckers. Lost River suckers comprised the largest proportion of the 2020 year-class and were only captured in July and August. Shortnose suckers were mainly captured in August and September and comprised a smaller proportion of the 2020 year-class.
Age distribution of suckers captured in Clear Lake indicates greater juvenile survival than in Upper Klamath Lake. Most juvenile suckers captured were age-3 and age-4 suckers classified as the combination of Klamath largescale suckers (Catostomus snyderi) and shortnose suckers from the Lost River Basin, from the 2016 and 2017 cohorts. A lack of age-0 suckers captured in Clear Lake during years with the low inflow or lake levels initially lead us to believe that low water prevented spawning and year class formation. However, recent data indicate that some cohorts that were not captured as age-0 suckers were detected in later years at age-1 or age-2. This finding indicates that juvenile suckers in Clear Lake may spend one or more years in the tributaries or that sampling efficacy for age-0 suckers varies among years because of water depth.
The first 5 years of this monitoring program indicated different patterns in recruitment and survival of juvenile suckers between Upper Klamath and Clear Lakes. Since the monitoring program began in 2015, age-0 sucker catch rates, interpreted as indices of year-class strength, were greatest in Upper Klamath Lake in 2016 and 2019. In those years Lost River suckers made up the majority of age-0 sucker catches; however, in 2017 and 2020 the age-1 sucker catches from these cohorts were mainly composed of shortnose suckers or suckers with genetic markers of both Klamath largescale and shortnose suckers, indicating a low overwinter survival for Lost River suckers even when the age-0 catches were high. Age-0 suckers do not fully recruit to our sampling gear in Upper Klamath Lake until August, experience high mortality by September, and are almost undetectable by the following July or August in most years. In Clear Lake, suckers frequently are not captured until age-1 or age-2 and annual survival appears much greater.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221099","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Martin, B.A., Kelsey, C.M., Burdick, S.M., and Bart, R.J., 2022, Growth, survival, and cohort formation of juvenile Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2020 monitoring report: U.S. Geological Survey Open-File Report 2022–1099, 27 p., https://doi.org/10.3133/ofr20221099.","productDescription":"vi, 27 p.","onlineOnly":"Y","ipdsId":"IP-141866","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":409276,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221099/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1099"},{"id":409274,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1099/coverthb.jpg"},{"id":409278,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1099/ofr20221099.XML"},{"id":409277,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1099/images"},{"id":409275,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1099/ofr20221099.pdf","text":"Report","size":"2.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1099"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Upper Klamath Lake, Clear Lake Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.23841270893135,\n 42.66770378348696\n ],\n [\n -122.23841270893135,\n 41.77275507129002\n ],\n [\n -121.00794395893129,\n 41.77275507129002\n ],\n [\n -121.00794395893129,\n 42.66770378348696\n ],\n [\n -122.23841270893135,\n 42.66770378348696\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Director, North Central Climate Adaptation Science Center
U.S. Geological Survey
University of Colorado - Boulder
Sustainability, Energy and Environment Community
4001 Discovery Dr., Suite 348
Boulder, CO 80303
No abstract available.
","language":"English","publisher":"Columbia Basin Research, School of Aquatic and Fishery Sciences, University of Washington","usgsCitation":"Kelley, J.R., Whitlock, S., Buchanan, R., and Perry, R., 2022, Resource guide and literature review for addressing the problem of tag predation in salmonid studies in the Central Valley of California, 40 p.","productDescription":"40 p.","ipdsId":"IP-142677","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":427217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":411416,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbr.washington.edu/analysis/apps/tagpredation"}],"country":"United States","state":"California","otherGeospatial":"Central Valley, Sacramento River, San Joaquin River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.07407209452549,\n 37.03003597568832\n ],\n [\n -120.20599440615521,\n 37.73368625903554\n ],\n [\n -121.60886401142395,\n 39.703614189808775\n ],\n [\n -122.56466653379951,\n 39.242668117453576\n ],\n [\n -121.07407209452549,\n 37.03003597568832\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kelley, Jacob Ryan 0000-0002-0316-679X","orcid":"https://orcid.org/0000-0002-0316-679X","contributorId":300600,"corporation":false,"usgs":true,"family":"Kelley","given":"Jacob","email":"","middleInitial":"Ryan","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":860906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whitlock, Steven L.","contributorId":267708,"corporation":false,"usgs":false,"family":"Whitlock","given":"Steven L.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":860907,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buchanan, Rebecca A.","contributorId":300601,"corporation":false,"usgs":false,"family":"Buchanan","given":"Rebecca A.","affiliations":[{"id":65208,"text":"Columbia Basin Research, School of Aquatic and Fishery Sciences, University of Washington 1325 Fourth Avenue, Suite 1515, Seattle, Washington 98101-2540","active":true,"usgs":false}],"preferred":false,"id":860908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perry, Russell 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":220189,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":860909,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70236074,"text":"70236074 - 2022 - Assessing global geologic carbon dioxide storage resources","interactions":[],"lastModifiedDate":"2023-04-26T14:49:25.005136","indexId":"70236074","displayToPublicDate":"2022-11-09T09:43:50","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Assessing global geologic carbon dioxide storage resources","docAbstract":"The U.S. Geological Survey (USGS), in conjunction with the U.S. Department of Energy (U.S. DOE) Office of Fossil Energy and Carbon Management (FECM), the IEA Greenhouse Gas R&D Programme (IEAGHG), and the Clean Energy Ministerial Carbon Capture, Utilization and Storage Initiative (CEM-CCUS Initiative), plans to work with partner nations to assess geologic carbon dioxide (CO2) storage resources globally. The goal of this work is to help countries, particularly those with emerging economies, understand the mass of CO2 they could potentially store in geologic units within their borders. Knowledge of the CO2 storage resources in their geologic units can provide countries pathways for reducing emissions to meet their future climate mitigation goals.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 16th Greenhouse Gas Control Technologies Conference (GHGT-16)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"16th Greenhouse Gas Control Technologies Conference","conferenceDate":"Oct 23-27, 2022","conferenceLocation":"Lyon, France","language":"English","publisher":"GHGT","doi":"10.2139/ssrn.4271675","usgsCitation":"Brennan, S., Warwick, P., Karimjee, A., Wong, A.Y., Dixon, T., Craig, J., and Lipponen, J., 2022, Assessing global geologic carbon dioxide storage resources, in Proceedings of the 16th Greenhouse Gas Control Technologies Conference (GHGT-16), Lyon, France, Oct 23-27, 2022, 6 p., https://doi.org/10.2139/ssrn.4271675.","productDescription":"6 p.","ipdsId":"IP-144166","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":494439,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2139/ssrn.4271675","text":"Publisher Index Page"},{"id":416380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brennan, Sean T. 0000-0002-7102-9359","orcid":"https://orcid.org/0000-0002-7102-9359","contributorId":204982,"corporation":false,"usgs":true,"family":"Brennan","given":"Sean T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":849936,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warwick, Peter D. 0000-0002-3152-7783","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":207248,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":849937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karimjee, Anhar","contributorId":295752,"corporation":false,"usgs":false,"family":"Karimjee","given":"Anhar","email":"","affiliations":[],"preferred":false,"id":849938,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wong, Adam Y.","contributorId":295753,"corporation":false,"usgs":false,"family":"Wong","given":"Adam","email":"","middleInitial":"Y.","affiliations":[],"preferred":false,"id":849939,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dixon, Timothy","contributorId":191178,"corporation":false,"usgs":false,"family":"Dixon","given":"Timothy","email":"","affiliations":[],"preferred":false,"id":849940,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Craig, James","contributorId":295756,"corporation":false,"usgs":false,"family":"Craig","given":"James","affiliations":[],"preferred":false,"id":849941,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lipponen, Juho","contributorId":295758,"corporation":false,"usgs":false,"family":"Lipponen","given":"Juho","email":"","affiliations":[],"preferred":false,"id":849942,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70241491,"text":"70241491 - 2022 - High dispersal rates in hybrids drive expansion of maladaptive hybridization","interactions":[],"lastModifiedDate":"2023-03-22T13:52:04.753564","indexId":"70241491","displayToPublicDate":"2022-11-09T08:40:07","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3173,"text":"Proceedings of the Royal Society B","active":true,"publicationSubtype":{"id":10}},"title":"High dispersal rates in hybrids drive expansion of maladaptive hybridization","docAbstract":"Hybridization between native and invasive species, a major cause of biodiversity loss, can spread rapidly even when hybrids have reduced fitness. This paradox suggests that hybrids have greater dispersal rates than non-hybridized individuals, yet this mechanism has not been empirically tested in animal populations. Here, we test if non-native genetic introgression increases reproductive dispersal using a human-mediated hybrid zone between native cutthroat trout (Oncorhynchus clarkii) and invasive rainbow trout (Oncorhynchus mykiss) in a large and connected river system. We quantified the propensity for individuals to migrate from natal rearing habitats (migrate), reproduce in non-natal habitats (stray), and the joint probability of dispersal as a function of genetic ancestry. Hybrid trout with predominantly non-native rainbow trout ancestry were more likely to migrate as juveniles and to stray as adults. Overall, hybrids with greater than 50% rainbow trout ancestry were 5.7 times more likely to disperse than native or hybrid trout with small amounts of rainbow trout ancestry. Our results show a genetic basis for increased dispersal in hybrids that is likely contributing to the rapid expansion of invasive hybridization between these species. Management actions that decrease the probability of hybrid dispersal may mitigate the harmful effects of invasive hybridization on native biodiversity.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rspb.2022.1813","usgsCitation":"Bourret, S., Kovach, R., Cline, T.J., Strait, J., and Muhlfeld, C.C., 2022, High dispersal rates in hybrids drive expansion of maladaptive hybridization: Proceedings of the Royal Society B, v. 289, 20221813, 7 p., https://doi.org/10.1098/rspb.2022.1813.","productDescription":"20221813, 7 p.","ipdsId":"IP-142129","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":445927,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9653238","text":"External Repository"},{"id":414548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Abbot Creek, Upper Flathead River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.06071873441293,\n 48.42865807789937\n ],\n [\n -114.06071873441293,\n 48.38447026195061\n ],\n [\n -113.89518022172545,\n 48.38447026195061\n ],\n [\n -113.89518022172545,\n 48.42865807789937\n ],\n [\n -114.06071873441293,\n 48.42865807789937\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"289","noUsgsAuthors":false,"publicationDate":"2022-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Bourret, Samuel 0000-0002-8521-1020","orcid":"https://orcid.org/0000-0002-8521-1020","contributorId":290597,"corporation":false,"usgs":false,"family":"Bourret","given":"Samuel","email":"","affiliations":[{"id":52338,"text":"Montana Fish, Wildlife & Parks","active":true,"usgs":false}],"preferred":false,"id":867011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kovach, Ryan P.","contributorId":126724,"corporation":false,"usgs":false,"family":"Kovach","given":"Ryan P.","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":867012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cline, Timothy Joseph 0000-0002-4955-654X","orcid":"https://orcid.org/0000-0002-4955-654X","contributorId":228871,"corporation":false,"usgs":true,"family":"Cline","given":"Timothy","email":"","middleInitial":"Joseph","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":867013,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Strait, Jeffrey 0000-0002-0901-3911","orcid":"https://orcid.org/0000-0002-0901-3911","contributorId":260879,"corporation":false,"usgs":false,"family":"Strait","given":"Jeffrey","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":867014,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":867015,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70238108,"text":"70238108 - 2022 - Tough places and safe spaces: Can refuges save salmon from a warming climate?","interactions":[],"lastModifiedDate":"2022-11-10T13:30:41.807133","indexId":"70238108","displayToPublicDate":"2022-11-09T07:28:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Tough places and safe spaces: Can refuges save salmon from a warming climate?","docAbstract":"The importance of thermal refuges in a rapidly warming world is particularly evident for migratory species, where individuals encounter a wide range of conditions throughout their lives. In this study, we used a spatially explicit, individual-based simulation model to evaluate the buffering potential of cold-water thermal refuges for anadromous salmon and trout (Oncorhynchus spp.) migrating upstream through a warm river corridor that can expose individuals to physiologically stressful temperatures. We considered upstream migration in relation to migratory phenotypes that were defined in terms of migration timing, spawn timing, swim speed, and use of cold-water thermal refuges. Individuals with different migratory phenotypes migrated upstream through riverine corridors with variable availability of cold-water thermal refuges and mainstem temperatures. Use of cold-water refuges (CWRs) decreased accumulated sublethal exposures to physiologically stressful temperatures when measured in degree-days above 20, 21, and 22°C. The availability of CWRs was an order of magnitude more effective in lowering accumulated sublethal exposures under current and future mainstem temperatures for summer steelhead than fall Chinook Salmon. We considered two emergent model outcomes, survival and percent of available energy used, in relation to thermal heterogeneity and migratory phenotype. Mean percent energy loss attributed to future warmer mainstem temperatures was at least two times larger than the difference in energy used in simulations without CWRs for steelhead and salmon. We also found that loss of CWRs reduced the diversity of energy-conserving migratory phenotypes when we examined the variability in entry timing and travel time outside of CWRs in relation to energy loss. Energy-conserving phenotypic space contracted by 7%–23% when CWRs were unavailable under the current thermal regime. Our simulations suggest that, while CWRs do not entirely mitigate for stressful thermal exposures in mainstem rivers, these features are important for maintaining a diversity of migration phenotypes. Our study suggests that the maintenance of diverse portfolios of migratory phenotypes and cool- and cold-water refuges might be added to the suite of policies and management actions presently being deployed to improve the likelihood of Pacific salmonid persistence into a future characterized by climate change.
The Big Lost River Basin, located in parts of Butte and Custer Counties in south-central Idaho, supports the communities surrounding the cities of Arco, Leslie, Mackay, and Moore and provides for agricultural resources that depend on a sustainable supply of surface water from the Big Lost River and its tributaries and groundwater from an unconfined aquifer. The aquifer, situated in a structurally controlled intermontane valley, is composed of unconsolidated alluvium, consolidated sedimentary and volcanic rocks, and younger interbedded volcanic rocks.
This report presents two separate groundwater budgets for the aquifer, one above and one below Mackay Dam, as well as a combined groundwater budget for the aquifer within the entire Big Lost River Basin. The budgets span a 20-year period (2000–19), characterizing average conditions, a dry year (2014), and a wet year (2017). The groundwater budgets will help address questions regarding the availability of groundwater supply in the Big Lost River Basin and inform future groundwater modeling. The Idaho Geological Survey has prepared the groundwater budgets as part of a larger hydrogeologic investigation completed by the U.S. Geological Survey and the Idaho Geological Survey in cooperation with the Idaho Department of Water Resources during 2018–21. Other reports describe the hydrogeologic framework and several streamflow-measurement events to evaluate gains and losses on the Big Lost River. Collectively, these reports provide an updated characterization of groundwater resources in the Big Lost River Basin which will help address water resources challenges.
A groundwater budget is a conceptual and numerical accounting of inflow (recharge) to groundwater and outflow (discharge) from groundwater. The predominant sources of recharge to the aquifer include losing river reaches (33 percent), areal recharge (as precipitation less evapotranspiration and surface runoff, comprising about 23 percent of the total inflow), tributary canyon underflow from higher altitudes (20 percent), canal seepage (13 percent), recharge through applied irrigation on fields below the root zone and other minor sources (11 percent), and Mackay Reservoir seepage (less than 1 percent). The primary sources of discharge from the aquifer are groundwater pumpage to meet irrigation demand, domestic supply, and municipal supply (76 percent) and gaining river reaches (24 percent).
The positive or negative difference between the sum of all inflows and outflows is regarded as the residual, representing the change in groundwater storage, groundwater outflow from the basin or subbasins, and uncertainty and errors in the budget. In the Big Lost River Basin, groundwater outflow is at the mouth of the basin below Arco into the eastern Snake River Plain aquifer.
The total mean annual estimated recharge to the Big Lost River Basin was 439,100 acre-feet per year (acre-ft/yr; 607 cubic feet per second [ft3/s]) for 2000–19, 373,900 acre-ft/yr (516 ft3/s) in 2014, and 762,100 acre-ft/yr (1,053 ft3/s) in 2017. The mean annual estimated groundwater discharge from the aquifer was about 112,300 acre-ft/yr (155 ft3/s) for 2000–19, 153,500 acre-ft/yr (212 ft3/s) in 2014, and 53,400 acre-ft/yr (74 ft3/s) in 2017. The estimated mean annual groundwater residual was 326,800 acre-ft/yr (451 ft3/s) for 2000–19, 220,400 acre-ft/yr (304 ft3/s) in 2014, and 708,700 acre-ft/yr (979 ft3/s) in 2017. The mean annual residual above Mackay Dam was 100,400 acre-ft/yr (2000-19), 96,700 acre-ft (2014), and 248,300 acre-ft (2017). The mean annual residual contribution below Mackay Dam, minus any groundwater-flow above Mackay Dam, was 226,400 acre-ft/yr (2000-19), 123,700 acre-ft (2014), and 460,400 acre-ft (2017).
These results are highly sensitive to assumptions about certain budget inflow parameters. In particular, the magnitude of the budget residuals during especially dry and wet periods is amplified by the groundwater-budget terms tributary streamflow and tributary underflow that contribute appreciable recharge but also have high uncertainty.
The results of the groundwater-budget evaluation describe an interconnected and complex hydrologic response throughout the basin to various climatic and water-use trends. The part of the basin above Mackay Dam typically has a positive groundwater residual derived from snowmelt recharge to tributary canyons and areal recharge in excess of groundwater pumpage for irrigation demand. This supply is used to meet irrigation demand above Mackay Dam and to provide for water supply below Mackay Dam. On average, groundwater inflow from above Mackay Dam to below Mackay Dam, assuming negligible reservoir storage effects, accounts for about 25 percent of the total groundwater recharge below Mackay Dam. Considerable recharge to groundwater below Mackay Dam occurs through seepage from the Big Lost River and canals and ditches. Most groundwater discharge from the aquifer is through irrigation pumping. The water supply below Mackay Dam is highly dependent on available upstream surface-water flows, the magnitude of the groundwater residual from above Mackay Dam, and annual variability in local groundwater conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215078C","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Clark, A., 2022, Groundwater budgets for the Big Lost River Basin, south-central Idaho, 2000–19, chap. C of Zinsser, L.M., ed., Characterization of water resources in the Big Lost River Basin, south-central Idaho: U.S. Geological Survey Scientific Investigations Report 2021–5078–C, 111 p., https://doi.org/10.3133/sir20215078C.","productDescription":"xi, 111 p.","ipdsId":"IP-125226","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":409232,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5078/c/coverthb.jpg"},{"id":409233,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5078/c/sir20215078C.pdf","text":"Reports","size":"6.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5078-C"},{"id":409235,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5078/c/images"},{"id":409236,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5078/c/sir20215078C.XML"},{"id":502105,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113824.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Idaho","otherGeospatial":"Big Lost River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.1863738631967,\n 43.10571945845362\n ],\n [\n -113.42308735779262,\n 43.54649028685452\n ],\n [\n -112.13258233834704,\n 44.22138739870667\n ],\n [\n -112.23487846793722,\n 44.737914300373745\n ],\n [\n -114.26506595862107,\n 46.10751185031063\n ],\n [\n -115.75229430420214,\n 46.493497990156555\n ],\n [\n -117.884775159506,\n 45.476547804668826\n ],\n [\n -117.57788677073549,\n 45.01671717637413\n ],\n [\n -116.38967788087962,\n 44.5307302025393\n ],\n [\n -115.2014689910242,\n 43.60919623765622\n ],\n [\n -114.1863738631967,\n 43.10571945845362\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director , Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520
The Powder River Basin (PRB) is a world-class oil province, in large part thanks to contributions from premier source rocks, Cretaceous Mowry and Niobrara shales. Both formations are also unconventional reservoirs. A critical aspect of evaluating production potential and finding sweet spots is the nature of the pore systems in these fine-grained source-rock reservoirs. Variation by stratigraphic interval is important for selecting optimum target zones for horizontal wells. Understanding variation in pore type, size, and connectivity and relationships with mineralogy and fabric help in determining prospectivity in different parts of the basin. Deciphering controls on pore-system development helps predict intervals and locations of optimum reservoir quality.
Imaging of Niobrara and Mowry samples from a range of thermal maturities provided observations and data on pore systems, organic matter (OM) types and associations with mineralogy and fabric, wettability, and microporosity associated with both diagenetic and detrital clays. Imaging techniques included scanning electron microscopy, organic petrography and correlative scanning electron microscopy, and mapping of mineralogy through energy dispersive spectroscopy.
Mean solid bitumen (BRo) and vitrinite reflectance (VRo) values indicate all samples are in the oil window with values ranging from 0.52 to 1.15%. Organic fluorescence is prominent in amorphous OM, solid bitumen and some vitrinite in the early oil window. The fluorescence is extinguished at higher thermal maturity. Carbonate pellets (in Niobrara) mainly contain migrated solid bitumen and residual live oil and little or no terrigenous OM (vitrinite and inertinite). However, terrigenous OM is common in siliceous/argillaceous laminae in both formations, where it occurs with amorphous OM, some of which has converted in situ to a solid bitumen petroleum residue.
One key finding is the widespread presence of migrated OM at very early oil window maturity. Distribution of such OM and associated wettability alteration is fabric-controlled, at all levels of thermal maturity studied. Clay morphology and abundance and supporting rigid mineral grain framework strongly influence pore development, preservation, and connectivity in both formations. Carbonate content is a good proxy for reservoir quality in Niobrara intervals due to association of porous solid bitumen with calcareous fecal pellets. High recrystallized microquartz content is associated with the best reservoir intervals in the Mowry.
","language":"English","publisher":"Elsesvier","doi":"10.1016/j.coal.2022.104134","usgsCitation":"Olson, T., Michalchuk, B., Hackley, P.C., Valentine, B.J., Parker, J., and San Martin, R., 2022, Pore systems and organic petrology of cretaceous Mowry and Niobrara source-rock reservoirs, Powder River Basin, Wyoming, USA: International Journal of Coal Geology, v. 264, 104134, 13 p., https://doi.org/10.1016/j.coal.2022.104134.","productDescription":"104134, 13 p.","ipdsId":"IP-142426","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":418454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Powder River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.22939078183438,\n 45.01127679602621\n ],\n [\n -106.22939078183438,\n 42.73172365239171\n ],\n [\n -104.01110426262045,\n 42.73172365239171\n ],\n [\n -104.01110426262045,\n 45.01127679602621\n ],\n [\n -106.22939078183438,\n 45.01127679602621\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"264","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Olson, Terri","contributorId":312451,"corporation":false,"usgs":false,"family":"Olson","given":"Terri","email":"","affiliations":[{"id":67672,"text":"Digital Rock Petrophysics LLC","active":true,"usgs":false}],"preferred":false,"id":876154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Michalchuk, Brad","contributorId":312452,"corporation":false,"usgs":false,"family":"Michalchuk","given":"Brad","email":"","affiliations":[{"id":67673,"text":"Anschutz Exploration and Production","active":true,"usgs":false}],"preferred":false,"id":876155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":876156,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valentine, Brett J. 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":3846,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":876157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parker, Jason","contributorId":312453,"corporation":false,"usgs":false,"family":"Parker","given":"Jason","email":"","affiliations":[{"id":67675,"text":"FIB-X","active":true,"usgs":false}],"preferred":false,"id":876158,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"San Martin, Ricardo","contributorId":312454,"corporation":false,"usgs":false,"family":"San Martin","given":"Ricardo","email":"","affiliations":[{"id":67675,"text":"FIB-X","active":true,"usgs":false}],"preferred":false,"id":876159,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70238130,"text":"70238130 - 2022 - Flyway-scale GPS tracking reveals migratory routes and key stopover and non-breeding locations of lesser yellowlegs","interactions":[],"lastModifiedDate":"2022-11-14T12:22:44.856742","indexId":"70238130","displayToPublicDate":"2022-11-09T06:12:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12820,"text":"Ecology and Evolution: Nature Notes","active":true,"publicationSubtype":{"id":10}},"title":"Flyway-scale GPS tracking reveals migratory routes and key stopover and non-breeding locations of lesser yellowlegs","docAbstract":"Many populations of long-distance migrant shorebirds are declining rapidly. Since the 1970s, the lesser yellowlegs (Tringa flavipes) has experienced a pronounced reduction in abundance of ~63%. The potential causes of the species' decline are complex and interrelated. Understanding the timing of migration, seasonal routes, and important stopover and non-breeding locations used by this species will aid in directing conservation planning to address potential threats. During 2018–2022, we tracked 118 adult lesser yellowlegs using GPS satellite tags deployed on birds from five breeding and two migratory stopover locations spanning the boreal forest of North America from Alaska to Eastern Canada. Our objectives were to identify migratory routes, quantify migratory connectivity, and describe key stopover and non-breeding locations. We also evaluated predictors of southbound migratory departure date and migration distance. Individuals tagged in Alaska and Central Canada followed similar southbound migratory routes, stopping to refuel in the Prairie Pothole Region of North America, whereas birds tagged in Eastern Canada completed multi-day transoceanic flights covering distances of >4000 km across the Atlantic between North and South America. Upon reaching their non-breeding locations, lesser yellowlegs populations overlapped, resulting in weak migratory connectivity. Sex and population origin were significantly associated with the timing of migratory departure from breeding locations, and body mass at the time of GPS-tag deployment was the best predictor of southbound migratory distance. Our findings suggest that lesser yellowlegs travel long distances and traverse numerous political boundaries each year, and breeding location likely has the greatest influence on migratory routes and therefore the threats birds experience during migration. Further, the species' dependence on wetlands in agricultural landscapes during migration and the non-breeding period may make them vulnerable to threats related to agricultural practices, such as pesticide exposure.