Understanding patterns of genetic structure and adaptive variation in natural populations is crucial for informing conservation and management. Past genetic research using 11 microsatellite loci identified six genetic stocks of lake whitefish (Coregonus clupeaformis) within Lake Michigan, USA. However, ambiguity in genetic stock assignments suggested those neutral microsatellite markers did not provide adequate power for delineating lake whitefish stocks in this system, prompting calls for a genomics approach to investigate stock structure. Here, we generated a dense genomic dataset to characterize population structure and investigate patterns of neutral and adaptive genetic diversity among lake whitefish populations in Lake Michigan. Using Rapture sequencing, we genotyped 829 individuals collected from 17 baseline populations at 197,588 SNP markers after quality filtering. Although the overall pattern of genetic structure was similar to the previous microsatellite study, our genomic data provided several novel insights. Our results indicated a large genetic break between the northwestern and eastern sides of Lake Michigan, and we found a much greater level of population structure on the eastern side compared to the northwestern side. Collectively, we observed five genomic islands of adaptive divergence on five different chromosomes. Each island displayed a different pattern of population structure, suggesting that combinations of genotypes at these adaptive regions are facilitating local adaptation to spatially heterogenous selection pressures. Additionally, we identified a large linkage disequilibrium block of ~8.5 Mb on chromosome 20 that is suggestive of a putative inversion but with a low frequency of the minor haplotype. Our study provides a comprehensive assessment of population structure and adaptive variation that can help inform the management of Lake Michigan's lake whitefish fishery and highlights the utility of incorporating adaptive loci into fisheries management.
","language":"English","publisher":"Wiley","doi":"10.1111/eva.13475","usgsCitation":"Shi, Y., Homola, J.J., Euclide, P., Isermann, D.A., Caroffino, D., and McPhee, M., 2022, High-density genomic data reveal fine-scale population structure and pronounced islands of adaptive divergence in lake whitefish (Coregonus clupeaformis) from Lake Michigan: Evolutionary Applications, v. 15, no. 11, p. 1776-1791, https://doi.org/10.1111/eva.13475.","productDescription":"16 p.","startPage":"1776","endPage":"1791","ipdsId":"IP-137991","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481072,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.13475","text":"Publisher Index Page"},{"id":480916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Wisconsin","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.55725950240699,\n 45.37753522596927\n ],\n [\n -87.39148683074085,\n 44.817230157751304\n ],\n [\n -88.03397794894306,\n 42.98217615918885\n ],\n [\n -87.66163831918826,\n 42.48489493230767\n ],\n [\n -86.3437295978575,\n 42.617675976389194\n ],\n [\n -86.40170815429047,\n 43.587414879850954\n ],\n [\n -84.89518851103124,\n 46.04290477047883\n ],\n [\n -86.20220438971735,\n 46.00276060146369\n ],\n [\n -87.55725950240699,\n 45.37753522596927\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-09-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Shi, Yue","contributorId":349037,"corporation":false,"usgs":false,"family":"Shi","given":"Yue","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":923948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Homola, Jared Joseph 0000-0003-3821-7224","orcid":"https://orcid.org/0000-0003-3821-7224","contributorId":303741,"corporation":false,"usgs":true,"family":"Homola","given":"Jared","email":"","middleInitial":"Joseph","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Euclide, Peter T.","contributorId":349039,"corporation":false,"usgs":false,"family":"Euclide","given":"Peter T.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":923950,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923951,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caroffino, David C.","contributorId":349042,"corporation":false,"usgs":false,"family":"Caroffino","given":"David C.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923952,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McPhee, Megan V.","contributorId":349044,"corporation":false,"usgs":false,"family":"McPhee","given":"Megan V.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":923953,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"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
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":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","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.
Hiking and backpacking on American National Scenic Trails has increased in popularity in recent years. To encourage responsible and sustainable outdoor recreation on these much-loved trails, direct and indirect management strategies must be employed by managerial agencies. The Leave No Trace (LNT) education program aims to protect natural resources by promoting minimum-impact behaviours that lessen environmental impacts. The accidental introduction and dispersal of non-native invasive flora by hikers is little studied but can have a detrimental environmental impact on protected areas. The purpose of our study was to understand whether Appalachian Trail thru-hikers are: 1) aware of this problem, 2) adhering to LNT principles to reduce this problem, and 3) willing to learn and adopt minimum-impact behaviours to address this problem. We found that thru-hiker knowledge of invasive plants was limited and that very few thru-hikers adopted low-impact practices to minimise plant introduction and spread. Promisingly, we found that most thru-hikers, once aware of the problems, were willing to learn and apply low-impact practices to minimise plant introduction and spread. We discuss the barriers to their adoption of these behaviours and present a comprehensive list of suggested LNT practices to limit invasive plant introduction and spread. We conclude that, whilst challenging, protected area managers can help deter the spread of invasive plants along trails by improving educational messaging, signage, personal communication, and providing supporting infrastructure that encourages visitors to adopt specific practices to minimise invasive plant introduction and spread within protected areas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jort.2022.100581","usgsCitation":"Dolman, M., and Marion, J.L., 2022, Invasive plant hitchhikers: Appalachian Trail thru-hiker knowledge and attitudes of invasive plants and Leave No Trace practices: Journal of Outdoor Recreation and Tourism, v. 40, 100581, 12 p., https://doi.org/10.1016/j.jort.2022.100581.","productDescription":"100581, 12 p.","ipdsId":"IP-132845","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":410278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia, West Virginia","otherGeospatial":"Appalachian Trail","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.663426481162,\n 39.327334819713826\n ],\n [\n -77.84650013772489,\n 39.352244826545075\n ],\n [\n -80.24694411951128,\n 37.65331631118197\n ],\n [\n -80.62871457673847,\n 37.33610604928302\n ],\n [\n -81.72490463550588,\n 36.63467327613432\n ],\n [\n -80.86786667184651,\n 36.60267551794206\n ],\n [\n -79.06482033698572,\n 37.834500309643815\n ],\n [\n -77.64378265768026,\n 39.08720414992473\n ],\n [\n -77.663426481162,\n 39.327334819713826\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dolman, Megan","contributorId":298242,"corporation":false,"usgs":false,"family":"Dolman","given":"Megan","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":858566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marion, Jeffrey L. 0000-0003-2226-689X jeff_marion@usgs.gov","orcid":"https://orcid.org/0000-0003-2226-689X","contributorId":3614,"corporation":false,"usgs":true,"family":"Marion","given":"Jeffrey","email":"jeff_marion@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":858567,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238678,"text":"70238678 - 2022 - Geologic map of the Mount Blue Sky (formerly Mount Evans) quadrangle, Clear Creek and Park Counties, Colorado","interactions":[],"lastModifiedDate":"2024-12-12T19:04:46.137756","indexId":"70238678","displayToPublicDate":"2022-11-01T11:37:18","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":128,"text":"Open-File Report","active":false,"publicationSubtype":{"id":2}},"seriesNumber":"OF-22-11","title":"Geologic map of the Mount Blue Sky (formerly Mount Evans) quadrangle, Clear Creek and Park Counties, Colorado","docAbstract":"The Mount Blue Sky (formerly Mount Evans) 7.5’ quadrangle lies in Park and Clear Creek counties, Colorado, about 60 km west of Denver. The highest elevation in the quadrangle is 14,265 ft (4,348 m) at the top of Mount Blue Sky. The lowest is at about 9,200 ft (2,804 m) on Guanella Pass Road at the southern edge of the quadrangle. Bedrock directly underlies most of the map area, with surficial deposits primarily in the valleys. The geology of the quadrangle was previously mapped at 1:100,000 scale as part of a regional compilation by Kellogg and others (2008). The oldest rocks in the Mount Blue Sky 7.5-minute quadrangle are Paleoproterozoic metasedimentary rocks, and mafic to felsic metaigneous rocks (all units starting with ‘X’ on Plate 1). These rocks were metamorphosed under upper amphibolite facies conditions and intruded by Mesoproterozoic felsic igneous rocks of the ~1442 Ma Mount Blue Sky (YgR, Yt, Ygdm, Ymgm and ~1424 Ma Silver Plume (Yg) batholiths (Spurr and others, 1908; Tweto, 1897; Aleinikoff and others, 1993; du Bray and others, 2018) and, in the southern part of the quadrangle, by rocks that may also be part of the Mount Blue Sky batholith, but may alternatively interpreted as part of the ~1115 Ma to ~1066 Ma Pikes Peak batholith (Unruh and others, 1995; Guitreau and others, 2016). Four generations of folds affected the area. The oldest, F1 folds are isoclinal of various orientations, but primarily northerly-plunging in the southern part of the quadrangle (Mahatma, 2019; Mahatma and others, 2022). In the northern part of the quadrangle (Powell, 2020), open to close F2 chevron folds exist with various orientations. F3 folds in the northern part of the quadrangle are open to close with upright axial planes and plunges to the north and south, and in the southern part of the quadrangle they are open centimeter- to meter- scale northerly-plunging folds, possibly overprinted by another generation of northerly-plunging folds based on orientations of axial planes (F2 and F3 of Mahatma and others, 2022). F4 folds throughout the quadrangle are open to gentle with upright axial planes and shallow plunges to the east and west. The Mount Blue Sky batholith displays a pervasive moderately NW-dipping biotite-hornblende foliation (Fig. 1) in addition to a flow foliation near the margins, indicating NW-directed shortening after ~1442 Ma (Powell, 2020). The relationship between this foliation and the folds is not clear. Various joint sets are present in the area. The most pervasive joint set strikes 355°-020° and is subvertical. It is best developed in the western to southwestern part of the map area, and may be related to late Cenozoic extension associated with the Rio Grande Rift. Joint orientations are generally consistent with the trends of topographical lineaments. Surficial deposits include two series of glacial till deposits (Qtb and Qtp), and outwash (Qgp) deposits. They correlate with the Bull Lake (170-120 ka) and Pinedale (30-12 ka) glacial periods (Dahms, 2004) based on original depositional morphology, geomorphic and topographic position, deposit weathering and pedogenic properties. Possible older glacial deposits (Qti) have been observed along topographically higher surfaces.
","language":"English","publisher":"Colorado Geological Survey","usgsCitation":"Powell, L., Mahatma, A.A., Kuiper, Y., and Ruleman, C.A., 2022, Geologic map of the Mount Blue Sky (formerly Mount Evans) quadrangle, Clear Creek and Park Counties, Colorado: Open-File Report OF-22-11, 2 Plates: 33.00 x 31.50 inches and 41.00 x 31.00 inches: Data Files.","productDescription":"2 Plates: 33.00 x 31.50 inches and 41.00 x 31.00 inches: Data Files","ipdsId":"IP-139573","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":413293,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":413292,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://coloradogeologicalsurvey.org/publications/geologic-map-mount-evans-quadrangle-clear-creek-park-colorado/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","otherGeospatial":"Mount Evans quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.75,\n 39.625\n ],\n [\n -105.75,\n 39.5\n ],\n [\n -105.625,\n 39.5\n ],\n [\n -105.625,\n 39.625\n ],\n [\n -105.75,\n 39.625\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Powell, Logan 0000-0002-0528-3092 ljpowell@usgs.gov","orcid":"https://orcid.org/0000-0002-0528-3092","contributorId":299647,"corporation":false,"usgs":false,"family":"Powell","given":"Logan","email":"ljpowell@usgs.gov","affiliations":[{"id":64912,"text":"Colorado School of Mines MS Graduate","active":true,"usgs":false}],"preferred":false,"id":858245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahatma, Asha A.","contributorId":299648,"corporation":false,"usgs":false,"family":"Mahatma","given":"Asha","email":"","middleInitial":"A.","affiliations":[{"id":64913,"text":"Colorado School of Mines PhD Graduate","active":true,"usgs":false}],"preferred":false,"id":858246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuiper, Yvette 0000-0002-8506-8180","orcid":"https://orcid.org/0000-0002-8506-8180","contributorId":299649,"corporation":false,"usgs":false,"family":"Kuiper","given":"Yvette","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":858247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":858248,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70238109,"text":"70238109 - 2022 - Know what you don't know: Embracing state uncertainty in disease-structured multistate models","interactions":[],"lastModifiedDate":"2022-12-15T15:44:51.910487","indexId":"70238109","displayToPublicDate":"2022-10-31T07:27:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Know what you don't know: Embracing state uncertainty in disease-structured multistate models","docAbstract":"The bedrock geology of the 7.5-minute Crown Point quadrangle consists of deformed and metamorphosed Mesoproterozoic gneisses of the Adirondack Highlands unconformably overlain by weakly deformed lower Paleozoic sedimentary rocks of the Champlain Valley. The Mesoproterozoic rocks occur on the eastern edge of the Adirondack Highlands and represent an extension of the Grenville Province of Laurentia. Granulite facies Mesoproterozoic paragneiss, marble, and amphibolite hosted the emplacement of granitic orthogneiss at approximately 1.18–1.15 giga-annum (Ga, billion years before present). The earliest of four phases of deformation (D1) is characterized by gneissosity, rarely preserved F1 isoclinal folds, and migmatite in the host rocks. Subsequent D2 deformation produced a composite penetrative gneissosity, migmatite, and isoclinal F2 folds. Towards the end of D2, felsic magmatism (including the regionally extensive Lyon Mountain Granite Gneiss, abbreviated “LMG”) spread by penetrative migration as semiconcordant alkali feldspar granite sheets subparallel to S2 into previously deformed lithologies. The LMG crystallized at approximately 1.15 Ga and displays synkinematic F2 folds thus constraining the time of D2 deformation. Exhumation during D3 produced F3 folds exhibited in regional domes and basins, such as the Keeney Mountain synform, local reactivation of the S2 foliation, partial melting, metamorphism, metasomatism, iron ore remobilization, and intrusion of magnetite-bearing pegmatite both as layer-parallel sills and crosscutting dikes. D4 created NE- and NW-trending boudinage, local high-grade ductile shear zones, and crosscutting granitic pegmatite dikes. Kilometer (km)-scale lineaments readily observed in lidar data are Ediacaran mafic dikes and Phanerozoic brittle faults. The Paleozoic rocks are part of the Early Cambrian to Late Ordovician great American carbonate bank on the ancient margin of Laurentia. Cambrian-Ordovician stratigraphy records an approximately 1-km-thick section and a transition from synrift clastics to passive margin peritidal carbonate buildups to gradually deeper water subtidal to shelf carbonates during foreland basin development associated with the Taconic orogeny. The Paleozoic rocks are weakly folded and block faulted. Large areas of the Champlain Valley are covered by undifferentiated glacial deposits, some of which contain mapped landslides. The map also shows waste rock piles and tailings from historical mining operations and large areas of artificial fill.
This study was undertaken to improve our understanding of the bedrock geology in the Adirondack Highlands, establish a modern framework for 1:24,000-scale bedrock geologic mapping in the Adirondacks, provide a context for historical iron mines in the eastern Adirondacks, and update the stratigraphy of the Champlain Valley in New York and Vermont. This Scientific Investigations Map of the Crown Point 7.5-minute quadrangle consists of a map sheet, an explanatory pamphlet, and a geographic information system database that includes bedrock geologic units, faults, outcrops, and structural geologic information. The map sheet includes a bedrock geologic map, a correlation of map units, a description of map units, an explanation of map symbols, three cross sections, and a simplified surficial geologic map that includes lidar percent slope. The explanatory pamphlet includes a discussion of the geology.
The bedrock geologic map on the map sheet is multi-layered and has been designed to enable the user to turn off the surficial map layer to view the concealed bedrock map units.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3491","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey, and the State of New York, Department of Education, New York Geological Survey","usgsCitation":"Walsh, G.J., Orndorff, R.C., and McAleer, R.J., 2022, Bedrock geologic map of the Crown Point quadrangle, Essex County, New York, and Addison County, Vermont: U.S. Geological Survey Scientific Investigations Map 3491, 1 sheet, scale 1:24,000, 44-p. pamphlet, https://doi.org/10.3133/sim3491.","productDescription":"Pamphlet: viii, 44 p.; Sheet: 62.00 x 41.00 inches; Base Map; Database; Metadata","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-117525","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":435638,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1FHRNVU","text":"USGS data release","linkHelpText":"Database for the bedrock geologic map of the Crown Point quadrangle, Essex County, New York, and Addison County, Vermont"},{"id":410043,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_sheet1.pdf","size":"178 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":408680,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_metadata.zip","size":"216 KB","linkFileType":{"id":6,"text":"zip"}},{"id":408682,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_basemap.zip","text":"Topographic Spatial Data","size":"119 MB","linkFileType":{"id":6,"text":"zip"}},{"id":408679,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_database.zip","size":"4.40 MB","linkFileType":{"id":6,"text":"zip"}},{"id":408674,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_pamphlet.pdf","text":"Pamphlet","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3491"},{"id":408673,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3491/coverthb.jpg"},{"id":501933,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113783.htm","linkFileType":{"id":5,"text":"html"}},{"id":408681,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_openaccess.zip","text":"Open Access","size":"6.29 MB","linkFileType":{"id":6,"text":"zip"}}],"country":"United States","state":"New York, Vermont","county":"Addison County, Essex County","otherGeospatial":"Crown Point quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.5,\n 44\n ],\n [\n -73.5,\n 43.875\n ],\n [\n -73.375,\n 43.875\n ],\n [\n -73.375,\n 44\n ],\n [\n -73.5,\n 44\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The Sevier/Toroweap Fault Zone is a major north-south-striking fault located in northern Arizona and southwestern Utah. In partnership with the National Park Service, the U.S. Geological Survey conducted two geophysical controlled-source audio-frequency magnetotelluric (CSAMT) surveys that transected the Sevier/Toroweap Fault Zone at Clay Flat, Utah, a potential pull-apart basin, west of a site of proposed groundwater pumping to evaluate the subsurface hydrogeology. The goal of the surveys was to enhance understanding of the interconnectedness of the Navajo aquifer, the region’s primary groundwater source, across two groundwater basins to the east and west of the fault zone, Water Rights Area (WRA) 81 and WRA 85.
In the Kane County, Utah, area, the Sevier/Toroweap Fault Zone consists of the Sevier section (to the north) and the northern Toroweap section (to the south). Two survey lines totaling 7 kilometers of CSAMT survey data were collected. The CSAMT survey line SV1 transected both the Sevier section and the northern Toroweap section of the fault zone; survey line SV2 transected only the Sevier section. Although offset of the Navajo Sandstone, the main component of the Navajo aquifer, by the Sevier/Toroweap Fault Zone is generally accepted as the geologic reason that the Navajo aquifer is disconnected in the study area, results of the CSAMT surveys suggest that vertical offset of the Navajo Sandstone of the Glen Canyon Group across the Sevier/Toroweap Fault Zone is insufficient to completely disconnect the aquifer in the study area. The effects of faulting on groundwater north and south of the study area, where offset of water-bearing layers may be greater, requires further study. A clearer understanding of groundwater movement across the Sevier /Toroweap Fault Zone will aid water-resource managers in making informed decisions concerning groundwater rights.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225071","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Jones, C.J.R., Robinson, M.J., and Macy, J.P., 2022, Characterization of the Sevier/Toroweap Fault Zone in Kane County, Utah, using controlled-source audio-frequency magnetotelluric (CSAMT) surveys: U.S. Geological Survey Scientific Investigations Report 2022–5071, 14 p., https://doi.org/10.3133/sir20225071.","productDescription":"Report: iv, 14 p.; Data Release","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-133730","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":503394,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113782.htm","linkFileType":{"id":5,"text":"html"}},{"id":408830,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QF9PFR","text":"Controlled source audio-frequency magnetotellurics (CSAMT) data from the Sevier fault near Red Knoll, Kane County, Utah (ver. 2.0, July 2022)","description":"Robinson, M.J., and Macy, J.P., 2022, Controlled source audio-frequency magnetotellurics (CSAMT) data from the Sevier fault near Red Knoll, Kane County, Utah: U.S. Geological Survey data release, https://doi.org/10.5066/P9QF9PFR."},{"id":408828,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5071/sir20225071.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":408827,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5071/covrthb.jpg"}],"country":"United States","state":"Utah","county":"Kane County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.97309886757559,\n 37.55221820418316\n ],\n [\n -112.97309886757559,\n 37.082590637675466\n ],\n [\n -112.15461742226314,\n 37.082590637675466\n ],\n [\n -112.15461742226314,\n 37.55221820418316\n ],\n [\n -112.97309886757559,\n 37.55221820418316\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
The Chesapeake Bay, along the mid-Atlantic coast of North America, is the largest estuary in the United States and provides critical habitat for wildlife. In contrast to point and non-point source release of pesticides, metals, and industrial, personal care and household use chemicals on biota in this watershed, there has only been scant attention to potential exposure and effects of algal toxins on wildlife in the Chesapeake Bay region. As background, we first review the scientific literature on algal toxins and harmful algal bloom (HAB) events in various regions of the world that principally affected birds, and to a lesser degree other wildlife. To examine the situation for the Chesapeake, we compiled information from government reports and databases summarizing wildlife mortality events for 2000 through 2020 that were associated with potentially toxic algae and HAB events. Summary findings indicate that there have been few wildlife mortality incidents definitively linked to HABs, other mortality events that were suspected to be related to HABs, and more instances in which HABs may have indirectly contributed to or occurred coincident with wildlife mortality. The dominant toxins found in the Chesapeake Bay drainage that could potentially affect wildlife are microcystins, with concentrations in water approaching or exceeding human-based thresholds for ceasing recreational use and drinking water at a number of locations. As an increasing trend in HAB events in the U.S. and in the Chesapeake Bay have been reported, additional information on HAB toxin exposure routes, comparative sensitivity among species, consequences of sublethal exposure, and better diagnostic and risk criteria would greatly assist in predicting algal toxin hazard and risks to wildlife.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.hal.2022.102319","usgsCitation":"Rattner, B., Wazniak, C.E., Lankton, J.S., McGowan, P.C., Drovetski, S.V., and Egerton, T.A., 2022, Review of harmful algal blooms effects on birds with implications for avian wildlife in the Chesapeake Bay region: Harmful Algae, v. 120, 102319, 20 p.; Data Release, https://doi.org/10.1016/j.hal.2022.102319.","productDescription":"102319, 20 p.; Data Release","ipdsId":"IP-138638","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446019,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hal.2022.102319","text":"Publisher Index Page"},{"id":408805,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418367,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ULAM7G","text":"Wildlife mortality events in counties surrounding the Chesapeake Bay recorded in the Wildlife Health Information Sharing Partnership Event Reporting System (WHISPers) from 2000-2020"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.18954322170708,\n 37.53524166994633\n ],\n [\n -77.44783397911205,\n 37.364931581898986\n ],\n [\n -76.73341273522277,\n 36.72453067388703\n ],\n [\n -76.21133567238093,\n 36.76416355102856\n ],\n [\n -75.98601820315514,\n 37.06311061060744\n ],\n [\n -75.93655827088573,\n 37.308289271077044\n ],\n [\n -75.41997675607354,\n 37.95675381093146\n ],\n [\n -75.69475415756958,\n 38.48348716740804\n ],\n [\n -75.77718737801817,\n 39.59326365864615\n ],\n [\n -76.0464692314839,\n 39.66521791944069\n ],\n [\n -77.45332952714315,\n 38.82253108298832\n ],\n [\n -77.40386959487374,\n 38.276702908455235\n ],\n [\n -77.18954322170708,\n 37.53524166994633\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"120","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":298580,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett A.","email":"brattner@usgs.gov","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":855925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wazniak, Catherine E.","contributorId":298582,"corporation":false,"usgs":false,"family":"Wazniak","given":"Catherine","email":"","middleInitial":"E.","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":855989,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lankton, Julia S. 0000-0002-6843-4388 jlankton@usgs.gov","orcid":"https://orcid.org/0000-0002-6843-4388","contributorId":5888,"corporation":false,"usgs":true,"family":"Lankton","given":"Julia","email":"jlankton@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":855990,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":855991,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Drovetski, Sergei V. 0000-0002-1832-5597","orcid":"https://orcid.org/0000-0002-1832-5597","contributorId":229520,"corporation":false,"usgs":true,"family":"Drovetski","given":"Sergei","middleInitial":"V.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":855992,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Egerton, Todd A.","contributorId":298583,"corporation":false,"usgs":false,"family":"Egerton","given":"Todd","email":"","middleInitial":"A.","affiliations":[{"id":64620,"text":"Virginia Department of Health","active":true,"usgs":false}],"preferred":false,"id":855993,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70237827,"text":"sim3494 - 2022 - Use of high-resolution topobathymetry to assess shoreline topography and potential future development of a slack water harbor near Dardanelle, Arkansas, October 2021","interactions":[],"lastModifiedDate":"2026-04-01T15:28:51.970121","indexId":"sim3494","displayToPublicDate":"2022-10-25T15:47:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3494","displayTitle":"Use of High-Resolution Topobathymetry to Assess Shoreline Topography and Potential Future Development of a Slack Water Harbor near Dardanelle, Arkansas, October 2021","title":"Use of high-resolution topobathymetry to assess shoreline topography and potential future development of a slack water harbor near Dardanelle, Arkansas, October 2021","docAbstract":"The U.S. Army Corps of Engineers (USACE), Southwestern Division, Little Rock District Civil Works program has a mission to maintain cohesion between physical and naturally developed environments. The USACE authorized the development of an off-channel harbor (hereinafter referred to as the “proposed slack water harbor”) along the McClellan-Kerr Arkansas River Navigation System at river mile 202.6, and an initial evaluation of shoreline stability and adjacent land near the proposed harbor was considered essential in establishing a baseline for potential effects and future monitoring. In October 2021, the U.S. Geological Survey, in cooperation with the USACE, completed high-resolution bathymetric (underwater elevation) and topographic surveys of the Arkansas River and a quarry at the location of the proposed slack water harbor near Dardanelle, Arkansas, using a combination of multibeam sound navigation and ranging (sonar) and high-resolution, low-altitude aerial light detection and ranging (lidar) data to provide data and analysis needed for as-built information and future monitoring of river shoreline and floodplain management and maintenance.
Bathymetric data were collected using a high-resolution multibeam mapping system, which consists of a multibeam echosounder and an inertial navigation system mounted on a marine survey vessel. Data were collected as the vessel traversed the river and quarry along overlapping survey lines distributed throughout the areas.
Topographic data were collected as a lidar point cloud using an unmanned aircraft system (UAS) with a YellowScan Vx20–100 lidar payload, which consists of the lidar scanner and an inertial navigation system. The lidar point cloud data were collected as the UAS followed two sets of parallel transect lines, oriented perpendicular to each other (nominally north to south and east to west) on separate flights. The bathymetric and UAS topographic datasets were combined with topographic data extracted from publicly available aerial lidar data collected in 2014 to create a multisource point cloud classified as “ground” (code 2) according to the American Society for Photogrammetry and Remote Sensing standard lidar point classes in the proposed harbor area and surroundings, from which topographic contours were derived.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3494","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Southwestern Division, Little Rock District","usgsCitation":"Huizinga, R.J., Richards, J.M., and Rivers, B.C., 2022, Use of high-resolution topobathymetry to assess shoreline topography and potential future development of a slack water harbor near Dardanelle, Arkansas, October 2021: U.S. Geological Survey Scientific Investigations Map 3494, 1 sheet, https://doi.org/10.3133/sim3494.","productDescription":"Sheet: 36.00 x 39.50 inches; Data Release","numberOfPages":"1","onlineOnly":"Y","ipdsId":"IP-137686","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":408700,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3494/sim3494.pdf","text":"Report","size":"2.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3494"},{"id":408699,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3494/coverthb.jpg"},{"id":408701,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3494/sim3494.XML"},{"id":408702,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3494/images"},{"id":408722,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sim3494/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":408703,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KW1D2D","text":"USGS data release","linkHelpText":"Use of high-resolution topobathymetry to assess shoreline topography and future development of a slack water harbor near Dardanelle, Arkansas, October 2021"},{"id":501937,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113784.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Arkansas","county":"Dardanelle","otherGeospatial":"Slack Water Harbor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.1753984002736,\n 34.7148432917307\n ],\n [\n -92.1753984002736,\n 34.70185497290542\n ],\n [\n -92.15152711351902,\n 34.70185497290542\n ],\n [\n -92.15152711351902,\n 34.7148432917307\n ],\n [\n -92.1753984002736,\n 34.7148432917307\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Despite significant investigation of fly ash spills and mineralogical controls on the release of potentially toxic elements (PTEs) from fly ash, interactions with the surficial environment remain relatively poorly understood. We conducted 90-day batch leaching studies with paired analysis of supernatant and solid-phase mineralogy to assess the elemental release and transformation of fly ash upon reaction with aquatic media (18 MΩ cm−1 water and simulated rainwater). The fly ash in this study, collected from the University of Alaska Fairbanks stoker-boiler power plant, is high in unburned carbon (~20% LOI) and highly enriched in several PTEs relative to the upper continental crust. Supernatant concentrations of oxyanion-forming elements (e.g., As, Se, Mo, Sb) remained relatively low and constant, suggesting equilibrium with the solid phase, possibly ettringite [Ca6Al2(SO4)3(OH)12•26H2O], which is known to incorporate and sorb oxyanion-forming PTEs and was identified by X-ray diffraction. Synthetic precipitation leaching procedure (SPLP) results failed to capture important temporal trends. Lead and Ba supernatant concentrations consistently exceeded drinking water standards, as well as others upon exposure to simulated physiological solutions. Seven-day experiments with dissolved organic matter-isolate solutions indicated that for certain elements, liberation was influenced by carbon concentration and/or the identity of the isolate. Overall, this paired approach can serve as a model for future studies, bridging existing gaps between batch leaching and single-element mineralogical, sorption, or speciation studies.
We present a model of the lower seismogenic depth of earthquakes in the western United States (WUS) estimated using the hypocentral depths of events M > 1, a crustal temperature model, and historical earthquake rupture depth models. Locations of earthquakes are from the Advanced National Seismic System Comprehensive Earthquake Catalog from 1980 to 2021 supplemented with seismicity in southern California for event hypocenters that were relocated by Hauksson et al. (2012) to obtain higher precision and better resolution in the model. We calculated the average depth of the deepest 10% of the merged catalog using an adaptive radius of 50 km or more. Along the San Andreas fault, the deepest seismogenic depths are located at 23 km around the Cholame segment, whereas the shallowest depths are located at about 10 km along the Rodgers Creek and Maacama faults. For the WUS outside California, the depth generally varies between 10 and 25 km with an average around 14 km but could extend to 35 km along Cascadia subduction zone. We find good agreement between the small‐magnitude depths and rupture depths derived from coseismic slip of large earthquakes across the region. Our estimates are generally deeper than the previous seismogenic depths determined for the Uniform California Earthquake Rupture Forecast, Version 3 model based on work by Petersen et al. (1996) who used seismicity cross sections along major fault zones in California. Our new seismogenic depth distribution correlates closely with crustal temperature derived from WUS heat flow (Blackwell et al., 2011). This correlation allowed us to develop a map of the brittle–ductile transition that we use to replace seismogenic depths in the model east of the Intermountain West Seismic Belt where the seismicity rate is low. This updated depth model is useful for recalibrating the lower geologic fault rupture depths, and constraining deformation and seismicity source models in updates of the U.S. Geological Survey National Seismic Hazard Model.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220220174","usgsCitation":"Zeng, Y., Petersen, M.D., and Boyd, O.S., 2022, Lower seismogenic depth model of western U.S. Earthquakes: Seismological Research Letters, v. 93, no. 6, p. 3186-3204, https://doi.org/10.1785/0220220174.","productDescription":"19 p.","startPage":"3186","endPage":"3204","ipdsId":"IP-142152","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":408265,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.33203125,\n 29.84064389983441\n ],\n [\n -103.35937499999999,\n 29.84064389983441\n ],\n [\n -103.35937499999999,\n 48.69096039092549\n ],\n [\n -125.33203125,\n 48.69096039092549\n ],\n [\n -125.33203125,\n 29.84064389983441\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"93","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Zeng, Yuehua 0000-0003-1161-1264 zeng@usgs.gov","orcid":"https://orcid.org/0000-0003-1161-1264","contributorId":145693,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":854484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":854485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":854486,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70237388,"text":"70237388 - 2022 - Comparing Landsat Dynamic Surface Water Extent to alternative methods of measuring inundation in developing waterbird habitats","interactions":[],"lastModifiedDate":"2022-10-17T16:42:25.152014","indexId":"70237388","displayToPublicDate":"2022-10-12T09:07:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5098,"text":"Remote Sensing Applications: Society and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Comparing Landsat Dynamic Surface Water Extent to alternative methods of measuring inundation in developing waterbird habitats","docAbstract":"This study investigates the applicability of the Landsat Dynamic Surface Water Extent (DSWE) science product for waterbird habitat modeling in multiple non-canopied habitat types. We compare surface water distribution estimates derived from DSWE to two site-specific survey methods: visual surveys and digitized aerial imagery. These site-specific surveys were conducted on Poplar Island, a restoration island project in the Chesapeake Bay, USA. Visual surveys were collected bimonthly from 2006 – 2013, and digitized aerial imagery was collected annually from 2006 – 2015. As a restoration island, Poplar Island presents a unique opportunity to analyze DSWE in a rapidly changing site. We structure our analysis based on the procedural development of individual sub-island cells developed from unconsolidated dredge material into fully restored wetlands that have independent hydrologic connection to the surrounding bay. Each development status is analyzed using our three DSWE classifications: Open Water (OW), a conservative estimate; Wetland Inclusive (WI), an aggressive estimate; and Development Dependent (DD), a landcover adaptive estimate. The OW classification consistently underestimates surface water coverage especially in the more complex, fully developed cells. The WI classification is better able to capture the tidal channels in these cells, but marginally overestimates surface water coverage in more sparsely vegetated cells. The DD classification does not significantly improve upon the estimations of the WI classification. Our data indicate that DSWE can be a capable alternative to our site-specific survey methods. However, the product is limited by Landsat’s 30 m spatial resolution, especially in more structurally complex wetlands. A recommended classification method for characterizing waterbird habitats would depend on the goals and targeted scale of analysis, for which DSWE may be a viable option.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rsase.2022.100845","usgsCitation":"Taylor, J., Sullivan, J.D., Teitelbaum, C.S., Reese, J.G., and Prosser, D., 2022, Comparing Landsat Dynamic Surface Water Extent to alternative methods of measuring inundation in developing waterbird habitats: Remote Sensing Applications: Society and Environment, v. 28, 100845, 9 p., https://doi.org/10.1016/j.rsase.2022.100845.","productDescription":"100845, 9 p.","ipdsId":"IP-139932","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446139,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rsase.2022.100845","text":"Publisher Index Page"},{"id":435658,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SW505K","text":"USGS data release","linkHelpText":"Surface water estimates for a complex study site derived from traditional and emerging methods"},{"id":408211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Chesapeake Bay, Poplar Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.36236190795898,\n 38.74631848708898\n ],\n [\n -76.36373519897461,\n 38.754886481591335\n ],\n [\n -76.36905670166014,\n 38.7564928660758\n ],\n [\n -76.37231826782227,\n 38.754886481591335\n ],\n [\n -76.37884140014648,\n 38.762114927054405\n ],\n [\n -76.37969970703125,\n 38.76519348705099\n ],\n [\n -76.37712478637695,\n 38.76827191422227\n ],\n [\n -76.36356353759766,\n 38.78165483591876\n ],\n [\n -76.35824203491211,\n 38.78580303175893\n ],\n [\n -76.35772705078125,\n 38.793295935073516\n ],\n [\n -76.36510848999022,\n 38.797577240505625\n ],\n [\n -76.36974334716797,\n 38.79650693825768\n ],\n [\n -76.37042999267578,\n 38.79102138696157\n ],\n [\n -76.37128829956055,\n 38.78807774637309\n ],\n [\n -76.37060165405273,\n 38.784331118923134\n ],\n [\n -76.37334823608398,\n 38.78272536117434\n ],\n [\n -76.37695312499999,\n 38.78339443129763\n ],\n [\n -76.38141632080078,\n 38.78138720209366\n ],\n [\n -76.39291763305664,\n 38.767201172010736\n ],\n [\n -76.39120101928711,\n 38.75582354360097\n ],\n [\n -76.38656616210938,\n 38.7500671112174\n ],\n [\n -76.38364791870117,\n 38.743239112884744\n ],\n [\n -76.37678146362305,\n 38.741766321754575\n ],\n [\n -76.36236190795898,\n 38.74631848708898\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, John B.","contributorId":296294,"corporation":false,"usgs":false,"family":"Taylor","given":"John B.","affiliations":[{"id":64012,"text":"Chesapeake Bay Trust","active":true,"usgs":false}],"preferred":false,"id":854370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullivan, Jeffery D. 0000-0002-9242-2432","orcid":"https://orcid.org/0000-0002-9242-2432","contributorId":265822,"corporation":false,"usgs":true,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":854371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teitelbaum, Claire S. 0000-0001-5646-3184","orcid":"https://orcid.org/0000-0001-5646-3184","contributorId":255382,"corporation":false,"usgs":false,"family":"Teitelbaum","given":"Claire","email":"","middleInitial":"S.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":854372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reese, Jan G.","contributorId":296295,"corporation":false,"usgs":false,"family":"Reese","given":"Jan","email":"","middleInitial":"G.","affiliations":[{"id":28165,"text":"No affiliation","active":true,"usgs":false}],"preferred":false,"id":854373,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":854374,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237391,"text":"70237391 - 2022 - An evaluation of the reliability of plumage characters for sexing adult Ruddy Turnstones Arenaria interpres morinella during northward passage in eastern North America","interactions":[],"lastModifiedDate":"2022-10-12T13:40:56.735739","indexId":"70237391","displayToPublicDate":"2022-10-12T08:20:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5557,"text":"Wader Study","active":true,"publicationSubtype":{"id":10}},"displayTitle":"An evaluation of the reliability of plumage characters for sexing adult Ruddy Turnstones Arenaria interpres morinella during northward passage in eastern North America","title":"An evaluation of the reliability of plumage characters for sexing adult Ruddy Turnstones Arenaria interpres morinella during northward passage in eastern North America","docAbstract":"We used two datasets to investigate the reliability of plumage for sexing adult Ruddy Turnstones Arenaria interpres of the morinella subspecies during May and early June in Delaware Bay, on the Mid-Atlantic Coast of the United States (39.1202°N, 75.2479°W). We first examined 23 years of data on the capture and recapture of 1,818 individual Ruddy Turnstones to assess the consistency of observers with varying levels of expertise in assigning sex using plumage criteria. Among birds recaptured once, the sex recorded for about 10% differed between captures. This increased to about 16% among birds recaptured more than once. Significantly more birds sexed as females early in the season (during 1–12 May) were later sexed as males than vice versa. This suggests that early-season captures may include birds still in non- (or partial) breeding plumage, which can be confused with female breeding plumage. Second, we compared plumage-based and genetic assessments of sex for 66 Ruddy Turnstones captured in Delaware Bay on 29 May 2016 and 19 May 2017; these individuals were sexed in the hand by an expert on shorebird plumages. Plumage-based and molecular assessments differed in only one case. This suggests that fewer birds will be wrongly sexed on plumage if more care is taken and better instruction is given to observers (including how to distinguish non- breeding plumage from female breeding plumage). We suggest simple procedures to reduce field-sexing errors for Ruddy Turnstones based on plumage.
","language":"English","publisher":"International Wader Study Group","doi":"10.18194/ws.00274","usgsCitation":"Fullagar, P.J., Chesser, R., Sitters, H.P., Davey, C.C., Niles, L., Drovetski, S.V., and Cortes-Rodriguez, M., 2022, An evaluation of the reliability of plumage characters for sexing adult Ruddy Turnstones Arenaria interpres morinella during northward passage in eastern North America: Wader Study, v. 129, no. 2, p. 138-147, https://doi.org/10.18194/ws.00274.","productDescription":"10 p.","startPage":"138","endPage":"147","ipdsId":"IP-133440","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":408208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey, Pennsylvania","otherGeospatial":"Delaware Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.09979248046875,\n 38.76479194327964\n ],\n [\n -74.94598388671875,\n 38.94232097947902\n ],\n [\n -74.87457275390625,\n 39.095962936305476\n ],\n [\n -74.85260009765625,\n 39.17478791493289\n ],\n [\n -74.8828125,\n 39.22587043822116\n ],\n [\n -75.13824462890625,\n 39.24288969082635\n ],\n [\n -75.23162841796875,\n 39.31517545076218\n ],\n [\n -75.27557373046875,\n 39.32579941789298\n ],\n [\n -75.311279296875,\n 39.36190883564925\n ],\n [\n -75.3662109375,\n 39.37677199661635\n ],\n [\n -75.44586181640625,\n 39.45316112807394\n ],\n [\n -75.51177978515625,\n 39.48284540453334\n ],\n [\n -75.498046875,\n 39.54217596171196\n ],\n [\n -75.47332763671875,\n 39.58240712203527\n ],\n [\n -75.531005859375,\n 39.63319206567459\n ],\n [\n -75.487060546875,\n 39.688167045890395\n ],\n [\n -75.42938232421875,\n 39.75999140525313\n ],\n [\n -75.311279296875,\n 39.82119422647453\n ],\n [\n -75.22064208984375,\n 39.83595916247957\n ],\n [\n -75.08880615234375,\n 39.86969567045658\n ],\n [\n -75.1519775390625,\n 39.91394967016644\n ],\n [\n -75.3662109375,\n 39.86969567045658\n ],\n [\n -75.53924560546875,\n 39.74521015328692\n ],\n [\n -75.5474853515625,\n 39.71141252523694\n ],\n [\n -75.63812255859375,\n 39.614152077002664\n ],\n [\n -75.6024169921875,\n 39.53370327008705\n ],\n [\n -75.62164306640625,\n 39.45528185347343\n ],\n [\n -75.56121826171875,\n 39.40861097325807\n ],\n [\n -75.5145263671875,\n 39.33854604847979\n ],\n [\n -75.42388916015625,\n 39.20246222588238\n ],\n [\n -75.44036865234375,\n 39.16839998800286\n ],\n [\n -75.42938232421875,\n 39.07677595221322\n ],\n [\n -75.38543701171875,\n 39.036252959636606\n ],\n [\n -75.34149169921875,\n 38.974357249228206\n ],\n [\n -75.34423828125,\n 38.9380483825641\n ],\n [\n -75.2947998046875,\n 38.884619201291905\n ],\n [\n -75.29754638671875,\n 38.86323626888358\n ],\n [\n -75.17669677734375,\n 38.77978137804918\n ],\n [\n -75.09979248046875,\n 38.76479194327964\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"129","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Fullagar, Peter J.","contributorId":297536,"corporation":false,"usgs":false,"family":"Fullagar","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":64424,"text":"private individual","active":true,"usgs":false}],"preferred":false,"id":854375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chesser, R. 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Terry","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":854376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sitters, Humphrey P.","contributorId":297537,"corporation":false,"usgs":false,"family":"Sitters","given":"Humphrey","email":"","middleInitial":"P.","affiliations":[{"id":64424,"text":"private individual","active":true,"usgs":false}],"preferred":false,"id":854377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davey, Christopher C.","contributorId":297538,"corporation":false,"usgs":false,"family":"Davey","given":"Christopher","email":"","middleInitial":"C.","affiliations":[{"id":64424,"text":"private individual","active":true,"usgs":false}],"preferred":false,"id":854378,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Niles, Lawrence J.","contributorId":297539,"corporation":false,"usgs":false,"family":"Niles","given":"Lawrence J.","affiliations":[{"id":64426,"text":"Wildlife Restoration Partnerships","active":true,"usgs":false}],"preferred":false,"id":854379,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drovetski, Sergei V. 0000-0002-1832-5597","orcid":"https://orcid.org/0000-0002-1832-5597","contributorId":229520,"corporation":false,"usgs":true,"family":"Drovetski","given":"Sergei","middleInitial":"V.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":854380,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cortes-Rodriguez, M. Nandadevi","contributorId":297540,"corporation":false,"usgs":false,"family":"Cortes-Rodriguez","given":"M. Nandadevi","affiliations":[{"id":18877,"text":"Ithaca College","active":true,"usgs":false}],"preferred":false,"id":854381,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70269055,"text":"70269055 - 2022 - Revised earthquake geology inputs for the central and eastern United States and southeast Canada for the 2023 National Seismic Hazard Model","interactions":[],"lastModifiedDate":"2025-07-15T15:43:20.638903","indexId":"70269055","displayToPublicDate":"2022-10-12T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Revised earthquake geology inputs for the central and eastern United States and southeast Canada for the 2023 National Seismic Hazard Model","docAbstract":"It has been nearly a decade since updates to seismic and fault sources in the central and eastern United States (CEUS) were last assessed for the 2012 Central and Eastern United States Seismic Source Characterization for nuclear facilities (CEUS-SSCn) and 2014 United States Geological Survey National Seismic Hazard Model (NSHM) for the conterminous U.S. In advance of the 2023 NSHM update, we created 3 related geospatial databases to summarize and characterize new fault source information for the CEUS. These include fault section, fault-zone polygon, and earthquake geology (fault slip rate, earthquake recurrence intervals) databases which document updates to fault parameters used in prior seismic hazard models in this region. The 2012 CEUS-SSCn and 2014 NSHM fault models served as a foundation, as we revised and added fault sources where new published studies documented significant changes to our understanding of fault location, geometry, or activity. We added 9 new fault sections that meet the criteria of (1) a length ≥7 km, (2) evidence of recurrent Quaternary tectonic activity, and (3) documentation that is publicly available in a peer-reviewed source. The prior CEUS models only included 6 fault sections (sources) and 10 fault-zone polygons (previously called repeating large magnitude earthquake (RLME) polygons). The revised databases include 15 fault sections and 10 fault zone polygons. Updates to the faults constitute a 150% increase in fault sections, but no change in the number of fault-zone polygons, although some fault-zone polygons differ from RLME polygons used in prior models. No faults were removed from past models. Several seismic zones and suspected faults were evaluated but not included in this update due to a lack of information about fault location, geometry, or recurrent Quaternary activity. These updates to the fault sections, fault-zone polygons, and earthquake geology databases will inform fault geometry and activity rates of CEUS sources during the 2023 NSHM implementation.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220220162","usgsCitation":"Jobe, J.A., Hatem, A.E., Gold, R.D., DuRoss, C., Reitman, N.G., Briggs, R.W., and Collett, C.M., 2022, Revised earthquake geology inputs for the central and eastern United States and southeast Canada for the 2023 National Seismic Hazard Model: Seismological Research Letters, v. 93, no. 6, p. 3100-3120, https://doi.org/10.1785/0220220162.","productDescription":"21 p.","startPage":"3100","endPage":"3120","ipdsId":"IP-138939","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":492251,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -104.33762311995545,\n 51.85857884546667\n ],\n [\n -104.33762311995545,\n 25.297267313035647\n ],\n [\n -66.17641020136095,\n 25.297267313035647\n ],\n [\n -66.17641020136095,\n 51.85857884546667\n ],\n [\n -104.33762311995545,\n 51.85857884546667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"93","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson Jobe, Jessica A. 0000-0001-5574-4523","orcid":"https://orcid.org/0000-0001-5574-4523","contributorId":295377,"corporation":false,"usgs":true,"family":"Thompson Jobe","given":"Jessica","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":943161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hatem, Alexandra Elise 0000-0001-7584-2235","orcid":"https://orcid.org/0000-0001-7584-2235","contributorId":225597,"corporation":false,"usgs":true,"family":"Hatem","given":"Alexandra","email":"","middleInitial":"Elise","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":943162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":943163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DuRoss, Christopher B. 0000-0002-6963-7451 cduross@usgs.gov","orcid":"https://orcid.org/0000-0002-6963-7451","contributorId":152321,"corporation":false,"usgs":true,"family":"DuRoss","given":"Christopher","email":"cduross@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":943164,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reitman, Nadine G. 0000-0002-6730-2682 nreitman@usgs.gov","orcid":"https://orcid.org/0000-0002-6730-2682","contributorId":5816,"corporation":false,"usgs":true,"family":"Reitman","given":"Nadine","email":"nreitman@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":943165,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":4136,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":943166,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Collett, Camille Marie 0000-0003-4836-0243","orcid":"https://orcid.org/0000-0003-4836-0243","contributorId":257819,"corporation":false,"usgs":true,"family":"Collett","given":"Camille","email":"","middleInitial":"Marie","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":943167,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70240887,"text":"70240887 - 2022 - Decision support for aquatic restoration based on species-specific responses to disturbance","interactions":[],"lastModifiedDate":"2023-02-28T13:05:03.312497","indexId":"70240887","displayToPublicDate":"2022-10-11T07:02:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Decision support for aquatic restoration based on species-specific responses to disturbance","docAbstract":"Disturbances to aquatic habitats are not uniformly distributed within the Great Lakes and acute effects can be strongest in nearshore areas where both landscape and within lake effects can have strong influence. Furthermore, different fish species respond to disturbances in different ways. A means to identify and evaluate locations and extent of disturbances that affect fish is needed throughout the Great Lakes. We used partial Canonical Correspondence Analysis to separate “natural” effects on nearshore assemblages from disturbance effects. Species-specific quadratic models of fish abundance as functions of in-lake disturbance or watershed-derived disturbance were developed separately for each of 35 species and lakewide predictions mapped for Lake Erie. Most responses were unimodal and more species decreased in abundance with increasing watershed disturbance than increased. However, eight species increased in abundance with current in-lake disturbance conditions. Optimum Yellow Perch (Perca flavescens) abundance occurred at in-lake disturbance values less than the gradient mean, but decreased continuously from minimum watershed disturbance to higher values. Bands of optimum in-lake conditions occurred throughout the eastern and western portions of the Lake Erie nearshore zone; some areas were less disturbed than desirable. However, watershed-derived disturbance conditions were generally poor for Yellow Perch throughout the lake. In contrast, optimum Smallmouth Bass (Micropterus dolomieu) abundance occurred at in-lake disturbance values greater than the gradient mean and continuously increased with increasing watershed disturbance. Smallmouth Bass responses to disturbance indicated that most of the nearshore zone was less disturbed than is desirable and were most abundant in areas that the Yellow Perch response indicated were highly disturbed. Mapping counts of species response models that agreed on the disturbance level in each spatial unit of the nearshore zone showed a fine-scale mosaic of areas in which habitat restoration may benefit many or few species. This tool may assist managers in prioritizing conservation and restoration efforts and evaluating environmental conditions that may be improved.
Habitat loss, flood control infrastructure, and drought have left most of southern California and northern Baja California's native freshwater fish near extinction, including the endangered unarmoured threespine stickleback (Gasterosteus aculeatus williamsoni). This subspecies, an unusual morph lacking the typical lateral bony plates of the G. aculeatus complex, occurs at arid southern latitudes in the eastern Pacific Ocean and survives in only three inland locations. Managers have lacked molecular data to answer basic questions about the ancestry and genetic distinctiveness of unarmoured populations. These data could be used to prioritize conservation efforts. We sampled G. aculeatus from 36 localities and used microsatellites and whole genome data to place unarmoured populations within the broader evolutionary context of G. aculeatus across southern California/northern Baja California. We identified three genetic groups with none consisting solely of unarmoured populations. Unlike G. aculeatus at northern latitudes, where Pleistocene glaciation has produced similar historical demographic profiles across populations, we found markedly different demographics depending on sampling location, with inland unarmoured populations showing steeper population declines and lower heterozygosity compared to low armoured populations in coastal lagoons. One exception involved the only high elevation population in the region, where the demography and alleles of unarmoured fish were similar to low armoured populations near the coast, exposing one of several cases of artificial translocation. Our results suggest that the current “management-by-phenotype” approach, based on lateral plates, is incidentally protecting the most imperilled populations; however, redirecting efforts toward evolutionary units, regardless of phenotype, may more effectively preserve adaptive potential.
","language":"English","publisher":"Wiley","doi":"10.1111/mec.16722","usgsCitation":"Turba, R., Richmond, J.Q., Fitz-Gibbon, S., Morselli, M., Fisher, R., Swift, C.C., Ruiz-Campos, G., Backlin, A.R., Dellith, C., and Jacobs, D.K., 2022, Genetic structure and historic demography of endangered unarmoured threespine stickleback at southern latitudes signals a potential new management approach: Molecular Ecology, v. 31, no. 24, p. 6515-6530, https://doi.org/10.1111/mec.16722.","productDescription":"16 p.","startPage":"6515","endPage":"6530","ipdsId":"IP-144634","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":446193,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/mec.16722","text":"Publisher Index Page"},{"id":409689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Baja California, California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.59972346173339,\n 29.66662912056644\n ],\n [\n -116.3228483705328,\n 34.94795462564349\n ],\n [\n -120.9183518200569,\n 35.38592392602483\n ],\n [\n -120.53381107775209,\n 34.39232111031369\n ],\n [\n -120.2934320651216,\n 32.72373688169593\n ],\n [\n -117.30697616896543,\n 32.28570882745247\n ],\n [\n -115.66154688239834,\n 29.533400726878227\n ],\n [\n -115.59972346173339,\n 29.66662912056644\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"31","issue":"24","noUsgsAuthors":false,"publicationDate":"2022-10-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Turba, 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Center","active":true,"usgs":true}],"preferred":true,"id":857629,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dellith, Chris","contributorId":139396,"corporation":false,"usgs":false,"family":"Dellith","given":"Chris","email":"","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":857630,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jacobs, David K.","contributorId":139394,"corporation":false,"usgs":false,"family":"Jacobs","given":"David","email":"","middleInitial":"K.","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":857631,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70237276,"text":"70237276 - 2022 - Range-wide population projections for Northern Red-Bellied Cooters (Pseudemys rubriventris)","interactions":[],"lastModifiedDate":"2022-10-06T13:47:45.013432","indexId":"70237276","displayToPublicDate":"2022-10-06T08:35:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2334,"text":"Journal of Herpetology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Range-wide population projections for Northern Red-Bellied Cooters (Pseudemys rubriventris)","title":"Range-wide population projections for Northern Red-Bellied Cooters (Pseudemys rubriventris)","docAbstract":"Northern Red-Bellied Cooters (Pseudemys rubriventris) have a disjunct distribution with a relictual population in southeastern Massachusetts and a larger range across the mid-Atlantic United States. The relictual population is currently listed with protections under the U.S. Endangered Species Act but the status of the population in the remainder of the species' range has not been assessed, and there is concern that it may be at risk of extinction without protection. The U.S. Fish and Wildlife Service requires scientific information of the species' status to inform conservation decisions. There is little empirical information available from P. rubriventris populations and, furthermore, the majority of what exists comes from the disjunct northern subpopulation. To fill data gaps in the species' life history and reduce geographic bias, we supplement available data from P. rubriventris with demographic rate estimates from other Pseudemys species to parameterize an age-structured population projection model. Our estimate of mean population growth rate was 0.987 (0.92–1.04), indicating that P. rubriventris populations may be in decline. However, there was considerable uncertainty in our results, with 35% of projections resulting in stable or increasing populations. Additional uncertainty about parameter values, geographic variation, and current threats limit the assessment. We discuss the merits and limitations of our population projection modeling (PPM) approach where other analytical methods are precluded by lack of available data.
","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","doi":"10.1670/21-065","usgsCitation":"Fleming, J.E., Moore, J.F., Waddle, H., Martin, J., and Campbell Grant, E.H., 2022, Range-wide population projections for Northern Red-Bellied Cooters (Pseudemys rubriventris): Journal of Herpetology, v. 56, no. 3, p. 362-369, https://doi.org/10.1670/21-065.","productDescription":"8 p.","startPage":"362","endPage":"369","ipdsId":"IP-130062","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":408028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Massachusetts, New Jersey, North Carolina, Pennsylvania, Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.332763671875,\n 34.551811369170494\n ],\n [\n -76.607666015625,\n 34.6241677899049\n ],\n [\n -76.201171875,\n 34.831841149828655\n ],\n [\n -75.399169921875,\n 35.23664622093195\n ],\n [\n -75.322265625,\n 35.47856499535729\n ],\n [\n -75.377197265625,\n 35.84453450421662\n ],\n [\n -75.83862304687499,\n 37.046408899699564\n ],\n [\n -74.970703125,\n 38.26406296833961\n ],\n [\n -74.981689453125,\n 38.65119833229951\n ],\n [\n -74.827880859375,\n 38.8824811975508\n ],\n [\n -74.168701171875,\n 39.58029027440865\n ],\n [\n -73.80615234375,\n 40.33817045213394\n ],\n [\n -74.1357421875,\n 40.49709237269567\n ],\n [\n -77.750244140625,\n 40.75557964275589\n ],\n [\n -79.332275390625,\n 39.715638134796336\n ],\n [\n -79.595947265625,\n 38.59970036588819\n ],\n [\n -78.134765625,\n 35.71975793933433\n ],\n [\n -77.332763671875,\n 34.551811369170494\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.202392578125,\n 41.72213058512578\n ],\n [\n -70.499267578125,\n 41.72213058512578\n ],\n [\n -70.499267578125,\n 42.27730877423709\n ],\n [\n -71.202392578125,\n 42.27730877423709\n ],\n [\n -71.202392578125,\n 41.72213058512578\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fleming, Jillian Elizabeth 0000-0003-2570-914X","orcid":"https://orcid.org/0000-0003-2570-914X","contributorId":238931,"corporation":false,"usgs":true,"family":"Fleming","given":"Jillian","email":"","middleInitial":"Elizabeth","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":853940,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Jennifer F.","contributorId":189122,"corporation":false,"usgs":false,"family":"Moore","given":"Jennifer","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":853941,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waddle, Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":206866,"corporation":false,"usgs":true,"family":"Waddle","given":"Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":853942,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":216734,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":853943,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":853944,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237558,"text":"70237558 - 2022 - Multispecies approaches to status assessments in support of endangered species classifications","interactions":[],"lastModifiedDate":"2022-11-16T17:13:33.687452","indexId":"70237558","displayToPublicDate":"2022-10-05T11:53:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Multispecies approaches to status assessments in support of endangered species classifications","docAbstract":"Multispecies risk assessments have developed within many international conservation programs, reflecting a widespread need for efficiency. Under the United States Endangered Species Act (ESA), multispecies assessments ultimately lead to species-level listing decisions. Although this approach provides opportunities for improved efficiency, it also risks overwhelming or biasing the assessment process and would benefit from clear guidance for practitioners. We reviewed multispecies assessments conducted between 1993 and 2019 for ESA listing decisions to identify the ecological basis for combining species, the assessment approach used, and the policy factors influencing their efficacy. We identified 42 cases covering 359 species. Most assessments (81%) included two to five species, although the maximum was 82. A common theme involved grouping narrow endemics or habitat specialists based on taxonomic relatedness, similar distributions, and common threats to persistence. All assessments included a combined threats analysis, but few employed a common species' response model or expert elicitation process. Although ESA risk assessments are distinct from policy decisions, most assessments (50%) supported decisions that all species warranted endangered status. Available guidance has generally emphasized ecological similarity as the key attribute leading to successful multispecies assessments. The challenge with consistently selecting species based on qualitative proxies such as common distributions or threats to persistence is that ecological patterns and processes are scale dependent. Focusing instead on the assessment methods and their potential for bias and increased efficiency may provide a stronger basis for developing consistent and transparent guidance.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.12825","usgsCitation":"Fitzgerald, D.B., Freeman, M., Maloney, K.O., Young, J.A., Rosenberger, A.E., Kazyak, D., and Smith, D.R., 2022, Multispecies approaches to status assessments in support of endangered species classifications: Conservation Science and Practice, v. 4, no. 11, e12825, 11 p., https://doi.org/10.1111/csp2.12825.","productDescription":"e12825, 11 p.","ipdsId":"IP-127956","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446217,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.12825","text":"Publisher Index Page"},{"id":408261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzgerald, Daniel Bruce 0000-0002-3254-7428","orcid":"https://orcid.org/0000-0002-3254-7428","contributorId":245718,"corporation":false,"usgs":true,"family":"Fitzgerald","given":"Daniel","email":"","middleInitial":"Bruce","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":854455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854457,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854458,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854459,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854460,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70238634,"text":"70238634 - 2022 - Regional models do not outperform continental models for invasive species","interactions":[],"lastModifiedDate":"2022-12-02T13:01:29.078063","indexId":"70238634","displayToPublicDate":"2022-10-04T07:00:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5071,"text":"NeoBiota","active":true,"publicationSubtype":{"id":10}},"title":"Regional models do not outperform continental models for invasive species","docAbstract":"Aim: Species distribution models can guide invasive species prevention and management by characterizing invasion risk across space. However, extrapolation and transferability issues pose challenges for developing useful models for invasive species. Previous work has emphasized the importance of including all available occurrences in model estimation, but managers attuned to local processes may be skeptical of models based on a broad spatial extent if they suspect the captured responses reflect those of other regions where data are more numerous. We asked whether species distribution models for invasive plants performed better when developed at national versus regional extents.
Location: Continental United States.
Methods: We developed ensembles of species distribution models trained nationally, on sagebrush habitat, or on sagebrush habitat within three ecoregions (Great Basin, eastern sagebrush, and Great Plains) for nine invasive plants of interest for early detection and rapid response at local or regional scales. We compared the performance of national versus regional models using spatially independent withheld test data from each of the three ecoregions.
Results: We found that models trained using a national spatial extent tended to perform better than regionally trained models. Regional models did not outperform national ones even when considerable occurrence data were available for model estimation within the focal region. Information was often unavailable to fit informative regional models precisely in those areas of greatest interest for early detection and rapid response.
Main conclusions: Habitat suitability models for invasive plant species trained at a continental extent can reduce extrapolation while maximizing information on species’ responses to environmental variation. Standard modeling methods can capture spatially varying limiting factors, while regional or hierarchical models may only be advantageous when populations differ in their responses to environmental conditions, a condition expected to be relatively rare at the expanding boundaries of invasive species’ distributions.
","language":"English","publisher":"NeoBiota","doi":"10.3897/neobiota.77.86364","usgsCitation":"Jarnevich, C.S., Sofaer, H., Engelstad, P., and Belamaric, P., 2022, Regional models do not outperform continental models for invasive species: NeoBiota, v. 77, https://doi.org/10.3897/neobiota.77.86364.","productDescription":"22 p.","startPage":"1-22","ipdsId":"IP-137001","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":446233,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/neobiota.77.86364","text":"Publisher Index Page"},{"id":435667,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90AL0PN","text":"USGS data release","linkHelpText":"Data to create and evaluate distribution models for invasive species for different geographic extents"},{"id":409981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"77","noUsgsAuthors":false,"publicationDate":"2022-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sofaer, Helen R. 0000-0002-9450-5223","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":216681,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858157,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Engelstad, Peder","contributorId":238758,"corporation":false,"usgs":false,"family":"Engelstad","given":"Peder","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":858158,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belamaric, Pairsa 0000-0001-7529-0370","orcid":"https://orcid.org/0000-0001-7529-0370","contributorId":299593,"corporation":false,"usgs":false,"family":"Belamaric","given":"Pairsa","affiliations":[{"id":64897,"text":"Student Contractor to the USGS Fort Collins Science Center","active":true,"usgs":false}],"preferred":false,"id":858159,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70246290,"text":"70246290 - 2022 - Use of regional breeding bird surveys to estimate bird populations in Big Thicket National Preserve","interactions":[],"lastModifiedDate":"2023-06-30T11:51:09.714357","indexId":"70246290","displayToPublicDate":"2022-10-04T06:49:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5991,"text":"The Southwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Use of regional breeding bird surveys to estimate bird populations in Big Thicket National Preserve","docAbstract":"We used data collected during surveys of seven North American Breeding Bird Survey routes in eastern Texas to estimate avian populations within Big Thicket National Preserve. On only 61 of the 350 count locations located along these routes did observers monitor birds within the boundaries of this preserve. On selected routes, we recorded initial bird detections during the 3-min bird count within 1-min time intervals and within two distance classes (≤50 or >50 m). We used these data, combined with data collected using standard Breeding Bird Survey protocols during 2009–2016, to estimate detection probabilities and effective detection radii for commonly detected species. For species often detected in flocks, we estimated these parameters for group detections. From these parameters, we estimated regional densities for 60 species. Because habitat within Big Thicket National Preserve differed from habitat along surveyed routes, for each species we adjusted the projected population estimate to account for the relationship between density of detected birds and habitat descriptors from the National Land Cover database. On the basis of our estimates of regional density of each species, and accounting for differences in habitat availability, we estimated that commonly detected avian species comprises a population of 192,201 breeding birds (95% confidence interval = 144,269–340,790) within Big Thicket National Preserve.
","language":"English","publisher":"BioOne","doi":"10.1894/0038-4909-66.3.240","usgsCitation":"Twedt, D.J., and Shackelford, C.E., 2022, Use of regional breeding bird surveys to estimate bird populations in Big Thicket National Preserve: The Southwestern Naturalist, v. 66, no. 3, p. 240-249, https://doi.org/10.1894/0038-4909-66.3.240.","productDescription":"10 p.","startPage":"240","endPage":"249","ipdsId":"IP-065568","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":418650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Big Thicket National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.4910453710765,\n 30.60117874378041\n ],\n [\n -94.4910453710765,\n 30.35392517388506\n ],\n [\n -94.20415064179676,\n 30.35392517388506\n ],\n [\n -94.20415064179676,\n 30.60117874378041\n ],\n [\n -94.4910453710765,\n 30.60117874378041\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"66","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Twedt, Daniel J. 0000-0003-1223-5045 dtwedt@usgs.gov","orcid":"https://orcid.org/0000-0003-1223-5045","contributorId":398,"corporation":false,"usgs":true,"family":"Twedt","given":"Daniel","email":"dtwedt@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":876669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shackelford, Clifford E.","contributorId":315488,"corporation":false,"usgs":false,"family":"Shackelford","given":"Clifford","email":"","middleInitial":"E.","affiliations":[{"id":68340,"text":"Texas Parks and Wildlife Department, 506 Hayter St., Nacogdoches, Texas 75965","active":true,"usgs":false}],"preferred":false,"id":876670,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237254,"text":"70237254 - 2022 - Barrier islands influence the assimilation of terrestrial energy in nearshore fishes","interactions":[],"lastModifiedDate":"2023-03-24T16:26:50.745968","indexId":"70237254","displayToPublicDate":"2022-10-03T06:35:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12614,"text":"Estuarine, Costal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Barrier islands influence the assimilation of terrestrial energy in nearshore fishes","docAbstract":"We examined the relative importance of landscape features on estuarine fish trophic structure and dependence on terrestrial organic matter (OMterr) in four barrier island lagoon systems along the Alaskan Beaufort Sea coast. Our study compared two relatively large lagoon systems characterized by high river discharge and relatively free ocean water exchanges (central region near Prudhoe Bay, Alaska) with two highly protected lagoons characterized by low river discharge and limited exchange with ocean waters (eastern region near Kaktovik, Alaska). We hypothesized that freshwater discharge would be a strong determinant of food web structure for both resident marine and diadromous fishes if more discharge increases availability of OMterr relative to lagoons with limited or no river inputs. To consider differences in trophic characteristics in fishes between study regions, we estimated community-wide measures of trophic structure (hereafter, community metrics) and the relative use of OMterr from mixing models using stable isotope composition (δ13C and δ15N; muscle tissue) among 12 species and identified the influences of region and body size. Fish captured in lagoons well protected by barrier islands had more distinct and diverse isotopic niches relative to those in more exposed lagoons based on community metrics. The use of OMterr by nearshore fishes in both regions was substantial and was >50% for diadromous species. Between regions, OMterr use differed in 6 of the 8 species considered but was not consistently higher in one region. The relative importance of OMterr varied with fish size in 7 of 10 species considered, with more OMterr used by smaller individuals. This work highlights the importance of OMterr to Arctic fishes and fisheries, some of which are of subsistence importance, even when feeding grounds are primarily marine. We propose that landscape features, particularly barrier islands, play an important role in structuring nearshore food webs. Barrier islands may provide a previously undocumented ecosystem service of increasing food web complexity, which may promote system resilience.