Chemically, petroleum is an extraordinarily complex mixture of different types of hydrocarbons that are now possible to isolate and identify because of advances in geochemistry. Here, we use biomarkers and carbon isotopes to establish genetic differences and similarities among oil samples. Conventional approaches for evaluating biomarker and carbon isotope relative abundances include statistical techniques such as principal component and cluster analysis. Considering that proportions of the different hydrocarbon molecules are relative parts of a laboratory sample, the data are compositional in nature, thus requiring the use of log-ratio approaches for adequate mathematical modeling. We apply both traditional and compositional modeling approaches to crude oil samples from an onshore area of about 50,000 square miles in southeast Texas. The data comprise 177 crude oil samples from producing oil fields that include key biomarkers, elemental, and isotopic values commonly used in source rock correlation studies. Our results indicate that compositional modeling has higher discriminating power and lower uncertainty than the traditional approach, allowing the identification of up to 16 clusters. Each cluster represents one oil family from a source rock organofacies ranging from Carboniferous to Paleogene. The families provide new insights into important petroleum systems in the Texas onshore region of the Gulf of Mexico sedimentary basin.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Advances in compositional data analysis—Festschrift in honor of Vera-Pawlowsky-Glahn","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-71175-7_16","usgsCitation":"Olea, R., Martin-Fernandez, J.A., and Craddock, W.H., 2021, Multivariate classification of the crude oil petroleum systems in southeast Texas, USA, using conventional and compositional data analysis of biomarkers, chap. of Advances in compositional data analysis—Festschrift in honor of Vera-Pawlowsky-Glahn, p. 303-307, https://doi.org/10.1007/978-3-030-71175-7_16.","productDescription":"5 p.","startPage":"303","endPage":"307","ipdsId":"IP-112995","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":387163,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.119140625,\n 25.97779895546436\n ],\n [\n -96.767578125,\n 27.68352808378776\n ],\n [\n -95.11962890625,\n 28.497660832963472\n ],\n [\n -93.8232421875,\n 29.49698759653577\n ],\n [\n -93.97705078125,\n 30.20211367909724\n ],\n [\n -95.55908203125,\n 30.240086360983426\n ],\n [\n -97.3388671875,\n 28.9600886880068\n ],\n [\n -98.23974609375,\n 27.586197857692664\n ],\n [\n -97.91015624999999,\n 26.13571361317392\n ],\n [\n -97.119140625,\n 25.97779895546436\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2021-06-02","publicationStatus":"PW","contributors":{"editors":[{"text":"Fitzmoser, Peter","contributorId":261055,"corporation":false,"usgs":false,"family":"Fitzmoser","given":"Peter","email":"","affiliations":[],"preferred":false,"id":819247,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Hron, Karel","contributorId":261056,"corporation":false,"usgs":false,"family":"Hron","given":"Karel","email":"","affiliations":[],"preferred":false,"id":819248,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Martin-Fernandez, Josep Antoni","contributorId":208528,"corporation":false,"usgs":false,"family":"Martin-Fernandez","given":" Josep Antoni","affiliations":[],"preferred":false,"id":819249,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Palarea-Albaladejo, Javier","contributorId":120518,"corporation":false,"usgs":true,"family":"Palarea-Albaladejo","given":"Javier","email":"","affiliations":[],"preferred":false,"id":819250,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":224285,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":819213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin-Fernandez, J. A 0000-0003-2366-1592","orcid":"https://orcid.org/0000-0003-2366-1592","contributorId":260957,"corporation":false,"usgs":false,"family":"Martin-Fernandez","given":"J.","email":"","middleInitial":"A","affiliations":[{"id":28183,"text":"University of Girona","active":true,"usgs":false}],"preferred":false,"id":819214,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Craddock, William H. 0000-0002-4181-4735 wcraddock@usgs.gov","orcid":"https://orcid.org/0000-0002-4181-4735","contributorId":3411,"corporation":false,"usgs":true,"family":"Craddock","given":"William","email":"wcraddock@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":819215,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221088,"text":"ds1138 - 2021 - Distribution and demography of coastal cactus wrens (Campylorhynchus brunneicapillus) in southern San Diego County, California—2020 data summary","interactions":[],"lastModifiedDate":"2021-06-02T11:41:30.374625","indexId":"ds1138","displayToPublicDate":"2021-06-01T13:17:25","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1138","displayTitle":"Distribution and Demography of Coastal Cactus Wrens (Campylorhynchus brunneicapillus) in Southern San Diego County, California—2020 Data Summary","title":"Distribution and demography of coastal cactus wrens (Campylorhynchus brunneicapillus) in southern San Diego County, California—2020 data summary","docAbstract":"Surveys for coastal Cactus Wren (Campylorhynchus brunneicapillus) were done in 378 established plots in southern San Diego County in 2020, encompassing three genetic clusters (Otay, Lake Jennings, and Sweetwater/Encanto genetic clusters). Two surveys were completed at each plot between March 1 and July 31. Cactus Wrens were detected in 131 plots (35 percent of plots). This is a slight increase over the proportion of occupied plots in 2019. One hundred and nine Cactus Wren territories were detected across all survey plots in 2020, an increase from 83 in 2019. At least 85 percent of Cactus Wren territories were occupied by pairs, and 62 fledglings were observed in 2020.
There were 89 color-banded Cactus Wrens observed in 2020, 84 of which we could identify to individual. Adults of known age ranged from 1 to at least 6 years old. Adult Cactus Wrens moved on average 0.2 kilometers (km; maximum 3.8 km) from their 2019 territories to their 2020 territories. Cactus Wrens that fledged in 2019 moved on average 1.2 km (maximum 9.9 km) to their 2020 territories. No known-identity Cactus Wrens moved between genetic clusters from 2019 to 2020.
Vegetation at Cactus Wren plots typically was dominated by coastal sage scrub shrubs such as California sagebrush (Artemisia californica), lemonadeberry (Rhus integrifolia), California buckwheat (Eriogonum fasciculatum), and broom baccharis (Baccharis sarothroides). Very little dead or unhealthy cactus was observed within Cactus Wren survey plots. Thirty-eight percent of plots had at least 25 percent of the cactus crowded or overtopped by vines and shrubs. Non-native annual cover was greater than 25 percent at 35 percent of plots.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1138","usgsCitation":"Lynn, S., and Kus, B.E., 2021, Distribution and demography of coastal cactus wrens (Campylorhynchus brunneicapillus) in southern San Diego County, California—2020 data summary: U.S. Geological Survey Data Series 1138, 12 p., https://doi.org/10.3133/ds1138.","productDescription":"Report: vi, 12 p.; Data Release","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-126296","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":386066,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76H4FK5","linkHelpText":"Surveys and Monitoring of Coastal Cactus Wren in Southern San Diego County"},{"id":386065,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/ds/1138/images"},{"id":386064,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/ds/1138/ds1138.xml"},{"id":386063,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1138/ds1138.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":386062,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1138/covrthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Southern San Diego County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.32299804687499,\n 32.48196313217176\n ],\n [\n -116.7132568359375,\n 32.48196313217176\n ],\n [\n -116.7132568359375,\n 32.8334428466495\n ],\n [\n -117.32299804687499,\n 32.8334428466495\n ],\n [\n -117.32299804687499,\n 32.48196313217176\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The Greater Yellowstone Area (GYA) is one of the last remaining large and nearly intact temperate ecosystems on Earth. GYA was originally defined in the 1970s as the Greater Yellowstone Ecosystem, which encompassed the minimum range of the grizzly bear. The boundary now includes about 22 million acres (8.9 million ha) in northwestern Wyoming, south central Montana, and eastern Idaho (Figure ES-1). Two national parks, five national forests, three wildlife refuges, 20 counties, and state and private lands lie within the GYA boundary (Figure ES-1). The Tribal Nations of the Eastern Shoshone, Northern Arapaho, Apsa´alooke/Crow, Northern Cheyenne, Shoshone, and Bannock have reservations in and near the Greater Yellowstone Area, and 27 Tribes are formally recognized to have historical connections to the lands and resources of the region. Natural resources sensitive to climate change connect many of the major economic activities of the GYA, including tourism and recreation, agriculture, and energy development.
","language":"English","publisher":"Montana State University","doi":"10.15788/GYCA2021","usgsCitation":"Hostetler, S.W., Whitlock, C., Shuman, B., Liefert, D., Wolf Drimal, C., and Bischke, S., 2021, Greater Yellowstone climate assessment: Past, present, and future climate change in the greater Yellowstone watersheds: Greater Yellowstone Climate Assessment, 218 p., https://doi.org/10.15788/GYCA2021.","productDescription":"218 p.","ipdsId":"IP-127170","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":452032,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15788/gyca2021","text":"Publisher Index Page"},{"id":436330,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P972JAUC","text":"USGS data release","linkHelpText":"Data release for Greater Yellowstone Climate Assessment (vol 1), Chapter 7. Future Water Projections for the GYA"},{"id":397116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone watersheds","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.54394531249999,\n 42.09822241118974\n ],\n [\n -108.2373046875,\n 42.09822241118974\n ],\n [\n -108.2373046875,\n 45.9511496866914\n ],\n [\n -112.54394531249999,\n 45.9511496866914\n ],\n [\n -112.54394531249999,\n 42.09822241118974\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2021-06-23","publicationStatus":"PW","contributors":{"editors":[{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":837847,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":837848,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":837841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whitlock, Cathy","contributorId":79745,"corporation":false,"usgs":false,"family":"Whitlock","given":"Cathy","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":837842,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shuman, Bryan","contributorId":205232,"corporation":false,"usgs":false,"family":"Shuman","given":"Bryan","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":837843,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liefert, David 0000-0001-7682-6835","orcid":"https://orcid.org/0000-0001-7682-6835","contributorId":288395,"corporation":false,"usgs":false,"family":"Liefert","given":"David","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":837844,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolf Drimal, Charles","contributorId":288398,"corporation":false,"usgs":false,"family":"Wolf Drimal","given":"Charles","email":"","affiliations":[{"id":61749,"text":"Greater Yellowstone Coalition","active":true,"usgs":false}],"preferred":false,"id":837845,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bischke, Scott","contributorId":288399,"corporation":false,"usgs":false,"family":"Bischke","given":"Scott","email":"","affiliations":[{"id":61752,"text":"Mountain Works","active":true,"usgs":false}],"preferred":false,"id":837846,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70255078,"text":"70255078 - 2021 - Modeling opportunistic exploitation: Increased extinction risk when targeting more than one species","interactions":[],"lastModifiedDate":"2024-06-12T16:51:25.835725","indexId":"70255078","displayToPublicDate":"2021-06-01T11:48:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Modeling opportunistic exploitation: Increased extinction risk when targeting more than one species","docAbstract":"Extinction rates are increasing globally, and direct exploitation is an important driver. Many pathways have been proposed to explain how exploitation can lead to extinction. One of these proposed but understudied multispecies pathways is opportunistic exploitation, which occurs when a highly valuable but rare species is encountered and targeted during exploitation of a less valuable, but more common, target species. Using individual-based simulations of exploiters in a two-species spatial model, we contribute evidence which supports that opportunistic exploitation increases depletion when compared to single-species exploitation, and is as detrimental to the more valuable, rare species as the anthropogenic Allee effect (where price increases with rarity) and the Allee effect (where population growth declines at low abundance). The most important factors affecting the impact of opportunistic exploitation are gross revenue and abundance of the more common, less valuable species, while ease of capture and growth rate of the more common, less valuable species are less important. Thus, valuable but rare species are most at risk when harvested alongside low-value abundant species; this information is relevant for managers focused on protection of rare species in multispecies systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2021.109611","usgsCitation":"Thurner, S., Converse, S.J., and Branch, T., 2021, Modeling opportunistic exploitation: Increased extinction risk when targeting more than one species: Ecological Modelling, v. 454, 109611, 12 p., https://doi.org/10.1016/j.ecolmodel.2021.109611.","productDescription":"109611, 12 p.","ipdsId":"IP-126753","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":452034,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2021.109611","text":"Publisher Index Page"},{"id":430024,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"454","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thurner, S.","contributorId":338523,"corporation":false,"usgs":false,"family":"Thurner","given":"S.","email":"","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":903328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":903329,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Branch, Trevor A.","contributorId":172088,"corporation":false,"usgs":false,"family":"Branch","given":"Trevor A.","affiliations":[],"preferred":false,"id":903330,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219911,"text":"70219911 - 2021 - Fisheries research and monitoring activities of the Lake Erie Biological Station, 2020","interactions":[],"lastModifiedDate":"2021-09-17T16:44:29.465926","indexId":"70219911","displayToPublicDate":"2021-06-01T11:44:02","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":8434,"text":"Lake Erie Biological Station Annual Report","active":true,"publicationSubtype":{"id":4}},"title":"Fisheries research and monitoring activities of the Lake Erie Biological Station, 2020","docAbstract":"This report presents biomass-based summaries of fish communities in the West Basin of Lake Erie derived from USGS bottom trawl surveys conducted from 2013 to 2020 during June and September. The survey design provided temporal and spatial coverage that did not exist in the interagency trawl database, and thus complemented the August ODNR-OMNRF effort to reinforce stock assessments with more robust data. Analyses herein evaluated trends in: total biomass, abundance of dominant predator and forage species, non-native species composition, biodiversity and community structure. Data from this effort can be explored interactively online\n(https://lebs.shinyapps.io/western-basin/), and are accessible for download (https://www.sciencebase.gov/catalog/item/6013031fd34e162231fed756, Keretz et al. 2021). Annual survey data are added to these sources as the data become available.","language":"English","publisher":"U.S. Geological Survey","usgsCitation":"Keretz, K.R., Kocovsky, P., Kraus, R., Roberts, J., and Schmitt, J., 2021, Fisheries research and monitoring activities of the Lake Erie Biological Station, 2020: Lake Erie Biological Station Annual Report, 12 p.","productDescription":"12 p.","ipdsId":"IP-126685","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":389405,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":389403,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.sealamprey.org/pubs/lake_committees/common_docs/2020%20LEC%20report_Final.pdf"}],"country":"Canada, United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": 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pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":814381,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":814382,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roberts, James 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":814383,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmitt, Joseph 0000-0002-8354-4067","orcid":"https://orcid.org/0000-0002-8354-4067","contributorId":221020,"corporation":false,"usgs":true,"family":"Schmitt","given":"Joseph","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":814384,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220465,"text":"70220465 - 2021 - Status and trends of pelagic and benthic prey fish populations in Lake Michigan, 2020","interactions":[],"lastModifiedDate":"2021-09-17T16:15:30.362165","indexId":"70220465","displayToPublicDate":"2021-06-01T11:13:08","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":9350,"text":"Lake Michigan Forage Report","active":true,"publicationSubtype":{"id":3}},"title":"Status and trends of pelagic and benthic prey fish populations in Lake Michigan, 2020","docAbstract":"Lakewide acoustic (AC) and bottom trawl (BT) surveys are conducted annually to generate indices of pelagic and benthic prey fish densities in Lake Michigan. The BT survey had been conducted each fall from 1973 through 2019 using 12-m trawls at depths ranging from 9 to 110 m and included 70 fixed locations distributed across seven transects; this survey estimates densities of seven prey fish species (i.e., alewife, bloater, rainbow smelt, deepwater sculpin, slimy sculpin, round goby, ninespine stickleback) as well as for age-0 yellow perch and large burbot. The AC survey, which serves to estimate densities of three prey fish species (i.e., alewife, bloater, and rainbow smelt), had been conducted each late summer/early fall from 2004-2019. The data generated from these surveys are used to estimate various population parameters that are, in turn, used by state and tribal agencies in managing Lake Michigan fish stocks. \n\nThe 2020 COVID-19 pandemic severely limited the Lake Michigan pelagic and benthic prey fish surveys. While the AC survey was not conducted, 32 tows across three of seven standard BT transects (Saugatuck, Waukegan and Port Washington) were completed during an abbreviated survey. Total prey fish biomass density from the abbreviated BT survey was 1.91 kg/ha, continuing a recent trend of historically low estimates below the long-term (i.e., 1973-2020) average of 34.94 kg/ha. Mean biomass of yearling and older (YAO) alewives in 2020 was 0.025 ± 0.017 kg/ha, tied for the lowest ever recorded on the BT survey. No age-0 alewife were captured in the bottom trawl and of the limited number (n=16) of alewife collected, none were older than age four. Bloater (1.39 kg/ha) and deepwater sculpin (0.47 kg/ha) accounted for greatest proportion of biomass in the BT survey, while biomass density of slimy sculpin, round goby and rainbow smelt were all ≤ 0.01 kg/ha. While caution must be taken when interpreting the results of the abbreviated BT survey, the estimates suggest that prey fish densities remain well below historical values.","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Tingley, R.W., Bunnell, D.B., Warner, D., Madenjian, C.P., and Dieter, P., 2021, Status and trends of pelagic and benthic prey fish populations in Lake Michigan, 2020: Lake Michigan Forage Report, 19 p.","productDescription":"19 p.","ipdsId":"IP-127217","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":389398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":389397,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.glfc.org/pubs/lake_committees/common_docs/LM_Forage_Report_2021_For_Dissemination.pdf"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n 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Less known, are the contributions these wolves make to scientific research. Recently the Center’s Exhibit Pack were subjects of behavioral and acoustic research.
","language":"English","publisher":"International Wolf Center","usgsCitation":"Barber-Meyer, S., Schmidt, L., Palacios, V., and Marti-Domken, B., 2021, Ambassador wolves participate In scientific research: International Wolf, v. 2021, no. Summer, p. 4-8.","productDescription":"5 p.","startPage":"4","endPage":"8","ipdsId":"IP-125450","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":396796,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396794,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://wolf.org/wolf-info/wolf-magazine/summer-2021/"}],"volume":"2021","issue":"Summer","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barber-Meyer, Shannon 0000-0002-3048-2616","orcid":"https://orcid.org/0000-0002-3048-2616","contributorId":217939,"corporation":false,"usgs":true,"family":"Barber-Meyer","given":"Shannon","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":816587,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, Lori","contributorId":192924,"corporation":false,"usgs":false,"family":"Schmidt","given":"Lori","affiliations":[],"preferred":false,"id":816588,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palacios, Vicente","contributorId":73043,"corporation":false,"usgs":true,"family":"Palacios","given":"Vicente","email":"","affiliations":[],"preferred":false,"id":816589,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marti-Domken, Barbara","contributorId":288087,"corporation":false,"usgs":false,"family":"Marti-Domken","given":"Barbara","affiliations":[],"preferred":false,"id":816590,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70229042,"text":"70229042 - 2021 - Diel patterns of predation and fledging at nests of four species of grassland songbirds","interactions":[],"lastModifiedDate":"2022-02-28T17:09:30.743422","indexId":"70229042","displayToPublicDate":"2021-06-01T10:56:56","publicationYear":"2021","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":"Diel patterns of predation and fledging at nests of four species of grassland songbirds","docAbstract":"Although it is common for nestlings to exhibit a strong bias for fledging in the morning, the mechanisms underlying this behavior are not well understood. Avoiding predation risk has been proposed as a likely mechanism by a number of researchers. We used video surveillance records from studies of grassland birds nesting in North Dakota, Minnesota, and Wisconsin to determine the diel pattern of nest predation and fledging patterns of four ground-nesting obligate grassland passerines (Grasshopper Sparrow (Ammodramus savannarum), Savannah Sparrow (Passerculus sandwichensis), Bobolink (Dolichonyx oryzivorus), and Eastern Meadowlark (Sturnella magna)). We used the nest predation pattern as a surrogate for predation activity to test whether nestlings minimized predation risk by avoiding fledging when predation activity was high and preferentially fledging when predation risk was low. Predation activity was significantly lower starting 3 hr before sunrise and ending 3 hr after sunrise, followed by a transition to a period of significantly higher activity lasting for 4 hr, before declining to an average activity level for the rest of the diel period. There was little evidence that the four grassland bird species avoided fledging during the high-risk period and Savannah Sparrow fledged at higher rates during that period. All four species had hours during the low-risk period where they fledged at higher rates, but only Grasshopper Sparrow fledged preferentially during that period. Bobolink and Eastern Meadowlark had multiple hours with high fledging rates throughout the daytime period, resulting in no relationship between probability of fledging and predation risk. Given the species variability in fledging pattern seen in our study, it is unlikely that there is a universal response to any driver that affects time of fledging. Further study is needed to understand the complex interplay between species ecology and drivers such as physiology, energetics, and predation in affecting grassland bird fledging behavior.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7541","usgsCitation":"Ribic, C., Rugg, D.J., Ellison, K., Koper, N., and Pietz, P.J., 2021, Diel patterns of predation and fledging at nests of four species of grassland songbirds: Ecology and Evolution, v. 11, no. 11, p. 6913-6926, https://doi.org/10.1002/ece3.7541.","productDescription":"14 p.","startPage":"6913","endPage":"6926","ipdsId":"IP-120613","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":452037,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.7541","text":"Publisher Index Page"},{"id":396566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, North Dakota, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.085693359375,\n 46.707852594536355\n ],\n [\n -98.31390380859375,\n 46.707852594536355\n ],\n [\n -98.31390380859375,\n 47.04766864046083\n ],\n [\n -99.085693359375,\n 47.04766864046083\n ],\n [\n -99.085693359375,\n 46.707852594536355\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.49630737304688,\n 47.05983195515023\n ],\n [\n -99.08843994140625,\n 47.05983195515023\n ],\n [\n -99.08843994140625,\n 47.24381345414034\n ],\n [\n -99.49630737304688,\n 47.24381345414034\n ],\n [\n -99.49630737304688,\n 47.05983195515023\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.00830078125,\n 48.50295743049266\n ],\n [\n -100.43289184570312,\n 48.50295743049266\n ],\n [\n -100.43289184570312,\n 48.672826384100354\n ],\n [\n -101.00830078125,\n 48.672826384100354\n ],\n [\n -101.00830078125,\n 48.50295743049266\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.7730712890625,\n 47.711609647845975\n ],\n [\n -96.4874267578125,\n 47.711609647845975\n ],\n [\n -96.4874267578125,\n 47.830674012109434\n ],\n [\n -96.7730712890625,\n 47.830674012109434\n ],\n [\n -96.7730712890625,\n 47.711609647845975\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.80361938476562,\n 42.96245265666877\n ],\n [\n -89.68276977539062,\n 42.96245265666877\n ],\n [\n -89.68276977539062,\n 43.04881979669318\n ],\n [\n -89.80361938476562,\n 43.04881979669318\n ],\n [\n -89.80361938476562,\n 42.96245265666877\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":836346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rugg, David J.","contributorId":171931,"corporation":false,"usgs":false,"family":"Rugg","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":836347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellison, Kevin","contributorId":274390,"corporation":false,"usgs":false,"family":"Ellison","given":"Kevin","affiliations":[{"id":37767,"text":"World Wildlife Fund","active":true,"usgs":false}],"preferred":false,"id":836348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koper, Nicola","contributorId":274389,"corporation":false,"usgs":false,"family":"Koper","given":"Nicola","affiliations":[{"id":16603,"text":"University of Manitoba","active":true,"usgs":false}],"preferred":false,"id":836349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pietz, Pamela J. 0000-0003-4606-044X","orcid":"https://orcid.org/0000-0003-4606-044X","contributorId":286892,"corporation":false,"usgs":true,"family":"Pietz","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":836350,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229037,"text":"70229037 - 2021 - Life-history theory provides a framework for detecting resource limitation: A test of the Nutritional Buffer Hypothesis","interactions":[],"lastModifiedDate":"2022-02-28T16:56:07.198194","indexId":"70229037","displayToPublicDate":"2021-06-01T10:43:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Life-history theory provides a framework for detecting resource limitation: A test of the Nutritional Buffer Hypothesis","docAbstract":"For ungulates and other long-lived species, life-history theory predicts that nutritional reserves are allocated to reproduction in a state-dependent manner because survival is highly conserved. Further, as per capita food abundance and nutritional reserves decline (i.e., density dependence intensifies), reproduction and recruitment become increasingly sensitive to weather. Thus, the degree to which weather influences vital rates should be associated with proximity to nutritional carrying capacity—a notion that we refer to as the Nutritional Buffer Hypothesis. We tested the Nutritional Buffer Hypothesis using six moose (Alces alces) populations that varied in calf recruitment (33–69 calves/100 cows). We predicted that populations with high calf recruitment were nutritionally buffered against the effects of unfavorable weather, and thus were below nutritional carrying capacity. We applied a suite of tools to quantify habitat and nutritional condition of each population and found that increased browse condition, forage quality, and body fat were associated with increased pregnancy and calf recruitment, thereby providing multiple lines of evidence that declines in calf recruitment were underpinned by resource limitation. From 2001 to 2015, recruitment was more sensitive to interannual variation in weather (e.g., winter severity, drought) and plant phenology (e.g., duration of spring) for populations with reduced browse condition, forage quality, and body fat, suggesting these populations lacked the nutritional reserves necessary to buffer demographic performance against the effects of unfavorable weather. Further, average within-population calf recruitment was determined by regional climatic variation, suggesting that the pattern of reduced recruitment near the southern range boundary of moose stems from an interaction between climate and resource limitation. When coupled with information on habitat, nutrition, weather, and climate, life-history theory provides a framework to estimate nutritional limitation, proximity to nutritional carrying capacity, and impacts of climate change for ungulates.
","language":"English","publisher":"Wiley","doi":"10.1002/eap.2299","usgsCitation":"Jesmer, B.R., Kauffman, M., Courtemanch, A.B., Kilpatrick, S., Thomas, T., Yost, J., Monteith, K.L., and Goheen, J.R., 2021, Life-history theory provides a framework for detecting resource limitation: A test of the Nutritional Buffer Hypothesis: Ecological Applications, v. 31, no. 4, p. 1-18, https://doi.org/10.1002/eap.2299.","productDescription":"e02299, 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-123651","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":452040,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/eap.2299","text":"External Repository"},{"id":396564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.11572265625,\n 38.51378825951165\n ],\n [\n -104.08447265624999,\n 38.51378825951165\n ],\n [\n -104.08447265624999,\n 45.042478050891546\n ],\n [\n -111.11572265625,\n 45.042478050891546\n ],\n [\n -111.11572265625,\n 38.51378825951165\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-03-08","publicationStatus":"PW","contributors":{"editors":[{"text":"Hobbs, N. Thompson","contributorId":35031,"corporation":false,"usgs":true,"family":"Hobbs","given":"N. 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We assessed avian responses in non-protected habitat, specifically shade-restored coffee plantations, because their structural complexity retains many attributes of secondary forests, and may contribute to landscape scale species resiliency. We tallied species richness, and estimated occupancy probability of 12 resident avian species, after adjusting for imperfect detection, to assess the impact of hurricane Maria (20 September 2017) in the context of two stages of shade-restored coffee plantations. For 5 of those species, we also estimated local colonization and extinction probabilities to assess their prospect of rebounding (resiliency). We used survey data collected March-June 2015-2017 (pre-hurricane) and 2018 (post-hurricane) in 58 coffee farms and satellite imagery to assess vegetation structure. Restored farms were grouped into two categories based on time-since-restoration: newly-restored and fully-restored. We predicted that mean percent forest cover in fully-restored farms (~30-40%) would revert to levels in newly-restored farms (<15%), with concomitant changes in occupancy by avian species. As predicted, mean percent forest cover (16.17 4.27%) in fully-restored farms post-hurricane reverted to pre-hurricane levels in newly-restored farms (15.00 5.61%). The loss represented 30-38% relative to the pre-hurricane cover levels. Detections of focal species dropped an average of 41% post-hurricane, with associated reductions in occupancy for 9/11 species. Occupancy of the Puerto Rican Bullfinch and Puerto Rican Spindalis reverted to levels detected in newly-restored plantations prior to the hurricane as predicted. Prospects of rebounding were more likely for species with invariant or increases in colonization probability (e.g., Yellow-faced Grassquit, Northern Mockingbird, Puerto Rican Spindalis). Rebounding for frugivores like the Puerto Rican Bullfinch would be protracted given that colonization rates dropped from 0.56 0.12 (pre-hurricane) to 0.04 0.2 (post-hurricane), regardless of restoration stage. Our work showed that the avian community associated with restored coffee farms exhibited as high degree of ecological resistance as the similarity in species composition before and after the hurricane was 81%, and all 12 focal species continued to occupy farms under both restoration stages. The prospect of the focal species to rebound (resiliency) was specific-specific, and in some cases, mediated by their affinity to a particular farm restoration stage. The strength of hurricanes is projected to intensify with global warming. Pockets of undamaged or partially damaged shade-grown or fully-restored coffee plantations may contribute to species resiliency by increasing landscape level habitat redundancy, and facilitate habitat shifts to secure food resources or harbor source populations to colonize recovering, hurricane-damaged habitat tracts.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2021.e01579","usgsCitation":"Irizarry, A.D., Collazo, J.A., Vandermeer, J., and Perfecto, I., 2021, Coffee plantations, hurricanes and avian resiliency: Insights from occupancy, and local colonization and extinction rates in Puerto Rico: Global Ecology and Conservation, v. 27, e01579, 12 p., https://doi.org/10.1016/j.gecco.2021.e01579.","productDescription":"e01579, 12 p.","ipdsId":"IP-120553","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":452043,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2021.e01579","text":"Publisher Index Page"},{"id":396563,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Puerto Rico","otherGeospatial":"Greater Antilles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.08251953125,\n 17.955219304287816\n ],\n [\n -66.42059326171874,\n 17.955219304287816\n ],\n [\n -66.42059326171874,\n 18.424896202842426\n ],\n [\n -67.08251953125,\n 18.424896202842426\n ],\n [\n -67.08251953125,\n 17.955219304287816\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Irizarry, Amarilys D.","contributorId":205434,"corporation":false,"usgs":false,"family":"Irizarry","given":"Amarilys","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":836342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collazo, Jaime A. 0000-0002-1816-7744","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":217287,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime","email":"","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":836343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vandermeer, J.","contributorId":286880,"corporation":false,"usgs":false,"family":"Vandermeer","given":"J.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":836344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perfecto, I.","contributorId":286882,"corporation":false,"usgs":false,"family":"Perfecto","given":"I.","email":"","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":836345,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237296,"text":"70237296 - 2021 - A roadmap for planetary caves science and exploration","interactions":[],"lastModifiedDate":"2022-10-06T16:54:14.55441","indexId":"70237296","displayToPublicDate":"2021-06-01T09:54:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6448,"text":"Nature Astronomy","active":true,"publicationSubtype":{"id":10}},"title":"A roadmap for planetary caves science and exploration","docAbstract":"While researchers have pondered the possibility of extraterrestrial caves for more than 50 years, we have now entered the incipient phase of planetary caves exploration. Our knowledge of planetary caves varies from body to body. Earth represents the most advanced level of exploration, but many unanswered questions remain. Beyond Earth, identification of possible caves is most advanced for the Moon and Mars , with hundreds of documented candidate cave entrances and several proposed cave mission concepts. To date, the community has catalogued 2,660 SAPs on eight planetary bodies (excluding Earth) across our Solar System. Planetary caves science has the potential to significantly expand over the next decade. A potential roadmap for planetary cave research and exploration is discussed.
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An idealized case study of a northern California rail system","interactions":[],"lastModifiedDate":"2022-09-29T14:14:36.220516","indexId":"70237100","displayToPublicDate":"2021-06-01T09:08:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9121,"text":"Frontiers Earth Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"A framework for evaluating earthquake early warning for an infrastructure network: An idealized case study of a northern California rail system","docAbstract":"Earthquake early warning (EEW) systems provide a few to tens of seconds of warning before shaking hits a site. Despite the recent rapid developments of EEW systems around the world, the optimal alert response strategy and the practical benefit of using EEW are still open-ended questions, especially in areas where EEW systems are new or have not yet been deployed. Here, we use a case study of a rail system in California’s San Francisco Bay Area to explore potential uses of EEW for rail systems. Rail systems are of particular interest not only because they are important lifeline infrastructure and a common application for EEW around the world, but also because their geographically broad yet networked infrastructure makes them almost uniquely well suited for utilizing EEW. While the most obvious potential benefit of EEW to the railway is to prevent derailments by stopping trains before the arrival of shaking, the lead time for warnings is usually not long enough to significantly reduce a train’s speed. In reality, EEW’s greatest impact is preventing derailment by alerting trains to slow down or stop before they encounter damaged track. We perform cost-benefit analyses of different decision-making strategies for several EEW system designs to find an optimal alerting strategy. On-site EEW provides better outcomes than source-parameter-based EEW when warning at a threshold of 120 gal (the level of shaking at which damage might occur) regardless of false alarm tolerance. A source-parameter-based EEW system with a lower alerting threshold (e.g., 40 gal) can reduce the exposure to potentially damaged track compared to an on-site system alerting at 120 gal, but a lower alerting threshold comes at the cost of additional precautionary system stops. The optimal EEW approach for rail systems depends strongly on the ratio of the cost of stopping the system unnecessarily to the potential loss from traversing damaged tracks.","language":"English","publisher":"Frontiers Media SA","doi":"10.3389/feart.2021.620467","usgsCitation":"Minson, S.E., Cochran, E.S., Wu, S., and Noda, S., 2021, A framework for evaluating earthquake early warning for an infrastructure network: An idealized case study of a northern California rail system: Frontiers Earth Science Journal, v. 9, 620467, 14 p., https://doi.org/10.3389/feart.2021.620467.","productDescription":"620467, 14 p.","ipdsId":"IP-123427","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":452049,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2021.620467","text":"Publisher Index Page"},{"id":407593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Clara Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.91778564453125,\n 37.26968150969715\n ],\n [\n -121.24237060546876,\n 37.26968150969715\n ],\n [\n -121.24237060546876,\n 38.0091482264894\n ],\n [\n -122.91778564453125,\n 38.0091482264894\n ],\n [\n -122.91778564453125,\n 37.26968150969715\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2021-06-02","publicationStatus":"PW","contributors":{"editors":[{"text":"Kuyuk, Huseyin Serdar","contributorId":297119,"corporation":false,"usgs":false,"family":"Kuyuk","given":"Huseyin","email":"","middleInitial":"Serdar","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":853368,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":853339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":853340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wu, Stephen","contributorId":198428,"corporation":false,"usgs":false,"family":"Wu","given":"Stephen","email":"","affiliations":[],"preferred":false,"id":853341,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noda, Shunta","contributorId":297102,"corporation":false,"usgs":false,"family":"Noda","given":"Shunta","affiliations":[{"id":27332,"text":"Railway Technical Research Institute","active":true,"usgs":false}],"preferred":false,"id":853342,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70229064,"text":"70229064 - 2021 - Post-white-nose syndrome passive acoustic sampling effort for determining bat species occupancy within the mid-Atlantic region","interactions":[],"lastModifiedDate":"2022-02-28T15:19:15.463275","indexId":"70229064","displayToPublicDate":"2021-06-01T09:04:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Post-white-nose syndrome passive acoustic sampling effort for determining bat species occupancy within the mid-Atlantic region","docAbstract":"We assessed the sampling effort requirements for detecting the presence of extant bat species following the impact of white-nose syndrome in the mid-Atlantic region of the United States. We acoustically sampled 27,796 nights across 846 sites between 15 May and 15 August 2016–2018 within the District of Columbia, Maryland, Pennsylvania, Virginia, and West Virginia. We developed simulations to determine the number of sites required to document bat species when each site was sampled different numbers of nights. We examined these simulations with respect to land cover, physiographic region, and time period. We generally found that sampling a greater number of sample sites within a survey area increased detection more than increasing the number of nights at individual sampling sites. The sampling effort required to detect a given bat species varied by species, as well as land-cover type and physiographic region. Our results suggest that land managers and researchers should use caution in using protocols developed with other objectives, e.g., the U.S. Fish and Wildlife Service endangered and threatened bat species and the North American Bat monitoring programs’ methods are designed relative to their specific needs. Unfortunately, neither protocol may be adequate for accurately detecting bat communities within all mid-Atlantic areas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2021.107489","usgsCitation":"Deeley, S.M., Kalen, N., Freeze, S., Barr, E.L., and Ford, W., 2021, Post-white-nose syndrome passive acoustic sampling effort for determining bat species occupancy within the mid-Atlantic region: Ecological Indicators, v. 125, p. 1-9, https://doi.org/10.1016/j.ecolind.2021.107489.","productDescription":"107489, 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-121354","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":452052,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2021.107489","text":"Publisher Index Page"},{"id":396551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Pennsylvania, Virginia, West Virginia","city":"Washington, D. C.","otherGeospatial":"Blue Ridge Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.508056640625,\n 38.1777509666256\n ],\n [\n -75.706787109375,\n 38.1777509666256\n ],\n [\n -75.706787109375,\n 39.740986355883564\n ],\n [\n -79.508056640625,\n 39.740986355883564\n ],\n [\n -79.508056640625,\n 38.1777509666256\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Deeley, Sabrina M.","contributorId":270674,"corporation":false,"usgs":false,"family":"Deeley","given":"Sabrina","email":"","middleInitial":"M.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":836389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalen, Nicholas J.","contributorId":286972,"corporation":false,"usgs":false,"family":"Kalen","given":"Nicholas J.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":836390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeze, Samuel R.","contributorId":270513,"corporation":false,"usgs":false,"family":"Freeze","given":"Samuel R.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":836391,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barr, Elaine L.","contributorId":270623,"corporation":false,"usgs":false,"family":"Barr","given":"Elaine","email":"","middleInitial":"L.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":836392,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. 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Potential sources of perchlorate to groundwater at the study site have been attributed to waste disposal and industrial activities as well as to past agricultural operations. Perchlorate concentrations in samples ranged from <1 to 40 g/l, with a median of 6.1 g/l. Concentrations were relativity consistent with depth except at one site where dilution may be occurring due to the infiltration of surface water from Pyrite Creek. Well-bore flow profiles indicated that perchlorate redistribution was occurring via intra-well bore flow at one site where up to 14,000 mg/year of perchlorate could be moving from the shallower to the deeper zones of the alluvial aquifer. Natural attenuation processes of perchlorate do not appear to be widespread in groundwater but does occur in portions of the aquifer adjacent to the Santa Ana River, likely limiting the mobility of perchlorate from the southernmost extent of the mapped plume to areas further down-gradient. Age dating tracers indicate that perchlorate originating from the waste disposal ponds has largely moved through the zones of the aquifer sampled. Age distributions, noble gas temperature, delta neon values and stable isotopes of water indicate that a substantial fraction of perchlorate in groundwater may have been mobilized from the unsaturated zone and/or is from the infiltration of storm water runoff originating from Pyrite Canyon.","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2021.104959","usgsCitation":"Wright, M., Izbicki, J.A., and Jurgens, B.C., 2021, A multi-tracer and well-bore flow profile approach to determine occurrence, movement, and sources of perchlorate in groundwater: Applied Geochemistry, v. 129, p. 1-18, https://doi.org/10.1016/j.apgeochem.2021.104959.","productDescription":"104959, 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-116219","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":452054,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2021.104959","text":"Publisher Index Page"},{"id":393189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Jurupa Valley","otherGeospatial":"Jurupa Mountains, Mira Loma Hills, Pedley Hills, San Sevaine Channel, Santa Ana River, Stringfellow Superfund Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.66082763671875,\n 33.945638452963024\n ],\n [\n -117.14241027832031,\n 33.945638452963024\n ],\n [\n -117.14241027832031,\n 34.34343606848294\n ],\n [\n -117.66082763671875,\n 34.34343606848294\n ],\n [\n -117.66082763671875,\n 33.945638452963024\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"129","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Wang, Z. Zimeng","contributorId":270243,"corporation":false,"usgs":false,"family":"Wang","given":"Z.","email":"","middleInitial":"Zimeng","affiliations":[],"preferred":false,"id":828813,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Wright, Michael 0000-0003-0653-6466 mtwright@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-6466","contributorId":151031,"corporation":false,"usgs":true,"family":"Wright","given":"Michael","email":"mtwright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828799,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Izbicki, John A. 0000-0003-0816-4408 jaizbick@usgs.gov","orcid":"https://orcid.org/0000-0003-0816-4408","contributorId":152474,"corporation":false,"usgs":true,"family":"Izbicki","given":"John","email":"jaizbick@usgs.gov","middleInitial":"A.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828800,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828801,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236147,"text":"70236147 - 2021 - Devils Hole calcite was precipitated at ±1°C stable aquifer temperatures during the last half million years","interactions":[],"lastModifiedDate":"2022-08-30T13:48:39.748661","indexId":"70236147","displayToPublicDate":"2021-06-01T08:42:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Devils Hole calcite was precipitated at ±1°C stable aquifer temperatures during the last half million years","docAbstract":"Subaqueous carbonates from the Devils Hole caves (southwestern USA) provide a continuous Holocene to Pleistocene North American paleoclimate record. The accuracy of this record relies on two assumptions: That carbonates precipitated close to isotope equilibrium and that groundwater temperature did not change significantly in the last 570 thousand years. Here, we investigate these assumptions using dual clumped isotope thermometry. This method relies on simultaneous analyses of carbonate ∆47 and ∆48 values and provides information on the existence and extent of kinetic isotope fractionation. Our results confirm the hypothesis that calcite precipitation occurred close to oxygen and clumped isotope equilibrium during the last half million years in Devils Hole. In addition, we provide evidence that aquifer temperatures varied by less than ±1°C during this interval. Thus, the Devils Hole calcite δ18O time series exclusively represents changes in groundwater δ18O values.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL093257","usgsCitation":"Bajnai, D., Coplen, T.B., Methner, K., Loffler, N., Krsnik, E., and Fiebig, J., 2021, Devils Hole calcite was precipitated at ±1°C stable aquifer temperatures during the last half million years: Geophysical Research Letters, v. 48, no. 11, e2021GL093257, 10 p., https://doi.org/10.1029/2021GL093257.","productDescription":"e2021GL093257, 10 p.","ipdsId":"IP-124752","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":452057,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021gl093257","text":"External Repository"},{"id":405900,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.98242187499999,\n 38.07404145941957\n ],\n [\n -117.0703125,\n 36.88840804313823\n ],\n [\n -114.64233398437499,\n 35.003003395276714\n ],\n [\n -114.5654296875,\n 35.290468565908775\n ],\n [\n -114.6533203125,\n 35.60371874069731\n ],\n [\n -114.76318359375,\n 36.13787471840729\n ],\n [\n -114.43359375,\n 36.11125252076156\n ],\n [\n -114.2138671875,\n 36.03133177633187\n ],\n [\n -114.093017578125,\n 36.03133177633187\n ],\n [\n -114.0380859375,\n 36.24427318493909\n ],\n [\n -114.071044921875,\n 38.151837403006766\n ],\n [\n -116.98242187499999,\n 38.07404145941957\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Bajnai, David 0000-0002-4053-5056","orcid":"https://orcid.org/0000-0002-4053-5056","contributorId":295938,"corporation":false,"usgs":false,"family":"Bajnai","given":"David","email":"","affiliations":[{"id":63949,"text":"Institute of Geosciences, Goethe University Frankfurt, Frankfurt am Main, Germany","active":true,"usgs":false}],"preferred":false,"id":850251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":850252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Methner, Katharina","contributorId":194316,"corporation":false,"usgs":false,"family":"Methner","given":"Katharina","email":"","affiliations":[],"preferred":false,"id":850253,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loffler, Niklas 0000-0002-3026-8126","orcid":"https://orcid.org/0000-0002-3026-8126","contributorId":295941,"corporation":false,"usgs":false,"family":"Loffler","given":"Niklas","email":"","affiliations":[{"id":63949,"text":"Institute of Geosciences, Goethe University Frankfurt, Frankfurt am Main, Germany","active":true,"usgs":false}],"preferred":false,"id":850254,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krsnik, Emilija","contributorId":295942,"corporation":false,"usgs":false,"family":"Krsnik","given":"Emilija","email":"","affiliations":[{"id":63954,"text":"Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Frankfurt am Main, Germany","active":true,"usgs":false}],"preferred":false,"id":850255,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fiebig, Jens 0000-0001-5074-1462","orcid":"https://orcid.org/0000-0001-5074-1462","contributorId":295949,"corporation":false,"usgs":false,"family":"Fiebig","given":"Jens","email":"","affiliations":[{"id":63949,"text":"Institute of Geosciences, Goethe University Frankfurt, Frankfurt am Main, Germany","active":true,"usgs":false}],"preferred":false,"id":850256,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70223497,"text":"70223497 - 2021 - Native mammalian predators can depredate adult Burmese Pythons in Florida","interactions":[],"lastModifiedDate":"2021-08-31T13:46:38.755411","indexId":"70223497","displayToPublicDate":"2021-06-01T08:41:14","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Native mammalian predators can depredate adult Burmese Pythons in Florida","docAbstract":"Invasive predators are of conservation concern because they contribute to species declines and extinctions worldwide. Interactions of native fauna and invasive predators can be complex, but understanding these relationships can guide management and restoration. Observations of these interactions are especially important for invaders with low detectability like Python bivittatus (Burmese Python) where data are sparse. Here, we provide the first detailed documentation of mammalian attacks on Burmese Pythons in Florida: 1 Lynx rufus (Bobcat) predation of an adult male python and 1 Ursus americanus floridanus (Florida Black Bear) non-lethal attack on an adult female python.
","language":"English","publisher":"Eagle Hill Publications","doi":"10.1656/058.020.0205","usgsCitation":"McCollister, M.F., Josimovich, J.M., Fitzgerald, A.L., Jansen, D.K., and Currylow, A.F., 2021, Native mammalian predators can depredate adult Burmese Pythons in Florida: Southeastern Naturalist, v. 20, no. 2, p. N55-N59, https://doi.org/10.1656/058.020.0205.","productDescription":"5 p.","startPage":"N55","endPage":"N59","ipdsId":"IP-121323","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":388689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Big Cypress National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.36474609375,\n 25.585801212943935\n ],\n [\n -80.79757690429686,\n 25.585801212943935\n ],\n [\n -80.79757690429686,\n 26.277408212953834\n ],\n [\n -81.36474609375,\n 26.277408212953834\n ],\n [\n -81.36474609375,\n 25.585801212943935\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McCollister, Matthew F.","contributorId":264909,"corporation":false,"usgs":false,"family":"McCollister","given":"Matthew","email":"","middleInitial":"F.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":822181,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Josimovich, Jillian Maureen 0000-0002-7523-3496 jjosimovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7523-3496","contributorId":257058,"corporation":false,"usgs":true,"family":"Josimovich","given":"Jillian","email":"jjosimovich@usgs.gov","middleInitial":"Maureen","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":822182,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzgerald, Austin Lee 0000-0002-9016-1849","orcid":"https://orcid.org/0000-0002-9016-1849","contributorId":264910,"corporation":false,"usgs":true,"family":"Fitzgerald","given":"Austin","email":"","middleInitial":"Lee","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":822183,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jansen, Deborah K.","contributorId":264911,"corporation":false,"usgs":false,"family":"Jansen","given":"Deborah","email":"","middleInitial":"K.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":822184,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Currylow, Andrea Faye 0000-0003-1631-8964","orcid":"https://orcid.org/0000-0003-1631-8964","contributorId":257055,"corporation":false,"usgs":true,"family":"Currylow","given":"Andrea","email":"","middleInitial":"Faye","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":822185,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221396,"text":"70221396 - 2021 - A survey of storm-induced seaward-transport features observed during the 2019 and 2020 hurricane seasons","interactions":[],"lastModifiedDate":"2021-06-14T12:56:49.325445","indexId":"70221396","displayToPublicDate":"2021-06-01T07:54:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8932,"text":"Shore and Beach","active":true,"publicationSubtype":{"id":10}},"title":"A survey of storm-induced seaward-transport features observed during the 2019 and 2020 hurricane seasons","docAbstract":"Hurricanes are known to play a critical role in reshaping coastlines, but often only impacts on the open ocean coast are considered, ignoring seaward-directed forces and responses. The identification of subaerial evidence for storm-induced seaward transport is a critical step towards understanding its impact on coastal resiliency. The visual features, found in the National Oceanic and Atmospheric Administration, National Geodetic Survey Emergency Response Imagery (ERI) collected after recent hurricanes on the U.S. East Atlantic and Gulf of Mexico coasts, include scours and channelized erosion, but also deposition on the shoreface or in the nearshore as deltas and fans of various sizes. We catalog all available ERI and describe recently formed features found on the North Core Banks, North Carolina, after Hurricane Dorian (2019); the Carolina coasts after Hurricane Isaias (2020); the Isles Dernieres, Louisiana, after Hurricane Zeta (2020); and the southwest coast of Louisiana, after Hurricanes Laura and Delta (2020). Hundreds of features were identified over nearly 200 km of coastline with the density of features exceeding 20 per km in some areas. Individual features range in size from 5 m to 500 m in the alongshore, with similar dimensions in the cross-shore direction, including the formation or reactivation of outlets. The extensive occurrence of these storm-induced return-flow and seawardflow morphologic features demonstrates that their role in coastal evolution and resilience may be more prominent than previously thought. Based on these observations we propose clarifying terms for return- and seaward-flow features to distinguish them from more frequently documented landward-flow features and advocate for their inclusion in coastal change hazards classification schemes and coastal evolution morphodynamic models.","language":"English","publisher":"American Shore & Beach Preservation Association","doi":"10.34237/1008924","usgsCitation":"Over, J.R., Brown, J., Sherwood, C.R., Hegermiller, C., Wernette, P., Ritchie, A.C., and Warrick, J.A., 2021, A survey of storm-induced seaward-transport features observed during the 2019 and 2020 hurricane seasons: Shore and Beach, v. 89, no. 2, p. 31-40, https://doi.org/10.34237/1008924.","productDescription":"10 p.","startPage":"31","endPage":"40","ipdsId":"IP-126879","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":452060,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.31223/x5dp69","text":"External Repository"},{"id":386467,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"southeast United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.306640625,\n 25.005972656239187\n ],\n [\n -75.146484375,\n 25.005972656239187\n ],\n [\n -75.146484375,\n 36.59788913307022\n ],\n [\n -94.306640625,\n 36.59788913307022\n ],\n [\n -94.306640625,\n 25.005972656239187\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"89","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Over, Jin-Si R. 0000-0001-6753-7185 jover@usgs.gov","orcid":"https://orcid.org/0000-0001-6753-7185","contributorId":260178,"corporation":false,"usgs":true,"family":"Over","given":"Jin-Si","email":"jover@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Jenna A. 0000-0003-3137-7073","orcid":"https://orcid.org/0000-0003-3137-7073","contributorId":208564,"corporation":false,"usgs":true,"family":"Brown","given":"Jenna A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hegermiller, Christie 0000-0002-6383-7508 chegermiller@usgs.gov","orcid":"https://orcid.org/0000-0002-6383-7508","contributorId":149010,"corporation":false,"usgs":true,"family":"Hegermiller","given":"Christie","email":"chegermiller@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817513,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wernette, Phillipe Alan 0000-0002-8902-5575","orcid":"https://orcid.org/0000-0002-8902-5575","contributorId":259274,"corporation":false,"usgs":true,"family":"Wernette","given":"Phillipe Alan","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817514,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ritchie, Andrew C. aritchie@usgs.gov","contributorId":4984,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew","email":"aritchie@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817515,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817516,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70221599,"text":"70221599 - 2021 - Watersheds and drainage networks","interactions":[],"lastModifiedDate":"2021-06-25T12:49:28.165348","indexId":"70221599","displayToPublicDate":"2021-06-01T07:47:23","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Watersheds and drainage networks","docAbstract":"This topic is an overview of basic concepts about how the distribution of water on the Earth, with specific regard to watersheds, stream and river networks, and waterbodies are represented by geographic data. The flowing and non-flowing bodies of water on the earth’s surface vary in extent largely due to seasonal and annual changes in climate and precipitation. Consequently, modeling the detailed representation of surface water using geographic information is important. The area of land that collects surface runoff and other flowing water and drains to a common outlet location defines a watershed. Terrain and surface features can be naturally divided into watersheds of various sizes. Drainage networks are important data structures for modeling the distribution and movement of surface water over the terrain. Numerous tools and methods exist to extract drainage networks and watersheds from digital elevation models (DEMs). The cartographic representations of surface water are referred to as hydrographic features and consist of a snapshot at a specific time. Hydrographic features can be assigned general feature types, such as lake, pond, river, and ocean. Hydrographic features can be stored, maintained, and distributed for use through vector geospatial databases, such as the National Hydrography Dataset (NHD) for the United States.
The Midcontinent Rift System (MRS) is expressed geophysically by a semi-linear, regional gravity high that trends across the Midcontinent and Great Lakes region of North America. The gravity high is interrupted by two prominent, semi-circular gravity lows, which have been interpreted from modeling and seismic-reflection sections as basement highs of Archean granite (Allen et al., 1997). One is centered southwest of Isle Royale in western Lake Superior (Grand Marais ridge) and the other over Bayfield Peninsula (White’s Ridge). Allen et al. (1997) suggest that the Archean granite highs were pre-rift features that remained high while lava basins of the MRS subsided adjacent to them. Hart et al. (1994) questioned the presence of granitic rocks underlying Grand Marais ridge (GMR) because heat flow measurements there are much lower than is typical for Archean granitic upper crust. They argued that the region must instead be underlain by rocks of low radiogenic heat production, such as gabbro, extending to at least 15 km depth. However, gabbro has high densities and would not produce the observed gravity low. Thus, the geophysical observations appear contradictory.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Institute on Lake Superior Geology: Proceedings 2021","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Institute of Lake Superior Geology","usgsCitation":"Grauch, V.J., and Heller, S.J., 2021, Integration of geophysical evidence suggests that anorthosite composes a significant portion of Grand Marais ridge, an inferred basement high in western Lake Superior, in Institute on Lake Superior Geology: Proceedings 2021, v. 67, p. 29-30.","productDescription":"2 p.","startPage":"29","endPage":"30","ipdsId":"IP-128430","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":387398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387391,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcollections.lakeheadu.ca/items/show/3063"}],"country":"United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.340576171875,\n 47.56170075451973\n ],\n [\n -89.26391601562499,\n 47.56170075451973\n ],\n [\n -89.26391601562499,\n 47.96785877999251\n ],\n [\n -90.340576171875,\n 47.96785877999251\n ],\n [\n -90.340576171875,\n 47.56170075451973\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.01074218749999,\n 46.76244305208004\n ],\n [\n -90.28564453124999,\n 46.76244305208004\n ],\n [\n -90.28564453124999,\n 47.249406957888446\n ],\n [\n -91.01074218749999,\n 47.249406957888446\n ],\n [\n -91.01074218749999,\n 46.76244305208004\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"67","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Grauch, V. J. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":152256,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":819754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heller, Samuel J. 0000-0002-6579-5620 sheller@usgs.gov","orcid":"https://orcid.org/0000-0002-6579-5620","contributorId":201350,"corporation":false,"usgs":true,"family":"Heller","given":"Samuel","email":"sheller@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":819755,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}