The reconstruction of human impact is pivotal in palaeoecological studies, as humans are among the most important drivers of Holocene vegetation and ecosystem change. Nevertheless, separating the anthropogenic footprint on vegetation dynamics from the impact of climate and other environmental factors (disturbances such as fire, erosion, floods, landslides, avalanches, volcanic eruptions) is a challenging and still largely open issue. For this purpose, palynologists mostly rely on cultural indicator pollen types and related indices that consist of sums or ratios of these pollen types. However, the high environmental and biogeographical specificity of cultural indicator plants hinders the application of the currently available indices to wide geographical settings. Furthermore, the achievable taxonomic resolution of cultural indicator pollen types may hamper their indicative capacity. In this study, we propose the agricultural land use probability (LUP) index, a novel approach to quantify human impact intensity on European ecosystems based on cultural indicator pollen types. From the ‘classic’ cultural indicators, we construct the LUP index by selecting those with the best indicator capacity based on bioindication criteria. We first train the LUP index using twenty palynological sequences along a broad environmental gradient, spanning from treeless alpine to subtropical mediterranean evergreen plant communities. We then validate the LUP index using independent pollen datasets and archaeological proxies. Finally, we discuss the suitability of the selected pollen types and the potential of the LUP index for quantifying Holocene human impact in Europe, concluding that careful application of the LUP index may significantly contribute to refining pollen-based land-use reconstructions.
Climate change can act to facilitate or inhibit invasions of non-native species. Here, we address the influence of climate change on control of non-native common carp (hereafter, carp), a species recognized as one of the “world's worst” invaders across the globe. Control of this species is exceedingly difficult, as it exhibits rapid population growth and compensatory density dependence. In many locations where carp have invaded, however, climate change is altering hydrologic regimes and may influence population demography and efficacy of human control efforts. To further evaluate these processes, we employed a modified version of an age-based population model (CarpMOD), to investigate how hydrologic variability (change in lake area) influences carp population dynamics and control efforts in Malheur Lake, southeastern Oregon, USA. We explored how changes in lake area influence carp populations under three control scenarios: (1) no carp removal, (2) carp removal during low water years, and (3) carp removal during all years. Lake area fluctuations strongly influenced carp populations and the efficacy of carp control. Modeled carp biomass peaked when the lake transitioned from high-to-low levels, and carp biomass declined when lake area transitioned from low-to-high. Removing carp during low water periods—when fish were concentrated into a smaller area—reduced carp populations almost as much as removing carp every year. Furthermore, the effectiveness of control efforts increased with the prevalence and severity of low lake conditions (longer durations of very low lake area). These simulations suggest that a drier climate may naturally decrease carp populations and make them easier to control. However, drier conditions may also negatively affect aquatic ecosystems and potentially have a greater impact than non-native species themselves.
Debris flows pose a significant hazard to communities in mountainous areas, and there is a continued need for methods to delineate hazard zones associated with debris-flow inundation. In certain situations, such as scenarios following wildfire, where there could be an abrupt increase in the likelihood and size of debris flows that necessitates a rapid hazard assessment, the computational demands of inundation models play a role in their utility. The inability to efficiently determine the downstream effects of anticipated debris-flow events remains a critical gap in our ability to understand, mitigate, and assess debris-flow hazards. To better understand the downstream effects of debris flows, we introduce a computationally efficient, reduced-complexity inundation model, which we refer to as the Progressive Debris-Flow routing and inundation model (ProDF). We calibrate ProDF against mapped inundation from five watersheds near Montecito, CA, that produced debris flows shortly after the 2017 Thomas Fire. ProDF reproduced 70% of mapped deposits across a 40 km2 study area. While this study focuses on a series of post-wildfire debris flows, ProDF is not limited to simulating debris-flow inundation following wildfire and could be applied to any scenario where it is possible to estimate a debris-flow volume. However, given its ability to reproduce mapped debris-flow deposits downstream of the 2017 Thomas Fire burn scar, and the modest run time associated with a simulation over this 40 km2 study area, results suggest ProDF may be particularly promising for post-wildfire hazard assessment applications.
An accretionary tectonic model for the Mesoproterozoic ca. 1500–1340 Ma tectonic evolution of the southern Laurentian margin is presented. The tectonic model incorporates key observations about the nature and timing of Mesoproterozoic deposition, magmatism, regional metamorphism, and deformation across the 5000-km-long southern Laurentian margin. This time period was one of transition in the supercontinent cycle and occurred between the breakup of Columbia and the formation of Rodinia, and the southern Laurentian margin was a significant component of a much greater accretionary margin extending into Baltica and Amazonia and possibly parts of Antarctica and Australia. However, fundamental questions and contradictions remain in our understanding of the tectonic evolution of Laurentia and paleogeography during this time interval.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Laurentia: Turning points in the evolution of a continent","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2022.1220(08)","usgsCitation":"Daniel, C.G., Aronoff, R., Indares, A., and Jones, J.V., 2022, Laurentia in transition during the Mesoproterozoic: Observations and speculation on the ca. 1500–1340 Ma tectonic evolution of the southern Laurentian margin, chap. of Laurentia: Turning points in the evolution of a continent, https://doi.org/10.1130/2022.1220(08).","ipdsId":"IP-134080","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":400620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Daniel, Christopher G.","contributorId":195246,"corporation":false,"usgs":false,"family":"Daniel","given":"Christopher","email":"","middleInitial":"G.","affiliations":[{"id":25242,"text":"Department of Biology, Bucknell University, Lewisburg, Pennsylvania 17837, USA","active":true,"usgs":false}],"preferred":false,"id":843031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aronoff, Ruth 0000-0001-5320-6596","orcid":"https://orcid.org/0000-0001-5320-6596","contributorId":291773,"corporation":false,"usgs":false,"family":"Aronoff","given":"Ruth","email":"","affiliations":[{"id":62750,"text":"Furman University","active":true,"usgs":false}],"preferred":false,"id":843032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Indares, Aphrodite 0000-0002-9604-079X","orcid":"https://orcid.org/0000-0002-9604-079X","contributorId":291774,"corporation":false,"usgs":false,"family":"Indares","given":"Aphrodite","email":"","affiliations":[{"id":62751,"text":"Memorial University Newfoundland","active":true,"usgs":false}],"preferred":false,"id":843033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, James V. III 0000-0002-6602-5935 jvjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6602-5935","contributorId":201245,"corporation":false,"usgs":true,"family":"Jones","given":"James","suffix":"III","email":"jvjones@usgs.gov","middleInitial":"V.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":843034,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70234285,"text":"70234285 - 2022 - Water-use data in the United States: Challenges and future directions","interactions":[],"lastModifiedDate":"2022-08-08T11:38:57.659502","indexId":"70234285","displayToPublicDate":"2022-05-10T06:32:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Water-use data in the United States: Challenges and future directions","docAbstract":"In the United States, greater attention has been given to developing water supplies and quantifying available waters than determining who uses water, how much they withdraw and consume, and how and where water use occurs. As water supplies are stressed due to an increasingly variable climate, changing land-use, and growing water needs, greater consideration of the demand side of the water balance equation is essential. Data about the spatial and temporal aspects of water use for different purposes are now critical to long-term water supply planning and resource management. We detail the current state of water-use data, the major stakeholders involved in their collection and applications, and the challenges in obtaining high-quality nationally consistent data applicable to a range of scales and purposes. Opportunities to improve access, use, and sharing of water-use data are outlined. We cast a vision for a world-class national water-use data product that is accessible, timely, and spatially detailed. Our vision will leverage the strengths of existing local, state, and federal agencies to facilitate rapid and informed decision-making, modeling, and science for water resources. To inform future decision-making regarding water supplies and uses, we must coordinate efforts to substantially improve our capacity to collect, model, and disseminate water-use data.
Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
Streams in the Loup River Basin are sensitive to groundwater withdrawals because of the close hydrologic connection between groundwater and surface water. The U.S. Geological Survey, in cooperation with the Upper Loup and Lower Loup Natural Resources Districts, and the Nebraska Environmental Trust, studied the age and water-quality characteristics of groundwater near the South Loup River to assess the possible effects of a multiyear drought on streamflow.
Groundwater sampled in wells screened in Quaternary-age deposits displayed a wide range of mean ages (27 to 2,100 years), fraction modern, and susceptibility index values. Groundwater with higher concentrations of chloride and higher specific conductance was indicative of younger groundwater with a narrower age distribution and is more sensitive to climatic disturbances such as short-term drought conditions, based on the calculated susceptibility index. Groundwater samples from wells and springs in Pliocene-age deposits were categorized into two groups with different geochemical and age characteristics. One sample group of springs and wells, called the Western Pliocene, had higher concentrations of chloride and nitrate with young mean ages (18 to 77 years) and narrow age distributions. Groundwater in the Western Pliocene sample group is susceptible to short-term drought. In contrast, the other sample group from Pliocene-age deposits to the east (called Pliocene) had lower concentrations of nitrate, chloride, and mean groundwater ages ranging from 1,900 to 2,900 years old and is less likely to be affected by short-term drought conditions. Groundwater sampled from three wells screened in the Ogallala Formation was shown to have the oldest mean ages ranging from 8,700 to 23,000 years and the lowest calculated susceptibility index values observed in this study. Strong upward hydraulic gradients measured in wells indicated that groundwater from the Ogallala Formation is likely contributing to streamflow of the South Loup River.
Continuously measured gage height and specific conductance data indicated groundwater discharge from Quaternary-age deposits was highly responsive to precipitation events. In contrast, groundwater discharge from Pliocene-age deposits (Pliocene sample group) was far less responsive, indicating groundwater discharge from Pliocene-age deposits is likely more resilient to short-term drought conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225042","collaboration":"Prepared in cooperation with the Upper Loup and Lower Loup Natural Resources Districts and the Nebraska Environmental Trust","usgsCitation":"Hobza, C.M., and Solder, J.E., 2022, Age and water-quality characteristics of groundwater discharge to the South Loup River, Nebraska, 2019: U.S. Geological Survey Scientific Investigations Report 2022–5042, 57 p., https://doi.org/10.3133/sir20225042.","productDescription":"Report: ix, 57 p.; Data Release","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-129114","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":400241,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5042/sir20225042.pdf","text":"Report","size":"15.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5042"},{"id":502397,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112991.htm","linkFileType":{"id":5,"text":"html"}},{"id":400244,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L6B4XE","text":"USGS data release","linkHelpText":"Lumped parameter models of groundwater age, South Loup River, Nebraska"},{"id":400243,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5042/images"},{"id":400242,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5042/sir20225042.XML"},{"id":400333,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225042/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":400240,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5042/coverthb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"South Loup River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.8599853515625,\n 41.075210270566636\n ],\n [\n -98.5089111328125,\n 41.075210270566636\n ],\n [\n -98.5089111328125,\n 42.07376224008719\n ],\n [\n -100.8599853515625,\n 42.07376224008719\n ],\n [\n -100.8599853515625,\n 41.075210270566636\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
A study was conducted to compile and evaluate data used to identify groundwater sources that are under the direct influence of surface water (GUDI) in Pennsylvania. In the early 1990s, the Pennsylvania Department of Environmental Protection (PADEP) implemented the Surface Water Identification Protocol (SWIP) for the identification of GUDI sources. Since the establishment of the SWIP, PADEP has classified more than 500 individual sources across Pennsylvania as GUDI, but Pennsylvania’s complex geology and physiography provide a challenge for a uniform method of GUDI determination. Components used in this study to compile and evaluate data associated with GUDI determination include: (1) a preliminary review of file information for 43 public water-supply wells, (2) quality control and addition of data to PADEP’s database for public water-supply systems to prepare data for analysis, and (3) exploratory evaluation of existing GUDI sources in the database with respect to hydrogeologic and source-construction characteristics that are currently utilized in the assessment methodology.
Case files for 43 wells from PADEP’s Northcentral and Southcentral regions were reviewed to: (1) provide a better understanding of how the SWIP was applied in practice, (2) verify and compile missing data, and (3) find additional attributes not previously available that might explain a well’s categorization as GUDI. Review of file information showed that the SWIP outlined in PADEP technical guidance was usually followed, but for some sources, the GUDI determination was more complex and could not be easily summarized.
Data compiled for study analyses provided by PADEP include source data derived from public water-supply system case files, a source-information database for public water-supply systems, and Microscopic Particulate Analysis (MPA) results and associated water-quality data for public water-supply system groundwater sources. Data from the Pennsylvania Drinking Water Information System (PADWIS), which is PADEP’s database for public water-supply systems, were also used for this study. The PADWIS database originally included data for 12,147 groundwater sources (11,812 groundwater sources not under the direct influence of surface water (non-GUDI) wells and 335 GUDI wells). A subset (4,018 wells consisting of 3,842 non-GUDI wells and 175 GUDI wells) of the PADWIS database was created for an analysis and includes only community wells evaluated in accordance with the SWIP. MPA results for 631 community and noncommunity wells were compiled, along with associated water-quality data (alkalinity, chloride, Escherichia coli, fecal coliform, nitrate, pH, sodium, specific conductance, sulfate, total coliform, total dissolved solids, total residue, and turbidity) populated from the PADEP Bureau of Laboratories Sample Information System. Data compiled from sources other than PADEP include spatial data, both naturogenic (for example, average precipitation or distance to closest hydrologic feature) and anthropogenic (for example, percentage of developed or agricultural land cover within a specific vicinity of a public water-supply system well) data representing spatially derived variables.
Comparison among wells in the PADWIS dataset subset using the nonparametric Kruskal-Wallis test showed that GUDI wells had significantly older median construction years, shallower depths, and static water levels closer to the land surface than non-GUDI wells and that carbonate aquifers had the highest percentages of wells designated as GUDI (12 percent; 57 wells). Further comparison of wells in the PADWIS database subset using the Spearman’s rho monotonic correlation test illustrated that public water-supply wells designated as GUDI largely occur in unconfined aquifers and have high average yield and shallow static water levels. Assessment of the MPA database subset using the Kruskal-Wallis test showed wells with MPA total risk-factor scores that exceeded zero had older median construction years and shallower casing depths than wells with MPA total risk-factor scores of zero and that carbonate aquifers had the highest percentages of wells with MPA total risk-factor scores exceeding zero (30 percent; 63 wells). Spearman’s rho correlations showed that wells completed in aquifers with depths to major water-bearing zones closer to the land-surface had higher total risk-factor scores resulting from MPA samples.
Based on the results of the analyses described in this report, broad conclusions can be drawn regarding site-specific well characteristics as well as anthropogenic and naturogenic factors that could be responsible for a well being designated as GUDI, but the accuracy of these results is dependent on the quality of the data being analyzed. Ultimately, study results serve as an added resource for initial desktop screening of wells to determine if additional site-specific investigation is warranted and underscore the need for field evaluation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221023","collaboration":"Prepared in cooperation with the Pennsylvania Department of Environmental Protection, Bureau of Safe Drinking Water","usgsCitation":"Gross, E.L., Conlon, M.D., Risser, D.W., and Reisch, C.E., 2022, Compilation and evaluation of data used to identify groundwater sources under the direct influence of surface water in Pennsylvania (ver. 2.0, June 2023): U.S. Geological Survey Open-File Report 2022–1023, 41 p., https://doi.org/10.3133/ofr20221023.","productDescription":"Report: viii, 38 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101611","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":417972,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2022/1023/versionHist.txt","size":"49.8 KB","linkFileType":{"id":2,"text":"txt"}},{"id":417970,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1023/images/"},{"id":417969,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1023/ofr20221023.XML"},{"id":417967,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1023/ofr20221023.pdf","text":"Report","size":"7.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1023"},{"id":400579,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1023/coverthb.jpg"},{"id":417968,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221023/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1023"},{"id":417971,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q0BXH1","text":"USGS data release","linkHelpText":"Database used for the evaluation of data used to identify groundwater sources under the direct influence of surface water in Pennsylvania"},{"id":501766,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112989.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Pennsylvania","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-79.916171,39.720893],[-80.075947,39.72135],[-80.421388,39.721189],[-80.519342,39.721403],[-80.519423,39.806181],[-80.518891,39.890964],[-80.519248,39.936967],[-80.51896,40.078089],[-80.519039,40.342101],[-80.517991,40.367968],[-80.51769,40.462467],[-80.51899,40.473667],[-80.519002,40.877543],[-80.519891,40.906661],[-80.519091,40.921061],[-80.518928,41.070954],[-80.519144,41.171203],[-80.518693,41.248855],[-80.518993,41.268155],[-80.518794,41.305509],[-80.519129,41.312408],[-80.519345,41.340145],[-80.518993,41.435454],[-80.519339,41.539297],[-80.519425,41.977522],[-80.435451,42.005611],[-80.409776,42.011578],[-80.373066,42.024102],[-80.371869,42.023966],[-80.363251,42.027973],[-80.349169,42.030243],[-80.329976,42.036168],[-80.296758,42.049076],[-80.230486,42.077957],[-80.188085,42.094257],[-80.165884,42.105857],[-80.154084,42.114757],[-80.136213,42.149937],[-80.13043,42.156331],[-80.117368,42.166341],[-80.088512,42.173184],[-80.077388,42.171262],[-80.073381,42.168658],[-80.080028,42.163625],[-80.071981,42.155357],[-80.078781,42.151457],[-80.076281,42.147857],[-80.07198,42.146057],[-80.06108,42.144857],[-79.989186,42.177051],[-79.931324,42.206737],[-79.923924,42.207546],[-79.90105,42.216701],[-79.886187,42.224933],[-79.867979,42.230999],[-79.844661,42.235486],[-79.798447,42.255939],[-79.761951,42.26986],[-79.762152,42.243054],[-79.761759,42.162675],[-79.762122,42.131246],[-79.761709,42.11899],[-79.761798,42.019042],[-79.761374,41.999067],[-79.670128,41.999335],[-79.472472,41.998255],[-79.249772,41.998807],[-79.17857,41.999458],[-79.061265,41.999259],[-78.983065,41.998949],[-78.874759,41.997559],[-78.749754,41.998109],[-78.59665,41.999877],[-78.308128,41.999415],[-78.271204,41.998968],[-78.12473,42.000452],[-78.031177,41.999415],[-77.997508,41.998758],[-77.83203,41.998524],[-77.505308,42.00007],[-77.124693,41.999395],[-77.063676,42.000461],[-76.920784,42.001774],[-76.749675,42.001689],[-76.558118,42.000155],[-76.462155,41.998934],[-76.343722,41.998346],[-76.131201,41.998954],[-75.98025,41.999035],[-75.870677,41.998828],[-75.742217,41.997864],[-75.610316,41.99896],[-75.359579,41.999445],[-75.353504,41.99711],[-75.346568,41.995324],[-75.341125,41.992772],[-75.337602,41.9867],[-75.337791,41.984386],[-75.34246,41.974303],[-75.342204,41.972872],[-75.339488,41.970786],[-75.335771,41.970315],[-75.329318,41.968232],[-75.322384,41.961693],[-75.32004,41.960867],[-75.318168,41.954236],[-75.312817,41.950182],[-75.310358,41.949012],[-75.303966,41.948216],[-75.301664,41.94838],[-75.301233,41.9489],[-75.301593,41.952811],[-75.300409,41.953871],[-75.29858,41.954521],[-75.293713,41.954593],[-75.29143,41.952477],[-75.291762,41.947092],[-75.290966,41.945039],[-75.289383,41.942891],[-75.279094,41.938917],[-75.277243,41.933598],[-75.276501,41.926679],[-75.276552,41.922208],[-75.275368,41.919564],[-75.269736,41.911363],[-75.267562,41.907054],[-75.267773,41.901971],[-75.272778,41.897112],[-75.272581,41.893168],[-75.271292,41.88736],[-75.267789,41.885982],[-75.263005,41.885109],[-75.260623,41.883783],[-75.257564,41.877108],[-75.258439,41.875087],[-75.261488,41.873277],[-75.263815,41.870757],[-75.263673,41.868105],[-75.262802,41.866213],[-75.260527,41.8638],[-75.257825,41.862154],[-75.251197,41.86204],[-75.248045,41.8633],[-75.243345,41.866875],[-75.241134,41.867118],[-75.238743,41.865699],[-75.234565,41.861569],[-75.231612,41.859459],[-75.22572,41.857481],[-75.223734,41.857456],[-75.220125,41.860534],[-75.21497,41.867449],[-75.209741,41.86925],[-75.204002,41.869867],[-75.197836,41.868807],[-75.194382,41.867287],[-75.191441,41.865063],[-75.190203,41.862454],[-75.188888,41.861264],[-75.186993,41.860109],[-75.185254,41.85993],[-75.183937,41.860515],[-75.182271,41.862198],[-75.180497,41.86568],[-75.179134,41.869935],[-75.176633,41.872371],[-75.174574,41.87266],[-75.170565,41.871608],[-75.169142,41.87029],[-75.168053,41.867043],[-75.168733,41.859258],[-75.166217,41.853862],[-75.164168,41.851586],[-75.161541,41.849836],[-75.156512,41.848327],[-75.152898,41.848564],[-75.143824,41.851737],[-75.140241,41.852078],[-75.130983,41.845145],[-75.127913,41.844903],[-75.118789,41.845819],[-75.115598,41.844638],[-75.114399,41.843583],[-75.113369,41.840698],[-75.113441,41.836298],[-75.114998,41.8303],[-75.115147,41.827285],[-75.114837,41.82567],[-75.113334,41.822782],[-75.100024,41.818347],[-75.093537,41.813375],[-75.089484,41.811576],[-75.085789,41.811626],[-75.079818,41.814815],[-75.078063,41.815112],[-75.074409,41.815088],[-75.072172,41.813732],[-75.071751,41.811901],[-75.072168,41.808327],[-75.074412,41.802191],[-75.076889,41.798509],[-75.07827,41.797467],[-75.081415,41.796483],[-75.088328,41.797534],[-75.092876,41.796386],[-75.101463,41.787941],[-75.102329,41.786503],[-75.103548,41.782008],[-75.10464,41.774203],[-75.104334,41.772693],[-75.103492,41.771238],[-75.10099,41.769121],[-75.095451,41.768366],[-75.09281,41.768361],[-75.079478,41.771205],[-75.075942,41.771518],[-75.074231,41.770518],[-75.072664,41.768807],[-75.068567,41.767298],[-75.064901,41.766686],[-75.060759,41.764638],[-75.053431,41.752538],[-75.052808,41.744725],[-75.054818,41.735168],[-75.053527,41.72715],[-75.049699,41.715093],[-75.049862,41.713309],[-75.050689,41.711969],[-75.052226,41.711396],[-75.061174,41.712935],[-75.06663,41.712588],[-75.068642,41.710146],[-75.06883,41.708161],[-75.067278,41.705434],[-75.059829,41.699716],[-75.056745,41.695703],[-75.052736,41.688393],[-75.051234,41.682439],[-75.051285,41.679961],[-75.052653,41.678436],[-75.058765,41.674412],[-75.059332,41.67232],[-75.05843,41.669653],[-75.057251,41.668933],[-75.053991,41.668194],[-75.04992,41.662556],[-75.048683,41.656317],[-75.049281,41.641862],[-75.048658,41.633781],[-75.048199,41.632011],[-75.043562,41.62364],[-75.044224,41.617978],[-75.045508,41.616203],[-75.047298,41.615791],[-75.048385,41.615986],[-75.051856,41.618157],[-75.05385,41.618655],[-75.060098,41.617482],[-75.06156,41.616429],[-75.061675,41.615468],[-75.059956,41.612306],[-75.059725,41.610801],[-75.062716,41.609639],[-75.067795,41.610143],[-75.071667,41.609501],[-75.074626,41.607905],[-75.074613,41.605711],[-75.066955,41.599428],[-75.063677,41.594739],[-75.060012,41.590813],[-75.052858,41.587772],[-75.04676,41.583258],[-75.043879,41.575094],[-75.04049,41.569688],[-75.036989,41.567049],[-75.033162,41.565092],[-75.029211,41.564637],[-75.027343,41.563541],[-75.018524,41.551802],[-75.016328,41.546501],[-75.016144,41.544246],[-75.017626,41.542734],[-75.022828,41.541456],[-75.024798,41.539801],[-75.024757,41.535099],[-75.024206,41.534018],[-75.023018,41.533147],[-75.016616,41.53211],[-75.014919,41.531399],[-75.009552,41.528461],[-75.00385,41.524052],[-75.001297,41.52065],[-75.000911,41.519292],[-75.000935,41.517638],[-75.002592,41.51456],[-75.003706,41.511118],[-75.003694,41.509295],[-75.003151,41.508101],[-74.999612,41.5074],[-74.993893,41.508754],[-74.987645,41.508738],[-74.985653,41.507926],[-74.984372,41.506611],[-74.982385,41.500981],[-74.982168,41.498486],[-74.982463,41.496467],[-74.985247,41.489113],[-74.985595,41.485863],[-74.985004,41.483703],[-74.983341,41.480894],[-74.981652,41.479945],[-74.969887,41.477438],[-74.95826,41.476396],[-74.956411,41.476735],[-74.94808,41.480625],[-74.945634,41.483213],[-74.941798,41.483542],[-74.932585,41.482323],[-74.926835,41.478327],[-74.924092,41.477138],[-74.917282,41.477041],[-74.912517,41.475605],[-74.909181,41.472436],[-74.908133,41.468117],[-74.908103,41.464639],[-74.906887,41.461131],[-74.9042,41.459806],[-74.895069,41.45819],[-74.892114,41.456959],[-74.890358,41.455324],[-74.889116,41.452534],[-74.889075,41.451245],[-74.894931,41.446099],[-74.896399,41.442179],[-74.896025,41.439987],[-74.893913,41.43893],[-74.888691,41.438259],[-74.876721,41.440338],[-74.864688,41.443993],[-74.858578,41.444427],[-74.8542,41.443166],[-74.848602,41.440179],[-74.845572,41.437577],[-74.836915,41.431625],[-74.834635,41.430796],[-74.830671,41.430503],[-74.828592,41.430698],[-74.826031,41.431736],[-74.82288,41.436792],[-74.817995,41.440505],[-74.812123,41.442982],[-74.807582,41.442847],[-74.805655,41.442101],[-74.801225,41.4381],[-74.80037,41.43606],[-74.800095,41.432661],[-74.799546,41.43129],[-74.795396,41.42398],[-74.793856,41.422671],[-74.790417,41.42166],[-74.784339,41.422397],[-74.778029,41.425104],[-74.773239,41.426352],[-74.77065,41.42623],[-74.763701,41.423612],[-74.758587,41.423287],[-74.754359,41.425147],[-74.75068,41.427984],[-74.743821,41.430635],[-74.740932,41.43116],[-74.738455,41.430641],[-74.736688,41.429228],[-74.735519,41.427465],[-74.734893,41.425818],[-74.734731,41.422699],[-74.738684,41.413463],[-74.741086,41.411413],[-74.741717,41.40788],[-74.740963,41.40512],[-74.738554,41.401191],[-74.736103,41.398398],[-74.73364,41.396975],[-74.730384,41.39566],[-74.720891,41.39469],[-74.715979,41.392584],[-74.713411,41.389814],[-74.710391,41.382102],[-74.708458,41.378901],[-74.703282,41.375093],[-74.694968,41.370431],[-74.691129,41.367324],[-74.689516,41.363843],[-74.689767,41.361558],[-74.691076,41.36034],[-74.696398,41.357339],[-74.694914,41.357423],[-74.700595,41.354553],[-74.704429,41.354043],[-74.708514,41.352734],[-74.720923,41.347384],[-74.730373,41.345983],[-74.735622,41.346518],[-74.753239,41.346122],[-74.755971,41.344953],[-74.760325,41.340325],[-74.763499,41.331568],[-74.766714,41.328558],[-74.771588,41.325079],[-74.774887,41.324326],[-74.781584,41.324229],[-74.789095,41.323281],[-74.792116,41.322465],[-74.79504,41.320407],[-74.795822,41.318516],[-74.792377,41.314088],[-74.791991,41.311639],[-74.792558,41.310628],[-74.806858,41.303155],[-74.812033,41.298157],[-74.815703,41.296151],[-74.821884,41.293838],[-74.830057,41.2872],[-74.834067,41.281111],[-74.838366,41.277286],[-74.841137,41.27098],[-74.846319,41.263077],[-74.846506,41.261576],[-74.845031,41.258055],[-74.845883,41.254945],[-74.846932,41.253318],[-74.848987,41.251192],[-74.854669,41.25051],[-74.856003,41.250094],[-74.857151,41.248975],[-74.861678,41.241575],[-74.862049,41.237609],[-74.866182,41.232132],[-74.867405,41.22777],[-74.866839,41.226865],[-74.860837,41.222317],[-74.859323,41.220507],[-74.859632,41.219077],[-74.860398,41.217454],[-74.867287,41.208754],[-74.874034,41.198543],[-74.878275,41.190489],[-74.878492,41.187504],[-74.882139,41.180836],[-74.889424,41.1736],[-74.899701,41.166181],[-74.901172,41.16387],[-74.90178,41.161394],[-74.905256,41.155668],[-74.923169,41.138146],[-74.931141,41.133387],[-74.945067,41.129052],[-74.947714,41.126292],[-74.947334,41.124439],[-74.947912,41.12356],[-74.964294,41.114237],[-74.966298,41.113669],[-74.969312,41.113869],[-74.972917,41.113327],[-74.979873,41.110423],[-74.982212,41.108245],[-74.991718,41.092284],[-74.991815,41.089132],[-74.991013,41.088578],[-74.988263,41.088222],[-74.984782,41.088545],[-74.981314,41.08986],[-74.975298,41.094073],[-74.972036,41.095562],[-74.969434,41.096074],[-74.967464,41.095327],[-74.966759,41.093425],[-74.968389,41.087797],[-74.970987,41.085293],[-74.98259,41.079172],[-74.989332,41.078319],[-74.994847,41.076556],[-74.999617,41.073943],[-75.006376,41.067546],[-75.011133,41.067521],[-75.01257,41.066281],[-75.015271,41.061215],[-75.015867,41.05821],[-75.017239,41.055491],[-75.019186,41.052968],[-75.025702,41.046482],[-75.026376,41.04444],[-75.02543,41.04071],[-75.025777,41.039806],[-75.030701,41.038416],[-75.034496,41.036755],[-75.040668,41.031755],[-75.070532,41.01862],[-75.074999,41.01713],[-75.081101,41.016838],[-75.089787,41.014549],[-75.090312,41.013302],[-75.095556,41.008874],[-75.100682,41.006716],[-75.109114,41.004102],[-75.110595,41.002174],[-75.123423,40.996129],[-75.127196,40.993954],[-75.130575,40.991093],[-75.131619,40.9889],[-75.13153,40.984914],[-75.132106,40.982566],[-75.133086,40.980179],[-75.135521,40.976865],[-75.135526,40.973807],[-75.13378,40.970973],[-75.131364,40.969277],[-75.129074,40.968976],[-75.122603,40.970152],[-75.120514,40.968369],[-75.11977,40.96651],[-75.12065,40.964028],[-75.119893,40.961646],[-75.118904,40.956361],[-75.117764,40.953023],[-75.111683,40.948111],[-75.106153,40.939671],[-75.105524,40.936294],[-75.095526,40.924152],[-75.079279,40.91389],[-75.076956,40.90988],[-75.076092,40.907042],[-75.075188,40.900154],[-75.075957,40.895694],[-75.07534,40.894162],[-75.07392,40.892176],[-75.065438,40.885682],[-75.062149,40.882289],[-75.058655,40.877654],[-75.053664,40.87366],[-75.051508,40.870224],[-75.050839,40.868067],[-75.051029,40.865662],[-75.053294,40.8599],[-75.060491,40.85302],[-75.064328,40.848338],[-75.066014,40.847591],[-75.07083,40.847392],[-75.073544,40.84894],[-75.076684,40.849875],[-75.090962,40.849187],[-75.095784,40.847082],[-75.097221,40.844672],[-75.097586,40.843042],[-75.097572,40.840967],[-75.097006,40.839336],[-75.09494,40.837103],[-75.085517,40.830085],[-75.083822,40.827805],[-75.083929,40.824471],[-75.085387,40.821972],[-75.090518,40.815913],[-75.096147,40.812211],[-75.098279,40.810286],[-75.100277,40.807578],[-75.100739,40.805488],[-75.100165,40.803],[-75.100277,40.801176],[-75.1008,40.799797],[-75.108505,40.791094],[-75.111343,40.789896],[-75.116842,40.78935],[-75.123088,40.786746],[-75.125867,40.784026],[-75.131465,40.77595],[-75.133303,40.774124],[-75.1344,40.773765],[-75.139106,40.773606],[-75.149378,40.774786],[-75.16365,40.778386],[-75.169523,40.778473],[-75.171587,40.777745],[-75.173349,40.776129],[-75.17562,40.772923],[-75.176855,40.768721],[-75.177477,40.764225],[-75.17904,40.761897],[-75.183037,40.759344],[-75.191796,40.75583],[-75.196533,40.751631],[-75.196861,40.750097],[-75.196325,40.747137],[-75.195349,40.745473],[-75.18578,40.737266],[-75.182804,40.73365],[-75.182084,40.731522],[-75.1825,40.729922],[-75.186372,40.72397],[-75.189412,40.71797],[-75.192612,40.715874],[-75.19442,40.714018],[-75.19872,40.705298],[-75.20392,40.691498],[-75.20092,40.685498],[-75.19692,40.681299],[-75.19058,40.679379],[-75.184516,40.679971],[-75.180564,40.679363],[-75.177587,40.677731],[-75.176803,40.675715],[-75.177491,40.672595],[-75.182756,40.665971],[-75.18794,40.663811],[-75.190852,40.661939],[-75.196676,40.655123],[-75.200452,40.649219],[-75.200468,40.646899],[-75.193492,40.642275],[-75.192276,40.640803],[-75.191059,40.637971],[-75.188579,40.624628],[-75.189283,40.621492],[-75.190691,40.619956],[-75.197891,40.619332],[-75.200708,40.618356],[-75.201812,40.617188],[-75.201348,40.614628],[-75.198499,40.611492],[-75.195923,40.606788],[-75.192291,40.602676],[-75.190146,40.590359],[-75.190796,40.586838],[-75.194656,40.58194],[-75.195114,40.579689],[-75.194046,40.576256],[-75.192352,40.574257],[-75.186737,40.569406],[-75.183151,40.567354],[-75.175307,40.564996],[-75.168609,40.564111],[-75.162871,40.564096],[-75.158446,40.565286],[-75.147368,40.573152],[-75.141906,40.575273],[-75.136748,40.575731],[-75.117292,40.573211],[-75.110903,40.570671],[-75.100325,40.567811],[-75.0957,40.564401],[-75.078503,40.548296],[-75.068615,40.542223],[-75.067257,40.539584],[-75.066426,40.536619],[-75.06509,40.526148],[-75.065853,40.519495],[-75.066001,40.510716],[-75.065275,40.504682],[-75.062373,40.491689],[-75.061937,40.486362],[-75.062227,40.481391],[-75.064327,40.476795],[-75.067776,40.472827],[-75.06805,40.468578],[-75.067302,40.464954],[-75.070568,40.456348],[-75.070568,40.455165],[-75.067425,40.448323],[-75.062923,40.433407],[-75.061489,40.422848],[-75.058848,40.418065],[-75.056102,40.416066],[-75.046473,40.413792],[-75.043071,40.411603],[-75.041651,40.409894],[-75.036616,40.406796],[-75.028315,40.403883],[-75.024775,40.403455],[-75.017221,40.404638],[-75.003351,40.40785],[-74.998651,40.410093],[-74.996378,40.410528],[-74.988901,40.408773],[-74.985467,40.405935],[-74.982735,40.404432],[-74.969597,40.39977],[-74.965508,40.397337],[-74.963997,40.395246],[-74.953697,40.376081],[-74.948722,40.364768],[-74.946006,40.357306],[-74.945088,40.347332],[-74.943776,40.342564],[-74.939711,40.338006],[-74.933111,40.333106],[-74.92681,40.329406],[-74.91741,40.322406],[-74.90831,40.316907],[-74.90331,40.315607],[-74.896409,40.315107],[-74.891609,40.313007],[-74.887109,40.310307],[-74.880609,40.305607],[-74.868209,40.295207],[-74.860492,40.284584],[-74.856508,40.277407],[-74.853108,40.269707],[-74.846608,40.258808],[-74.842308,40.250508],[-74.836307,40.246208],[-74.823907,40.241508],[-74.819507,40.238508],[-74.795306,40.229408],[-74.781206,40.221508],[-74.77136,40.215399],[-74.770406,40.214508],[-74.766905,40.207709],[-74.760605,40.198909],[-74.756905,40.189409],[-74.755605,40.186709],[-74.754305,40.185209],[-74.751705,40.183309],[-74.744105,40.181009],[-74.737205,40.177609],[-74.733804,40.174509],[-74.722304,40.160609],[-74.721504,40.158409],[-74.721604,40.15381],[-74.722604,40.15001],[-74.724304,40.14701],[-74.725663,40.145495],[-74.740605,40.13521],[-74.742905,40.13441],[-74.745905,40.13421],[-74.755305,40.13471],[-74.758882,40.134036],[-74.762864,40.132541],[-74.769488,40.129145],[-74.782106,40.12081],[-74.785106,40.12031],[-74.788706,40.12041],[-74.800607,40.12281],[-74.812807,40.12691],[-74.816307,40.12761],[-74.819007,40.12751],[-74.822307,40.12671],[-74.825907,40.12391],[-74.828408,40.12031],[-74.832808,40.11171],[-74.835108,40.10391],[-74.838008,40.10091],[-74.843408,40.09771],[-74.851108,40.09491],[-74.854409,40.09311],[-74.856509,40.09131],[-74.858209,40.08881],[-74.859809,40.08491],[-74.860909,40.08371],[-74.863809,40.08221],[-74.880209,40.07881],[-74.88781,40.07581],[-74.909011,40.07021],[-74.911911,40.06991],[-74.920811,40.07111],[-74.925311,40.07071],[-74.932211,40.068411],[-74.944412,40.063211],[-74.974713,40.048711],[-74.983913,40.042711],[-74.989914,40.037311],[-75.007914,40.023111],[-75.011115,40.021311],[-75.015515,40.019511],[-75.039316,40.013012],[-75.047016,40.008912],[-75.051217,40.004512],[-75.059017,39.992512],[-75.072017,39.980612],[-75.088618,39.975212],[-75.093718,39.974412],[-75.108119,39.970312],[-75.11922,39.965412],[-75.12692,39.961112],[-75.13012,39.958712],[-75.13352,39.954412],[-75.13572,39.947112],[-75.13612,39.933912],[-75.13502,39.927312],[-75.13282,39.921612],[-75.13012,39.917013],[-75.12792,39.911813],[-75.13082,39.900213],[-75.13342,39.896213],[-75.140221,39.888213],[-75.145421,39.884213],[-75.150721,39.882713],[-75.183023,39.882013],[-75.189323,39.880713],[-75.195324,39.877013],[-75.210425,39.865913],[-75.221025,39.861113],[-75.235026,39.856613],[-75.243431,39.854597],[-75.271159,39.84944],[-75.293376,39.848782],[-75.309674,39.850179],[-75.323232,39.849812],[-75.330433,39.849012],[-75.341765,39.846082],[-75.3544,39.839917],[-75.371835,39.827612],[-75.390536,39.815312],[-75.403737,39.807512],[-75.415041,39.801786],[-75.428038,39.809212],[-75.45374,39.820312],[-75.463341,39.823812],[-75.481242,39.829112],[-75.498843,39.833312],[-75.518444,39.836311],[-75.539346,39.838211],[-75.570464,39.839007],[-75.579849,39.838526],[-75.593666,39.837455],[-75.617251,39.833999],[-75.634706,39.830164],[-75.641518,39.828363],[-75.662822,39.82115],[-75.685991,39.811054],[-75.701208,39.802606],[-75.716969,39.791998],[-75.727049,39.784126],[-75.736489,39.775759],[-75.744394,39.767855],[-75.753066,39.757631],[-75.760346,39.747231],[-75.766058,39.737811],[-75.773558,39.722411],[-75.788359,39.721811],[-75.998649,39.721576],[-76.013067,39.72192],[-76.233259,39.721305],[-76.715594,39.721103],[-76.8901,39.720401],[-76.936601,39.720701],[-76.990903,39.7198],[-77.058204,39.7202],[-77.534758,39.720134],[-77.724115,39.720894],[-77.874719,39.722219],[-78.330715,39.722689],[-78.337111,39.722461],[-78.438839,39.722481],[-78.461422,39.722869],[-78.537702,39.72249],[-78.546415,39.722869],[-78.575893,39.722561],[-78.723529,39.723043],[-79.045548,39.722883],[-79.548465,39.720778],[-79.610623,39.721245],[-79.763774,39.720776],[-79.916171,39.720893]]]},\"properties\":{\"name\":\"Pennsylvania\",\"nation\":\"USA \"}}]}","edition":"Version 1.0: May 2022; Version 2.0: June 2023","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
Although declines in grassland birds have been documented, national initiatives to conserve grasslands and their biota have fallen short in part because the non-market values of natural ecosystems and species are often not recognized in political decision making. Identifying shared, anthropogenic threats faced by market-valued and non-market-valued species may generate additional support for grassland conservation. We quantify the relationship between the market value of grasslands to commercial beekeepers and the importance of grasslands for birds of conservation concern in North and South Dakota. Our models estimated beekeeping annual revenue increased by $7525 USD and grassland bird abundances increased 2 to 7% per 10-km2 increase in grassland area. We estimated grassland conversion from 2006 to 2012 resulted in a $2.0 to $2.8 M USD decrease in annual revenue for beekeepers in the Dakotas. Through this study we demonstrate both the market value of grasslands to commercial beekeepers and the non-market benefits of grasslands in supporting migratory birds and discuss the implications of future land-use change. As grassland conversion and subsequent biodiversity loss continue, understanding the co-benefits of grassland conservation may be necessary to illuminate their contributions to society.
The U.S. Geological Survey (USGS) maintains an archive of 189,180 digitized scans of analog seismic records from the World‐Wide Standardized Seismograph Network (WWSSN). Although these scans have been made public, the archive is too large to manually review, and few researchers have utilized large numbers of these records. To facilitate further research using this historical dataset, we develop a simple convolutional neural network (CNN) that rapidly (∼4.75 s/film chip) classifies scanned film chip images (called “chips,” because they are individually cut segments of 70 mm film) into four categories of “interestingness” to earthquake seismologists based on the presence of earthquakes and other seismic signals in the record: “no interest,” “little interest,” “interest,” and “high interest.” The CNN, dubbed “Seismic Analog Record Network” (SARNet), can identify four types of seismic traces (“no events,” “minor events,” “major events,” and “errors”) in 200 × 200 pixel subcrops with an accuracy of 92% using a confidence threshold of 85%. SARNet then converts 100 random subcrops from each film chip into the overall classification of interestingness. In this task, SARNet performed as well as expert human classifiers in determining the film chip’s overall interest grade. Applying SARNet to 34,000 film chips in the WWSSN archive found that 21% of the images were of “high interest” and had an “indeterminate” rate of only 4%. Thus, the need for the manual review of images was reduced by 79%. Sorting of film chips derived from SARNet will expedite further exploration of the archive of digitized analog seismic records stored at the USGS.
Many species around the world are declining precipitously as a result of multiple threats and changing climate. Managers tasked with protecting species often face difficult decisions in regard to identifying which threats should be addressed, given limited resources and uncertainty in the success of any identified management action. On Kaua‘i Island, Hawai‘i, USA, forest bird species have experienced accelerated declines over the last 20 years, and 2 species, the ‘akikiki (Oreomystis bairdi) and ‘akeke‘e (Loxops caeruleirostris), are now at the brink of extinction. Both species face multiple threats, and managers face difficult decisions on whether to mitigate threats in the wild, establish a captive population as insurance against extinction, translocate birds to novel locations, or some combination of these actions. Each set of actions (alternatives) would require substantial resources with considerable uncertainty in success. In 2014, we brought together 14 experts representing biologists and managers familiar with the species and island to develop a conservation strategy under a structured decision making (SDM) framework, an approach for making complex decisions under uncertainty. The group's challenge was to identify a set of alternatives that reduces the risk of extinction, set the foundation for one or more genetically viable, reproducing, stable to increasing populations in 10 years, and promote conditions for long-term persistence in the wild. Multiple alternatives were evaluated, via expert judgement, in terms of the probability they would achieve the objectives concerning immediate extinction risk, near-term viability, and adequacy of habitat. Factors that might impede the success of each action were also evaluated. The process identified the establishment of a captive population and efforts to stabilize the existing wild population as the approach most likely to meet the objectives of preventing imminent extinction and ensuring long-term viability.
Chemically intensive crop production depletes wildlife food resources, hinders animal development, health, survival, and reproduction, and it suppresses wildlife immune systems, facilitating emergence of infectious diseases with excessive mortality rates. Gut microbiota is crucial for wildlife's response to environmental stressors. Its composition and functionality are sensitive to diet changes and environmental pollution associated with modern crop production. In this study we use shotgun metagenomics (median 8,326,092 sequences/sample) to demonstrate that exposure to modern crop production detrimentally affects cecal microbiota of sharp-tailed grouse (Tympanuchus phasianellus: 9 exposed, 18 unexposed and greater prairie chickens (T. cupido; 11, 11). Exposure to crop production had greater effect on microbiota richness (t = 6.675, P < 0.001) and composition (PERMANOVA r2 = 0.212, P = 0.001) than did the host species (t = 4.762, P < 0.001; r2 = 0.070, P = 0.001) or their interaction (t = 3.449; r2 = 0.072, both P = 0.001), whereas sex and age had no effect. Although microbiota richness was greater in exposed (T. cupido chao1 = 152.8 ± 20.5; T. phasianellus 115.3 ± 17.1) than in unexposed (102.9 ± 15.1 and 101.1 ± 17.2, respectively) birds, some beneficial bacteria dropped out of exposed birds' microbiota or declined and were replaced by potential pathogens. Exposed birds also had higher richness and load of virulome (mean ± standard deviation; T. cupido 24.8 ± 10.0 and 10.1 ± 5.5, respectively; T. phasianellus 13.4 ± 6.8/4.9 ± 2.8) and resistome (T. cupido 46.8 ± 11.7/28.9 ± 10.2, T. phasianellus 38.3 ± 16.7/18.9 ± 14.2) than unexposed birds (T. cupido virulome: 14.2 ± 13.5, 4.5 ± 4.2; T. cupido resistome: 31.6 ± 20.2 and 13.1 ± 12.0; T. phasianellus virulome: 5.2 ± 4.7 and 1.4 ± 1.5; T. phasianellus resistome: 13.7 ± 16.1 and 4.0 ± 6.4).
This study examined the association of air, land, and water variables with the first historical occurrence and current distribution of toxic Prymnesium parvum blooms in reservoirs of the Brazos River and Colorado River, Texas (USA). One impacted and one reference reservoir were selected per basin. Land cover and use variables were estimated for the whole watershed (WW) and a 0.5-km zone on either side of streams (near field, NF). Variables were expressed in annual values. Principal component and trend analyses were used to determine (1) differences in environmental conditions before and after the 2001 onset of toxic blooms in impacted reservoirs (study period, 1992–2017), and (2) traits that uniquely discriminate impacted from reference reservoirs (2001–2017). Of thirty-three variables examined, two positively aligned with the reoccurring appearance of blooms in impacted reservoirs (air CO2 and herbicide Glyphosate) and another two negatively aligned (insecticides Terbufos and Malathion). Glyphosate use was observed throughout the study period but a turning point for an upward trend occurred near the year of first bloom occurrence. While the relevance of the decreased use of insecticides is uncertain, prior experimental studies reported that increasing concentrations of air CO2 and water Glyphosate can enhance P. parvum growth. Consistent with prior findings, impacted reservoirs were of higher salinity than reference reservoirs. In addition, their watersheds had far lower wetland cover at NF and WW scales. The value of wetlands in reducing harmful algal bloom incidence by reducing nutrient inputs has been previously recognized, but wetlands can also capture pesticides. Therefore, a diminished wetland cover could magnify Glyphosate loads flowing into impacted reservoirs. These observations are consistent with a scenario where rising levels of air CO2 and Glyphosate use contributed to the establishment of P. parvum blooms in reservoirs of relatively high salinity and minimal wetland cover over their watersheds.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.155567","usgsCitation":"Tabora-Sarmientoa, S., Patino, R., Portillo-Quintero, C., and Coldren, C., 2022, Air, land, and water variables associated with the first appearance and current spatial distribution of toxic Prymnesium parvum blooms in reservoirs of the Southern Great Plains, USA: Science of the Total Environment, v. 836, 155567, 11 p., https://doi.org/10.1016/j.scitotenv.2022.155567.","productDescription":"155567, 11 p.","ipdsId":"IP-135673","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433321,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Southern Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102.79055428065931,\n 33.96150939341686\n ],\n [\n -102.79055428065931,\n 30.40651030229435\n ],\n [\n -95.3521242635305,\n 30.40651030229435\n ],\n [\n -95.3521242635305,\n 33.96150939341686\n ],\n [\n -102.79055428065931,\n 33.96150939341686\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"836","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tabora-Sarmientoa, Shisbeth","contributorId":341529,"corporation":false,"usgs":false,"family":"Tabora-Sarmientoa","given":"Shisbeth","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":908565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patino, Reynaldo 0000-0002-4831-8400 r.patino@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-8400","contributorId":2311,"corporation":false,"usgs":true,"family":"Patino","given":"Reynaldo","email":"r.patino@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908566,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Portillo-Quintero, Carlos","contributorId":341530,"corporation":false,"usgs":false,"family":"Portillo-Quintero","given":"Carlos","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":908567,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coldren, Cade","contributorId":341531,"corporation":false,"usgs":false,"family":"Coldren","given":"Cade","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":908568,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237696,"text":"70237696 - 2022 - The effect of diagenesis and acetolysis on the preservation of morphology and ultrastructural features of pollen","interactions":[],"lastModifiedDate":"2022-10-19T12:09:20.689887","indexId":"70237696","displayToPublicDate":"2022-05-07T07:03:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3275,"text":"Review of Palaeobotany and Palynology","active":true,"publicationSubtype":{"id":10}},"title":"The effect of diagenesis and acetolysis on the preservation of morphology and ultrastructural features of pollen","docAbstract":"Pollen morphology on its own and in conjunction with other characteristics has elucidated the origin and evolution of various plant groups. Previous studies of fossil pollen rarely discuss the effects of diagenesis and sample preparation on pollen characteristics, i.e., variability in staining, pollen morphology, and pollen wall ultrastructural characteristics. This paper examines the effect of acetolysis on reflectance and spectral epi-fluorescence measurements. Based on empirical studies, different species under similar experimental conditions display different reflectance values, indicating individual species respond differently to similar post-depositional thermal events. The quantitative pollen fluorescence spectra showed significant variability, but there is an overall increase in the mean wavelength of maximum emission with acetolysis. Increases in these spectral parameters are used to infer thermal maturation and diagenetic pathways in fossil pollen. The paper also discusses observations made on fossil pollen of a known thermal maturity using Pearson's Pollen/Spore Color Standard. Assessment of pollen thermal maturity using this color standard can be an indicator of the quality of morphological and ultrastructural information that can be extracted from fossil pollen. Increasing thermal maturity of pollen may have an effect on staining variability. Based on observations, staining for brightfield or electron microscopy in fossil pollen, although useful for improving contrast in the specimen, must be used with caution when interpreting pollen wall structure. Although single fossil pollen investigations are useful, replication of these studies on similar or the same specimens from the same locality or various localities will collectively provide more information for elucidation of the morphology and ultrastructure of the once living pollen, and is helpful in sorting out characteristics that may be artifacts from post-depositional diagenesis.
A state-space model (SSM) of infiltration estimates daily groundwater recharge using time-series of groundwater-level altitude and meteorological inputs (liquid precipitation, snowmelt, and evapotranspiration). The model includes diffuse and preferential flow through the unsaturated zone, where preferential flow is a function of liquid precipitation and snowmelt rates and a threshold rate, above which there is direct recharge to the water table. Model parameters are estimated over seasonal periods and the SSM is coupled with the Kalman Filter (KF) to assimilate recent observations (hydraulic head) and meteorological inputs into recharge estimates. The approach can take advantage of real-time hydrologic and meteorological data to deliver real-time recharge estimates. The model is demonstrated on daily observations from two bedrock wells in carbonate aquifers of northwestern New York (USA) between 2013 and 2018. Meteorological inputs for liquid precipitation and snowmelt are compiled from SNODAS (2021). Results for recharge during winter and spring seasons show preferential flow events to the water table from liquid precipitation, snowmelt, or a combination of the two. Recharge estimates summed annually are consistent with previous estimates of recharge reported from groundwater flow and surface-process models. Results from the SSM and KF point to errors in meteorological inputs, such as the snowmelt rate, that are not compatible with hydraulic head observations. Whereas liquid and solid precipitation are measured at discrete stations and extrapolated to 1-km2 grid cells, snowmelt is a meteorological modeled outcome that may not represent conditions in the vicinity of monitoring well locations.
","language":"English","publisher":"National Ground Water Association","doi":"10.1111/gwat.13206","usgsCitation":"Shapiro, A.M., Day-Lewis, F., Kappel, W.M., and Williams, J., 2022, Incorporating snowmelt into daily estimates of recharge using a state-space model of infiltration: Groundwater, v. 60, no. 6, p. 721-746, https://doi.org/10.1111/gwat.13206.","productDescription":"26 p.","startPage":"721","endPage":"746","ipdsId":"IP-130903","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":447877,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13206","text":"Publisher Index Page"},{"id":435854,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MRGR88","text":"USGS data release","linkHelpText":"Algorithms for model parameter estimation and state estimation applied to a state-space model for one-dimensional vertical infiltration incorporating snowmelt rate as a system input"},{"id":400497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-05-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Shapiro, Allen M. 0000-0002-6425-9607 ashapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":2164,"corporation":false,"usgs":true,"family":"Shapiro","given":"Allen","email":"ashapiro@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":842636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick 0000-0003-3526-886X","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":216359,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":842637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kappel, William M. 0000-0002-2382-9757 wkappel@usgs.gov","orcid":"https://orcid.org/0000-0002-2382-9757","contributorId":1074,"corporation":false,"usgs":true,"family":"Kappel","given":"William","email":"wkappel@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, John H. 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","middleInitial":"H.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842639,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70231264,"text":"dr1156 - 2022 - U.S. Geological Survey national shoreline change— Summary statistics for updated vector shorelines (1800s–2010s) and associated shoreline change data for the Georgia and Florida coasts","interactions":[],"lastModifiedDate":"2026-03-18T19:28:05.893773","indexId":"dr1156","displayToPublicDate":"2022-05-06T11:45:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1156","displayTitle":"U.S. Geological Survey National Shoreline Change— Summary Statistics for Updated Vector Shorelines (1800s–2010s) and Associated Shoreline Change Data for the Georgia and Florida Coasts","title":"U.S. Geological Survey national shoreline change— Summary statistics for updated vector shorelines (1800s–2010s) and associated shoreline change data for the Georgia and Florida coasts","docAbstract":"Rates of shoreline change have been updated for the open-ocean sandy coastlines of Georgia and Florida as part of the U.S. Geological Survey’s Coastal Change Hazards programmatic focus. This work was formerly within the National Assessment of Shoreline Change project. Shorelines were compiled from the original report published in 2005, recent update reports, and additional light detection and ranging (lidar) shorelines which were extracted from lidar data collected prior to and following Hurricane Irma, which made landfall in September 2017. These shorelines were used to compute long- and short-term rates that incorporate the proxy-datum bias on a transect-by-transect basis. The proxy-datum bias accounts for the unidirectional onshore bias of proxy-based high water line shorelines relative to datum-based mean high water shorelines. In this study, the coast of Georgia exhibited the highest average rates of erosion and accretion in both the long term (approximately 150 years) and the short term (approximately 30 years). Shoreline positions from the mid-1800s through 2018 were used to update the shoreline change rates for Florida and Georgia using the Digital Shoreline Analysis System (DSAS) software.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1156","usgsCitation":"Kratzmann, M.G., 2022, U.S. Geological Survey national shoreline change— Summary statistics for updated vector shorelines (1800s–2010s) and associated shoreline change data for the Georgia and Florida coasts: U.S. Geological Survey Data Report 1156, 8 p., https://doi.org/10.3133/dr1156.","productDescription":"Report: vi, 8 p.; Data Release","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-132897","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":400139,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1156/dr1156.XML"},{"id":400294,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/dr1156/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1156"},{"id":400136,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J3CVN4","text":"USGS data release","linkHelpText":"USGS national shoreline change—A GIS compilation of updated vector shorelines (1800s–2010s) and associated shoreline change data for the Georgia and Florida Coasts"},{"id":400134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1156/coverthb.jpg"},{"id":400135,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1156/dr1156.pdf","text":"Report","size":"1.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1156"},{"id":400138,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1156/images/"},{"id":501269,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112990.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida, Georgia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.71484375,\n 24.287026865376436\n ],\n [\n -78.486328125,\n 24.287026865376436\n ],\n [\n -78.486328125,\n 32.69486597787505\n ],\n [\n -87.71484375,\n 32.69486597787505\n ],\n [\n -87.71484375,\n 24.287026865376436\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598
Methods are being developed to capitalize on citizen science data for research and monitoring, but these data are rarely used within established decision-making frameworks of wildlife agencies. Citizen science data are often collected at higher resolution and extent than targeted monitoring programs, and may provide complementary information. Here, we demonstrate that carefully filtered semi-structured citizen science observations, when paired with targeted survey data, can produce ecological predictions at higher resolution and extent than targeted surveys alone, and both datasets can represent complementary aspects of species' ecology. We present case studies demonstrating how citizen science data can enhance or supplement decision-making of government and conservation organizations. First, we show how the continuous spatial coverage of citizen science projects, when coupled with targeted surveys, can improve estimates of metrics used by the U.S. Fish and Wildlife Service in regulatory processes to estimate population size, and inform take limits of federally managed species nationwide. Second, we show that the spatial coverage of citizen science accommodates dynamic avian space use patterns during key times of the year, relative to standardized monitoring protocols carried out by the Illinois Natural History Survey. Lastly, we demonstrate that citizen science information can replicate estimates of migratory chronologies for the Illinois Natural History Survey and the U.S. Fish and Wildlife Service for some waterfowl species, and in some contexts can supplement missing data on abundance. These findings illustrate the value of integrating validated information from semi-structured citizen science into the current evidence base used to justify, inform, and evaluate conservation decision-making.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2022.109556","usgsCitation":"Stuber, E.F., Robinson, O., Bjerre, E.R., Otto, M.C., Millsap, B., Zimmerman, G., Brasher, M., Ringelman, K., Fournier, A., Yetter, A., Isola, J., and Ruiz-Gutierrez, V., 2022, The potential of semi-structured citizen science data as a supplement for conservation decision-making: Validating the performance of eBird against targeted avian monitoring efforts: Biological Conservation, v. 270, 109556, 11 p., https://doi.org/10.1016/j.biocon.2022.109556.","productDescription":"109556, 11 p.","ipdsId":"IP-134088","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":488728,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2022.109556","text":"Publisher Index Page"},{"id":430277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Illinois, Iowa, Missouri","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.49828581034168,\n 39.76455400687408\n ],\n [\n -122.49828581034168,\n 38.81660641718298\n ],\n [\n -121.0222303704384,\n 38.81660641718298\n ],\n [\n -121.0222303704384,\n 39.76455400687408\n ],\n [\n -122.49828581034168,\n 39.76455400687408\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.90160005903965,\n 41.45769825249826\n ],\n [\n -92.50893391243744,\n 41.45769825249826\n ],\n [\n -92.50893391243744,\n 38.85655448556952\n ],\n [\n -88.90160005903965,\n 38.85655448556952\n ],\n [\n -88.90160005903965,\n 41.45769825249826\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"270","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stuber, Erica Francis 0000-0002-2687-6874","orcid":"https://orcid.org/0000-0002-2687-6874","contributorId":298084,"corporation":false,"usgs":true,"family":"Stuber","given":"Erica","email":"","middleInitial":"Francis","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":903404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Orin","contributorId":338622,"corporation":false,"usgs":false,"family":"Robinson","given":"Orin","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":903405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bjerre, Emily R.","contributorId":338623,"corporation":false,"usgs":false,"family":"Bjerre","given":"Emily","email":"","middleInitial":"R.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Otto, Mark C.","contributorId":338624,"corporation":false,"usgs":false,"family":"Otto","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Millsap, Brian A.","contributorId":338625,"corporation":false,"usgs":false,"family":"Millsap","given":"Brian A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zimmerman, Guthrie S.","contributorId":338626,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie S.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903409,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brasher, Michael G.","contributorId":338627,"corporation":false,"usgs":false,"family":"Brasher","given":"Michael G.","affiliations":[{"id":81180,"text":"Ducks Unlimited, Inc","active":true,"usgs":false}],"preferred":false,"id":903410,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ringelman, Kevin M.","contributorId":338628,"corporation":false,"usgs":false,"family":"Ringelman","given":"Kevin M.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":903411,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fournier, Auriel","contributorId":338631,"corporation":false,"usgs":false,"family":"Fournier","given":"Auriel","email":"","affiliations":[{"id":81181,"text":"University of Illinois at Urbana-Champaign, Havana","active":true,"usgs":false}],"preferred":false,"id":903412,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yetter, Aaron","contributorId":338634,"corporation":false,"usgs":false,"family":"Yetter","given":"Aaron","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":903413,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Isola, Jennifer","contributorId":242027,"corporation":false,"usgs":false,"family":"Isola","given":"Jennifer","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":904306,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ruiz-Gutierrez, Viviana","contributorId":261212,"corporation":false,"usgs":false,"family":"Ruiz-Gutierrez","given":"Viviana","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":904307,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70254768,"text":"70254768 - 2022 - Using predictions from multiple anthropogenic threats to estimate future population persistence of an imperiled species","interactions":[],"lastModifiedDate":"2024-06-07T14:46:22.029683","indexId":"70254768","displayToPublicDate":"2022-05-06T09:38:02","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Using predictions from multiple anthropogenic threats to estimate future population persistence of an imperiled species","docAbstract":"Imperiled species face numerous and diverse anthropogenic threats to their persistence, and wildlife managers charged with making conservation decisions benefit from a sound understanding of how populations, species, and ecosystems will respond to future changes in threats to biodiversity. In southeastern North America, the gopher tortoise (Gopherus polyphemus) is a keystone species in upland ecosystems; however, tortoise populations have declined strongly over the last century, and the species is a candidate for increased protection by the United States federal government under the Endangered Species Act (ESA). Here, we sought to support conservation decision making for G. polyphemus by developing a spatially-explicit predictive population model that linked four anthropogenic threats (climate warming, sea-level rise, urbanization, habitat degradation) to demographic vital rates and used the model to estimate future changes in the number of individuals, populations, and metapopulations across the species’ range. Using recent survey data, we projected 457 populations for 80 years into the future under scenarios varying in threat magnitude, management magnitude, and demographic uncertainty. Population projections predicted that the number of individuals, populations, and metapopulations would decline among all simulated scenarios in the next 80 years. Model predictions were more sensitive to variation in adult survival and immigration rates than to variation in threat magnitude. A scenario with decreased habitat management and threat effects from climate warming, sea-level rise, and urbanization predicted geographic variation in persistence probabilities for populations that might result in decreased genetic representation across the species' range. Our results can be used to support conservation listing decisions for the gopher tortoise as part of its federal Species Status Assessment and provide an analytical framework for how to link diverse threats to geographically-varying demographic rates during population viability analyses for wide-ranging imperiled species around the world.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02143","usgsCitation":"Folt, B., Marshall, M., Emanuel, J.A., Dziadzio, M., Cooke, J., Mena, L., Hinderliter, M., Hoffmann, S., Rankin, N., Tupy, J., and McGowan, C., 2022, Using predictions from multiple anthropogenic threats to estimate future population persistence of an imperiled species: Global Ecology and Conservation, v. 36, e02143, 21 p., https://doi.org/10.1016/j.gecco.2022.e02143.","productDescription":"e02143, 21 p.","ipdsId":"IP-133548","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":447881,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02143","text":"Publisher Index Page"},{"id":429647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Folt, Brian","contributorId":267702,"corporation":false,"usgs":false,"family":"Folt","given":"Brian","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":902450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Michael","contributorId":337474,"corporation":false,"usgs":false,"family":"Marshall","given":"Michael","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":902451,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Emanuel, Jo Anna","contributorId":337478,"corporation":false,"usgs":false,"family":"Emanuel","given":"Jo","email":"","middleInitial":"Anna","affiliations":[{"id":81021,"text":"Florida Ecological Services","active":true,"usgs":false}],"preferred":false,"id":902452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dziadzio, Michelina","contributorId":337480,"corporation":false,"usgs":false,"family":"Dziadzio","given":"Michelina","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":902453,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooke, Jane","contributorId":337481,"corporation":false,"usgs":false,"family":"Cooke","given":"Jane","email":"","affiliations":[{"id":81021,"text":"Florida Ecological Services","active":true,"usgs":false}],"preferred":false,"id":902454,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mena, Lourdes","contributorId":105576,"corporation":false,"usgs":true,"family":"Mena","given":"Lourdes","email":"","affiliations":[],"preferred":false,"id":902455,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hinderliter, Matthew","contributorId":337483,"corporation":false,"usgs":false,"family":"Hinderliter","given":"Matthew","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902456,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hoffmann, Scott","contributorId":337616,"corporation":false,"usgs":false,"family":"Hoffmann","given":"Scott","email":"","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":902457,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rankin, Nicole","contributorId":337485,"corporation":false,"usgs":false,"family":"Rankin","given":"Nicole","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902458,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tupy, John","contributorId":337486,"corporation":false,"usgs":false,"family":"Tupy","given":"John","affiliations":[{"id":81024,"text":"Mississippi Ecological Services Office","active":true,"usgs":false}],"preferred":false,"id":902459,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":3381,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":902460,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70231315,"text":"70231315 - 2022 - Compression behavior of hydrate-bearing sediments","interactions":[],"lastModifiedDate":"2022-05-06T14:27:50.929128","indexId":"70231315","displayToPublicDate":"2022-05-06T09:22:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":605,"text":"AAPG Bulletin","printIssn":"0149-1423","active":true,"publicationSubtype":{"id":10}},"title":"Compression behavior of hydrate-bearing sediments","docAbstract":"This work experimentally explores porosity, compressibility, and the ratio of horizontal to vertical effective stress (K0) in hydrate-bearing sandy silts from Green Canyon Block 955 in the deep-water Gulf of Mexico. The samples have an in situ porosity of 0.38 to 0.40 and a hydrate saturation of more than 80%. The hydrate-bearing sediments are stiffer than the equivalent hydrate-free sediments; the K0 stress ratio is greater for hydrate-bearing sediments relative to the equivalent hydrate-free sediments. The porosity decreases by 0.01 to 0.02 when the hydrate is dissociated at the in situ effective stress. We interpret that the hydrate in the sediment pores is a viscoelastic material that behaves like a fluid over experimental time scales, yet it cannot escape the sediment skeleton. During compression, the hydrate bears a significant fraction of the applied vertical load and transfers this load laterally, resulting in the apparent increased stiffness and a larger apparent K0 stress ratio. When dissociation occurs, the load carried by the hydrate is transferred to the sediment skeleton, resulting in further compaction and a decrease in the lateral stress. The viewpoint that the hydrate is a trapped viscous phase provides a mechanism for how stiffness and stress ratio (K0) are greater when hydrate is present in the porous media. This study provides insight into the initial stress state of hydrate-bearing reservoirs and the geomechanical evolution of these reservoirs during production.
","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/01132221002","usgsCitation":"Fang, Y., Flemings, P., Germaine, J., Daigle, H., Phillips, S.C., and O’Connell, J., 2022, Compression behavior of hydrate-bearing sediments: AAPG Bulletin, v. 106, no. 5, p. 1101-1126, https://doi.org/10.1306/01132221002.","productDescription":"26 p.","startPage":"1101","endPage":"1126","ipdsId":"IP-125588","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":400283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Green Canyon Block 955, Green Knoll, Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.417236328125,\n 26.82407078047018\n ],\n [\n -89.527587890625,\n 26.82407078047018\n ],\n [\n -89.527587890625,\n 28.497660832963472\n ],\n [\n -91.417236328125,\n 28.497660832963472\n ],\n [\n -91.417236328125,\n 26.82407078047018\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fang, Yi","contributorId":138799,"corporation":false,"usgs":false,"family":"Fang","given":"Yi","email":"","affiliations":[{"id":6727,"text":"Pacific Northwest National Laboratory, Richland, WA","active":true,"usgs":false}],"preferred":false,"id":842295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flemings, Peter","contributorId":198205,"corporation":false,"usgs":false,"family":"Flemings","given":"Peter","affiliations":[{"id":13127,"text":"Jackson School of Geosciences, University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":842296,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Germaine, John","contributorId":291403,"corporation":false,"usgs":false,"family":"Germaine","given":"John","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":842298,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daigle, Hugh","contributorId":291400,"corporation":false,"usgs":false,"family":"Daigle","given":"Hugh","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":842297,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phillips, Stephen C. 0000-0003-0858-4701","orcid":"https://orcid.org/0000-0003-0858-4701","contributorId":268177,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":842299,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Connell, Joshua","contributorId":239907,"corporation":false,"usgs":false,"family":"O’Connell","given":"Joshua","email":"","affiliations":[{"id":48038,"text":"Institute for Geophysics and Department of Geological Sciences, Jackson School of Geosciences, University of Texas","active":true,"usgs":false}],"preferred":false,"id":842300,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70231312,"text":"70231312 - 2022 - Permeability of methane hydrate-bearing sandy silts in the deep-water Gulf of Mexico (Green Canyon Block 955)","interactions":[],"lastModifiedDate":"2022-05-06T14:20:14.06089","indexId":"70231312","displayToPublicDate":"2022-05-06T09:17:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":605,"text":"AAPG Bulletin","printIssn":"0149-1423","active":true,"publicationSubtype":{"id":10}},"title":"Permeability of methane hydrate-bearing sandy silts in the deep-water Gulf of Mexico (Green Canyon Block 955)","docAbstract":"Permeability is one of the most crucial properties governing fluid flow in methane hydrate reservoirs. This paper presents a comprehensive permeability analysis of hydrate-bearing sandy silt pressure-cored from Green Canyon Block 955 (GC 955) in the deep-water Gulf of Mexico. We developed an experimental protocol to systematically characterize the transport and petrophysical properties in pressure cores. The in situ effective permeability ranges from 0.1 md (1.0 × 10−16 m2) to 2.4 md (2.4 × 10−15 m2) in these natural sandy silts cores with hydrate occupying 83%–93% of the pore space. When hydrate dissociates from these cores, the measured intrinsic permeability (k0) is 0.3 md (3.0 × 10−16 m2) to 9.3 md (9.3 × 10−15 m2); these results are affected by fines migration during hydrate dissociation. We analyzed samples reconstituted from these sandy silts and found k0 to range from ∼12 md (∼1.2 × 10−14 m2) to ∼41 md (∼4.1 × 10−14 m2). The water relative permeabilities (krw) of GC 955 pressure cores are large relative to other natural pressure cores from offshore Japan, offshore India, and onshore Alaska. These krw values are also higher than predicted by current conceptual relative permeability models where hydrate fills the pores or coats the grains of the sediments. This fundamental conundrum requires further study. Our work provides essential parameters to reservoir simulation models seeking to predict hydrate formation in geological systems, evaluate the gas production potential, and explore the best way to produce this energy resource in sandy silt reservoirs.
","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/08102121001","usgsCitation":"Fang, Y., Flemings, P., Daigle, H., Phillips, S.C., and O’Connell, J., 2022, Permeability of methane hydrate-bearing sandy silts in the deep-water Gulf of Mexico (Green Canyon Block 955): AAPG Bulletin, v. 106, no. 5, p. 1071-1100, https://doi.org/10.1306/08102121001.","productDescription":"30 p.","startPage":"1071","endPage":"1100","ipdsId":"IP-125587","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":400282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Green Canyon Block 955, Green Knoll, Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.417236328125,\n 26.82407078047018\n ],\n [\n -89.527587890625,\n 26.82407078047018\n ],\n [\n -89.527587890625,\n 28.497660832963472\n ],\n [\n -91.417236328125,\n 28.497660832963472\n ],\n [\n -91.417236328125,\n 26.82407078047018\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fang, Yi","contributorId":138799,"corporation":false,"usgs":false,"family":"Fang","given":"Yi","email":"","affiliations":[{"id":6727,"text":"Pacific Northwest National Laboratory, Richland, WA","active":true,"usgs":false}],"preferred":false,"id":842290,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flemings, Peter","contributorId":198205,"corporation":false,"usgs":false,"family":"Flemings","given":"Peter","affiliations":[{"id":13127,"text":"Jackson School of Geosciences, University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":842291,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daigle, Hugh","contributorId":291400,"corporation":false,"usgs":false,"family":"Daigle","given":"Hugh","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":842292,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phillips, Stephen C. 0000-0003-0858-4701","orcid":"https://orcid.org/0000-0003-0858-4701","contributorId":268177,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":842293,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Connell, Joshua","contributorId":239907,"corporation":false,"usgs":false,"family":"O’Connell","given":"Joshua","email":"","affiliations":[{"id":48038,"text":"Institute for Geophysics and Department of Geological Sciences, Jackson School of Geosciences, University of Texas","active":true,"usgs":false}],"preferred":false,"id":842294,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231324,"text":"70231324 - 2022 - Assessing conservation and management actions with ecosystem services better communicates conservation value to the public","interactions":[],"lastModifiedDate":"2022-05-06T14:14:23.881476","indexId":"70231324","displayToPublicDate":"2022-05-06T09:08:02","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Assessing conservation and management actions with ecosystem services better communicates conservation value to the public","docAbstract":"Fish and wildlife populations are under unprecedented threats from changes in land use and climate. With increasing threats comes a need for an expanded constituency that can contribute to the public support and financial capital needed for habitat conservation and management. Using an ecosystem services approach can provide a framework for a more holistic accounting of conservation benefits. Our objective here is to provide a greater understanding of the role that taking an ecosystem services approach can have in expanding the public constituency that supports the use of financial capital required to conserve and manage the nation’s natural capital. To demonstrate a methodology and the usefulness of taking an ecosystem services approach when communicating the value of conserving and managing fish and wildlife habitats, we performed an evaluation of U.S. Fish and Wildlife Service-owned Waterfowl Production Areas, National Wildlife Refuges, and easement lands (both wetland and grassland) in Stutsman County, North Dakota. We quantified amphibian habitat, grassland bird habitat, floral resources for pollinators, and carbon storage services under various scenarios of conservation. While we did not include all possible ecosystem services in our model, our case study shows how this process can provide a more complete picture of the collateral benefits of conservation directed primarily toward waterfowl. Using this ecosystem services approach, we documented marked losses in all services modeled if current conservation lands were developed for the production of agricultural crops. By having access to a more complete picture of benefits provided by conservation lands, decision makers can better communicate their value. By garnering greater public support through a more accurate accounting of societal benefits, conservation and management of dwindling natural capital may someday attain the same level of thought and consideration that is put into the conservation and management of the nation’s financial capital.","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-21-083","usgsCitation":"Mushet, D., Post van der Burg, M., and Anteau, M.J., 2022, Assessing conservation and management actions with ecosystem services better communicates conservation value to the public: Journal of Fish and Wildlife Management, v. 13, no. 1, 13 p., https://doi.org/10.3996/JFWM-21-083.","productDescription":"13 p.","ipdsId":"IP-126556","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":447884,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-083","text":"Publisher Index Page"},{"id":400280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","county":"Stutsman County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-99.2669,47.3268],[-98.8466,47.327],[-98.8392,47.327],[-98.8232,47.3272],[-98.8152,47.3271],[-98.4991,47.327],[-98.467,47.3266],[-98.4677,47.2402],[-98.4685,46.9788],[-98.4412,46.9789],[-98.4396,46.6296],[-98.7894,46.6294],[-99.0379,46.6309],[-99.1616,46.6317],[-99.4122,46.6316],[-99.4498,46.6319],[-99.4477,46.8044],[-99.4476,46.9788],[-99.4821,46.9795],[-99.4824,47.0089],[-99.4822,47.0162],[-99.4821,47.0249],[-99.4826,47.0396],[-99.4827,47.1558],[-99.4801,47.3267],[-99.2669,47.3268]]]},\"properties\":{\"name\":\"Stutsman\",\"state\":\"ND\"}}]}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":248468,"corporation":false,"usgs":true,"family":"Mushet","given":"David M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842306,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842307,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70231309,"text":"70231309 - 2022 - Integrated geochemical approach to determine the source of methane in gas hydrate from Green Canyon Block 955 in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2022-05-06T14:07:26.017969","indexId":"70231309","displayToPublicDate":"2022-05-06T09:01:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":605,"text":"AAPG Bulletin","printIssn":"0149-1423","active":true,"publicationSubtype":{"id":10}},"title":"Integrated geochemical approach to determine the source of methane in gas hydrate from Green Canyon Block 955 in the Gulf of Mexico","docAbstract":"Massive volumes of gas are sequestered within gas hydrate in subsurface marine sediments in the Gulf of Mexico. Methane associated with gas hydrate is a potentially important economic resource and a significant reservoir of carbon within the global carbon cycle. Nevertheless, uncertainties remain about the genetic source (e.g., microbial, thermogenic) and possible migration history of natural gas incorporated into hydrate. Previous studies have primarily used the hydrocarbon molecular (CH4/C2H6+) and isotopic (δ13C-CH4, δ2H-CH4) compositions of natural gas to address these uncertainties. However, hydrocarbon tracers are altered by mixing, oxidation, secondary methanogenesis, or fluid migration, which presents challenges when deciphering the mechanisms responsible for methane formation and accumulation. To evaluate the genetic source of natural gases from Green Canyon Block 955 (GC 955), east of the Sigsbee escarpment, we collected and analyzed samples from the first pressurized hydrate-bearing sediment cores collected from a coarse-grained hydrate reservoir in the Gulf of Mexico. Gas samples were analyzed for hydrocarbon gas (C1–C5), major gas (e.g., N2, CO2), and noble gas (He-Xe) abundance and isotopic (e.g., δ13C-CH4, δ2H-CH4, δ13C-CO2, δ15N-N2, 3He/4He, 4He/20Ne) compositions. We determined that natural gas in hydrates from this location are predominantly of primary microbial origin (conservatively at least 76%) and are formed by the hydrogenotrophic (CO2 reduction) methanogenesis pathway. We also note increased thermogenic proportions (∼6%) in a hydrate-bearing layer below the main hydrate-bearing interval (separated by a 5-m water-bearing layer). Our results suggest that microbial methane may be abundant below the base of gas hydrate stability at GC 955.
","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/05272120087","usgsCitation":"Moore, M.T., Phillips, S.C., Cook, A., and Darrah, T.H., 2022, Integrated geochemical approach to determine the source of methane in gas hydrate from Green Canyon Block 955 in the Gulf of Mexico: AAPG Bulletin, v. 106, no. 5, p. 949-980, https://doi.org/10.1306/05272120087.","productDescription":"32 p.","startPage":"949","endPage":"980","ipdsId":"IP-125029","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":400279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Green Canyon Block 955, Green Knoll, Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.417236328125,\n 26.82407078047018\n ],\n [\n -89.527587890625,\n 26.82407078047018\n ],\n [\n -89.527587890625,\n 28.497660832963472\n ],\n [\n -91.417236328125,\n 28.497660832963472\n ],\n [\n -91.417236328125,\n 26.82407078047018\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Myles T. 0000-0002-4405-8349","orcid":"https://orcid.org/0000-0002-4405-8349","contributorId":291397,"corporation":false,"usgs":true,"family":"Moore","given":"Myles","email":"","middleInitial":"T.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Stephen C. 0000-0003-0858-4701","orcid":"https://orcid.org/0000-0003-0858-4701","contributorId":268177,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":842287,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cook, Ann","contributorId":242644,"corporation":false,"usgs":false,"family":"Cook","given":"Ann","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":842288,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Darrah, Thomas H.","contributorId":145769,"corporation":false,"usgs":false,"family":"Darrah","given":"Thomas","email":"","middleInitial":"H.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":842289,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70231649,"text":"70231649 - 2022 - A forested wetland at a climate-induced tipping-point: 17-year demographic evidence of widespread tree recruitment failure","interactions":[],"lastModifiedDate":"2022-05-18T13:55:43.960202","indexId":"70231649","displayToPublicDate":"2022-05-06T08:46:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"A forested wetland at a climate-induced tipping-point: 17-year demographic evidence of widespread tree recruitment failure","docAbstract":"Regeneration and survival of forested wetlands are affected by environmental variables related to the hydrologic regime. Climate change, specifically alterations to precipitation patterns, may have outsized effects on these forests. In Tennessee, USA, precipitation has increased by 15% since 1960. The goal of our research was to assess the evidence for whether this change in precipitation patterns resulted in shorter growing seasons and recruitment failure in common canopy trees for a forest wetland. In 2001 and 2018, the density of Quercus lyrata (overcup oak), Liquidambar styraciflua (sweetgum), Quercus phellos (willow oak), and Betula nigra (river birch) seedling, sapling and adult density were mapped in an area of 2.3 ha within a seasonally flooded karst depression. Overall, the percentage of the growing season experiencing inundation was 26% greater in the deep than in shallow areas between 2001 and 2018. Saplings and small adults of all four species were restricted to shallow areas, and their abundance has declined substantially. Overcup oak and sweetgum individuals that were recruited into the adult life history stage were repelled from the deep zone. Overcup oak and sweetgum adults experienced lower mortality across the 2.3-ha study area (11% and 26%, respectively) relative to willow oak (56%) and river birch (64%) over the 17-year study. Growing-season inundation showed no relation to mortality in adult sweetgum and willow oak, a positive relation to mortality among adult river birch across size classes and among small adult overcup oak, and an inverse relation to mortality among large adult overcup oak. In shallow regions, overcup oak and sweetgum adults had greater basal area increment relative to the intermediate and deep regions of the pond. Results of hydrologic modeling for the study area, based on rainfall and temperature records covering 1855–2019, show ponding durations after 1970 considerably longer than the historical baseline, across ponding-depth classes. Our results strongly suggest that climate change is a driving factor suppressing tree regeneration since 1970 in this seasonally flooded karst depression.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2022.120247","usgsCitation":"Evans, J., McCarthy-Neumann, S., Pritchard, A., Cartwright, J.M., and Wolfe, W., 2022, A forested wetland at a climate-induced tipping-point: 17-year demographic evidence of widespread tree recruitment failure: Forest Ecology and Management, v. 517, 120247, 12 p., https://doi.org/10.1016/j.foreco.2022.120247.","productDescription":"120247, 12 p.","ipdsId":"IP-135244","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":447887,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2022.120247","text":"Publisher Index Page"},{"id":400755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","otherGeospatial":"Arnold Engineering Development Complex, Sinking Pond","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.09521865844725,\n 35.38932985634939\n ],\n [\n -86.04337692260742,\n 35.38932985634939\n ],\n [\n -86.04337692260742,\n 35.42151066245934\n ],\n [\n -86.09521865844725,\n 35.42151066245934\n ],\n [\n -86.09521865844725,\n 35.38932985634939\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"517","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Evans, Jonathan","contributorId":291851,"corporation":false,"usgs":false,"family":"Evans","given":"Jonathan","affiliations":[{"id":62773,"text":"University of the South at Sewanee","active":true,"usgs":false}],"preferred":false,"id":843227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarthy-Neumann, Sarah","contributorId":291852,"corporation":false,"usgs":false,"family":"McCarthy-Neumann","given":"Sarah","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":843228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pritchard, Angus","contributorId":291853,"corporation":false,"usgs":false,"family":"Pritchard","given":"Angus","email":"","affiliations":[{"id":62773,"text":"University of the South at Sewanee","active":true,"usgs":false}],"preferred":false,"id":843229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cartwright, Jennifer M. 0000-0003-0851-8456 jmcart@usgs.gov","orcid":"https://orcid.org/0000-0003-0851-8456","contributorId":5386,"corporation":false,"usgs":true,"family":"Cartwright","given":"Jennifer","email":"jmcart@usgs.gov","middleInitial":"M.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843230,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolfe, William J. 0000-0002-3292-051X","orcid":"https://orcid.org/0000-0002-3292-051X","contributorId":224729,"corporation":false,"usgs":false,"family":"Wolfe","given":"William J.","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":843231,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}