Hoary bats (Lasiurus cinereus) are among the bat species most commonly killed by wind turbine strikes in the midwestern United States. The impact of this mortality on species census size is not understood, due in part to the difficulty of estimating population size for this highly migratory and elusive species. Genetic effective population size (Ne) could provide an index of changing census population size if other factors affecting Ne are stable.
We used the NeEstimator package to derive effective breeding population size (Nb) estimates for two temporally spaced cohorts: 93 hoary bats collected in 2009–2010 and an additional 93 collected in 2017–2018. We sequenced restriction-site associated polymorphisms and generated a de novo genome assembly to guide the removal of sex-linked and multi-copy loci, as well as identify physically linked markers.
Analysis of the reference genome with psmc suggested at least a doubling of Ne in the last 100,000 years, likely exceeding Ne = 10,000 in the Holocene. Allele and genotype frequency analyses confirmed that the two cohorts were comparable, although some samples had unusually high or low observed heterozygosities. Additionally, the older cohort had lower mean coverage and greater variability in coverage, and batch effects of sampling locality were observed that were consistent with sample degradation. We therefore excluded samples with low coverage or outlier heterozygosity, as well as loci with sequence coverage far from the mode value, from the final data set. Prior to excluding these outliers, contemporary Nb estimates were significantly higher in the more recent cohort, but this finding was driven by high values for the 2018 sample year and low values for all other years. In the reduced data set, Nb did not differ significantly between cohorts. We found base substitutions to be strongly biased toward cytosine to thymine or the complement, and further partitioning loci by substitution type had a strong effect on Nb estimates. Minor allele frequency and base quality bias thresholds also had strong effects on Nb estimates. Instability of Nb with respect to common data filtering parameters and empirically identified factors prevented robust comparison of the two cohorts. Given that confidence intervals frequently included infinity as the stringency of data filtering increased, contemporary trends in Nb of North American hoary bats may not be tractable with the linkage disequilibrium method, at least using the protocol employed here.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.11285","usgsCitation":"Cornman, R.S., Fike, J., Oyler-McCance, S.J., and Cryan, P.M., 2021, Historical effective population size of North American hoary bat (Lasiurus cinereus) and challenges to estimating trends in contemporary effective breeding population size from archived samples: PeerJ, v. 9, e11285, 27 p., https://doi.org/10.7717/peerj.11285.","productDescription":"e11285, 27 p.","ipdsId":"IP-125432","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":452631,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.11285","text":"Publisher Index Page"},{"id":436402,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VSG54Z","text":"USGS data release","linkHelpText":"Genetic variation in hoary bats (Lasiurus cinereus) assessed from archived samples"},{"id":385284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2021-04-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":814602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fike, Jennifer A. 0000-0001-8797-7823","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":207268,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":814603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":814604,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cryan, Paul M. 0000-0002-2915-8894 cryanp@usgs.gov","orcid":"https://orcid.org/0000-0002-2915-8894","contributorId":147942,"corporation":false,"usgs":true,"family":"Cryan","given":"Paul","email":"cryanp@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":814605,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263927,"text":"70263927 - 2021 - Spatiotemporal clustering of great earthquakes on a transform fault controlled by geometry","interactions":[],"lastModifiedDate":"2025-02-28T15:50:17.631195","indexId":"70263927","displayToPublicDate":"2021-04-19T09:46:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal clustering of great earthquakes on a transform fault controlled by geometry","docAbstract":"Minor changes in geometry along the length of mature strike-slip faults may act as conditional barriers to earthquake rupture, terminating some and allowing others to pass. This hypothesis remains largely untested because palaeoearthquake data that constrain spatial and temporal patterns of fault rupture are generally imprecise. Here we develop palaeoearthquake event data that encompass the last 20 major-to-great earthquakes along approximately 320 km of the Alpine Fault in New Zealand with sufficient temporal resolution and spatial coverage to reveal along-strike patterns of rupture extent. The palaeoearthquake record shows that earthquake terminations tend to cluster in time near minor along-strike changes in geometry. These terminations limit the length to which rupture can grow and produce two modes of earthquake behaviour characterized by phases of major (Mw 7–8) and great (Mw > 8) earthquakes. Physics-based simulations of seismic cycles closely resemble our observations when parameterized with realistic fault geometry. Switching between the rupture modes emerges due to heterogeneous stress states that evolve over multiple seismic cycles in response to along-strike differences in geometry. These geometric complexities exert a first-order control on rupture behaviour that is not currently accounted for in fault-source models for seismic hazard.
","language":"English","publisher":"Nature","doi":"10.1038/s41561-021-00721-4","usgsCitation":"Howarth, J., Barth, N.C., Fitzsimons, S., Richards-Dinger, K.B., Clark, K., Biasi, G., Cochran, U., Langridge, R.M., Berryman, K., and Sutherland, R., 2021, Spatiotemporal clustering of great earthquakes on a transform fault controlled by geometry: Nature Geoscience, v. 14, p. 314-320, https://doi.org/10.1038/s41561-021-00721-4.","productDescription":"7 p.","startPage":"314","endPage":"320","ipdsId":"IP-123083","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"South Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 166.14130042117392,\n -45.855254614357875\n ],\n [\n 167.55703138687022,\n -47.72709088799331\n ],\n [\n 171.04329453684727,\n -45.90628854385326\n ],\n [\n 172.01003756617126,\n -44.16671517350856\n ],\n [\n 173.28236889170694,\n -43.93388994721674\n ],\n [\n 173.01583587447817,\n -43.26711906105943\n ],\n [\n 174.6610670093284,\n -41.74200766025002\n ],\n [\n 174.2430988469256,\n -40.59327885176259\n ],\n [\n 172.24758921841533,\n -40.37688312712664\n ],\n [\n 171.32279188614189,\n -41.531725778001864\n ],\n [\n 169.84538818345476,\n -43.00565520661165\n ],\n [\n 167.88893104162912,\n -43.84009881514205\n ],\n [\n 166.14130042117392,\n -45.855254614357875\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2021-04-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Howarth, Jamie D.","contributorId":351620,"corporation":false,"usgs":false,"family":"Howarth","given":"Jamie D.","affiliations":[{"id":34109,"text":"Victoria University of Wellington, New Zealand","active":true,"usgs":false}],"preferred":false,"id":929132,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barth, Nicolas C.","contributorId":206132,"corporation":false,"usgs":false,"family":"Barth","given":"Nicolas","email":"","middleInitial":"C.","affiliations":[{"id":37254,"text":"University of California, Riverside, CA","active":true,"usgs":false}],"preferred":false,"id":929133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzsimons, Sean J.","contributorId":351621,"corporation":false,"usgs":false,"family":"Fitzsimons","given":"Sean J.","affiliations":[{"id":13378,"text":"University of Otago, New Zealand","active":true,"usgs":false}],"preferred":false,"id":929134,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richards-Dinger, Keith B.","contributorId":198155,"corporation":false,"usgs":false,"family":"Richards-Dinger","given":"Keith","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":929135,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Kate","contributorId":295749,"corporation":false,"usgs":false,"family":"Clark","given":"Kate","email":"","affiliations":[],"preferred":false,"id":929136,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Biasi, Glenn 0000-0003-0940-5488 gbiasi@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-5488","contributorId":195946,"corporation":false,"usgs":true,"family":"Biasi","given":"Glenn","email":"gbiasi@usgs.gov","affiliations":[],"preferred":true,"id":929137,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cochran, Ursula A.","contributorId":351622,"corporation":false,"usgs":false,"family":"Cochran","given":"Ursula A.","affiliations":[{"id":26939,"text":"GNS Science, Lower Hutt, New Zealand","active":true,"usgs":false}],"preferred":false,"id":929138,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Langridge, Robert M.","contributorId":175117,"corporation":false,"usgs":false,"family":"Langridge","given":"Robert","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":929139,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Berryman, Kelvin R.","contributorId":351623,"corporation":false,"usgs":false,"family":"Berryman","given":"Kelvin R.","affiliations":[{"id":26939,"text":"GNS Science, Lower Hutt, New Zealand","active":true,"usgs":false}],"preferred":false,"id":929140,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sutherland, Rupert 0000-0001-7430-0055","orcid":"https://orcid.org/0000-0001-7430-0055","contributorId":278669,"corporation":false,"usgs":false,"family":"Sutherland","given":"Rupert","email":"","affiliations":[{"id":57245,"text":"School of Geography, Environment and Earth Sciences, Victoria University of Wellington","active":true,"usgs":false}],"preferred":false,"id":929141,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70222437,"text":"70222437 - 2021 - Organo-facies and mineral effects on sorption capacity of low-maturity Permian Barakar shales from the Auranga Basin, Jharkhand, India","interactions":[],"lastModifiedDate":"2021-07-30T14:14:46.655583","indexId":"70222437","displayToPublicDate":"2021-04-19T09:12:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1506,"text":"Energy & Fuels","active":true,"publicationSubtype":{"id":10}},"title":"Organo-facies and mineral effects on sorption capacity of low-maturity Permian Barakar shales from the Auranga Basin, Jharkhand, India","docAbstract":"Shales associated with the Lower Permian (Barakar Formation) sediments of the Auranga Coalfield, India, occur in the immature–early mature stage. The sorption capacity of Barakar shale samples has been studied through high-pressure methane (CH4) adsorption and low-pressure N2 gas adsorption (LPN2GA) methods, supported with proximate analyses, programmed pyrolysis, optical petrography, and with energy-dispersive spectroscopy, X-ray diffraction, and inductively coupled plasma mass spectrometry. The sorption capacity is a function of the organic and inorganic constituents present in the shale samples. The methane sorption capacity (MSC) and Langmuir volume of the shale samples vary from 0.217 to 0.314 and 0.315 to 0.429 mmol/g rock, respectively. The BET-calculated surface area of the studied shales varies from 8.12 to 30.36 m2/g. The sorption capacities show the importance of the total organic content (TOC) through weak but positive correlations with MSC (r2 = 0.45) and S1 values (mg hydrocarbons/g rock from programmed pyrolysis; r2 = 0.40). Moreover, apparent inverse relationships were observed between MSC and clay mineral abundances, suggesting that individual clay mineral types may influence MSC, although more work is needed. The TOC-normalized MSC (MSC*) of shale samples shows a positive trend with quartz plus clay mineral content and ash yield of r2 = 0.64 for both. In addition, MSC* shows a negative logarithmic relationship with S1 + S2 (r2 = 0.63) and a positive linear relationship with TOC-normalized total organic matter (TOM*) (r2 = 0.88, when 5 low TOM* samples are excluded) indicating complex relationships possibly including bitumen retention in the sample pore spaces. The micropore study of the samples through LPN2GA, applying Dubinin–Radushkevich, Dubinin–Astakhov, and density functional theory models, shows the dominance of micro-mesopore concentrations in the shale matrix of ∼2 nm pore diameter. However, these pores might be present as blind or closed pores. The presence of thorium and zirconium is reflective of terrigenous detrital matter, i.e., moderately to strongly recycled sediments. The fluviatile facies of deposited shales in the Auranga Coalfield are noted by the significant presence of kaolinite (32.5–78.3%), which suggests the importance of its effect on the sorption capacity of proximal terrigenous shales.
Fish migration in rivers is a growing area of concern as mounting anthropogenic influences, particularly fragmentation from dams and barriers, constitute major threats to global river species diversity. Barriers can impede the movement of fishes between areas critical to the completion of their lifecycle, affecting both population and ecosystem viability. In response, fish passage solutions have been identified as a critical need to maintain fisheries viability in the Laurentian Great Lakes, and around the world. Pivotal to the success of these fish passage solutions is a more complete understanding of the movement phenology and environmental cues that instigate migration. We used a dual-frequency identification sonar (DIDSON) to evaluate environmental triggers of river entry during spring and summer for three size classes of migratory fishes in the Boardman River, a Lake Michigan tributary. Our results indicate that medium size fish (>30 cm and < 50 cm), primarily composed of white sucker Catostomus commersonii and longnose sucker Catostomus catostomus were 21% more likely to enter the river at sunset and 25% less likely at midnight in comparison to midday. Entry rates of medium fish increased 6% for every 1 °C increase in river temperature, 4% for every 1 m3/s increase in river discharge from the day prior, and were reduced by 1% for every 10 cm increase in lake level. Understanding these processes in the tributaries of the Great Lakes is important to inform the fish passage solutions currently being developed for the Boardman River, and to inform management regulations for Great Lakes migratory fishes.
Researchers at the U.S. Geological Survey (USGS) and their collaborators conducted a study of the geochemical properties of coals currently produced for electric power generation in the Illinois Basin in Illinois and Indiana. The study follows from recommendations by an expert panel for the USGS to investigate the distribution and controls of trace constituents such as mercury (Hg) in Illinois Basin coals and the behavior of these constituents in coal preparation. A total of 72 new samples were collected by USGS collaborators between 2015 and 2017. These samples include raw coals, prepared coals, and waste coals from coal preparation. To understand the geochemistry and cleaning behavior of these coals, these samples were subjected to an integrated series of analyses described here, including microanalysis of coal constituents and bulk sample chemical analysis. Of the procedures used, whole-sample Hg analysis quantified overall mercury contents and its reduction by coal preparation. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) of pyrite in coal quantified Hg and other potentially harmful elements contained in pyrite, the most likely host of these constituents. Trace elements investigated include those whose emissions are regulated under the U.S. Environmental Protection Agency Mercury and Air Toxics Standards. This report and the corresponding data release, serve as an archive for geochemical data obtained in our study of the geochemistry of Illinois Basin coals. Material included in this report also define approaches used by the USGS over the period of study to characterize coal samples, requiring combined use of results from USGS and non-USGS laboratories.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1135","usgsCitation":"Kolker, A., Scott, C., Lefticariu, L., Mastalerz, M., Drobniak, A., and Scott, A., 2021, Geochemical data for Illinois Basin coal samples, 2015–2018: U.S. Geological Survey Data Series 1135, 14 p., https://doi.org/10.3133/ds1135.","productDescription":"Report: vii, 14 p.; Data Release","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-112300","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":383452,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1135/coverthb.jpg"},{"id":383454,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GUURCK","text":"USGS data release","linkHelpText":"Geochemical data for Illinois Basin coal samples, 2015–2018"},{"id":383453,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1135/ds1135.pdf","text":"Report","size":"4.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1135"}],"country":"United States","state":"Illinois","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.56103515625,\n 40.91351257612758\n ],\n [\n -87.71484375,\n 41.57436130598913\n ],\n [\n -88.76953125,\n 42.13082130188811\n ],\n [\n -89.53857421875,\n 42.114523952464246\n ],\n [\n -90.15380859375,\n 41.376808565702355\n ],\n [\n -91.07666015625,\n 40.79717741518766\n ],\n [\n -91.38427734374999,\n 40.04443758460856\n ],\n [\n -90.76904296874999,\n 39.095962936305476\n ],\n [\n -90.24169921875,\n 38.53097889440024\n ],\n [\n -90.19775390625,\n 38.13455657705411\n ],\n [\n -89.56054687499999,\n 37.70120736474139\n ],\n [\n -89.36279296875,\n 37.10776507118514\n ],\n [\n -89.31884765624999,\n 37.020098201368114\n ],\n [\n -88.70361328125,\n 37.125286284966805\n ],\n [\n -88.26416015625,\n 37.31775185163688\n ],\n [\n -88.06640625,\n 37.735969208590504\n ],\n [\n -87.5830078125,\n 38.58252615935333\n ],\n [\n -87.5390625,\n 39.26628442213066\n ],\n [\n -87.56103515625,\n 40.91351257612758\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Geology, Energy & Minerals Science Center
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12201 Sunrise Valley Drive
954 National Center
Reston, VA 20192
Coking coal, or metallurgical coal, has been produced in the United States for nearly 200 years. Coking coal is primarily used in the production of coke for use in the steel industry, and for other uses (for example, foundries, blacksmithing, heating buildings, and brewing). Currently, U.S. coking coal is produced in Alabama, Arkansas, Pennsylvania, Virginia , and West Virginia. Historically, coking coal has also been produced in 15 other states (Alaska, Colorado, Georgia, Illinois, Indiana, Kentucky, Maryland, Montana, New Mexico, Ohio, Oklahoma, Tennessee, Utah, Washington, and Wyoming), but currently is not. Coals from the Appalachian, Arkoma, and Illinois basins are Pennsylvanian in age, while coals in Alaska, Colorado, Montana, New Mexico, Utah, Washington, and Wyoming range in age from Early Cretaceous through Eocene.
This Open-File Report presents the geographic locations of current and historical coking coal deposits of the United States, with additional information about recent and historical mining and exploration activities. Chemical, rheological, petrographic, and other criteria for evaluating the coking potential of coals are discussed, and historical data for coking coals in the United States are presented. In addition, new coking coal samples from Alabama, Arkansas, Kentucky, and Oklahoma were collected and analyzed for this report, and the data are presented in multiple tables, including proximate and ultimate analyses; calorific value; sulfur forms; major-, minor-, and trace-element abundances; Free-Swelling Index; Gieseler Plastometer analyses; American Society for Testing and Materials (ASTM) dilatation; coal petrography; and predicted values of Coal Stability Factor and Coal Strength after Reaction with CO2 (pCSF and pCSR, respectively). Data from previously analyzed coking coal samples in Kentucky, Pennsylvania, Virginia, and West Virginia were supplied by three companies, including results from all the tests listed above, plus oxidation, Hardgrove Grindability Index, and ash fusion (in a reducing environment) temperatures are also presented in tables in the report.
Geographic Information System (GIS) data compiled for this project are available for download for public and private utilization and may be used to create maps for a variety of energy resource studies. These GIS data are in shapefile format, and metadata files are included describing all GIS processing. Additional geographic information about coking coal areas of the United States are also presented in tabular format in the report, including the following: names of coal basins, fields, regions, districts, and areas; coal beds or zones; geographic locations including States, counties, towns, rivers, mountains, etc.; stratigraphic hierarchy and age of the coal-bearing interval; coking characteristics including sulfur content, ash yield, volatile matter, moisture, calorific value, and Free-Swelling Index; coal rank; names of coal mines and coal-mining companies; current and past mining activity; and references for reports about the coal.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201113","usgsCitation":"Trippi, M.H., Ruppert, L.F., Eble, C.F., and Hower, J.C., 2021, Coking coal of the United States—Modern and historical coking coal mining locations and chemical, rheological, petrographic, and other data from modern samples: U.S. Geological Survey Open-File Report 2020–1113, 112 p., https://doi.org/10.3133/ofr20201113.","productDescription":"Report: xi, 112 p.; Tables 1.1-21.1; Data Release; Metadata; Spatial Data","numberOfPages":"112","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-111543","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":381899,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1113/ofr20201113_appendix_tables_csv.zip","text":"Tables","size":"88.9 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Zip file of tables 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Using a geology-based assessment methodology, the U.S. Geological Survey estimated a mean of 1,407 billion (1.4 trillion) cubic feet of gas in conventional accumulations in Upper Devonian to Lower Cretaceous strata of the western North Slope, Alaska.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213003","usgsCitation":"Houseknecht, D.W., Mercier, T.J., Schenk, C.J., Moore, T.E., Rouse, W.A., Dumoulin, J.A., Craddock, W.H., Lease, R.O., Botterell, P.J., Sanders, M.M., Smith, R.A., Connors, C.D., Garrity, C.P., Whidden, K.J., Gooley, J.T., Counts, J.W., Long, J.H., and DeVera, C.A., 2021, Assessment of undiscovered gas resources in Upper Devonian to Lower Cretaceous strata of the western North Slope, Alaska, 2021: U.S. Geological Survey Fact Sheet 2021-3003, 4 p., https://doi.org/10.3133/fs20213003.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"N","ipdsId":"IP-125170","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":382891,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3003/coverthb.jpg"},{"id":382892,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3003/fs20213003.pdf","text":"Report","size":"1.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2021-3003"},{"id":382893,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C3N5VV","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project - Northern Alaska Province, Western North Slope Assessment Unit Boundaries and Assessment Input Data Forms"}],"country":"United States","state":"Alaska","otherGeospatial":"North Slope","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -166.640625,\n 66.16051056018838\n ],\n [\n -155.302734375,\n 66.16051056018838\n ],\n [\n -155.302734375,\n 71.49703690095419\n ],\n [\n -166.640625,\n 71.49703690095419\n ],\n [\n -166.640625,\n 66.16051056018838\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Geology, Energy & Minerals Science Center
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Salinity in the Colorado River Basin causes an estimated $300 to $400 million per year in economic damages in the U.S. To inform and improve salinity‐control efforts, this study quantifies long‐term trends in salinity (dissolved solids) across the Upper Colorado River Basin (UCRB), including time periods prior to the construction of large dams and preceding the implementation of salinity‐control projects. Weighted Regressions on Time, Discharge, and Season was used with datasets of dissolved‐solids and specific‐conductance measurements, collected as early as 1929, to evaluate long‐term trends in dissolved‐solids loads and concentrations in streams from 1929 to 2019 (n=14). Results indicate that large, widespread, and sustained downward trends in dissolved‐solids concentrations and loads occurred over the last 50 to 90 years. For 12 of the 14 stream sites with significant downward change, median declines of ‐38% (range of ‐14 to ‐57%) and ‐40% (range of ‐9 to ‐65%) were observed for flow‐normalized concentration and load, respectively. Steepest rates of decline occurred from 1980 to 2000, coincident with the initiation of salinity‐control efforts in the 1980s. However, there was a consistent slowing or reversing of downward trends after 2000 even though salinity‐control efforts continued. Significant decreases in salinity occurred as early as the 1940s at some streams, indicating that, in addition to salinity‐control projects, changes in land cover, land use, and/or climate substantially affect salinity transport in the UCRB. Observed dissolved‐solids trends are likely the result of changes to watershed‐related processes, not due to changes in the streamflow regime.
Remote oceanic islands have high potential to harbor unique fauna and flora, but opportunities to conduct in-depth biotic surveys are often limited. Furthermore, underrepresentation of existing biodiversity in the literature has the potential to detract from conservation planning and action. Between 18 and 29 October 2018, we surveyed the terrestrial vertebrates of East Rennell, a UNESCO World Heritage Site in Solomon Islands. We documented 56 species, including 15 squamates, 13 mammals, and 38 birds, and present four new vertebrate records for the island: Stephan's emerald dove (Chalcophaps stephani), Maluku myotis (Myotis moluccarum), littoral skink (Emoia atrocostata) and brahminy blindsnake (Indotyphlops braminus). East Rennell was designated a World Heritage site for its significant on-going ecological and biological processes, and importance for the study of island biogeography. The new records presented here provide evidence that continued field studies combined with DNA analysis will continue to uncover even greater endemic biodiversity. Rennell is currently experiencing major habitat destruction in parts of the island that are not under World Heritage protection, and we anticipate collateral damage will likely extend into protected areas. Our survey also underscores the incredible vertebrate biodiversity that stands to be lost unless conservation actions and local community needs are intertwined to promote beneficial outcomes on both fronts.
Infectious Hematopoietic Necrosis Virus (IHNV) infects juvenile salmonid fish in conservation hatcheries and aquaculture facilities, and in some cases, causes lethal disease. This study assesses intra-specific variation in the IHNV susceptibility of Chinook salmon (Oncorhynchus tshawytscha) in the Columbia River Basin (CRB), in the northwestern United States. The virulence and infectivity of IHNV strains from three divergent virus genogroups are measured in four Chinook salmon populations, including spring-run and fall-run fish from the lower or upper regions of the CRB. Following controlled laboratory exposures, our results show that the positive control L strain had significantly higher virulence, and the UC and MD strains that predominate in the CRB had equivalently low virulence, consistent with field observations. By several experimental measures, there was little variation in host susceptibility to infection or disease. However, a small number of exceptions suggested that the lower CRB spring-run Chinook salmon population may be less susceptible than other populations tested. The UC and MD viruses did not differ in infectivity, indicating that the observed asymmetric field prevalence in which IHNV detected in CRB Chinook salmon is 83% UC and 17% MD is not due to the UC virus being more infectious. Overall, we report little intra-species variation in CRB Chinook salmon susceptibility to UC or MD IHNV infection or disease, and suggest that other factors may instead influence the ecology of IHNV in the CRB.
","language":"English","publisher":"MDPI","doi":"10.3390/v13040701","usgsCitation":"Hernandez, D.G., Brown, W.E., Naish, K.A., and Kurath, G., 2021, Virulence and infectivity of UC, MD and L strains of infectious hematopoietic necrosis virus (IHNV) in four populations of Columbia River Basin Chinook salmon: Viruses, v. 13, no. 4, 701, 25 p., https://doi.org/10.3390/v13040701.","productDescription":"701, 25 p.","ipdsId":"IP-127662","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":452642,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/v13040701","text":"Publisher Index Page"},{"id":385459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Columbia River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6513671875,\n 44.02442151965934\n ],\n [\n -114.7412109375,\n 44.02442151965934\n ],\n [\n -114.7412109375,\n 53.30462107510271\n ],\n [\n -122.6513671875,\n 53.30462107510271\n ],\n [\n -122.6513671875,\n 44.02442151965934\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Hernandez, Daniel G.","contributorId":257868,"corporation":false,"usgs":false,"family":"Hernandez","given":"Daniel","email":"","middleInitial":"G.","affiliations":[{"id":52147,"text":"University of Washington, School of Aquatic and Fishery Sciences, Seattle, WA, 98195, USA","active":true,"usgs":false}],"preferred":false,"id":815185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, William E. 0000-0003-1595-9655","orcid":"https://orcid.org/0000-0003-1595-9655","contributorId":245082,"corporation":false,"usgs":false,"family":"Brown","given":"William","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":815186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Naish, Kerry A. 0000-0002-3275-8778","orcid":"https://orcid.org/0000-0002-3275-8778","contributorId":201136,"corporation":false,"usgs":false,"family":"Naish","given":"Kerry","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":815187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kurath, Gael 0000-0003-3294-560X","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":220175,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":815188,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221858,"text":"70221858 - 2021 - Evaluating lower computational burden approaches for calibration of large environmental models","interactions":[],"lastModifiedDate":"2021-11-16T15:29:25.457376","indexId":"70221858","displayToPublicDate":"2021-04-18T08:52:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating lower computational burden approaches for calibration of large environmental models","docAbstract":"Realistic environmental models used for decision making typically require a highly parameterized approach. Calibration of such models is computationally intensive because widely used parameter estimation approaches require individual forward runs for each parameter adjusted. These runs construct a parameter-to-observation sensitivity, or Jacobian, matrix used to develop candidate parameter upgrades. Parameter estimation algorithms are also commonly adversely affected by numerical noise in the calculated sensitivities within the Jacobian matrix, which can result in unnecessary parameter estimation iterations and less model-to-measurement fit. Ideally, approaches to reduce the computational burden of parameter estimation will also increase the signal-to-noise ratio related to observations influential to the parameter estimation even as the number of forward runs decrease. In this work a simultaneous increments, an iterative ensemble smoother (IES), and a randomized Jacobian approach were compared to a traditional approach that uses a full Jacobian matrix. All approaches were applied to the same model developed for decision making in the Mississippi Alluvial Plain, USA. Both the IES and randomized Jacobian approach achieved a desirable fit and similar parameter fields in many fewer forward runs than the traditional approach; in both cases the fit was obtained in fewer runs than the number of adjustable parameters. The simultaneous increments approach did not perform as well as the other methods due to inability to overcome suboptimal dropping of parameter sensitivities. This work indicates that use of highly efficient algorithms can greatly speed parameter estimation, which in turn increases calibration vetting and utility of realistic models used for decision making.
","language":"English","publisher":"Wiley Publishing","doi":"10.1111/gwat.13106","usgsCitation":"Hunt, R., White, J., Duncan, L.L., Haugh, C., and Doherty, J.E., 2021, Evaluating lower computational burden approaches for calibration of large environmental models: Groundwater, v. 59, no. 6, p. 788-798, https://doi.org/10.1111/gwat.13106.","productDescription":"11 p.","startPage":"788","endPage":"798","ipdsId":"IP-126431","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":452645,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13106","text":"Publisher Index Page"},{"id":436403,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AR7Y02","text":"USGS data release","linkHelpText":"MODFLOW-NWT models and calibration files for the Mississippi Alluvial Plain, USA"},{"id":387106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi Embayment regional aquifer system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.04296874999999,\n 32.69486597787505\n ],\n [\n -87.275390625,\n 32.69486597787505\n ],\n [\n -87.275390625,\n 39.774769485295465\n ],\n [\n -94.04296874999999,\n 39.774769485295465\n ],\n [\n -94.04296874999999,\n 32.69486597787505\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"59","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":208800,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[],"preferred":true,"id":819023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Jeremy T. 0000-0002-4950-1469","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":248830,"corporation":false,"usgs":false,"family":"White","given":"Jeremy T.","affiliations":[{"id":50032,"text":"GNS New Zealand","active":true,"usgs":false}],"preferred":false,"id":819024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duncan, Leslie L. 0000-0002-5938-5721","orcid":"https://orcid.org/0000-0002-5938-5721","contributorId":204004,"corporation":false,"usgs":true,"family":"Duncan","given":"Leslie","email":"","middleInitial":"L.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819025,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haugh, Connor J. 0000-0002-5204-8271","orcid":"https://orcid.org/0000-0002-5204-8271","contributorId":219945,"corporation":false,"usgs":true,"family":"Haugh","given":"Connor J.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819026,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doherty, John E.","contributorId":8817,"corporation":false,"usgs":false,"family":"Doherty","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":7046,"text":"Watermark Numerical Computing","active":true,"usgs":false}],"preferred":false,"id":819027,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220296,"text":"70220296 - 2021 - The seismo-acoustics of submarine volcanic eruptions","interactions":[],"lastModifiedDate":"2021-04-30T12:03:05.512782","indexId":"70220296","displayToPublicDate":"2021-04-18T06:59:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"The seismo-acoustics of submarine volcanic eruptions","docAbstract":"Many of the world’s volcanoes are hidden beneath the ocean’s surface where eruptions are difficult to observe. However, seismo‐acoustic signals produced by these eruptions provide a useful means of identifying active submarine volcanism. A literature survey revealed reports of 119 seismo‐acoustically recorded submarine eruptions since 1939. Submarine eruptions have been recorded in all major tectonic settings, with a range of geochemistries, and at a variety of water depths, but the reports are dominated by eruptions in the Pacific and at only a few locations. Many of the reports offer little detail, with over half of the observations made from distances >500 km, and only about half were confirmed as eruptions by non‐seismo‐acoustic evidence. The reported seismo‐acoustic signals cover a wide variety of processes, including earthquakes, explosions, various types of tremor, signals related to lava extrusion, and landslides. Recorded signals can sometimes be difficult to classify or confidently associate with an eruption, although there has been progress in this regard. Real‐time monitoring of submarine eruptions has been on‐going for several decades on regional and global scales with growing interest and effort in local networks. Real‐time networks are complemented by short‐term instrument deployments that often give more detailed insights into the dynamics and processes of submarine eruptions. Thorough seismo‐acoustic monitoring and study has increased our understanding of submarine eruptions, especially of deep‐sea volcanoes and spreading centers. Despite this, there are still many outstanding questions that need to be addressed for submarine volcanoes to be as well understood and monitored as their terrestrial counterparts.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020912","usgsCitation":"Tepp, G., and Dziak, R.P., 2021, The seismo-acoustics of submarine volcanic eruptions: Journal of Geophysical Research, v. 126, no. 4, e2020JB020912, 29 p., https://doi.org/10.1029/2020JB020912.","productDescription":"e2020JB020912, 29 p.","ipdsId":"IP-121537","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":385403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Tepp, Gabrielle 0000-0001-5388-5138","orcid":"https://orcid.org/0000-0001-5388-5138","contributorId":206305,"corporation":false,"usgs":true,"family":"Tepp","given":"Gabrielle","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":815037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dziak, Robert P. 0000-0001-8775-3416","orcid":"https://orcid.org/0000-0001-8775-3416","contributorId":257794,"corporation":false,"usgs":false,"family":"Dziak","given":"Robert","email":"","middleInitial":"P.","affiliations":[{"id":52124,"text":"NOAA/Pacific Marine Environmental Lab","active":true,"usgs":false}],"preferred":false,"id":815038,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70220316,"text":"70220316 - 2021 - Long‐term surveys support declines in early‐season forest plants used by bumblebees","interactions":[],"lastModifiedDate":"2021-08-03T14:08:51.128094","indexId":"70220316","displayToPublicDate":"2021-04-18T06:58:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Long‐term surveys support declines in early‐season forest plants used by bumblebees","docAbstract":"Fish managers must weigh trade-offs among cost, speed, efficiency, and ecological adaptation when deciding how to translocate native salmonids to either establish or genetically augment populations. Remote site incubators (RSIs) appear to be a reasonable strategy, but large-scale evaluations of this method have been limited. We used 129 RSIs to incubate >35,700 eyed embryos of Westslope Cutthroat Trout Oncorhynchus clarkii lewisi at eight sites within the upper 30 km of the Cherry Creek basin (Madison River, Montana) from 2007 to 2010, after using piscicides to remove all fish. We obtained gametes from 258 parental-pair crosses (164 females and 258 males) from four wild populations and two hatchery broods. All embryos were incubated to the eyed stage in two hatcheries prior to placing them in RSIs. Green-to-eyed egg survivals were higher for progeny of wild-spawned adults (median, 91.0%; 95% CI, 88.7–93.7%) than for progeny of hatchery-spawned adults (median, 81.7%; 95% CI, 74.9–88.4%), and this difference was highly significant (P < 0.01). Over 26,500 fry were counted leaving RSIs. Median embryo-to-fry survival was 75.6% (95% CI, 72.2–79.0%). Fry exited individual RSIs from 8 to 45 d after embryo translocation. Fry survivals differed among years and sites, and year was more important than site in explaining variation in survival. The success of RSI fry introductions was confirmed by annual monitoring of fish abundance, which indicated that abundances of Westslope Cutthroat Trout 5 to 9 years after RSI introductions were equal to or higher than abundances of nonnative salmonids prior to their removal using piscicides.
Archival geolocators have transformed the study of small, migratory organisms but analysis of data from these devices requires bias correction because tags are only recovered from individuals that survive and are re-captured at their tagging location. We show that integrating geolocator recovery data and mark–resight data enables unbiased estimates of both migratory connectivity between breeding and nonbreeding populations and region-specific survival probabilities for wintering locations. Using simulations, we first demonstrate that an integrated Bayesian model returns unbiased estimates of transition probabilities between seasonal ranges. We also used simulations to determine how different sampling designs influence the estimability of transition probabilities. We then parameterized the model with tracking data and mark–resight data from declining Painted Bunting (Passerina ciris) populations breeding in the eastern United States, hypothesized to be threatened by the illegal pet trade in parts of their Caribbean, nonbreeding range. Consistent with this hypothesis, we found that male buntings wintering in Cuba were 20% less likely to return to the breeding grounds than birds wintering elsewhere in their range. Improving inferences from archival tags through proper data collection and further development of integrated models will advance our understanding of the full annual cycle ecology of migratory species.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duab010","usgsCitation":"Rushing, C.S., Van Tatenhove, A.M., Sharp, A., Ruiz-Gutierrez, V., Freeman, M., Sykes, P.W., Given, A.M., and Sillett, T., 2021, Integrating tracking and resight data enables unbiased inferences about migratory connectivity and winter range survival from archival tags: Ornithological Applications, v. 123, no. 2, duab010, https://doi.org/10.1093/ornithapp/duab010.","productDescription":"duab010","ipdsId":"IP-118948","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":452649,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duab010","text":"Publisher Index Page"},{"id":387261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Rushing, Clark S","contributorId":237020,"corporation":false,"usgs":false,"family":"Rushing","given":"Clark","email":"","middleInitial":"S","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":819483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Tatenhove, Aimee M","contributorId":261211,"corporation":false,"usgs":false,"family":"Van Tatenhove","given":"Aimee","email":"","middleInitial":"M","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":819484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sharp, Andrew","contributorId":261213,"corporation":false,"usgs":false,"family":"Sharp","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":819485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":819486,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819488,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sykes, Paul W.","contributorId":214917,"corporation":false,"usgs":false,"family":"Sykes","given":"Paul","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":819489,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Given, Aaron M.","contributorId":49474,"corporation":false,"usgs":true,"family":"Given","given":"Aaron","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":819490,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sillett, T. Scott","contributorId":80788,"corporation":false,"usgs":false,"family":"Sillett","given":"T. Scott","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":819487,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70223435,"text":"70223435 - 2021 - Landscape characterization of floral resources for pollinators in the Prairie Pothole Region of the United States","interactions":[],"lastModifiedDate":"2021-08-26T16:05:22.364676","indexId":"70223435","displayToPublicDate":"2021-04-17T10:22:54","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1006,"text":"Biodiversity and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Landscape characterization of floral resources for pollinators in the Prairie Pothole Region of the United States","docAbstract":"Across agricultural areas of the Prairie Pothole Region (PPR), floral resources are primarily found on public grasslands, roadsides, and private grasslands used as pasture or enrolled in federal conservation programs. Little research has characterized the availability of flowers across the region or identified the primary stakeholders managing lands supporting pollinators. We explored spatial and temporal variability in flower abundance and richness across multiple grassland categories (i.e. general grassland, conservation grassland, and engineered pollinator habitat) in the PPR from 2015 to 2018 and used these data to estimate the number of flowering stems present across the region on private and public land holdings. Both flowering plant abundance and richness were greatest on engineered pollinator habitat, but this land category encompassed <0.01% of the total grassland area in the PPR. There was a steady decrease in flower abundance over the growing season across all land categories. We detected considerable variation in flower abundance and richness across grassland categories, indicating that not all natural or semi-natural covers provide similar value to pollinators. At a landscape scale, large land holdings such as privately-owned grasslands and Conservation Reserve Program lands contributed the greatest number of flowers by an order of magnitude, though these lands collectively did not support the greatest abundance of flowers per unit area. Our research depicts spatial and temporal variation in pollinator resources across the region. Further, our research will assist managers and policy makers in understanding the role of public and private lands and conservation programs in supporting pollinators.
","language":"English","publisher":"Springer","doi":"10.1007/s10531-021-02177-9","usgsCitation":"Smart, A.H., Otto, C., Gallant, A.L., and Simanonok, M., 2021, Landscape characterization of floral resources for pollinators in the Prairie Pothole Region of the United States: Biodiversity and Conservation, v. 30, p. 1991-2015, https://doi.org/10.1007/s10531-021-02177-9.","productDescription":"25 p.","startPage":"1991","endPage":"2015","ipdsId":"IP-123388","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":388547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, North Dakota, South Dakota","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.0625,\n 48.019324184801185\n ],\n [\n -103.02978515625,\n 48.06339653776211\n ],\n [\n -102.76611328125,\n 47.82790816919329\n ],\n [\n -102.45849609375,\n 47.45780853075031\n ],\n [\n -101.689453125,\n 47.47266286861342\n ],\n [\n -100.8984375,\n 46.63435070293566\n ],\n [\n -100.6787109375,\n 45.55252525134013\n ],\n [\n -101.09619140625,\n 44.653024159812\n ],\n [\n -99.580078125,\n 43.91372326852401\n ],\n [\n -99.60205078124999,\n 43.59630591596548\n ],\n [\n -98.32763671875,\n 42.76314586689492\n ],\n [\n -97.80029296875,\n 42.8115217450979\n ],\n [\n -96.6796875,\n 42.58544425738491\n ],\n [\n -96.3720703125,\n 43.58039085560784\n ],\n [\n -92.30712890625,\n 43.50075243569041\n ],\n [\n -93.75732421875,\n 45.38301927899065\n ],\n [\n -97.2509765625,\n 48.99463598353405\n ],\n [\n -104.08447265624999,\n 49.009050809382046\n ],\n [\n -104.0625,\n 48.019324184801185\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","noUsgsAuthors":false,"publicationDate":"2021-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Smart, Autumn H. 0000-0003-0711-3035","orcid":"https://orcid.org/0000-0003-0711-3035","contributorId":228828,"corporation":false,"usgs":true,"family":"Smart","given":"Autumn","email":"","middleInitial":"H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":822058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":822036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":822059,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simanonok, Michael P. 0000-0002-4710-4515","orcid":"https://orcid.org/0000-0002-4710-4515","contributorId":229685,"corporation":false,"usgs":true,"family":"Simanonok","given":"Michael P.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":822060,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220566,"text":"70220566 - 2021 - Pesticides in US Rivers: Regional differences in use, occurrence, and environmental toxicity, 2013 to 2017","interactions":[],"lastModifiedDate":"2021-06-30T18:55:17.802352","indexId":"70220566","displayToPublicDate":"2021-04-17T07:30:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Pesticides in US Rivers: Regional differences in use, occurrence, and environmental toxicity, 2013 to 2017","docAbstract":"Pesticides pose a threat to the environment, but because of the substantial number of compounds, a comprehensive assessment of pesticides and an evaluation of the risk that they pose to human and aquatic life is challenging. In this study, improved analytical methods were used to quantify 221 pesticide concentrations in surface waters over the time period from 2013 to 2017. Samples were collected from 74 river sites in the conterminous US (CONUS). Potential toxicity was assessed by comparing surface water pesticide concentrations to standard concentrations that are considered to have adverse effects on human health or aquatic organisms. The majority of pesticide use is related to agriculture, and agricultural production varies across the CONUS. Therefore, our results were summarized by region (Northeast, South, Midwest, West and Pacific), with the expectation that crop production differences would drive variability in pesticide use, detection frequency, and benchmark exceedance patterns. Although agricultural pesticide use was at least 2.5 times higher in the Midwest (49 kg km−2) than in any of the other four regions (Northeast, South, West, and Pacific, 3 to 21 kg km−2) and the average number of pesticides detected in the Midwest was at least 1.5 higher (n = 25) than the other four regions (n = 8 to n = 16), the potential toxicity results were more evenly distributed. At least 50% of the sites within each of the 5 regions had at least 1 chronic benchmark exceedance. Imidacloprid posed the greatest potential threat to aquatic life with a total of 245 benchmark exceedances at 60 of the 74 sites. These results show that pesticides persist in the environment beyond the site of application and expected period of use. Continued monitoring and research are needed to improve our understanding of pesticide effects on aquatic and human life.
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sstackpoole@usgs.gov","orcid":"https://orcid.org/0000-0002-5876-4922","contributorId":3784,"corporation":false,"usgs":true,"family":"Stackpoole","given":"Sarah","email":"sstackpoole@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":816038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shoda, Megan E. 0000-0002-5343-9717 meshoda@usgs.gov","orcid":"https://orcid.org/0000-0002-5343-9717","contributorId":4352,"corporation":false,"usgs":true,"family":"Shoda","given":"Megan","email":"meshoda@usgs.gov","middleInitial":"E.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes 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Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Range expansion and factors affecting abundance of invasive Flathead Catfish in the Delaware and Susquehanna Rivers, Pennsylvania, USA","docAbstract":"Flathead Catfish Pylodictis olivaris have been either intentionally or accidentally introduced into Atlantic Slope drainages extending from Florida to Pennsylvania and have quickly become established. In Pennsylvania, Flathead Catfish were first detected in the Schuylkill River at the Fairmont Dam in 1999 and in the Susquehanna River at Safe Harbor Dam in 2002. The species has since moved throughout the respective basins, with subsequent detections during 244 riverine surveys in these drainages. Fishway and electrofishing surveys in the tidal Schuylkill River, a Delaware River tributary, have documented an increase in abundances since 2004, when the surveys were first implemented. Hoop-net surveys in nontidal large-river reaches found mean (±SD) catch rates varying from 0.00 to 4.51 ± 4.38 fish/series. A Bayesian hierarchical Poisson regression model indicated that Flathead Catfish abundance decreased as the distance from the initial point of detection increased, demonstrating a general pattern of fish expansion upstream from the point of detection. The distance downstream of the nearest dam, although not significant, had a relatively high posterior probability of being negatively correlated with Flathead Catfish abundance. Ongoing and future targeted surveys should help to better understand changes in the distribution and abundance of Flathead Catfish in these systems.
","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10628","usgsCitation":"Smith, G.D., Massie, D.L., Perillo, J., Wagner, T., and Pierce, D., 2021, Range expansion and factors affecting abundance of invasive Flathead Catfish in the Delaware and Susquehanna Rivers, Pennsylvania, USA: North American Journal of Fisheries Management, v. 41, no. S1, p. S205-S220, https://doi.org/10.1002/nafm.10628.","productDescription":"16 p.","startPage":"S205","endPage":"S220","ipdsId":"IP-116902","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Delaware River, Juniata River, Lehigh River, Schuylkill River, Susquehanna River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.7774658203125,\n 39.7240885773337\n ],\n [\n -75.73974609375,\n 39.7240885773337\n ],\n [\n -75.16845703124999,\n 39.80853604144591\n ],\n [\n -74.619140625,\n 40.111688665595956\n ],\n [\n -75.16845703124999,\n 40.713955826286046\n ],\n [\n -74.94873046875,\n 40.863679665481676\n ],\n [\n -75.08056640625,\n 40.9964840143779\n ],\n [\n -74.739990234375,\n 41.45919537950706\n ],\n [\n -74.81689453125,\n 41.463311976686235\n ],\n [\n -74.9542236328125,\n 41.50446357504803\n ],\n [\n -75.0311279296875,\n 41.611335399441735\n ],\n [\n -75.0311279296875,\n 41.775408403663285\n ],\n [\n -75.1025390625,\n 41.87774145109676\n ],\n [\n -75.223388671875,\n 41.89001042401827\n ],\n [\n -75.322265625,\n 42.00848901572399\n ],\n [\n -78.7335205078125,\n 42.00032514831621\n ],\n [\n -78.7774658203125,\n 39.7240885773337\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"S1","noUsgsAuthors":false,"publicationDate":"2021-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Geoffrey D.","contributorId":274361,"corporation":false,"usgs":false,"family":"Smith","given":"Geoffrey","email":"","middleInitial":"D.","affiliations":[{"id":36966,"text":"Pennsylvania Fish and Boat Commission","active":true,"usgs":false}],"preferred":false,"id":834438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Massie, Danielle L.","contributorId":196717,"corporation":false,"usgs":false,"family":"Massie","given":"Danielle","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":834439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perillo, Joseph","contributorId":275966,"corporation":false,"usgs":false,"family":"Perillo","given":"Joseph","email":"","affiliations":[{"id":56915,"text":"Philadelphia Water Department","active":true,"usgs":false}],"preferred":false,"id":834440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834437,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pierce, Daryl","contributorId":276044,"corporation":false,"usgs":false,"family":"Pierce","given":"Daryl","email":"","affiliations":[{"id":36966,"text":"Pennsylvania Fish and Boat Commission","active":true,"usgs":false}],"preferred":false,"id":834514,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70219983,"text":"ofr20211033 - 2021 - Connectivity of Mojave Desert tortoise populations—Management implications for maintaining a viable recovery network","interactions":[],"lastModifiedDate":"2021-04-19T11:44:39.479074","indexId":"ofr20211033","displayToPublicDate":"2021-04-16T12:10:46","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1033","displayTitle":"Connectivity of Mojave Desert Tortoise Populations: Management Implications for Maintaining a Viable Recovery Network","title":"Connectivity of Mojave Desert tortoise populations—Management implications for maintaining a viable recovery network","docAbstract":"The historic distribution of Mojave desert tortoises (Gopherus agassizii) was relatively continuous across the range, and the importance of tortoise habitat outside of designated tortoise conservation areas (TCAs) to recovery has long been recognized for its contributions to supporting gene flow between TCAs and to minimizing impacts and edge effects within TCAs. However, connectivity of Mojave desert tortoise populations has become a concern because of recent and proposed development of large tracts of desert tortoise habitat that cross, fragment, and surround designated conservation areas. This paper summarizes the underlying concepts and importance of connectivity for Mojave desert tortoise populations by reviewing current information on connectivity and providing information to managers for maintaining or enhancing desert tortoise population connectivity as they consider future proposals for development and management actions.
Maintaining an ecological network for the Mojave desert tortoise, with a system of core habitats (TCAs) connected by linkages, is necessary to support demographically viable populations and long-term gene flow within and between TCAs. There are four points for wildlife and land-management agencies to consider when making decisions that could affect connectivity of Mojave desert tortoise populations (for example, in updating actions in resource management plans or amendments that could help maintain or restore functional connectivity in light of the latest information):
Each TCA has unique strengths and weaknesses regarding its ability to support minimum sustainable populations based on areal extent and its ability to support population increases based on landscape connection with adjacent populations. Considering how proposed projects (inside or outside of TCAs) affect connectivity and the ability of TCAs to support at least 5,000 adult tortoises (the numerical goal for each TCA) could help managers to maintain the resilience of TCAs to population declines. The same project, in an alternative location, could have very different impacts on local and regional populations. For example, within the habitat matrix surrounding TCAs, narrowly delineated corridors may not allow for natural population dynamics if they do not accommodate overlapping home ranges along most of their widths so that tortoises reside, grow, find mates, and produce offspring that can replace older tortoises. In addition, most habitat outside TCAs may receive more surface disturbance than habitat within TCAs. Therefore, managing the entire remaining matrix of desert tortoise habitat for permeability may be better than delineating fixed corridors. These concepts apply, especially given uncertainty about long-term condition of habitat, within and outside of TCAs under a changing climate.
Ultimately, questions such as “What are the critical linkages that need to be protected?” could be better framed as “How can we manage the remaining habitat matrix in ways that sustain ecological processes and habitat suitability for special status species?” Land-management decisions made in the context of the latter question may be more conducive to maintenance of a functional ecological network.
In California, the Bureau of Land Management established 0.1–1.0 percent caps on new surface-disturbance for TCAs and mapped linkages that address the issues described in number 1 of this list.
Nevada, Utah, and Arizona currently do not have surface-disturbance limits. Limits comparable to those in the Desert Renewable Energy Conservation Plan (DRECP) would be 0.5 percent within TCAs and 1 percent within the linkages modeled by Averill-Murray and others (2013). Limits in some areas of California within the Desert Renewable Energy Conservation Plan, such as Ivanpah Valley, are more restrictive, at 0.1 percent. Continuity across the state line in Nevada could be achieved with comparable limits in the adjacent portion of Ivanpah Valley, as well as the Greater Trout Canyon Translocation Area and the Stump Springs Regional Augmentation Site. These more restrictive limits would help protect remaining habitat in the major interstate connectivity pathway through Ivanpah Valley and focal areas of population augmentation that provide additional population connectivity along the western flank of the Spring Mountains.
In a recent study that analyzed 13 years of desert tortoise monitoring data, nearly all desert tortoise observations were at sites in which 5 percent or less of the surrounding landscape within 1 kilometer was disturbed (Carter and others, 2020a). To help maintain tortoise habitability and permeability across all other non-conservation-designated tortoise habitat, all surface disturbance could be limited to less than 5-percent development per square kilometer because the 5-percent threshold for development is the point at which tortoise occupation drops precipitously (Carter and others, 2020a). However, although individual desert tortoises were observed at development levels up to 5 percent, we do not know the fitness or reproductive characteristics of these individuals. This level of development also may not allow for long-term persistence of healthy populations that are of adequate size needed for demographic or functional connectivity; therefore, a conservative interpretation suggests that, ideally, development could be lower. Lower development levels would be particularly useful in areas within the upper 5th percentile of connectivity values modeled by Gray and others (2019).
Reducing ancillary threats in places where connectivity is restricted to narrow strips of habitat, for example, narrow mountain passes or vegetated strips between solar development, could enhance the functionality of these vulnerable linkages. In such areas, maintaining multiple, redundant linkages could further enhance overall connectivity.
Minimization of mortality from roads and maximization of passage under roads. Roads pose a significant threat to the long-term persistence of local tortoise populations, and roads of high traffic volume lead to severe population declines, which ultimately fragments populations farther away from the roads. Three points (a.–c.) pertain to reducing direct mortality of tortoises on the many paved roads that cross desert tortoise habitat and to maintaining a minimal level of permeability across these roads:
Tortoise-exclusion fencing tied into culverts, underpasses, overpasses, or other passages below roads in desert tortoise habitat, would limit vehicular mortality of tortoises and provide opportunities for movement across the roads. Installation of shade structures on the habitat side of fences installed in areas with narrow population-depletion zones would limit overheating of tortoises that may pace the fence.
Passages below highways could be maintained or retrofitted to ensure safe tortoise access, for example, by filling eroded drop-offs or modifying erosion-control features such as rip-rap to make them safer and more passable for tortoises. Wildlife management agencies could work with transportation departments to develop construction standards that are consistent with hydrologic/erosion management goals, while also incorporating a design and materials consistent with tortoise survival and passage and make the standards widely available. The process would be most effective if the status of passages was regularly monitored and built into management plans.
Healthy tortoise populations along fenced highways could be supported by ensuring that land inside tortoise-exclusion fences is not so degraded that it leads to degradation of tortoise habitat outside the exclusion areas. For example, severe invasive plant infestations inside a highway exclusion could cause an increase of invasive plants outside the exclusion area and degrade habitat; therefore, invasive plants inside road rights of way could be mown or treated with herbicide to limit their spread into adjacent tortoise habitat and minimize the risk of these plants carrying wildfires into adjacent habitat.
Adaptation of management based on new information. Future research will continue to build upon and refine models related to desert tortoise population connectivity and develop new ones. New models could consider landscape levels of development and be constructed such that they share common foundations to support future synthesis efforts. If model development was undertaken in partnership with entities that are responsible for management of desert tortoise habitat, it would facilitate incorporation of current and future modeling results into their land management decisions. There are specific topics that may be clarified with further evaluation:
The effects of climate change on desert tortoise habitat, distribution, and population connectivity;
The effects of large-scale fires, especially within repeatedly burned habitat, on desert tortoise distribution and population connectivity;
The ability of solar energy facilities or similar developments to support tortoise movement and presence by leaving washes intact; leaving native vegetation intact whenever possible, or if not possible, mowing the site, allowing vegetation to re-sprout, and managing weeds; and allowing tortoises to occupy the sites; and
The design and frequency of underpasses necessary to maintain functional demographic and genetic connectivity across linear features, like highways.
Wildlife Program
Prepared in cooperation with the U.S. Fish and Wildlife Service
","usgsCitation":"Averill-Murray, R.C., Esque, T.C., Allison, L.J., Bassett, S., Carter, S.K., Dutcher, K.E., Hromada, S.J., Nussear, K.E., and Shoemaker, K., 2021, Connectivity of Mojave Desert tortoise populations—Management implications for maintaining a viable recovery network: U.S. Geological Survey Open-File Report 2021–1033, 23 p., https://doi.org/10.3133/ofr20211033.","productDescription":"vi, 23 p.","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-125269","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":385161,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1033/covrthb.jpg"},{"id":385162,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1033/ofr20211033.pdf","text":"Report","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":385163,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1033/images"},{"id":385164,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1033/ofr20211033.xml"}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.71923828124999,\n 33.669496972795535\n ],\n [\n -113.8623046875,\n 33.578014746143985\n ],\n [\n -112.69775390625,\n 33.50475906922609\n ],\n [\n -111.51123046875,\n 33.284619968887675\n ],\n [\n -111.73095703125,\n 34.10725639663118\n ],\n [\n -111.9287109375,\n 35.51434313431818\n ],\n [\n -113.00537109375,\n 36.24427318493909\n ],\n [\n -114.3896484375,\n 36.73888412439431\n ],\n [\n -115.86181640625001,\n 37.07271048132943\n ],\n [\n -117.42187500000001,\n 37.68382032669382\n ],\n [\n -118.27880859375001,\n 37.579412513438385\n ],\n [\n -117.7734375,\n 35.97800618085566\n ],\n [\n -117.72949218749999,\n 35.44277092585766\n ],\n [\n -118.76220703125001,\n 34.75966612466248\n ],\n [\n -117.99316406249999,\n 34.488447837809304\n ],\n [\n -116.74072265625,\n 34.288991865037524\n ],\n [\n -114.71923828124999,\n 33.669496972795535\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Interactions between climate and hydrogeologic settings contribute to the hydrologic and chemical variability among depressional wetlands, which influences their aquatic communities. These interactions and resulting variability have led to inconsistent results in terms of identifying reliable predictors of aquatic-macroinvertebrate community composition for depressional wetlands. This is especially true in the Prairie Pothole Region of North America where, in addition to pronounced climate variability, studies are often confounded by fish introductions. We used environmental monitoring data collected over a 24-year period from a complex of sixteen depressional wetlands and structural equation modeling techniques that incorporated theoretical and empirical relationships outlined in the Wetland Continuum to identify key environmental (climate and hydrogeologic setting) and biotic (competition and predation) drivers of aquatic-macroinvertebrate community composition for prairie-pothole wetlands. Uplands in the study area were primarily native prairie, thus, embedded wetlands were impacted minimally by agricultural influences. Additionally, study wetlands were predominately fishless. In the absence of the overwhelming influence of fishes, major drivers influencing aquatic-macroinvertebrate communities were revealed through the use of data spanning multidecadal-long climate cycles. We found variables related to the placement of wetlands along axes of the Wetland Continuum, e.g., hydrogeologic setting (relative wetland elevation) and hydroclimatic setting (proportion of wetland ponded), to be influential drivers of within-wetland habitat characteristics, such as the proportion of open-water area, which in turn was the strongest predictor of macroinvertebrate community composition. In contrast, predatory invertebrate and salamander abundance and non-predatory invertebrate biomass (i.e., predation and competition) were found to have minimal influence on community composition.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2021.107678","usgsCitation":"McLean, K., Mushet, D.M., Newton, W.E., and Sweetman, J.N., 2021, Long-term multidecadal data from a prairie-pothole wetland complex reveal controls on aquatic-macroinvertebrate communities: Ecological Indicators, v. 126, 107678, 11 p., https://doi.org/10.1016/j.ecolind.2021.107678.","productDescription":"107678, 11 p.","ipdsId":"IP-094142","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":452658,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2021.107678","text":"Publisher Index Page"},{"id":396116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Cottonwood Lake Study Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.70600509643555,\n 47.85014598272475\n ],\n [\n -100.60781478881836,\n 47.85014598272475\n ],\n [\n -100.60781478881836,\n 47.9002325297653\n ],\n [\n -100.70600509643555,\n 47.9002325297653\n ],\n [\n -100.70600509643555,\n 47.85014598272475\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McLean, Kyle 0000-0003-3803-0136 kmclean@usgs.gov","orcid":"https://orcid.org/0000-0003-3803-0136","contributorId":168533,"corporation":false,"usgs":true,"family":"McLean","given":"Kyle","email":"kmclean@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":835106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mushet, David M. 0000-0002-5910-2744","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":248538,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":835107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Newton, Wesley E. 0000-0002-1377-043X wnewton@usgs.gov","orcid":"https://orcid.org/0000-0002-1377-043X","contributorId":3661,"corporation":false,"usgs":true,"family":"Newton","given":"Wesley","email":"wnewton@usgs.gov","middleInitial":"E.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":835108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sweetman, Jon N.","contributorId":279537,"corporation":false,"usgs":false,"family":"Sweetman","given":"Jon","email":"","middleInitial":"N.","affiliations":[{"id":12471,"text":"North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":835109,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222459,"text":"70222459 - 2021 - Stock composition of Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) encountered in marine and estuarine environments on the U.S. Atlantic Coast","interactions":[],"lastModifiedDate":"2021-09-14T16:40:31.75938","indexId":"70222459","displayToPublicDate":"2021-04-16T08:54:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Stock composition of Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) encountered in marine and estuarine environments on the U.S. Atlantic Coast","title":"Stock composition of Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) encountered in marine and estuarine environments on the U.S. Atlantic Coast","docAbstract":"Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) is a large, anadromous fish native to the Atlantic Coast of North America. Although this species once supported important fisheries, centuries of exploitation and habitat degradation have resulted in dramatic declines, presumed extirpation in some rivers, and ultimately listing under the U.S. Endangered Species Act (ESA). Under the ESA, Atlantic sturgeon are listed as five separate Distinct Population Segments (DPSs), which form the basis for federal management. Despite state and federal protections Atlantic sturgeon still face significant threats to their recovery, including fisheries bycatch mortality, marine construction, dredging, dams, and vessel strikes. However, because subadult and adult Atlantic sturgeon migrate extensively across estuarine and marine environments and frequently form mixed-stock aggregations in non-natal habitats, it can be difficult to determine how these threats impact specific populations and DPSs. To better understand ontogenetic shifts in habitat use and stock-specific exposure to anthropogenic threats, we performed a mixed-stock analysis of 1704 Atlantic sturgeon encountered across the U.S. Atlantic Coast. Collections made north of Cape Cod, MA and south of Cape Hatteras, NC were dominated by individuals from regional stocks; however, we found extensive stock mixing in the mid-Atlantic region, particularly in coastal environments where individuals from all five DPSs were commonly observed. Subadults and adults that were encountered in offshore environments had moved, on average, 277 km from their natal source; however, 23% were sampled over 500 km from their natal river suggesting long-distance movements are relatively common in these age classes. Overall, our work highlights that Atlantic sturgeon populations are vulnerable to threats over vast areas and emphasizes the need for continued genetic monitoring to track recovery progress.
Lahontan Cutthroat Trout (LCT) Oncorhynchus clarkii henshawi have experienced some of the most marked reductions in abundance and distribution among Cutthroat Trout subspecies. The population of LCT in Pyramid Lake, Nevada has returned from the brink of extirpation, and although it is highly managed via stocking, the population is thriving and has recently started to reproduce naturally. Our objectives were to determine (1) whether predator and prey remain tightly coupled, (2) whether LCT are food limited, and (3) the status of the LCT population with regard to the potential prey-based contemporary carrying capacity. We used a multifaceted approach, including intensive field sampling of fish, bioenergetics modeling, cohort reconstruction, and comparisons of prey availability to consumption. We estimated that the average population of LCT in Pyramid Lake is 1.2 million, average annual stocking is 650,000, and the number of fish angled ranges from 5,000 to 14,000 per year, with a 90% release rate. Driven by seasonal and size variation in consumption, individual annual consumption by LCT varied from 667 to 992 g/year for small LCT (200–400 mm TL) and from 2,388 to 3,057 g/year for large LCT (>400 mm TL). Lahontan Cutthroat Trout are consuming, on average, 14–63% of the standing crop of Tui Chub Siphateles bicolor annually, indicating that LCT are currently not exceeding their prey-based carrying capacity. The LCT in Pyramid Lake remain tightly coupled to their primary native prey, Tui Chub, despite considerable changes to the ecosystem; therefore, managing for a robust population of LCT translates largely to managing for forage fish. This supply-versus-demand issue is of particular concern for Pyramid Lake given that the density of Tui Chub may be declining concordant with declining lake elevation. Given the conservation importance of this LCT population, careful monitoring is critical; however, “predation inertia” indicates that effective short-term management in response to fluctuations in forage fishes is likely possible.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10291","usgsCitation":"Budy, P., Heredia, N.A., Thiede, G.P., and Horgen, E., 2021, Exploring the contemporary relationship between predator and prey in a significant, reintroduced Lahontan Cutthroat Trout population: Transactions of the American Fisheries Society, v. 150, no. 3, p. 291-306, https://doi.org/10.1002/tafs.10291.","productDescription":"16 p.","startPage":"291","endPage":"306","ipdsId":"IP-119395","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":396479,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Pyramid Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.7344970703125,\n 39.85072092501597\n ],\n [\n -119.36920166015624,\n 39.85072092501597\n ],\n [\n -119.36920166015624,\n 40.22082997283287\n ],\n [\n -119.7344970703125,\n 40.22082997283287\n ],\n [\n -119.7344970703125,\n 39.85072092501597\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"150","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":836014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heredia, Nicholas A.","contributorId":181858,"corporation":false,"usgs":false,"family":"Heredia","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":836015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thiede, Gary P.","contributorId":9154,"corporation":false,"usgs":true,"family":"Thiede","given":"Gary","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":836016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horgen, Erik","contributorId":280086,"corporation":false,"usgs":false,"family":"Horgen","given":"Erik","email":"","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":836017,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220383,"text":"70220383 - 2021 - On the human appropriation of wetland primary production","interactions":[],"lastModifiedDate":"2021-05-10T12:49:38.118494","indexId":"70220383","displayToPublicDate":"2021-04-16T07:43:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"On the human appropriation of wetland primary production","docAbstract":"Humans are changing the Earth's surface at an accelerating pace, with significant consequences for ecosystems and their biodiversity. Landscape transformation has far-reaching implications including reduced net primary production (NPP) available to support ecosystems, reduced energy supplies to consumers, and disruption of ecosystem services such as carbon storage. Anthropogenic activities have reduced global NPP available to terrestrial ecosystems by nearly 25%, but the loss of NPP from wetland ecosystems is unknown. We used a simple approach to estimate aquatic NPP from measured habitat areas and habitat-specific areal productivity in the largest wetland complex on the USA west coast, comparing historical and modern landscapes and a scenario of wetland restoration. Results show that a 77% loss of wetland habitats (primarily marshes) has reduced ecosystem NPP by 94%, C (energy) flow to herbivores by 89%, and detritus production by 94%. Our results also show that attainment of habitat restoration goals could recover 12% of lost NPP and measurably increase carbon flow to consumers, including at-risk species and their food resources. This case study illustrates how a simple approach for quantifying the loss of NPP from measured habitat losses can guide wetland conservation plans by establishing historical baselines, projecting functional outcomes of different restoration scenarios, and establishing performance metrics to gauge success.