{"pageNumber":"420","pageRowStart":"10475","pageSize":"25","recordCount":184785,"records":[{"id":70227367,"text":"sir20215119 - 2022 - Characterization of ambient groundwater quality within a statewide, fixed-station monitoring network in Pennsylvania, 2015–19","interactions":[],"lastModifiedDate":"2026-04-02T19:50:24.033174","indexId":"sir20215119","displayToPublicDate":"2022-01-18T09:40:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5119","displayTitle":"Characterization of Ambient Groundwater Quality Within a Statewide, Fixed-Station Monitoring Network in Pennsylvania, 2015–19","title":"Characterization of ambient groundwater quality within a statewide, fixed-station monitoring network in Pennsylvania, 2015–19","docAbstract":"<p>Pennsylvania leads the Nation in the number of individuals that use groundwater for private domestic water supply; more than 3 million rural and suburban Pennsylvania residents rely on private domestic supplies for drinking water. These supplies are not regulated nor routinely monitored; thus relevant groundwater-quality information is not widely available. The U.S. Geological Survey (USGS), in cooperation with the Pennsylvania Department of Environmental Protection (PaDEP) Safe Drinking Water Bureau, established a statewide, fixed-station ambient groundwater quality network in 2015. The goals for the Pennsylvania Groundwater Monitoring Network (GWMN) include characterizing ambient groundwater quality conditions in rural areas of the State and documenting potential changes in conditions over time. Seventeen wells were selected for monitoring at 6-month intervals beginning in 2015. Since then, several wells have been added to the GWMN, bringing the total number of wells sampled in the fall of 2019 to 28. Routinely monitored constituents included physical characteristics and chemical concentrations in filtered and unfiltered samples (major and trace elements, nutrients, and organic compounds). Samples for volatile organic compounds (VOCs), radionuclides, and dissolved hydrocarbon gases were collected during the first sampling event at each well.</p><p>To offer insights on the quality of groundwater used for domestic supply in Pennsylvania, summary statistics for the 221 GWMN samples collected during 2015–19 are compared to U.S. Environmental Protection Agency (EPA) drinking-water standards, which are applicable to public water supplies. Results show that samples across the GWMN generally meet drinking-water standards for inorganic and organic constituents; however, a percentage of samples had concentrations that exceeded maximum contaminant level (MCL) thresholds for nitrate (3 percent) and secondary maximum contaminant level (SMCL) thresholds for iron (32 percent), manganese (36 percent), and aluminum (5 percent). Radon-222 activities, which were sampled only during the initial visit to a well, exceeded the lower proposed drinking water standard of 300 picocuries per liter (pCi/L) in 64 percent of wells in the GWMN; additionally, 7 percent of wells exceeded the higher proposed standard of 4,000 pCi/L. There were no exceedances for VOCs, but one well had a tribromomethane detection. Three wells had detectable concentrations of methane, with one sample exceeding the Pennsylvania action level of 7 milligrams per liter (mg/L).</p><p>The pH and dissolved oxygen concentrations varied widely across the GWMN and were correlated with dissolved metal concentrations and other chemical characteristics of groundwater samples. Considering all samples collected for the study, the pH ranged from 4.2 to 8.3; 42 percent of pH values were either above or below the SMCL range of 6.5–8.5. The highest pH values resulted from contamination of loose grout used in the construction of one well and decreased to levels consistent with other wells in the vicinity after repeated sampling rounds. Dissolved oxygen (DO), which ranged from 0 to 13.9 mg/L, influences the mobility and prevalence of constituents with variable oxidation state, including iron, manganese, and nitrogen species. Samples with acidic pH (less than 6.5) and (or) low DO had the highest concentrations of manganese and iron, whereas those with neutral to alkaline pH values had the highest concentrations of calcium, magnesium, sodium, and other major ions. Analysis of major ions indicates that calcium/bicarbonate water types are the most common, with a few characterized as calcium/chloride or sodium/chloride, and most others as mixed water types including calcium-magnesium/bicarbonate, sodium-magnesium/bicarbonate, and sodium/bicarbonate-chloride.</p><p>Nonparametric statistical methods were used to evaluate the data for spatial and temporal trends. A principal components analysis (PCA) model developed with ranked data values for the entire network resulted in three components, (1) dissolved solids, (2) redox, and (3) sodium-chloride, which explained 74.5 percent of variance in the dataset. On the basis of individual contributions to the PCA, certain wells were identified through hierarchical cluster analysis that shared relevant water-quality characteristics. The spatial distribution of sampling locations and the temporal trends of constituent concentrations indicate that hydrogeologic setting and topographic position as defined in the PCA model are important factors affecting the spatial and temporal patterns of groundwater quality in the GWMN.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215119","collaboration":"Prepared in cooperation with Pennsylvania Department of Environmental Protection","usgsCitation":"Conlon, M.D., and Duris, J.W., 2022, Characterization of ambient groundwater quality within a statewide, fixed-station monitoring network in Pennsylvania, 2015–19: U.S. Geological Survey Scientific Investigations Report 2021–5119, 118 p., https://doi.org/10.3133/sir20215119.","productDescription":"Report: x, 118 p.; Data Release","numberOfPages":"118","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-120798","costCenters":[{"id":532,"text":"Pennsylvania 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 \"}}]}","contact":"<p><a href=\"mailto:dc_pa@usgs.gov\" data-mce-href=\"mailto:dc_pa@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/pa-water\" data-mce-href=\"https://www.usgs.gov/centers/pa-water\">Pennsylvania Water Science Center</a><br>U.S. Geological Survey<br>215 Limekiln Road<br>New Cumberland, PA 17070</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Status of Groundwater Quality Constituents</li><li>Statistical Analysis of Groundwater Quality Data</li><li>Considerations for Future Work</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Supplemental information for wells from the Pennsylvania Groundwater Monitoring Network</li><li>Appendix 2. Analytical methods used by the Pennsylvania Department of Environmental Protection Bureau of Laboratories</li><li>Appendix 3. Distributions of continuous variables for wells from the Pennsylvania Groundwater Monitoring Network</li><li>Appendix 4. Correlation matrix of selected constituents and PDSI values for wells from the Pennsylvania GWMN wells</li><li>Appendix 5. Seasonal differences in water-quality constituents measured in selected Pennsylvania GWMN wells</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2022-01-18","noUsgsAuthors":false,"publicationDate":"2022-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Conlon, Matthew D. 0000-0001-8266-9610 mconlon@usgs.gov","orcid":"https://orcid.org/0000-0001-8266-9610","contributorId":201291,"corporation":false,"usgs":true,"family":"Conlon","given":"Matthew","email":"mconlon@usgs.gov","middleInitial":"D.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duris, Joseph W. 0000-0002-8669-8109 jwduris@usgs.gov","orcid":"https://orcid.org/0000-0002-8669-8109","contributorId":172426,"corporation":false,"usgs":true,"family":"Duris","given":"Joseph","email":"jwduris@usgs.gov","middleInitial":"W.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":830613,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70228253,"text":"70228253 - 2022 - A pilot study to assess the influence of infiltrated stormwater on groundwater: Hydrology and trace organic contaminants","interactions":[],"lastModifiedDate":"2022-02-08T15:05:51.21267","indexId":"70228253","displayToPublicDate":"2022-01-18T08:58:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3711,"text":"Water Environment Research","active":true,"publicationSubtype":{"id":10}},"title":"A pilot study to assess the influence of infiltrated stormwater on groundwater: Hydrology and trace organic contaminants","docAbstract":"<p><span>Underground infiltration basins (UIBs) mimic the natural hydrologic cycle by allowing stormwater to recharge local groundwater aquifers. However, little is known about the potential transport of organic contaminants to receiving groundwater. We conducted a pilot study in which we collected paired grab samples of stormwater runoff flowing into two UIBs (inflow) and shallow groundwater adjacent to the UIBs. Samples were collected coincident with three rain events and analyzed for volatile organic compounds, semi-volatile organic compounds, pharmaceuticals, and pesticides. Few contaminants were detected in groundwater, compared with inflow, and groundwater concentrations were typically an order of magnitude less. With one exception (trichloroethene), all groundwater concentrations were at least two orders of magnitude below available guidance or screening values. This short communication highlights information gaps in understanding the hydrologic connectivity between UIBs and receiving groundwater and potential consequent contaminant transport to the subsurface from varying climatic conditions.</span></p>","language":"English","publisher":"Water Environment Federation","doi":"10.1002/wer.10690","usgsCitation":"Elliott, S.M., Kiesling, R.L., Berg, A.M., and Schoenfuss, H.L., 2022, A pilot study to assess the influence of infiltrated stormwater on groundwater: Hydrology and trace organic contaminants: Water Environment Research, v. 94, no. 2, e10690, 9 p., https://doi.org/10.1002/wer.10690.","productDescription":"e10690, 9 p.","ipdsId":"IP-131245","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":449122,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/wer.10690","text":"External Repository"},{"id":395614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","city":"Minneapolis-St. Paul","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.59115600585936,\n              44.80814739879984\n            ],\n            [\n              -93.13522338867188,\n              44.80814739879984\n            ],\n            [\n              -93.13522338867188,\n              45.30773430004869\n            ],\n            [\n              -93.59115600585936,\n              45.30773430004869\n            ],\n            [\n              -93.59115600585936,\n              44.80814739879984\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"94","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833540,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berg, Andrew M. 0000-0001-9312-240X aberg@usgs.gov","orcid":"https://orcid.org/0000-0001-9312-240X","contributorId":5642,"corporation":false,"usgs":true,"family":"Berg","given":"Andrew","email":"aberg@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schoenfuss, Heiko L.","contributorId":76409,"corporation":false,"usgs":false,"family":"Schoenfuss","given":"Heiko","email":"","middleInitial":"L.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":833745,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70231252,"text":"70231252 - 2022 - Seismic background noise levels across the continental United States from USArray Transportable Array: The influence of geology and geography","interactions":[],"lastModifiedDate":"2022-07-07T16:53:37.67699","indexId":"70231252","displayToPublicDate":"2022-01-18T08:32:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Seismic background noise levels across the continental United States from USArray Transportable Array: The influence of geology and geography","docAbstract":"Since 2004, the most complete estimate of background noise levels across the continental U.S. was attained using 61 broadband seismic stations to calculate power spectral density (PSD) probability density functions. To improve seismic noise estimates across the U.S., we examine vertical component seismic data from the EarthScope USArray Transportable Array seismic network that rolled across the U.S. and southeastern Canada between 2004 and 2015 and form a large (10 TB) PSD database from 1679 stations that contains no smoothing or binning of the spectral estimates. Including station outages, our database has a mean of 98.9% data completeness, and we present maps showing the spatial and temporal variability of seismic noise in six bands of interest between 0.2- and 75-s period. At 0.2 s period, seismic noise across the eastern U.S. is predominantly anthropogenically generated and may be subsequently amplified more than 20 decibels in the sandy and water-saturated sediments of the southeastern U.S. Coastal Plain and Mississippi Embayment. In these sediments, 1 s noise shows similar amplification and is generated through a variety of mechanisms including cultural activity throughout Kentucky and the southeastern Appalachian Mountains, lake waves around the Great Lakes, and ocean waves throughout New England, the Pacific Northwest, and Florida. Both 0.2 and 1 s noise levels are the lowest in the Intermountain West portion of the U.S. We attribute this to a combination of installations on crystalline rocks and reduced population density. Finally, we find that sensors emplaced in sandy, water-saturated sediments observe median, diurnal variations in vertical component power at 18 to 75 s period, which we infer arise through local deformation driven by pressure variations. Ultimately, our results underscore that for shallow (<5 m depth) sensor installation, bedrock provides superior broadband noise performance compared to unconsolidated sediments.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120210176","usgsCitation":"Anthony, R.E., Ringler, A.T., and Wilson, D.C., 2022, Seismic background noise levels across the continental United States from USArray Transportable Array: The influence of geology and geography: Bulletin of the Seismological Society of America, v. 112, no. 2, p. 646-668, https://doi.org/10.1785/0120210176.","productDescription":"23 p.","startPage":"646","endPage":"668","ipdsId":"IP-131111","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":400126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": 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-124.5661,\n                48.37971\n              ],\n              [\n                -123.12,\n                48.04\n              ],\n              [\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"112","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":842130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":3946,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":842131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":842132,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70227515,"text":"70227515 - 2022 - The Coastal Imaging Research Network (CIRN)","interactions":[],"lastModifiedDate":"2022-01-20T13:26:52.29354","indexId":"70227515","displayToPublicDate":"2022-01-18T07:25:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"The Coastal Imaging Research Network (CIRN)","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">The Coastal Imaging Research Network (CIRN) is an international group of researchers who exploit signatures of phenomena in imagery of coastal, estuarine, and riverine environments. CIRN participants develop and implement new coastal imaging methodologies. The research objective of the group is to use imagery to gain a better fundamental understanding of the processes shaping those environments. Coastal imaging data may also be used to derive inputs for model boundary and initial conditions through assimilation, to validate models, and to make management decisions. CIRN was officially formed in 2016 to provide an integrative, multi-institutional group to collaborate on remotely sensed data techniques. As of 2021, the network is a collaboration between researchers from approximately 16 countries and includes investigators from universities, government laboratories and agencies, non-profits, and private companies. CIRN has a strong emphasis on education, exemplified by hosting annual “boot camps” to teach photogrammetry fundamentals and toolboxes from the CIRN code repository, as well as hosting an annual meeting for its members to present coastal imaging research. In this review article, we provide context for the development of CIRN as well as describe the goals and accomplishments of the CIRN community. We highlight components of CIRN’s resources for researchers worldwide including an open-source GitHub repository and coding boot camps. Finally, we provide CIRN’s perspective on the future of coastal imaging.<span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span></span></span></div>","language":"English","publisher":"MDPI","doi":"10.3390/rs14030453","usgsCitation":"Palmsten, M.L., and Brodie, K., 2022, The Coastal Imaging Research Network (CIRN): Remote Sensing, v. 3, no. 14, 453, 18 p., https://doi.org/10.3390/rs14030453.","productDescription":"453, 18 p.","ipdsId":"IP-133886","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":449125,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14030453","text":"Publisher Index Page"},{"id":394572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"14","noUsgsAuthors":false,"publicationDate":"2022-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Palmsten, Margaret L. 0000-0002-6424-2338","orcid":"https://orcid.org/0000-0002-6424-2338","contributorId":239955,"corporation":false,"usgs":true,"family":"Palmsten","given":"Margaret","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":831222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brodie, Katherine L.","contributorId":271224,"corporation":false,"usgs":false,"family":"Brodie","given":"Katherine L.","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":831223,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70236994,"text":"70236994 - 2022 - The occurrence and hazards of great subduction zone earthquakes","interactions":[],"lastModifiedDate":"2022-09-27T12:06:13.316143","indexId":"70236994","displayToPublicDate":"2022-01-18T07:03:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7460,"text":"Nature Reviews Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"The occurrence and hazards of great subduction zone earthquakes","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Subduction zone earthquakes result in some of the most devastating natural hazards on Earth. Knowledge of where great (moment magnitude<span>&nbsp;</span><strong>M</strong> ≥ 8) subduction zone earthquakes can occur and how they rupture is critical to constraining future seismic and tsunami hazards. Since the occurrence of well-instrumented great earthquakes, such as the 2004<span>&nbsp;</span><strong>M</strong>9.1 Sumatra–Andaman and 2011<span>&nbsp;</span><strong>M</strong>9.1 Tohoku earthquakes, the hypotheses that plate age and convergence rate influence the ability of subduction zones to host large earthquakes have been dispelled. In this Review, we highlight how certain subduction zone properties might influence the location and characteristics of great earthquake rupture and impact seismic and tsunami hazard. The rupture characteristics of great earthquakes that most heavily impact earthquake hazards include the rupture extent (seaward and landward), location of strong motion-generating areas and earthquake recurrence. By contrast, large slip or displacement at the seafloor is one of the major controls of tsunami hazard. Future improvements in addressing hazards posed by subduction zones depend heavily on sustained geophysical monitoring in subduction zone systems (both onshore and offshore), expanded development of palaeoseismic data sets and improved integration of observations and models across disciplines and timescales.</p></div></div><div id=\"Abs3-section\" class=\"c-article-section\"><br></div>","language":"English","publisher":"Springer Nature","doi":"10.1038/s43017-021-00245-w","usgsCitation":"Wirth, E.A., Sahakian, V., Wallace, L.M., and Melnick, D., 2022, The occurrence and hazards of great subduction zone earthquakes: Nature Reviews Earth & Environment, v. 3, p. 125-140, https://doi.org/10.1038/s43017-021-00245-w.","productDescription":"16 p.","startPage":"125","endPage":"140","ipdsId":"IP-128504","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":407391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2022-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Wirth, Erin A. 0000-0002-8592-4442","orcid":"https://orcid.org/0000-0002-8592-4442","contributorId":207853,"corporation":false,"usgs":true,"family":"Wirth","given":"Erin","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":852964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sahakian, Valerie J.","contributorId":208097,"corporation":false,"usgs":false,"family":"Sahakian","given":"Valerie J.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":852965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wallace, Laura M","contributorId":296955,"corporation":false,"usgs":false,"family":"Wallace","given":"Laura","email":"","middleInitial":"M","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":852966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Melnick, Daniel","contributorId":195525,"corporation":false,"usgs":false,"family":"Melnick","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":852967,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227482,"text":"70227482 - 2022 - Decision analysis and CO2–Enhanced oil recovery development strategies","interactions":[],"lastModifiedDate":"2022-03-15T16:54:56.067797","indexId":"70227482","displayToPublicDate":"2022-01-18T06:41:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2832,"text":"Natural Resources Research","onlineIssn":"1573-8981","printIssn":"1520-7439","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Decision analysis and CO<sub>2</sub>–Enhanced oil recovery development strategies","title":"Decision analysis and CO2–Enhanced oil recovery development strategies","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>This paper analyzes the relationship between actual reservoir conditions and predicted measures of performance of carbon dioxide enhanced oil recovery (CO<sub>2</sub>–EOR) programs. It then shows how CO<sub>2</sub>–EOR operators might maximize the value of their projects by approaching implementation using a “flexible selective” pattern development strategy, where the CO<sub>2</sub>–EOR program patterns are selectively developed based on site-specific reservoir properties. It also analyzes performance measures and economic consequences of utilizing a continuous CO<sub>2</sub><span>&nbsp;</span>injection strategy intended to maximize CO<sub>2</sub><span>&nbsp;</span>retention for a defined time period. “Net CO<sub>2</sub><span>&nbsp;</span>utilization,” calculated as difference between the volumes of CO<sub>2</sub><span>&nbsp;</span>injected and CO<sub>2</sub><span>&nbsp;</span>recovered in the production stream divided by the oil produced, is a standard measure of CO<sub>2</sub>–EOR carbon utilization, but it can be a misleading predictor of the actual CO<sub>2</sub><span>&nbsp;</span>retained in the reservoir. Asset value can be added to a CO<sub>2</sub>–EOR project by recognizing effects of variations in reservoir parameter values and basing incremental development decisions on those data. For policy analysts, the consequences of ignoring geologic variability within a reservoir that is a candidate for CO<sub>2</sub>–EOR will likely be to substantially overestimate predicted adoption of CO<sub>2</sub>–EOR in response to economic incentives. This result holds true whether the CO<sub>2</sub>–EOR program objective is to maximize net value by maximizing oil production or maximize CO<sub>2</sub><span>&nbsp;</span>storage with oil recovery.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s11053-021-09983-6","usgsCitation":"Attanasi, E., and Freeman, P., 2022, Decision analysis and CO2–Enhanced oil recovery development strategies: Natural Resources Research, v. 31, p. 735-749, https://doi.org/10.1007/s11053-021-09983-6.","productDescription":"15 p.","startPage":"735","endPage":"749","ipdsId":"IP-128672","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":394500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","noUsgsAuthors":false,"publicationDate":"2022-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Attanasi, Emil 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":1809,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":831143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Philip A. 0000-0002-0863-7431","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":206294,"corporation":false,"usgs":true,"family":"Freeman","given":"Philip A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":831144,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70254795,"text":"70254795 - 2022 - Estimating allowable take for an increasing bald eagle population in the United States","interactions":[],"lastModifiedDate":"2024-06-12T00:26:13.112644","indexId":"70254795","displayToPublicDate":"2022-01-17T19:20:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimating allowable take for an increasing bald eagle population in the United States","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Effectively managing take of wildlife resulting from human activities poses a major challenge for applied conservation. Demographic data essential to decisions regarding take are often expensive to collect and are either not available or based on limited studies for many species. Therefore, modeling approaches that efficiently integrate available information are important to improving the scientific basis for sustainable take thresholds. We used the prescribed take level (PTL) framework to estimate allowable take for bald eagles (<i>Haliaeetus leucocephalus</i>) in the conterminous United States. We developed an integrated population model (IPM) that incorporates multiple sources of information and then use the model output as the scientific basis for components of the PTL framework. Our IPM is structured to identify key parameters needed for the PTL and to quantify uncertainties in those parameters at the scale at which the United States Fish and Wildlife Service manages take. Our IPM indicated that mean survival of birds &gt;1 year old was high and precise (0.91, 95% CI = 0.90–0.92), whereas mean survival of first-year eagles was lower and more variable (0.69, 95% CI = 0.62–0.78). We assumed that density dependence influenced recruitment by affecting the probability of breeding, which was highly imprecise and estimated to have declined from approximately 0.988 (95% CI = 0.985–0.993) to 0.66 (95% CI = 0.34–0.99) between 1994 and 2018. We sampled values from the posterior distributions of the IPM for use in the PTL and estimated that allowable take (e.g., permitted take for energy development, incidental collisions with human made structures, or removal of nests for development) ranged from approximately 12,000 to 20,000 individual eagles depending on risk tolerance and form of density dependence at the scale of the conterminous United States excluding the Southwest. Model-based thresholds for allowable take can be inaccurate if the assumptions of the underlying framework are not met, if the influence of permitted take is under-estimated, or if undetected population declines occur from other sources. Continued monitoring and use of the IPM and PTL frameworks to identify key uncertainties in bald eagle population dynamics and management of allowable take can mitigate this potential bias, especially where improved information could reduce the risk of permitting non-sustainable take.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.22158","usgsCitation":"Zimmerman, G.S., Millsap, B., Abadi, F., Gedir, J.V., Kendall, W.L., and Sauer, J.R., 2022, Estimating allowable take for an increasing bald eagle population in the United States: Journal of Wildlife Management, v. 86, no. 2, e22158, 26 p., https://doi.org/10.1002/jwmg.22158.","productDescription":"e22158, 26 p.","ipdsId":"IP-126921","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449130,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22158","text":"Publisher Index Page"},{"id":429933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -129.4303959184181,\n              51.87936304101626\n            ],\n            [\n              -129.4303959184181,\n              24.11089370259188\n            ],\n            [\n              -65.44602091841801,\n              24.11089370259188\n            ],\n            [\n              -65.44602091841801,\n              51.87936304101626\n            ],\n            [\n              -129.4303959184181,\n              51.87936304101626\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"86","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Zimmerman, Guthrie S.","contributorId":261410,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie","email":"","middleInitial":"S.","affiliations":[{"id":7199,"text":"US FWS","active":true,"usgs":false}],"preferred":false,"id":902595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Millsap, Brian","contributorId":182410,"corporation":false,"usgs":false,"family":"Millsap","given":"Brian","affiliations":[],"preferred":false,"id":902596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Abadi, Fitsum","contributorId":244779,"corporation":false,"usgs":false,"family":"Abadi","given":"Fitsum","affiliations":[{"id":48968,"text":"New Mexico State University, Department of Fish, Wildlife and Conservation Ecology","active":true,"usgs":false}],"preferred":false,"id":902597,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gedir, Jay V.","contributorId":337911,"corporation":false,"usgs":false,"family":"Gedir","given":"Jay","email":"","middleInitial":"V.","affiliations":[{"id":24672,"text":"New Mexico Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":902598,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902594,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":902599,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70256755,"text":"70256755 - 2022 - Large-scale fire management restores grassland bird richness for a private lands ecoregion","interactions":[],"lastModifiedDate":"2024-09-04T16:21:04.778526","indexId":"70256755","displayToPublicDate":"2022-01-17T11:02:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9977,"text":"Ecological Solutions and Evidence","active":true,"publicationSubtype":{"id":10}},"title":"Large-scale fire management restores grassland bird richness for a private lands ecoregion","docAbstract":"<ol class=\"\"><li><p>Of all terrestrial biomes, grasslands are losing the most biodiversity the most rapidly, so there is a critical need to document and learn from large-scale restoration successes.</p></li><li><p>In the Loess Canyons ecoregion of the Great Plains, USA, an association of private ranchers and natural resource agencies has led a multi-decadal, ecoregion-scale initiative to combat the loss of grasslands to woody plant encroachment by restoring large-scale fire regimes. Here, we use 14 years of fire treatment history with 6 years of grassland bird monitoring and remotely sensed tree cover data across 136,767 ha of privately owned grassland to quantify outcomes of large-scale grassland restoration efforts.</p></li><li><p>Grassland bird richness increased across 65% (90,032&nbsp;ha) of the Loess Canyons, and woody plant cover decreased up to 55% across 25% (7408&nbsp;ha) of all fire-treated areas.</p></li><li><p>This was accomplished with extreme fire treatments that killed mature trees, were large (mean annual area burned was 3100&nbsp;ha), spatially clustered and straddled boundaries between invasive woodlands and remaining grasslands – not heavily infested woodlands.</p></li><li><p>Findings from this study provide the first evidence of human management reversing the impacts of woody encroachment on grassland birds at an ecoregion scale.</p></li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1002/2688-8319.12119","usgsCitation":"Roberts, C.P., Scholtz, R., Fogarty, D., Twidwell, D., and Walker, T., 2022, Large-scale fire management restores grassland bird richness for a private lands ecoregion: Ecological Solutions and Evidence, v. 3, no. 1, e12119, 7 p., https://doi.org/10.1002/2688-8319.12119.","productDescription":"e12119, 7 p.","ipdsId":"IP-128296","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":449132,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2688-8319.12119","text":"Publisher Index Page"},{"id":433457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Loess Canyons ecoregion","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -100.66,\n              41\n            ],\n            [\n              -100.66,\n              40.64\n            ],\n            [\n              -100.06445,\n              40.64\n            ],\n            [\n              -100.06445,\n              41\n            ],\n            [\n              -100.66,\n              41\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"3","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts, Caleb Powell 0000-0002-8716-0423","orcid":"https://orcid.org/0000-0002-8716-0423","contributorId":288567,"corporation":false,"usgs":true,"family":"Roberts","given":"Caleb","email":"","middleInitial":"Powell","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scholtz, R.","contributorId":341768,"corporation":false,"usgs":false,"family":"Scholtz","given":"R.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":908876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fogarty, D.T.","contributorId":341767,"corporation":false,"usgs":false,"family":"Fogarty","given":"D.T.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":908875,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Twidwell, D.","contributorId":244285,"corporation":false,"usgs":false,"family":"Twidwell","given":"D.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":908874,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walker, T.L. Jr.","contributorId":341771,"corporation":false,"usgs":false,"family":"Walker","given":"T.L.","suffix":"Jr.","email":"","affiliations":[{"id":81786,"text":"Nebraska Game & Parks Commission","active":true,"usgs":false}],"preferred":false,"id":908877,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70227442,"text":"70227442 - 2022 - BIOTAS: BIOTelemetry Analysis Software, for the semi-automated removal of false positives from radio telemetry data","interactions":[],"lastModifiedDate":"2022-01-17T17:07:37.612612","indexId":"70227442","displayToPublicDate":"2022-01-17T11:01:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"BIOTAS: BIOTelemetry Analysis Software, for the semi-automated removal of false positives from radio telemetry data","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Introduction</h3><p>Radio telemetry, one of the most widely used techniques for tracking wildlife and fisheries populations, has a false-positive problem. Bias from false-positive detections can affect many important derived metrics, such as home range estimation, site occupation, survival, and migration timing. False-positive removal processes have relied upon simple filters and personal opinion. To overcome these shortcomings, we have developed BIOTAS (BIOTelemetry Analysis Software) to assist with false-positive identification, removal, and data management for large-scale radio telemetry projects.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>BIOTAS uses a naïve Bayes classifier to identify and remove false-positive detections from radio telemetry data. The semi-supervised classifier uses spurious detections from unknown tags and study tags as training data. We tested BIOTAS on four scenarios: wide-band receiver with a single Yagi antenna, wide-band receiver that switched between two Yagi antennas, wide-band receiver with a single dipole antenna, and single-band receiver that switched between five frequencies. BIOTAS has a built in a<span>&nbsp;</span><i>k</i>-fold cross-validation and assesses model quality with sensitivity, specificity, positive and negative predictive value, false-positive rate, and precision-recall area under the curve. BIOTAS also assesses concordance with a traditional consecutive detection filter using Cohen’s<span>&nbsp;</span><span class=\"mathjax-tex\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi>&amp;#x03BA;</mi></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"mi\">κ</span></span></span></span><span class=\"MJX_Assistive_MathML\">κ</span></span></span>.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>Overall BIOTAS performed equally well in all scenarios and was able to discriminate between known false-positive detections and valid study tag detections with low false-positive rates (&lt; 0.001) as determined through cross-validation, even as receivers switched between antennas and frequencies. BIOTAS classified between 94 and 99% of study tag detections as valid.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusion</h3><p>As part of a robust data management plan, BIOTAS is able to discriminate between detections from study tags and known false positives. BIOTAS works with multiple manufacturers and accounts for receivers that switch between antennas and frequencies. BIOTAS provides the framework for transparent, objective, and repeatable telemetry projects for wildlife conservation surveys, and increases the efficiency of data processing.</p>","language":"English","publisher":"BioMed Central Ltd.","doi":"10.1186/s40317-022-00273-3","usgsCitation":"Nebiolo, K., and Castro-Santos, T.R., 2022, BIOTAS: BIOTelemetry Analysis Software, for the semi-automated removal of false positives from radio telemetry data: Animal Biotelemetry, v. 10, p. 1-16, https://doi.org/10.1186/s40317-022-00273-3.","productDescription":"2, 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-122256","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":449135,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-022-00273-3","text":"Publisher Index Page"},{"id":394441,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Nebiolo, Kevin","contributorId":271123,"corporation":false,"usgs":false,"family":"Nebiolo","given":"Kevin","email":"","affiliations":[{"id":56294,"text":"Kleinschmidt Associates, Essex, CT","active":true,"usgs":false}],"preferred":false,"id":830917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":830918,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227444,"text":"70227444 - 2022 - Primary deposition and early diagenetic effects on the high saturation accumulation of gas hydrate in a silt dominated reservoir in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2022-01-17T16:59:17.812984","indexId":"70227444","displayToPublicDate":"2022-01-17T10:46:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Primary deposition and early diagenetic effects on the high saturation accumulation of gas hydrate in a silt dominated reservoir in the Gulf of Mexico","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0100\">On continental margins, high saturation gas hydrate systems (&gt;60% pore volume) are common in canyon and channel environments within the gas hydrate stability zone, where reservoirs are dominated by coarse-grained, high porosity sand deposits. Recent studies, including the results presented here, suggest that rapidly deposited, silt-dominated channel-levee environments can also host high saturation gas hydrate accumulations. Here we present several sedimentological data sets, including sediment composition, biostratigraphic age from calcareous nannofossils, grain size, total organic carbon (TOC), C/N elemental ratio, δ<sup>13</sup>C-TOC<sub>,</sub><span>&nbsp;</span>CaCO<sub>3</sub>, total sulfur (TS), and δ<sup>34</sup>S-TS from sediments collected with pressure cores from a gas hydrate rich, turbidite channel-levee system in the Gulf of Mexico during the 2017 UT-GOM2-1 Hydrate Pressure Coring Expedition. Our results indicate the reservoir is composed of three main lithofacies, which have distinct sediment grain size distributions (type A-silty clay to clayey silt, type B-clayey silt, and type C-sandy silt to silty sand) that are characteristic of variable turbidity current energy regimes within a Pleistocene (&lt; 0.91&nbsp;Ma) channel-levee environment. We document that the TOC in the sediments of the reservoir is terrestrial in origin and contained within the fine fraction of each lithofacies, while the CaCO<sub>3</sub><span>&nbsp;</span>fraction is composed of primarily reworked grains, including Cretaceous calcareous nannofossils, and part of the detrital load. The lack of biogenic grains within the finest grained sediment intervals throughout the reservoir suggests interevent hemipelagic sediments are not preserved, resulting in a reservoir sequence of silt dominated, stacked turbidites. We observe two zones of enhanced TS at the top and bottom of the reservoir that correspond with enriched bulk sediment δ<sup>34</sup>S, indicating stalled or slowly advancing paleo-sulfate-methane transition zone (SMTZ) positions likely driven by relative decreases in sedimentation rate. Despite these two diagenetic zones, the low abundance of diagenetic precipitates throughout the reservoir allowed the primary porosity to remain largely intact, thus better preserving primary porosity for subsequent pore-filling gas hydrate. In canyon, channel, and levee environments, early diagenesis may be regulated via sedimentation rates, where high rates result in rapid progression through the SMTZ and minimal diagenetic mineralization and low rates result in the stalling of the SMTZ, enhancing diagenetic mineralization. Here, we observed some enhanced pyritization to implicate potential sedimentation rate changes, but not enough to consume primary porosity, resulting in a high saturation gas hydrate reservoir. These results emphasize the important implications of sedimentary processes, sedimentation rates, and early diagenesis on the distribution of gas hydrate in marine sediments along continental margins.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2021.106718","usgsCitation":"Johnson, J., MacLeod, D.R., Phillips, S.C., Phillips Purkey, M., and Divins, D.L., 2022, Primary deposition and early diagenetic effects on the high saturation accumulation of gas hydrate in a silt dominated reservoir in the Gulf of Mexico: Marine Geology, v. 444, p. 1-22, https://doi.org/10.1016/j.margeo.2021.106718.","productDescription":"106718, 22 p.","startPage":"1","endPage":"22","ipdsId":"IP-135252","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":449137,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.margeo.2021.106718","text":"Publisher Index Page"},{"id":394440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Louisiana, Mississippi","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94.053955078125,\n              25.34402602913433\n            ],\n            [\n              -87.923583984375,\n              25.34402602913433\n            ],\n            [\n              -87.923583984375,\n              30.845647420182598\n            ],\n            [\n              -94.053955078125,\n              30.845647420182598\n            ],\n            [\n              -94.053955078125,\n              25.34402602913433\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"444","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Joel E.","contributorId":29259,"corporation":false,"usgs":true,"family":"Johnson","given":"Joel E.","affiliations":[],"preferred":false,"id":830922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacLeod, Douglas R.","contributorId":271125,"corporation":false,"usgs":false,"family":"MacLeod","given":"Douglas","email":"","middleInitial":"R.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":830923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, Stephen C. 0000-0003-0858-4701","orcid":"https://orcid.org/0000-0003-0858-4701","contributorId":268177,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":830924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phillips Purkey, Marcie","contributorId":271126,"corporation":false,"usgs":false,"family":"Phillips Purkey","given":"Marcie","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":830925,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Divins, David L.","contributorId":271127,"corporation":false,"usgs":false,"family":"Divins","given":"David","email":"","middleInitial":"L.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":830926,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70227445,"text":"70227445 - 2022 - Northern Cascadia Margin gas hydrates — Regional geophysical surveying, IODP drilling leg 311, and cabled observatory monitoring","interactions":[],"lastModifiedDate":"2022-01-17T16:45:44.547375","indexId":"70227445","displayToPublicDate":"2022-01-17T10:31:53","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Northern Cascadia Margin gas hydrates — Regional geophysical surveying, IODP drilling leg 311, and cabled observatory monitoring","docAbstract":"<p id=\"Par1\" class=\"Para\">This article reviews extensive geophysical survey data, ocean drilling results and long-term seafloor monitoring that constrain the distribution and concentration of gas hydrates within the accretionary prism of the northern Cascadia subduction margin, located offshore Vancouver Island in Canada. Seismic surveys and geologic studies conducted since the 1980s have mapped the bottom simulating reflector (BSR), detected gas hydrate occurrence and estimated gas hydrate and free gas concentrations. Additional constraints were obtained from seafloor-towed, controlled-source electromagnetic surveying. A component of these studies has been the examination of low-temperature seafloor vents and seeps that emit gas and fluids into the ocean. These features are identified seismically as chimney-like zones of reduced acoustic reflectivity within the sediment stratigraphy, functioning as conduits for gas and fluid migration from below the BSR to the seafloor. Gas hydrates have been recovered from the seafloor and from sediment cores at vent sites, mostly in massive (nodular) form and as a vein-like fracture filling. The Ocean Networks Canada cabled NEPTUNE observatory has gathered extensive continuous, long-term observations on gas hydrate dynamics at the seafloor and in boreholes at two nodes on the continental slope featuring high gas hydrate concentrations. Measurements taken at the observatory include a time-series of gas bubble emission rates, changes in the near-seafloor electromagnetic structure and seafloor compliance linked to gas hydrate formation and dissociation. Two Integrated Ocean Drilling Program (IODP) expeditions collected cores, measured downhole properties and deployed downhole instruments within the central accretionary prism. At IODP Site U1364, pore pressures are being monitored above and below the base of the gas hydrate stability zone at a slope setting using an “Advanced Circulation Obviation Retrofit Kit” (A-CORK). Downhole pore pressures, temperatures and electrical resistivities also are being monitored at IODP Site U1416 using the “Simple Cabled Instrument for Measuring Parameters In Situ” (SCIMPI) tool at a vent site from near-seafloor to just above the base of the gas hydrate stability zone.</p><div id=\"cobranding-and-download-availability-text\" class=\"note test-pdf-link\"><br></div>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"World atlas of submarine gas hydrates in continental margins","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-81186-0_8","usgsCitation":"Riedel, M., Collett, T.S., Scherwath, M., Pohlman, J.W., Hyndman, R., and Spence, G., 2022, Northern Cascadia Margin gas hydrates — Regional geophysical surveying, IODP drilling leg 311, and cabled observatory monitoring, chap. <i>of</i> World atlas of submarine gas hydrates in continental margins, p. 109-120, https://doi.org/10.1007/978-3-030-81186-0_8.","productDescription":"12 p.","startPage":"109","endPage":"120","ipdsId":"IP-119383","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":394439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"British Columbia","otherGeospatial":"Vancouver Island, Pacific Ocean","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.09057617187499,\n              48.31973404047173\n            ],\n            [\n              -123.56323242187499,\n              48.23199134320962\n            ],\n            [\n              -123.20068359374999,\n              48.29781249243716\n            ],\n            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-127.06787109374999,\n              50.79899141148548\n            ],\n            [\n              -127.705078125,\n              51.04830113331224\n            ],\n            [\n              -127.9248046875,\n              51.23440735163459\n            ],\n            [\n              -128.07861328125,\n              51.41291212935532\n            ],\n            [\n              -130.9130859375,\n              50.83369767098071\n            ],\n            [\n              -128.968505859375,\n              48.144097934938884\n            ],\n            [\n              -124.76074218749999,\n              48.480204398955145\n            ],\n            [\n              -124.09057617187499,\n              48.31973404047173\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationDate":"2022-01-01","publicationStatus":"PW","contributors":{"editors":[{"text":"Mienert, Jurgen","contributorId":19384,"corporation":false,"usgs":true,"family":"Mienert","given":"Jurgen","email":"","affiliations":[],"preferred":false,"id":831008,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Berndt, Christian","contributorId":271120,"corporation":false,"usgs":false,"family":"Berndt","given":"Christian","email":"","affiliations":[],"preferred":false,"id":831009,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Trehu, Anne M.","contributorId":49884,"corporation":false,"usgs":false,"family":"Trehu","given":"Anne","email":"","middleInitial":"M.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":831010,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Camerlenghi, Angelo","contributorId":7450,"corporation":false,"usgs":true,"family":"Camerlenghi","given":"Angelo","email":"","affiliations":[],"preferred":false,"id":831011,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Liu, Char-Shine","contributorId":271121,"corporation":false,"usgs":false,"family":"Liu","given":"Char-Shine","email":"","affiliations":[],"preferred":false,"id":831012,"contributorType":{"id":2,"text":"Editors"},"rank":5}],"authors":[{"text":"Riedel, Michael","contributorId":271128,"corporation":false,"usgs":false,"family":"Riedel","given":"Michael","affiliations":[{"id":36241,"text":"GEOMAR Helmholtz Centre for Ocean Research Kiel","active":true,"usgs":false}],"preferred":false,"id":830927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":830928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scherwath, Martin","contributorId":271129,"corporation":false,"usgs":false,"family":"Scherwath","given":"Martin","email":"","affiliations":[{"id":56295,"text":"Ocean Networks Canada, University of Victoria, V8N1V8, Victoria, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":830929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pohlman, John W. 0000-0002-3563-4586 jpohlman@usgs.gov","orcid":"https://orcid.org/0000-0002-3563-4586","contributorId":145771,"corporation":false,"usgs":true,"family":"Pohlman","given":"John","email":"jpohlman@usgs.gov","middleInitial":"W.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":830930,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hyndman, Roy","contributorId":271130,"corporation":false,"usgs":false,"family":"Hyndman","given":"Roy","affiliations":[{"id":56296,"text":"Geological Survey of Canada - Pacific, Sidney, BC, V7L4B2, Canada","active":true,"usgs":false}],"preferred":false,"id":830931,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spence, George","contributorId":271131,"corporation":false,"usgs":false,"family":"Spence","given":"George","affiliations":[{"id":56297,"text":"School of Earth and Ocean Sciences, University of Victoria, Victoria, BC, V8P 3E6, Canada","active":true,"usgs":false}],"preferred":false,"id":830932,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70256712,"text":"70256712 - 2022 - Three scleral ossicles in the West African Denticle herring Denticeps clupeoides (Clupeiformes: Denticipitidae)","interactions":[],"lastModifiedDate":"2024-09-03T15:31:40.552779","indexId":"70256712","displayToPublicDate":"2022-01-17T10:27:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Three scleral ossicles in the West African Denticle herring <i>Denticeps clupeoides</i> (Clupeiformes: Denticipitidae)","title":"Three scleral ossicles in the West African Denticle herring Denticeps clupeoides (Clupeiformes: Denticipitidae)","docAbstract":"<p><span>The eyes of teleostean fishes typically exhibit two ossifications, the anterior and posterior sclerotics, both associated with the scleral cartilage. The West African Denticle herring&nbsp;</span><i>Denticeps clupeoides</i><span>&nbsp;has three scleral ossifications, including the typical two associated with the scleral cartilage (anterior and posterior sclerotic) and a third ossification (Di Dario's ossicle), spatially separated from the scleral cartilage and located within the anteromedial wall of the sclera. The medial rectus muscle inserts on the medial surface of Di Dario's ossicle, suggesting that this third sclerotic may play a role in forward rotation of the eye in this surface feeding fish.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/jfb.14996","usgsCitation":"Kubicek, K.M., Britz, R., Pinion, A.K., Bower, L.M., and Conway, K.W., 2022, Three scleral ossicles in the West African Denticle herring Denticeps clupeoides (Clupeiformes: Denticipitidae): Journal of Fish Biology, v. 100, no. 3, p. 852-855, https://doi.org/10.1111/jfb.14996.","productDescription":"4 p.","startPage":"852","endPage":"855","ipdsId":"IP-133161","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433409,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Kubicek, Kole M.","contributorId":341649,"corporation":false,"usgs":false,"family":"Kubicek","given":"Kole","email":"","middleInitial":"M.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":908742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Britz, Ralf","contributorId":341651,"corporation":false,"usgs":false,"family":"Britz","given":"Ralf","email":"","affiliations":[{"id":81769,"text":"Senckenberg Natural History Collections Dresden","active":true,"usgs":false}],"preferred":false,"id":908743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pinion, Amanda K.","contributorId":341652,"corporation":false,"usgs":false,"family":"Pinion","given":"Amanda","email":"","middleInitial":"K.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":908744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bower, Luke Max 0000-0002-0739-858X","orcid":"https://orcid.org/0000-0002-0739-858X","contributorId":341034,"corporation":false,"usgs":true,"family":"Bower","given":"Luke","email":"","middleInitial":"Max","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908741,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Conway, Kevin W.","contributorId":341653,"corporation":false,"usgs":false,"family":"Conway","given":"Kevin","email":"","middleInitial":"W.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":908745,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70227446,"text":"70227446 - 2022 - Alaska North Slope terrestrial gas hydrate systems: Insights from scientific drilling","interactions":[],"lastModifiedDate":"2022-01-17T16:30:58.678965","indexId":"70227446","displayToPublicDate":"2022-01-17T10:17:29","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Alaska North Slope terrestrial gas hydrate systems: Insights from scientific drilling","docAbstract":"<p id=\"Par1\" class=\"Para\">A wealth of information has been accumulated regarding the occurrence of gas hydrates in nature, leading to significant advancements in our understanding of the geologic controls on their occurrence in both the terrestrial and marine settings of the Arctic. Gas hydrate accumulations discovered in the Alaska North Slope have been the focus of several important geoscience and production testing research programs. The Mount Elbert Gas Hydrate Stratigraphic Test Well of 2007 yielded one of the most complete geologic datasets on Arctic gas hydrate systems and important reservoir engineering data. The 2011/2012 field test of the Iġnik Sikumi gas hydrate production test well provided important insight into gas hydrate production technologies, yielding additional information on the petrophysical properties of gas hydrate reservoir systems. The Hydrate-01 Stratigraphic Test Well, drilled late in 2018, confirmed the geologic conditions at an Alaska North Slope drill site that was selected for an extended gas hydrate production test. In 2018, the US Geological Survey used information derived from previous scientific drilling programs to assess the volume of undiscovered, technically recoverable gas resources at a mean estimate of about 54 trillion cubic feet (~1.5 trillion cubic meters) within the gas hydrates in the North Slope of Alaska. This assessment has shown that the amount of gas stored as gas hydrates in this area is equal to about half of the known volume of conventional natural gas resources in the region.</p><div id=\"cobranding-and-download-availability-text\" class=\"note test-pdf-link\"><br></div>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"World atlas of submarine gas hydrates in continental margins","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-81186-0_16","usgsCitation":"Collett, T.S., Boswell, R.M., and Zyrianova, M.V., 2022, Alaska North Slope terrestrial gas hydrate systems: Insights from scientific drilling, chap. <i>of</i> World atlas of submarine gas hydrates in continental margins, p. 195-206, https://doi.org/10.1007/978-3-030-81186-0_16.","productDescription":"12 p.","startPage":"195","endPage":"206","ipdsId":"IP-120020","costCenters":[{"id":164,"text":"Central Energy Resources Science 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Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":830933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boswell, Ray M.","contributorId":72926,"corporation":false,"usgs":true,"family":"Boswell","given":"Ray","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":830934,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zyrianova, Margarita V. 0000-0002-3669-1320 rita@usgs.gov","orcid":"https://orcid.org/0000-0002-3669-1320","contributorId":198970,"corporation":false,"usgs":true,"family":"Zyrianova","given":"Margarita","email":"rita@usgs.gov","middleInitial":"V.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":830935,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70227449,"text":"70227449 - 2022 - A review of the exploration, discovery, and characterization of highly concentrated gas hydrate accumulations in coarse-grained reservoir systems along the Eastern Continental Margin of India","interactions":[],"lastModifiedDate":"2022-01-17T15:24:04.259517","indexId":"70227449","displayToPublicDate":"2022-01-17T09:12:27","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"A review of the exploration, discovery, and characterization of highly concentrated gas hydrate accumulations in coarse-grained reservoir systems along the Eastern Continental Margin of India","docAbstract":"<p id=\"Par1\" class=\"Para\">The analysis of 3-D seismic data has become one of the most powerful ways to identify sand-rich gas hydrate reservoir systems and to directly identify highly concentrated gas hydrate prospects. Scientific drilling programs have shown that the occurrence of highly concentrated gas hydrate accumulations in coarse-grained, sand-rich, reservoir systems has a significant impact on the physical properties of sediments, allowing gas hydrates to be “directly detected” by conventional seismic analysis techniques. One of the most diagnostic responses of a gas hydrate-bearing sand reservoir is that of a high-velocity sedimentary section and an associated high-amplitude seismic response with a reflection polarity matching that of the seafloor. Knowledge of this physical relationship guided the Indian National Gas Hydrate Program Expedition 02 (NGHP-02) in their pre-drill site review and selection effort along the eastern continental margin of India in 2016. Within the planning, operational and post-operational data analysis phases of the NGHP-02 Expedition, scientists relied heavily on the analyses of the (1) pre-expedition acquired 3-D seismic data from offshore India, (2) downhole logging data acquired during NGHP-02 and (3) core samples and data obtained from NGHP-02 conventional- and pressure-cores to identify gas hydrates and assess the geologic controls on the formation and stability of these accumulations. Data analysis has confirmed the presence of extensive sand-rich depositional systems throughout the deepwater portions of the Krishna-Godavari and Mahanadi Basins in the Bay of Bengal. Two areas of the Krishna-Godavari Basin contain substantial gas hydrate accumulations in sand-rich systems, representing candidate sites for future potential energy exploitation.</p><div id=\"cobranding-and-download-availability-text\" class=\"note test-pdf-link\"><br></div>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"World atlas of submarine gas hydrates in continental margins","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-81186-0_11","usgsCitation":"Collett, T.S., Chopra, K., Bhardwaj, A., Boswell, R., Waite, W., Misra, A.K., and Kumar, P., 2022, A review of the exploration, discovery, and characterization of highly concentrated gas hydrate accumulations in coarse-grained reservoir systems along the Eastern Continental Margin of India, chap. <i>of</i> World atlas of submarine gas hydrates in continental margins, p. 139-154, https://doi.org/10.1007/978-3-030-81186-0_11.","productDescription":"16 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Ray","contributorId":271136,"corporation":false,"usgs":false,"family":"Boswell","given":"Ray","affiliations":[{"id":40277,"text":"U.S. Department of Energy","active":true,"usgs":false}],"preferred":false,"id":830944,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waite, William F. 0000-0002-9436-4109 wwaite@usgs.gov","orcid":"https://orcid.org/0000-0002-9436-4109","contributorId":625,"corporation":false,"usgs":true,"family":"Waite","given":"William F.","email":"wwaite@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":830945,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Misra, A. K.","contributorId":271137,"corporation":false,"usgs":false,"family":"Misra","given":"A.","email":"","middleInitial":"K.","affiliations":[{"id":40269,"text":"Oil and Natural Gas Corporation Ltd","active":true,"usgs":false}],"preferred":false,"id":830946,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kumar, Pushpendra","contributorId":271138,"corporation":false,"usgs":false,"family":"Kumar","given":"Pushpendra","affiliations":[{"id":40269,"text":"Oil and Natural Gas Corporation Ltd","active":true,"usgs":false}],"preferred":false,"id":830947,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70259613,"text":"70259613 - 2022 - Volcano-tectonic history of the Hood River graben: A late Pliocene-Holocene intra-arc graben at the crest of the northern Oregon Cascade Range, USA","interactions":[],"lastModifiedDate":"2024-10-18T10:57:25.817346","indexId":"70259613","displayToPublicDate":"2022-01-17T08:47:27","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":128,"text":"Open-File Report","active":false,"publicationSubtype":{"id":2}},"seriesNumber":"22-2","title":"Volcano-tectonic history of the Hood River graben: A late Pliocene-Holocene intra-arc graben at the crest of the northern Oregon Cascade Range, USA","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"Minnesota Geological Survey","usgsCitation":"McClaughry, J.D., Madin, I.P., Bennett, S.E., and Conrey, R.M., 2022, Volcano-tectonic history of the Hood River graben: A late Pliocene-Holocene intra-arc graben at the crest of the northern Oregon Cascade Range, USA: Open-File Report 22-2, 2 p.","productDescription":"2 p.","startPage":"35","endPage":"36","ipdsId":"IP-138155","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":462921,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://conservancy.umn.edu/server/api/core/bitstreams/f0230ff9-4dc6-4865-8b40-a72b2d2be87c/content"},{"id":462955,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.86121809846372,\n              44.65404950748291\n            ],\n            [\n              -120.60902083283865,\n              44.65404950748291\n            ],\n            [\n              -120.60902083283865,\n              45.86041592045436\n            ],\n            [\n              -122.86121809846372,\n              45.86041592045436\n            ],\n            [\n              -122.86121809846372,\n              44.65404950748291\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McClaughry, Jason D.","contributorId":194544,"corporation":false,"usgs":false,"family":"McClaughry","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":915960,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Madin, Ian P. 0000-0003-2008-8815","orcid":"https://orcid.org/0000-0003-2008-8815","contributorId":345199,"corporation":false,"usgs":false,"family":"Madin","given":"Ian","email":"","middleInitial":"P.","affiliations":[{"id":32397,"text":"Oregon Department of Geology and Mineral Industries","active":true,"usgs":false}],"preferred":false,"id":915961,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, Scott E.K. 0000-0002-9772-4122 sekbennett@usgs.gov","orcid":"https://orcid.org/0000-0002-9772-4122","contributorId":5340,"corporation":false,"usgs":true,"family":"Bennett","given":"Scott","email":"sekbennett@usgs.gov","middleInitial":"E.K.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":915962,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrey, Richard M.","contributorId":194345,"corporation":false,"usgs":false,"family":"Conrey","given":"Richard","email":"","middleInitial":"M.","affiliations":[{"id":13203,"text":"School of the Environment, Washington State University","active":true,"usgs":false}],"preferred":false,"id":915963,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227451,"text":"70227451 - 2022 - Applied citizen science in freshwater research","interactions":[],"lastModifiedDate":"2022-03-28T16:42:00.577703","indexId":"70227451","displayToPublicDate":"2022-01-17T08:47:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5067,"text":"WIREs Water","active":true,"publicationSubtype":{"id":10}},"title":"Applied citizen science in freshwater research","docAbstract":"<p>Worldwide, scientists are increasingly collaborating with the general public. Citizen science methods are readily applicable to freshwater research, monitoring, and education. In addition to providing cost-effective data on spatial and temporal scales that are otherwise unattainable, citizen science provides unique opportunities for engagement with local communities and stakeholders in resource management and decision-making. However, these methods are not infallible. Citizen science projects require deliberate planning in order to collect high data quality and sustain meaningful community partnerships. Citizen science practitioners also have an ethical responsibility to ensure that projects are not putting the safety of participants at stake. We discuss here how citizen science is being applied in freshwater research, emerging challenges in project planning and implementation, as well as how citizen science is shaping public understanding, policy, and management of freshwaters.</p>","language":"English","publisher":"Wiley","doi":"10.1002/wat2.1578","usgsCitation":"Metcalfe, A.N., Kennedy, T.A., Mendez, G.A., and Muehlbauer, J.D., 2022, Applied citizen science in freshwater research: WIREs Water, v. 9, e1578, 11 p., https://doi.org/10.1002/wat2.1578.","productDescription":"e1578, 11 p.","ipdsId":"IP-128560","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":394433,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2022-01-12","publicationStatus":"PW","contributors":{"editors":[{"text":"Lane, Stuart N.","contributorId":271165,"corporation":false,"usgs":false,"family":"Lane","given":"Stuart","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":830996,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Metcalfe, Anya N. 0000-0002-6286-4889 ametcalfe@usgs.gov","orcid":"https://orcid.org/0000-0002-6286-4889","contributorId":5271,"corporation":false,"usgs":true,"family":"Metcalfe","given":"Anya","email":"ametcalfe@usgs.gov","middleInitial":"N.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Theodore A. 0000-0003-3477-3629 tkennedy@usgs.gov","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":167537,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","email":"tkennedy@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830955,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mendez, Gabriella A.","contributorId":271142,"corporation":false,"usgs":false,"family":"Mendez","given":"Gabriella","email":"","middleInitial":"A.","affiliations":[{"id":52178,"text":"Northern Arizona University, Flagstaff, AZ 86011","active":true,"usgs":false}],"preferred":false,"id":830956,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muehlbauer, Jeffrey D. 0000-0003-1808-580X jmuehlbauer@usgs.gov","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":5045,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","email":"jmuehlbauer@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830957,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227452,"text":"70227452 - 2022 - Risk-based prioritization of organic chemicals and locations of ecological concern in sediment from Great Lakes tributaries","interactions":[],"lastModifiedDate":"2022-03-28T16:40:43.379038","indexId":"70227452","displayToPublicDate":"2022-01-17T08:45:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Risk-based prioritization of organic chemicals and locations of ecological concern in sediment from Great Lakes tributaries","docAbstract":"<p>With improved analytical techniques, environmental monitoring studies are increasingly able to report the occurrence of tens or hundreds of chemicals per site, making it difficult to identify the most relevant chemicals from a biological standpoint. For this study, organic chemical occurrence was examined, individually and as mixtures, in the context of potential biological effects. Sediment was collected at 71 Great Lakes tributary sites and analyzed for 87 chemicals. Multiple risk-based lines of evidence were used to prioritize chemicals and locations, including comparing sediment concentrations and estimated porewater concentrations to established whole-organism benchmarks (i.e., sediment and water quality criteria and screening values) and to high-throughput toxicity screening data from the U.S. Environmental Protection Agency's ToxCast database, estimating additive effects of chemical mixtures on common ToxCast endpoints, and estimating toxic equivalencies for mixtures of alkylphenols and polycyclic aromatic hydrocarbons (PAHs). This multiple-lines-of-evidence approach enabled the screening of more chemicals, mitigated the uncertainties of individual approaches, and strengthened common conclusions. Collectively, at least one benchmark/screening value was exceeded for 54 of the 87 chemicals, with exceedances observed at all 71 of the monitoring sites. Chemicals with the greatest potential for biological effects, both individually and as mixture components, were bisphenol A, 4-nonylphenol, indole, carbazole, and several polycyclic aromatic hydrocarbons (PAHs). Potential adverse outcomes based on ToxCast gene targets and putative adverse outcome pathways relevant to individual chemicals and chemical mixtures included tumors, skewed sex ratios, reproductive dysfunction, hepatic steatosis, and early mortality, among others. Results provide a screening level prioritization of chemicals with the greatest potential for adverse biological effects and an indication of sites where they are most likely to occur.</p>","language":"English","publisher":"Wiley","doi":"10.1002/etc.5286","usgsCitation":"Baldwin, A.K., Corsi, S., Stefaniak, O.M., Loken, L.C., Villeneuve, D.L., Ankley, G., Blackwell, B., Lenaker, P.L., Nott, M.A., and Mills, M.A., 2022, Risk-based prioritization of organic chemicals and locations of ecological concern in sediment from Great Lakes tributaries: Environmental Toxicology and Chemistry, v. 41, no. 4, p. 1016-1041, https://doi.org/10.1002/etc.5286.","productDescription":"26 p.","startPage":"1016","endPage":"1041","ipdsId":"IP-129929","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science 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,{"id":70227815,"text":"70227815 - 2022 - Individual heterogeneity influences the effects of translocation on urban dispersal of an invasive reptile","interactions":[],"lastModifiedDate":"2022-02-02T14:20:06.194879","indexId":"70227815","displayToPublicDate":"2022-01-15T13:52:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Individual heterogeneity influences the effects of translocation on urban dispersal of an invasive reptile","docAbstract":"<p><strong>Background</strong><br>Invasive reptiles pose a serious threat to global biodiversity, but early detection of individuals in an incipient population is often hindered by their cryptic nature, sporadic movements, and variation among individuals. Little is known about the mechanisms that affect the movement of these species, which limits our understanding of their dispersal. Our aim was to determine whether translocation or small-scale landscape features affect movement patterns of brown treesnakes (<i>Boiga irregularis</i>), a destructive invasive predator on the island of Guam.</p><p><strong>Methods</strong><br>We conducted a field experiment to compare the movements of resident (control) snakes to those of snakes translocated from forests and urban areas into new urban habitats. We developed a Bayesian hierarchical model to analyze snake movement mechanisms and account for attributes unique to invasive reptiles by incorporating multiple behavioral states and individual heterogeneity in movement parameters.</p><p><strong>Results</strong><br>We did not observe strong differences in mechanistic movement parameters (turning angle or step length) among experimental treatment groups. We found some evidence that translocated snakes from both forests and urban areas made longer movements than resident snakes, but variation among individuals within treatment groups weakened this effect. Snakes translocated from forests moved more frequently from pavement than those translocated from urban areas. Snakes translocated from urban areas moved less frequently from buildings than resident snakes. Resident snakes had high individual heterogeneity in movement probability.</p><p><strong>Conclusions</strong><br>Our approach to modeling movement improved our understanding of invasive reptile dispersal by allowing us to examine the mechanisms that influence their movement. 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0000-0002-1614-723X","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":119998,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin B.","affiliations":[],"preferred":false,"id":832361,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70256713,"text":"70256713 - 2022 - Seed germination responses to salinity for three rare wetland plants of spring-fed arid systems","interactions":[],"lastModifiedDate":"2024-09-03T15:42:50.820207","indexId":"70256713","displayToPublicDate":"2022-01-15T10:32:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Seed germination responses to salinity for three rare wetland plants of spring-fed arid systems","docAbstract":"<p><span>Spring-fed wetlands within arid systems host unique species of plants, many of which are threatened due to the vulnerability of these ecosystems. Increased salinity and drier hydrologic regimes due to anthropogenic activities threaten these systems. Furthermore, limited knowledge regarding key life history traits of species jeopardize the restoration and management of their rare plants. Here, we evaluated key aspects of the seed ecophysiology of three rare plants of the Southwestern United States:&nbsp;</span><i>Helianthus paradoxus</i><span>&nbsp;(Pecos sunflower),&nbsp;</span><i>Cirsium wrightii</i><span>&nbsp;(Wright's marsh thistle), and&nbsp;</span><i>Agalinis calycina</i><span>&nbsp;(Leoncita false-foxglove). We examined seed dormancy break under controlled conditions and evaluated the effects of field-derived salinity gradients on seed dormancy break and germination. Seeds of&nbsp;</span><i>C. wrightii</i><span>&nbsp;were nondormant at dispersal, germination was high (&gt;70%) under all treatments and was not affected by the tested salinities. Germination in&nbsp;</span><i>H. paradoxus</i><span>&nbsp;was high (&gt;70%) following cold stratification, but increasing salinities reduced germination.&nbsp;</span><i>A. calycina</i><span>&nbsp;seeds required cold stratification, but germination was low (&lt;50%) under all tested treatments and increasing salinities during incubation had the greatest negative effects in this species. Our findings contribute to the restoration of rare wetland plants within spring-fed arid marshes susceptible to groundwater declines and human-induced salinization.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2021.104705","usgsCitation":"Cantu de Leija, A., King, S.L., and Hawkins, T.S., 2022, Seed germination responses to salinity for three rare wetland plants of spring-fed arid systems: Journal of Arid Environments, v. 199, 104705, 9 p., https://doi.org/10.1016/j.jaridenv.2021.104705.","productDescription":"104705, 9 p.","ipdsId":"IP-132822","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":449151,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jaridenv.2021.104705","text":"Publisher Index Page"},{"id":433410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Bitter Lake National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -104.36080938594469,\n              33.520358619429445\n            ],\n            [\n              -104.43881579390636,\n              33.51880990926614\n            ],\n            [\n              -104.4425286679454,\n              33.4036104944898\n            ],\n            [\n              -104.3632761203099,\n              33.4036104944898\n            ],\n            [\n              -104.36080938594469,\n              33.520358619429445\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"199","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cantu de Leija, Antonio","contributorId":341654,"corporation":false,"usgs":false,"family":"Cantu de Leija","given":"Antonio","email":"","affiliations":[{"id":81771,"text":"1307 School of Renewable Natural Resources","active":true,"usgs":false}],"preferred":false,"id":908747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hawkins, Tracy S.","contributorId":341655,"corporation":false,"usgs":false,"family":"Hawkins","given":"Tracy","email":"","middleInitial":"S.","affiliations":[{"id":81773,"text":"Research Ecologist","active":true,"usgs":false}],"preferred":false,"id":908748,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70228669,"text":"70228669 - 2022 - Geographic variation and thermal plasticity shape salamander metabolic rates under current and future climates","interactions":[],"lastModifiedDate":"2022-02-17T11:44:32.416322","indexId":"70228669","displayToPublicDate":"2022-01-15T10:18:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Geographic variation and thermal plasticity shape salamander metabolic rates under current and future climates","docAbstract":"<p><span>Predicted changes in global temperature are expected to increase extinction risk for ectotherms, primarily through increased metabolic rates. Higher metabolic rates generate increased maintenance energy costs which are a major component of energy budgets. Organisms often employ plastic or evolutionary (e.g., local adaptation) mechanisms to optimize metabolic rate with respect to their environment. We examined relationships between temperature and standard metabolic rate across four populations of a widespread amphibian species to determine if populations vary in metabolic response and if their metabolic rates are plastic to seasonal thermal cues. Populations from warmer climates lowered metabolic rates when acclimating to summer temperatures as compared to spring temperatures. This may act as an energy saving mechanism during the warmest time of the year. No such plasticity was evident in populations from cooler climates. Both juvenile and adult salamanders exhibited metabolic plasticity. Although some populations responded to historic climate thermal cues, no populations showed plastic metabolic rate responses to future climate temperatures, indicating there are constraints on plastic responses. We postulate that impacts of warming will likely impact the energy budgets of salamanders, potentially affecting key demographic rates, such as individual growth and investment in reproduction.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8433","usgsCitation":"Munoz, D.J., Miller, D., Schilder, R., and Campbell Grant, E.H., 2022, Geographic variation and thermal plasticity shape salamander metabolic rates under current and future climates: Ecology and Evolution, v. 12, no. 1, e8433,12 p., https://doi.org/10.1002/ece3.8433.","productDescription":"e8433,12 p.","ipdsId":"IP-116918","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":449154,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.8433","text":"Publisher Index Page"},{"id":435997,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RKLDFU","text":"USGS data release","linkHelpText":"Report to NECSC: Adaptive capacity in a forest indicator species"},{"id":396069,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -58.3154296875,\n              45.82879925192134\n            ],\n            [\n              -60.16113281250001,\n              47.60616304386874\n            ],\n            [\n              -65.3466796875,\n              49.5822260446217\n            ],\n            [\n              -68.5546875,\n              49.724479188712984\n            ],\n            [\n              -79.8046875,\n              48.69096039092549\n            ],\n            [\n              -81.6943359375,\n       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      -65.6982421875,\n              43.100982876188546\n            ],\n            [\n              -58.3154296875,\n              45.82879925192134\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -96.13037109375,\n              44.276671273775186\n            ],\n            [\n              -95.42724609375,\n              44.276671273775186\n            ],\n            [\n              -95.42724609375,\n              44.824708282300236\n            ],\n            [\n              -96.13037109375,\n              44.824708282300236\n            ],\n            [\n              -96.13037109375,\n              44.276671273775186\n            ]\n          ]\n        ]\n      }\n    }\n  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J.","contributorId":279475,"corporation":false,"usgs":false,"family":"Munoz","given":"D.","email":"","middleInitial":"J.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":834967,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, D. A. W.","contributorId":264739,"corporation":false,"usgs":false,"family":"Miller","given":"D. A. W.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":834968,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schilder, R.","contributorId":279476,"corporation":false,"usgs":false,"family":"Schilder","given":"R.","email":"","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":834969,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":834970,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70262054,"text":"70262054 - 2022 - A machine learning approach to identify barriers in stream networks demonstrates high prevalence of unmapped riverine dams","interactions":[],"lastModifiedDate":"2025-01-13T14:43:45.646463","indexId":"70262054","displayToPublicDate":"2022-01-15T07:41:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"A machine learning approach to identify barriers in stream networks demonstrates high prevalence of unmapped riverine dams","docAbstract":"<p><span>Restoring stream ecosystem integrity by removing unused or derelict dams has become a priority for watershed conservation globally. However, efforts to restore connectivity are constrained by the availability of accurate dam inventories which often overlook smaller unmapped riverine dams. Here we develop and test a machine learning approach to identify unmapped dams using a combination of publicly available topographic and geospatial habitat data. Specifically, we trained a random forest classification algorithm to identify unmapped dams using digitally engineered predictor variables and known dam sites for validation. We applied our algorithm to two subbasins in the Hudson River watershed,&nbsp;</span>USA<span>, and quantified connectivity impacts, as well as evaluated a range of predictor sets to examine tradeoffs between classification accuracy and model parameterization effort. The random forest classifier achieved high accuracy in predicting dam sites (true positive rate&nbsp;=&nbsp;89%, false positive rate&nbsp;=&nbsp;1.2%) using a subset of variables related to stream slope and presence of upstream lentic habitats. Unmapped dams were prevalent throughout the two test watersheds. In fact, existing dam inventories underestimated the true number of dams by ∼80–94%. Accounting for previously unmapped dams resulted in a 62–90% decrease in dendritic connectivity indices for&nbsp;migratory fishes. Unmapped dams may be pervasive and can dramatically bias stream connectivity information. However, we find that machine learning approaches can provide an accurate and scalable means of identifying unmapped dams that can guide efforts to develop accurate dam inventories, thereby informing and empowering efforts to better manage them.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2021.113952","usgsCitation":"Buchanan, B., Sethi, S., Cuppett, S., Lung, M., Jackman, G., Zarri, L., Duvall, E., Dietrich, J., Sullivan, P., Dominitz, A., Archibald, J., Flecker, A., and Rahm, B., 2022, A machine learning approach to identify barriers in stream networks demonstrates high prevalence of unmapped riverine dams: Journal of Environmental Management, v. 302, no. Part A, 113952, 11 p., https://doi.org/10.1016/j.jenvman.2021.113952.","productDescription":"113952, 11 p.","ipdsId":"IP-129279","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467204,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2021.113952","text":"Publisher Index Page"},{"id":465979,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Foundry Brook, Lattintown Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -73.85258131006508,\n              41.29588488429172\n            ],\n            [\n              -73.85258131006508,\n              41.72638789605105\n        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ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cuppett, Scott","contributorId":348049,"corporation":false,"usgs":false,"family":"Cuppett","given":"Scott","affiliations":[{"id":56439,"text":"NY DEC","active":true,"usgs":false}],"preferred":false,"id":922902,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lung, Megan","contributorId":348050,"corporation":false,"usgs":false,"family":"Lung","given":"Megan","affiliations":[{"id":56439,"text":"NY DEC","active":true,"usgs":false}],"preferred":false,"id":922903,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackman, George","contributorId":348051,"corporation":false,"usgs":false,"family":"Jackman","given":"George","affiliations":[{"id":83297,"text":"Riverkeeper, Inc.","active":true,"usgs":false}],"preferred":false,"id":922904,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zarri, Liam","contributorId":348052,"corporation":false,"usgs":false,"family":"Zarri","given":"Liam","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922905,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Duvall, Ethan","contributorId":348053,"corporation":false,"usgs":false,"family":"Duvall","given":"Ethan","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922906,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dietrich, Jeremy","contributorId":348054,"corporation":false,"usgs":false,"family":"Dietrich","given":"Jeremy","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922907,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sullivan, Patrick","contributorId":348055,"corporation":false,"usgs":false,"family":"Sullivan","given":"Patrick","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922908,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dominitz, Alon","contributorId":348057,"corporation":false,"usgs":false,"family":"Dominitz","given":"Alon","affiliations":[{"id":56930,"text":"New York DEC","active":true,"usgs":false}],"preferred":false,"id":922909,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Archibald, Josephine","contributorId":348060,"corporation":false,"usgs":false,"family":"Archibald","given":"Josephine","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":922910,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Flecker, Alexander","contributorId":348061,"corporation":false,"usgs":false,"family":"Flecker","given":"Alexander","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922911,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rahm, Brian","contributorId":348062,"corporation":false,"usgs":false,"family":"Rahm","given":"Brian","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922912,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70250299,"text":"70250299 - 2022 - A comparison of orbital-resolution, Late Pleistocene Alkenone and foraminiferal assemblage-based sea surface temperature reconstructions from the Southwest Pacific","interactions":[],"lastModifiedDate":"2023-12-01T12:50:53.526701","indexId":"70250299","displayToPublicDate":"2022-01-15T06:49:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of orbital-resolution, Late Pleistocene Alkenone and foraminiferal assemblage-based sea surface temperature reconstructions from the Southwest Pacific","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif text-s\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\"><span>Global and regional reconstructions of past climate conditions often incorporate&nbsp;sea surface temperature&nbsp;(SST) estimates from multiple proxies because not every&nbsp;paleotemperature&nbsp;proxy is applicable in all geographic locations. This practice of assimilating estimates from different proxies in global or regional temperature syntheses makes the implicit assumption that estimates derived from different proxies can be meaningfully intercompared. However, evidence to support the validity of this assumption is limited. Using paleotemperature data from sediments collected from&nbsp;ODP&nbsp;Site 1125 in the Southwest Pacific, we conduct a ∼1 Myr, orbital-scale SST proxy comparison of a recently published alkenone-derived SST record with a previously published foraminiferal assemblage-based SST record. These&nbsp;alkenone&nbsp;and foraminiferal assemblage SST datasets show strong structural similarity and yield remarkably similar estimates for basic climate metrics, including mean, median, standard deviation, and range. Statistical analysis indicates that the correlation between the two SST records is highly significant. In the spectral domain, the records share the same dominant 100 kyr beat, are coherent and in phase with each other at this frequency, and have the same coherence and phase relationship with benthic foraminiferal δ</span><sup>18</sup><span>O. Results from this work demonstrate that these two proxies would yield very similar estimates for the&nbsp;paleoclimate&nbsp;metrics most commonly used in empirical paleoclimate reconstructions that seek to document the evolution of climate over this interval. However, significant disparities between SST estimates derived from the two proxies exist for some time periods, particularly during glacial and interglacial extrema. This comparison suggests that treating estimates from these proxies as equivalent in studies that focus on short time windows (e.g. a few thousand to tens-of-thousands of years), particularly in investigations that seek to characterize glacial or interglacial extrema, could be potentially problematic. However, the sensitive location of Site 1125, just north of the Subtropical Front, likely accentuates the difference between temperature estimates from these proxies, which may be attenuated in other oceanographic settings. We attribute the discrepancies between the two SST records to two main causes: seasonal&nbsp;leakages&nbsp;of cold water across the Subtropical Front during glacial extrema and differential&nbsp;seasonality&nbsp;of maximum alkenone and foraminiferal production.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2021.107345","usgsCitation":"Henry, E.A., Lawrence, K., Peterson, L.C., and Robinson, M., 2022, A comparison of orbital-resolution, Late Pleistocene Alkenone and foraminiferal assemblage-based sea surface temperature reconstructions from the Southwest Pacific: Quaternary Science Reviews, v. 277, 107345, 13 p., https://doi.org/10.1016/j.quascirev.2021.107345.","productDescription":"107345, 13 p.","ipdsId":"IP-131918","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":449157,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2021.107345","text":"Publisher Index Page"},{"id":423137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"277","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Henry, Emilie A.","contributorId":332081,"corporation":false,"usgs":false,"family":"Henry","given":"Emilie","email":"","middleInitial":"A.","affiliations":[{"id":79380,"text":"Lafayette College","active":true,"usgs":false}],"preferred":false,"id":889360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Kira T.","contributorId":332082,"corporation":false,"usgs":false,"family":"Lawrence","given":"Kira T.","affiliations":[{"id":79380,"text":"Lafayette College","active":true,"usgs":false}],"preferred":false,"id":889361,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Laura C.","contributorId":332083,"corporation":false,"usgs":false,"family":"Peterson","given":"Laura","email":"","middleInitial":"C.","affiliations":[{"id":34070,"text":"Luther College","active":true,"usgs":false}],"preferred":false,"id":889362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robinson, Marci M.","contributorId":332084,"corporation":false,"usgs":true,"family":"Robinson","given":"Marci M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":889363,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70262062,"text":"70262062 - 2022 - Similar environmental conditions are associated with Walleye and Yellow Perch recruitment success in Wisconsin lakes","interactions":[],"lastModifiedDate":"2025-01-10T17:20:31.111342","indexId":"70262062","displayToPublicDate":"2022-01-15T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Similar environmental conditions are associated with Walleye and Yellow Perch recruitment success in Wisconsin lakes","docAbstract":"<p><span>Since the mid-2000s, recruitment of Walleye&nbsp;</span><i>Sander vitreus</i><span>&nbsp;in some northern Wisconsin lakes has declined, potentially because of climate-induced changes in lake environments. Yellow Perch&nbsp;</span><i>Perca flavescens</i><span>&nbsp;is also an ecologically and culturally important fish species in this region, but mechanisms driving Yellow Perch recruitment are unclear because of a lack of targeted sampling. Previous studies have suggested that recruitment of these two species may be regulated by similar factors, and observed declines in Walleye recruitment may be cause for concern about Yellow Perch recruitment. Our objectives were to determine if abiotic factors related to recruitment success were similar between Walleye and Yellow Perch populations in northern Wisconsin lakes and if the probability of successful Walleye recruitment was related to estimates of juvenile Yellow Perch abundance before Walleye recruitment declines were observed. We addressed these objectives using historical data from Wisconsin lakes. Random forest analysis incorporating lake-specific averages of predictor variables indicated that winter conditions (duration or severity), growing degree days, variation in spring temperatures, peak summer temperature, and Secchi depth were important predictors of recruitment success for both species. Logistic regression indicated that before Walleye recruitment declines were observed on some lakes (2000–2006), Walleye recruitment success was related to relative abundance of juvenile Yellow Perch in mini-fyke-net sampling. Our results indicate that landscape-level patterns in recruitment success for the two species are likely similar and additional research to understand Yellow Perch recruitment trends is warranted. Better information on Yellow Perch recruitment could contribute to a better understanding of Walleye recruitment trends as declines in Yellow Perch could influence prey availability and survival of age-0 Walleye. Furthermore, potential declines in Yellow Perch could lead to changes in the numbers and size of Yellow Perch caught by anglers, which may have implications for harvest management.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10729","usgsCitation":"Brandt, E., Feiner, Z., Latzka, A., and Isermann, D.A., 2022, Similar environmental conditions are associated with Walleye and Yellow Perch recruitment success in Wisconsin lakes: North American Journal of Fisheries Management, v. 42, no. 3, p. 630-641, https://doi.org/10.1002/nafm.10729.","productDescription":"12 p.","startPage":"630","endPage":"641","ipdsId":"IP-127934","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -92.3619142125417,\n              46.69624201075456\n            ],\n            [\n              -92.3619142125417,\n              45.451292765361956\n            ],\n            [\n              -89.83163049007825,\n              45.451292765361956\n            ],\n            [\n              -89.83163049007825,\n              46.69624201075456\n            ],\n            [\n              -92.3619142125417,\n              46.69624201075456\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"42","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Brandt, Ethan J.","contributorId":348096,"corporation":false,"usgs":false,"family":"Brandt","given":"Ethan J.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":922936,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feiner, Zachary S.","contributorId":348097,"corporation":false,"usgs":false,"family":"Feiner","given":"Zachary S.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":922937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Latzka, Alexander W.","contributorId":348099,"corporation":false,"usgs":false,"family":"Latzka","given":"Alexander W.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":922938,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922935,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70262536,"text":"70262536 - 2022 - Differences in population characteristics and modeled response to harvest regulations in reestablished Appalachian Walleye populations","interactions":[],"lastModifiedDate":"2025-01-22T23:17:51.695114","indexId":"70262536","displayToPublicDate":"2022-01-15T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Differences in population characteristics and modeled response to harvest regulations in reestablished Appalachian Walleye populations","docAbstract":"<p><span>Historically, the Monongahela, Tygart, and Cheat River watersheds in West Virginia were impaired by acidification from acid mine drainage and Walleye&nbsp;</span><i>Sander vitreus</i><span>&nbsp;were extirpated from these watersheds by the 1940s. Walleye were reestablished after water quality improvements following passage of environmental legislation and subsequent reintroduction efforts. We compared population characteristics, with emphasis on growth, of Walleye and used modeling to predict the potential effects of harvest regulations in the Monongahela River and two main-stem reservoirs in the Cheat River and Tygart River watersheds. Statistical comparisons of von Bertalanffy growth curves and relative growth indices indicated that Walleye growth significantly differed across all water bodies. Relative growth index results suggested that Walleye growth was above average in Cheat Lake, average in the Monongahela River, and below average in Tygart Lake relative to other North American populations. Growth was negatively correlated with Walleye relative abundance and positively correlated with estimates of productivity (total phosphorus, chlorophyll&nbsp;</span><i>a</i><span>). Walleye diets significantly differed across all water bodies, with diets dominated by Yellow Perch&nbsp;</span><i>Perca flavescens</i><span>&nbsp;and Gizzard Shad&nbsp;</span><i>Dorosoma cepedianum</i><span>&nbsp;in Cheat Lake, where growth was fastest. Population modeling suggested that effects of exploitation on yield, spawning potential, and size structure were similar under regulations of no length limit and a minimum length limit (381 mm). Models suggested that removing length limits in Tygart Lake could increase angler harvest opportunities and pose minimal threat to the fishery. Models suggested that a protected slot limit could provide increased protection to the spawning potential of Cheat Lake and the Monongahela River populations. Additionally, models predicted that a protected slot limit could increase the number of large (&gt;630-mm) Walleye in these waters. Our findings demonstrate the different characteristics that Walleye populations can develop after reestablishment based on abiotic and biotic conditions and the need for watershed-specific management.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10723","usgsCitation":"Smith, D., Hilling, C., Welsh, S.A., and Wellman Jr., D., 2022, Differences in population characteristics and modeled response to harvest regulations in reestablished Appalachian Walleye populations: North American Journal of Fisheries Management, v. 42, no. 3, p. 612-629, https://doi.org/10.1002/nafm.10723.","productDescription":"18 p.","startPage":"612","endPage":"629","ipdsId":"IP-127935","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480960,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Cheat Lake, Monongahela River, Tygart Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.43609032800657,\n              39.70971363776053\n            ],\n            [\n              -80.43609032800657,\n              39.288105835150134\n            ],\n            [\n              -79.48527811621443,\n              39.288105835150134\n            ],\n            [\n              -79.48527811621443,\n              39.70971363776053\n            ],\n            [\n              -80.43609032800657,\n              39.70971363776053\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"42","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Dustin M.","contributorId":349597,"corporation":false,"usgs":false,"family":"Smith","given":"Dustin M.","affiliations":[{"id":56173,"text":"West Virginia DNR","active":true,"usgs":false}],"preferred":false,"id":924503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hilling, Corbin D.","contributorId":349598,"corporation":false,"usgs":false,"family":"Hilling","given":"Corbin D.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":924504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welsh, Stuart A. 0000-0003-0362-054X","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":217037,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart","email":"","middleInitial":"A.","affiliations":[{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924502,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wellman Jr., David I.","contributorId":349599,"corporation":false,"usgs":false,"family":"Wellman Jr.","given":"David I.","affiliations":[{"id":56173,"text":"West Virginia DNR","active":true,"usgs":false}],"preferred":false,"id":924505,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70255063,"text":"70255063 - 2022 - Wildfire effects on mass and thermal tolerance of Hydropsyche oslari (Trichoptera) in southwestern USA montane grassland streams","interactions":[],"lastModifiedDate":"2024-06-12T23:33:17.581674","indexId":"70255063","displayToPublicDate":"2022-01-14T18:30:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Wildfire effects on mass and thermal tolerance of Hydropsyche oslari (Trichoptera) in southwestern USA montane grassland streams","docAbstract":"<div class=\"col-lg-9 article__content\"><div class=\"article__body show-references \"><div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>Large-scale disturbances, such as wildfire, can markedly affect streams for years. As terrestrial areas within a watershed slowly recover, stream environments and biota can experience repeated and long-lasting challenges. In 2011, the Las Conchas wildfire burned<span>&nbsp;</span><sup>1</sup>/<sub>3</sub><span>&nbsp;</span>of the Valles Caldera National Preserve in northern New Mexico, USA. Seven y post-fire, streams located near the burn perimeter continue to experience varying levels of alteration (e.g., channel alteration with large diel temperature swings), whereas the terrestrial uplands have begun to recover. Extreme temperatures in stream systems may affect the aquatic community, including ectotherms such as caddisflies. These post-fire temperature ranges may increase an ectotherm’s breadth of thermal adaptation, but at metabolic costs that diminish organismal performance, such as growth, development, and fecundity. In this study we characterized in-situ effects of varied thermal regimes across preserve streams on the performance of the caddisfly<span>&nbsp;</span><i>Hydropsyche oslari</i><span>&nbsp;</span>Banks, 1905. We measured mass and critical thermal maximum (CT<sub>max</sub>) in<span>&nbsp;</span><i>H. oslari</i><span>&nbsp;</span>larvae from preserve streams affected by wildfire (high temperature range) and in streams minimally affected by wildfire (low temperature range). We predicted that increased daily temperature maxima and reduced daily temperature minima (i.e., large diel temperature swings) would be associated with reduced<span>&nbsp;</span><i>H. oslari</i><span>&nbsp;</span>mass because of the limiting effects of suboptimal temperatures on growth. As predicted, in the weeks prior to their emergence as terrestrial adults, 5<sup>th</sup>-instar larvae within the high-temperature range stream had reduced mass (mean 3.3 ± SE 0.55 mg) relative to larvae from the low-temperature range stream (6.2 ± 0.69 mg). We also predicted that CT<sub>max</sub><span>&nbsp;</span>of<span>&nbsp;</span><i>H. oslari</i><span>&nbsp;</span>would reflect stream thermal history. Indeed, larvae<span>&nbsp;</span><i>H. oslari</i><span>&nbsp;</span>from the high-temperature range stream exhibited increased CT<sub>max</sub><span>&nbsp;</span>(35.4 ± 0.17°C) compared with larvae from the low-temperature range stream (34.4 ± 0.28°C). We demonstrated that the effects of wildfire on caddisflies can be long lasting, as evidenced by the reduced size at maturity and higher thermal tolerance in a caddisfly population 7 y post-fire.</p></div></div></div></div>","language":"English","publisher":"University of Chicago Press","doi":"10.1086/718556","usgsCitation":"Kremer, L., and Caldwell, C.A., 2022, Wildfire effects on mass and thermal tolerance of Hydropsyche oslari (Trichoptera) in southwestern USA montane grassland streams: Freshwater Science, v. 41, no. 1, https://doi.org/10.1086/718556.","ipdsId":"IP-126038","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":430055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kremer, Lauren","contributorId":338486,"corporation":false,"usgs":false,"family":"Kremer","given":"Lauren","email":"","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":903301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell, Colleen A. 0000-0002-4730-4867 ccaldwel@usgs.gov","orcid":"https://orcid.org/0000-0002-4730-4867","contributorId":3050,"corporation":false,"usgs":true,"family":"Caldwell","given":"Colleen","email":"ccaldwel@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903300,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
]}