{"pageNumber":"226","pageRowStart":"5625","pageSize":"25","recordCount":41062,"records":[{"id":70226499,"text":"70226499 - 2021 - Is the grass always greener? Land surface phenology reveals differences in peak and season-long vegetation productivity responses to climate and management","interactions":[],"lastModifiedDate":"2021-11-22T13:10:05.542882","indexId":"70226499","displayToPublicDate":"2021-07-22T07:04:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Is the grass always greener? Land surface phenology reveals differences in peak and season-long vegetation productivity responses to climate and management","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Vegetation phenology—the seasonal timing and duration of vegetative phases—is controlled by spatiotemporally variable contributions of climatic and environmental factors plus additional potential influence from human management. We used land surface phenology derived from the Advanced Very High Resolution Radiometer and climate data to examine variability in vegetation productivity and phenological dates from 1989 to 2014 in the U.S. Northwestern Plains, a region with notable spatial heterogeneity in climate, vegetation, and land use. We first analyzed interannual trends in six phenological measures as a baseline. We then demonstrated how including annual-resolution predictors can provide more nuanced insights into measures of phenology between plant communities and across the ecoregion. Across the study area, higher annual precipitation increased both peak and season-long productivity. In contrast, higher mean annual temperatures tended to increase peak productivity but for the majority of the study area decreased season-long productivity. Annual precipitation and temperature had strong explanatory power for productivity-related phenology measures but predicted date-based measures poorly. We found that relationships between climate and phenology varied across the region and among plant communities and that factors such as recovery from disturbance and anthropogenic management also contributed in certain regions. In sum, phenological measures did not respond ubiquitously nor covary in their responses. Nonclimatic dynamics can decouple phenology from climate; therefore, analyses including only interannual trends should not assume climate alone drives patterns. For example, models of areas exhibiting greening or browning should account for climate, anthropogenic influence, and natural disturbances. Investigating multiple aspects of phenology to describe growing-season dynamics provides a richer understanding of spatiotemporal patterns that can be used for predicting ecosystem responses to future climates and land-use change. Such understanding allows for clearer interpretation of results for conservation, wildlife, and land management.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7904","usgsCitation":"Wood, D.J., Powell, S., Stoy, P.C., Thurman, L., and Beever, E.A., 2021, Is the grass always greener? Land surface phenology reveals differences in peak and season-long vegetation productivity responses to climate and management: Ecology and Evolution, v. 11, no. 16, p. 11168-11199, https://doi.org/10.1002/ece3.7904.","productDescription":"32 p.","startPage":"11168","endPage":"11199","ipdsId":"IP-123458","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":451442,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.7904","text":"External Repository"},{"id":391973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"16","noUsgsAuthors":false,"publicationDate":"2021-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, David J. A. 0000-0003-4315-5160 dwood@usgs.gov","orcid":"https://orcid.org/0000-0003-4315-5160","contributorId":177588,"corporation":false,"usgs":true,"family":"Wood","given":"David","email":"dwood@usgs.gov","middleInitial":"J. A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":827115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powell, Scott","contributorId":192347,"corporation":false,"usgs":false,"family":"Powell","given":"Scott","affiliations":[],"preferred":false,"id":827116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stoy, Paul C.","contributorId":204157,"corporation":false,"usgs":false,"family":"Stoy","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":827117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurman, Lindsey 0000-0003-3142-4909","orcid":"https://orcid.org/0000-0003-3142-4909","contributorId":269425,"corporation":false,"usgs":true,"family":"Thurman","given":"Lindsey","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":827118,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beever, Erik A. 0000-0002-9369-486X ebeever@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-486X","contributorId":2934,"corporation":false,"usgs":true,"family":"Beever","given":"Erik","email":"ebeever@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":827119,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70223319,"text":"70223319 - 2021 - Mycobiome traits associated with disease tolerance predict many western North American bat species will be susceptible to white-nose syndrome","interactions":[],"lastModifiedDate":"2023-06-21T16:13:12.306551","indexId":"70223319","displayToPublicDate":"2021-07-21T18:17:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9147,"text":"Microbilogy Spectrum","active":true,"publicationSubtype":{"id":10}},"title":"Mycobiome traits associated with disease tolerance predict many western North American bat species will be susceptible to white-nose syndrome","docAbstract":"<div class=\"sections-navbar__container\"><div class=\"core-self-citation\"></div></div><div id=\"abstracts\"><div class=\"core-container\"><div>White-nose syndrome (WNS), a fungal disease that has caused catastrophic population declines of bats in eastern North America, is rapidly spreading across the continent and now threatens previously unexposed bat species in western North America. The causal agent of WNS, the fungus<span>&nbsp;</span><span class=\"named-content\" data-type=\"genus-species\">Pseudogymnoascus destructans</span>, can infect many species of hibernating bats, but susceptibility to WNS varies by host species. We previously reported that certain traits of the skin microbiome, particularly yeast diversity and abundance, of bat species in eastern North America are strongly associated with resistance to WNS. Using these traits, we developed models to predict WNS susceptibility of 13 species of western North American bats. Based on models derived from yeast species diversity, only one bat species,<span>&nbsp;</span><span class=\"named-content\" data-type=\"genus-species\">Myotis velifer</span>, was predicted to be WNS resistant (i.e., may develop the disease, but with low mortality rates). We also screened yeasts found on western bats for<span>&nbsp;</span><i>P. destructans</i>-antagonistic properties by spore germination and growth inhibition/competition assays and found the ability of yeasts to inhibit<span>&nbsp;</span><i>P. destructans in vitro</i><span>&nbsp;</span>to be strain specific. Similar to results of inhibition assays performed with yeasts isolated from bats in eastern North America, few yeasts isolated from bats in western North America inhibited<span>&nbsp;</span><i>P. destructans in vitro.</i><span>&nbsp;</span>Continued monitoring of western bat populations will serve to validate the accuracy of the mycobiome analysis in predicting WNS susceptibility, document population and susceptibility trends, and identify additional predictors to assess the vulnerability of naive bat populations to WNS.</div></div></div>","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/Spectrum.00254-21","usgsCitation":"Vanderwolf, K., Campbell, L., Taylor, D.R., Goldberg, T.L., Blehert, D.S., and Lorch, J., 2021, Mycobiome traits associated with disease tolerance predict many western North American bat species will be susceptible to white-nose syndrome: Microbilogy Spectrum, v. 9, no. 1, e00254-21. 11 p.; Data Release, https://doi.org/10.1128/Spectrum.00254-21.","productDescription":"e00254-21. 11 p.; Data Release","ipdsId":"IP-129959","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":451445,"rank":3,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1128/spectrum.00254-21","text":"External Repository"},{"id":388401,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418303,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H8Q23E"}],"volume":"9","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Vanderwolf, Karen J","contributorId":244763,"corporation":false,"usgs":false,"family":"Vanderwolf","given":"Karen J","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":821713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell, Lewis J. 0000-0002-7852-2250","orcid":"https://orcid.org/0000-0002-7852-2250","contributorId":244773,"corporation":false,"usgs":false,"family":"Campbell","given":"Lewis J.","affiliations":[],"preferred":false,"id":821714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, Daniel R. 0000-0001-5391-0321","orcid":"https://orcid.org/0000-0001-5391-0321","contributorId":260163,"corporation":false,"usgs":false,"family":"Taylor","given":"Daniel","email":"","middleInitial":"R.","affiliations":[{"id":52527,"text":"National Wildlife Health Center (previous employee)","active":true,"usgs":false}],"preferred":false,"id":821715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldberg, Tony L. 0000-0003-3962-4913","orcid":"https://orcid.org/0000-0003-3962-4913","contributorId":244765,"corporation":false,"usgs":false,"family":"Goldberg","given":"Tony","email":"","middleInitial":"L.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":821716,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blehert, David S. 0000-0002-1065-9760 dblehert@usgs.gov","orcid":"https://orcid.org/0000-0002-1065-9760","contributorId":140397,"corporation":false,"usgs":true,"family":"Blehert","given":"David","email":"dblehert@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":821717,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":264594,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":821718,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":58027,"text":"ofr20041348 - 2021 - Hazard analysis of landslides triggered by Typhoon Chata’an on July 2, 2002, in Chuuk State, Federated States of Micronesia","interactions":[],"lastModifiedDate":"2025-01-29T20:22:29.930774","indexId":"ofr20041348","displayToPublicDate":"2021-07-21T12:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2004-1348","displayTitle":"Hazard Analysis of Landslides Triggered by Typhoon Chata’an on July 2, 2002, in Chuuk State, Federated States of Micronesia","title":"Hazard analysis of landslides triggered by Typhoon Chata’an on July 2, 2002, in Chuuk State, Federated States of Micronesia","docAbstract":"<p>More than 250 landslides were triggered across the eastern volcanic islands of Chuuk State in the Federated States of Micronesia by torrential rainfall from tropical storm Chata’an on July 2, 2002. Landslides triggered during nearly 20 inches of rainfall in less than 24 hours caused 43 fatalities and the destruction or damage of 231 structures, including homes, schools, community centers, and medical dispensaries. Landslides also buried roads, crops, and water supplies. The landslides ranged in volume from a few cubic meters to more than 1 million cubic meters. Most of the failures began as slumps and transformed into debris flows, some of which traveled several hundred meters across coastal flatlands into populated areas. A landslide-inventory map produced after the storm shows that the island of Tonoas had the largest area affected by landslides, although the islands of Weno, Fefan, Etten, Uman, Siis, Udot, Eot, and Fanapanges also had significant landslides. Based on observations since the storm, we estimate the continuing hazard from landslides triggered by Chata’an to be relatively low. However, tropical storms and typhoons similar to Chata’an frequently develop in Micronesia and are likely to affect the islands of Chuuk in the future. <br></p><p>To assess the landslide hazard from future tropical storms, we produced a hazard map that identifies landslide-source areas of high, moderate, and low hazard. This map can be used to identify relatively safe areas for relocating structures or establishing areas where people could gather for shelter in relative safety during future typhoons or tropical storms similar to Chata’an.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20041348","productDescription":"Report: 22 p.; 2 Plates: 35.71 x 40.02 inches","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":387302,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2004/1348/ofr20041348_plate1_Revision.pdf","text":"Plate 1","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2004-1348 Plate 1","linkHelpText":"Landslide Inventory Map of Chuuk Islands Affected by Typhoon Chata'an"},{"id":182255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2004/1348/coverthb.jpg"},{"id":387301,"rank":2,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2004/1348/versionHist.txt","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2004-1348 version history"},{"id":387300,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2004/1348/ofr20041348_pamphlet_Revision.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2004-1348 Pamphlet"},{"id":387303,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2004/1348/ofr20041348_plate2_Revision.pdf","text":"Plate 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2004-1348 Plate 2","linkHelpText":"Debris-Flow Hazard Map of Chuuk Islands Affected by Typhoon Chata’an"},{"id":391875,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_69259.htm"}],"country":"Federated States of Micronesia","state":"Chuuk State","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              151.675,\n              7.2789\n            ],\n            [\n              151.9022,\n              7.2789\n            ],\n            [\n              151.9022,\n              7.4689\n            ],\n            [\n              151.675,\n              7.4689\n            ],\n            [\n              151.675,\n              7.2789\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.1: July 21, 2021","contact":"<p>Director,&nbsp;<a href=\"https://www.usgs.gov/centers/geohazards/\" data-mce-href=\"https://www.usgs.gov/centers/geohazards/\">Geologic Hazards Science Center</a><br>U.S. Geological Survey<br>Box 25046, Mail Stop 966<br>Denver, CO 80225</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Overview of the Landslide Event</li><li>Geology and Physiographic Setting</li><li>Landslides Triggered by Chata’an</li><li>Significant Landslides</li><li>Assessment of Remaining and Future Landslide Hazards</li><li>Summary and Conclusions</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishedDate":"2004-10-11","revisedDate":"2021-07-21","noUsgsAuthors":false,"publicationDate":"2004-10-11","publicationStatus":"PW","scienceBaseUri":"4f4e4a6be4b07f02db63d776","contributors":{"authors":[{"text":"Harp, Edwin L. harp@usgs.gov","contributorId":1290,"corporation":false,"usgs":true,"family":"Harp","given":"Edwin","email":"harp@usgs.gov","middleInitial":"L.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":258170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reid, Mark E. 0000-0002-5595-1503 mreid@usgs.gov","orcid":"https://orcid.org/0000-0002-5595-1503","contributorId":1167,"corporation":false,"usgs":true,"family":"Reid","given":"Mark","email":"mreid@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":258169,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Michael, John A. jmichael@usgs.gov","contributorId":1877,"corporation":false,"usgs":true,"family":"Michael","given":"John","email":"jmichael@usgs.gov","middleInitial":"A.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":258171,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70222368,"text":"70222368 - 2021 - Ignitions explain more than climate or weather in driving Santa Ana Wind fires","interactions":[],"lastModifiedDate":"2021-07-23T14:36:21.91754","indexId":"70222368","displayToPublicDate":"2021-07-21T09:32:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Ignitions explain more than climate or weather in driving Santa Ana Wind fires","docAbstract":"<p><span>Autumn and winter Santa Ana wind (SAW)–driven wildfires play a substantial role in area burned and societal losses in southern California. Temperature during the event and antecedent precipitation in the week or month prior play a minor role in determining area burned. Burning is dependent on wind intensity and number of human-ignited fires. Over 75% of all SAW events generate no fires; rather, fires during a SAW event are dependent on a fire being ignited. Models explained 40 to 50% of area burned, with number of ignitions being the strongest variable. One hundred percent of SAW fires were human caused, and in the past decade, powerline failures have been the dominant cause. Future fire losses can be reduced by greater emphasis on maintenance of utility lines and attention to planning urban growth in ways that reduce the potential for powerline ignitions.</span></p>","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.abh2262","usgsCitation":"Keeley, J., Guzman-Morales, J., Gershunov, A., Syphard, A.D., Cayan, D., Pierce, D.W., Flannigan, M., and Brown, T.J., 2021, Ignitions explain more than climate or weather in driving Santa Ana Wind fires: Science Advances, v. 7, no. 30, eabh2262, 10 p., https://doi.org/10.1126/sciadv.abh2262.","productDescription":"eabh2262, 10 p.","ipdsId":"IP-126058","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":451452,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1126/sciadv.abh2262","text":"External 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David W","contributorId":261327,"corporation":false,"usgs":false,"family":"Pierce","given":"David","email":"","middleInitial":"W","affiliations":[{"id":52819,"text":"Climate, Atmospheric Science and Physical Oceanography Division, Scripps Institution of Oceanography, University of California, San Diego, San Diego, CA 92093, USA","active":true,"usgs":false}],"preferred":false,"id":819772,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flannigan, Michael","contributorId":261328,"corporation":false,"usgs":false,"family":"Flannigan","given":"Michael","affiliations":[{"id":52822,"text":"Department of Renewable Resources, University of Alberta, Edmonton, Alberta T6G 2H1, Canada","active":true,"usgs":false}],"preferred":false,"id":819773,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brown, Tim J","contributorId":261329,"corporation":false,"usgs":false,"family":"Brown","given":"Tim","email":"","middleInitial":"J","affiliations":[{"id":52823,"text":"Western Regional Climate Center, Desert Research Institute, Reno, NV 89512, USA","active":true,"usgs":false}],"preferred":false,"id":819774,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70223244,"text":"70223244 - 2021 - Benthic and planktonic inorganic nutrient processing rates at the interface between a river and lake","interactions":[],"lastModifiedDate":"2021-08-19T16:50:06.649243","indexId":"70223244","displayToPublicDate":"2021-07-20T11:47:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Benthic and planktonic inorganic nutrient processing rates at the interface between a river and lake","docAbstract":"<p><span>The interface between lotic and lentic ecosystems is often a zone of intense metabolic activity, as primary production in streams and rivers can be light limited whereas nutrients often limit primary production in lake ecosystems. Our objective was to model the influence that rivermouths (the lotic-lentic interface) could have on the loads of soluble reactive phosphorus (SRP) and dissolved inorganic nitrogen (N) passing from the tributary to the nearshore zone of a lake. To achieve this objective, we modeled the combined role of water column nutrient transformation rates with sediment nutrient flux rates. For sensitivity analysis, we picked plausible parameter ranges based on values previously measured in the Fox rivermouth (a tributary to Lake Michigan). Sensitivity analysis of the model demonstrated that overall the importance of water column processing rates increases with increasing nutrient concentration and discharge. We then applied the model to the Fox rivermouth, simulating the change in nutrients on four dates where all of the necessary parameters had been estimated. This modeling suggests that the Fox rivermouth is often a net sink for SRP and source for ammonia (NH</span><sub>4</sub><span>), with water column processing driving SRP removal and both water column and sediment flux driving NH</span><sub>4</sub><span>&nbsp;dynamics. Removal of SRP in the water column means conversion to particulate and/or organic P, and those P pools are generally considered to be less bioavailable than SRP, so it may be that rivermouths disconnect upstream sources of nutrients from nearshore food webs. These results demonstrate that the interface zone between lotic and lentic systems has the potential to substantially alter the load and character of nutrients as river waters pass through rivermouths to adjacent nearshore areas.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s10533-021-00821-8","usgsCitation":"Larson, J.H., Evans, M.A., Fitzpatrick, F., Frost, P., Xenopoulos, M., James, W.F., and Reneau, P., 2021, Benthic and planktonic inorganic nutrient processing rates at the interface between a river and lake: Biogeochemistry, v. 155, p. 189-203, https://doi.org/10.1007/s10533-021-00821-8.","productDescription":"15 p.","startPage":"189","endPage":"203","ipdsId":"IP-118338","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":436267,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PNDSXR","text":"USGS data release","linkHelpText":"Code associated with analysis and modeling of benthic and pelagic inorganic nutrient processing rates at the interface between a river and lake"},{"id":388171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"155","noUsgsAuthors":false,"publicationDate":"2021-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":821513,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":149358,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":821514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209612,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821515,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frost, Paul C.","contributorId":138622,"corporation":false,"usgs":false,"family":"Frost","given":"Paul C.","affiliations":[{"id":12467,"text":"Department of Biology, Trent University, Peterborough, ON  CA","active":true,"usgs":false}],"preferred":false,"id":821516,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xenopoulos, Marguerite A.","contributorId":138623,"corporation":false,"usgs":false,"family":"Xenopoulos","given":"Marguerite A.","affiliations":[{"id":12467,"text":"Department of Biology, Trent University, Peterborough, ON  CA","active":true,"usgs":false}],"preferred":false,"id":821517,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"James, William F.","contributorId":213265,"corporation":false,"usgs":false,"family":"James","given":"William","email":"","middleInitial":"F.","affiliations":[{"id":38729,"text":"University of Wisconsin-Stout","active":true,"usgs":false}],"preferred":false,"id":821518,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reneau, Paul C. 0000-0002-1335-7573","orcid":"https://orcid.org/0000-0002-1335-7573","contributorId":220311,"corporation":false,"usgs":true,"family":"Reneau","given":"Paul C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821519,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70229384,"text":"70229384 - 2021 - Translocation, survival, and recovery of Kansas-banded Canada geese","interactions":[],"lastModifiedDate":"2022-03-04T16:08:57.776602","indexId":"70229384","displayToPublicDate":"2021-07-20T09:52:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Translocation, survival, and recovery of Kansas-banded Canada geese","docAbstract":"<p><span>Temperate-breeding, or resident, Canada geese were once extirpated in Kansas, USA, but currently provide abundant viewing and hunting opportunities. Kansas Department of Wildlife, Parks, and Tourism (KDWPT) began reintroducing geese in 1980 with a goal of re-establishing a breeding population. Successful reintroductions led to translocating flocks to regions with no previous records of nesting geese; however, KDWPT continues to translocate individuals from nuisance flocks in urban areas to rural reservoirs to reduce human conflicts with urban geese. Our goal was to determine the effects of such translocations on survival and recovery of adult, sub-adult, and juvenile temperate-breeding Canada geese. We used Brownie dead-recovery models in Program MARK to compare survival and recovery probabilities between translocated and nontranslocated (normal wild) Kansas-banded Canada geese for 2012–2017. Model-estimated annual survival differed between status (normal wild <i>Ŝ</i></span><span>&nbsp;=&nbsp;0.761, 95% CI 0.734–0.785; translocated <i>Ŝ</i></span><span>&nbsp;=&nbsp;0.598, 95% CI 0.528–0.665). Recovery probability differed between normal and translocated adults (normal wild <i>ḟ</i></span><span>&nbsp;=&nbsp;0.074, 95% CI&nbsp;=&nbsp;0.069–0.078; translocated <i>ḟ</i></span><span>&nbsp;=&nbsp;0.138, 95% CI&nbsp;=&nbsp;0.120–0.158) and juveniles (normal wild <i>ḟ</i></span><span>&nbsp;=&nbsp;0.067, 95% CI&nbsp;=&nbsp;0.059–0.075; translocated <i>ḟ</i></span><span>&nbsp;=&nbsp;0.250, 95% CI&nbsp;=&nbsp;0.199–0.310). Recovery probability did not differ between status in the sub-adult age class (normal wild <i>ḟ</i></span><span>&nbsp;=&nbsp;0.126, 95% CI&nbsp;=&nbsp;0.115–0.137; translocated <i>ḟ</i></span><span>&nbsp;=&nbsp;0.090, 95% CI&nbsp;=&nbsp;0.055–0.144). Translocation is a viable management option to successfully reduce survival and increase recovery probability of urban nuisance geese in Kansas.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.3659","usgsCitation":"Malanchuk, J.B., Ross, B., Haukos, D.A., Bidrowski, T.F., and Schultheis, R., 2021, Translocation, survival, and recovery of Kansas-banded Canada geese: Ecosphere, v. 12, no. 7, p. 1-11, https://doi.org/10.1002/ecs2.3659.","productDescription":"e03659, 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-124602","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":489060,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3659","text":"Publisher Index Page"},{"id":396754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Boomer","contributorId":287969,"corporation":false,"usgs":false,"family":"Malanchuk","given":"J.","email":"","middleInitial":"Boomer","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":837240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ross, Beth 0000-0001-5634-4951 bross@usgs.gov","orcid":"https://orcid.org/0000-0001-5634-4951","contributorId":199242,"corporation":false,"usgs":true,"family":"Ross","given":"Beth","email":"bross@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":837239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":837238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bidrowski, Thomas F.","contributorId":287970,"corporation":false,"usgs":false,"family":"Bidrowski","given":"Thomas","email":"","middleInitial":"F.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":837241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schultheis, Richard","contributorId":287971,"corporation":false,"usgs":false,"family":"Schultheis","given":"Richard","email":"","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":837242,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70259284,"text":"70259284 - 2021 - Hydrothermal alteration can result in pore pressurization and volcano instability","interactions":[],"lastModifiedDate":"2024-10-03T12:20:50.607266","indexId":"70259284","displayToPublicDate":"2021-07-20T07:19:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrothermal alteration can result in pore pressurization and volcano instability","docAbstract":"<div id=\"131449056\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><p>The collapse of a volcanic flank can be destructive and deadly. Hydrothermal alteration is common to volcanoes worldwide and is thought to promote volcano instability by decreasing rock strength. However, some laboratory studies have shown that not all alteration reduces rock strength. Our new laboratory data for altered rhyodacites from Chaos Crags (Lassen volcanic center, California, USA) show that pore- and crack-filling mineral precipitation can reduce porosity and permeability and increase strength, Young's modulus, and cohesion. A significant reduction in permeability, by as much as four orders of magnitude, will inhibit fluid circulation and create zones of high pore fluid pressure. We explored the consequences of pore fluid pressurization on volcano stability using large-scale numerical modeling. Upscaled physical and mechanical properties for hydrothermally altered rocks were used as input parameters in our modeling. Results show that a high-pore-pressure zone within a volcano increases volcano deformation and that increasing the size of this zone increases the observed deformation. Hydrothermal alteration associated with mineral precipitation, and increases to rock strength, can therefore promote pore pressurization and volcano deformation, increasing the likelihood of volcano spreading, flank collapses, and phreatic/phreatomagmatic explosions. We conclude that porosity-decreasing alteration, explored here, and porosity-increasing alteration can both promote volcano instability and collapse, but by different mechanisms. Hydrothermal alteration should therefore be monitored at volcanoes worldwide and incorporated into hazard assessments.</p></div>","language":"English","publisher":"Geological Society of America","doi":"10.1130/G49063.1","usgsCitation":"Heap, M.J., Baumann, T., Gilg, H.A., Kolzenburg, S., Ryan, A., Villeneuve, M.C., Russell, J.K., Kennedy, L.A., Rosas-Carbajal, M., and Clynne, M.A., 2021, Hydrothermal alteration can result in pore pressurization and volcano instability: Geology, v. 49, no. 11, p. 1348-1352, https://doi.org/10.1130/G49063.1.","productDescription":"5 p.","startPage":"1348","endPage":"1352","ipdsId":"IP-127468","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467231,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-03547431","text":"External Repository"},{"id":462527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Heap, Michael J. 0000-0002-4748-735X","orcid":"https://orcid.org/0000-0002-4748-735X","contributorId":297882,"corporation":false,"usgs":false,"family":"Heap","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":64429,"text":"Université de Strasbourg","active":true,"usgs":false}],"preferred":false,"id":914774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baumann, Tobias 0000-0003-4834-8586","orcid":"https://orcid.org/0000-0003-4834-8586","contributorId":344808,"corporation":false,"usgs":false,"family":"Baumann","given":"Tobias","email":"","affiliations":[{"id":64804,"text":"Johannes Gutenberg University","active":true,"usgs":false}],"preferred":false,"id":914775,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilg, H. Albert 0000-0003-4304-9763","orcid":"https://orcid.org/0000-0003-4304-9763","contributorId":344809,"corporation":false,"usgs":false,"family":"Gilg","given":"H.","email":"","middleInitial":"Albert","affiliations":[{"id":82413,"text":"Technical University of Munich","active":true,"usgs":false}],"preferred":false,"id":914776,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolzenburg, Stephan","contributorId":292030,"corporation":false,"usgs":false,"family":"Kolzenburg","given":"Stephan","email":"","affiliations":[{"id":40126,"text":"University of Buffalo","active":true,"usgs":false}],"preferred":false,"id":914777,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ryan, Amy","contributorId":300368,"corporation":false,"usgs":false,"family":"Ryan","given":"Amy","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":914778,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Villeneuve, Marlene C. 0000-0001-6001-0786","orcid":"https://orcid.org/0000-0001-6001-0786","contributorId":300370,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Marlene","email":"","middleInitial":"C.","affiliations":[{"id":65093,"text":"Montanuniversität Leoben","active":true,"usgs":false}],"preferred":false,"id":914779,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Russell, James K. 0000-0002-2062-3155","orcid":"https://orcid.org/0000-0002-2062-3155","contributorId":344810,"corporation":false,"usgs":false,"family":"Russell","given":"James","email":"","middleInitial":"K.","affiliations":[{"id":36972,"text":"University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":914780,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kennedy, Lori A. 0000-0001-5583-1264","orcid":"https://orcid.org/0000-0001-5583-1264","contributorId":344811,"corporation":false,"usgs":false,"family":"Kennedy","given":"Lori","email":"","middleInitial":"A.","affiliations":[{"id":36972,"text":"University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":914781,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rosas-Carbajal, Marina 0000-0002-5393-0389","orcid":"https://orcid.org/0000-0002-5393-0389","contributorId":300367,"corporation":false,"usgs":false,"family":"Rosas-Carbajal","given":"Marina","email":"","affiliations":[{"id":65092,"text":"Université de Paris","active":true,"usgs":false}],"preferred":false,"id":914782,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":914783,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70222411,"text":"70222411 - 2021 - Herring Disease Program - Annual Project Report 2012011-E, February 1, 2010-January 31, 2021","interactions":[],"lastModifiedDate":"2021-07-27T12:20:08.02197","indexId":"70222411","displayToPublicDate":"2021-07-20T07:18:09","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Herring Disease Program - Annual Project Report 2012011-E, February 1, 2010-January 31, 2021","docAbstract":"<p>We will investigate fish health factors that may be contributing to the failed recovery of Pacific herring populations in Prince William Sound. Field samples will provide infection and disease prevalence data from Prince William Sound and Sitka Sound to inform the age structured assessment (ASA) model, serological data will indicate the prior exposure history and future susceptibility of herring to viral hemorrhagic septicemia virus (VHSV), and diet information will provide insights into the unusually high prevalence of Ichthyophonus that occurs in juvenile herring from Cordova Harbor. Laboratory studies will validate the newly developed plaque neutralization assay as a quantifiable measure of herd immunity against VHS, provide further understanding of disease cofactors including salinity, and investigate possible routes of transmission for Ichthyophonus. Information from the field and laboratory studies will be integrated into the current ASA model and inform a novel ASA-type model that is based on the immune status of herring age cohorts.</p>","language":"English","publisher":"Exxon Valdez Oil Spill Trustee Council (EVOSTC)","usgsCitation":"Hershberger, P., and Purcell, M.K., 2021, Herring Disease Program - Annual Project Report 2012011-E, February 1, 2010-January 31, 2021, 26 p.","productDescription":"26 p.","ipdsId":"IP-127098","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":387460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387451,"type":{"id":15,"text":"Index Page"},"url":"https://evostc.state.ak.us/restoration-projects/project-search/hrm-program-herring-disease-program-ii-20120111-e/"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -149.56787109375,\n              59.567723306212955\n            ],\n            [\n              -144.33837890625,\n              59.567723306212955\n            ],\n            [\n              -144.33837890625,\n              61.41775026352097\n            ],\n            [\n              -149.56787109375,\n              61.41775026352097\n            ],\n            [\n              -149.56787109375,\n              59.567723306212955\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hershberger, Paul 0000-0002-2261-7760","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":203322,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819958,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227749,"text":"70227749 - 2021 - Spatial and temporal variation in length-weight relationships of age-0 Scaphirhynchus sturgeon in the lower Missouri River","interactions":[],"lastModifiedDate":"2022-01-28T15:28:49.002502","indexId":"70227749","displayToPublicDate":"2021-07-19T09:05:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":737,"text":"American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal variation in length-weight relationships of age-0 Scaphirhynchus sturgeon in the lower Missouri River","docAbstract":"<p>Length-weight relationships can be useful tools for assessing fish condition. We developed these equations (W =<span>&nbsp;</span><i>a</i>L<i><sup>b</sup></i>) for wild-caught age-0 (4.1–12.0 cm)<span>&nbsp;</span><i>Scaphirhynchus</i><span>&nbsp;</span>sturgeon from eight reaches spanning over 750 river km of the lower Missouri River from 2014 to 2017. We used nonlinear modeling to estimate the constant (<i>a</i>) and exponent (<i>b</i>) of the LW equation for each reach to assess potential spatial differences. We also assessed long-term temporal effects by estimating these parameters by year at Lexington reach, which is located in the middle of our sampling area and was the only reach sampled all 4 y. Constant and exponent estimates from linearized regressions varied by reach and were inversely related during the spatial analyses. Similarly, parameter estimates were also inversely related and varied among years during the temporal analysis at Lexington. To account for the relationship between constant and exponent values, we used predicted weights at 2 cm increments (4.1–12.0 cm) for the spatial analysis (by reach) and for the temporal analysis (by year). During the 2014 and 2015 spatial analyses, weights varied by size but were usually higher in Lexington and Glasgow, which were the furthest upstream reaches sampled during those years. During 2016 and 2017, Lexington was the furthest downstream reach sampled but did not consistently yield relatively high predicted weights. Temporal analysis at Lexington yielded higher predicted weights for 2014–2015 compared to 2016–2017 for higher size categories (10- and 12-cm). In general our results suggest differences in body condition among reaches and years in the lower Missouri River. Further research is needed to identify the specific mechanisms driving spatial and temporal L-W relationship differences observed and to determine if differences in predicted body conditions affect long-term survival and recruitment of age-0<span>&nbsp;</span><i>Scaphirhynchus</i><span>&nbsp;</span>sturgeon. Currently, factors influencing age-0<span>&nbsp;</span><i>Scaphirhynchus</i><span>&nbsp;</span>sturgeon condition and growth are unknown and this work serves to highlight knowledge gaps regarding factors influencing<span>&nbsp;</span><i>Scaphirhynchus</i><span>&nbsp;</span>sturgeon recruitment.</p>","language":"English","publisher":"University of Notre Dame","doi":"10.1674/0003-0031-186.1.106","usgsCitation":"Gonzalez, A., Long, J.M., Gosch, N.J., Civiello, A., Gemeinhardt, T., and Hall, J.R., 2021, Spatial and temporal variation in length-weight relationships of age-0 Scaphirhynchus sturgeon in the lower Missouri River: American Midland Naturalist, v. 186, no. 1, p. 106-121, https://doi.org/10.1674/0003-0031-186.1.106.","productDescription":"17 p.","startPage":"106","endPage":"121","ipdsId":"IP-108837","costCenters":[{"id":198,"text":"Coop Res Unit 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University","active":true,"usgs":false}],"preferred":false,"id":832028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gosch, N. J. C.","contributorId":272518,"corporation":false,"usgs":false,"family":"Gosch","given":"N.","email":"","middleInitial":"J. C.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":832030,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Civiello, A. P.","contributorId":272519,"corporation":false,"usgs":false,"family":"Civiello","given":"A. P.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":832031,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gemeinhardt, T.R.","contributorId":272520,"corporation":false,"usgs":false,"family":"Gemeinhardt","given":"T.R.","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":832032,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hall, J. R.","contributorId":272561,"corporation":false,"usgs":false,"family":"Hall","given":"J.","email":"","middleInitial":"R.","affiliations":[{"id":17640,"text":"Nebraska Game and Parks Commission","active":true,"usgs":false}],"preferred":false,"id":832141,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70222350,"text":"70222350 - 2021 - Model estimated baseflow for streams with endangered Atlantic Salmon in Maine, USA","interactions":[],"lastModifiedDate":"2021-11-16T15:32:29.208233","indexId":"70222350","displayToPublicDate":"2021-07-18T09:08:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Model estimated baseflow for streams with endangered Atlantic Salmon in Maine, USA","docAbstract":"<p><span>We present a regression model for estimating mean August baseflow per square kilometer of drainage area to help resource managers assess relative amounts of baseflow in Maine streams with Atlantic Salmon habitat. The model was derived from mean August baseflows computed at 31 USGS streamflow gages in Maine. We use an ordinary least squares regression model to estimate mean August baseflow per unit drainage area from two explanatory variables: percentage of the basin underlain by sand and gravel aquifers and mean July precipitation in the basin. This model provides the ability to estimate mean August baseflow in cubic meters per second per square kilometer of basin area on user-selected, ungaged sites throughout Maine south of 46° 21′55″ N latitude. The model has an adjusted R</span><sup>2</sup><span>&nbsp;of 0.78 and a mean 95% prediction interval of plus or minus 0.002 cubic meters per second per square kilometer. A map of the Narraguagus watershed in eastern coastal Maine shows reaches color coded by relative amounts of baseflow predicted by the model as an example of how this method could be applied throughout Maine. The map can be used to identify reaches with relatively higher amounts of baseflow during summer low flows for habitat conservation and restoration work. These areas have the potential to be high-quality habitat for Atlantic salmon and other cold-water fish because baseflows are known to moderate stream temperatures in summer low-flow periods.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/rra.3835","usgsCitation":"Lombard, P.J., Dudley, R., Collins, M.J., Saunders, R., and Atkinson, E., 2021, Model estimated baseflow for streams with endangered Atlantic Salmon in Maine, USA: River Research and Applications, v. 37, no. 9, p. 1254-1264, https://doi.org/10.1002/rra.3835.","productDescription":"11 p.","startPage":"1254","endPage":"1264","ipdsId":"IP-124443","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":451480,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.3835","text":"Publisher Index Page"},{"id":436271,"rank":0,"type":{"id":30,"text":"Data 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 \"}}]}","volume":"37","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":203509,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819723,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dudley, Robert W. 0000-0002-0934-0568","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":220211,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, Matthias J. 0000-0003-4238-2038","orcid":"https://orcid.org/0000-0003-4238-2038","contributorId":196365,"corporation":false,"usgs":false,"family":"Collins","given":"Matthias","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":819725,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saunders, Rory","contributorId":261311,"corporation":false,"usgs":false,"family":"Saunders","given":"Rory","email":"","affiliations":[{"id":52809,"text":"NOAA, National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":819726,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atkinson, Ernie","contributorId":261312,"corporation":false,"usgs":false,"family":"Atkinson","given":"Ernie","email":"","affiliations":[{"id":52810,"text":"Maine Department of Marine Resources, Division of Sea-run Fisheries","active":true,"usgs":false}],"preferred":false,"id":819727,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70222389,"text":"70222389 - 2021 - Multicriteria decisions and portfolio analysis: Land acquisition for biological and social objectives","interactions":[],"lastModifiedDate":"2021-10-06T15:35:26.925959","indexId":"70222389","displayToPublicDate":"2021-07-18T07:22:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Multicriteria decisions and portfolio analysis: Land acquisition for biological and social objectives","docAbstract":"<p><span>Resource allocation for land acquisition is a common multi-objective problem that involves complex trade-offs. The National Wildlife Refuge System (NWRS) of the U.S. Fish and Wildlife Service currently uses the Targeted Resource Acquisition Comparison Tool (TRACT) to allocate funds from the Migratory Bird Conservation Fund (MBCF; established through the Migratory Bird Hunting and Conservation Act of 1934) for land acquisition based on cost-benefit analysis, regional priority rankings of candidate land parcels available for acquisition, and the overall biological contribution to duck population objectives. However, current policy encourages decision makers to consider societal and economic benefits of lands acquired, in addition to their biological benefits to waterfowl. These decisions about portfolio elements (i.e. individual land parcels) require an analysis of the difficult trade-offs among multiple objectives. In the last decade the application of multi-criteria decision analysis (MCDA) methods has been instrumental in aiding decision makers with complex multi-objective decisions. In this study, we present an alternative approach to developing land acquisition portfolios using MCDA and Modern Portfolio Theory (MPT). We describe the development of a portfolio decision analysis tool using constrained optimization for land acquisition decisions by the NWRS. We outline the decision framework, describe development of the prototype tool in Microsoft Excel, and test the results of the tool using land parcels submitted as candidates for MBCF funding in 2019. Our results indicate that the constrained optimization outperformed the traditional TRACT method and ad hoc portfolios developed using current NWRS criteria.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2420","usgsCitation":"Krainyk, A., Lyons, J., Rice, M.B., Fowler, K., Soulliere, G.J., Brasher, M.G., Humburg, D.D., and Coluccy, J.M., 2021, Multicriteria decisions and portfolio analysis: Land acquisition for biological and social objectives: Ecological Applications, v. 31, no. 2, e02420, 46 p., https://doi.org/10.1002/eap.2420.","productDescription":"e02420, 46 p.","ipdsId":"IP-108367","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":387464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-08-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Krainyk, Anastasia Ihorvina 0000-0002-3100-9011","orcid":"https://orcid.org/0000-0002-3100-9011","contributorId":261353,"corporation":false,"usgs":true,"family":"Krainyk","given":"Anastasia Ihorvina","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819915,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":261354,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819916,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rice, Mindy B.","contributorId":214399,"corporation":false,"usgs":false,"family":"Rice","given":"Mindy","email":"","middleInitial":"B.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":819917,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fowler, Kenneth A.","contributorId":261355,"corporation":false,"usgs":false,"family":"Fowler","given":"Kenneth A.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":819918,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soulliere, Gregory J.","contributorId":172329,"corporation":false,"usgs":false,"family":"Soulliere","given":"Gregory","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":819919,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brasher, Michael G.","contributorId":214393,"corporation":false,"usgs":false,"family":"Brasher","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":36215,"text":"Ducks Unlimited","active":true,"usgs":false}],"preferred":false,"id":819920,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Humburg, Dale D.","contributorId":79357,"corporation":false,"usgs":false,"family":"Humburg","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":13073,"text":"Ducks Unlimited, Inc.","active":true,"usgs":false}],"preferred":false,"id":819921,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coluccy, John M.","contributorId":214395,"corporation":false,"usgs":false,"family":"Coluccy","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":36215,"text":"Ducks Unlimited","active":true,"usgs":false}],"preferred":false,"id":819922,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70222346,"text":"70222346 - 2021 - The Chesapeake Bay program modeling system: Overview and recommendations for future development","interactions":[],"lastModifiedDate":"2021-07-22T14:30:50.592821","indexId":"70222346","displayToPublicDate":"2021-07-17T09:14:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"The Chesapeake Bay program modeling system: Overview and recommendations for future development","docAbstract":"<p><span>The Chesapeake Bay is the largest, most productive, and most biologically diverse estuary in the continental United States providing crucial habitat and natural resources for culturally and economically important species. Pressures from human population growth and associated development and agricultural intensification have led to excessive nutrient and sediment inputs entering the Bay, negatively affecting the health of the Bay ecosystem and the economic services it provides. The Chesapeake Bay Program (CBP) is a unique program formally created in 1983 as a multi-stakeholder partnership to guide and foster restoration of the Chesapeake Bay and its watershed. Since its inception, the CBP Partnership has been developing, updating, and applying a complex linked modeling system of watershed, airshed, and estuary models as a planning tool to inform strategic management decisions and Bay restoration efforts. This paper provides a description of the 2017 CBP Modeling System and the higher trophic level models developed by the NOAA Chesapeake Bay Office, along with specific recommendations that emerged from a 2018 workshop designed to inform future model development. Recommendations highlight the need for simulation of watershed inputs, conditions, processes, and practices at higher resolution to provide improved information to guide local nutrient and sediment management plans. More explicit and extensive modeling of connectivity between watershed landforms and estuary sub-areas, estuarine hydrodynamics, watershed and estuarine water quality, the estuarine-watershed socioecological system, and living resources will be important to broaden and improve characterization of responses to targeted nutrient and sediment load reductions. Finally, the value and importance of maintaining effective collaborations among jurisdictional managers, scientists, modelers, support staff, and stakeholder communities is emphasized. An open collaborative and transparent process has been a key element of successes to date and is vitally important as the CBP Partnership moves forward with modeling system improvements that help stakeholders evolve new knowledge, improve management strategies, and better communicate outcomes.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2021.109635","usgsCitation":"Hood, R., Shenk, G.W., Dixon, R.L., Smith, S.M., Ball, W.P., Bash, J., Batiuk, R., Boomer, K., Brady, D.C., Cerco, C., Claggett, P., de Mutsert, K., Easton, Z.M., Elmore, A., Friedrichs, M.A., Harris, L.A., Ihde, T.F., Lacher, I., Li, L., Linker, L.C., Miller, A., Moriarty, J., Noe, G.E., Onyullo, G., Rose, K.A., Skalak, K., Tian, R., Veith, T.L., Wainger, L.A., Weller, D.E., and Zhang, Y.J., 2021, The Chesapeake Bay program modeling system: Overview and recommendations for future development: Ecological Modelling, v. 456, 109635, 28 p., 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We describe mathematical characteristics of CAST and develop a constrained nonlinear BMP-subset model, software, and visualization framework. This represents the first publicly available optimization framework for exploring least-cost strategies of&nbsp;pollutant load&nbsp;control for the United States' largest&nbsp;</span>estuary<span>. The optimization identifies implementation options for a BMP subset modeled with load reduction effectiveness factors, and the web interface facilitates interactive exploration of &gt;30,000 solutions organized by objective, nutrient control level, and for ~200 counties. We assess framework performance and demonstrate modeled cost improvements when comparing optimization-suggested proposals with proposals inspired by jurisdiction plans. Stakeholder feedback highlights the framework's current utility for investigating cost-effective&nbsp;tradeoffs&nbsp;and its usefulness as a foundation for future analysis of restoration strategies.</span></p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2021.105141","usgsCitation":"Kaufman, D.E., Shenk, G.W., Bhatt, G., Asplen, K., Devereux, O., Rigelman, J., Ellis, J.H., Hobbs, B.F., Bosch, D.J., Van Houtven, G.L., McGarity, A.E., Linker, L.C., and Ball, W.P., 2021, Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework: Environmental Modelling & Software, v. 144, 105141, 18 p., https://doi.org/10.1016/j.envsoft.2021.105141.","productDescription":"105141, 18 p.","ipdsId":"IP-128779","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":451489,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Hugh","contributorId":267329,"corporation":false,"usgs":false,"family":"Ellis","given":"J.","email":"","middleInitial":"Hugh","affiliations":[],"preferred":false,"id":824980,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hobbs, Benjamin F 0000-0003-1783-3597","orcid":"https://orcid.org/0000-0003-1783-3597","contributorId":267323,"corporation":false,"usgs":false,"family":"Hobbs","given":"Benjamin","email":"","middleInitial":"F","affiliations":[{"id":36717,"text":"Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":824981,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bosch, Darrell J 0000-0002-7758-4935","orcid":"https://orcid.org/0000-0002-7758-4935","contributorId":267324,"corporation":false,"usgs":false,"family":"Bosch","given":"Darrell","email":"","middleInitial":"J","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":824995,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Van Houtven, George L 0000-0001-6141-7318","orcid":"https://orcid.org/0000-0001-6141-7318","contributorId":267325,"corporation":false,"usgs":false,"family":"Van Houtven","given":"George","email":"","middleInitial":"L","affiliations":[{"id":7151,"text":"RTI International","active":true,"usgs":false}],"preferred":false,"id":824982,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McGarity, Arthur E 0000-0003-3579-5088","orcid":"https://orcid.org/0000-0003-3579-5088","contributorId":267326,"corporation":false,"usgs":false,"family":"McGarity","given":"Arthur","email":"","middleInitial":"E","affiliations":[{"id":55474,"text":"Swarthmore College","active":true,"usgs":false}],"preferred":false,"id":824983,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Linker, Lewis C. 0000-0002-3456-3659","orcid":"https://orcid.org/0000-0002-3456-3659","contributorId":252964,"corporation":false,"usgs":false,"family":"Linker","given":"Lewis","email":"","middleInitial":"C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":824984,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ball, William P.","contributorId":174394,"corporation":false,"usgs":false,"family":"Ball","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":27446,"text":"Johns Hopkins University, Department of Geography and Environmental Engineering","active":true,"usgs":false}],"preferred":false,"id":824985,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70221832,"text":"sir20205080 - 2021 - Simulation of water-table response to sea-level rise and change in recharge, Sandy Hook unit, Gateway National Recreation Area, New Jersey","interactions":[],"lastModifiedDate":"2021-07-19T11:54:16.429643","indexId":"sir20205080","displayToPublicDate":"2021-07-16T15:00:00","publicationYear":"2021","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":"2020-5080","displayTitle":"Simulation of Water-Table Response to Sea-Level Rise and Change in Recharge, Sandy Hook Unit, Gateway National Recreation Area, New Jersey","title":"Simulation of water-table response to sea-level rise and change in recharge, Sandy Hook unit, Gateway National Recreation Area, New Jersey","docAbstract":"<p>The Sandy Hook Unit, Gateway National Recreation Area (hereafter Sandy Hook) in New Jersey is a 10-kilometer-long spit visited by thousands of people each year who take advantage of the historical and natural resources and recreational opportunities. The historical and natural resources are threatened by global climate change, including sea-level rise (SLR), changes in precipitation and groundwater recharge, and changes in the frequency and severity of coastal storms. Fresh groundwater resources are important to the ecosystems of Sandy Hook. The Bayside Holly Forest, one of only two known old-growth American holly (<i>Ilex opaca</i>) maritime forests, is particularly vulnerable to global climate change because of the proximity of the water table to land surface in low-lying areas and the potential for saltwater intrusion and inundation.</p><p>The shallow groundwater-flow system on Sandy Hook is dominated by recharge from precipitation, fresh groundwater discharge to evapotranspiration (ET), discharge to surface seeps, and submarine groundwater discharge (groundwater discharging directly to the ocean). A three-dimensional groundwater-flow model that simulates the shallow groundwater-flow system and interaction with surrounding saltwater boundaries was constructed to simulate multi-density groundwater flow, treating the freshwater/saltwater transition zone as a sharp interface that represents the half-seawater surface.</p><p>Groundwater-flow simulations completed for this study include a Baseline scenario, three SLR scenarios (0.2, 0.4, and 0.6 meter [m]), two Recharge scenarios—a 10-percent Increased Recharge scenario and a 10-percent Decreased Recharge scenario—and a scenario with 0.6 m of SLR and 10-percent increase in recharge. The Recharge scenarios indicate the system is not sensitive to a 10-percent increase or decrease in recharge from the Baseline scenario. In the SLR scenarios, SLR causes the water table to rise, resulting in increased fresh groundwater discharge to ET and seeps, and reduced submarine discharge compared to the Baseline scenario. The increased discharge to ET and seeps causes the magnitude of water-table rise to be less than that of SLR, which in turn causes the thickness of the freshwater lens to thin, reducing the depth to the half-seawater surface. Water-table rise associated with SLR diminishes the thickness of the unsaturated zone; comparing the Baseline and the 0.6-m SLR scenarios, the area where the simulated water table is above land surface increases by 50.6 hectares, from about 0.9 to 7.4 percent of the land area of Sandy Hook. Areas where the simulated water table is above land surface are likely to be emergent wetlands and contain freshwater if they are tens of meters or more from the shoreline. The steady-state simulations indicate that the percentage of land where the half-seawater surface is less than 9 m below the water table increases from about 2.5 percent (20 hectares) to about 9 percent (74 hectares) with 0.6 m of SLR. In low-lying areas close to the Sandy Hook Bay shoreline, the half-seawater surface is simulated to be as much as 20 m closer to the water table with SLR of 0.6 m. Transient salinization, if any, of shallow groundwater from increased frequency or severity of storm-driven inundation is not included in the analysis.</p><p>Natural resources on Sandy Hook, particularly the Bayside Holly Forest, may be adversely affected by the rising water table associated with SLR. Freshwater emergent wetlands may increase in area at the expense of other ecosystem assemblages occurring in or on the edges of low-lying enclosed depressions. Cultural resources close to the water table, such as existing basements of structures, may be adversely affected.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205080","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Carleton, G.B., Charles, E.G., Fiore, A.R., and Winston, R.B., 2021, Simulation of water-table response to sea-level rise and change in recharge, Sandy Hook unit, Gateway National Recreation Area, New Jersey: U.S. Geological Survey Scientific Investigations Report 2020–5080, 91 p., https://doi.org/10.3133/sir20205080.","productDescription":"Report: ix, 91 p.; Data Release","numberOfPages":"91","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081081","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":387036,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205117","text":"Scientific Investigations Report 2020–5117","linkHelpText":"- Simulation of Water-Table and Freshwater/Saltwater Interface Response to Climate-Change-Driven Sea-Level Rise and Changes in Recharge at Fire Island National Seashore, New York"},{"id":387037,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205104","text":"Scientific Investigations Report 2020–5104","linkHelpText":"- Simulated Effects of Sea-Level Rise on the Shallow, Fresh Groundwater System of Assateague Island, Maryland and Virginia"},{"id":387032,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BP018M","text":"USGS data release","linkHelpText":"MODFLOW-2005 with SWI2 used to evaluate the water-table response to sea-level rise and change in recharge, Sandy Hook Unit, Gateway National Recreation Area, New Jersey"},{"id":387033,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5080/coverthb.jpg"},{"id":387034,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5080/sir20205080.pdf","text":"Report","size":"19.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5080"}],"country":"United States","state":"New Jersey","otherGeospatial":"Gateway National Recreation Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.04716491699219,\n              40.39467254512293\n            ],\n            [\n              -73.95927429199219,\n              40.39467254512293\n            ],\n            [\n              -73.95927429199219,\n              40.49239284038429\n            ],\n            [\n              -74.04716491699219,\n              40.49239284038429\n            ],\n            [\n              -74.04716491699219,\n              40.39467254512293\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_nj@usgs.gov\" data-mce-href=\"mailto:dc_nj@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/nj-water\" data-mce-href=\"https://www.usgs.gov/centers/nj-water\">New Jersey Water Science Center</a><br>U.S. Geological Survey<br>3450 Princeton Pike<br>Lawrenceville, NJ 08648</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Hydrogeologic Framework</li><li>Simulated Effects of Sea-Level Rise and Changes in Recharge on Groundwater Flow on Sandy Hook</li><li>Summary and Conclusions</li><li>References Cited</li><li>Appendix 1. Wells, Coreholes, and Geophysical Logs</li><li>Appendix 2. Specific Conductance and Water-Level Data</li><li>Appendix 3. Groundwater-Flow Model Design and Calibration</li><li>Appendix 4. SWI Observation Extractor</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2021-07-16","noUsgsAuthors":false,"publicationDate":"2021-07-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Carleton, Glen B. 0000-0002-7666-4407 carleton@usgs.gov","orcid":"https://orcid.org/0000-0002-7666-4407","contributorId":3795,"corporation":false,"usgs":true,"family":"Carleton","given":"Glen","email":"carleton@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":true,"id":818870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Charles, Emmanuel G. 0000-0002-3338-4958 echarles@usgs.gov","orcid":"https://orcid.org/0000-0002-3338-4958","contributorId":4280,"corporation":false,"usgs":true,"family":"Charles","given":"Emmanuel","email":"echarles@usgs.gov","middleInitial":"G.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fiore, Alex R. 0000-0002-0986-5225 afiore@usgs.gov","orcid":"https://orcid.org/0000-0002-0986-5225","contributorId":4977,"corporation":false,"usgs":true,"family":"Fiore","given":"Alex","email":"afiore@usgs.gov","middleInitial":"R.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818872,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winston, Richard B. 0000-0002-6287-8834 rbwinst@usgs.gov","orcid":"https://orcid.org/0000-0002-6287-8834","contributorId":3567,"corporation":false,"usgs":true,"family":"Winston","given":"Richard","email":"rbwinst@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":818873,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70221830,"text":"sir20205117 - 2021 - Simulation of water-table and freshwater/saltwater interface response to climate-change-driven sea-level rise and changes in recharge at Fire Island National Seashore, New York","interactions":[],"lastModifiedDate":"2021-07-20T11:37:26.378841","indexId":"sir20205117","displayToPublicDate":"2021-07-16T15:00:00","publicationYear":"2021","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":"2020-5117","displayTitle":"Simulation of Water-Table and Freshwater/Saltwater Interface Response to Climate-Change-Driven Sea-Level Rise and Changes in Recharge at Fire Island National Seashore, New York","title":"Simulation of water-table and freshwater/saltwater interface response to climate-change-driven sea-level rise and changes in recharge at Fire Island National Seashore, New York","docAbstract":"<p>The fresh groundwater system at Fire Island National Seashore in New York is one of the natural resources that is most vulnerable to climate change; the various federally listed threatened or endangered species that live on Fire Island, including the piping plover, roseate tern shorebird, and seabeach amaranth may be affected by changes in the groundwater system. The U.S. Geological Survey, in cooperation with the National Park Service, developed a three-dimensional groundwater-flow model to simulate climate-change-related changes in depth to the water table and depth to freshwater/saltwater interfaces on Fire Island. An existing SEAWAT three-dimensional variable-density groundwater flow and transport model was converted to a MODFLOW–NWT three-dimensional finite-difference groundwater model with the Seawater Intrusion (SWI2) package and recalibrated using the UCODE_2005 automatic calibration software. The simulated groundwater divide was found to be skewed strongly toward the ocean shore in response to the modeled wave setup and tidal pumping overheight.</p><p>Effects of climate change include sea-level rise and changes in groundwater recharge rates. Sea-level rise scenarios included specified uniform steady states at 0.2-, 0.4-, and 0.6-meter increases above the 2015 level, applied to the existing topography. A high-recharge scenario was created by increasing 2015 recharge rates by 10 percent. Under all scenarios except the low-recharge scenario, the depth to the water table and the thickness of the unsaturated zone decreased. The thickness of the freshwater lens decreased under every scenario. Resulting maps were generated on a 25-meter grid and indicate changes in areas where natural resources may be vulnerable because of projected climate changes.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205117","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Misut, P.E., and Dressler, S., 2021, Simulation of water-table and freshwater/saltwater interface response to climate-change-driven sea-level rise and changes in recharge at Fire Island National Seashore, New York: U.S. Geological Survey Scientific Investigations Report 2020–5117, 47 p., https://doi.org/10.3133/sir20205117.","productDescription":"Report: vii, 47 p.; Data Release","numberOfPages":"47","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-082635","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":387031,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95TBIMW","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to simulate water-table and freshwater/saltwater interface response to climate-change-driven sea-level rise and changes in recharge at the Fire Island National Seashore, New York"},{"id":387039,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205104","text":"Scientific Investigations Report 2020–5104","linkHelpText":"- Simulated Effects of Sea-Level Rise on the Shallow, Fresh Groundwater System of Assateague Island, Maryland and Virginia"},{"id":387038,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205080","text":"Scientific Investigations Report 2020–5080","linkHelpText":"- Simulation of Water-Table Response to Sea-Level Rise and Change in Recharge, Sandy Hook Unit, Gateway National Recreation Area, New Jersey"},{"id":387030,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5117/sir20205117.pdf","text":"Report","size":"21.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5117"},{"id":387029,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5117/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island National Seashore","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.31314086914062,\n              40.614994915836924\n            ],\n            [\n              -73.2513427734375,\n              40.612909950230936\n            ],\n            [\n              -73.06869506835938,\n              40.65563874006118\n            ],\n            [\n              -72.84072875976562,\n              40.730608477796636\n            ],\n            [\n              -72.75146484374999,\n              40.763901280945866\n            ],\n            [\n              -72.76931762695312,\n              40.77534183237267\n            ],\n            [\n              -72.83798217773438,\n              40.74725696280421\n            ],\n            [\n              -72.96157836914061,\n              40.72228267283148\n            ],\n            [\n              -73.08792114257812,\n              40.66918118282895\n            ],\n            [\n              -73.2403564453125,\n              40.637925243274374\n            ],\n            [\n              -73.30215454101562,\n              40.63375667842965\n            ],\n            [\n              -73.32687377929688,\n              40.62020704520565\n            ],\n            [\n              -73.31314086914062,\n              40.614994915836924\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ny@usgs.gov\" data-mce-href=\"mailto:dc_ny@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/ny-water\" data-mce-href=\"https://www.usgs.gov/centers/ny-water\">New York Water Science Center</a><br>U.S. Geological Survey<br>425 Jordan Road<br>Troy, NY 12180–8349</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Hydrogeologic Framework</li><li>Results of Shallow Groundwater Flow System Simulations of Fire Island</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Groundwater-Flow Model Design and Calibration</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2021-07-16","noUsgsAuthors":false,"publicationDate":"2021-07-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Misut, Paul E. 0000-0002-6502-5255 pemisut@usgs.gov","orcid":"https://orcid.org/0000-0002-6502-5255","contributorId":1073,"corporation":false,"usgs":true,"family":"Misut","given":"Paul","email":"pemisut@usgs.gov","middleInitial":"E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dressler, Sarken","contributorId":244619,"corporation":false,"usgs":false,"family":"Dressler","given":"Sarken","email":"","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":true,"id":818861,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70223280,"text":"70223280 - 2021 - Global-scale changes to extreme ocean wave events due to anthropogenic warming","interactions":[],"lastModifiedDate":"2021-08-19T15:19:20.697385","indexId":"70223280","displayToPublicDate":"2021-07-16T10:14:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Global-scale changes to extreme ocean wave events due to anthropogenic warming","docAbstract":"<p><span>Extreme surface ocean waves are often primary drivers of coastal flooding and erosion over various time scales. Hence, understanding future changes in extreme wave events owing to global warming is of socio-economic and environmental significance. However, our current knowledge of potential changes in high-frequency (defined here as having return periods of less than 1 year) extreme wave events are largely unknown, despite being strongly linked to coastal hazards across time scales relevant to coastal management. Here, we present global climate-modeling evidence, based on the most comprehensive multi-method, multi-model wave ensemble, of projected changes in a core set of extreme wave indices describing high-frequency, extra-tropical storm-driven waves. We find changes in high-frequency extreme wave events of up to ∼50%–100% under RCP8.5 high-emission scenario; which is nearly double the expected changes for RCP4.5 scenario, when globally integrated. The projected changes exhibit strong inter-hemispheric asymmetry, with strong increases in extreme wave activity across the tropics and high latitudes of the Southern Hemisphere region, and a widespread decrease across most of the Northern Hemisphere. We find that the patterns of projected increase across these extreme wave events over the Southern Hemisphere region resemble their historical response to the positive anomaly of the Southern Annular Mode. Our findings highlight that many countries with low-adaptive capacity are likely to face increasing exposure to much more frequent extreme wave events in the future.</span></p>","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ac1013","usgsCitation":"Morim, J., Vitousek, S., Hemer, M., Reguero, B., Erikson, L.H., Casas-Prat, M., Wang, X.L., Semedo, A., Mori, N., Shimura, T., Mentaschi, L., and Timmerman, B., 2021, Global-scale changes to extreme ocean wave events due to anthropogenic warming: Environmental Research Letters, v. 16, no. 7, 074056, 10 p., https://doi.org/10.1088/1748-9326/ac1013.","productDescription":"074056, 10 p.","ipdsId":"IP-116482","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451497,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ac1013","text":"Publisher Index Page"},{"id":388151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Morim, Joao","contributorId":264483,"corporation":false,"usgs":false,"family":"Morim","given":"Joao","email":"","affiliations":[{"id":7117,"text":"Griffith University","active":true,"usgs":false}],"preferred":false,"id":821581,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":821582,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hemer, Mark","contributorId":264484,"corporation":false,"usgs":false,"family":"Hemer","given":"Mark","email":"","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":821583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reguero, Borja","contributorId":264485,"corporation":false,"usgs":false,"family":"Reguero","given":"Borja","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":821584,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":821585,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casas-Prat, Merce","contributorId":264487,"corporation":false,"usgs":false,"family":"Casas-Prat","given":"Merce","email":"","affiliations":[{"id":54478,"text":"Environment and Climate Change Canada,","active":true,"usgs":false}],"preferred":false,"id":821586,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, Xiaolan L.","contributorId":264488,"corporation":false,"usgs":false,"family":"Wang","given":"Xiaolan","email":"","middleInitial":"L.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":821587,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Semedo, Alvaro","contributorId":264491,"corporation":false,"usgs":false,"family":"Semedo","given":"Alvaro","affiliations":[{"id":54479,"text":"IHE-Delft","active":true,"usgs":false}],"preferred":false,"id":821588,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mori, Nobuhito","contributorId":264492,"corporation":false,"usgs":false,"family":"Mori","given":"Nobuhito","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":821589,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shimura, Tomoya","contributorId":264493,"corporation":false,"usgs":false,"family":"Shimura","given":"Tomoya","email":"","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":821590,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mentaschi, Lorenzo","contributorId":264494,"corporation":false,"usgs":false,"family":"Mentaschi","given":"Lorenzo","email":"","affiliations":[{"id":54481,"text":"European Commission","active":true,"usgs":false}],"preferred":false,"id":821591,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Timmerman, Ben","contributorId":264495,"corporation":false,"usgs":false,"family":"Timmerman","given":"Ben","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":821592,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70222933,"text":"70222933 - 2021 - Regeneration trends along climate gradients in Taxodium distichum forests of the southeastern United States","interactions":[],"lastModifiedDate":"2023-06-09T14:09:27.431715","indexId":"70222933","displayToPublicDate":"2021-07-16T09:23:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Regeneration trends along climate gradients in <i>Taxodium distichum</i> forests of the southeastern United States","title":"Regeneration trends along climate gradients in Taxodium distichum forests of the southeastern United States","docAbstract":"<p><span>The development of relict vegetation at the edges of some ecosystems has taken place particularly in environments where the regeneration of foundational species is declining. As an important stage of regeneration in the&nbsp;</span><i>Taxodium distichum</i><span>, this study explored the relationship of cone volume and seed number across environmental gradients in the Mississippi River Alluvial Valley (MRAV) and northern Gulf of Mexico Coast (GOM) in a long-term network of forested wetlands (North American Baldcypress Swamp Network (NABCSN)) from 2007 to 2019. Resembling spheroids, the volumes of&nbsp;</span><i>Taxodium distichum</i><span>&nbsp;cones were based on the measured dimensions of the cones collected in swamps across southeastern environmental gradients. Cones with larger volumes also had larger numbers of seeds (r</span><sup>2</sup><span>&nbsp;=&nbsp;0.423, F&nbsp;=&nbsp;113.9, p&nbsp;&lt;&nbsp;0.0001; Linear regression equation: Seed number per cone&nbsp;=&nbsp;9.8925223&nbsp;+&nbsp;0.8854056* Cone volume cm</span><sup>3</sup><span>). Mean cone volumes were related to water availability with highest volumes in locations with moderate amounts of total annual precipitation (e.g., White River National Wildlife Refuge (NWR) Arkansas, Tensas NWR Louisiana, and Morgan Brake NWR Mississippi), and longer periods of annual percent time of site drawdown. Cone volume was high in 2018 following the 2017 mega-flood in the Mississippi River Alluvial Valley (MRAV) generated by Hurricane Harvey. Mean annual air temperature was not related to cone volume. Along the Gulf Coast, mean cone volume increased from east to west from Florida to Texas. Especially near the edge of the range of&nbsp;</span><i>T. distichum</i><span>&nbsp;forests, smaller cones may be related to regeneration failure and lower seed numbers to support regeneration. A better understanding of regeneration constraints can inform managers of the emergence of relict status in these forests.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2021.119485","usgsCitation":"Middleton, B., Lei, T., Villegas, O., and Liu, X., 2021, Regeneration trends along climate gradients in Taxodium distichum forests of the southeastern United States: Forest Ecology and Management, v. 497, 119485, 10 p.; Data Release, https://doi.org/10.1016/j.foreco.2021.119485.","productDescription":"119485, 10 p.; Data Release","ipdsId":"IP-125636","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":387812,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417855,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H7WGM5"}],"country":"United States","state":"Arkansas, Florida, Illinois, Kentucky, Louisiana, Mississippi, Missouri, Tennessee","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.76953125,\n              37.43997405227057\n            ],\n            [\n              -89.9560546875,\n              37.26530995561875\n            ],\n            [\n              -91.4501953125,\n              33.8339199536547\n            ],\n            [\n              -91.62597656249999,\n              31.765537409484374\n            ],\n            [\n              -91.8896484375,\n              30.44867367928756\n            ],\n            [\n              -90.087890625,\n              29.19053283229458\n            ],\n            [\n              -89.384765625,\n              30.06909396443887\n            ],\n            [\n              -90.4833984375,\n              30.44867367928756\n            ],\n            [\n              -89.3408203125,\n              32.84267363195431\n            ],\n            [\n              -88.76953125,\n              37.43997405227057\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.814453125,\n              29.6880527498568\n            ],\n            [\n              -83.6279296875,\n              29.878755346037977\n            ],\n            [\n              -83.671875,\n              30.675715404167743\n            ],\n            [\n              -85.1220703125,\n              30.600093873550072\n            ],\n            [\n              -84.814453125,\n              29.6880527498568\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"497","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":206922,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":820867,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lei, Ting","contributorId":245022,"corporation":false,"usgs":false,"family":"Lei","given":"Ting","affiliations":[{"id":40912,"text":"Beijing Forestry","active":true,"usgs":false}],"preferred":false,"id":820868,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Villegas, Omag 0000-0003-0169-895X","orcid":"https://orcid.org/0000-0003-0169-895X","contributorId":263439,"corporation":false,"usgs":false,"family":"Villegas","given":"Omag","email":"","affiliations":[{"id":53989,"text":"Universidad Juarez del Estado de Durango, Mexico","active":true,"usgs":false}],"preferred":false,"id":820869,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liu, Xiaohui","contributorId":263440,"corporation":false,"usgs":false,"family":"Liu","given":"Xiaohui","email":"","affiliations":[{"id":53990,"text":"NE Institute  of Geography and Agroecology, Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":820870,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70222057,"text":"tm13B2 - 2021 - A numerical model for the cooling of a lava sill with heat pipe effects","interactions":[],"lastModifiedDate":"2021-07-19T11:39:28.138117","indexId":"tm13B2","displayToPublicDate":"2021-07-16T09:00:07","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"13-B2","displayTitle":"A Numerical Model for the Cooling of a Lava Sill with Heat Pipe Effects","title":"A numerical model for the cooling of a lava sill with heat pipe effects","docAbstract":"<p>Understanding the cooling process of volcanic intrusions into wet sediments is a difficult but important problem, given the presence of extremely large temperature gradients and potentially complex water-magma interactions. This report presents a numerical model to study such interactions, including the effect of heat pipes on the cooling of volcanic intrusions. Udell (1985) has shown that heat pipes may develop in heated saturated granular media under laboratory conditions. In previous work, Baker and others (2015) calculated temperatures in the vicinity of a volcanic sill that intruded into wet sediment, showing an unexpected temperature profile in which peak temperatures remained near constant over a region extending a meter above and below the sill. This is challenging to explain with conduction or convection heating methods but is predicted if the heat transfer is performed primarily by a heat pipe. We have numerically modeled the cooling of a lava sill under similar circumstances, using the experimental findings of Udell (1985) to estimate the characteristics of the heat pipe. We have constructed a model using Microsoft C#.NET, complete with an intuitive graphical user interface. The model is available from the U.S. Geological Survey and is capable of being run on Microsoft Windows 7 and higher with modest hardware. We find that the resulting overall temperature profile has some key similarities to the profile inferred by Baker and others (2015). Future models including more detailed convective heat transfer physics will be necessary to fully reproduce the effects of boiling in sediments.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm13B2","usgsCitation":"Williams, K.E., Dundas, C.M., and Kestay, L.P., 2021, A numerical model for the cooling of a lava sill with heat pipe effects: U.S. Geological Survey Techniques and Methods, book 13, chap. B2, 14 p., https://doi.org/10.3133/tm13B2.","productDescription":"v, 14 p.","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-120432","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":387233,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/13/b2/tm13B2_LavaCooling-Heatpipe_executable.zip","text":"Program — LavaCooling-Heatpipe.exe","size":"30 KB","linkFileType":{"id":6,"text":"zip"}},{"id":387194,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/13/b2/tm13B2.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":387193,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/13/b2/covrthb.jpg"}],"contact":"<p><a href=\"https://www.usgs.gov/centers/astrogeology-science-center/connect\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/astrogeology-science-center/connect\">Contact Astrogeology Research Program staff</a><br><a href=\"https://www.usgs.gov/centers/astrogeology-science-center\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/astrogeology-science-center\">Astrogeology Science Center</a><br><a data-mce-href=\"https://usgs.gov\" href=\"https://usgs.gov\" target=\"_blank\" rel=\"noopener\">U.S. Geological Survey</a><br>2255 N. Gemini Dr.<br>Flagstaff, AZ 86001</p>","tableOfContents":"<ul><li>Abstract&nbsp;&nbsp;</li><li>Introduction and Motivation&nbsp;&nbsp;</li><li>Model Description&nbsp;&nbsp;</li><li>Model Usage&nbsp;&nbsp;</li><li>Example&nbsp;</li><li>Summary&nbsp;&nbsp;</li><li>References Cited&nbsp;</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2021-07-16","noUsgsAuthors":false,"publicationDate":"2021-07-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, Kaj E. 0000-0003-1755-1872 kewilliams@usgs.gov","orcid":"https://orcid.org/0000-0003-1755-1872","contributorId":196988,"corporation":false,"usgs":true,"family":"Williams","given":"Kaj","email":"kewilliams@usgs.gov","middleInitial":"E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":819344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":819345,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keszthelyi, Laszlo P. 0000-0003-1879-4331 laz@usgs.gov","orcid":"https://orcid.org/0000-0003-1879-4331","contributorId":227,"corporation":false,"usgs":true,"family":"Keszthelyi","given":"Laszlo","email":"laz@usgs.gov","middleInitial":"P.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":819346,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70222137,"text":"70222137 - 2021 - Timing of iceberg scours and massive ice-rafting events in the subtropical North Atlantic","interactions":[],"lastModifiedDate":"2021-07-22T13:10:48.697227","indexId":"70222137","displayToPublicDate":"2021-07-16T07:01:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Timing of iceberg scours and massive ice-rafting events in the subtropical North Atlantic","docAbstract":"<p><span>High resolution seafloor mapping shows extraordinary evidence that massive (&gt;300 m thick) icebergs once drifted &gt;5,000 km south along the eastern United States, with &gt;700 iceberg scours now identified south of Cape Hatteras. Here we report on sediment cores collected from several buried scours that show multiple plow marks align with Heinrich Event 3 (H3), ~31,000 years ago. Numerical glacial iceberg simulations indicate that the transport of icebergs to these sites occurs during massive, but short-lived, periods of elevated meltwater discharge. Transport of icebergs to the subtropics, away from deep water formation sites, may explain why H3 was associated with only a modest increase in ice-rafting across the subpolar North Atlantic, and implies a complex relationship between freshwater forcing and climate change. Stratigraphy from subbottom data across the scour marks shows there are additional features that are both older and younger, and may align with other periods of elevated meltwater discharge.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41467-021-23924-0","usgsCitation":"Condron, A., and Hill, J.C., 2021, Timing of iceberg scours and massive ice-rafting events in the subtropical North Atlantic: Nature Communications, v. 12, 3668, 14 p., https://doi.org/10.1038/s41467-021-23924-0.","productDescription":"3668, 14 p.","ipdsId":"IP-120103","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451504,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-021-23924-0","text":"Publisher Index Page"},{"id":387321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Florida, Georgia, South Carolina","otherGeospatial":"Atlantic Coast","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.37695312499999,\n              34.88593094075317\n            ],\n            [\n              -77.82714843749999,\n              34.161818161230386\n            ],\n            [\n              -79.365234375,\n              33.137551192346145\n            ],\n            [\n              -81.0791015625,\n              31.653381399664\n            ],\n            [\n              -81.474609375,\n              30.259067203213018\n            ],\n            [\n              -79.6728515625,\n              26.86328062676624\n            ],\n            [\n              -75.76171875,\n              27.916766641249065\n            ],\n            [\n              -73.0810546875,\n              28.92163128242129\n            ],\n            [\n              -71.71875,\n              34.161818161230386\n            ],\n            [\n              -76.37695312499999,\n              34.88593094075317\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2021-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Condron, Alan 0000-0002-7337-1713","orcid":"https://orcid.org/0000-0002-7337-1713","contributorId":229547,"corporation":false,"usgs":false,"family":"Condron","given":"Alan","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":819626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, Jenna C. 0000-0002-7475-357X","orcid":"https://orcid.org/0000-0002-7475-357X","contributorId":21987,"corporation":false,"usgs":true,"family":"Hill","given":"Jenna","email":"","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":819627,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70222088,"text":"70222088 - 2021 - Mapping of suspended sediment transport using acoustic methods in a Pantanal tributary","interactions":[],"lastModifiedDate":"2021-07-19T23:32:45.066778","indexId":"70222088","displayToPublicDate":"2021-07-15T18:24:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Mapping of suspended sediment transport using acoustic methods in a Pantanal tributary","docAbstract":"<p><span>Generally, fluvial systems are used for different objectives including energy production, water supply, recreation, and navigation. Thus, many impacts must be considered with their use. An understanding of sediment dynamics in fluvial systems is often of value for a variety of objectives, given that erosion and depositional processes can change the fluvial system morphology and can substantially alter the fluvial environment. In this sense, sediment monitoring is important because it helps to explain and quantify sediment dynamics in the environment. Hence, this study presents an innovative sediment monitoring technique: the use of the acoustic Doppler current profiler, commonly used to obtain discharge measurements, to obtain suspended sediment concentration (SSC). This paper aims to describe the application of additional corrections to the ADP-M9 signal to obtain SSC from measurement campaigns that used the ADP only for discharge measurements. The analyses were based on traditional sediment sampling methods and discharge measurements, with the ADP-M9, from 7 field campaigns at the Taquari River, a major tributary from the Alto Paraguay Basin, in the Pantanal Biome, known as the largest freshwater wetland system in the world. The correlation was assessed considering the following: (a) the equipment frequency operation mode (Smart Pulse or Fixed Frequency) and (b) by checking the influence of the sediment attenuation coefficient. Furthermore, extrapolation was conducted in filtered and unmeasured areas of the ADP to map the suspended sediment concentration over the entire cross section. Results indicate that ADP correlations can be an effective tool for estimating SSC in the Taquari River when samples cannot be collected. Correlations could be applied to past and future ADP measurements made at the location where the correlation was created, as long as similar environmental conditions are present as when the correlation was developed. The described technique can expand the amount of sediment data available at a monitoring site even with reduced traditional sampling and by leveraging instruments used for other monitoring purposes.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10661-021-09266-w","usgsCitation":"Wosiacki, L.F., Koji Suekame, H., Wood, M.S., Verissimo Goncalves, F., and Bleninger, T., 2021, Mapping of suspended sediment transport using acoustic methods in a Pantanal tributary: Environmental Monitoring and Assessment, v. 193, 493, 19 p., https://doi.org/10.1007/s10661-021-09266-w.","productDescription":"493, 19 p.","ipdsId":"IP-120116","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":387258,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Taquari River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -57.041015625,\n              -22.105998799750566\n            ],\n            [\n              -54.31640625,\n              -19.84939395842278\n            ],\n            [\n              -52.9541015625,\n              -18.437924653474393\n            ],\n            [\n              -53.78906249999999,\n              -17.853290114098\n            ],\n            [\n              -53.7451171875,\n              -17.26672782352052\n            ],\n            [\n              -54.4921875,\n              -17.434510551522894\n            ],\n            [\n              -56.82128906249999,\n              -16.63619187839765\n            ],\n            [\n              -57.041015625,\n              -14.944784875088372\n            ],\n            [\n              -59.501953125,\n              -14.349547837185362\n            ],\n            [\n              -60.16113281250001,\n              -14.902321826141796\n            ],\n            [\n              -60.1171875,\n              -16.1724728083975\n            ],\n            [\n              -58.447265625,\n              -16.13026201203474\n            ],\n            [\n              -58.18359375,\n              -16.762467717941593\n            ],\n            [\n              -57.78808593749999,\n              -17.560246503294888\n            ],\n            [\n              -57.7001953125,\n              -18.729501999072138\n            ],\n            [\n              -58.3154296875,\n              -20.055931265194438\n            ],\n            [\n              -57.919921875,\n              -21.943045533438166\n            ],\n            [\n              -57.041015625,\n              -22.105998799750566\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"193","noUsgsAuthors":false,"publicationDate":"2021-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Wosiacki, Liege F.K.","contributorId":261197,"corporation":false,"usgs":false,"family":"Wosiacki","given":"Liege","email":"","middleInitial":"F.K.","affiliations":[{"id":52772,"text":"Federal University of Parana, Curitiba, Brazil","active":true,"usgs":false}],"preferred":false,"id":819460,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koji Suekame, Hugo","contributorId":261198,"corporation":false,"usgs":false,"family":"Koji Suekame","given":"Hugo","email":"","affiliations":[{"id":52773,"text":"Federal University of Mato Grosso do Sul, Campo Grande, Brazil","active":true,"usgs":false}],"preferred":false,"id":819461,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":819462,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Verissimo Goncalves, Fabio","contributorId":261199,"corporation":false,"usgs":false,"family":"Verissimo Goncalves","given":"Fabio","email":"","affiliations":[{"id":52773,"text":"Federal University of Mato Grosso do Sul, Campo Grande, Brazil","active":true,"usgs":false}],"preferred":false,"id":819463,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bleninger, Tobias","contributorId":261200,"corporation":false,"usgs":false,"family":"Bleninger","given":"Tobias","email":"","affiliations":[{"id":52772,"text":"Federal University of Parana, Curitiba, Brazil","active":true,"usgs":false}],"preferred":false,"id":819464,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70224570,"text":"70224570 - 2021 - Down to Earth with nuclear electromagnetic pulse: Realistic surface impedance affects mapping of the E3 geoelectric hazard","interactions":[],"lastModifiedDate":"2021-09-28T12:22:22.806471","indexId":"70224570","displayToPublicDate":"2021-07-15T07:20:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9361,"text":"Earth and Space Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Down to Earth with nuclear electromagnetic pulse: Realistic surface impedance affects mapping of the E3 geoelectric hazard","docAbstract":"<div class=\"article-section__content en main\"><p>An analysis is made of Earth-surface geoelectric fields and voltages on electricity transmission power-grids induced by a late-phase E3 nuclear electromagnetic pulse (EMP). A hypothetical scenario is considered of an explosion of several hundred kilotons set several hundred kilometers above the eastern-midcontinental United States. Ground-level E3 geoelectric fields are estimated by convolving a standard parameterization of E3 geomagnetic field variation with magnetotelluric Earth-surface impedance tensors derived from wideband measurements acquired across the study region during a recent survey. These impedance tensors are a function of subsurface three-dimensional electrical conductivity structure. Results, presented as a movie-map, demonstrate that localized differences in surface impedance strongly distort the amplitude, polarization, and variational phase of induced E3 geoelectric fields. Locations with a high degree of E3 geoelectric polarization tend to have high geoelectric amplitude. Uniform half-space models and one-dimensional, depth-dependent models of Earth-surface impedance, such as those widely used in government and industry reports informing power-grid vulnerability assessment projects, do not provide accurate estimates of the E3 geoelectric hazard in complex geological settings. In particular, for the Eastern-Midcontinent, half-space models can lead to (order-one) overestimates/underestimates of EMP-induced geovoltages on parts of the power grid by as much as<span>&nbsp;</span><img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/8e96158e-c9db-42eb-9c50-0ec06cf1a5bf/ess2899-math-0001.png\" alt=\"urn:x-wiley:23335084:media:ess2899:ess2899-math-0001\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/8e96158e-c9db-42eb-9c50-0ec06cf1a5bf/ess2899-math-0001.png\">1,000&nbsp;volts (a range of 2,000&nbsp;volts)—comparable to the amplitudes of the geovoltages themselves.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EA001792","usgsCitation":"Love, J.J., Lucas, G., Murphy, B.S., Bedrosian, P.A., Rigler, E.J., and Kelbert, A., 2021, Down to Earth with nuclear electromagnetic pulse: Realistic surface impedance affects mapping of the E3 geoelectric hazard: Earth and Space Sciences, v. 8, no. 8, e2021EA001792, 25 p., https://doi.org/10.1029/2021EA001792.","productDescription":"e2021EA001792, 25 p.","ipdsId":"IP-128556","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":451509,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021ea001792","text":"Publisher Index Page"},{"id":389861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":824100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lucas, Greg M. 0000-0003-1331-1863","orcid":"https://orcid.org/0000-0003-1331-1863","contributorId":223556,"corporation":false,"usgs":false,"family":"Lucas","given":"Greg M.","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":824101,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Benjamin Scott 0000-0001-7636-3711","orcid":"https://orcid.org/0000-0001-7636-3711","contributorId":242928,"corporation":false,"usgs":true,"family":"Murphy","given":"Benjamin","email":"","middleInitial":"Scott","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":824102,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":824103,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rigler, E. Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":824104,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelbert, Anna 0000-0003-4395-398X akelbert@usgs.gov","orcid":"https://orcid.org/0000-0003-4395-398X","contributorId":184053,"corporation":false,"usgs":true,"family":"Kelbert","given":"Anna","email":"akelbert@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":824105,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70221835,"text":"sir20215031 - 2021 - Optimization of the Idaho National Laboratory water-quality aquifer monitoring network, southeastern Idaho","interactions":[],"lastModifiedDate":"2021-07-16T12:31:02.274219","indexId":"sir20215031","displayToPublicDate":"2021-07-15T07:17:18","publicationYear":"2021","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":"2021-5031","displayTitle":"Optimization of the Idaho National Laboratory Water-Quality Aquifer Monitoring Network, Southeastern Idaho","title":"Optimization of the Idaho National Laboratory water-quality aquifer monitoring network, southeastern Idaho","docAbstract":"<p class=\"p1\">Long-term monitoring of water-quality data collected from wells at the Idaho National Laboratory (INL) has provided essential information for delineating the movement of radiochemical and chemical wastes in the eastern Snake River Plain aquifer, southeastern Idaho. Since 1949, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, has maintained as many as 200 wells in the INL water-quality monitoring network. A network design tool, distributed as an R package, was developed to evaluate and optimize groundwater monitoring in the existing network based on water-quality data collected at 153 sampling sites since January 1, 1989. The objective of the optimization design tool is to reduce well monitoring redundancy while retaining sufficient data to reliably characterize water-quality conditions in the aquifer. A spatial optimization was used to identify a set of wells whose removal leads to the smallest increase in the deviation between interpolated concentration maps using the existing and reduced monitoring networks while preserving significant long-term trends and seasonal components in the data. Additionally, a temporal optimization was used to identify reductions in sampling frequencies by minimizing the redundancy in sampling events.</p><p class=\"p1\">Spatial optimization uses an islands genetic algorithm to identify near-optimal network designs removing 10, 20, 30, 40, and 50 wells from the existing monitoring network. With this method, choosing a greater number of wells to remove results in greater cost savings and decreased accuracy of the average relative difference between interpolated maps of the reduced-dataset and the full-dataset. The genetic search algorithm identified reduced networks that best capture the spatial patterns of the average concentration plume while preserving long-term temporal trends at individual wells. Concentration data for 10 analyte types are integrated in a single optimization so that all datasets may be evaluated simultaneously. A constituent was selected for inclusion in the spatial optimization problem when the observations were sufficient to (1) establish a two-range variability model, (2) classify at least one concentration time series as a continuous record block, and (3) make a prediction using the quantile-kriging interpolation method. The selected constituents include sodium, chloride, sulfate, nitrate, carbon tetrachloride, 1,1-dichloroethylene, 1,1,1-trichloroethane, trichloroethylene, tritium, strontium-90, and plutonium-238.</p><p class=\"p2\">In temporal optimization, an iterative-thinning method was used to find an optimal sampling frequency for each analyte-well pair. Optimal frequencies indicate that for many of the wells, samples may be collected less frequently and still be able to characterize the concentration over time. The optimization results indicated that the sample-collection interval may be increased by an of average of 273 days owing to temporal redundancy.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215031","collaboration":"DOE/ID-22252<br />Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Fisher, J.C., Bartholomay, R.C., Rattray, G.W., and Maimer, N.V., 2021, Optimization of the Idaho National Laboratory water-quality aquifer monitoring network, southeastern Idaho: U.S. Geological Survey Scientific Investigations Report 2021–5031 (DOE/ID-22252), 63 p., https://doi.org/10.3133/sir20215031.","productDescription":"Report: vii, 63 p.; Appendix 1-12; 2 Software Releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071486","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":387046,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app02.html","text":"Appendix 2","size":"854 KB","linkFileType":{"id":5,"text":"html"},"description":"SIR 2021-5031 Appendix 2"},{"id":387045,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app01.html","text":"Appendix 1","size":"6.3 MB","linkFileType":{"id":5,"text":"html"},"description":"SIR 2021-5031 Appendix 1"},{"id":387058,"rank":16,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9X71CSU","text":"USGS software release —","description":"USGS software release","linkHelpText":"ObsNetQW—Assessment of a water-quality aquifer monitoring network"},{"id":387057,"rank":15,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9PP9UXZ","text":"USGS software release —","description":"USGS software release","linkHelpText":"inldata—Collection of datasets for the U.S. Geological Survey-Idaho National Laboratory aquifer monitoring networks"},{"id":387056,"rank":14,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app12.pdf","text":"Appendix 12","size":"116 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 12"},{"id":387054,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app10.pdf","text":"Appendix 10","size":"171 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 10"},{"id":387053,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app09.pdf","text":"Appendix 9","size":"12.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 9"},{"id":387052,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app08.pdf","text":"Appendix 8","size":"138 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 8"},{"id":387051,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app07.pdf","text":"Appendix 7","size":"7.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 7"},{"id":387047,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app03.pdf","text":"Appendix 3","size":"354 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 3"},{"id":387043,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5031/coverthb.jpg"},{"id":387048,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app04.pdf","text":"Appendix 4","size":"14.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 4"},{"id":387049,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app05.pdf","text":"Appendix 5","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 5"},{"id":387050,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app06.pdf","text":"Appendix 6","size":"154 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 6"},{"id":387044,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031.pdf","text":"Report","size":"14.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031"},{"id":387055,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app11.pdf","text":"Appendix 11","size":"21.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 11"}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.4393310546875,\n              43.45291889355465\n            ],\n            [\n              -112.4725341796875,\n              43.432977075795606\n            ],\n            [\n              -112.43957519531251,\n              44.06390660801777\n            ],\n            [\n              -113.389892578125,\n              44.09547572946637\n            ],\n            [\n              -113.4393310546875,\n              43.45291889355465\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_id@usgs.gov\" data-mce-href=\"mailto:dc_id@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/id-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/id-water\">Idaho Water Science Center</a><br>U.S. Geological Survey<br>230 Collins Road<br>Boise, Idaho 83702-4520</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Sources and Descriptions of Data</li><li>Temporal Regression</li><li>Spatial Interpolation</li><li>Spatial Optimization</li><li>Temporal Optimization</li><li>Summary and Conclusions</li><li>Acknowledgments</li><li>Appendixes</li></ul>","publishedDate":"2021-07-15","noUsgsAuthors":false,"publicationDate":"2021-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Fisher, Jason C. 0000-0001-9032-8912 jfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-9032-8912","contributorId":2523,"corporation":false,"usgs":true,"family":"Fisher","given":"Jason","email":"jfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartholomay, Roy C. 0000-0002-4809-9287 rcbarth@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-9287","contributorId":1131,"corporation":false,"usgs":true,"family":"Bartholomay","given":"Roy","email":"rcbarth@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rattray, Gordon W. 0000-0002-1690-3218 grattray@usgs.gov","orcid":"https://orcid.org/0000-0002-1690-3218","contributorId":2521,"corporation":false,"usgs":true,"family":"Rattray","given":"Gordon","email":"grattray@usgs.gov","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818876,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maimer, Neil V. 0000-0003-3047-3282 nmaimer@usgs.gov","orcid":"https://orcid.org/0000-0003-3047-3282","contributorId":5659,"corporation":false,"usgs":true,"family":"Maimer","given":"Neil","email":"nmaimer@usgs.gov","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818877,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70224273,"text":"70224273 - 2021 - Electrical properties of carbon dioxide hydrate: Implications for monitoring CO2 in the gas hydrate stability zone","interactions":[],"lastModifiedDate":"2021-09-17T12:22:01.918037","indexId":"70224273","displayToPublicDate":"2021-07-15T07:09:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Electrical properties of carbon dioxide hydrate: Implications for monitoring CO2 in the gas hydrate stability zone","docAbstract":"<div class=\"article-section__content en main\"><p>CO<sub>2</sub><span>&nbsp;</span>and CH<sub>4</sub><span>&nbsp;</span>clathrate hydrates are of keen interest for energy and carbon cycle considerations. While both typically form on Earth as cubic structure I (sI), we find that pure CO<sub>2</sub><span>&nbsp;</span>hydrate exhibits over an order of magnitude higher electrical conductivity (<i>σ</i>) than pure CH<sub>4</sub><span>&nbsp;</span>hydrate at geologically relevant temperatures. The conductivity was obtained from frequency-dependent impedance (<i>Z</i>) measurements made on polycrystalline CO<sub>2</sub><span>&nbsp;</span>hydrate (CO<sub>2</sub>·6.0&nbsp;±&nbsp;0.2H<sub>2</sub>O by methods here) with 25% gas-filled porosity, compared with CH<sub>4</sub><span>&nbsp;</span>hydrate (CH<sub>4</sub>·5.9H<sub>2</sub>O) formed and measured in the same apparatus and exhibiting closely matching grain characteristics. The conductivity of CO<sub>2</sub><span>&nbsp;</span>hydrate is 6.5&nbsp;×&nbsp;10<sup>−4</sup><span>&nbsp;</span>S/m at 273K with an activation energy (<i>E</i><sub>a</sub>) of 46.5&nbsp;kJ/mol at 260–281&nbsp;K, compared with ∼5&nbsp;×&nbsp;10<sup>−5</sup><span>&nbsp;</span>S/m and 34.8&nbsp;kJ/m for CH<sub>4</sub><span>&nbsp;</span>hydrate. Equivalent circuit modeling indicates that different pathways govern conduction in CO<sub>2</sub><span>&nbsp;</span>versus CH<sub>4</sub><span>&nbsp;</span>hydrate. Results show promise for use of electromagnetic methods in monitoring CO<sub>2</sub><span>&nbsp;</span>hydrate formation in certain natural settings or in CO<sub>2</sub>/CH<sub>4</sub><span>&nbsp;</span>exchange efforts.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL093475","usgsCitation":"Stern, L.A., Constable, S., Lu, R., Du Frane, W.L., and Roberts, J., 2021, Electrical properties of carbon dioxide hydrate: Implications for monitoring CO2 in the gas hydrate stability zone: Geophysical Research Letters, v. 48, no. 15, e2021GL093475, 9 p., https://doi.org/10.1029/2021GL093475.","productDescription":"e2021GL093475, 9 p.","ipdsId":"IP-125168","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":451512,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1811333","text":"Publisher Index Page"},{"id":389384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"15","noUsgsAuthors":false,"publicationDate":"2021-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Stern, Laura A. 0000-0003-3440-5674","orcid":"https://orcid.org/0000-0003-3440-5674","contributorId":212238,"corporation":false,"usgs":true,"family":"Stern","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":823427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Constable, S.","contributorId":238841,"corporation":false,"usgs":false,"family":"Constable","given":"S.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":823428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lu, Ryan","contributorId":238835,"corporation":false,"usgs":false,"family":"Lu","given":"Ryan","email":"","affiliations":[{"id":13621,"text":"Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":823429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Du Frane, Wyatt L.","contributorId":23067,"corporation":false,"usgs":false,"family":"Du Frane","given":"Wyatt","email":"","middleInitial":"L.","affiliations":[{"id":13621,"text":"Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":823430,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, J. Murray","contributorId":190580,"corporation":false,"usgs":false,"family":"Roberts","given":"J. Murray","affiliations":[],"preferred":false,"id":823431,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70229177,"text":"70229177 - 2021 - Demographic responses to climate change in a threatened Arctic species","interactions":[],"lastModifiedDate":"2022-03-02T17:55:54.727772","indexId":"70229177","displayToPublicDate":"2021-07-14T11:45:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Demographic responses to climate change in a threatened Arctic species","docAbstract":"<p><span>The Arctic is undergoing rapid and accelerating change in response to global warming, altering biodiversity patterns, and ecosystem function across the region. For Arctic endemic species, our understanding of the consequences of such change remains limited. Spectacled eiders (</span><i>Somateria fischeri</i><span>), a large Arctic sea duck, use remote regions in the Bering Sea, Arctic Russia, and Alaska throughout the annual cycle making it difficult to conduct comprehensive surveys or demographic studies. Listed as Threatened under the U.S. Endangered Species Act, understanding the species response to climate change is critical for effective conservation policy and planning. Here, we developed an integrated population model to describe spectacled eider population dynamics using capture–mark–recapture, breeding population survey, nest survey, and environmental data collected between 1992 and 2014. Our intent was to estimate abundance, population growth, and demographic rates, and quantify how changes in the environment influenced population dynamics. Abundance of spectacled eiders breeding in western Alaska has increased since listing in 1993 and responded more strongly to annual variation in first-year survival than adult survival or productivity. We found both adult survival and nest success were highest in years following intermediate sea ice conditions during the wintering period, and both demographic rates declined when sea ice conditions were above or below average. In recent years, sea ice extent has reached new record lows and has remained below average throughout the winter for multiple years in a row. Sea ice persistence is expected to further decline in the Bering Sea. Our results indicate spectacled eiders may be vulnerable to climate change and the increasingly variable sea ice conditions throughout their wintering range with potentially deleterious effects on population dynamics. Importantly, we identified that different demographic rates responded similarly to changes in sea ice conditions, emphasizing the need for integrated analyses to understand population dynamics.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7873","usgsCitation":"Dunham, K., Tucker, A., Koons, D., Abebe, A., Dobson, F., and Grand, J.B., 2021, Demographic responses to climate change in a threatened Arctic species: Ecology and Evolution, v. 11, no. 15, p. 10627-10643, https://doi.org/10.1002/ece3.7873.","productDescription":"17 p.","startPage":"10627","endPage":"10643","ipdsId":"IP-123223","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":451515,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.7873","text":"Publisher Index Page"},{"id":396660,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic Coastal Plain, Arctic Russia, Yukon-Kuskokwim Delta","volume":"11","issue":"15","noUsgsAuthors":false,"publicationDate":"2021-07-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Dunham, K.D.","contributorId":287550,"corporation":false,"usgs":false,"family":"Dunham","given":"K.D.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":836868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, A.M.","contributorId":287552,"corporation":false,"usgs":false,"family":"Tucker","given":"A.M.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":836869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koons, D.N.","contributorId":287553,"corporation":false,"usgs":false,"family":"Koons","given":"D.N.","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":836870,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abebe, A.","contributorId":287556,"corporation":false,"usgs":false,"family":"Abebe","given":"A.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":836871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dobson, F.S.","contributorId":287558,"corporation":false,"usgs":false,"family":"Dobson","given":"F.S.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":836872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grand, J. Barry 0000-0002-3576-4567 barry_grand@usgs.gov","orcid":"https://orcid.org/0000-0002-3576-4567","contributorId":579,"corporation":false,"usgs":true,"family":"Grand","given":"J.","email":"barry_grand@usgs.gov","middleInitial":"Barry","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":836873,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70221762,"text":"70221762 - 2021 - Comparison of preservation and extraction methods on five taxonomically disparate coral microbiomes","interactions":[],"lastModifiedDate":"2021-09-15T13:44:45.088065","indexId":"70221762","displayToPublicDate":"2021-07-14T08:42:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of preservation and extraction methods on five taxonomically disparate coral microbiomes","docAbstract":"<p><span>All animals are host to a multitude of microorganisms that are essential to the animal’s health. Host-associated microbes have been shown to defend against potential pathogens, provide essential nutrients, interact with the host’s immune system, and even regulate mood. However, it can be difficult to preserve and obtain nucleic acids from some host-associated microbiomes, making studying their microbial communities challenging. Corals are an example of this, in part due to their potentially remote, underwater locations, their thick surface mucopolysaccharide layer, and various inherent molecular inhibitors. This study examined three different preservatives (RNAlater, DNA/RNA Shield, and liquid nitrogen) and two extraction methods (the Qiagen PowerBiofilm kit and the Promega Maxwell RBC kit with modifications) to determine if there was an optimum combination for examining the coral microbiome. These methods were employed across taxonomically diverse coral species, including deep-sea/shallow, stony/soft, and zooxanthellate/azooxanthellate:&nbsp;</span><i>Lophelia pertusa</i><span>,&nbsp;</span><i>Paragorgia johnsoni</i><span>,&nbsp;</span><i>Montastraea cavernosa</i><span>,&nbsp;</span><i>Porites astreoides</i><span>, and&nbsp;</span><i>Stephanocoenia intersepta</i><span>. Although significant differences were found between preservative types and extraction methods, these differences were subtle, and varied in nature from coral species to coral species. Significant differences between coral species were far more profound than those detected between preservative or extraction method. We suggest that the preservative types presented here and extraction methods using a bead-beating step provide enough consistency to compare coral microbiomes across various studies, as long as subtle differences in microbial communities are attributed to dissimilar methodologies. Additionally, the inclusion of internal controls such as a mock community and extraction blanks can help provide context regarding data quality, improving downstream analyses.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2021.684161","usgsCitation":"Pratte, Z.A., and Kellogg, C.A., 2021, Comparison of preservation and extraction methods on five taxonomically disparate coral microbiomes: Frontiers in Marine Science, v. 8, 684161, 13 p., https://doi.org/10.3389/fmars.2021.684161.","productDescription":"684161, 13 p.","ipdsId":"IP-127754","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451519,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2021.684161","text":"Publisher Index Page"},{"id":436274,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96GBWDM","text":"USGS data release","linkHelpText":"Coral Microbiome Preservation and Extraction Method Comparison-Raw Data"},{"id":389261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2021-07-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Pratte, Zoe A.","contributorId":214260,"corporation":false,"usgs":false,"family":"Pratte","given":"Zoe","email":"","middleInitial":"A.","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":818655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818656,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
]}