{"pageNumber":"234","pageRowStart":"5825","pageSize":"25","recordCount":41062,"records":[{"id":70222113,"text":"70222113 - 2021 - Linking behavioral states to landscape features for improved conservation management","interactions":[],"lastModifiedDate":"2021-07-20T12:24:27.865412","indexId":"70222113","displayToPublicDate":"2021-05-25T07:21:43","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":"Linking behavioral states to landscape features for improved conservation management","docAbstract":"<ol class=\"\"><li>A central theme for conservation is understanding how animals differentially use, and are affected by change in, the landscapes they inhabit. However, it has been challenging to develop conservation schemes for habitat-specific behaviors.</li><li>Here we use behavioral change point analysis to identify behavioral states of golden eagles (<i>Aquila</i><span>&nbsp;</span><i>chrysaetos</i>) in the Sonoran and Mojave Deserts of the southwestern United States, and we identify, for each behavioral state, conservation-relevant habitat associations.</li><li>We modeled behavior using 186,859 GPS points from 48 eagles and identified 2,851 distinct segments comprising four behavioral states. Altitude above ground level (AGL) best differentiated behavioral states, with two clusters of short-distance movement behaviors characterized by low AGL (state 1 AGL&nbsp;=&nbsp;14&nbsp;m (median); state 2 AGL&nbsp;=&nbsp;11&nbsp;m) and two associated with longer-distance movement behaviors and characterized by higher AGL (state 3 AGL&nbsp;=&nbsp;108&nbsp;m; state 4 AGL&nbsp;=&nbsp;450&nbsp;m).</li><li>Behaviors such as perching and low-altitude hunting were associated with short-distance movements in updraft-poor environments, at higher elevations, and over steeper and more north-facing terrain. In contrast, medium-distance movements such as hunting and transiting were over gentle and south-facing slopes. Long-distance transiting occurred over the desert habitats that generate the best updraft.</li><li>This information can guide management of this species, and our approach provides a template for behavior-specific habitat associations for other species of management concern.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7621","usgsCitation":"Sur, M., Woodbridge, B., Esque, T., Belthoff, J.R., Bloom, P.H., Fisher, R., Longshore, K., Nussear, K., Tracey, J.A., Braham, M., and Katzner, T., 2021, Linking behavioral states to landscape features for improved conservation management: Ecology and Evolution, v. 11, no. 12, p. 7905-7916, https://doi.org/10.1002/ece3.7621.","productDescription":"12 p.","startPage":"7905","endPage":"7916","ipdsId":"IP-122296","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":452150,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.7621","text":"Publisher Index Page"},{"id":387296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.99316406249999,\n              33.284619968887675\n            ],\n            [\n              -115.02685546875,\n              33.284619968887675\n            ],\n            [\n              -115.02685546875,\n              35.67514743608467\n            ],\n            [\n              -117.99316406249999,\n              35.67514743608467\n            ],\n            [\n              -117.99316406249999,\n              33.284619968887675\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-05-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Sur, Maitreyi","contributorId":191354,"corporation":false,"usgs":false,"family":"Sur","given":"Maitreyi","email":"","affiliations":[],"preferred":false,"id":819567,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodbridge, Brian","contributorId":198923,"corporation":false,"usgs":false,"family":"Woodbridge","given":"Brian","email":"","affiliations":[{"id":17821,"text":"U.S. Fish and Wildlife Service, Division of Migratory Birds","active":true,"usgs":false}],"preferred":false,"id":819568,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819569,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belthoff, Jim R","contributorId":261244,"corporation":false,"usgs":false,"family":"Belthoff","given":"Jim","email":"","middleInitial":"R","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":819570,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bloom, Peter H.","contributorId":191356,"corporation":false,"usgs":false,"family":"Bloom","given":"Peter","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":819571,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819572,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Longshore, Kathleen 0000-0001-6621-1271","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":216374,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819573,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nussear, Kenneth","contributorId":194538,"corporation":false,"usgs":false,"family":"Nussear","given":"Kenneth","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":819574,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tracey, Jeff A. 0000-0002-1619-1054 jatracey@usgs.gov","orcid":"https://orcid.org/0000-0002-1619-1054","contributorId":5780,"corporation":false,"usgs":true,"family":"Tracey","given":"Jeff","email":"jatracey@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819575,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Braham, Melissa A.","contributorId":140127,"corporation":false,"usgs":false,"family":"Braham","given":"Melissa A.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":819576,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":819577,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70225657,"text":"70225657 - 2021 - Catch rates for sturgeon chubs and sicklefin chubs in the Upper Missouri River 2004–2016 and correlations with biotic and abiotic variables","interactions":[],"lastModifiedDate":"2021-12-10T17:12:29.221872","indexId":"70225657","displayToPublicDate":"2021-05-25T07:12:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Catch rates for sturgeon chubs and sicklefin chubs in the Upper Missouri River 2004–2016 and correlations with biotic and abiotic variables","docAbstract":"<div class=\"article-section-wrapper js-article-section js-content-section  \"><p>A multiweek standardized sampling regime during 2004–2016 in a 60-km reach of the Upper Missouri River assessed reproduction and catch rates for Sturgeon Chub<span>&nbsp;</span><i>Macrhybopsis gelida</i><span>&nbsp;</span>and Sicklefin Chub<span>&nbsp;</span><i>Macrhybopsis meeki</i>. We sampled age-0<span>&nbsp;</span><i>Macrhybopsis</i><span>&nbsp;</span>(primarily Sturgeon Chubs, but potentially including Sicklefin Chubs) all years to indicate successful reproduction, but noted an inverse correlation of catch per unit area (CPUA) with year. There was an inverse correlation for CPUA of age-1+ Sturgeon Chubs with year. There was no correlation for CPUA of age-1+ Sicklefin Chubs with year, but we noted a depression in CPUA during 2010 and 2012. The study reach includes restoration directives for federally endangered Pallid Sturgeon<span>&nbsp;</span><i>Scaphirhynchus albus</i>, with 245,000 hatchery-origin Pallid Sturgeon (HOPS) stocked since 1998 to supplement the declining wild stock. Pallid Sturgeon longer than 350 mm fork length transition to piscivory and are known to prey on Sturgeon Chubs and Sicklefin Chubs. We examined the hypothesis that mass additions of HOPS to the existing predator community could have population-level effects on the two chub species. Population modeling for the stocked HOPS through time yielded estimates of nearly 1,300 piscivore-sized HOPS in 2004, an increase to 26,000 HOPS in 2012, and decreasing numbers through 2016 (14,500). A negative correlation between HOPS abundance and age-0<span>&nbsp;</span><i>Macrhybopsis</i><span>&nbsp;</span>CPUA had the best support among other candidate variables (discharge, water temperature, catch rates of Sauger<span>&nbsp;</span><i>Sander canadensis</i>). We found an inverse correlation for CPUA of age-1+ Sturgeon Chubs and estimated HOPS abundance, and there was also evidence of an inverse association between age-1+ Sicklefin Chub CPUA and HOPS in the study area. Results for a 60-km reach of the Upper Missouri River suggest declining CPUA for age-0<span>&nbsp;</span><i>Macrhybopsis</i><span>&nbsp;</span>and Sturgeon Chubs during 2004–2016 and modest recovery of Sicklefin Chubs after 2012. Although causative factors driving CPUA changes through time are not known, correlative analyses suggest that large numbers of HOPS added to the Missouri River predator community potentially influence CPUA of Sturgeon Chubs and Sicklefin Chubs in the study area. Testing this hypothesis will require expanded quantification of chub populations and HOPS numbers through time.</p></div>","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-20-086","usgsCitation":"Braaten, P., Fuller, D.B., Haddix, T., Hunziker, J.R., Colvin, M., Holmquist, L.M., and Wilson, R.H., 2021, Catch rates for sturgeon chubs and sicklefin chubs in the Upper Missouri River 2004–2016 and correlations with biotic and abiotic variables: Journal of Fish and Wildlife Management, v. 12, no. 2, p. 322-337, https://doi.org/10.3996/JFWM-20-086.","productDescription":"16 p.","startPage":"322","endPage":"337","ipdsId":"IP-114484","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":452152,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-20-086","text":"Publisher Index Page"},{"id":391201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","otherGeospatial":"Missouri River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.6552734375,\n              47.22329888685773\n            ],\n            [\n              -103.07922363281249,\n              47.22329888685773\n            ],\n            [\n              -103.07922363281249,\n              48.469279317167164\n            ],\n            [\n              -106.6552734375,\n              48.469279317167164\n            ],\n            [\n              -106.6552734375,\n              47.22329888685773\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-05-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Braaten, Patrick 0000-0003-3362-420X pbraaten@usgs.gov","orcid":"https://orcid.org/0000-0003-3362-420X","contributorId":152682,"corporation":false,"usgs":true,"family":"Braaten","given":"Patrick","email":"pbraaten@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":826080,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, David B.","contributorId":149098,"corporation":false,"usgs":false,"family":"Fuller","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":17641,"text":"Montana Fish, Wildlife and Parks-Glasgow, MT","active":true,"usgs":false}],"preferred":false,"id":826081,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haddix, Tyler M.","contributorId":268184,"corporation":false,"usgs":false,"family":"Haddix","given":"Tyler M.","affiliations":[{"id":55585,"text":"Montana Fish, Wildlife and Parks, P.O. Box 165, Fort Peck, Montana","active":true,"usgs":false}],"preferred":false,"id":826082,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunziker, John R.","contributorId":268185,"corporation":false,"usgs":false,"family":"Hunziker","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":55585,"text":"Montana Fish, Wildlife and Parks, P.O. Box 165, Fort Peck, Montana","active":true,"usgs":false}],"preferred":false,"id":826083,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colvin, Michael E.","contributorId":264842,"corporation":false,"usgs":false,"family":"Colvin","given":"Michael E.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":826098,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holmquist, Luke M. 0000-0002-9282-8897","orcid":"https://orcid.org/0000-0002-9282-8897","contributorId":244286,"corporation":false,"usgs":false,"family":"Holmquist","given":"Luke","email":"","middleInitial":"M.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":826084,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":826099,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70221488,"text":"70221488 - 2021 - The Independent Volcanic Eruption Source Parameter Archive (IVESPA, version 1.0): A new observational database to support explosive eruptive column model validation and development","interactions":[],"lastModifiedDate":"2021-06-30T19:06:54.739246","indexId":"70221488","displayToPublicDate":"2021-05-25T06:34:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"The Independent Volcanic Eruption Source Parameter Archive (IVESPA, version 1.0): A new observational database to support explosive eruptive column model validation and development","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0085\">Eruptive column models are powerful tools for investigating the transport of volcanic gas and ash, reconstructing past explosive eruptions, and simulating future hazards. However, the evaluation of these models is challenging as it requires independent estimates of the main model inputs (e.g. mass eruption rate) and outputs (e.g. column height). There exists no database of independently estimated eruption source parameters (ESPs) that is extensive, standardized, maintained, and consensus-based. This paper introduces the Independent<span>&nbsp;</span>Volcanic Eruption<span>&nbsp;Source Parameter Archive (IVESPA, ivespa.co.uk), a community effort endorsed by the International Association of Volcanology and Chemistry of the Earth’s Interior (IAVCEI) Commission on&nbsp;Tephra&nbsp;Hazard Modelling. We compiled data for 134 explosive eruptive events, spanning the 1902-2016 period, with independent estimates of: i) total erupted mass of fall deposits; ii) duration; iii) eruption column height; and iv) atmospheric conditions. Crucially, we distinguish plume top versus umbrella spreading height, and the height of ash versus&nbsp;sulphur dioxide&nbsp;injection. All parameter values provided have been vetted independently by at least two experts. Uncertainties are quantified systematically, including flags to describe the degree of interpretation of the literature required for each estimate. IVESPA also includes a range of additional parameters such as total grain size distribution, eruption style, morphology of the plume (weak versus strong), and mass contribution from pyroclastic density currents, where available. We discuss the future developments and potential applications of IVESPA and make recommendations for reporting ESPs to maximize their usability across different applications. IVESPA covers an unprecedented range of ESPs and can therefore be used to evaluate and develop eruptive column models across a wide range of conditions using a standardized dataset.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107295","usgsCitation":"Aubry, T., Engwell, S., Bonadonna, C., Carazzo, G., Scollo, S., Van Eaton, A.R., Taylor, I.A., Jessop, D., Eychenne, J., Gouhier, M., Mastin, L.G., Wallace, K.L., Biass, S., Bursik, M., Grainger, R., Jellinek, M., and Schmidt, A., 2021, The Independent Volcanic Eruption Source Parameter Archive (IVESPA, version 1.0): A new observational database to support explosive eruptive column model validation and development: Journal of Volcanology and Geothermal Research, v. 417, 107295, 31 p., https://doi.org/10.1016/j.jvolgeores.2021.107295.","productDescription":"107295, 31 p.","ipdsId":"IP-124135","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":452161,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2021.107295","text":"Publisher Index Page"},{"id":386561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"417","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Aubry, Thomas J","contributorId":260383,"corporation":false,"usgs":false,"family":"Aubry","given":"Thomas J","affiliations":[{"id":52574,"text":"University of Cambridge, UK","active":true,"usgs":false}],"preferred":false,"id":817817,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engwell, Samantha 0000-0001-7719-6257","orcid":"https://orcid.org/0000-0001-7719-6257","contributorId":251719,"corporation":false,"usgs":false,"family":"Engwell","given":"Samantha","email":"","affiliations":[{"id":25567,"text":"British Geological Survey","active":true,"usgs":false}],"preferred":false,"id":817818,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonadonna, Costanza","contributorId":199721,"corporation":false,"usgs":false,"family":"Bonadonna","given":"Costanza","email":"","affiliations":[],"preferred":false,"id":817819,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carazzo, Guillaume","contributorId":260384,"corporation":false,"usgs":false,"family":"Carazzo","given":"Guillaume","email":"","affiliations":[{"id":52575,"text":"CNRS, Paris, France","active":true,"usgs":false}],"preferred":false,"id":817820,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scollo, Simona","contributorId":260385,"corporation":false,"usgs":false,"family":"Scollo","given":"Simona","email":"","affiliations":[{"id":27605,"text":"INGV, Catania, Italy","active":true,"usgs":false}],"preferred":false,"id":817821,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":817822,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Taylor, Isabelle A","contributorId":260386,"corporation":false,"usgs":false,"family":"Taylor","given":"Isabelle","email":"","middleInitial":"A","affiliations":[{"id":30742,"text":"University of Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":817823,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jessop, David","contributorId":260387,"corporation":false,"usgs":false,"family":"Jessop","given":"David","affiliations":[{"id":52575,"text":"CNRS, Paris, France","active":true,"usgs":false}],"preferred":false,"id":817824,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Eychenne, Julia","contributorId":168818,"corporation":false,"usgs":false,"family":"Eychenne","given":"Julia","email":"","affiliations":[{"id":25364,"text":"Univ. Hawai`i","active":true,"usgs":false}],"preferred":false,"id":817825,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gouhier, Mathieu","contributorId":260388,"corporation":false,"usgs":false,"family":"Gouhier","given":"Mathieu","email":"","affiliations":[{"id":29878,"text":"Université Clermont Auvergne, Clermont-Ferrand, France","active":true,"usgs":false}],"preferred":false,"id":817826,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mastin, Larry G. 0000-0002-4795-1992 lgmastin@usgs.gov","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":555,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"lgmastin@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":817827,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wallace, Kristi L. 0000-0002-0962-048X kwallace@usgs.gov","orcid":"https://orcid.org/0000-0002-0962-048X","contributorId":3454,"corporation":false,"usgs":true,"family":"Wallace","given":"Kristi","email":"kwallace@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":817828,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Biass, Sebastien","contributorId":243518,"corporation":false,"usgs":false,"family":"Biass","given":"Sebastien","email":"","affiliations":[{"id":35755,"text":"University of Hawai’i at Mānoa","active":true,"usgs":false}],"preferred":false,"id":817829,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bursik, Marcus","contributorId":199707,"corporation":false,"usgs":false,"family":"Bursik","given":"Marcus","affiliations":[],"preferred":false,"id":817830,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Grainger, Roy G","contributorId":260389,"corporation":false,"usgs":false,"family":"Grainger","given":"Roy G","affiliations":[{"id":30742,"text":"University of Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":817831,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Jellinek, Mark","contributorId":260390,"corporation":false,"usgs":false,"family":"Jellinek","given":"Mark","email":"","affiliations":[{"id":52578,"text":"University of British Columbia, Vancouver, Canada","active":true,"usgs":false}],"preferred":false,"id":817832,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Schmidt, Anja","contributorId":260391,"corporation":false,"usgs":false,"family":"Schmidt","given":"Anja","email":"","affiliations":[{"id":52574,"text":"University of Cambridge, UK","active":true,"usgs":false}],"preferred":false,"id":817833,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70224643,"text":"70224643 - 2021 - Species mixture effects and climate influence growth, recruitment and mortality in Interior West USA Populus tremuloides-conifer communities","interactions":[],"lastModifiedDate":"2021-10-01T12:42:19.576185","indexId":"70224643","displayToPublicDate":"2021-05-24T07:38:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Species mixture effects and climate influence growth, recruitment and mortality in Interior West USA Populus tremuloides-conifer communities","docAbstract":"<ol class=\"\"><li>Tree-species mixture effects (e.g. complementarity and facilitation) have been found to increase individual-tree productivity, lessen mortality and improve recruitment in forests worldwide. By promoting more efficient and complete resource use, mixture effects may also lessen individual-tree-level water stress, thus improving drought resistance. We investigated the influence of mixture effects on tree productivity, mortality and recruitment across broad compositional and moisture gradients in high-elevation Interior West US mixed-conifer communities, where<span>&nbsp;</span><i>Populus tremuloides</i><span>&nbsp;</span>(trembling aspen) is the major contributor to functional diversity. Our goal was to provide a more complete scientific foundation for managing these drought-prone, fire-excluded systems under an uncertain climate.</li><li>We used landscape-scale national forest inventory data to examine mixture effects on<span>&nbsp;</span><i>P. tremuloides</i><span>&nbsp;</span>and the major associated conifer species,<span>&nbsp;</span><i>Pseudotsuga menziesii</i>,<span>&nbsp;</span><i>Pinus contorta</i>,<span>&nbsp;</span><i>Abies lasiocarpa</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Picea engelmannii</i>. Using generalized linear mixed modelling, we isolated the influences of<span>&nbsp;</span><i>P. tremuloides</i><span>&nbsp;</span>relative density and climate on tree-level (stems ≥ 12.7&nbsp;cm DBH) growth, mortality and stand-level recruitment (presence/absence of new trees). Cold-season precipitation (PPT) and warm-season vapour pressure deficit (VPD) served to represent soil moisture supply and demand, respectively.</li><li><i>Populus tremuloides</i><span>&nbsp;</span>growth declined as interspecific density increased. In contrast,<span>&nbsp;</span><i>Pinus contorta</i><span>&nbsp;</span>and<span>&nbsp;</span><i>A. lasiocarpa</i><span>&nbsp;</span>growth increased with<span>&nbsp;</span><i>P. tremuloides</i><span>&nbsp;</span>density. For all species except<span>&nbsp;</span><i>A. lasiocarpa</i><span>&nbsp;</span>and<span>&nbsp;</span><i>P. menziesii,</i><span>&nbsp;</span>growth increased under higher PPT and VPD.<span>&nbsp;</span><i>Populus tremuloides</i><span>&nbsp;</span>mortality increased under high VPD but not with interspecific relative density. We found limited evidence that<span>&nbsp;</span><i>A. lasiocarpa</i><span>&nbsp;</span>mortality decreased as<span>&nbsp;</span><i>P. tremuloides</i><span>&nbsp;</span>density increased.<span>&nbsp;</span><i>Populus tremuloides</i><span>&nbsp;</span>recruitment declined steeply above 25% interspecific relative density. We found a decline in conifer recruitment odds as<span>&nbsp;</span><i>P. tremuloides</i><span>&nbsp;</span>density increased, ranging from strong in<span>&nbsp;</span><i>P. contorta</i><span>&nbsp;</span>to insubstantial in<span>&nbsp;</span><i>P. engelmannii</i>.</li><li><i>Synthesis</i>. Our findings have implications for sustaining mixed-conifer communities impacted by climate change and historical fire exclusion. Mixtures of<span>&nbsp;</span><i>P. tremuloides</i><span>&nbsp;</span>and conifers may improve conifer growth while adversely impacting<span>&nbsp;</span><i>P. tremuloides</i><span>&nbsp;</span>growth relative to pure stands. Higher conifer productivity combined with lower<span>&nbsp;</span><i>P. tremuloides</i><span>&nbsp;</span>recruitment at high conifer relative density may accelerate succession.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2745.13709","usgsCitation":"Looney, C.E., Previant, W.J., Bradford, J., and Nagel, L.M., 2021, Species mixture effects and climate influence growth, recruitment and mortality in Interior West USA Populus tremuloides-conifer communities: Journal of Ecology, v. 109, no. 8, p. 2934-2949, https://doi.org/10.1111/1365-2745.13709.","productDescription":"16 p.","startPage":"2934","endPage":"2949","ipdsId":"IP-126822","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":452164,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2745.13709","text":"Publisher Index Page"},{"id":390103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"109","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Looney, Christopher E.","contributorId":222544,"corporation":false,"usgs":false,"family":"Looney","given":"Christopher","email":"","middleInitial":"E.","affiliations":[{"id":40558,"text":"University of Minnesota, Department of Forest Resources, Green Hall, 1530 Cleveland Ave. N, St. Paul, MN 55108, USA","active":true,"usgs":false}],"preferred":false,"id":824516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Previant, Wilfred J","contributorId":266179,"corporation":false,"usgs":false,"family":"Previant","given":"Wilfred","email":"","middleInitial":"J","affiliations":[{"id":54940,"text":"Forest Inventory and Analysis Program Manager, Colorado State Forest Service, 5060 Campus Delivery, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":824517,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":824518,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nagel, Linda M","contributorId":266180,"corporation":false,"usgs":false,"family":"Nagel","given":"Linda","email":"","middleInitial":"M","affiliations":[{"id":54941,"text":"Colorado State University, Department of Forest and Rangeland Stewardship, 1472 Campus Delivery, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":824519,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70220862,"text":"70220862 - 2021 - Time marches on, but do the causal pathways driving instream habitat and biology remain consistent?","interactions":[],"lastModifiedDate":"2021-06-01T17:50:52.039437","indexId":"70220862","displayToPublicDate":"2021-05-24T07:29:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Time marches on, but do the causal pathways driving instream habitat and biology remain consistent?","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0060\">Stream ecosystems are complex networks of interacting terrestrial and aquatic drivers. To untangle these ecological networks, efforts evaluating the direct and indirect effects of landscape, climate, and instream predictors on biological condition through time are needed. We used structural equation modeling and leveraged a stream survey program to identify and compare important predictors driving condition of benthic macroinvertebrate and fish assemblages. We used data resampled 14 years apart at 252 locations across Maryland, USA. Sample locations covered a wide range of conditions that varied spatiotemporally. Overall, the relationship directions were consistent between sample periods, but their relative strength varied temporally. For benthic macroinvertebrates, we found that the total effect of natural landscape (<i>e.g</i>., elevation, longitude, latitude, geology) and land use (<i>i.e</i>., forest, development, agriculture) predictors was 1.4 and 1.5 times greater in the late 2010s compared to the 2000s. Moreover, the total effect of water quality (<i>e.g</i>., total nitrogen and conductivity) and habitat (<i>e.g</i>., embeddedness, riffle quality) was 1.2 and 4.8 times lower in the 2010s, respectively. For fish assemblage condition, the total effect of land use-land cover predictors was 2.3 times greater in the 2010s compared to the 2000s, while the total effect of local habitat was 1.4 times lower in the 2010s, respectively. As expected, we found biological assemblages in catchments with more agriculture and urban development were generally comprised of tolerant, generalist species, while assemblages in catchments with greater forest cover had more-specialized, less-tolerant species (<i>e.g.,</i><span>&nbsp;</span>Ephemeroptera, Plecoptera, and Trichoptera taxa, clingers, benthic and lithophilic spawning fishes). Changes in the relative importance of landscape and land-use predictors suggest other correlated, yet unmeasured, proximal factors became more important over time. By untangling these ecological networks, stakeholders can gain a better understanding of the spatiotemporal relationships driving biological condition to implement management practices aimed at improving stream condition.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.147985","usgsCitation":"Walker, R.H., Ashton, M.J., Cashman, M.J., Fanelli, R., Krause, K.P., Noe, G.E., and Maloney, K.O., 2021, Time marches on, but do the causal pathways driving instream habitat and biology remain consistent?: Science of the Total Environment, v. 789, 147985, 14 p., https://doi.org/10.1016/j.scitotenv.2021.147985.","productDescription":"147985, 14 p.","ipdsId":"IP-127928","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":452166,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2021.147985","text":"Publisher Index Page"},{"id":385980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Branch","active":true,"usgs":true}],"preferred":true,"id":816493,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":816494,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70221101,"text":"70221101 - 2021 - Improved methods for understanding the role of predation on dreissenid population dynamics","interactions":[],"lastModifiedDate":"2021-06-02T12:16:04.697333","indexId":"70221101","displayToPublicDate":"2021-05-24T07:14:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Improved methods for understanding the role of predation on dreissenid population dynamics","docAbstract":"<p><span>Impacts of dreissenid mussels (</span><i>Dreissena</i><span>&nbsp;spp.) on Great Lakes ecosystems are well documented, and a better understanding of mechanisms that cause variation in dreissenid abundance is needed. An outstanding question is how much dreissenid biomass is consumed by fish predation. A significant difficulty for investigating dreissenid consumption by fish is that dreissenids in stomachs are often a mix of indigestible shell and flesh, which can bias bioenergetics models and estimates of daily ration. Here, we develop an analysis to convert crushed shell and flesh mixtures found in fish diets to dry weight of digestible dreissenid flesh. Quagga&nbsp;</span><i>Dreissena rostiformis bugensis</i><span>&nbsp;and zebra&nbsp;</span><i>Dreissena polymorpha</i><span>&nbsp;mussels were used in separate dry weight analyses simulating stomach contents ranging from individual mussels to aggregates of each species. A species-specific dry weight relationship was observed when comparing flesh-only dry weight to total dry weight (shell + flesh) for individual dreissenid but not for aggregates. Thus, the model is applicable in providing more precise estimates of dreissenid flesh dry weight in fish diets.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10641-021-01054-2","usgsCitation":"Keretz, K.R., Kraus, R., and Schmitt, J., 2021, Improved methods for understanding the role of predation on dreissenid population dynamics: Environmental Biology of Fishes, v. 104, p. 629-633, https://doi.org/10.1007/s10641-021-01054-2.","productDescription":"5 p.","startPage":"629","endPage":"633","ipdsId":"IP-116741","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":436352,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P941VMIN","text":"USGS data release","linkHelpText":"Zebra and Quagga Mussel Dry Weight Information; Lake Erie 2014"},{"id":386112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"104","noUsgsAuthors":false,"publicationDate":"2021-05-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Keretz, Kevin R. 0000-0002-4808-8350 kkeretz@usgs.gov","orcid":"https://orcid.org/0000-0002-4808-8350","contributorId":5859,"corporation":false,"usgs":true,"family":"Keretz","given":"Kevin","email":"kkeretz@usgs.gov","middleInitial":"R.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":816767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":816768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmitt, Joseph 0000-0002-8354-4067","orcid":"https://orcid.org/0000-0002-8354-4067","contributorId":221020,"corporation":false,"usgs":true,"family":"Schmitt","given":"Joseph","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":816769,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70220497,"text":"ofr20211019 - 2021 - Effect of groundwater withdrawals, river stage, and precipitation on water-table elevations in the Iowa River alluvial aquifer near Tama, Iowa, 2017–20","interactions":[],"lastModifiedDate":"2021-05-24T20:54:59.887262","indexId":"ofr20211019","displayToPublicDate":"2021-05-21T16:29:14","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1019","displayTitle":"Effect of Groundwater Withdrawals, River Stage, and Precipitation on Water-Table Elevations in the Iowa River Alluvial Aquifer near Tama, Iowa, 2017–20","title":"Effect of groundwater withdrawals, river stage, and precipitation on water-table elevations in the Iowa River alluvial aquifer near Tama, Iowa, 2017–20","docAbstract":"<p>The Sac and Fox Tribe of the Mississippi in Iowa is the only federally recognized Tribe in the State of Iowa and is commonly known as the Meskwaki Nation. The Tribe owns more than 8,100 acres, referred to as the “Meskwaki Settlement.” The Meskwaki Settlement uses a well field that withdraws water from the Iowa River alluvial aquifer (IRAA) to supply drinking water to members of the Tribe. Increased severity and timing of flooding and drought conditions, coupled with water-quality concerns in the Iowa River, have prompted the Meskwaki Nation to start identifying tools to provide a better understanding of how extreme climate events (changes in streamflow, flood frequency, and magnitude and persistence of drought conditions), increasing water-supply demands, and groundwater storage depletion will affect water availability in the IRAA.</p><p>From June 2017 through September 2020, the U.S. Geological Survey, in cooperation with the Meskwaki Nation, collected continuous and discrete groundwater level data from 11 wells in a U.S. Geological Survey monitoring-well network. Groundwater level data collected at these wells were assessed with daily precipitation data and compared to changes in stream level elevations and daily groundwater withdrawals to determine how these changes affect groundwater-table elevations. Results from this study could be used to guide the development of a conceptual model for groundwater flow and a groundwater flow model for the IRAA to quantify and forecast the effect of groundwater withdrawals, Iowa River streamflow, and local precipitation on the water table in the IRAA.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211019","collaboration":"Prepared in cooperation with the Sac and Fox Tribe of the Mississippi in Iowa","usgsCitation":"Gruhn, L.R., and Haj, A.E., 2021, Effect of groundwater withdrawals, river stage, and precipitation on water-table elevations in the Iowa River alluvial aquifer near Tama, Iowa, 2017–20: U.S. Geological Survey Open-File Report 2021–1019, 11 p., https://doi.org/10.3133/ofr20211019.","productDescription":"Report: vi, 11 p.; Data Release; Dataset","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-124518","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":385788,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1019/images"},{"id":385789,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1019/ofr20211019.XML"},{"id":385680,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1019/coverthb.jpg"},{"id":385681,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1019/ofr20211019.pdf","text":"Report","size":"2.92 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1019"},{"id":385682,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":385683,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P912FO3L","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial datasets for the flood-inundation study for the Iowa River at the Meskwaki Settlement in Iowa, 2019"}],"country":"United States","state":"Iowa","county":"Tama County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-92.2996,42.2975],[-92.2992,42.2098],[-92.2989,42.1226],[-92.2991,42.0354],[-92.2977,41.9786],[-92.2994,41.95],[-92.299,41.8623],[-92.418,41.8625],[-92.5357,41.8621],[-92.6522,41.862],[-92.7674,41.8618],[-92.7671,41.9494],[-92.7662,42.0348],[-92.7672,42.1234],[-92.7687,42.2101],[-92.7697,42.2964],[-92.6531,42.2971],[-92.5353,42.2972],[-92.418,42.2976],[-92.2996,42.2975]]]},\"properties\":{\"name\":\"Tama\",\"state\":\"IA\"}}]}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/cm-water\" href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>400 South Clinton Street, Suite 269<br>Iowa City, IA 52240</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Hydrologic Effect of Groundwater Withdrawals, River Stage, and Precipitation on the Iowa River Alluvial Aquifer</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-05-17","noUsgsAuthors":false,"publicationDate":"2021-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Gruhn, Lance R. 0000-0002-7120-3003 lgruhn@usgs.gov","orcid":"https://orcid.org/0000-0002-7120-3003","contributorId":219710,"corporation":false,"usgs":true,"family":"Gruhn","given":"Lance","email":"lgruhn@usgs.gov","middleInitial":"R.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":815833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haj, Adel E. 0000-0002-3377-7161 ahaj@usgs.gov","orcid":"https://orcid.org/0000-0002-3377-7161","contributorId":147631,"corporation":false,"usgs":true,"family":"Haj","given":"Adel","email":"ahaj@usgs.gov","middleInitial":"E.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":815834,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227718,"text":"70227718 - 2021 - Hydrologic variation influences stream fish assemblage dynamics through flow regime and drought","interactions":[],"lastModifiedDate":"2022-01-27T16:46:41.231123","indexId":"70227718","displayToPublicDate":"2021-05-21T10:41:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic variation influences stream fish assemblage dynamics through flow regime and drought","docAbstract":"<p><span>Hydrologic variation can play a major role in structuring stream fish assemblages and relationships between hydrology and biology are likely to be influenced by flow regime. We hypothesized that more variable flow regimes would have lower and more variable species richness, higher species turnover and lower assemblage stability, and greater abiotic environment-fish relationships than more stable flow regimes. We sampled habitats (pool, run, and riffle) in three Runoff/Intermittent Flashy streams (highly variable flow regime) and three Groundwater Flashy streams (less variable flow regime) seasonally (spring, early summer, summer and autumn) in 2002 (drought year) and 2003 (wet year). We used backpack electrofishing and three-pass removal techniques to estimate fish species richness, abundance and density. Fish species richness and abundance remained relatively stable within streams and across seasons, but densities changed substantially as a result of decreased habitat volume. Mixed model analysis showed weak response variable-habitat relationships with strong season effects in 2002, and stronger habitat relationships and no season effect in 2003, and flow regime was not important in structuring these relationships. Seasonal fish species turnover was significantly greater in 2002 than 2003, but did not differ between flow regimes. Fish assemblage stability was significantly lower in Runoff/Intermittent Flashy than Groundwater Flashy streams in 2002, but did not differ between flow regimes in 2003. Redundancy analysis showed fish species densities were well separated by flow regime in both years. Periodic and opportunistic species were characteristic of Runoff/Intermittent Flashy streams, whereas mainly equilibrium species were characteristic of Groundwater Flashy streams. We found that spatial and temporal variation in hydrology had a strong influence on fish assemblage dynamics in Ozark streams with lower assemblage stability and greater fluctuations in density in more hydrologically variable streams and years. Understanding relationships between fish assemblage structure and hydrologic variation is vital for conservation of fish biodiversity. Future work should consider addressing how alteration of hydrologic variation will affect biotic assemblages.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41598-021-89632-3","usgsCitation":"Magoulick, D.D., Dekar, M.P., Hodges, S.W., Scott, M.K., Rabalais, M.R., and Bare, C.M., 2021, Hydrologic variation influences stream fish assemblage dynamics through flow regime and drought: Scientific Reports, v. 11, 10704, 15 p., https://doi.org/10.1038/s41598-021-89632-3.","productDescription":"10704, 15 p.","ipdsId":"IP-084686","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":452176,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-021-89632-3","text":"Publisher Index Page"},{"id":394978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri, Oklahoma","otherGeospatial":"Ozark Plateau","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.7578125,\n              33.137551192346145\n            ],\n            [\n              -92.2412109375,\n              34.379712580462204\n            ],\n            [\n              -89.912109375,\n              37.75334401310656\n            ],\n            [\n              -93.4716796875,\n              38.272688535980976\n            ],\n            [\n              -94.6142578125,\n              36.84446074079564\n            ],\n            [\n              -95.9326171875,\n              35.38904996691167\n            ],\n            [\n              -96.767578125,\n              34.70549341022544\n            ],\n            [\n              -96.1962890625,\n              33.8339199536547\n            ],\n            [\n              -94.4384765625,\n              33.797408767572485\n            ],\n            [\n              -93.955078125,\n              33.137551192346145\n            ],\n            [\n              -91.7578125,\n              33.137551192346145\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2021-05-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","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":831901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dekar, M. P.","contributorId":272274,"corporation":false,"usgs":false,"family":"Dekar","given":"M.","email":"","middleInitial":"P.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":831902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hodges, S. W.","contributorId":272275,"corporation":false,"usgs":false,"family":"Hodges","given":"S.","email":"","middleInitial":"W.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":831903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scott, M. K.","contributorId":272276,"corporation":false,"usgs":false,"family":"Scott","given":"M.","email":"","middleInitial":"K.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":831904,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rabalais, M. R.","contributorId":272277,"corporation":false,"usgs":false,"family":"Rabalais","given":"M.","email":"","middleInitial":"R.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":831905,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bare, C. M.","contributorId":272278,"corporation":false,"usgs":false,"family":"Bare","given":"C.","email":"","middleInitial":"M.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":831906,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70262416,"text":"70262416 - 2021 - Threading the needle: How humans influence predator–prey spatiotemporal interactions in a multiple‐predator system","interactions":[],"lastModifiedDate":"2025-01-23T16:23:49.063822","indexId":"70262416","displayToPublicDate":"2021-05-21T10:02:10","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Threading the needle: How humans influence predator–prey spatiotemporal interactions in a multiple‐predator system","docAbstract":"<ol class=\"\"><li>Perceived predation risk and the resulting antipredator behaviour varies across space, time and predator identity. Communities with multiple predators that interact and differ in their use of space, time of activity and hunting mode create a complex landscape for prey to avoid predation. Anthropogenic presence and disturbance have the potential to shift interactions among predators and prey and the where and when encounters occur.</li><li>We examined how white-tailed deer<span>&nbsp;</span><i>Odocoileus virginianus</i><span>&nbsp;</span>fawn spatiotemporal antipredator behaviour differed along an anthropogenic disturbance gradient that had black bears<span>&nbsp;</span><i>Ursus americanus</i>, coyotes<span>&nbsp;</span><i>Canis latrans</i>, bobcats<span>&nbsp;</span><i>Lynx rufus</i><span>&nbsp;</span>and humans present.</li><li>We quantified (a) spatial co-occurrence in species distributions, (b) temporal overlap across the diel cycle and (c) spatiotemporal associations between humans, bears, coyotes, bobcats, adult male deer and fawns. We also examined how deer vigilance behaviour changed across the anthropogenic disturbance gradient and survey duration.</li><li>Anthropogenic disturbance influenced spatiotemporal co-occurrence across multiple scales, often increasing spatiotemporal overlap among species. In general, species’ spatial co-occurrence was neutral or positive in anthropogenically disturbed environments. Bears and fawns, coyotes and adult male deer, and bobcats and fawns all had higher temporal overlap in the agriculture-development matrix sites. In addition, factors that influenced deer vigilance (e.g. distance to forest edge and predator relative abundance) in the agriculture-development matrix sites did not in the forest matrix site.</li><li>By taking into account the different antipredator behaviours that can be detected and the different scales these behaviours might occur, we were able to gain a more comprehensive picture of how humans reduce available niche space for wildlife, creating the neutral and positive spatiotemporal associations between species that studies have been seeing in more disturbed areas.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2656.13548","usgsCitation":"Murphy, A., Diefenbach, D.R., Ternent, M., Lovallo, M., and Miller, D., 2021, Threading the needle: How humans influence predator–prey spatiotemporal interactions in a multiple‐predator system: Journal of Animal Ecology, v. 90, no. 10, p. 2377-2390, https://doi.org/10.1111/1365-2656.13548.","productDescription":"14 p.","startPage":"2377","endPage":"2390","ipdsId":"IP-124481","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":502428,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":481002,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Bald Eagle State Forest, Rothrock State Forest,Susquehannock State Forest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -79.02157116572491,\n              41.972108198483454\n            ],\n            [\n              -79.02157116572491,\n              39.782215061770785\n            ],\n            [\n              -75.79463976505332,\n              39.782215061770785\n            ],\n            [\n              -75.79463976505332,\n              41.972108198483454\n            ],\n            [\n              -79.02157116572491,\n              41.972108198483454\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"90","issue":"10","noUsgsAuthors":false,"publicationDate":"2021-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Asia","contributorId":349218,"corporation":false,"usgs":false,"family":"Murphy","given":"Asia","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":924149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924148,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ternent, Mark","contributorId":349219,"corporation":false,"usgs":false,"family":"Ternent","given":"Mark","affiliations":[{"id":56616,"text":"PA Game Commission","active":true,"usgs":false}],"preferred":false,"id":924150,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lovallo, Matt","contributorId":349220,"corporation":false,"usgs":false,"family":"Lovallo","given":"Matt","affiliations":[{"id":56616,"text":"PA Game Commission","active":true,"usgs":false}],"preferred":false,"id":924151,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, David","contributorId":349221,"corporation":false,"usgs":false,"family":"Miller","given":"David","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":924152,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70220594,"text":"sir20205138 - 2021 - Improving flood-frequency analysis with a 4,000-year record of flooding on the Tennessee River near Chattanooga, Tennessee","interactions":[],"lastModifiedDate":"2021-05-24T11:50:23.066538","indexId":"sir20205138","displayToPublicDate":"2021-05-21T09:15:36","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":"2020-5138","displayTitle":"Improving Flood-Frequency Analysis with a 4,000-Year Record of Flooding on the Tennessee River near Chattanooga, Tennessee","title":"Improving flood-frequency analysis with a 4,000-year record of flooding on the Tennessee River near Chattanooga, Tennessee","docAbstract":"<p class=\"p1\">This comprehensive field study applied paleoflood hydrology methods to estimate the frequency of low-probability floods for the Tennessee River near Chattanooga, Tennessee. The study combined stratigraphic records of large, previously unrecorded floods with modern streamflow records and historical flood accounts. The overall approach was to (1) develop a flood chronology for the Tennessee River near Chattanooga using stratigraphic analyses and geochronology from multiple sites at multiple elevations in the study area; (2) estimate peak flow magnitudes associated with elevations of flood evidence using a one-dimensional hydraulic model; (3) combine the information obtained from steps 1 and 2 to develop a history of timing and magnitude of large floods in the study reach; and (4) use all available information (including paleoflood, gaged, and historical records of flooding) to estimate flood frequency using a standardized statistical approach for flood-frequency analysis.</p><p class=\"p1\">The stratigraphy, geochronology, and hydraulic modeling results from all paleoflood sites along the Tennessee River were distilled into an overall chronology of the number, timing, and magnitude of large unrecorded floods. In total, 30 sites were identified and the stratigraphy of 17 of those sites was closely examined, measured, and recorded. Flood-frequency analyses were done using the U.S. Geological Survey software program PeakFQ v7.2 that follows the Guidelines for Determining Flood Flow Frequency—Bulletin 17C.</p><p class=\"p1\">Resolving stratigraphic and chronologic information from all 17 sites yielded information for eight unique large floods in the last 3,500–4,000 years for the Tennessee River near Chattanooga. Two of these floods had discharges of 470,000 cubic feet per second (ft<sup><span class=\"s1\">3</span></sup>/s), slightly greater than the 1867 historical peak at the Chattanooga streamgage (459,000 ft<sup><span class=\"s1\">3</span></sup>/s). One flood with a discharge of 1,100,000 ft<sup><span class=\"s1\">3</span></sup>/s was substantially greater than any other flood on the Tennessee River during the last several thousand years. This large flood occurred only a few hundred years ago, likely in the mid-to-late 1600s. Two additional floods in the last 1,000 years had estimated magnitudes of about 420,000 and 400,000 ft<sup><span class=\"s1\">3</span></sup>/s. The remaining three unique floods identified in the paleoflood record were much smaller (less than 240,000 ft<sup><span class=\"s1\">3</span></sup>/s) and occurred about 3,000–800 years ago.</p><p class=\"p2\">Flood-frequency analyses show that the addition of paleoflood information markedly improves estimates of low probability floods—most clearly shown by substantial narrowing of the 95-percent confidence limits. For the most plausible flood scenario, the 95-percent confidence interval for the 1,000-year quantile estimate derived from incorporating the four most recent paleofloods is about 480,000–620,000 ft<sup><span class=\"s1\">3</span></sup>/s compared to about 380,000–610,000 ft<sup><span class=\"s1\">3</span></sup>/s for the gaged and historical record alone, a reduction in the uncertainty of the estimate by 38 percent. Similarly, uncertainty for all flood quantile estimates from 100 to 10,000 years was reduced by 22–44 percent by the addition of the paleoflood record to the flood-frequency analyses.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205138","collaboration":"Prepared in cooperation with the Nuclear Regulatory Commission","usgsCitation":"Harden, T.M., O’Connor, J.E., Carr, M.L., and Keith, M., 2021, Improving flood-frequency analysis with a 4,000-year record of flooding on the Tennessee River near Chattanooga, Tennessee: U.S. Geological Survey Scientific Investigations Report 2020–5138, 64 p., https://doi.org/10.3133/sir20205138.","productDescription":"Report: viii, 64 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-116587","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":385808,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5138/coverthb.jpg"},{"id":385809,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5138/sir20205138.pdf","text":"Report","size":"20.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5138"},{"id":385810,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P914SLVM","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Hydraulic modeling and flood-frequency analyses using paleoflood hydrology for the Tennessee River near Chattanooga, Tennessee"}],"country":"United States","state":"Tennessee","city":"Chattanooga","otherGeospatial":"Tennessee River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -85.572509765625,\n              34.96699890670367\n            ],\n            [\n              -85.0286865234375,\n              34.96699890670367\n            ],\n            [\n              -85.0286865234375,\n              35.191766965947394\n            ],\n            [\n              -85.572509765625,\n              35.191766965947394\n            ],\n            [\n              -85.572509765625,\n              34.96699890670367\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_or@usgs.gov\" data-mce-href=\"mailto:dc_or@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/or-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/or-water\">Oregon Water Science Center</a><br>U.S. Geological Survey<br>2130 SW 5th Avenue<br>Portland, Oregon 97201</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Paleoflood Hydrology</li><li>Description of Study Area</li><li>Methods of Investigation</li><li>Stratigraphic Analysis and Site Paleoflood Chronologies</li><li>Overall Paleoflood Chronology—Number, Magnitude, and Timing</li><li>Flood-Frequency Analysis</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Stratigraphic Descriptions of Supporting Paleoflood Sites</li></ul>","publishedDate":"2021-05-21","noUsgsAuthors":false,"publicationDate":"2021-05-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Harden, Tessa M. 0000-0001-9854-1347 tharden@usgs.gov","orcid":"https://orcid.org/0000-0001-9854-1347","contributorId":192153,"corporation":false,"usgs":true,"family":"Harden","given":"Tessa","email":"tharden@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816110,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":816111,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carr, Meredith L. 0000-0003-1970-8511","orcid":"https://orcid.org/0000-0003-1970-8511","contributorId":238712,"corporation":false,"usgs":false,"family":"Carr","given":"Meredith","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":816112,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keith, Mackenzie 0000-0002-7239-0576 mkeith@usgs.gov","orcid":"https://orcid.org/0000-0002-7239-0576","contributorId":258250,"corporation":false,"usgs":false,"family":"Keith","given":"Mackenzie","email":"mkeith@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":816113,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70224334,"text":"70224334 - 2021 - Robust projections of future fire probability for the conterminous United States","interactions":[],"lastModifiedDate":"2021-09-23T12:28:04.656418","indexId":"70224334","displayToPublicDate":"2021-05-21T07:25:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Robust projections of future fire probability for the conterminous United States","docAbstract":"<div id=\"ab0005\" class=\"abstract author\"><div id=\"as0005\"><p id=\"sp0040\"><span>Globally increasing wildfires have been attributed to anthropogenic climate change. However, providing decision makers with a clear understanding of how future planetary warming could affect fire regimes is complicated by confounding land use factors that influence wildfire and by uncertainty associated with model simulations of climate change. We use an ensemble of statistically downscaled Global Climate Models in combination with the Physical Chemistry Fire Frequency Model (PC2FM) to project changing potential fire probabilities in the conterminous United States for two scenarios representing lower (RCP 4.5) and higher (RCP 8.5)&nbsp;greenhouse gas emission&nbsp;futures. PC2FM is a physically-based and scale-independent model that predicts mean fire return intervals from both fire reactant and reaction variables, which are largely dependent on a locale's climate. Our results overwhelmingly depict increasing potential fire probabilities across the conterminous US for both climate scenarios. The primary mechanism for the projected increases is rising temperatures, reflecting changes in the chemical reaction environment commensurate with enhanced photosynthetic rates and available thermal molecular energy. Existing high risk areas, such as the Cascade Range and the Coastal California Mountains, are projected to experience greater annual fire occurrence probabilities, with relative increases of 122% and 67%, respectively, under RCP 8.5 compared to increases of 63% and 38% under RCP 4.5. Regions not currently associated with frequently occurring wildfires, such as New England and the Great Lakes, are projected to experience a doubling of occurrence probabilities by 2100 under RCP 8.5. This high resolution, continental-scale modeling study of&nbsp;</span>climate change impacts<span>&nbsp;</span>on potential fire probability accounts for shifting background environmental conditions across regions that will interact with topographic drivers to significantly alter future fire probabilities. The ensemble modeling approach presents a useful planning tool for mitigation and adaptation strategies in regions of increasing wildfire risk.</p></div></div><div id=\"ab0010\" class=\"abstract graphical\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.147872","usgsCitation":"Gao, P., Terando, A., Kupfer, J., Varner, J., Stambaugh, M.C., Lei, T.L., and Hiers, J.K., 2021, Robust projections of future fire probability for the conterminous United States: Science of the Total Environment, v. 789, 147872, 13 p., https://doi.org/10.1016/j.scitotenv.2021.147872.","productDescription":"147872, 13 p.","ipdsId":"IP-126842","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":452181,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2021.147872","text":"Publisher Index 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         -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"789","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gao, Peng","contributorId":224731,"corporation":false,"usgs":false,"family":"Gao","given":"Peng","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":823787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terando, Adam J. 0000-0002-9280-043X","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":216875,"corporation":false,"usgs":true,"family":"Terando","given":"Adam J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":823788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kupfer, John A","contributorId":224730,"corporation":false,"usgs":false,"family":"Kupfer","given":"John A","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":823790,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Varner, J. Morgan","contributorId":265933,"corporation":false,"usgs":false,"family":"Varner","given":"J. Morgan","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":823791,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stambaugh, Michael C.","contributorId":202826,"corporation":false,"usgs":false,"family":"Stambaugh","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":13706,"text":"University of Missouri-Columbia","active":true,"usgs":false}],"preferred":false,"id":823792,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lei, Ting L","contributorId":265934,"corporation":false,"usgs":false,"family":"Lei","given":"Ting","email":"","middleInitial":"L","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":823793,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hiers, J. Kevin","contributorId":224733,"corporation":false,"usgs":false,"family":"Hiers","given":"J.","email":"","middleInitial":"Kevin","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":823789,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70220480,"text":"sir20205133 - 2021 - Sediment budget for watersheds of West Maui, Hawaii","interactions":[],"lastModifiedDate":"2021-05-21T15:15:51.254453","indexId":"sir20205133","displayToPublicDate":"2021-05-21T07:16:09","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":"2020-5133","displayTitle":"Sediment Budget for Watersheds of West Maui, Hawaii","title":"Sediment budget for watersheds of West Maui, Hawaii","docAbstract":"<p>Episodic runoff brings suspended sediment to West Maui’s nearshore waters, turning them from blue to brown. This pollution degrades the ecological, cultural, and recreational value of these iconic nearshore waters. We used mapping, monitoring, and modeling to identify and quantify the watershed sources for fine sediment that pollutes the nearshore each year. These results focus strategies to reduce pollution on the outstanding sources for this sediment.</p><p>Terrestrial runoff causing coastal plumes now occurs when two or more hours of rain falls at rates greater than 10–20 millimeter (mm) per hour in source watersheds. Analysis of recent and historical rainfall indicates that West Maui communities can expect rainfalls to bring coastal plumes at least 3–5 times per year. Former agricultural fields and some unimproved roads are possible sources for the fine sediment of these plumes. We found, however, that these obvious sources do not produce plumes during small annual storms, because they drain water at rates that far exceed most annual rainfalls and because there is no evidence for runoff from rains that caused recent plumes. Streambanks now eroding into historic fill terraces of sands, silts, and clays are a more plausible source. These terraces are found only downstream of historical agricultural fields and are composed of silt and fine sand. Surveys show that the fill terraces occupy ~40 percent of streambank length, making them extensive. During 2015–2016, these deposits eroded at median rates of 5–24 mm per year. Summed over West Maui’s watersheds, these rates imply sediment loads carried to the coast that can be ten times or more than modeled pre-human values. A sediment budget indicates that bank erosion of fill terraces from a few watersheds likely dominates the current annual fine-sediment load to the nearshore, with Kahana Stream watershed producing the largest annual input of 285 metric tons, the equivalent of 29 dump-truck loads every year.</p><p>Although past large storms have contributed to sediment loading, annual plume generation is now caused by smaller rainfalls eroding these near-stream terrace deposits, a legacy of historic agriculture. Treatments of former agricultural fields, roads, and reserve forests are consequently not likely to measurably effect sediment pollution from smaller, more frequent storms. Increased runoff from residential and commercial development of West Maui has the potential to exacerbate sediment plumes from such storms.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205133","usgsCitation":"Stock, J.D., and Cerovski-Darriau, Corina, 2021, Sediment budget for watersheds of West Maui, Hawaii: U.S. Geological Survey Scientific Investigations Report 2020–5133, 61 p., 1 plate, scale 1:25,000, https://doi.org/10.3133/sir20205133.","productDescription":"Report: xi, 61 p.; 1 Plate: 28.50 x 30 inches","numberOfPages":"61","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-105315","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":385647,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5133/covrthb.jpg"},{"id":385648,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5133/sir20205133.pdf","text":"Report","size":"25 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":385649,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2020/5133/sir20205133_plate.pdf","text":"Plate","size":"17 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Hawaii","otherGeospatial":"West Maui","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -156.75018310546875,\n              20.776659051878816\n            ],\n            [\n              -156.5496826171875,\n              20.776659051878816\n            ],\n            [\n              -156.5496826171875,\n              21.022982546427425\n            ],\n            [\n              -156.75018310546875,\n              21.022982546427425\n            ],\n            [\n              -156.75018310546875,\n              20.776659051878816\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/gmeg/employee-directory\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg/employee-directory\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/gmeg\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Geology, Minerals, Energy, &amp; Geophysics Science Center</a><br><a href=\"https://www.usgs.gov/centers/gmeg\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Menlo Park, California</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey</a><br>345 Middlefield Road<br>Menlo Park, CA 94025-3591</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Conclusion</li><li>References Cited</li><li>Appendix</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2021-05-21","noUsgsAuthors":false,"publicationDate":"2021-05-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Stock, Jonathan D. 0000-0001-8565-3577 jstock@usgs.gov","orcid":"https://orcid.org/0000-0001-8565-3577","contributorId":3648,"corporation":false,"usgs":true,"family":"Stock","given":"Jonathan","email":"jstock@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":815693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cerovski-Darriau, Corina 0000-0002-0543-0902","orcid":"https://orcid.org/0000-0002-0543-0902","contributorId":221159,"corporation":false,"usgs":true,"family":"Cerovski-Darriau","given":"Corina","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":815694,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70221495,"text":"70221495 - 2021 - Sources of volcanic tremor associated with the summit caldera collapse during the 2018 east rift eruption of Kīlauea Volcano, Hawai'i","interactions":[],"lastModifiedDate":"2021-06-21T11:42:17.813341","indexId":"70221495","displayToPublicDate":"2021-05-21T06:50:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Sources of volcanic tremor associated with the summit caldera collapse during the 2018 east rift eruption of Kīlauea Volcano, Hawai'i","docAbstract":"<div class=\"article-section__content en main\"><p>Volcanic tremor occurring at the beginning of the 2018 Kīlauea eruption is characterized using both seismic and tilt data recorded at the Kīlauea summit. An automatic seismic network-based approach detects several types of tremor including (a) 0.5–1&nbsp;Hz long-period tremor preceding the eruption, located at the south-southwest edge of Halema'uma'u Crater and attributed to the quasi-steady radiation from a shallow hydrothermal system and (b) two sequences of gliding tremor at the beginning of the eruption, both with locations on the edges of the crater and within it. The first sequence is attributed to two swarms of low-amplitude regularly repeating earthquakes induced by the jerky motions of a cylindrical rock piston with radius of 325&nbsp;m, height of 250&nbsp;m, and mass of 2.07&nbsp;×&nbsp;10<sup>11</sup>&nbsp;kg, progressively intruding 12.3&nbsp;m into the shallow hydrothermal system with volume of 10<sup>8</sup>&nbsp;m<sup>3</sup><span>&nbsp;</span>and depth extent of 300&nbsp;m. The second sequence is attributed to a gradual evolution in the properties of a bubbly magma within an east-striking dike below Halema'uma'u Crater, impacted by repeated roof collapses. A fluid-filled crack model points to a decrease in gas volume fraction from 4.22% to 1.6&nbsp;×&nbsp;10<sup>−2</sup>% in the magma filling the dike, and a model of gas retro-diffusion within the melt suggests a two orders of magnitude decrease in bubble number density from 7&nbsp;×&nbsp;10<sup>8</sup>&nbsp;m<sup>−3</sup><span>&nbsp;</span>down to 4&nbsp;×&nbsp;10<sup>6</sup>&nbsp;m<sup>−3</sup>. Both models feature a quasi to totally degassed magma by May 26.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB021572","usgsCitation":"Soubestre, J., Chouet, B., and Dawson, P.B., 2021, Sources of volcanic tremor associated with the summit caldera collapse during the 2018 east rift eruption of Kīlauea Volcano, Hawai'i: Journal of Geophysical Research: Solid Earth, v. 126, no. 6, e2020JB021572, 33 p., https://doi.org/10.1029/2020JB021572.","productDescription":"e2020JB021572, 33 p.","ipdsId":"IP-125499","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":386584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.35423278808594,\n              19.20288950660437\n            ],\n            [\n              -155.00885009765625,\n              19.20288950660437\n            ],\n            [\n              -155.00885009765625,\n              19.480186937661344\n            ],\n            [\n              -155.35423278808594,\n              19.480186937661344\n            ],\n            [\n              -155.35423278808594,\n              19.20288950660437\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"126","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Soubestre, J. 0000-0002-9403-8821","orcid":"https://orcid.org/0000-0002-9403-8821","contributorId":260399,"corporation":false,"usgs":false,"family":"Soubestre","given":"J.","email":"","affiliations":[{"id":52584,"text":"Instituto Volcanologico de Canarias (INVOLCAN)","active":true,"usgs":false}],"preferred":false,"id":817860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chouet, B. 0000-0001-5527-0532","orcid":"https://orcid.org/0000-0001-5527-0532","contributorId":260400,"corporation":false,"usgs":false,"family":"Chouet","given":"B.","affiliations":[{"id":52585,"text":"Retired (USGS)","active":true,"usgs":false}],"preferred":false,"id":817861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dawson, Phillip B. 0000-0003-4065-0588 dawson@usgs.gov","orcid":"https://orcid.org/0000-0003-4065-0588","contributorId":206751,"corporation":false,"usgs":true,"family":"Dawson","given":"Phillip","email":"dawson@usgs.gov","middleInitial":"B.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":817862,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70220582,"text":"ofr20201147 - 2021 - GIS-based identification of areas that have resource potential for sediment-hosted Pb-Zn deposits in Alaska","interactions":[],"lastModifiedDate":"2021-05-21T14:58:21.181526","indexId":"ofr20201147","displayToPublicDate":"2021-05-20T18:00:00","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":"2020-1147","displayTitle":"GIS-Based Identification of Areas that have Resource Potential for Sediment-hosted Pb-Zn deposits in Alaska","title":"GIS-based identification of areas that have resource potential for sediment-hosted Pb-Zn deposits in Alaska","docAbstract":"<p>A state-wide Geographic Information System analysis was conducted to assess prospectivity for lead (Pb) and zinc (Zn) in sediment-hosted deposits in Alaska. The datasets that were utilized include publicly available geospatial datasets of lithologic, geochemical, and mineral occurrence data. Key characteristics of Pb-Zn deposits were identified in available datasets and scored with respect to relative importance. To evaluate resource potential, drainage basins of the smallest size were chosen, each of which covers approximately 100 square kilometers (km<sup>2</sup>). Drainage basins are the most logical and efficient unit for evaluation because the most regionally robust dataset comes from stream sediment geochemistry.</p><p>Sediment-hosted Pb-Zn deposits in Alaska include those contained in carbonate rocks (similar to Mississippi Valley Type or MVT deposits) and those contained in clastic-dominated (CD) sequences (CD Pb-Zn), historically referred to as SEDEX (sedimentary exhalative). The latter include the deposits currently being mined in the Red Dog district in the western Brooks Range. Host rocks for the two subtypes are distinct: carbonate versus fine-grained clastic rocks for CD Pb-Zn deposits. However, there are exceptions: some CD Pb-Zn deposits are hosted in carbonate layers within a thick clastic-dominated rock sequence. The statewide geologic map database contains units that commonly include mixed carbonate-clastic sequences that cannot be subdivided. The most significant difference between the two deposit types is their respective depositional environments and tectonic settings, but at the reconnaissance level of mapping in most areas of the state, these distinctions are not possible. Furthermore, nearly all critical geochemical parameters (silver [Ag], barium [Ba], Pb, Zn) are common to both types, and therefore it was not possible to do separate assessments for carbonate-hosted and CD Pb-Zn deposits.</p><p>Areas identified that have moderate to high potential for sediment-hosted Pb-Zn deposits include the (1) western and central Brooks Range, referred to in this report as the Brooks Range zinc belt; (2) Seward Peninsula (and adjacent St. Lawrence Island); (3) Farewell terrane in Interior Alaska; (4) two spatially distinct belts in east-central Alaska; and (5) the central Alaska Range. All areas contain some known deposits, and that provides credibility to the scoring process. Some hydrologic unit codes (HUCs) that have high potential for sediment-hosted Pb-Zn deposits are located adjacent to areas of known deposits and indicate the potential for expansion of known Pb-Zn districts. There are a few areas that have high potential but contain no known sediment hosted Pb-Zn occurrences, prospects, or deposits. In such areas, future investigations could be focused on better defining and constraining prospectivity with additional data.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20201147","usgsCitation":"Kelley, K.D., Graham, G.E., Labay, K.A., and Shew, N.B., 2021, GIS-based identification of areas that have resource potential for sediment-hosted Pb-Zn deposits in Alaska: U.S. Geological Survey Open-File Report 2020−1147, 37 p.,  1 app., 2 pls., scale 1:10,500,000, https://doi.org/10.3133/ofr20201147.","productDescription":"Report: v, 37 p.; 2 Plates: 15.41 x 15.11 inches and 15.53 x 15.17 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-105816","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":385779,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1147/coverthb_pamphlet.jpg"},{"id":385780,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1147/ofr20201147_pamphlet.pdf","text":"Report","size":"2.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1147 pamphlet"},{"id":385781,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2020/1147/ofr20201147_plate1.pdf","text":"Plate 1—","size":"8.87 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1147 Plate 1","linkHelpText":"Estimated Resource Potential and Certainty for  Sediment-Hosted Pb-Zn Deposits"},{"id":385782,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2020/1147/ofr20201147_plate2.pdf","text":"Plate 2—","size":"7.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1147 Plate 2","linkHelpText":"Permissive Rock Types and Known Sediment-Hosted  Pb-Zn Deposits"},{"id":385783,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P943BUQZ","text":"USGS data release","linkHelpText":"Data and results for GIS-based identification of areas that have resource potential for sediment-hosted Pb-Zn deposits in Alaska"},{"id":385784,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/ofr20161191","text":"USGS Open-File Report 2016-1191—","linkHelpText":"GIS-based identification of areas that have resource potential for critical minerals in six selected groups of deposit types in Alaska"}],"country":"United 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<a href=\"https://www.usgs.gov/centers/gggsc\" data-mce-href=\"https://www.usgs.gov/centers/gggsc\">Geology, Geophysics, and Geochemistry Science Center</a><br>U.S. Geological Survey<br>MS 973, Box 25046<br>Denver, CO 80225</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Sediment-hosted Pb-Zn Deposit Definitions</li><li>Analytical Process and Data Sources</li><li>GIS-Based Methods</li><li>Mineral Resource Potential Estimation Method</li><li>Results and Discussion</li><li>Summary and Conclusions</li><li>References Cited</li><li>Appendix 1. Boxplots of select elements in rock samples from areas with high potential</li></ul>","publishedDate":"2021-05-20","noUsgsAuthors":false,"publicationDate":"2021-05-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kelley, Karen D. 0000-0002-3232-5809 kdkelley@usgs.gov","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":179012,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":816084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Garth E. 0000-0003-0657-0365 ggraham@usgs.gov","orcid":"https://orcid.org/0000-0003-0657-0365","contributorId":1031,"corporation":false,"usgs":true,"family":"Graham","given":"Garth","email":"ggraham@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":816085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Labay, Keith A. 0000-0002-6763-3190 klabay@usgs.gov","orcid":"https://orcid.org/0000-0002-6763-3190","contributorId":217714,"corporation":false,"usgs":true,"family":"Labay","given":"Keith","email":"klabay@usgs.gov","middleInitial":"A.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":816086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shew, Nora B. 0000-0003-0025-7220 nshew@usgs.gov","orcid":"https://orcid.org/0000-0003-0025-7220","contributorId":3382,"corporation":false,"usgs":true,"family":"Shew","given":"Nora","email":"nshew@usgs.gov","middleInitial":"B.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":816087,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70228361,"text":"70228361 - 2021 - Modeling effects of disturbance across life history strategies of stream fishes","interactions":[],"lastModifiedDate":"2022-02-09T17:16:52.980052","indexId":"70228361","displayToPublicDate":"2021-05-20T11:11:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Modeling effects of disturbance across life history strategies of stream fishes","docAbstract":"A central goal of population ecology is to establish linkages between life history strategy, disturbance, and population dynamics. Globally, disturbance events such as drought and invasive species have dramatically impacted stream fish populations and contributed to sharp declines in freshwater biodiversity. Here, we used RAMAS-Metapop to construct stage-based demographic metapopulation models for stream fishes with periodic, opportunistic, and equilibrium life history strategies and assessed their responses to disturbance scenarios that approximated the effects of invasion, drought, and the additive effects of both disturbances. Our models indicated that populations respond differentially to disturbance based on life history strategy. Equilibrium strategists were best able to deal with simulated invasion. Periodic strategists did well under lower levels of drought, whereas opportunistic strategists outperformed other life histories under extreme seasonal drought. When we modeled additive effects scenarios, these disturbances interacted synergistically, dramatically increasing terminal extinction risk for all three life history strategies. Modeling exercises that examine broad life history categories can help to answer fundamental ecological questions about the relationship between disturbance resilience and life history, as well as help managers to develop generalized conservation strategies when species-specific data are lacking.  Our results indicate that life history strategy is a fundamental determinant of population trajectories, and that disturbances can interact synergistically to dramatically impact extinction outcomes.","language":"English","publisher":"Springer","doi":"10.1007/s00442-021-04941-8","usgsCitation":"Fournier, R.J., Bond, N.R., and Magoulick, D.D., 2021, Modeling effects of disturbance across life history strategies of stream fishes: Oecologia, v. 196, p. 413-425, https://doi.org/10.1007/s00442-021-04941-8.","productDescription":"13 p.","startPage":"413","endPage":"425","ipdsId":"IP-111010","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"196","noUsgsAuthors":false,"publicationDate":"2021-05-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Fournier, Robert J.","contributorId":244358,"corporation":false,"usgs":false,"family":"Fournier","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":833949,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bond, Nick R.","contributorId":275297,"corporation":false,"usgs":false,"family":"Bond","given":"Nick","email":"","middleInitial":"R.","affiliations":[{"id":24850,"text":"La Trobe university","active":true,"usgs":false}],"preferred":false,"id":833950,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","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":833951,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70230774,"text":"70230774 - 2021 - Stress controls rupture extent and maximum magnitude of induced earthquakes","interactions":[],"lastModifiedDate":"2022-04-26T15:28:05.269094","indexId":"70230774","displayToPublicDate":"2021-05-20T10:24:54","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":"Stress controls rupture extent and maximum magnitude of induced earthquakes","docAbstract":"<p><span>Seismic hazard forecasts of induced seismicity often require estimates of the maximum possible magnitude (</span><i>M</i><sub>max</sub><span>). Empirical models suggest that maximum magnitudes, or expected number of earthquakes, are related to the volume of injected fluid. We perform a suite of 3D physics-based earthquake simulations with rate- and state-dependent friction, systematically varying the area of the pressurized region and the amplitude of the initial homogeneous or heterogeneous shear stress. Using the resulting catalog we explore the conditions that result in pressure-controlled versus runaway ruptures that extend outside the pressurized zone. We find that proposed empirical scaling laws correctly predict&nbsp;</span><i>M</i><sub>max</sub><span>&nbsp;when shear stresses are further from failure (≤90% of maximum shear stress) and for high amplitude stress fields. Runaway ruptures are observed for higher initial shear stresses and smoother stress fields. In these cases, runaway ruptures occur early after the onset of injection and rarely preceded by foreshock activity.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL092148","usgsCitation":"Kroll, K.A., and Cochran, E.S., 2021, Stress controls rupture extent and maximum magnitude of induced earthquakes: Geophysical Research Letters, v. 48, no. 11, e2020GL092148, 10 p., https://doi.org/10.1029/2020GL092148.","productDescription":"e2020GL092148, 10 p.","ipdsId":"IP-127145","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":452195,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1785427","text":"Publisher Index Page"},{"id":399673,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kroll, K. A.","contributorId":290588,"corporation":false,"usgs":false,"family":"Kroll","given":"K.","email":"","middleInitial":"A.","affiliations":[{"id":16721,"text":"LLNL","active":true,"usgs":false}],"preferred":false,"id":841341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":841342,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70269376,"text":"70269376 - 2021 - An empirically based simulation model to inform flow management for endangered species conservation","interactions":[],"lastModifiedDate":"2025-07-21T14:36:27.500642","indexId":"70269376","displayToPublicDate":"2021-05-20T09:33:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"An empirically based simulation model to inform flow management for endangered species conservation","docAbstract":"<p><span>Increasing water demand, water development, and ongoing climate change have driven extensive changes to the hydrology, geomorphology and biology of arid-land rivers globally, driving an increasing need to understand how annual hydrologic conditions affect the distribution and abundance of imperiled desert fish populations. We analyzed the relationship between annual hydrologic conditions and the endangered Rio Grande silvery minnow (</span><i>Hybognathus amarus</i><span>) in the Middle Rio Grande, New Mexico, USA, using hurdle models to predict both presence and density as a function of integrated annual hydrologic metrics. Both presence and density were positively related to spring high flow magnitude and duration and negatively related to summer drying, as indicated by an integrated flow metric. Simulations suggest hydrologic conditions near the wettest observed in the data set would be required to meet recovery goals in a single year in all reaches. We demonstrate how the models developed herein can be used to examine alternative water management strategies, including strategies that may currently be socially and logistically infeasible to implement, to identify strategies minimizing trade-offs between conservation and other management goals.</span></p>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2020-0353","usgsCitation":"Walsworth, T., and Budy, P., 2021, An empirically based simulation model to inform flow management for endangered species conservation: Canadian Journal of Fisheries and Aquatic Sciences, v. 78, no. 12, p. 1770-1781, https://doi.org/10.1139/cjfas-2020-0353.","productDescription":"12 p.","startPage":"1770","endPage":"1781","ipdsId":"IP-121942","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":492624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Middle Rio Grande","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.70549244802783,\n              35.898256634325534\n            ],\n            [\n              -107.7975020546316,\n              35.898256634325534\n            ],\n            [\n              -107.7975020546316,\n              33.04558932070461\n            ],\n            [\n              -105.70549244802783,\n              33.04558932070461\n            ],\n            [\n              -105.70549244802783,\n              35.898256634325534\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"78","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walsworth, Timothy E.","contributorId":358375,"corporation":false,"usgs":false,"family":"Walsworth","given":"Timothy E.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":943609,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":943608,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70221711,"text":"70221711 - 2021 - Development of soil radiocarbon profiles in a reactive transport framework","interactions":[],"lastModifiedDate":"2021-06-29T13:58:18.394862","indexId":"70221711","displayToPublicDate":"2021-05-20T08:54:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Development of soil radiocarbon profiles in a reactive transport framework","docAbstract":"<p><span>Today, there is a greater appreciation for the importance of the physical protection of carbon (C) through interactions with mineral surfaces, isolation from&nbsp;microbes, and the important role of transport in shaping&nbsp;soil properties&nbsp;and controlling moisture limitations on decomposition. As our paradigm for soil&nbsp;organic carbon&nbsp;(SOC) preservation changes, so too should our representation of the underlying processes in soil models. Reactive transport models (RTMs) provide a framework capable of assessing the interactive influence of soil chemistry and transport processes on the accumulation and turnover of SOC. In this study, we present new developments in the isotopically enabled RTM “CrunchTope,” which is capable of explicitly tracking the three isotopes of carbon (</span><sup>12</sup><span>C,&nbsp;</span><sup>13</sup><span>C, and&nbsp;</span><sup>14</sup><span>C) and their fractionation between multiple coexisting and interacting solid, liquid and gas phases. This modeling framework opens the door to new applications of depth-resolved RTMs models in application to SOC and deeper subsurface carbon reservoirs. Here, we demonstrate SOC accumulation and radiocarbon aging for long-timescale models of soil development in CrunchTope. Our goal is to assess advantages and limitations of such an approach and to identify the type and complexity of reaction networks that are required to adequately apply this model to&nbsp;SOC dynamics. We assess the behavior of this model relative to a high-resolution dataset of SOC content,&nbsp;stable isotope&nbsp;composition, and radiocarbon ages as well as physical and hydrologic data measured from a&nbsp;chronosequence&nbsp;of soils located near Santa Cruz, California. Starting from a previously published model using a simplified reaction network with a single class of carbon, we sequentially incorporate multiple C reservoirs subject to both reactivity and transport pathways. Our results indicate that multiple SOC pools with different mean ages of C do not inherently emerge as a result of including reactions which are conventionally expected to provide a diversity of transit times, i.e.,&nbsp;sorption&nbsp;and complexation of SOC on mineral surfaces. Instead, transit times emerge as a result of the timescales of the reactions represented in the reaction network. For mineral associated C, the RTM framework imposes dynamic equilibrium with the fluid phase dissolved organic C, such that no distinction in radiocarbon ages is achieved between these pools. Aged C can be produced by including a solid-phase C reservoir, with a rate-limited&nbsp;solubilization&nbsp;coefficient. Aging of SOC in this way is more akin to selective preservation than to mineral protection and, while such a mechanism may be at play in many soils, mineral protection is thought to be at least as important. As such, our results indicate that additional parameterization is required to reproduce the heterogeneity of carbon transit times that result from organo-mineral interactions. These efforts show the promise of a modeling approach where the varied transit time of soil C emerges from the dynamic physical and hydrologic properties of the model rather than from the&nbsp;</span><i>a priori</i><span>&nbsp;assignment of operationally defined pools.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2021.05.021","usgsCitation":"Druhan, J., and Lawrence, C., 2021, Development of soil radiocarbon profiles in a reactive transport framework: Geochimica et Cosmochimica Acta, v. 306, no. 1, p. 63-83, https://doi.org/10.1016/j.gca.2021.05.021.","productDescription":"21 p.","startPage":"63","endPage":"83","ipdsId":"IP-118940","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":452196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2021.05.021","text":"Publisher Index Page"},{"id":386847,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"306","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Druhan, Jennifer","contributorId":260703,"corporation":false,"usgs":false,"family":"Druhan","given":"Jennifer","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":818494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Corey 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202373,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":818495,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70220541,"text":"ofr20211047 - 2021 - Science needs of southeastern grassland species of conservation concern: A framework for species status assessments","interactions":[],"lastModifiedDate":"2021-09-13T18:27:03.858532","indexId":"ofr20211047","displayToPublicDate":"2021-05-20T07:06:51","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1047","displayTitle":"Science Needs of Southeastern Grassland Species of Conservation Concern: A Framework for Species Status Assessments","title":"Science needs of southeastern grassland species of conservation concern: A framework for species status assessments","docAbstract":"<p>The unglaciated southeastern United States is a biodiversity hotspot, with a disproportionate amount of this biodiversity concentrated in grasslands. Like most hotspots, the Southeast is also threatened by human activities, with the total reduction of southeastern grasslands estimated as 90 percent (upwards to 100 percent for some types) and with many threats escalating today. This report summarizes the results of a multistakeholder workshop organized by the Southeastern Grasslands Initiative and the U.S. Geological Survey, held in January 2020 to provide a scientific needs assessment to help inform the Species Status Assessment (SSA) process under the U.S. Endangered Species Act, with a focus on grassland species and communities of conservation concern in the southeastern United States. This report reviews the ecology of southeastern grasslands, including influences on their origin, maintenance, and high species richness and endemism; presents findings from the workshop; and discusses science questions, hypotheses, and possibilities for future research projects to help fill key knowledge gaps.</p><p>Participants in the January 2020 workshop, representing diverse expertise in various topics in southeastern grassland ecology, were tasked with identifying major threats to grassland species in the Southeast as well as potential ways to make the SSA process more efficient and effective. An underlying assumption and starting place for workshop discussion was that an ecosystem-based approach to the SSA process is more cost-efficient than a species-by-species approach, in large part because many species with similar biological requirements can be addressed by the same actions. Nevertheless, one partner in this effort, the U.S. Fish and Wildlife Service, does require specific attention be given to taxa that have been petitioned for Federal listing, though as often as possible these taxa are considered alongside a larger group of priority taxa with an ecosystem approach.</p><p>For group discussions, workshop participants followed a modified “World Café” method, a structured conversational approach for knowledge sharing. Group discussions focused on five categories of threats to grassland communities and species: (1) habitat loss, fragmentation, and disruption of functional population connectivity; (2) climate change, especially changes in temperature and precipitation, including intensity and seasonality, and impacts on soil moisture, groundwater levels, and other ecosystem parameters; (3) changes to disturbance regimes, as influenced by climate and land-use change, extinctions, and human attitudes and behaviors; (4) invasive species (not limited to nonnative species); and (5) localized or subregional impacts such as sea-level rise. In addition to group discussions, workshop participants—as well as other grassland experts who were unable to attend the workshop—completed a preworkshop survey concerning challenges and opportunities for grassland conservation. Findings reported here under each of these topics represent ideas, problems, hypotheses, and questions identified by a diverse community of grassland managers and researchers which may be addressed by future research and monitoring in southeastern grassland ecosystems to help guide science-based conservation of grassland-dependent species.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211047","collaboration":"Prepared in cooperation with the Department of the Interior Southeast Climate Adaptation Science Center","usgsCitation":"Noss, R.F., Cartwright, J.M., Estes, D., Witsell, T., Elliott, K.G., Adams, D.S., Albrecht, M.A., Boyles, R., Comer, P.J., Doffitt, C., Faber-Langendoen, D., Hill, J.G., Hunter, W.C., Knapp, W.M., Marshall, M., Pyne, M., Singhurst, J.R., Tracey, C., Walck, J.L., and Weakley, A., 2021, Science needs of southeastern grassland species of conservation concern—A framework for species status assessments: U.S. Geological Survey Open-File Report 2021–1047, 58 p., https://doi.org/10.3133/ofr20211047.","productDescription":"ix, 58 p.","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-122270","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":385785,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1047/images"},{"id":385732,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1047/ofr20211047.pdf","text":"Report","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1047"},{"id":385731,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1047/coverthb.jpg"}],"country":"United States","state":"Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, Tennessee, Virginia, South 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 \"}}]}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/lmg-water\" href=\"https://www.usgs.gov/centers/lmg-water\">Lower Mississippi-Gulf Water Science Center</a><br>U.S. Geological Survey<br>640 Grassmere Park Drive <br>Nashville, TN 37211<br></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Results: Science and Information Needed To Support Conservation of Southeastern Grasslands</li><li>References Cited</li><li>Glossary</li><li>Appendix 1. Grassland Ecosystems of the Southeastern United States</li><li>Appendix 2. Southeastern Climate and Grasslands Workshop: Summary of Survey Results</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2021-05-20","noUsgsAuthors":false,"publicationDate":"2021-05-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Noss, Reed F. 0000-0003-2997-4688","orcid":"https://orcid.org/0000-0003-2997-4688","contributorId":98615,"corporation":false,"usgs":true,"family":"Noss","given":"Reed","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":815922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cartwright, Jennifer M. 0000-0003-0851-8456 jmcart@usgs.gov","orcid":"https://orcid.org/0000-0003-0851-8456","contributorId":5386,"corporation":false,"usgs":true,"family":"Cartwright","given":"Jennifer","email":"jmcart@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":815923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Estes, Dwayne 0000-0003-1088-7082","orcid":"https://orcid.org/0000-0003-1088-7082","contributorId":112194,"corporation":false,"usgs":true,"family":"Estes","given":"Dwayne","email":"","affiliations":[],"preferred":false,"id":815924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Witsell, Theo","contributorId":258187,"corporation":false,"usgs":false,"family":"Witsell","given":"Theo","email":"","affiliations":[],"preferred":false,"id":815925,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elliott, K. Gregg","contributorId":258188,"corporation":false,"usgs":false,"family":"Elliott","given":"K.","email":"","middleInitial":"Gregg","affiliations":[],"preferred":false,"id":815926,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adams, Daniel S. 0000-0001-9695-0577","orcid":"https://orcid.org/0000-0001-9695-0577","contributorId":258189,"corporation":false,"usgs":false,"family":"Adams","given":"Daniel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":815927,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Albrecht, Matthew A. 0000-0002-1079-1630","orcid":"https://orcid.org/0000-0002-1079-1630","contributorId":213559,"corporation":false,"usgs":false,"family":"Albrecht","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":38790,"text":"Missouri Botanical Garden","active":true,"usgs":false}],"preferred":false,"id":815928,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boyles, Ryan P. 0000-0001-9272-867X rboyles@usgs.gov","orcid":"https://orcid.org/0000-0001-9272-867X","contributorId":197670,"corporation":false,"usgs":true,"family":"Boyles","given":"Ryan","email":"rboyles@usgs.gov","middleInitial":"P.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":815929,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Comer, Patrick J. 0000-0002-5869-2105","orcid":"https://orcid.org/0000-0002-5869-2105","contributorId":258190,"corporation":false,"usgs":false,"family":"Comer","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":815930,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Doffitt, Chris","contributorId":258191,"corporation":false,"usgs":false,"family":"Doffitt","given":"Chris","email":"","affiliations":[],"preferred":false,"id":815931,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Faber-Langendoen, Don 0000-0002-2630-6898","orcid":"https://orcid.org/0000-0002-2630-6898","contributorId":258192,"corporation":false,"usgs":false,"family":"Faber-Langendoen","given":"Don","email":"","affiliations":[],"preferred":false,"id":815932,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hill, JoVonn G. 0000-0002-1892-7117","orcid":"https://orcid.org/0000-0002-1892-7117","contributorId":258193,"corporation":false,"usgs":false,"family":"Hill","given":"JoVonn","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":815933,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hunter, William C.","contributorId":258194,"corporation":false,"usgs":false,"family":"Hunter","given":"William","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":815934,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Knapp, Wesley M. 0000-0002-5289-5649","orcid":"https://orcid.org/0000-0002-5289-5649","contributorId":258195,"corporation":false,"usgs":false,"family":"Knapp","given":"Wesley","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":815935,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Marshall, Mike","contributorId":52473,"corporation":false,"usgs":true,"family":"Marshall","given":"Mike","email":"","affiliations":[],"preferred":false,"id":815936,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Pyne, Milo","contributorId":26378,"corporation":false,"usgs":true,"family":"Pyne","given":"Milo","affiliations":[],"preferred":false,"id":815937,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Singhurst, Jason R.","contributorId":258196,"corporation":false,"usgs":false,"family":"Singhurst","given":"Jason","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":815938,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Tracey, Christopher 0000-0002-3866-9020","orcid":"https://orcid.org/0000-0002-3866-9020","contributorId":40591,"corporation":false,"usgs":true,"family":"Tracey","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":815939,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Walck, Jeffrey L. 0000-0002-8518-9900","orcid":"https://orcid.org/0000-0002-8518-9900","contributorId":258197,"corporation":false,"usgs":false,"family":"Walck","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":815940,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Weakley, Alan 0000-0003-2093-3767","orcid":"https://orcid.org/0000-0003-2093-3767","contributorId":197982,"corporation":false,"usgs":false,"family":"Weakley","given":"Alan","email":"","affiliations":[],"preferred":false,"id":815941,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}}
,{"id":70220499,"text":"sir20205151 - 2021 - Characterization of factors affecting groundwater levels in and near the former Lake Traverse Indian Reservation, South Dakota, water years 1956–2017","interactions":[],"lastModifiedDate":"2021-05-20T11:45:53.918338","indexId":"sir20205151","displayToPublicDate":"2021-05-19T09:12:25","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":"2020-5151","displayTitle":"Characterization of Factors Affecting Groundwater Levels in and near the Former Lake Traverse Indian Reservation, South Dakota, Water Years 1956–2017","title":"Characterization of factors affecting groundwater levels in and near the former Lake Traverse Indian Reservation, South Dakota, water years 1956–2017","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with the Sisseton Wahpeton Oyate, completed a study to characterize water-level fluctuations in observation wells relative to driving factors that affect water levels in and near the historical 1867 boundary of the Lake Traverse Indian Reservation. The study investigated concerns regarding potential effects of groundwater withdrawals and climate conditions on groundwater levels within an area that includes the historical boundary of the reservation and a surrounding area that extends 10 miles in all directions within South Dakota. Characterization of water-level fluctuations in observation wells and relative driving factors was accomplished by statistical trend analysis.</p><p>Monthly data from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) were aggregated to obtain annual and seasonal datasets for total precipitation, minimum air temperature (<i>T<sub>min</sub></i>), and maximum air temperature (<i>T<sub>max</sub></i>) for the study area and a surrounding buffer area. Trend tests for gridded data for total precipitation, <i>T<sub>min</sub></i>, and <i>T<sub>max</sub></i> were completed for annual and seasonal time series for water years 1956–2017, which is about 2 years before the earliest available water-level measurements. A 2-year offset was arbitrarily selected because scrutiny of water-level and precipitation data indicated that responses of groundwater levels for many of the observation wells lagged major changes in precipitation patterns by about 2 years. Statistically significant upward trends were detected for annual precipitation and annual <i>T<sub>min</sub></i> for most of the study area and the surrounding buffer area. Statistically significant downward trends in <i>T<sub>max</sub></i> were detected for only a few 2.5 arc-minute grid cells; however, the sparsity of the spatial coverage reduces confidence that these are true trends, in contrast to the near completeness of the spatial coverage in upward trends for <i>T<sub>min</sub></i>. Spatial distributions of statistically significant trends in seasonal climate data were generally similar to the annual trends, but with substantial differences in the spatial density of the trends.</p><p>Potential interactions among water levels in observation wells and streamflow were examined through correlation analyses of the annual median water level for each of 76 observation wells versus the annual mean streamflow for each of four area streamgages. Potential interactions among water levels in observation wells and lake levels were examined through correlation analyses involving 25 area lakes. Resulting correlation coefficients were used as part of an approach for selecting a lake to be plotted in conjunction with water-level and precipitation data for each observation well.</p><p>Groundwater trends for 76 observation wells were analyzed for three separate water-level parameters (minimum, median, and maximum) because wells are measured sporadically, and data are biased towards more frequent measurements during periods of heaviest irrigation demand. Trends in the time series of annual precipitation (from PRISM) starting 2 years earlier than the associated water-level trend also were analyzed for the location of each individual observation well. Sen’s slope and Mann-Kendall <i>p</i>-values were computed for the three water-level parameters and for the annual precipitation time series. Graphs showing results of trend analyses for each observation well also showed changes with time in the sum of licensed groundwater withdrawals within six specified radii (0.5, 1.0, 2.0, 3.0, 4.0, and 5.0 miles) of each well as a qualitative indicator of proximal groundwater demand.</p><p>Trends in groundwater levels in observation wells in the study area are predominantly upward, with 43 of 76 wells having significant upward trends for at least one of the three water-level parameters and only 8 wells having significant downward trends for at least one water-level parameter. The upward groundwater trends are driven by predominantly upward precipitation trends, with 43 wells (not all the same wells) also having significant upward trends and no wells having significant downward trends. Significant upward precipitation trends were detected for only two of the eight wells with significant downward groundwater trends. Groundwater levels in some observation wells likely are also substantially affected by interactions with surface water, especially with lakes. Water levels in many area lakes increased in response to wet conditions of the early 1990s and have maintained high water levels ever since. It is recognized that in many cases lakes that were selected for plotting with groundwater hydrographs likely are not hydraulically connected with a groundwater system or aquifer associated with an individual well; however, interactions also are plausible for numerous other lakes for which water-level records are not available.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205151","collaboration":"Prepared in cooperation with the Sisseton Wahpeton Oyate","usgsCitation":"Valseth, K.J., and Driscoll, D.G., 2021, Characterization of factors affecting groundwater levels in and near the former Lake Traverse Indian Reservation, South Dakota, water years 1956–2017: U.S. Geological Survey Scientific Investigations Report 2020–5151, 64 p., https://doi.org/10.3133/sir20205151.","productDescription":"Report: vi, 64 p.; 2 Appendixes; Dataset","numberOfPages":"74","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-114147","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":385692,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5151/sir20205151_appendix1.pdf","text":"Appendix 1","size":"957 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5151 Appendix 1","linkHelpText":"— Figure 1.1 Graphs showing trends in annual precipitation totals, trends in measured groundwater levels, lake levels for a selected lake, and proximal groundwater withdrawals"},{"id":385685,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5151/coverthb.jpg"},{"id":385686,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5151/sir20205151.pdf","text":"Report","size":"4.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5151"},{"id":385689,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":385693,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5151/sir20205151_appendix2.pdf","text":"Appendix 2","size":"165 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5151 Appendix 2","linkHelpText":"— Figure 2.1 Graphs showing autocorrelation function values for annual total precipitation, annual mean maximum temperature, and annual mean minimum temperature for the study area from 1956 to 2017"}],"country":"United States","state":"South Dakota","otherGeospatial":"Lake Traverse Indian Reservation","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -97.72338867187499,\n              45.034714778688624\n            ],\n            [\n              -96.43798828125,\n              45.034714778688624\n            ],\n            [\n              -96.43798828125,\n              45.9511496866914\n            ],\n            [\n              -97.72338867187499,\n              45.9511496866914\n            ],\n            [\n              -97.72338867187499,\n              45.034714778688624\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/dakota-water\" href=\"https://www.usgs.gov/centers/dakota-water\">Dakota Water Science Center</a><br>U.S. Geological Survey<br>821 East Interstate Avenue, Bismarck, ND 58503<br>1608 Mountain View Road, Rapid City, SD 57702</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Data Sources and Analytical Methods</li><li>Characterization of Factors Affecting Groundwater Levels</li><li>Summary</li><li>References Cited</li><li>Appendixes</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-05-19","noUsgsAuthors":false,"publicationDate":"2021-05-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Valseth, Kristen J. 0000-0003-4257-6094","orcid":"https://orcid.org/0000-0003-4257-6094","contributorId":203447,"corporation":false,"usgs":true,"family":"Valseth","given":"Kristen","email":"","middleInitial":"J.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":815835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driscoll, Daniel G. 0000-0003-0016-8535 dgdrisco@usgs.gov","orcid":"https://orcid.org/0000-0003-0016-8535","contributorId":207583,"corporation":false,"usgs":true,"family":"Driscoll","given":"Daniel","email":"dgdrisco@usgs.gov","middleInitial":"G.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":815836,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70221155,"text":"70221155 - 2021 - Prototyping a methodology for long-term (1680-2100) historical-to-future landscape modeling for the conterminous United States","interactions":[],"lastModifiedDate":"2022-04-01T22:14:57.190942","indexId":"70221155","displayToPublicDate":"2021-05-19T08:12:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Prototyping a methodology for long-term (1680-2100) historical-to-future landscape modeling for the conterminous United States","docAbstract":"<p>Land system change has been identified as one of four major Earth system processes where change has passed a destabilizing threshold. A historical record of landscape change is required to understand the impacts change has had on human and natural systems, while scenarios of future landscape change are required to facilitate planning and mitigation efforts. A methodology for modeling long-term historical and future landscape change was applied in the Delaware River Basin of the United States. A parcel-based modeling framework was used to reconstruct historical landscapes back to 1680, parameterized with a variety of spatial and nonspatial historical datasets. Similarly, scenarios of future landscape change were modeled for multiple scenarios out to 2100. Results demonstrate the ability to represent historical land cover proportions and general patterns at broad spatial scales and model multiple potential future landscape trajectories. The resulting land cover collection provides consistent data from 1680 through 2100, at a 30-m spatial resolution, 10-year intervals, and high thematic resolution. The data are consistent with the spatial and thematic characteristics of widely used national-scale land cover datasets, facilitating use within existing land management and research workflows. The methodology demonstrated in the Delaware River Basin is extensible and scalable, with potential applications at national scales for the United States.</p>","language":"English","publisher":"MDPI","doi":"10.3390/land10050536","usgsCitation":"Dornbierer, J., Wika, S., Robison, C., Rouze, G., and Sohl, T.L., 2021, Prototyping a methodology for long-term (1680-2100) historical-to-future landscape modeling for the conterminous United States: Land, v. 10, no. 5, 536, 31 p.; Data Release, https://doi.org/10.3390/land10050536.","productDescription":"536, 31 p.; Data Release","ipdsId":"IP-127950","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":452199,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land10050536","text":"Publisher Index Page"},{"id":386174,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":397938,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93J4Z2W"}],"country":"United States","state":"Delaware, Maryland, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.728759765625,\n              38.676933444637925\n            ],\n            [\n              -75.333251953125,\n              38.46219172306828\n            ],\n            [\n              -74.827880859375,\n              39.06184913429154\n            ],\n            [\n              -75.025634765625,\n              39.38526381099774\n            ],\n            [\n              -74.2236328125,\n              40.212440718286466\n            ],\n            [\n              -74.696044921875,\n              40.78885994449482\n            ],\n            [\n              -73.58642578125,\n              41.5579215778042\n            ],\n            [\n              -74.278564453125,\n              42.27730877423709\n            ],\n            [\n              -76.83837890625,\n              40.538851525354666\n            ],\n            [\n              -75.728759765625,\n              38.676933444637925\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-05-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Dornbierer, Jordan 0000-0003-2099-5095","orcid":"https://orcid.org/0000-0003-2099-5095","contributorId":213067,"corporation":false,"usgs":false,"family":"Dornbierer","given":"Jordan","affiliations":[{"id":38270,"text":"SGT Inc., contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":816876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wika, Steve 0000-0001-9992-8973","orcid":"https://orcid.org/0000-0001-9992-8973","contributorId":213068,"corporation":false,"usgs":false,"family":"Wika","given":"Steve","affiliations":[{"id":38700,"text":"SGT Inc.","active":true,"usgs":false}],"preferred":false,"id":816877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robison, Charles 0000-0002-7623-2380","orcid":"https://orcid.org/0000-0002-7623-2380","contributorId":217916,"corporation":false,"usgs":false,"family":"Robison","given":"Charles","email":"","affiliations":[{"id":39714,"text":"SGT Inc. (USGS Contractor)","active":true,"usgs":false}],"preferred":false,"id":816878,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rouze, Gregory 0000-0002-3344-2708","orcid":"https://orcid.org/0000-0002-3344-2708","contributorId":259239,"corporation":false,"usgs":false,"family":"Rouze","given":"Gregory","email":"","affiliations":[{"id":52337,"text":"TSSC contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":816879,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sohl, Terry L. 0000-0002-9771-4231 sohl@usgs.gov","orcid":"https://orcid.org/0000-0002-9771-4231","contributorId":648,"corporation":false,"usgs":true,"family":"Sohl","given":"Terry","email":"sohl@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":816880,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70220861,"text":"70220861 - 2021 - Incorporating climate change in a harvest risk assessment for polar bears Ursus maritimus in Southern Hudson Bay","interactions":[],"lastModifiedDate":"2021-05-26T12:28:44.821314","indexId":"70220861","displayToPublicDate":"2021-05-19T07:26:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating climate change in a harvest risk assessment for polar bears Ursus maritimus in Southern Hudson Bay","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0035\"><span>Arctic&nbsp;marine mammals&nbsp;are harvested by Indigenous people for subsistence and are socially and culturally important. For ice-dependent species like the polar bear&nbsp;</span><i>Ursus maritimus</i>, management and conservation require understanding interactions between harvest and sea-ice loss due to climate change. We developed a demographic model to evaluate harvest risk for polar bears in Southern Hudson Bay, Canada, where the annual ice-free season has increased by approximately one month in recent decades. The model was based on the theta-logistic equation and allowed for density-dependent changes (through carrying capacity [<i>K</i>]) and density-independent changes (through population growth rate [<i>r</i><span>]). Model parameters were estimated using a Bayesian&nbsp;Monte Carlo method&nbsp;that included capture-recapture,&nbsp;aerial survey, and harvest data. Harvest management followed a state-dependent approach under which new estimates of abundance were used to update the harvest level every five years. Under a middle-of-the-road environmental scenario that assumed&nbsp;</span><i>K</i><span>&nbsp;</span>and<span>&nbsp;</span><i>r</i><span>&nbsp;would decline in proportion to projected sea-ice declines, annual removal of 0.02–0.03 of females resulted in a 0.8 probability of maintaining subpopulation abundance above maximum net productivity level for three polar bear generations (~34&nbsp;years), our primary criterion for sustainability. Under more pessimistic and optimistic environmental scenarios, comparable female harvest rates were 0.01 and 0.055, respectively. Our coupled modeling-management framework can be used to inform&nbsp;tradeoffs&nbsp;between protection and sustainable use for wildlife populations experiencing habitat loss.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2021.109128","usgsCitation":"Regehr, E.V., Dyck, M., Iverson, S.A., Lee, D.S., Lunn, N.J., Northrup, J.M., Richer, M., Szor, G., and Runge, M.C., 2021, Incorporating climate change in a harvest risk assessment for polar bears Ursus maritimus in Southern Hudson Bay: Biological Conservation, v. 258, 109128, 12 p., https://doi.org/10.1016/j.biocon.2021.109128.","productDescription":"109128, 12 p.","ipdsId":"IP-119919","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":488581,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2021.109128","text":"Publisher Index Page"},{"id":385979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Southern Hudson Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -86.8359375,\n              50.51342652633956\n            ],\n            [\n              -72.0703125,\n              50.51342652633956\n            ],\n            [\n              -73.125,\n              58.90464570302001\n            ],\n            [\n              -91.93359375,\n              57.70414723434193\n            ],\n            [\n              -86.8359375,\n              50.51342652633956\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"258","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Regehr, Eric V. 0000-0003-4487-3105","orcid":"https://orcid.org/0000-0003-4487-3105","contributorId":66364,"corporation":false,"usgs":false,"family":"Regehr","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":816479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dyck, Markus","contributorId":173868,"corporation":false,"usgs":false,"family":"Dyck","given":"Markus","affiliations":[],"preferred":false,"id":816480,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iverson, Samuel A.","contributorId":52308,"corporation":false,"usgs":false,"family":"Iverson","given":"Samuel","email":"","middleInitial":"A.","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":false,"id":816481,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lee, David S.","contributorId":257883,"corporation":false,"usgs":false,"family":"Lee","given":"David","email":"","middleInitial":"S.","affiliations":[{"id":52159,"text":"Department of Wildlife and Environment, Nunavut Tunngavik Inc., Ottawa, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":816482,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lunn, Nicholas J","contributorId":198991,"corporation":false,"usgs":false,"family":"Lunn","given":"Nicholas","email":"","middleInitial":"J","affiliations":[],"preferred":false,"id":816483,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Northrup, Joseph M","contributorId":258776,"corporation":false,"usgs":false,"family":"Northrup","given":"Joseph","email":"","middleInitial":"M","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":816484,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Richer, Marie-Claude","contributorId":258777,"corporation":false,"usgs":false,"family":"Richer","given":"Marie-Claude","email":"","affiliations":[{"id":52285,"text":"Ministere des Forets, de la Faune et des Parcs, Gourvernement du Quebec","active":true,"usgs":false}],"preferred":false,"id":816485,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Szor, Guillaume","contributorId":258778,"corporation":false,"usgs":false,"family":"Szor","given":"Guillaume","email":"","affiliations":[{"id":52286,"text":"Ministere des Forets, de la Faune et des Parcs, Gouvernement du Quebec","active":true,"usgs":false}],"preferred":false,"id":816486,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":816487,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70220681,"text":"70220681 - 2021 - The 2008-2010 subsidence of Dallol volcano on the 2 spreading Erta Ale ridge: InSAR observations and source models","interactions":[],"lastModifiedDate":"2021-05-25T12:19:14.37282","indexId":"70220681","displayToPublicDate":"2021-05-19T07:14:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"The 2008-2010 subsidence of Dallol volcano on the 2 spreading Erta Ale ridge: InSAR observations and source models","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">In this work, we study the subsidence of Dallol, an explosive crater and hydrothermal area along the spreading Erta Ale ridge of Afar (Ethiopia). No volcanic products exist at the surface. However, a diking episode in 2004, accompanied by dike-induced faulting, indicates that Dallol is an active volcanic area. The 2004 diking episode was followed by quiescence until subsidence started in 2008. We use InSAR to measure the deformation, and inverse, thermoelastic and poroelastic modelling to understand the possible causes of the subsidence. Analysis of InSAR data from 2004–2010 shows that subsidence, centered at Dallol, initiated in October 2008, and continued at least until February 2010 at an approximately regular rate of up to 10 cm/year. The inversion of InSAR average velocities finds that the source causing the subsidence is shallow (depth between 0.5 and 1.5 km), located under Dallol and with a volume decrease between −0.63 and −0.26 × 10<sup>6</sup><span>&nbsp;</span>km<sup>3</sup>/year. The most likely explanation for the subsidence of Dallol volcano is a combination of outgassing (depressurization), cooling and contraction of the roof of a shallow crustal magma chamber or of the hydrothermal system.<span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span></span></span></div>","language":"English","publisher":"MDPI","doi":"10.3390/rs13101991","usgsCitation":"Battaglia, M., Paglia, C., and Meuti, S., 2021, The 2008-2010 subsidence of Dallol volcano on the 2 spreading Erta Ale ridge: InSAR observations and source models: Remote Sensing, v. 13, no. 10, 1991, 14 p., https://doi.org/10.3390/rs13101991.","productDescription":"1991, 14 p.","ipdsId":"IP-128962","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":452204,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13101991","text":"Publisher Index Page"},{"id":385913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ethiopia","otherGeospatial":"Dallol volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              40.12481689453125,\n              14.064652358057725\n            ],\n            [\n              40.450286865234375,\n              14.064652358057725\n            ],\n            [\n              40.450286865234375,\n              14.368173317117904\n            ],\n            [\n              40.12481689453125,\n              14.368173317117904\n            ],\n            [\n              40.12481689453125,\n              14.064652358057725\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"10","noUsgsAuthors":false,"publicationDate":"2021-05-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Battaglia, Maurizio 0000-0003-4726-5287 mbattaglia@usgs.gov","orcid":"https://orcid.org/0000-0003-4726-5287","contributorId":204742,"corporation":false,"usgs":true,"family":"Battaglia","given":"Maurizio","email":"mbattaglia@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":816417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paglia, Carolina 0000-0002-9072-3004","orcid":"https://orcid.org/0000-0002-9072-3004","contributorId":258325,"corporation":false,"usgs":false,"family":"Paglia","given":"Carolina","email":"","affiliations":[{"id":52280,"text":"Universita' di Pisa","active":true,"usgs":false}],"preferred":false,"id":816418,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meuti, Stefano","contributorId":258326,"corporation":false,"usgs":false,"family":"Meuti","given":"Stefano","email":"","affiliations":[{"id":52281,"text":"University of Rome","active":true,"usgs":false}],"preferred":false,"id":816422,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70233540,"text":"70233540 - 2021 - American crocodiles (Crocodylus acutus) as restoration bioindicators in the Florida Everglades","interactions":[],"lastModifiedDate":"2022-07-25T12:07:10.672213","indexId":"70233540","displayToPublicDate":"2021-05-19T07:04:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"American crocodiles (Crocodylus acutus) as restoration bioindicators in the Florida Everglades","docAbstract":"<div class=\"abstract toc-section abstract-type-\"><div class=\"abstract-content\"><p>The federally threatened American crocodile (<i>Crocodylus acutus</i>) is a flagship species and ecological indicator of hydrologic restoration in the Florida Everglades. We conducted a long-term capture-recapture study on the South Florida population of American crocodiles from 1978 to 2015 to evaluate the effects of restoration efforts to more historic hydrologic conditions. The study produced 10,040 crocodile capture events of 9,865 individuals and more than 90% of captures were of hatchlings. Body condition and growth rates of crocodiles were highly age-structured with younger crocodiles presenting with the poorest body condition and highest growth rates. Mean crocodile body condition in this study was 2.14±0.35 SD across the South Florida population. Crocodiles exposed to hypersaline conditions (&gt; 40 psu) during the dry season maintained lower body condition scores and reduced growth rate by 13% after one year, by 24% after five years, and by 29% after ten years. Estimated hatchling survival for the South Florida population was 25% increasing with ontogeny and reaching near 90% survival at year six. Hatchling survival was 34% in NE Florida Bay relative to a 69% hatchling survival at Crocodile Lake National Wildlife Refuge and 53% in Flamingo area of Everglades National Park. Hypersaline conditions negatively affected survival, growth and body condition and was most pronounced in NE Florida Bay, where the hydrologic conditions have been most disturbed. The American crocodile, a long-lived animal, with relatively slow growth rate provides an excellent model system to measure the effects of altered hydropatterns in the Everglades landscape. These results illustrate the need for continued long-term monitoring to assess system-wide restoration outcomes and inform resource managers.</p></div></div>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0250510","usgsCitation":"Briggs-Gonzalez, V.S., Basille, M., Cherkiss, M., and Mazzotti, F., 2021, American crocodiles (Crocodylus acutus) as restoration bioindicators in the Florida Everglades: PLoS ONE, v. 16, no. 5, e0250510, 23 p., https://doi.org/10.1371/journal.pone.0250510.","productDescription":"e0250510, 23 p.","ipdsId":"IP-095038","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":452206,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0250510","text":"Publisher Index Page"},{"id":404415,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.76025390624999,\n              24.996015742094006\n            ],\n            [\n              -80.16723632812499,\n              24.996015742094006\n            ],\n            [\n              -80.16723632812499,\n              26.716173757934094\n            ],\n            [\n              -81.76025390624999,\n              26.716173757934094\n            ],\n            [\n              -81.76025390624999,\n              24.996015742094006\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"16","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-05-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs-Gonzalez, Venetia S.","contributorId":293592,"corporation":false,"usgs":false,"family":"Briggs-Gonzalez","given":"Venetia","email":"","middleInitial":"S.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":847369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Basille, Mathieu","contributorId":175274,"corporation":false,"usgs":false,"family":"Basille","given":"Mathieu","email":"","affiliations":[],"preferred":false,"id":847370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cherkiss, Michael 0000-0002-7802-6791","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":222180,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":847371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazzotti, Frank J.","contributorId":100018,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":847372,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70220616,"text":"70220616 - 2021 - Forest evapotranspiration dynamics over a fragmented forest landscape under drought in southwestern Amazonia","interactions":[],"lastModifiedDate":"2021-05-24T11:56:27.126561","indexId":"70220616","displayToPublicDate":"2021-05-19T06:45:47","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":681,"text":"Agricultural and Forest Meteorology","active":true,"publicationSubtype":{"id":10}},"title":"Forest evapotranspiration dynamics over a fragmented forest landscape under drought in southwestern Amazonia","docAbstract":"<p id=\"spara011\">Ongoing climate change and human conversion of forests to other land uses alter regional evapotranspiration dynamics and, consequently, impact associated hydrological systems in Amazonia. We studied the effects of drought and fragmentation on forest evapotranspiration using the surface energy balance-based model METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) for a fragmented forest landscape in Brazil's Amazonian state of Rondônia.</p><p id=\"spara012\">Dry season (June-August) forest evapotranspiration estimates were produced for the 2009-2011 period that encompassed the 2010 drought event, one of the extreme droughts in the Amazon. METRIC evapotranspiration data were analyzed in relation to climate (monthly precipitation and cumulative water deficit) and forest fragmentation (edge distance from 100m to 1000m from forest edge and edge density). During the dry season of 2009, pre-drought, forest evapotranspiration did not fall below 110mm/month. However, the 2010 drought year showed a drastic decline in evapotranspiration by 32%, to 75mm/month, from July to August. In 2011, evapotranspiration rates were still depressed with August rates dropping as low as 85mm/month. Forest evapotranspiration dynamics were driven mainly by precipitation and corresponding water deficits in the drier years (2010 and 2011), although evapotranspiration deficits along the edges of forest fragments were locally significant, at the landscape scale. The forests near edges (to 100m) had progressively lower evapotranspiration levels than interior forests as dry seasons progressed and these differences were greatest in the 2010 drought year, reaching almost 5%.</p><p id=\"spara013\">Our results suggest that during the driest months, fragmentation exacerbated both the rate and extent of evapotranspiration reductions over forest areas up to 100m from edges, equivalent to ~20% of the forested landscape in our study area.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2021.108446","usgsCitation":"Numata, I., Khand, K.B., Kjaersgaard, J., Cochrane, M.A., and Silva, S.S., 2021, Forest evapotranspiration dynamics over a fragmented forest landscape under drought in southwestern Amazonia: Agricultural and Forest Meteorology, v. 306, 108446, 9 p., https://doi.org/10.1016/j.agrformet.2021.108446.","productDescription":"108446, 9 p.","ipdsId":"IP-122348","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":452208,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agrformet.2021.108446","text":"Publisher Index Page"},{"id":385833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","state":"Rondonia","otherGeospatial":"Amazon Rain Forest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -66.97265625,\n              -2.4162756547063857\n            ],\n            [\n              -56.6455078125,\n              -2.4162756547063857\n            ],\n            [\n              -56.6455078125,\n              6.18424616128059\n            ],\n            [\n              -66.97265625,\n              6.18424616128059\n            ],\n            [\n              -66.97265625,\n              -2.4162756547063857\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"306","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Numata, Izaya","contributorId":219508,"corporation":false,"usgs":false,"family":"Numata","given":"Izaya","email":"","affiliations":[],"preferred":false,"id":816235,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Khand, Kul Bikram 0000-0002-1593-1508","orcid":"https://orcid.org/0000-0002-1593-1508","contributorId":242921,"corporation":false,"usgs":true,"family":"Khand","given":"Kul","email":"","middleInitial":"Bikram","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":816236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kjaersgaard, Jeppe","contributorId":258261,"corporation":false,"usgs":false,"family":"Kjaersgaard","given":"Jeppe","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":816237,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cochrane, Mark A.","contributorId":20884,"corporation":false,"usgs":false,"family":"Cochrane","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":816238,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Silva, Sonaira S.","contributorId":258262,"corporation":false,"usgs":false,"family":"Silva","given":"Sonaira","email":"","middleInitial":"S.","affiliations":[{"id":52266,"text":"Federal University of Acre","active":true,"usgs":false}],"preferred":false,"id":816239,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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