{"pageNumber":"141","pageRowStart":"3500","pageSize":"25","recordCount":40783,"records":[{"id":70239372,"text":"70239372 - 2023 - The over-prediction of seismically induced soil liquefaction during the 2016 Kumamoto, Japan earthquake sequence","interactions":[],"lastModifiedDate":"2023-01-11T12:48:02.805173","indexId":"70239372","displayToPublicDate":"2022-12-27T06:42:09","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1816,"text":"Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"The over-prediction of seismically induced soil liquefaction during the 2016 Kumamoto, Japan earthquake sequence","docAbstract":"<div class=\"html-p\">Following the M7.0 strike-slip earthquake near Kumamoto, Japan, in April of 2016, most geotechnical engineering experts believed that there would be significant soil liquefaction and liquefaction-induced infrastructure damage observed in the densely populated city of Kumamoto during the post-event engineering reconnaissance. This belief was driven by several factors including the young geologic environment, alluvially deposited soils, a predominance of loose sandy soils documented in publicly available boring logs throughout the region, and the high intensity ground motions observed from the earthquake. To the surprise of many of the researchers, soil liquefaction occurred both less frequently and less severely than expected. This paper summarizes findings from our field, laboratory, and simplified analytical studies common to engineering practice to assess the lower occurrence of liquefaction. Measured in situ SPT and CPT resistance values were evaluated with current liquefaction triggering procedures. Minimally disturbed samples were subjected to cyclic triaxial testing. Furthermore, an extensive literature review on Kumamoto volcanic soils was performed. Our findings suggest that current liquefaction triggering procedures over-predict liquefaction frequency and effects in alluvially deposited volcanic soils. Volcanic soils were found to possess properties of soil crushability, high fines content, moderate plasticity, and unanticipated organic constituents. Cyclic triaxial tests confirm the high liquefaction resistance of these soils. Moving forward, geotechnical engineers should holistically consider the soil’s mineralogy and geology before relying solely on simplified liquefaction triggering procedures when evaluating volcanic soils for liquefaction.</div>","language":"English","publisher":"MDPI","doi":"10.3390/geosciences13010007","usgsCitation":"Anderson, D.J., Franke, K.W., Kayen, R., Dashti, S., and Badanagki, M., 2023, The over-prediction of seismically induced soil liquefaction during the 2016 Kumamoto, Japan earthquake sequence: Geosciences, v. 13, no. 1, 7, 28 p., https://doi.org/10.3390/geosciences13010007.","productDescription":"7, 28 p.","ipdsId":"IP-147235","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":445026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/geosciences13010007","text":"Publisher Index Page"},{"id":411708,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan","otherGeospatial":"Mount Aso","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              130.37897745486168,\n              33.136385469043276\n            ],\n            [\n              130.37897745486168,\n              32.55051970765922\n            ],\n            [\n              131.50459805879575,\n              32.55051970765922\n            ],\n            [\n              131.50459805879575,\n              33.136385469043276\n            ],\n            [\n              130.37897745486168,\n              33.136385469043276\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Donald J.","contributorId":300727,"corporation":false,"usgs":false,"family":"Anderson","given":"Donald","email":"","middleInitial":"J.","affiliations":[{"id":65243,"text":"Utah-DOT","active":true,"usgs":false}],"preferred":false,"id":861311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Franke, Kevin W.","contributorId":300728,"corporation":false,"usgs":false,"family":"Franke","given":"Kevin","email":"","middleInitial":"W.","affiliations":[{"id":48387,"text":"BYU","active":true,"usgs":false}],"preferred":false,"id":861312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kayen, Robert 0000-0002-0356-072X","orcid":"https://orcid.org/0000-0002-0356-072X","contributorId":219065,"corporation":false,"usgs":true,"family":"Kayen","given":"Robert","email":"","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861313,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dashti, Shideh","contributorId":189768,"corporation":false,"usgs":false,"family":"Dashti","given":"Shideh","email":"","affiliations":[],"preferred":false,"id":861314,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Badanagki, M","contributorId":300729,"corporation":false,"usgs":false,"family":"Badanagki","given":"M","email":"","affiliations":[{"id":65244,"text":"WSP, University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":861315,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70256709,"text":"70256709 - 2023 - Multiple dimensions of functional diversity affect stream fish β-diversity","interactions":[],"lastModifiedDate":"2024-09-03T15:19:48.638587","indexId":"70256709","displayToPublicDate":"2022-12-26T10:12:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Multiple dimensions of functional diversity affect stream fish β-diversity","docAbstract":"<ol class=\"\"><li>When investigating metacommunity dynamics, functional differences among species are often assumed to be as important as environmental differences between sites in determining β-diversity. However, few studies have examined the influence of functional diversity on β-diversity. We examine the relative importance of regional functional diversity partitioned by niche dimensions and environmental variation in structuring taxonomic β-diversity of stream fishes using a large dataset of stream fish assemblages (hereafter, simply β-diversity). We predicted that both functional diversity and environmental variation play a role in determining β-diversity.</li><li>We tested this prediction by modelling the patterns of stream fish β-diversity as a function of environmental variation, functional diversity and γ-richness across 10,220 sites for 329 fish species using a series of conceptual path models.</li><li>Environmental variation consistently affected β-diversity across all models, whereas functional diversity and γ-richness influenced β-diversity only in some models. We show that including relevant trait differences among species in path models can improve their ability to explain β-diversity, suggesting that functional traits influence β-diversity.</li><li>The ability of path models to explain β-diversity varied depending on the trait grouping included in the model, demonstrating that specific path models representing different niche dimensions can improve the ability of a model to explain β-diversity. In addition, parsing traits into different niche dimensions revealed alternative patterns of functional diversity–β-diversity relationships that otherwise would have been missed.</li><li>The selection of relevant traits and linked niche dimensions is critical for detecting relationships between functional diversity and β-diversity. Using traits associated with different niche dimensions allows for the identification of niche dimensions most strongly associated with species sorting and the detection of patterns missed by focusing on a single niche dimension. Determining the niche dimensions that influence β-diversity could provide insights into the processes driving biodiversity and metacommunity dynamics, improving our ability to conserve or restore aquatic communities.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1111/fwb.14036","usgsCitation":"Bower, L.M., Stoczynski, L., Peoples, B.K., Patrick, C., and Brown, B.L., 2023, Multiple dimensions of functional diversity affect stream fish β-diversity: Freshwater Biology, v. 68, no. 3, p. 437-451, https://doi.org/10.1111/fwb.14036.","productDescription":"15 p.","startPage":"437","endPage":"451","ipdsId":"IP-134787","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445030,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/fwb.14036","text":"Publisher Index Page"},{"id":433407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Eastern United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -85.08254453558935,\n              29.663955568318002\n            ],\n            [\n              -84.00353049201316,\n              31.24197817552016\n            ],\n            [\n              -82.54620654241978,\n              29.549345286801383\n            ],\n            [\n              -81.08225667140708,\n              30.220016244291074\n            ],\n            [\n              -81.13068353501534,\n              32.32776358432194\n            ],\n            [\n              -82.29417301039534,\n              34.379604334810125\n            ],\n           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         -69.25928679202123,\n              47.54170256695585\n            ],\n            [\n              -71.21905272640619,\n              45.12756083037783\n            ],\n            [\n              -74.09987276280616,\n              45.1570079552298\n            ],\n            [\n              -74.83668470001416,\n              43.00167109657585\n            ],\n            [\n              -78.7139760431753,\n              42.94670064885159\n            ],\n            [\n              -82.49681964219468,\n              40.92727818455322\n            ],\n            [\n              -80.23949798942652,\n              38.65161657169966\n            ],\n            [\n              -82.81095598309338,\n              36.708283361840515\n            ],\n            [\n              -87.42378197623401,\n              35.73782637186412\n            ],\n            [\n              -86.2161486208606,\n              31.10920872480844\n            ],\n            [\n              -85.08254453558935,\n              29.663955568318002\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"68","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-12-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Bower, Luke Max 0000-0002-0739-858X","orcid":"https://orcid.org/0000-0002-0739-858X","contributorId":341034,"corporation":false,"usgs":true,"family":"Bower","given":"Luke","email":"","middleInitial":"Max","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stoczynski, Lauren","contributorId":341643,"corporation":false,"usgs":false,"family":"Stoczynski","given":"Lauren","email":"","affiliations":[{"id":81766,"text":"Clemson University Clemson","active":true,"usgs":false}],"preferred":false,"id":908735,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peoples, Brandon K.","contributorId":341644,"corporation":false,"usgs":false,"family":"Peoples","given":"Brandon","email":"","middleInitial":"K.","affiliations":[{"id":81766,"text":"Clemson University Clemson","active":true,"usgs":false}],"preferred":false,"id":908736,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patrick, Christopher J.","contributorId":341645,"corporation":false,"usgs":false,"family":"Patrick","given":"Christopher J.","affiliations":[{"id":81768,"text":"Clemson University Clemson,","active":true,"usgs":false}],"preferred":false,"id":908737,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Bryan L.","contributorId":341646,"corporation":false,"usgs":false,"family":"Brown","given":"Bryan","email":"","middleInitial":"L.","affiliations":[{"id":6686,"text":"College of William and Mary","active":true,"usgs":false}],"preferred":false,"id":908738,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70241127,"text":"70241127 - 2023 - Divergent climate impacts on C3 versus C4 grasses imply widespread 21st century shifts in grassland functional composition","interactions":[],"lastModifiedDate":"2023-03-13T11:18:23.661025","indexId":"70241127","displayToPublicDate":"2022-12-26T06:16:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Divergent climate impacts on C3 versus C4 grasses imply widespread 21st century shifts in grassland functional composition","docAbstract":"<h3 id=\"ddi13669-sec-0001-title\" class=\"article-section__sub-title section1\">Aim</h3><p>Grasslands cover a third of Earth's landmass and provide critical ecosystem services. Anticipating how perennial C<sub>3</sub><span>&nbsp;</span>(cool-season) and C<sub>4</sub><span>&nbsp;</span>(warm-season) grasses respond to climate change will be key to predicting future composition and functioning of grasslands. Here, we evaluate environmental drivers of C<sub>3</sub><span>&nbsp;</span>and C<sub>4</sub><span>&nbsp;</span>perennial distributions and assess how C<sub>3</sub><span>&nbsp;</span>and C<sub>4</sub><span>&nbsp;</span>grass distributions shift in response to future climate change.</p><h3 id=\"ddi13669-sec-0002-title\" class=\"article-section__sub-title section1\">Location</h3><p>Western United States.</p><h3 id=\"ddi13669-sec-0003-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We developed integrated species distribution models to identify climate and soil drivers of relative abundance of C<sub>3</sub><span>&nbsp;</span>and C<sub>4</sub><span>&nbsp;</span>perennial grasses. We then created projections of species abundances under future climate and evaluated when and where projected shifts in relative abundance were robust across climate models.</p><h3 id=\"ddi13669-sec-0004-title\" class=\"article-section__sub-title section1\">Results</h3><p>Historically, C<sub>3</sub><span>&nbsp;</span>grasses occupied areas with lower temperature and more variable precipitation regimes, while C<sub>4</sub><span>&nbsp;</span>grasses occupied areas of higher temperature, greater temperature variability and greater warm-season precipitation. C<sub>4</sub><span>&nbsp;</span>species also occupied narrower soil texture niches. In response to future climate change, C<sub>3</sub><span>&nbsp;</span>grass abundance declined across 74% of areas, while C<sub>4</sub><span>&nbsp;</span>abundance increased across 66% of areas. C<sub>3</sub><span>&nbsp;</span>grasses expanded in mid- to higher-latitude areas with increasing temperature and decreasing seasonality of precipitation. In contrast, C<sub>4</sub><span>&nbsp;</span>grasses increased in higher-latitude regions, but declined in lower-latitude, dryer regions. Results were surprisingly robust across climate scenarios, suggesting high confidence in the direction of these future changes.</p><h3 id=\"ddi13669-sec-0005-title\" class=\"article-section__sub-title section1\">Main Conclusions</h3><p>Findings imply C<sub>3</sub><span>&nbsp;</span>and C<sub>4</sub><span>&nbsp;</span>perennial grasses will have highly divergent responses to climate change that may result in grassland functional compositional changes. Increasing temperatures and precipitation variability may favour some C<sub>4</sub><span>&nbsp;</span>grasses, but C<sub>4</sub><span>&nbsp;</span>habitat expansion may be constrained by soil conditions in western USA. Results provide actionable insights for anticipating the impacts of climate change on grass-dominated and co-dominated ecosystems and improving large-scale conservation and restoration efforts.</p>","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13669","usgsCitation":"Havrilla, C., Bradford, J., Yackulic, C., and Munson, S.M., 2023, Divergent climate impacts on C3 versus C4 grasses imply widespread 21st century shifts in grassland functional composition: Diversity and Distributions, v. 29, no. 3, p. 379-394, https://doi.org/10.1111/ddi.13669.","productDescription":"16 p.","startPage":"379","endPage":"394","ipdsId":"IP-143038","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":445039,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13669","text":"Publisher Index Page"},{"id":435532,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99EGD2E","text":"USGS data release","linkHelpText":"Bioclimatic suitability for 11 dominant Colorado Plateau perennial grass species (ver. 2.0, November 2022)"},{"id":413999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -125.54030283521868,\n              49.526621871576566\n            ],\n            [\n              -125.54030283521868,\n              28.895094929809844\n            ],\n            [\n              -101.38064109224445,\n              28.895094929809844\n            ],\n            [\n              -101.38064109224445,\n              49.526621871576566\n            ],\n            [\n              -125.54030283521868,\n              49.526621871576566\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-12-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Havrilla, Caroline A.","contributorId":303002,"corporation":false,"usgs":false,"family":"Havrilla","given":"Caroline A.","affiliations":[{"id":65592,"text":"Department of Forest and Rangeland Stewardship, Colorado State University, Fort Collins, CO 80524","active":true,"usgs":false}],"preferred":false,"id":866173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":866174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":866175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":866176,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70240131,"text":"70240131 - 2023 - Borealization of nearshore fishes on an interior Arctic shelf over multiple decades","interactions":[],"lastModifiedDate":"2023-03-15T15:06:22.506747","indexId":"70240131","displayToPublicDate":"2022-12-24T06:37:51","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Borealization of nearshore fishes on an interior Arctic shelf over multiple decades","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Borealization is a type of community reorganization where Arctic specialists are replaced by species with more boreal distributions in response to climatic warming. The process of borealization is often exemplified by the northward range expansions and subsequent proliferation of boreal species on the Pacific and Atlantic inflow Arctic shelves (i.e., Bering/Chukchi and Barents seas, respectively). But the circumpolar nearshore distribution of Arctic-boreal fishes that predates recent warming suggests borealization is possible beyond inflow shelves. To examine this question, we revisited two nearshore lagoons in the eastern Alaska Beaufort Sea (Kaktovik and Jago lagoons, Arctic National Wildlife Refuge, Alaska, USA), a High Arctic interior shelf. We compared summer fish species assemblage, catch rate, and size distribution among three periods that spanned a 30-year record (baseline conditions, 1988–1991; moderate sea ice decline, 2003–2005; rapid sea ice decline, 2017–2019). Fish assemblages differed among periods in both lagoons, consistent with borealization. Among Arctic specialists, a clear decline in fourhorn sculpin (<i>Myoxocephalus quadricornis</i>, Kanayuq in Iñupiaq) occurred in both lagoons with 86%–90% lower catch rates compared with the baseline period. Among the Arctic-boreal species, a dramatic 18- to 19-fold increase in saffron cod (<i>Eleginus gracilis</i>, Uugaq) occurred in both lagoons. Fish size (length) distributions demonstrated increases in the proportion of larger fish for most species examined, consistent with increasing survival and addition of age-classes. These field data illustrate borealization of an Arctic nearshore fish community during a period of rapid warming. Our results agree with predictions that Arctic-boreal fishes (e.g., saffron cod) are well positioned to exploit the changing Arctic ecosystem. Another Arctic-boreal species, Dolly Varden (<i>Salvelinus malma</i>, Iqalukpik), appear to have already responded to warming by shifting from Arctic nearshore to shelf waters. More broadly, our findings suggest that areas of borealization could be widespread in the circumpolar nearshore.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16576","usgsCitation":"von Biela, V.R., Laske, S.M., Stanek, A.E., Brown, R., and Dunton, K., 2023, Borealization of nearshore fishes on an interior Arctic shelf over multiple decades: Global Change Biology, v. 29, no. 7, p. 1822-1838, https://doi.org/10.1111/gcb.16576.","productDescription":"17 p.","startPage":"1822","endPage":"1838","ipdsId":"IP-140988","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":445048,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.16576","text":"Publisher Index Page"},{"id":412437,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic National Wildlife Refuge,  Kaktovik and Jago lagoons","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -143.72717327290792,\n              70.14108904245526\n            ],\n            [\n              -143.72717327290792,\n              70.05929996195823\n            ],\n            [\n              -143.24258750157804,\n              70.05929996195823\n            ],\n            [\n              -143.24258750157804,\n              70.14108904245526\n            ],\n            [\n              -143.72717327290792,\n              70.14108904245526\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"29","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-01-04","publicationStatus":"PW","contributors":{"authors":[{"text":"von Biela, Vanessa R. 0000-0002-7139-5981 vvonbiela@usgs.gov","orcid":"https://orcid.org/0000-0002-7139-5981","contributorId":3104,"corporation":false,"usgs":true,"family":"von Biela","given":"Vanessa","email":"vvonbiela@usgs.gov","middleInitial":"R.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":862727,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Laske, Sarah M. 0000-0002-6096-0420 slaske@usgs.gov","orcid":"https://orcid.org/0000-0002-6096-0420","contributorId":204872,"corporation":false,"usgs":true,"family":"Laske","given":"Sarah","email":"slaske@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":862728,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stanek, Ashley E. 0000-0001-5184-2126","orcid":"https://orcid.org/0000-0001-5184-2126","contributorId":290682,"corporation":false,"usgs":true,"family":"Stanek","given":"Ashley","email":"","middleInitial":"E.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":862729,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Randy J","contributorId":243248,"corporation":false,"usgs":false,"family":"Brown","given":"Randy J","affiliations":[{"id":48666,"text":"USFWS, Fairbanks, Alaska","active":true,"usgs":false}],"preferred":false,"id":862730,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dunton, Kenneth H.","contributorId":171775,"corporation":false,"usgs":false,"family":"Dunton","given":"Kenneth H.","affiliations":[],"preferred":false,"id":862731,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70239202,"text":"70239202 - 2023 - Pesticide prioritization by potential biological effects in tributaries of the Laurentian Great Lakes","interactions":[],"lastModifiedDate":"2023-02-02T17:57:35.332175","indexId":"70239202","displayToPublicDate":"2022-12-23T07:07:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Pesticide prioritization by potential biological effects in tributaries of the Laurentian Great Lakes","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Watersheds of the Great Lakes Basin (USA/Canada) are highly modified and impacted by human activities including pesticide use. Despite labeling restrictions intended to minimize risks to nontarget organisms, concerns remain that environmental exposures to pesticides may be occurring at levels negatively impacting nontarget organisms. We used a combination of organismal-level toxicity estimates (in vivo aquatic life benchmarks) and data from high-throughput screening (HTS) assays (in vitro benchmarks) to prioritize pesticides and sites of concern in streams at 16 tributaries to the Great Lakes Basin. In vivo or in vitro benchmark values were exceeded at 15 sites, 10 of which had exceedances throughout the year. Pesticides had the greatest potential biological impact at the site with the greatest proportion of agricultural land use in its basin (the Maumee River, Toledo, OH, USA), with 72 parent compounds or transformation products being detected, 47 of which exceeded at least one benchmark value. Our risk-based screening approach identified multiple pesticide parent compounds of concern in tributaries of the Great Lakes; these compounds included: eight herbicides (metolachlor, acetochlor, 2,4-dichlorophenoxyacetic acid, diuron, atrazine, alachlor, triclopyr, and simazine), three fungicides (chlorothalonil, propiconazole, and carbendazim), and four insecticides (diazinon, fipronil, imidacloprid, and clothianidin). We present methods for reducing the volume and complexity of potential biological effects data that result from combining contaminant surveillance with HTS (in vitro) and traditional (in vivo) toxicity estimates.<span>&nbsp;</span><i>Environ Toxicol Chem</i><span>&nbsp;</span>2022;00:1–18. Published 2022. This article is a U.S. Government work and is in the public domain in the USA.<span>&nbsp;</span><i>Environmental Toxicology and Chemistry</i><span>&nbsp;</span>published by Wiley Periodicals LLC on behalf of SETAC.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/etc.5522","usgsCitation":"Oliver, S.K., Corsi, S., Baldwin, A.K., Nott, M.A., Ankley, G., Blackwell, B., Villeneuve, D.L., Hladik, M.L., Kolpin, D., Loken, L.C., DeCicco, L.A., Meyer, M., and Loftin, K.A., 2023, Pesticide prioritization by potential biological effects in tributaries of the Laurentian Great Lakes: Environmental Toxicology and Chemistry, v. 42, no. 2, p. 367-384, https://doi.org/10.1002/etc.5522.","productDescription":"18 p.","startPage":"367","endPage":"384","ipdsId":"IP-137314","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":445058,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.5522","text":"Publisher Index Page"},{"id":411338,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.41831603390857,\n              49.80549590740878\n            ],\n            [\n              -91.41831603390857,\n              41.07851415036595\n            ],\n            [\n              -74.90189273325733,\n              41.07851415036595\n            ],\n            [\n              -74.90189273325733,\n              49.80549590740878\n            ],\n            [\n              -91.41831603390857,\n              49.80549590740878\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"42","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860748,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860749,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860750,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nott, Michelle A. 0000-0003-3968-7586","orcid":"https://orcid.org/0000-0003-3968-7586","contributorId":221766,"corporation":false,"usgs":true,"family":"Nott","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860751,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ankley, Gerald T.","contributorId":177970,"corporation":false,"usgs":false,"family":"Ankley","given":"Gerald T.","affiliations":[{"id":13485,"text":"U.S. Environmental Protection Agency, Duluth, MN","active":true,"usgs":false}],"preferred":false,"id":860752,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blackwell, Brett R.","contributorId":173601,"corporation":false,"usgs":false,"family":"Blackwell","given":"Brett R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":860753,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Villeneuve, Daniel L. 0000-0003-2801-0203","orcid":"https://orcid.org/0000-0003-2801-0203","contributorId":197436,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Daniel","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":860754,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221229,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860755,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":205652,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"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":860756,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860757,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"DeCicco, Laura A. 0000-0002-3915-9487 ldecicco@usgs.gov","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":174716,"corporation":false,"usgs":true,"family":"DeCicco","given":"Laura","email":"ldecicco@usgs.gov","middleInitial":"A.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":860758,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Meyer, Michael T. 0000-0001-6006-7985","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":205665,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":860759,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Loftin, Keith A. 0000-0001-5291-876X","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":221964,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":860760,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70247139,"text":"70247139 - 2023 - Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions","interactions":[],"lastModifiedDate":"2023-07-25T14:31:36.964032","indexId":"70247139","displayToPublicDate":"2022-12-22T09:14:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions","docAbstract":"<p><span>Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.13093","usgsCitation":"Zwart, J.A., Oliver, S.K., Watkins, W., Sadler, J.M., Appling, A.P., Corson-Dosch, H.R., Jia, X., Kumar, V., and Read, J., 2023, Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions: Journal of the American Water Resources Association, v. 59, no. 2, p. 317-337, https://doi.org/10.1111/1752-1688.13093.","productDescription":"21 p.","startPage":"317","endPage":"337","ipdsId":"IP-135607","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":445061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.13093","text":"Publisher Index Page"},{"id":419302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watkins, William 0000-0002-7544-0700 wwatkins@usgs.gov","orcid":"https://orcid.org/0000-0002-7544-0700","contributorId":178146,"corporation":false,"usgs":true,"family":"Watkins","given":"William","email":"wwatkins@usgs.gov","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":879030,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sadler, Jeffrey Michael 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":260092,"corporation":false,"usgs":true,"family":"Sadler","given":"Jeffrey","email":"","middleInitial":"Michael","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879031,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":879032,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corson-Dosch, Hayley R. 0000-0001-8695-1584","orcid":"https://orcid.org/0000-0001-8695-1584","contributorId":244707,"corporation":false,"usgs":true,"family":"Corson-Dosch","given":"Hayley","middleInitial":"R.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879033,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":879034,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kumar, Vipin","contributorId":237812,"corporation":false,"usgs":false,"family":"Kumar","given":"Vipin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":879035,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879036,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70244195,"text":"70244195 - 2023 - Investigating effects of climate-induced changes in water temperature and diet on mercury concentrations in an Arctic freshwater forage fish","interactions":[],"lastModifiedDate":"2023-06-07T14:07:58.189314","indexId":"70244195","displayToPublicDate":"2022-12-22T09:02:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1561,"text":"Environmental Research","active":true,"publicationSubtype":{"id":10}},"title":"Investigating effects of climate-induced changes in water temperature and diet on mercury concentrations in an Arctic freshwater forage fish","docAbstract":"<p><span>The amount of mercury (Hg) in Arctic lake food webs is, and will continue to be, affected by rapid, ongoing climate change. At warmer temperatures, fish require more energy to sustain growth; changes in their metabolic rates and consuming prey with potentially higher Hg concentrations could result in increased Hg accumulation. To examine the potential implications of climate warming on forage fish Hg accumulation in Arctic lakes, we quantified growth and Hg accumulation in Ninespine Stickleback&nbsp;</span><i>Pungitius pungitius</i><span>&nbsp;under different temperature and diet scenarios using&nbsp;bioenergetics&nbsp;models. Four scenarios were considered that examined the role of climate, diet, climate&nbsp;×&nbsp;diet, and climate&nbsp;×&nbsp;diet&nbsp;×&nbsp;elevated prey Hg. As expected, annual fish growth increased with warmer temperatures, but growth rates and Hg accumulation were largely diet dependent. Compared to current growth rates of 0.3&nbsp;g⋅y</span><sup>−1</sup><span>, fish growth increased at least 200% for fish consuming energy-dense benthic prey and decreased at least 40% for fish consuming pelagic prey. Compared to baseline levels, the Hg burden per kilocalorie of Ninespine Stickleback declined up to 43% with benthic consumption – indicating strong somatic growth dilution – but no more than 4% with pelagic consumption; elevated prey Hg concentrations led to moderate Hg declines in benthic-foraging fish and Hg increases in pelagic-foraging fish. Bioenergetics models demonstrated the complex interaction of water temperature, growth, prey proportions, and prey Hg concentrations that respond to climate change. Further work is needed to resolve mechanisms and rates linking climate change to Hg availability and uptake in Arctic freshwater systems.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envres.2022.114851","usgsCitation":"Laske, S.M., Burke, S.M., Carey, M.P., Swanson, H.K., and Zimmerman, C.E., 2023, Investigating effects of climate-induced changes in water temperature and diet on mercury concentrations in an Arctic freshwater forage fish: Environmental Research, v. 218, 114851, 13 p., https://doi.org/10.1016/j.envres.2022.114851.","productDescription":"114851, 13 p.","ipdsId":"IP-144262","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":445064,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envres.2022.114851","text":"Publisher Index Page"},{"id":417911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -157.67980839183957,\n              70.52713703737254\n            ],\n            [\n              -157.67980839183957,\n              70\n            ],\n            [\n              -156.79804904275505,\n              70\n            ],\n            [\n              -156.79804904275505,\n              70.52713703737254\n            ],\n            [\n              -157.67980839183957,\n              70.52713703737254\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"218","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Laske, Sarah M. 0000-0002-6096-0420 slaske@usgs.gov","orcid":"https://orcid.org/0000-0002-6096-0420","contributorId":204872,"corporation":false,"usgs":true,"family":"Laske","given":"Sarah","email":"slaske@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":874844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burke, Samantha M.","contributorId":203348,"corporation":false,"usgs":false,"family":"Burke","given":"Samantha","email":"","middleInitial":"M.","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":874845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":874846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swanson, Heidi K.","contributorId":203350,"corporation":false,"usgs":false,"family":"Swanson","given":"Heidi","email":"","middleInitial":"K.","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":874847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":874848,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70239217,"text":"70239217 - 2023 - Revised age and regional correlations of Cenozoic strata on Bat Mountain, Death Valley region, California, USA, from zircon U-Pb geochronology of sandstones and ash-fall tuffs","interactions":[],"lastModifiedDate":"2023-02-02T17:56:41.715738","indexId":"70239217","displayToPublicDate":"2022-12-22T08:57:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Revised age and regional correlations of Cenozoic strata on Bat Mountain, Death Valley region, California, USA, from zircon U-Pb geochronology of sandstones and ash-fall tuffs","docAbstract":"<p><span>Basin analysis and tectonic reconstructions of the Cenozoic history of the Death Valley region, California, USA, are hindered by a lack of volcanic (tuff) age control in many stratigraphic successions exposed in the Grapevine and Funeral Mountains of California, USA. Although maximum depositional ages (MDAs) interpreted from detrital zircon U-Pb data may be a promising alternative to volcanic ages, arguments remain regarding the calculation of MDAs including, but not limited to, the number of “young” grains to consider (i.e., the spectrum of dates used to calculate the MDA); which grains, if any, should be ignored; which approaches yield results that are statistically rigorous; and ultimately, which approaches result in ages that are geologically reasonable. We compare commonly used metrics of detrital zircon MDA for five sandstone samples from the Cenozoic strata exposed on Bat Mountain in the southern Funeral Mountains of California—i.e., the youngest single grain (YSG), the weighted mean of the youngest grain cluster of two or more grains at 1σ uncertainty (YC1σ(2+)) and of three or more grains at 2σ uncertainty (YC2σ(3+)), the youngest graphical peak (YPP), and the maximum likelihood age (MLA). Every sandstone sample yielded abundant Cenozoic zircon U-Pb dates that formed unimodal, near-normal age distributions that were clearly distinguishable from the next-oldest grains in each sample and showed an apparent up-section decrease in peak age. Benchmarked against published K/Ar and&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar ages and five new zircon U-Pb ages of ash-fall tuffs, our analysis parallels prior studies and demonstrates that many MDA metrics—YSG, YC1σ(2+), YC2σ(3+), and YPP—drift toward unreasonably young or old values. In contrast, the maximum likelihood estimation approach and the resulting MLA metric consistently produce geologically appropriate estimates of MDA without arbitrary omission of any young (or old) zircon dates. Using the MLAs of sandstones and zircon U-Pb ages of interbedded ash-fall tuffs, we develop a new age model for the Oligocene–Miocene Amargosa Valley Formation (deposited ca. 28.5–18.5 Ma) and the Miocene Bat Mountain Formation (deposited ca. 15.5–13.5 Ma) and revise correlations to Cenozoic strata across the eastern Death Valley region.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02543.1","usgsCitation":"Schwartz, T.M., Souders, A., Lundstern, J., Gilmer, A.K., and Thompson, R., 2023, Revised age and regional correlations of Cenozoic strata on Bat Mountain, Death Valley region, California, USA, from zircon U-Pb geochronology of sandstones and ash-fall tuffs: Geosphere, v. 19, no. 1, p. 235-257, https://doi.org/10.1130/GES02543.1.","productDescription":"23 p.","startPage":"235","endPage":"257","ipdsId":"IP-139248","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":445066,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02543.1","text":"Publisher Index Page"},{"id":435534,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P982KK4D","text":"USGS data release","linkHelpText":"Zircon U-Pb data for ash-fall tuffs and sandstones of the Cenozoic Amargosa Valley and Bat Mountain Formations exposed on Bat Mountain, southern Funeral Mountains, California, USA"},{"id":411342,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Bat Mountain, Death Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.12127468750195,\n              37.16000456147583\n            ],\n            [\n              -117.12127468750195,\n              35.551070951522945\n            ],\n            [\n              -115.75746797181529,\n              35.551070951522945\n            ],\n            [\n              -115.75746797181529,\n              37.16000456147583\n            ],\n            [\n              -117.12127468750195,\n              37.16000456147583\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"19","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Schwartz, Theresa Maude 0000-0001-6606-4072","orcid":"https://orcid.org/0000-0001-6606-4072","contributorId":245180,"corporation":false,"usgs":true,"family":"Schwartz","given":"Theresa","email":"","middleInitial":"Maude","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Souders, Amanda 0000-0002-1367-8924","orcid":"https://orcid.org/0000-0002-1367-8924","contributorId":296423,"corporation":false,"usgs":true,"family":"Souders","given":"Amanda","email":"","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":860788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lundstern, Jens-Erik 0000-0003-0000-8013","orcid":"https://orcid.org/0000-0003-0000-8013","contributorId":264189,"corporation":false,"usgs":true,"family":"Lundstern","given":"Jens-Erik","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gilmer, Amy K. 0000-0001-5038-8136","orcid":"https://orcid.org/0000-0001-5038-8136","contributorId":218307,"corporation":false,"usgs":true,"family":"Gilmer","given":"Amy","email":"","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860790,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Ren A. 0000-0002-3044-3043","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":207982,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860791,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70239141,"text":"70239141 - 2023 - Sharing land via keystone structure: Retaining naturally regenerated trees may efficiently benefit birds in plantations","interactions":[],"lastModifiedDate":"2023-04-11T16:56:36.003705","indexId":"70239141","displayToPublicDate":"2022-12-22T07:02:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Sharing land via keystone structure: Retaining naturally regenerated trees may efficiently benefit birds in plantations","docAbstract":"<p>Meeting food/wood demands with increasing human population and per-capita consumption is a pressing conservation issue, and is often framed as a choice between land sparing and land sharing. Although most empirical studies comparing the efficacy of land sparing and sharing supported land sparing, land sharing may be more efficient if its performance is tested by rigorous experimental design and habitat structures providing crucial resources for various species––keystone structures––are clearly involved. We launched a manipulative experiment to retain naturally regenerated broad-leaved trees when harvesting conifer plantations in central Hokkaido, northern Japan. We surveyed birds in harvested treatments, unharvested plantation controls and natural forest references one-year before the harvest and for three consecutive post-harvest years. We developed a hierarchical community model separating abundance and space-use (territorial proportion overlapping treatment plots) subject to imperfect detection to assess population consequences of retention harvesting. Application of the model to our data showed that retaining some broad-leaved trees increased total abundance of forest birds over the harvest rotation cycle. Specifically, pre-harvest survey showed that the amount of broad-leaved trees increased forest bird abundance in a concave manner (i.e., in a form of diminishing-return). After harvesting, a small amount of retained broad-leaved trees mitigated negative harvesting impacts on abundance though retention harvesting reduced the space-use. Nevertheless, positive retention effects on the post-harvest bird density as the product of abundance and space-use exhibited a concave form. Thus, small profit reductions were shown to yield large increases in forest bird abundance. The difference in bird abundance between clear-cutting and low amounts of broad-leaved tree retention increased slightly from the first to second post-harvesting years. We conclude that retaining a small amount of broad-leaved trees may be a cost-effective on-site conservation approach for the management of conifer plantations. Retention of 20-30 broad-leaved trees per ha may be sufficient to maintain higher forest bird abundance than clear-cutting over the rotation cycle. Retention approaches can be incorporated into management systems using certification schemes and best management practices. Developing an awareness of the roles and values of naturally regenerated trees is needed to diversify plantations.</p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2802","usgsCitation":"Yamaura, Y., Unno, A., and Royle, A., 2023, Sharing land via keystone structure: Retaining naturally regenerated trees may efficiently benefit birds in plantations: Ecological Applications, v. 33, no. 3, e2802, https://doi.org/10.1002/eap.2802.","productDescription":"e2802","ipdsId":"IP-136595","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":445068,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":411174,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Yamaura, Yuichi","contributorId":300495,"corporation":false,"usgs":false,"family":"Yamaura","given":"Yuichi","affiliations":[{"id":65171,"text":"Shikoku Research Center, Forestry and Forest Products Research Institute","active":true,"usgs":false}],"preferred":false,"id":860324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Unno, Akira","contributorId":300496,"corporation":false,"usgs":false,"family":"Unno","given":"Akira","email":"","affiliations":[{"id":65172,"text":"Fores try Research Institute, Hokkaido Research Organization, Koshunai, Bibai,","active":true,"usgs":false}],"preferred":false,"id":860325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":860326,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70242008,"text":"70242008 - 2023 - A genetic warning system for a hierarchically structured wildlife monitoring framework","interactions":[],"lastModifiedDate":"2023-04-04T12:00:53.306947","indexId":"70242008","displayToPublicDate":"2022-12-22T06:53:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"A genetic warning system for a hierarchically structured wildlife monitoring framework","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Genetic variation is a well-known indicator of population fitness yet is not typically included in monitoring programs for sensitive species. Additionally, most programs monitor populations at one scale, which can lead to potential mismatches with ecological processes critical to species' conservation. Recently developed methods generating hierarchically nested population units (i.e., clusters of varying scales) for greater sage-grouse (<i>Centrocercus urophasianus</i>) have identified population trend declines across spatiotemporal scales to help managers target areas for conservation. The same clusters used as a proxy for spatial scale can alert managers to local units (i.e., neighborhood-scale) with low genetic diversity, further facilitating identification of management targets. We developed a genetic warning system utilizing previously developed hierarchical population units to identify management-relevant areas with low genetic diversity within the greater sage-grouse range. Within this warning system we characterized conservation concern thresholds based on values of genetic diversity and developed a statistical model for microsatellite data to robustly estimate these values for hierarchically nested populations. We found that 41 of 224 neighborhood-scale clusters had low genetic diversity, 23 of which were coupled with documented local population trend decline. We also found evidence of cross-scale low genetic diversity in the small and isolated Washington population, unlikely to be reversed through typical local management actions alone. The combination of low genetic diversity and a declining population suggests relatively high conservation concern. Our findings could further facilitate conservation action prioritization in combination with population trend assessments and (or) local information, and act as a base-line of genetic diversity for future comparison. Importantly, the approach we used is broadly applicable across taxa.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2787","usgsCitation":"Zimmerman, S.J., Aldridge, C.L., O’Donnell, M.S., Edmunds, D.R., Coates, P.S., Prochazka, B.G., Fike, J., Cross, T.B., Fedy, B.C., and Oyler-McCance, S.J., 2023, A genetic warning system for a hierarchically structured wildlife monitoring framework: Ecological Applications, v. 33, no. 3, e2787, 18 p., https://doi.org/10.1002/eap.2787.","productDescription":"e2787, 18 p.","ipdsId":"IP-133541","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445071,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2787","text":"Publisher Index Page"},{"id":435536,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FATNI9","text":"USGS data release","linkHelpText":"Greater sage-grouse genetic warning system, western United States (ver 1.1, January 2023)"},{"id":435535,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98Q5F6R","text":"USGS data release","linkHelpText":"Genotypes and cluster definitions for a range-wide greater sage-grouse dataset collected 2005-2017 (ver 1.1, January 2023)"},{"id":415157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -102.07344624886372,\n              49.512419389230956\n            ],\n            [\n              -125.31052090062897,\n              49.512419389230956\n            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aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":868513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":868514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edmunds, David R. 0000-0002-5212-8271 dedmunds@usgs.gov","orcid":"https://orcid.org/0000-0002-5212-8271","contributorId":152210,"corporation":false,"usgs":true,"family":"Edmunds","given":"David","email":"dedmunds@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":868515,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":868516,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":868518,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fike, Jennifer A. 0000-0001-8797-7823","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":207268,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":868519,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cross, Todd B.","contributorId":189267,"corporation":false,"usgs":false,"family":"Cross","given":"Todd","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":868517,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fedy, Bradley C.","contributorId":191347,"corporation":false,"usgs":false,"family":"Fedy","given":"Bradley","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":868520,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":868521,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70241953,"text":"70241953 - 2023 - Estimating phosphorus retention capacity of flow-through wetlands","interactions":[],"lastModifiedDate":"2023-04-03T11:47:46.606064","indexId":"70241953","displayToPublicDate":"2022-12-21T06:44:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Estimating phosphorus retention capacity of flow-through wetlands","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0035\"><span>A Bayesian hierarchical modeling approach is introduced to pool data properly from multiple flow-through wetlands to estimate wetland-specific long-term phosphorus retention capacity. By pooling data from multiple wetlands, we overcome the difficulties in estimating the effectiveness of using constructed and natural wetlands for nutrient reduction. The Bayesian hierarchical modeling approach reduces estimation uncertainty by shrinking wetland-specific estimates towards the overall average of the same quantity from multiple wetlands, facilitating information sharing across sites, thereby reducing the demand on sample sizes from individual wetlands and avoiding several common pitfalls of using large data (i.e., from multiple systems) induced by Simpson's paradox. In this paper, we develop a sequential updating framework to alleviate the computational burden of compiling and modeling data from multiple wetlands. We then demonstrate the sequential updating process to estimate retention capacity of a suite of wetlands in Ohio,&nbsp;USA. A total of four wetlands, representing both natural and&nbsp;constructed wetlands, were used. The estimated total phosphorus retention capacities range less than 0.01 to well over 1 ton per year per system. As&nbsp;</span>wetland restoration<span>&nbsp;</span>initiatives expand around the Laurentian Great Lakes and nationally, this model serves as an important initial step in developing tools to meet nutrient reduction goals and standards. Extending this work, we have developed a publicly accessible on-line open computation platform that can help natural resource specialists better plan for wetland efficacy in the future.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2022.106869","usgsCitation":"Qian, S.S., Arend, K.K., Jacquemin, S.J., Sullivan, S.M., and Kowalski, K., 2023, Estimating phosphorus retention capacity of flow-through wetlands: Ecological Engineering, v. 187, 106869, 8 p., https://doi.org/10.1016/j.ecoleng.2022.106869.","productDescription":"106869, 8 p.","ipdsId":"IP-142368","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":445078,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2022.106869","text":"Publisher Index Page"},{"id":415049,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"187","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Qian, Song S.","contributorId":198934,"corporation":false,"usgs":false,"family":"Qian","given":"Song","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":868364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arend, Kristi K.","contributorId":303882,"corporation":false,"usgs":false,"family":"Arend","given":"Kristi","email":"","middleInitial":"K.","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":868365,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacquemin, Stephen J","contributorId":303884,"corporation":false,"usgs":false,"family":"Jacquemin","given":"Stephen","email":"","middleInitial":"J","affiliations":[{"id":13348,"text":"Wright State University","active":true,"usgs":false}],"preferred":false,"id":868366,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan, S. Mazeika Patricio","contributorId":303885,"corporation":false,"usgs":false,"family":"Sullivan","given":"S.","email":"","middleInitial":"Mazeika Patricio","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":868367,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":868368,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70263896,"text":"70263896 - 2023 - Validation of earthquake ground-motion models in southern California, USA, using precariously balanced rocks","interactions":[],"lastModifiedDate":"2025-02-27T15:51:42.500906","indexId":"70263896","displayToPublicDate":"2022-12-20T09:47:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Validation of earthquake ground-motion models in southern California, USA, using precariously balanced rocks","docAbstract":"<p><span>Accurate estimates of earthquake ground shaking rely on uncertain ground-motion models derived from limited instrumental recordings of historical earthquakes. A critical issue is that there is currently no method to empirically validate the resultant ground-motion estimates of these models at the timescale of rare, large earthquakes; this lack of validation causes great uncertainty in ground-motion estimates. Here, we address this issue and validate ground-motion estimates for southern California utilizing the unexceeded ground motions recorded by 20 precariously balanced rocks. We used cosmogenic&nbsp;</span><sup>10</sup><span>Be exposure dating to model the age of the precariously balanced rocks, which ranged from ca. 1 ka to ca. 50 ka, and calculated their probability of toppling at different ground-motion levels. With this rock data, we then validated the earthquake ground motions estimated by the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3) seismic-source characterization and the Next Generation Attenuation (NGA)-West2 ground-motion models. We found that no ground-motion model estimated levels of earthquake ground shaking consistent with the observed continued existence of all 20 precariously balanced rocks. The ground-motion model I14 estimated ground-motion levels that were inconsistent with the most rocks; therefore, I14 was invalidated and removed. At a 2475 year mean return period, the removal of this invalid ground-motion model resulted in a 2–7% reduction in the mean and a 10–36% reduction in the 5th–95th fractile uncertainty of the ground-motion estimates. Our findings demonstrate the value of empirical data from precariously balanced rocks as a validation tool for removing invalid ground-motion models and, in turn, reducing the uncertainty in earthquake ground-motion estimates.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/B36484.1","usgsCitation":"Rood, A.H., Rood, D., Balco, G., Stafford, P.J., Grant Ludwig, L., Kendrick, K.J., and Wilcken, K., 2023, Validation of earthquake ground-motion models in southern California, USA, using precariously balanced rocks: GSA Bulletin, v. 135, no. 9-10, p. 2179-2199, https://doi.org/10.1130/B36484.1.","productDescription":"21 p.","startPage":"2179","endPage":"2199","ipdsId":"IP-143199","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482565,"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        \"coordinates\": [\n          [\n            [\n              -118,\n              34.6\n            ],\n            [\n              -118,\n              33.6\n            ],\n            [\n              -116,\n              33.6\n            ],\n            [\n              -116,\n              34.6\n            ],\n            [\n              -118,\n              34.6\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"135","issue":"9-10","noUsgsAuthors":false,"publicationDate":"2022-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Rood, Anna H.","contributorId":245478,"corporation":false,"usgs":false,"family":"Rood","given":"Anna","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":928942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rood, Dylan","contributorId":167067,"corporation":false,"usgs":false,"family":"Rood","given":"Dylan","email":"","affiliations":[{"id":24608,"text":"Imperial College London","active":true,"usgs":false}],"preferred":false,"id":928943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balco, Greg","contributorId":347027,"corporation":false,"usgs":false,"family":"Balco","given":"Greg","email":"","affiliations":[{"id":13621,"text":"Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":928944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stafford, Peter J.","contributorId":261918,"corporation":false,"usgs":false,"family":"Stafford","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":24608,"text":"Imperial College London","active":true,"usgs":false}],"preferred":false,"id":928945,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grant Ludwig, Lisa","contributorId":245422,"corporation":false,"usgs":false,"family":"Grant Ludwig","given":"Lisa","email":"","affiliations":[{"id":34134,"text":"UC Irvine","active":true,"usgs":false}],"preferred":false,"id":928946,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kendrick, Katherine J. 0000-0002-9839-6861","orcid":"https://orcid.org/0000-0002-9839-6861","contributorId":207907,"corporation":false,"usgs":true,"family":"Kendrick","given":"Katherine","email":"","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928947,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilcken, Klaus","contributorId":351569,"corporation":false,"usgs":false,"family":"Wilcken","given":"Klaus","affiliations":[{"id":84009,"text":"Australian Nuclear Science and Technology Organisation","active":true,"usgs":false}],"preferred":false,"id":928948,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70238993,"text":"70238993 - 2023 - Five year analyses of vegetation response to restoration using rock detention structures in southeastern Arizona, United States","interactions":[],"lastModifiedDate":"2023-05-01T15:34:08.422765","indexId":"70238993","displayToPublicDate":"2022-12-19T07:20:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Five year analyses of vegetation response to restoration using rock detention structures in southeastern Arizona, United States","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Rock detention structures (RDS) are used in restoration of riparian areas around the world. The purpose of this study was to analyze the effect of RDS installation on vegetation in terms of species abundance and composition. We present the results from 5 years of annual vegetation sampling which focused on short term non-woody vegetation response within the riparian channel at 3 restoration sites across southeastern Arizona. We examined the potential ways that RDS can preserve native species, encourage wetland species, and/or introduce nonnative species using a Control-Impact-Paired-Series study design. Species composition and frequency were measured within quadrats and zones on an annual basis. Multivariate bootstrap analyses were performed, including Bray-Curtis dissimilarity index and non-metric multidimensional scaling ordination. We found that response to RDS was variable and could be related to the level of degradation or proximity to groundwater. The non-degraded site did not show a response to RDS and the severely degraded site showed a slight increase in vegetation frequency, but the moderately degraded site experienced a significant increase. At the moderately degraded site, located between two historic ciénegas (desert wetlands), species composition shifted and nonnative species invaded, dominating the vegetation increase at this location. At the severely degraded site, pre-existing wetland species frequency increased in response to the installation of RDS. These findings extend the understanding of RDS effects on vegetation, provide scenarios to help land and water resource managers understand potential outcomes, and can assist in optimizing success for restoration projects.</p></div></div>","language":"English","publisher":"Springer Nature","doi":"10.1007/s00267-022-01762-0","usgsCitation":"Wilson, N., and Norman, L., 2023, Five year analyses of vegetation response to restoration using rock detention structures in southeastern Arizona, United States: Environmental Management, v. 71, p. 921-939, https://doi.org/10.1007/s00267-022-01762-0.","productDescription":"19 p.","startPage":"921","endPage":"939","ipdsId":"IP-139780","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":445086,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00267-022-01762-0","text":"Publisher Index Page"},{"id":410788,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -109.06809425904859,\n              31.39517669949646\n            ],\n            [\n              -109.06809425904859,\n              32.671239706816536\n            ],\n            [\n              -111.56747161928966,\n              32.671239706816536\n            ],\n            [\n              -111.56747161928966,\n              31.39517669949646\n            ],\n            [\n              -109.06809425904859,\n              31.39517669949646\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"71","noUsgsAuthors":false,"publicationDate":"2022-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Natalie R. 0000-0001-5145-1221","orcid":"https://orcid.org/0000-0001-5145-1221","contributorId":202534,"corporation":false,"usgs":true,"family":"Wilson","given":"Natalie R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":859556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":859557,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70239789,"text":"70239789 - 2023 - Wetland occupancy by duck broods in cropland-dominated landscapes of the United States Prairie Pothole Region","interactions":[],"lastModifiedDate":"2023-01-20T13:03:06.231565","indexId":"70239789","displayToPublicDate":"2022-12-19T07:00:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Wetland occupancy by duck broods in cropland-dominated landscapes of the United States Prairie Pothole Region","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>The Prairie Pothole Region (PPR) is globally important for breeding waterfowl but has been altered via wetland drainage and grassland conversion to accommodate agricultural land use. Thus, understanding the ecology of waterfowl in these highly modified landscapes is essential for their conservation. Brood occurrence is the cumulative outcome of key life-history events including pair formation and territory establishment, nest success, and early brood survival. We applied new technological advances in brood surveying methods to understand brood use of wetlands and how land use and wetland-specific factors influenced brood use of 413 wetlands in crop-dominated landscapes in the PPR of Iowa, Minnesota, North Dakota, and South Dakota, USA, during summers of 2018–2020. Dynamic occupancy models combining information from 2 visits throughout the year revealed no difference among the 4 states or between private and public lands, resulting in a region-wide annual wetland occupancy estimate of 0.41 (95% credible interval [CrI] = 0.26, 0.58). We assessed aquatic invertebrate forage availability, wetland and upland vegetation communities, and various water chemistry metrics in a subset (<i>n</i> = 225) of these wetlands to evaluate how landscape and wetland-specific factors influenced occupancy. The amount of grassland surrounding wetlands was the only variable to influence occupancy at a landscape scale, while wetland size, invertebrates, fish, and vegetation communities influenced occupancy at finer scales. Closer scrutiny of wetland area revealed occupancy was greater in small wetlands after controlling for total wetland area. Our results indicate the greatest constraint on brood occupancy across crop-dominated landscapes of the PPR in the United States was the occurrence of semipermanent wetlands suitable for brood rearing. Other factors, such as wetland vegetation or surrounding land use, had minor intervening influences on duck brood use and ducks were distributed invariant of wetland ownership or broad spatial processes occurring among states. These results demonstrated wetland conservation and restoration strategies are likely to yield gains in annual duck broods across this vast, altered, and highly modified landscape.</p></div></div>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22347","usgsCitation":"Mitchell, B.J., Terry, C.V., Ringelman, K.M., Kemink, K., Anteau, M.J., and Janke, A.K., 2023, Wetland occupancy by duck broods in cropland-dominated landscapes of the United States Prairie Pothole Region: Journal of Wildlife Management, v. 87, no. 2, e22347, 26 p., https://doi.org/10.1002/jwmg.22347.","productDescription":"e22347, 26 p.","ipdsId":"IP-140006","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":445089,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22347","text":"Publisher Index Page"},{"id":412114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Minnesota, North Dakota, South Dakota","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -96.29653960243344,\n              48.97443267103543\n            ],\n            [\n              -103.81695065949702,\n              49.04648442059704\n            ],\n            [\n              -100.56637798862401,\n              47.79300521453408\n            ],\n            [\n              -99.68784483433396,\n              46.08364286612411\n            ],\n            [\n              -99.16072494176002,\n              43.40115466919687\n            ],\n            [\n              -97.57936526403823,\n              42.85616461776857\n            ],\n            [\n              -96.17371221717424,\n              41.52182814884887\n            ],\n            [\n              -93.7138193851624,\n              41.91528041046746\n            ],\n            [\n              -93.18669949258846,\n              42.75948597666104\n            ],\n            [\n              -95.43748196681628,\n              46.96875525238039\n            ],\n            [\n              -96.29653960243344,\n              48.97443267103543\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"87","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Mitchell, Blake J","contributorId":301081,"corporation":false,"usgs":false,"family":"Mitchell","given":"Blake","email":"","middleInitial":"J","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":861960,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terry, Catrina V","contributorId":301082,"corporation":false,"usgs":false,"family":"Terry","given":"Catrina","email":"","middleInitial":"V","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":861961,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ringelman, Kevin M","contributorId":301083,"corporation":false,"usgs":false,"family":"Ringelman","given":"Kevin","email":"","middleInitial":"M","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":861962,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kemink, Kaylan M","contributorId":301084,"corporation":false,"usgs":false,"family":"Kemink","given":"Kaylan M","affiliations":[{"id":65300,"text":"Ducks Unlimited Inc","active":true,"usgs":false}],"preferred":false,"id":861963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":861964,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Janke, Adam K. 0000-0003-2781-7857","orcid":"https://orcid.org/0000-0003-2781-7857","contributorId":130959,"corporation":false,"usgs":false,"family":"Janke","given":"Adam","email":"","middleInitial":"K.","affiliations":[{"id":7176,"text":"Dept of Natl Res Mgmt, SDSU, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":861965,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70260117,"text":"70260117 - 2023 - Lava-ice interactions during historical eruptions of Veniaminof Volcano, Alaska and the potential for meltwater floods and lahars","interactions":[],"lastModifiedDate":"2024-10-30T22:04:32.679399","indexId":"70260117","displayToPublicDate":"2022-12-16T10:06:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Lava-ice interactions during historical eruptions of Veniaminof Volcano, Alaska and the potential for meltwater floods and lahars","docAbstract":"<p><span>Veniaminof Volcano on the Alaska Peninsula of southwest Alaska is one of a small group of ice-clad volcanoes globally that erupts lava flows in the presence of glacier ice. Here, we describe the nature of lava-ice-snow interactions that have occurred during historical eruptions of the volcano since 1944. Lava flows with total volumes on the order of 0.006&nbsp;km</span><sup>3</sup><span>&nbsp;have been erupted in 1983–1984, 1993–1994, 2013, and 2018. Smaller amounts of lava (1 × 10</span><sup>−4</sup><span>&nbsp;km</span><sup>3</sup><span> or less) were generated during eruptions in 1944 and 2021. All known historical eruptions have occurred at a 300-m-high cinder cone (informally named cone A) within the 8 × 10-km-diameter ice-filled caldera that characterizes Veniaminof Volcano. Supraglacial lava flows erupted at cone A, resulted in minor amounts of melting and did not lead to any significant outflows of water in nearby drainages. Subglacial effusion of lava in 1983–1984, 2021 and possibly in 1944 and 1993–1994 resulted in more significant melting including a partially water-filled melt pit, about 0.8&nbsp;km</span><sup>2</sup><span>&nbsp;in area, that developed during the 1983–1984 eruption. The 1983–1984 event created an impression that meltwater floods from Mount Veniaminof’s ice-filled caldera could be significant and hazardous given the large amount of glacier ice resident within the caldera (ice volume about 8&nbsp;km</span><sup>3</sup><span>). To date, no evidence supporting catastrophic outflow of meltwater from lava-ice interactions at cone A has been found. Analysis of imagery from the 1983–1984 eruption shows that the initial phase erupted englacial lavas that melted ice/snow/firn from below, producing surface subsidence outward from the cone with no discernable surface connection to the summit vent on cone A. This also happened during the 2021 eruption, and possibly during the 1993–1994 eruption although meltwater lakes did not form during these events. Thus, historical eruptions at Veniaminof Volcano appear to have two different modes of effusive eruptive behavior, where lava reaches the ice subglacially from flank vents, or where lava flows are erupted subaerially from vents near the summit of cone A and flow down the cone on to the ice surface. When placed in the context of global lava-ice eruptions, in cases where lava flows melt the ice from the surface downward, the main hazards are from localized phreatic explosions as opposed to potential flood/lahar hazards. However, when lava effusion/emplacement occurs beneath the ice surface, melting is more rapid and can produce lakes whose drainage could plausibly produce localized floods and lahars.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s11069-022-05523-4","usgsCitation":"Waythomas, C.F., Edwards, B.R., Miller, T.P., and McGimsey, R.G., 2023, Lava-ice interactions during historical eruptions of Veniaminof Volcano, Alaska and the potential for meltwater floods and lahars: Natural Hazards, v. 115, p. 73-106, https://doi.org/10.1007/s11069-022-05523-4.","productDescription":"34 p.","startPage":"73","endPage":"106","ipdsId":"IP-135174","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467131,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11069-022-05523-4","text":"Publisher Index Page"},{"id":463345,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Veniaminof Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -159.5358525511267,\n              56.27834441063078\n            ],\n            [\n              -159.5358525511267,\n              56.05302637076889\n            ],\n            [\n              -159.12370600367657,\n              56.05302637076889\n            ],\n            [\n              -159.12370600367657,\n              56.27834441063078\n            ],\n            [\n              -159.5358525511267,\n              56.27834441063078\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"115","noUsgsAuthors":false,"publicationDate":"2022-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Waythomas, Christopher F. 0000-0002-3898-272X cwaythomas@usgs.gov","orcid":"https://orcid.org/0000-0002-3898-272X","contributorId":640,"corporation":false,"usgs":true,"family":"Waythomas","given":"Christopher","email":"cwaythomas@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, Benjamin R","contributorId":345586,"corporation":false,"usgs":false,"family":"Edwards","given":"Benjamin","email":"","middleInitial":"R","affiliations":[{"id":39028,"text":"Dickinson College","active":true,"usgs":false}],"preferred":false,"id":917056,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Thomas P","contributorId":345587,"corporation":false,"usgs":false,"family":"Miller","given":"Thomas","email":"","middleInitial":"P","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":917057,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGimsey, Robert G. 0000-0001-5379-7779 mcgimsey@usgs.gov","orcid":"https://orcid.org/0000-0001-5379-7779","contributorId":2352,"corporation":false,"usgs":true,"family":"McGimsey","given":"Robert","email":"mcgimsey@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917058,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70239011,"text":"70239011 - 2023 - Genetic architecture and evolution of color variation in American black bears","interactions":[],"lastModifiedDate":"2023-01-18T17:28:15.216346","indexId":"70239011","displayToPublicDate":"2022-12-16T07:49:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1352,"text":"Current Biology","active":true,"publicationSubtype":{"id":10}},"title":"Genetic architecture and evolution of color variation in American black bears","docAbstract":"<p><span>Color variation is a frequent evolutionary substrate for camouflage in small mammals, but the underlying genetics and evolutionary forces that drive color variation in natural populations of large mammals are mostly unexplained. The American black bear,&nbsp;</span><i>Ursus americanus</i><span>&nbsp;(</span><i>U.&nbsp;americanus</i><span>), exhibits a range of colors including the cinnamon morph, which has a similar color to the brown bear,&nbsp;</span><i>U.&nbsp;arctos</i><span>, and is found at high frequency in the American southwest. Reflectance and chemical melanin measurements showed little distinction between&nbsp;</span><i>U.&nbsp;arctos</i><span>&nbsp;and cinnamon&nbsp;</span><i>U.&nbsp;americanus</i><span>&nbsp;individuals. We used a genome-wide association for hair color as a quantitative trait in 151&nbsp;</span><i>U.&nbsp;americanus</i><span>&nbsp;individuals and identified a single major locus (p&nbsp;&lt;&nbsp;10</span><sup>−13</sup><span>). Additional genomic and functional studies identified a missense alteration (R153C) in&nbsp;</span><i>Tyrosinase-related protein 1</i><span>&nbsp;(</span><i>TYRP1</i><span>) that likely affects binding of the zinc cofactor, impairs protein localization, and results in decreased pigment production. Population genetic analyses and demographic modeling indicated that the R153C variant arose 9.36 kya in a southwestern population where it likely provided a selective advantage, spreading both northwards and eastwards by gene flow. A different&nbsp;</span><i>TYRP1</i><span>&nbsp;allele, R114C, contributes to the characteristic brown color of&nbsp;</span><i>U.&nbsp;arctos</i><span>&nbsp;but is not fixed across the range.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.cub.2022.11.042","usgsCitation":"Puckett, E., Davis, I.S., Harper, D.C., Wakamatsu, K., Battu, G., Belant, J., Beyer, D.E., Carpenter, C., Crupi, A., Davidson, M., DePerno, C.S., Forman, N., Fowler, N.L., Garshelis, D.L., Gould, N., Gunther, K., Haroldson, M.A., Ito, S., Kocka, D.M., Lackey, C., Leahy, R., Lee-Roney, C., Lewis, T., Lutto, A., McGowan, K., Olfenbuttel, C., Orlando, M., Platt, A., Pollard, M.D., Ramaker, M., Reich, H., Sajecki, J.L., Sell, S.K., Strules, J., Thompson, S., van Manen, F.T., Whitman, C., Williamson, R., Winslow, F., Kaelin, C.B., Marks, M.S., and Barsh, G.S., 2023, Genetic architecture and evolution of color variation in American black bears: Current Biology, v. 33, no. 1, p. 86-97, 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K.","contributorId":300245,"corporation":false,"usgs":false,"family":"Sell","given":"S.","email":"","middleInitial":"K.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":859714,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Strules, J.","contributorId":300246,"corporation":false,"usgs":false,"family":"Strules","given":"J.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":859715,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Thompson, S.","contributorId":77103,"corporation":false,"usgs":false,"family":"Thompson","given":"S.","email":"","affiliations":[],"preferred":false,"id":859737,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":859716,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Whitman, Craig 0000-0002-1187-4649 cwhitman@usgs.gov","orcid":"https://orcid.org/0000-0002-1187-4649","contributorId":206044,"corporation":false,"usgs":true,"family":"Whitman","given":"Craig","email":"cwhitman@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":859717,"contributorType":{"id":1,"text":"Authors"},"rank":37},{"text":"Williamson, R.","contributorId":300247,"corporation":false,"usgs":false,"family":"Williamson","given":"R.","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":859718,"contributorType":{"id":1,"text":"Authors"},"rank":38},{"text":"Winslow, F.","contributorId":300248,"corporation":false,"usgs":false,"family":"Winslow","given":"F.","email":"","affiliations":[{"id":24672,"text":"New Mexico Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":859719,"contributorType":{"id":1,"text":"Authors"},"rank":39},{"text":"Kaelin, C. B.","contributorId":300249,"corporation":false,"usgs":false,"family":"Kaelin","given":"C.","email":"","middleInitial":"B.","affiliations":[{"id":65057,"text":"School of Medicine, Stanford","active":true,"usgs":false}],"preferred":false,"id":859720,"contributorType":{"id":1,"text":"Authors"},"rank":40},{"text":"Marks, M. S.","contributorId":300250,"corporation":false,"usgs":false,"family":"Marks","given":"M.","email":"","middleInitial":"S.","affiliations":[{"id":64596,"text":"Perelman School of Medicine, University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":859721,"contributorType":{"id":1,"text":"Authors"},"rank":41},{"text":"Barsh, G. S.","contributorId":300251,"corporation":false,"usgs":false,"family":"Barsh","given":"G.","email":"","middleInitial":"S.","affiliations":[{"id":65054,"text":"HudsonAlpha","active":true,"usgs":false}],"preferred":false,"id":859722,"contributorType":{"id":1,"text":"Authors"},"rank":42}]}}
,{"id":70240631,"text":"70240631 - 2023 - Spatial and temporal distribution of sinuous ridges in southeastern Terra Sabaea and the northern region of Hellas Planitia, Mars","interactions":[],"lastModifiedDate":"2023-03-01T17:25:37.201183","indexId":"70240631","displayToPublicDate":"2022-12-16T07:14:28","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal distribution of sinuous ridges in southeastern Terra Sabaea and the northern region of Hellas Planitia, Mars","docAbstract":"<p id=\"sp0065\">Sinuous ridges are an important yet understudied component of Mars' hydrologic history. We have produced a map of sinuous ridges, valleys and channels, and tectonic ridges across southeastern Terra Sabaea and into northern Hellas Planitia (10°-45° S, 35°-80° E) using a CTX mosaic. Although we mapped different types of ridges and negative relief features, the focus of this paper are the sinuous ridges. We present here a new dataset of sinuous ridges that includes basic morphometry (e.g., length, width, sinuosity), morphology, and the types of terrains they are located on. We chose our region of interest because it includes surface ages spanning Mars' geologic history, with emphasis on Noachian and Hesperian terrains. The shift from either a warm and wet or a cold and icy environment to our modern cold and dry climate occurred towards the end of the Noachian and into the Hesperian, a critical temporal window to characterize fluvial landforms.</p><p id=\"sp0070\">Our CTX-based mapping significantly improved the documentation of fluvial landforms within the study region, with over an order of magnitude increase in the number of valley networks and channels, and nearly 1700 sinuous ridges. Sinuous ridges are found in concentrated settings, with the majority (∼80%) located within impact craters and relatively few (∼20%) on the intercrater plains. Fluvial features are prevalent on Early and Middle Noachian-aged terrain but are relatively rare in the Late Noachian, signifying a shift in fluvial activity that likely led to a decrease in channel incision and subsequent inversion of relief. A subset of sinuous ridges—radial ridges in high-elevation, degraded craters— are possible records of ancient proglacial lakes. The youngest sinuous ridges are associated with intracrater alluvial fans in a narrow zone (∼12°S to 30°S and&nbsp;∼&nbsp;62°E to 77°E). These formed in the Late Hesperian into the Amazonian, reflecting a later epoch of punctuated fluvial events driven by pre-existing topography and solar insolation.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2022.115399","usgsCitation":"Gullikson, A.L., Anderson, R.B., and Williams, R.M., 2023, Spatial and temporal distribution of sinuous ridges in southeastern Terra Sabaea and the northern region of Hellas Planitia, Mars: Icarus, v. 394, 115399, 14 p., https://doi.org/10.1016/j.icarus.2022.115399.","productDescription":"115399, 14 p.","ipdsId":"IP-129949","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":445100,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.icarus.2022.115399","text":"Publisher Index Page"},{"id":412941,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Hellas Plantia, Mars, Terra Sabaea","volume":"394","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gullikson, Amber L. 0000-0002-1505-3151","orcid":"https://orcid.org/0000-0002-1505-3151","contributorId":208679,"corporation":false,"usgs":true,"family":"Gullikson","given":"Amber","email":"","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":864024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Ryan B. 0000-0003-4465-2871 rbanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-4465-2871","contributorId":170054,"corporation":false,"usgs":true,"family":"Anderson","given":"Ryan","email":"rbanderson@usgs.gov","middleInitial":"B.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":864025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, Rebecca M.E.","contributorId":302332,"corporation":false,"usgs":false,"family":"Williams","given":"Rebecca","email":"","middleInitial":"M.E.","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":864026,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70242754,"text":"70242754 - 2023 - Disentangling direct and indirect effects of extreme events on coastal wetland communities","interactions":[],"lastModifiedDate":"2023-06-09T15:16:53.249242","indexId":"70242754","displayToPublicDate":"2022-12-16T06:56:32","publicationYear":"2023","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":"Disentangling direct and indirect effects of extreme events on coastal wetland communities","docAbstract":"<ol class=\"\"><li>One of the primary ways in which climate change will impact coastal freshwater wetlands is through changes in the frequency, intensity, timing and distribution of extreme weather events. Disentangling the direct and indirect mechanisms of population- and community-level responses to extreme events is vital to predicting how species composition of coastal wetlands will change under future conditions.</li><li>We extended static structural equation modelling approaches to incorporate system dynamics in a multi-year multispecies occupancy model to quantify the effects of extreme weather events on a coastal freshwater wetland system.</li><li>We used data from an 8-year study (2009–2016) on St. Marks National Wildlife Refuge in Florida, USA, to quantify species-specific and community-level changes in amphibian and fish occupancy associated with two flooding events in 2012 and 2013. We examine how physical changes to the landscape, including potential changes in salinity and increased wetland connectivity, may have contributed to or exacerbated the effects of these extreme weather events on the biota of isolated coastal wetlands.</li><li>We provide evidence that the primary effects of flooding on the amphibian community were through indirect mechanisms via changes in the composition of the sympatric fish community that may have had lethal (i.e. through direct predation) or non-lethal (i.e. through direct or indirect competitive interactions) effects. In addition, we have shown that amphibian species differed in their sensitivity to direct flooding effects and indirect changes in the fish community and wetland-specific conductance, which led to variable responses across the community. These effects led to the overall decline in amphibian species richness from 2009 to 2016, suggesting that wetland-breeding amphibian communities on St. Marks National Wildlife Refuge may not be resilient to predicted changes in coastal disturbance regimes because of climate change.</li><li>Understanding both direct and indirect effects, as well as species interactions, is important for predicting the effects of a changing climate on individual species, communities and ecosystems.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2656.13874","collaboration":"Pennsylvania State University","usgsCitation":"Davis, C.L., Walls, S.E., Barichivich, W.J., Brown, M., and Miller, D., 2023, Disentangling direct and indirect effects of extreme events on coastal wetland communities: Journal of Animal Ecology, v. 92, no. 6, 14 p.; Data Release, https://doi.org/10.1111/1365-2656.13874.","productDescription":"14 p.; Data Release","ipdsId":"IP-142600","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":445105,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.13874","text":"Publisher Index Page"},{"id":415845,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417811,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N4YYCQ","linkFileType":{"id":5,"text":"html"}}],"volume":"92","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-12-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Courtney L.","contributorId":181922,"corporation":false,"usgs":false,"family":"Davis","given":"Courtney","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":869703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walls, Susan E. 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":209862,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","middleInitial":"E.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":869704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barichivich, William J. 0000-0003-1103-6861","orcid":"https://orcid.org/0000-0003-1103-6861","contributorId":216371,"corporation":false,"usgs":true,"family":"Barichivich","given":"William","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":869705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Mary 0000-0002-5580-137X","orcid":"https://orcid.org/0000-0002-5580-137X","contributorId":207007,"corporation":false,"usgs":true,"family":"Brown","given":"Mary","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":869706,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, David A.W.","contributorId":198461,"corporation":false,"usgs":false,"family":"Miller","given":"David A.W.","affiliations":[],"preferred":false,"id":869707,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70245395,"text":"70245395 - 2023 - Understanding and modeling tephra transport: Lessons learned from the 18 May 1980 eruption of Mount St. Helens","interactions":[],"lastModifiedDate":"2023-06-22T11:56:26.815434","indexId":"70245395","displayToPublicDate":"2022-12-16T06:53:44","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Understanding and modeling tephra transport: Lessons learned from the 18 May 1980 eruption of Mount St. Helens","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Discoveries made during the 18 May 1980 eruption of Mount St. Helens advanced our understanding of tephra transport and deposition in fundamental ways. The eruption enabled detailed, quantitative observations of downwind cloud movement and particle sedimentation, along with the dynamics of co-pyroclastic-density current (PDC) clouds lofted from ground-hugging currents. The deposit was mapped and sampled over more than 150,000&nbsp;km<sup>2</sup><span>&nbsp;</span>within days of the event and remains among the most thoroughly documented tephra deposits in the world. Abundant observations were made possible by the large size of the eruption, its occurrence in good weather during daylight hours, cloud movement over a large, populated continent, and the availability of images from recently deployed satellites. These observations underpinned new, quantitative models for the rise and growth of volcanic plumes, the importance of umbrella clouds in dispersing ash, and the roles of particle aggregation and gravitational instabilities in removing ash from the atmosphere. Exceptional detail in the eruption chronology and deposit characterization helped identify the eruptive phases contributing to deposition in different sectors of the distal deposit. The eruption was the first to significantly impact civil aviation, leading to the earliest documented case of in-flight engine damage. Continued eruptive activity in 1980 also motivated pioneering use of meteorological models to forecast ash-cloud movement. In this paper, we consider the most important discoveries and how they changed the science of tephra transport.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s00445-022-01613-0","usgsCitation":"Mastin, L.G., Carey, S., Van Eaton, A.R., Eychenne, J., and Sparks, R., 2023, Understanding and modeling tephra transport: Lessons learned from the 18 May 1980 eruption of Mount St. Helens: Bulletin of Volcanology, v. 85, 4, 21 p., https://doi.org/10.1007/s00445-022-01613-0.","productDescription":"4, 21 p.","ipdsId":"IP-143793","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467132,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/gsofacpubs/1018","text":"External Repository"},{"id":418351,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.34180374032127,\n              46.3196569134532\n            ],\n            [\n              -122.34180374032127,\n              46.09927063967487\n            ],\n            [\n              -122.02059145969264,\n              46.09927063967487\n            ],\n            [\n              -122.02059145969264,\n              46.3196569134532\n            ],\n            [\n              -122.34180374032127,\n              46.3196569134532\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"85","noUsgsAuthors":false,"publicationDate":"2022-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Mastin, Larry G. 0000-0002-4795-1992","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":265985,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":875954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carey, Steven","contributorId":311127,"corporation":false,"usgs":false,"family":"Carey","given":"Steven","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":875955,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":875956,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":875957,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sparks, Russell","contributorId":311128,"corporation":false,"usgs":false,"family":"Sparks","given":"Russell","affiliations":[{"id":17708,"text":"Hawai`i Department of Land and Natural Resources Division of Aquatic, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":true,"id":875958,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70248126,"text":"70248126 - 2023 - Seasonal resource selection and movement ecology of free-ranging horses in the western United States","interactions":[],"lastModifiedDate":"2023-09-05T12:26:23.603732","indexId":"70248126","displayToPublicDate":"2022-12-14T07:22:41","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal resource selection and movement ecology of free-ranging horses in the western United States","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Understanding factors driving resource selection and habitat use of different species is an important component of management and conservation. Feral horses (<i>Equus caballus</i>) are free ranging across various vegetation types in the western United States, yet few studies have quantified their resource selection and seasonal use. We conducted a study to determine effects of vegetation community, distance to water, and topographic variables on seasonal resource selection in 2 feral horse populations in Great Basin sagebrush (<i>Artemisia</i><span>&nbsp;</span>spp.) ecosystems of west-central Utah, USA: Conger Herd Management Area (HMA) and Frisco HMA. We deployed global positioning system (GPS) radio-collars on 38 female horses and GPS-transmitters braided and glued into the tail hair of 14 males, collecting locations every 2 hours for 1–4 years between 2016 and 2020. We calculated home range size and core use area of social groups (harems) and bachelor males using auto-correlated kernel density estimators for each biologically defined season (breeding, fall, and winter) per study year. We examined seasonal home range size and overlap of harem groups and bachelor males and compared movement speed of bachelors and harems among seasons. We determined seasonal resource selection in a use-availability framework using resource selection functions. We hypothesized that horses would select for areas of high herbaceous vegetation, that water would be a key variable in resource selection models like other equids, and home range size in winter would be largest because horses can eat snow for hydration and could therefore roam farther from surface water. Mean annual home range size was 103.12 ± 37.38 km<sup>2</sup><span>&nbsp;</span>(SD) for Conger harems and 117.47 ± 32.75 km<sup>2</sup><span>&nbsp;</span>for Frisco harems. At Conger there was no difference in home range size between harem groups and bachelor males, but home range size was smaller in winter than other seasons, whereas winter home range size at Frisco was larger than other seasons. Bachelor males moved at higher speeds than harems during all seasons, and harem groups from both populations had lower movement speeds in winter. Harem groups had distinct winter ranges with little overlap on breeding season ranges. In both populations, all horses selected for herbaceous vegetation types and avoided forest relative to shrubland throughout the year. Harems at Frisco were consistently located closer to water sources, whereas selection for water sources by Conger harems varied seasonally, with winter having the lowest selection. Harem groups at Conger had an average of 10.6% of their home ranges outside the HMA boundary and Frisco harems had up to 66.8% outside, likely because of the horseshoe shape of Frisco HMA in which shrub meadows (foraging areas) comprise the horseshoe center, which is outside the HMA. Our results highlight the importance of water sources, which were a key predictor of horse movement patterns in our study. We emphasize the utility of telemetry devices to understand resource selection of feral horses at a fine scale, enabling management to be more targeted and facilitate planning.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.22341","usgsCitation":"Schoenecker, K., Esmaelli, S., and King, S.R., 2023, Seasonal resource selection and movement ecology of free-ranging horses in the western United States: Journal of Wildlife Management, v. 87, no. 2, e22341, 21 p., https://doi.org/10.1002/jwmg.22341.","productDescription":"e22341, 21 p.","ipdsId":"IP-117794","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":445114,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22341","text":"Publisher Index Page"},{"id":435542,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90NHXZL","text":"USGS data release","linkHelpText":"GPS locations of feral horses in Utah, USA, from 2016-2020"},{"id":420468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70239220,"text":"70239220 - 2023 - Quantifying connectivity and its effects on sediment budgeting for an agricultural basin, Chesapeake Bay Watershed, United States","interactions":[],"lastModifiedDate":"2023-01-04T12:38:17.863489","indexId":"70239220","displayToPublicDate":"2022-12-14T06:35:51","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying connectivity and its effects on sediment budgeting for an agricultural basin, Chesapeake Bay Watershed, United States","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Excessive sediment runoff as a result of anthropogenic activities is a major concern for watershed ecologic health. This study sought to determine the sources, storage, and delivery of sediment using a sediment budget approach for the predominantly pasture and forested Smith Creek watershed, Virginia United States, a tributary to the Chesapeake Bay. Utilizing a novel combination of the Universal Soil Loss Equation (USLE) model and an index of connectivity along with field surveys of channels, this study indicated that streambanks and pastures were major sources of sediment. Overestimation of fine-grained sediment flux exported from the watershed according to this study's models (3811 Mg/year) compared to export measured at the outlet (2918 Mg/year) most likely indicates underestimation of storage in the watershed from unaccounted for geomorphic features (ponds, toe slopes, and colluvial slopes). Sediment budget results indicating that streambanks are a major source of sediment in the watershed support previous sediment fingerprinting results and provide a framework for managers to address the sediment problem in Smith Creek and similar tributaries to the Chesapeake Bay.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14777","usgsCitation":"Clifton, Z.J., Gellis, A.C., Cashman, M.J., Katoski, M.P., Nibert, L.A., and Noe, G.E., 2023, Quantifying connectivity and its effects on sediment budgeting for an agricultural basin, Chesapeake Bay Watershed, United States: Hydrological Processes, v. 36, no. 12, e14777, 26 p., https://doi.org/10.1002/hyp.14777.","productDescription":"e14777, 26 p.","ipdsId":"IP-133801","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":435543,"rank":0,"type":{"id":30,"text":"Data 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-80.013427734375,\n              37.3002752813443\n            ],\n            [\n              -79.8486328125,\n              37.23907530202184\n            ],\n            [\n              -79.771728515625,\n              37.18657859524883\n            ],\n            [\n              -79.6728515625,\n              37.07271048132943\n            ],\n            [\n              -79.541015625,\n              37.09900294387622\n            ],\n            [\n              -79.354248046875,\n              37.142803443716836\n            ],\n            [\n              -79.1455078125,\n              37.10776507118514\n            ],\n            [\n              -79.112548828125,\n              37.055177106660814\n            ],\n            [\n              -78.936767578125,\n              36.932330061503144\n            ],\n            [\n              -78.837890625,\n              36.94111143010769\n            ],\n            [\n              -78.662109375,\n              37.055177106660814\n            ],\n            [\n              -78.486328125,\n              37.03763967977139\n            ],\n            [\n              -78.42041015625,\n              36.94111143010769\n            ],\n            [\n              -78.20068359374999,\n              36.96744946416934\n            ],\n            [\n              -77.904052734375,\n              37.03763967977139\n            ],\n            [\n              -77.750244140625,\n              37.081475648860525\n            ],\n            [\n              -77.53051757812499,\n              37.081475648860525\n            ],\n            [\n              -77.354736328125,\n              37.07271048132943\n            ],\n            [\n              -77.069091796875,\n              37.081475648860525\n            ],\n            [\n              -76.959228515625,\n              37.01132594307015\n            ],\n            [\n              -76.893310546875,\n              36.932330061503144\n            ],\n            [\n              -76.871337890625,\n              36.83566824724438\n            ],\n            [\n              -76.849365234375,\n              36.677230602346214\n            ],\n            [\n              -76.7724609375,\n              36.527294814546245\n            ],\n            [\n              -76.629638671875,\n              36.55377524336089\n            ],\n            [\n              -76.46484375,\n              36.589068371399115\n            ],\n            [\n              -76.35498046875,\n              36.48314061639213\n            ],\n            [\n              -76.256103515625,\n              36.57142382346277\n            ],\n            [\n              -76.190185546875,\n              36.66841891894786\n            ],\n            [\n              -76.0693359375,\n              36.65079252503471\n            ],\n            [\n              -75.9375,\n              36.66841891894786\n            ],\n            [\n              -75.948486328125,\n              36.76529191711624\n            ],\n            [\n              -75.904541015625,\n              37.01132594307015\n            ],\n            [\n              -75.926513671875,\n              37.17782559332976\n            ],\n            [\n              -75.882568359375,\n              37.42252593456307\n            ],\n            [\n              -75.618896484375,\n              37.640334898059486\n            ],\n            [\n              -75.509033203125,\n              37.82280243352756\n            ],\n            [\n              -75.38818359375,\n              38.013476231041935\n            ],\n            [\n              -75.16845703124999,\n              38.272688535980976\n            ],\n            [\n              -75.1904296875,\n              38.41916639395372\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-12-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Clifton, Zachary J. 0000-0002-8148-5454","orcid":"https://orcid.org/0000-0002-8148-5454","contributorId":220551,"corporation":false,"usgs":true,"family":"Clifton","given":"Zachary","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cashman, Matthew J. 0000-0002-6635-4309","orcid":"https://orcid.org/0000-0002-6635-4309","contributorId":203315,"corporation":false,"usgs":true,"family":"Cashman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":860804,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Katoski, Michelle P. 0000-0001-5550-0705","orcid":"https://orcid.org/0000-0001-5550-0705","contributorId":300555,"corporation":false,"usgs":true,"family":"Katoski","given":"Michelle","middleInitial":"P.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nibert, Lucas A 0000-0003-3542-1596","orcid":"https://orcid.org/0000-0003-3542-1596","contributorId":223438,"corporation":false,"usgs":false,"family":"Nibert","given":"Lucas","email":"","middleInitial":"A","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":860806,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":860807,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70239073,"text":"70239073 - 2023 - Efficacy of bear spray as a deterrent against polar bears","interactions":[],"lastModifiedDate":"2023-03-01T17:06:48.254688","indexId":"70239073","displayToPublicDate":"2022-12-14T06:33:28","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Efficacy of bear spray as a deterrent against polar bears","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Although there have been few attempts to systematically analyze information on the use of deterrents on polar bears (<i>Ursus maritimus</i>), understanding their effectiveness in mitigating human-polar bear conflicts is critical to ensuring both human safety and polar bear conservation. To fill this knowledge gap, we analyzed 19 incidents involving the use of bear spray on free-ranging polar bears from 1986 to 2019 in Canada, Russia, and the United States to evaluate the effectiveness of bear spray as a polar bear deterrent. We found that bear spray was an effective deterrent in close-range encounters with polar bears, stopping undesirable behavior in 18 of 19 incidents. Bear spray effectively deterred both curious and aggressive polar bears, including polar bears attempting to attack people. The mean distance between user and bear at the time of spraying was 2 m (min–max = 0.2–10.0 m, mode = 1 m), though bears were usually first seen at greater distances. Bear spray was successfully deployed against polar bears in all 4 seasons. Wind affected spray performance in 1 of 19 of incidents. In 8 of 14 bear spray incidents, other deterrents were used without success before bear spray was used effectively to deter polar bears. No humans or polar bears were killed or injured in any of the incidents in which bear spray was used. We also analyzed 54 polar bear attacks and attempted attacks on humans where bear spray was not carried. The data suggest that in 93% of those incidents, the use of bear spray might have saved the lives of both the people and bears involved if it had been available and used. Our analysis improves our understanding of the effectiveness of bear spray for polar bear conflict mitigation.</p></div></div>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1403","usgsCitation":"Wilder, J., Mangipane, L., Atwood, T.C., Kochnev, A., Smith, T., and Vongraven, D., 2023, Efficacy of bear spray as a deterrent against polar bears: Wildlife Society Bulletin, v. 47, no. 1, e1403, 11 p., https://doi.org/10.1002/wsb.1403.","productDescription":"e1403, 11 p.","ipdsId":"IP-136228","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":445124,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wsb.1403","text":"Publisher Index Page"},{"id":410993,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilder, James","contributorId":152610,"corporation":false,"usgs":false,"family":"Wilder","given":"James","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":859952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mangipane, Lindsey","contributorId":201731,"corporation":false,"usgs":false,"family":"Mangipane","given":"Lindsey","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":859953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":859954,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kochnev, Anatoly A.","contributorId":292912,"corporation":false,"usgs":false,"family":"Kochnev","given":"Anatoly A.","affiliations":[{"id":63069,"text":"Russian Academy of the Sciences","active":true,"usgs":false}],"preferred":false,"id":859955,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Tom","contributorId":207440,"corporation":false,"usgs":false,"family":"Smith","given":"Tom","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":859956,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vongraven, Dag","contributorId":131092,"corporation":false,"usgs":false,"family":"Vongraven","given":"Dag","email":"","affiliations":[{"id":7238,"text":"Norwegian Polar Institute","active":true,"usgs":false}],"preferred":false,"id":859957,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70247517,"text":"70247517 - 2023 - Estimates of k0 and effects on ground motions in the San Francisco Bay area","interactions":[],"lastModifiedDate":"2023-08-11T13:23:21.704651","indexId":"70247517","displayToPublicDate":"2022-12-13T07:00:33","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Estimates of k<sub>0</sub> and effects on ground motions in the San Francisco Bay area","title":"Estimates of k0 and effects on ground motions in the San Francisco Bay area","docAbstract":"<p><span>Ground‐motion studies are a key component of seismic hazard analyses and often rely on information of the source, path, and site. Extensive research has been done on each of these parameters; however, site‐specific studies are of particular interest to seismic hazard studies, especially in the field of earthquake engineering, as near‐site conditions can have a significant impact on the resulting ground motion at a site. There has been much focus on the constraint of site parameters and their application to seismic hazard studies, especially in the development of ground‐motion models (GMMs). Kappa is an observational parameter describing the high‐frequency attenuation of spectra, and its site contribution (</span><span class=\"inline-formula no-formula-id\">⁠<span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>&amp;#x3BA;</mi><mn>0</mn></msub></math>\"><span id=\"MathJax-Span-11\" class=\"math\"><span><span id=\"MathJax-Span-12\" class=\"mrow\"><span id=\"MathJax-Span-13\" class=\"msub\"><span id=\"MathJax-Span-14\" class=\"mi\">κ</span><span id=\"MathJax-Span-15\" class=\"mn\">0</span></span></span></span></span></span></span><span>) has shown to be a good predictor of high‐frequency ground motions; however, measurements are often limited. In this study, we develop a <span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>&amp;#x3BA;</mi><mn>0</mn></msub></math>\"><span id=\"MathJax-Span-11\" class=\"math\"><span id=\"MathJax-Span-12\" class=\"mrow\"><span id=\"MathJax-Span-13\" class=\"msub\"><span id=\"MathJax-Span-14\" class=\"mi\">κ</span><span id=\"MathJax-Span-15\" class=\"mn\">0</span></span></span></span></span></span></span><span>&nbsp;dataset for the San Francisco Bay area (SFBA) by estimating&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-5-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>&amp;#x3BA;</mi><mn>0</mn></msub></math>\"><span id=\"MathJax-Span-21\" class=\"math\"><span><span id=\"MathJax-Span-22\" class=\"mrow\"><span id=\"MathJax-Span-23\" class=\"msub\"><span id=\"MathJax-Span-24\" class=\"mi\">κ</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">0</span></span></span><span>&nbsp;for 228 stations, and we produce a continuous regional map of&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-6-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>&amp;#x3BA;</mi><mn>0</mn></msub></math>\"><span id=\"MathJax-Span-26\" class=\"math\"><span><span id=\"MathJax-Span-27\" class=\"mrow\"><span id=\"MathJax-Span-28\" class=\"msub\"><span id=\"MathJax-Span-29\" class=\"mi\">κ</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">0</span></span>⁠</span><span>. We find <span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>&amp;#x3BA;</mi><mn>0</mn></msub></math>\"><span id=\"MathJax-Span-11\" class=\"math\"><span id=\"MathJax-Span-12\" class=\"mrow\"><span id=\"MathJax-Span-13\" class=\"msub\"><span id=\"MathJax-Span-14\" class=\"mi\">κ</span><span id=\"MathJax-Span-15\" class=\"mn\">0</span></span></span></span></span></span></span><span>&nbsp;to range between 0.003 and 0.072&nbsp;s, with larger values concentrating on the east, north, and south sides of the bay, and lower values concentrating on the west side. We also evaluate the robustness of&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-8-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>&amp;#x3BA;</mi><mn>0</mn></msub></math>\"><span id=\"MathJax-Span-36\" class=\"math\"><span><span id=\"MathJax-Span-37\" class=\"mrow\"><span id=\"MathJax-Span-38\" class=\"msub\"><span id=\"MathJax-Span-39\" class=\"mi\">κ</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">0</span></span></span><span>&nbsp;as a site parameter and find it to correlate with peak ground acceleration. These estimates of&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-9-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>&amp;#x3BA;</mi><mn>0</mn></msub></math>\"><span id=\"MathJax-Span-41\" class=\"math\"><span><span id=\"MathJax-Span-42\" class=\"mrow\"><span id=\"MathJax-Span-43\" class=\"msub\"><span id=\"MathJax-Span-44\" class=\"mi\">κ</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">0</span></span></span><span>&nbsp;can add predictive power to GMMs, thus increasing the accuracy of predicted ground motion and improving the robustness of ground‐motion studies in the SFBA.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120220046","usgsCitation":"Nye, T., Sahakian, V., King, E., Baltay Sundstrom, A.S., and Klimasewski, A., 2023, Estimates of k0 and effects on ground motions in the San Francisco Bay area: Bulletin of the Seismological Society of America, v. 113, no. 2, p. 823-842, https://doi.org/10.1785/0120220046.","productDescription":"20 p.","startPage":"823","endPage":"842","ipdsId":"IP-144911","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":419696,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francsico Bay area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.29195503444339,\n              38.66666455573278\n            ],\n            [\n              -123.29195503444339,\n              36.89623058193166\n            ],\n            [\n              -121.22741114527435,\n              36.89623058193166\n            ],\n            [\n              -121.22741114527435,\n              38.66666455573278\n            ],\n            [\n              -123.29195503444339,\n              38.66666455573278\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"113","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Nye, Tara","contributorId":318226,"corporation":false,"usgs":false,"family":"Nye","given":"Tara","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":879964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sahakian, Valerie J.","contributorId":208097,"corporation":false,"usgs":false,"family":"Sahakian","given":"Valerie J.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":879965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"King, Elias","contributorId":318227,"corporation":false,"usgs":false,"family":"King","given":"Elias","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":879966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":879967,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Klimasewski, Alexis","contributorId":219664,"corporation":false,"usgs":false,"family":"Klimasewski","given":"Alexis","email":"","affiliations":[{"id":40043,"text":"U. Oregon","active":true,"usgs":false}],"preferred":false,"id":879968,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70242845,"text":"70242845 - 2023 - A regionally varying habitat model to inform management for greater sage-grouse persistence across their range","interactions":[],"lastModifiedDate":"2023-04-20T11:35:25.223462","indexId":"70242845","displayToPublicDate":"2022-12-13T06:32:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"A regionally varying habitat model to inform management for greater sage-grouse persistence across their range","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"ab0010\" class=\"abstract author\"><div id=\"abs0010\"><p id=\"sp0035\">Identifying habitat needs for species with large distributions is challenging because species-habitat associations may vary across scales and regions (spatial nonstationarity). Furthermore, management efforts often cross jurisdictional boundaries, complicating the development of cohesive conservation strategies among management entities. The greater sage-grouse (<i>Centrocercus urophasianus</i><span>) is a rapidly declining species that spans 11&nbsp;U.S.&nbsp;states and responds to habitat conditions across a wide range of spatial scales and regions. Allowing for regional variance in species-habitat associations and suitability predictions could systematically identify important habitats at levels relevant to management. We collaboratively developed a model with Bureau of Land Management (BLM) biologists that: (1) evaluated the scale&nbsp;of&nbsp;effect for different environmental covariates; (2) accounted for regional differences in population-level responses; and (3) predicted probabilities of persistence across the U.S. occupied range. We modeled range-wide lek persistence data (6615 communal&nbsp;breeding sites&nbsp;classified as active or inactive) as a function of environmental covariates. Environmental covariates included sagebrush cover, pinyon-juniper cover, topography, precipitation, point and line disturbance densities, and landscape configuration metrics. Our model treated habitat assessment areas – regionally delineated by BLM biologists – as random intercepts and slopes that allowed for&nbsp;geographic variation&nbsp;in species-habitat associations and predicted probabilities of lek persistence. Our final model indicated support for 12 environmental covariates predicting lek persistence at scales extending between 1- to 15-km radii from lek centers, and a covariate measuring distance to the occupied range boundary. Five of these covariates showed significant regionally varying responses: sagebrush clumpiness (a measure of habitat aggregation), pinyon-juniper cover, point disturbance of anthropogenic features such as energy infrastructure and communication towers, elevation, and a topographic index associated with mesic habitats. This spatial&nbsp;nonstationarity&nbsp;indicates unitary range-wide recommendations, or rules-of-thumb with respect to their effects on lek persistence, may be problematic for these environmental conditions. For covariates that did not include random slopes, and which were potentially amenable to management actions, we found that leks were predicted to become extirpated when sagebrush cover fell below 9.6 % (summarized at the 3.2-km radius extent), and the proportion of classified sagebrush habitat fell below 0.7 (1-km). We produced a continuous predictive probability surface of lek persistence which we binned based on model sensitivity thresholds to produce habitat quality categories. The highest quality habitat (capturing 50 % of active leks) covered 25.5 % of the occupied range, while the combined lowest through highest quality habitats (capturing 95 % of active leks) covered 65.0 %. Accommodating regional environmental differences in models that are relevant to habitat management planning will help ensure their applicability to targeted goals. Continuous collaboration between modelers and land managers early in the modeling process increases the likelihood of this outcome.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02349","usgsCitation":"Wann, G.T., Van Schmidt, N.D., Shyvers, J.E., Tarbox, B.C., McLachlan, M.M., O’Donnell, M.S., Titolo, A.J., Coates, P.S., Edmunds, D.R., Heinrichs, J., Monroe, A., and Aldridge, C.L., 2023, A regionally varying habitat model to inform management for greater sage-grouse persistence across their range: Global Ecology and Conservation, v. 41, e02349, 14 p., https://doi.org/10.1016/j.gecco.2022.e02349.","productDescription":"e02349, 14 p.","ipdsId":"IP-134391","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445132,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02349","text":"Publisher Index Page"},{"id":435548,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95YAUPH","text":"USGS data release","linkHelpText":"U.S. range-wide spatial prediction layers of lek persistence probabilities for greater sage-grouse"},{"id":416045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wann, Gregory T. 0000-0001-9076-7819 wanng@usgs.gov","orcid":"https://orcid.org/0000-0001-9076-7819","contributorId":3855,"corporation":false,"usgs":true,"family":"Wann","given":"Gregory","email":"wanng@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":869967,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Schmidt, Nathan D. 0000-0002-5973-7934","orcid":"https://orcid.org/0000-0002-5973-7934","contributorId":288931,"corporation":false,"usgs":true,"family":"Van Schmidt","given":"Nathan","email":"","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":869968,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shyvers, Jessica E. 0000-0002-4307-0004","orcid":"https://orcid.org/0000-0002-4307-0004","contributorId":288929,"corporation":false,"usgs":true,"family":"Shyvers","given":"Jessica","email":"","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":869969,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tarbox, Bryan C. 0000-0001-5040-3949","orcid":"https://orcid.org/0000-0001-5040-3949","contributorId":288930,"corporation":false,"usgs":true,"family":"Tarbox","given":"Bryan","email":"","middleInitial":"C.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":869970,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McLachlan, Megan M.","contributorId":300301,"corporation":false,"usgs":false,"family":"McLachlan","given":"Megan","email":"","middleInitial":"M.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":869971,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":869972,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Titolo, Anthony J","contributorId":300302,"corporation":false,"usgs":false,"family":"Titolo","given":"Anthony","email":"","middleInitial":"J","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":869973,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":869974,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Edmunds, David R. 0000-0002-5212-8271 dedmunds@usgs.gov","orcid":"https://orcid.org/0000-0002-5212-8271","contributorId":152210,"corporation":false,"usgs":true,"family":"Edmunds","given":"David","email":"dedmunds@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":869975,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Heinrichs, Julie A. 0000-0001-7733-5034","orcid":"https://orcid.org/0000-0001-7733-5034","contributorId":240888,"corporation":false,"usgs":false,"family":"Heinrichs","given":"Julie A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":869976,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":869977,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":869978,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70238784,"text":"70238784 - 2023 - Modeling of historical and current distributions of lone star tick, Amblyomma americanum (Acari: Ixodidae), is consistent with ancestral range recovery","interactions":[],"lastModifiedDate":"2023-02-02T17:49:46.942846","indexId":"70238784","displayToPublicDate":"2022-12-08T08:52:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1610,"text":"Experimental and Applied Acarology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Modeling of historical and current distributions of lone star tick, <i>Amblyomma americanum</i> (Acari: Ixodidae), is consistent with ancestral range recovery","title":"Modeling of historical and current distributions of lone star tick, Amblyomma americanum (Acari: Ixodidae), is consistent with ancestral range recovery","docAbstract":"<p><span>The lone star tick,&nbsp;</span><i>Amblyomma americanum</i><span>&nbsp;L., is a three-host hard tick notorious for aggressive feeding behavior. In the early to mid-20th century, this species’ range was mostly limited to the southern USA. Since the 1950s,&nbsp;</span><i>A. americanum</i><span>&nbsp;has been detected in many new localities in the western, northcentral, and northeastern regions of the country. To examine the influence of climate on this apparent expansion, we used historical (1748–1950) lone star locations from the literature and museum records to model areas suitable for this species based on past environmental conditions in the late 1800s – early 1900s. We then projected this model forward using present (2011–2020) climatic conditions and compared the two for evidence of climate-associated distributional shifts. A maximum entropy distribution or Maxent model was generated by using&nbsp;</span><i>a priori</i><span>&nbsp;selected climatic variables including temperature, precipitation, and vapor pressure deficit. Temperature and vapor pressure deficit were selected as the most important factors in creating a sensitive and specific model (success rate = 82.6 ± 6.1%) that had a good fit to the existing data and was significantly better than a random model [partial ROC (receiver operating characteristic) to AUC (area under the ROC curve) ratio = 1.97 ± 0.07,&nbsp;</span><i>P</i><span> &lt; 0.001]. The present projected model was tested with an independent dataset of curated museum records (1952–2020) and found to be 95.6% accurate. Comparison of past and present models revealed &gt; 98%&nbsp;</span><i>A. americanum</i><span>&nbsp;niche overlap. The model suggests that some areas along the western fringe are becoming less suitable for&nbsp;</span><i>A. americanum</i><span>, whereas areas in some Great Lakes and coastal northeastern regions are becoming more suitable, results that are compatible with possible effects of climate change. However, these changes are minor, and overall climate in North America does not appear to have changed in ways significant to&nbsp;</span><i>A. americanum</i><span>’s distribution. These findings are consistent with an alternative hypothesis that recent changes in&nbsp;</span><i>A. americanum</i><span>’s distribution are a result of this species re-occupying its historical range, driven predominantly by factors other than climate, such as shifts in land use and population densities of major hosts.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10493-022-00765-0","usgsCitation":"Rochlin, I., Egizi, A., and Ginsberg, H., 2023, Modeling of historical and current distributions of lone star tick, Amblyomma americanum (Acari: Ixodidae), is consistent with ancestral range recovery: Experimental and Applied Acarology, v. 89, p. 85-103, https://doi.org/10.1007/s10493-022-00765-0.","productDescription":"19 p.","startPage":"85","endPage":"103","ipdsId":"IP-134334","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":498447,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/pls_facpubs/132","text":"External Repository"},{"id":410279,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","noUsgsAuthors":false,"publicationDate":"2022-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Rochlin, Ilia","contributorId":299797,"corporation":false,"usgs":false,"family":"Rochlin","given":"Ilia","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":858696,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Egizi, Andrea","contributorId":299798,"corporation":false,"usgs":false,"family":"Egizi","given":"Andrea","email":"","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":858697,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ginsberg, Howard 0000-0002-4933-2466","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":15473,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":858698,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
]}