{"pageNumber":"128","pageRowStart":"3175","pageSize":"25","recordCount":46644,"records":[{"id":70240823,"text":"70240823 - 2023 - Point count offsets for estimating population sizes of north American landbirds","interactions":[],"lastModifiedDate":"2023-03-15T15:10:22.837786","indexId":"70240823","displayToPublicDate":"2022-12-07T06:34:35","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"title":"Point count offsets for estimating population sizes of north American landbirds","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Bird monitoring in North America over several decades has generated many open databases, housing millions of structured and semi-structured bird observations. These provide the opportunity to estimate bird densities and population sizes, once variation in factors such as underlying field methods, timing, land cover, proximity to roads, and uneven spatial coverage are accounted for. To facilitate integration across databases, we introduce NA-POPS: Point Count Offsets for Population Sizes of North American Landbirds. NA-POPS is a large-scale, multi-agency project providing an open-source database of detectability functions for all North American landbirds. These detectability functions allow the integration of data from across disparate survey methods using the QPAD approach, which considers the probability of detection (q) and availability (p) of birds in relation to area (a) and density (d). To date, NA-POPS has compiled over 7.1 million data points spanning 292 projects from across North America, and produced detectability functions for 338 landbird species. Here, we describe the methods used to curate these data and generate these detectability functions, as well as the open-access nature of the resulting database.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/ibi.13169","usgsCitation":"Edwards, B., Smith, A., Docherety, T., Gahbauer, M., Gillespie, C., Grinde, A., Harmer, T., Iles, D., Matsuoka, S.M., Michel, N., Murray, N., Niemi, G., Pasher, J., Pavlacky, D., Robinson, B., Ryder, B., Solymos, P., Stralberg, D., and Zlonis, E., 2023, Point count offsets for estimating population sizes of north American landbirds: Ibis, v. 165, no. 2, p. 482-503, https://doi.org/10.1111/ibi.13169.","productDescription":"22 p.","startPage":"482","endPage":"503","ipdsId":"IP-137637","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":445162,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ibi.13169","text":"Publisher Index Page"},{"id":413337,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"165","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Edwards, B.P.M.","contributorId":302637,"corporation":false,"usgs":false,"family":"Edwards","given":"B.P.M.","email":"","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":864952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, A.C.","contributorId":302638,"corporation":false,"usgs":false,"family":"Smith","given":"A.C.","affiliations":[{"id":12590,"text":"Canadian Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":864953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Docherety, T.D.S.","contributorId":302639,"corporation":false,"usgs":false,"family":"Docherety","given":"T.D.S.","email":"","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":864954,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gahbauer, M.A.","contributorId":302640,"corporation":false,"usgs":false,"family":"Gahbauer","given":"M.A.","email":"","affiliations":[{"id":12590,"text":"Canadian Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":864955,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gillespie, C.R.","contributorId":205138,"corporation":false,"usgs":false,"family":"Gillespie","given":"C.R.","email":"","affiliations":[{"id":37031,"text":"Nebraska Cooperative Fish & Wildlife Research Unit, University of Nebraska-Lincoln, Lincoln, Nebraska","active":true,"usgs":false}],"preferred":false,"id":864956,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grinde, A.R.","contributorId":302641,"corporation":false,"usgs":false,"family":"Grinde","given":"A.R.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":864957,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harmer, T.","contributorId":302642,"corporation":false,"usgs":false,"family":"Harmer","given":"T.","email":"","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":864958,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Iles, D.","contributorId":302643,"corporation":false,"usgs":false,"family":"Iles","given":"D.","email":"","affiliations":[{"id":12590,"text":"Canadian Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":864959,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Matsuoka, Steven M. 0000-0001-6415-1885 smatsuoka@usgs.gov","orcid":"https://orcid.org/0000-0001-6415-1885","contributorId":184173,"corporation":false,"usgs":true,"family":"Matsuoka","given":"Steven","email":"smatsuoka@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":864960,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Michel, N.L.","contributorId":302644,"corporation":false,"usgs":false,"family":"Michel","given":"N.L.","email":"","affiliations":[{"id":27800,"text":"National Audubon Society","active":true,"usgs":false}],"preferred":false,"id":864961,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Murray, N.L.","contributorId":302645,"corporation":false,"usgs":false,"family":"Murray","given":"N.L.","email":"","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":864962,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Niemi, G.","contributorId":302646,"corporation":false,"usgs":false,"family":"Niemi","given":"G.","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":864963,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Pasher, J.","contributorId":302647,"corporation":false,"usgs":false,"family":"Pasher","given":"J.","email":"","affiliations":[{"id":12590,"text":"Canadian Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":864964,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Pavlacky, D.","contributorId":302648,"corporation":false,"usgs":false,"family":"Pavlacky","given":"D.","email":"","affiliations":[{"id":25644,"text":"Bird Conservancy of the Rockies","active":true,"usgs":false}],"preferred":false,"id":864965,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Robinson, B.","contributorId":193847,"corporation":false,"usgs":false,"family":"Robinson","given":"B.","email":"","affiliations":[],"preferred":false,"id":864966,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Ryder, B.","contributorId":302649,"corporation":false,"usgs":false,"family":"Ryder","given":"B.","email":"","affiliations":[{"id":25644,"text":"Bird Conservancy of the Rockies","active":true,"usgs":false}],"preferred":false,"id":864967,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Solymos, P.","contributorId":302650,"corporation":false,"usgs":false,"family":"Solymos","given":"P.","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":864968,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Stralberg, D.","contributorId":302651,"corporation":false,"usgs":false,"family":"Stralberg","given":"D.","affiliations":[{"id":13540,"text":"Canadian Forest Service","active":true,"usgs":false}],"preferred":false,"id":864969,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Zlonis, E.J.","contributorId":302652,"corporation":false,"usgs":false,"family":"Zlonis","given":"E.J.","email":"","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":864970,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}}
,{"id":70238767,"text":"70238767 - 2023 - Estimating reproductive and juvenile survival rates when offspring ages are uncertain: A novel multievent mark-resight model with beluga whale case study","interactions":[],"lastModifiedDate":"2023-02-14T14:46:31.815152","indexId":"70238767","displayToPublicDate":"2022-12-06T06:33:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Estimating reproductive and juvenile survival rates when offspring ages are uncertain: A novel multievent mark-resight model with beluga whale case study","docAbstract":"<ol class=\"\"><li>Understanding the survival and reproductive rates of a population is critical to determining its long-term dynamics and viability. Mark-resight models are often used to estimate these demographic rates, but estimation of survival and reproductive rates is challenging, especially for wide-ranging, patchily distributed, or cryptic species. In particular, existing mark-resight models cannot accommodate data from populations in which offspring remain with parents for multiple years, are not always detected, and cannot be aged with certainty.</li><li>Here we describe a Bayesian multievent mark-resight modelling framework that uses all available adult and adult-offspring sightings (including sightings with older offspring of uncertain age) to estimate reproductive rates and survival rates of adults and juveniles. We extend existing multievent mark-resight models that typically only incorporate adult breeding state uncertainty by additionally accounting for age uncertainty in unmarked offspring and uncertainty in the duration of the mother-offspring association. We describe our model in general terms and with a simple illustrative example, then apply it in a more complex empirical setting using 13 years of photo-ID data from a critically endangered population of beluga whales<span>&nbsp;</span><i>Delphinapterus leucas</i>. We evaluated model performance using simulated data under a range of sample sizes, and adult and offspring detection rates.</li><li>Applying our model to the beluga data yielded precise estimates for all demographic rates of interest (despite substantial uncertainty in calf ages), including nonbreeder survival and reproductive rates lower than in other beluga populations. Simulations suggested our model yields asymptotically unbiased parameter estimates with good precision and low bias even with moderate sample sizes and detection rates.</li><li>This work represents an important new development in multievent mark-resight modelling, allowing estimation of reproductive and juvenile survival rates for populations with extended adult—offspring associations and uncertain offspring ages (e.g. some marine mammals, elephants, bears, great apes, bats and birds). Our model facilitated estimation of robust demographic rates for an endangered beluga population that were previously inestimable (e.g. nonbreeder and juvenile survival, reproductive rate) and that will yield new insights into this population's continued decline.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.14032","usgsCitation":"Himes Boor, G.K., McGuire, T.L., Warlick, A.J., Taylor, R.L., Converse, S.J., McClung, J.R., and Stephens, A.D., 2023, Estimating reproductive and juvenile survival rates when offspring ages are uncertain: A novel multievent mark-resight model with beluga whale case study: Methods in Ecology and Evolution, v. 14, no. 2, p. 631-642, https://doi.org/10.1111/2041-210X.14032.","productDescription":"12 p.","startPage":"631","endPage":"642","ipdsId":"IP-133177","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":445167,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.14032","text":"Publisher Index Page"},{"id":410192,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Himes Boor, Gina K","contributorId":299748,"corporation":false,"usgs":false,"family":"Himes Boor","given":"Gina","email":"","middleInitial":"K","affiliations":[{"id":64940,"text":"Montana State University, Ecology Department","active":true,"usgs":false}],"preferred":false,"id":858522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Tamara L","contributorId":299749,"corporation":false,"usgs":false,"family":"McGuire","given":"Tamara","email":"","middleInitial":"L","affiliations":[{"id":64941,"text":"The Cook Inlet Beluga Whale Photo-ID Project","active":true,"usgs":false}],"preferred":false,"id":858523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warlick, Amanda J.","contributorId":299750,"corporation":false,"usgs":false,"family":"Warlick","given":"Amanda","email":"","middleInitial":"J.","affiliations":[{"id":13190,"text":"School of Aquatic and Fishery Sciences, University of Washington","active":true,"usgs":false}],"preferred":false,"id":858524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":858525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":858526,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McClung, John R","contributorId":299751,"corporation":false,"usgs":false,"family":"McClung","given":"John","email":"","middleInitial":"R","affiliations":[{"id":64941,"text":"The Cook Inlet Beluga Whale Photo-ID Project","active":true,"usgs":false}],"preferred":false,"id":858527,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stephens, Amber D","contributorId":299752,"corporation":false,"usgs":false,"family":"Stephens","given":"Amber","email":"","middleInitial":"D","affiliations":[{"id":64941,"text":"The Cook Inlet Beluga Whale Photo-ID Project","active":true,"usgs":false}],"preferred":false,"id":858528,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70239254,"text":"70239254 - 2023 - Geochemistry and fluxes of gases from hydrothermal features at Newberry Volcano, Oregon, USA","interactions":[],"lastModifiedDate":"2023-01-10T15:16:44.498624","indexId":"70239254","displayToPublicDate":"2022-12-05T09:12:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Geochemistry and fluxes of gases from hydrothermal features at Newberry Volcano, Oregon, USA","docAbstract":"<p><span>We present the chemical and isotopic compositions of gases and fluxes of CO</span><sub>2</sub><span>&nbsp;from the hydrothermal features of Newberry Volcano, a large composite volcano located in Oregon's Cascade Range with a summit caldera that hosts two lakes, Paulina and East Lakes. Gas samples were collected from 1982 to 2021 from Paulina Hot Springs (PHS) on the shore of Paulina Lake, East Lake Hot Springs (ELHS) on the shore of East Lake, and Obsidian Flow Gas Seep (OFGS), an area of diffuse gas emissions. Surveys of CO</span><sub>2</sub><span>&nbsp;flux were conducted in 2020 at OFGS (1400&nbsp;m</span><sup>2</sup><span>) and East Lake (4.1&nbsp;km</span><sup>2</sup><span>). Gases from all three sites were CO</span><sub>2</sub><span>-rich (≥79&nbsp;mol% in dry gas) but showed considerable compositional variability over time due to interaction with ground and surface water. An increase in H</span><sub>2</sub><span>S concentrations and decline in CO</span><sub>2</sub><span>/H</span><sub>2</sub><span>S ratios in ELHS gases coincided with a drop in East Lake water level from 1999 to 2021. ELHS and OFGS gases were high in CH</span><sub>4</sub><span>&nbsp;relative to PHS and the δ</span><sup>13</sup><span>C of CH</span><sub>4</sub><span>&nbsp;values for ELHS gases (−72.2 and&nbsp;−&nbsp;63.6 ‰) reflected a predominantly biogenic origin. The dominant source of N</span><sub>2</sub><span>&nbsp;and Ar in PHS, ELHS, and OFGS samples was likely groundwater. Helium isotopic ratios (6.47 to 8.02 R</span><sub>c</sub><span>/R</span><sub>a</sub><span>) support a persistent source of magmatic He beneath Newberry caldera and consistently high values measured at OFGS and PHS relative to ELHS suggest distinct fluid flow paths from depth to the surface features. The δ</span><sup>13</sup><span>C of CO</span><sub>2</sub><span>&nbsp;and CO</span><sub>2</sub><span>/</span><sup>3</sup><span>He values (−8.9 to −5.35 ‰ and 1.3&nbsp;×&nbsp;10</span><sup>9</sup><span>&nbsp;to 4.6&nbsp;×&nbsp;10</span><sup>10</sup><span>, respectively) measured in gases reflect contributions of CO</span><sub>2</sub><span>&nbsp;from both mantle and crustal sources. Measured CO</span><sub>2</sub><span>&nbsp;fluxes at OFGS and East Lake ranged from 1 to 8808 and&nbsp;&lt;&nbsp;1 to 364&nbsp;g&nbsp;m</span><sup>−2</sup><span>&nbsp;d</span><sup>−1</sup><span>, respectively. A CO</span><sub>2</sub><span>&nbsp;emission rate of 0.5&nbsp;t d</span><sup>−1</sup><span>&nbsp;was calculated for OFGS. The CO</span><sub>2</sub><span>&nbsp;emission rate estimated for East Lake was 30&nbsp;t d</span><sup>−1</sup><span>&nbsp;and when compared to prior estimates, reflects steady-state lake degassing. An enhanced geochemical monitoring plan, including annual sampling of gases at ELHS, OFGS, and PHS for geochemical analysis, installation of a continuous lake-level monitoring station at East Lake, and annual CO</span><sub>2</sub><span>&nbsp;flux surveys at OFGS, would provide valuable background data and insights into any precursor volcanic activity. Integrating geochemical data with data from the real-time seismic and GPS network at Newberry Volcano could better resolve and interpret potential changes in its magma-hydrothermal system.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2022.107729","usgsCitation":"Lewicki, J.L., Evans, W.C., Ingebritsen, S.E., Clor, L., Kelly, P.J., Peek, S., Jensen, R.A., and Hunt, A., 2023, Geochemistry and fluxes of gases from hydrothermal features at Newberry Volcano, Oregon, USA: Journal of Volcanology and Geothermal Research, v. 433, 107729, 16 p., https://doi.org/10.1016/j.jvolgeores.2022.107729.","productDescription":"107729, 16 p.","ipdsId":"IP-142077","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":445171,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2022.107729","text":"Publisher Index Page"},{"id":411629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Newberry Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.4446630583071,\n              43.958977799999275\n            ],\n            [\n              -121.4446630583071,\n              43.4616991485112\n            ],\n            [\n              -121.0217250470551,\n              43.4616991485112\n            ],\n            [\n              -121.0217250470551,\n              43.958977799999275\n            ],\n            [\n              -121.4446630583071,\n              43.958977799999275\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"433","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":860927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, William C. 0000-0001-5942-3102 wcevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5942-3102","contributorId":2353,"corporation":false,"usgs":true,"family":"Evans","given":"William","email":"wcevans@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":860928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":860929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clor, Laura E. 0000-0003-2633-5100","orcid":"https://orcid.org/0000-0003-2633-5100","contributorId":209969,"corporation":false,"usgs":true,"family":"Clor","given":"Laura E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":860930,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":860931,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peek, Sara 0000-0002-9770-6557","orcid":"https://orcid.org/0000-0002-9770-6557","contributorId":209971,"corporation":false,"usgs":true,"family":"Peek","given":"Sara","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":860932,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jensen, Robert A.","contributorId":35469,"corporation":false,"usgs":false,"family":"Jensen","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":860933,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hunt, Andrew G. 0000-0002-3810-8610","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":206197,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":860934,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70238973,"text":"70238973 - 2023 - Assessment of resource potential from mine tailings using geostatistical modeling for compositions: A methodology and application to Katherine Mine site, Arizona, USA","interactions":[],"lastModifiedDate":"2022-12-20T12:49:04.741255","indexId":"70238973","displayToPublicDate":"2022-12-02T06:37:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2302,"text":"Journal of Geochemical Exploration","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of resource potential from mine tailings using geostatistical modeling for compositions: A methodology and application to Katherine Mine site, Arizona, USA","docAbstract":"<p id=\"sp0135\">The mining industry, in most cases, targets a specific valuable commodity that is present in small quantities within large volumes of extracted material. After milling and processing, most of the extracted material and the effluents are stored as waste (tailings) in impoundments, such as dams or waste dumps, or are backfilled into underground mines. In time, tailing materials may become an issue of environmental and health concern due to the hazardous elements, ions, and oxides contained within the waste material. In addition, handling and storage of such waste in dams may pose the risk of dam failure with catastrophic consequences to nature and nearby communities. On the other hand, tailings may offer potential as secondary sources of critical elements (CEs), including rare earth elements (REEs), which may have been overlooked during primary production and processing. Therefore, treating mine tailings as a resource has economic and environmental benefits by reducing the waste from new and historical mine sites through remining. One of the critical steps for taking advantage of these benefits is to spatially quantify the resources and the pollutants, which require the application of adequate data analysis and modeling methods, often to compositional geochemical data. Utilizing adequate methods is especially important for correctly quantifying resource potential, as the quantities will often be at low concentrations.</p><p id=\"sp0140\">This work presents quantification of resource potential (Au, Ag, Cu, Zn, Pb) and elements of environmental concern (Hg and As) from the tailings of a historic mine site, Katherine Mine, AZ, USA. Data reported by the U.S. Bureau of Mines (USBM) after extensive field campaigns in the 1990s, including sampling from tailing impoundment and surrounding areas for geochemical characterization and geophysical surveys, were used. First, compositional data (CoDa) analysis was employed to explore associations of sampling locations, geochemical parts, and the clustering of samples. Next, sequential Gaussian simulation (SGSIM) was applied to samples that showed a genetic link to tailing material after isometric log-ratio transformation (ilr) and mix/max autocorrelation factor (MAF) transformation for spatial modeling and uncertainty evaluation. Geostatistical results revealed spatial variability of concentrations within the tailing area. Uncertainty evaluation based on realizations indicated that Cu (14.27–20.01&nbsp;t), Zn (44.23–76.23&nbsp;t), and Pb (22.56–38.28&nbsp;t) are the most abundant elements within a 5&nbsp;%–95&nbsp;% interval, followed by Ag and Au (~5.3 and 0.18&nbsp;t, at 50th percentile), respectively. Of the elements of health concern, As was found to be ~4.8&nbsp;t (50th percentile) in the tailing area. The work also showed that ~0.51&nbsp;t As, 0.005&nbsp;t Hg, 0.020&nbsp;t of Au, and 0.62&nbsp;t of Ag were carried to Lake Mohave by an ephemeral stream called Katherine Wash, which transects the tailings.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2022.107142","usgsCitation":"Karacan, C.O., Erten, O., and Martin-Fernandez, J.A., 2023, Assessment of resource potential from mine tailings using geostatistical modeling for compositions: A methodology and application to Katherine Mine site, Arizona, USA: Journal of Geochemical Exploration, v. 245, 107142, 23 p., https://doi.org/10.1016/j.gexplo.2022.107142.","productDescription":"107142, 23 p.","ipdsId":"IP-142163","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":410781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Katherine Mine site","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -114.66102965470434,\n              35.592576061702815\n            ],\n            [\n              -114.66102965470434,\n              35.179363749635115\n            ],\n            [\n              -114.1226599998257,\n              35.179363749635115\n            ],\n            [\n              -114.1226599998257,\n              35.592576061702815\n            ],\n            [\n              -114.66102965470434,\n              35.592576061702815\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"245","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":859489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erten, Oktay","contributorId":300145,"corporation":false,"usgs":false,"family":"Erten","given":"Oktay","email":"","affiliations":[],"preferred":false,"id":859490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin-Fernandez, Josep Antoni","contributorId":300146,"corporation":false,"usgs":false,"family":"Martin-Fernandez","given":"Josep","email":"","middleInitial":"Antoni","affiliations":[],"preferred":false,"id":859491,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70248260,"text":"70248260 - 2023 - Hydroclimate and fire paleorecords across the southern Rockies and Colorado Plateau over the common era","interactions":[],"lastModifiedDate":"2026-03-19T14:46:05.60671","indexId":"70248260","displayToPublicDate":"2022-12-01T09:44:02","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Hydroclimate and fire paleorecords across the southern Rockies and Colorado Plateau over the common era","docAbstract":"<p>The southwestern US has been experiencing a severe drought and increased fire activity over the past two decades, affecting people’s health, homes, and businesses. Many individual fires occurring in the Southwest are the most severe in recorded history both in terms of dollars of damages as well as in fire extent. It is essential to be able to place the present drought and fires into the context of the current changing climate as well as in the framework of climate variability and human activity over centennial to millennial timescales. Dendrochronology can determine both the seasonality of fires as well as changes in precipitation. Charcoal, pollen, and the biomarkers levoglucosan, mannosan, and galactosan can help determine fire activity and the type of burned vegetation. People have controlled and utilized fire in the southwestern US for thousands of years. While proxies cannot yet determine if people ignited a specific fire, fecal sterols can determine if people were within an individual watershed. Here, we examine the strengths and weaknesses of using high-resolution tree-ring data in conjunction with biomarkers in ice and lake cores from the southwestern US to study interactions between changes in hydroclimate, fires, and human activity.&nbsp;</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 89th annual western snow conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Western Snow Conference","usgsCitation":"Kehrwald, N.M., and Brice, R.L., 2023, Hydroclimate and fire paleorecords across the southern Rockies and Colorado Plateau over the common era, <i>in</i> Proceedings of the 89th annual western snow conference, p. 41-45.","productDescription":"5 p.","startPage":"41","endPage":"45","ipdsId":"IP-143647","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":420531,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://westernsnowconference.org/proceedings/"},{"id":501308,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kehrwald, Natalie M. 0000-0002-9160-2239 nkehrwald@usgs.gov","orcid":"https://orcid.org/0000-0002-9160-2239","contributorId":168918,"corporation":false,"usgs":true,"family":"Kehrwald","given":"Natalie","email":"nkehrwald@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":882138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brice, Rebecca Lynn 0000-0003-0023-5988","orcid":"https://orcid.org/0000-0003-0023-5988","contributorId":247868,"corporation":false,"usgs":true,"family":"Brice","given":"Rebecca","email":"","middleInitial":"Lynn","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":882139,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70239116,"text":"70239116 - 2023 - Porosity, strength, and alteration – Towards a new volcano stability assessment tool using VNIR-SWIR reflectance spectroscopy","interactions":[],"lastModifiedDate":"2022-12-28T13:48:14.915737","indexId":"70239116","displayToPublicDate":"2022-11-30T07:43:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Porosity, strength, and alteration – Towards a new volcano stability assessment tool using VNIR-SWIR reflectance spectroscopy","docAbstract":"<div id=\"ab0010\" class=\"abstract author\"><div id=\"as0010\"><p id=\"sp0090\">Volcano slope stability analysis is a critical component of volcanic hazard assessments and monitoring. However, traditional methods for assessing rock strength require physical samples of rock which may be difficult to obtain or characterize in bulk. Here, visible to shortwave infrared (350–2500 nm; VNIR–SWIR) reflected light spectroscopy on laboratory-tested rock samples from Ruapehu, Ohakuri, Whakaari, and Banks Peninsula (New Zealand), Merapi (Indonesia), Chaos Crags (USA), Styrian Basin (Austria) and La Soufrière de Guadeloupe (Eastern Caribbean) volcanoes was used to design a novel rapid chemometric-based method to estimate uniaxial compressive strength (UCS) and porosity. Our Partial Least Squares Regression models return moderate accuracies for both UCS and porosity, with R<sup>2</sup><span>&nbsp;</span>of 0.43–0.49 and Mean Absolute Percentage Error (MAPE) of 0.2–0.4. When laboratory-measured porosity is included with spectral data, UCS prediction reaches an R<sup>2</sup><span>&nbsp;</span>of 0.82 and MAPE of 0.11. Our models highlight that the observed changes in the UCS are coupled with subtle mineralogical changes due to hydrothermal alteration at wavelengths of 360–438, 532–597, 1405–1455, 2179–2272, 2332–2386, and 2460–2490 nm. These mineralogical changes include mineral replacement, precipitation hydrothermal alteration processes which impact the strength of volcanic rocks, such as mineral replacement, precipitation, and/or silicification. Our approach highlights that spectroscopy can provide a first order assessment of rock strength and/or porosity or be used to complement laboratory porosity-based predictive models. VNIR-SWIR spectroscopy therefore provides an accurate non-destructive way of assessing rock strength and alteration mineralogy, even from remote sensing platforms.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2022.117929","usgsCitation":"Kereszturi, G., Heap, M.J., Schaefer, L.N., Darmawan, H., Deegan, F.M., Kennedy, B.M., Komorowski, J., Mead, S., Rosas-Carbajal, M., Ryan, A., Troll, V.R., Villeneuve, M.C., and Walter, T., 2023, Porosity, strength, and alteration – Towards a new volcano stability assessment tool using VNIR-SWIR reflectance spectroscopy: Earth and Planetary Science Letters, v. 602, 117929, 12 p., https://doi.org/10.1016/j.epsl.2022.117929.","productDescription":"117929, 12 p.","ipdsId":"IP-144625","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":445187,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2022.117929","text":"Publisher Index Page"},{"id":411116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"602","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kereszturi, Gabor 0000-0003-4336-2012","orcid":"https://orcid.org/0000-0003-4336-2012","contributorId":247601,"corporation":false,"usgs":false,"family":"Kereszturi","given":"Gabor","email":"","affiliations":[{"id":49587,"text":"Volcanic Risk Solutions, Massey University, Palmerston North, 4474, New Zealand","active":true,"usgs":false}],"preferred":false,"id":860100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heap, Michael J. 0000-0002-4748-735X","orcid":"https://orcid.org/0000-0002-4748-735X","contributorId":297882,"corporation":false,"usgs":false,"family":"Heap","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":64429,"text":"Université de Strasbourg","active":true,"usgs":false}],"preferred":false,"id":860101,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaefer, Lauren N. 0000-0003-3216-7983","orcid":"https://orcid.org/0000-0003-3216-7983","contributorId":241997,"corporation":false,"usgs":true,"family":"Schaefer","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":860102,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Darmawan, Herlan","contributorId":300363,"corporation":false,"usgs":false,"family":"Darmawan","given":"Herlan","email":"","affiliations":[{"id":65091,"text":"Universitas Gadjah Mada","active":true,"usgs":false}],"preferred":false,"id":860103,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Deegan, Frances M. 0000-0002-9065-9225","orcid":"https://orcid.org/0000-0002-9065-9225","contributorId":300364,"corporation":false,"usgs":false,"family":"Deegan","given":"Frances","email":"","middleInitial":"M.","affiliations":[{"id":37671,"text":"Uppsala University","active":true,"usgs":false}],"preferred":false,"id":860104,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kennedy, Ben M. 0000-0001-7235-6493","orcid":"https://orcid.org/0000-0001-7235-6493","contributorId":270276,"corporation":false,"usgs":false,"family":"Kennedy","given":"Ben","email":"","middleInitial":"M.","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":860105,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Komorowski, Jean-Christophe","contributorId":300365,"corporation":false,"usgs":false,"family":"Komorowski","given":"Jean-Christophe","affiliations":[{"id":65092,"text":"Université de Paris","active":true,"usgs":false}],"preferred":false,"id":860106,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mead, Stuart","contributorId":300366,"corporation":false,"usgs":false,"family":"Mead","given":"Stuart","affiliations":[{"id":13571,"text":"Massey University","active":true,"usgs":false}],"preferred":false,"id":860107,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rosas-Carbajal, Marina 0000-0002-5393-0389","orcid":"https://orcid.org/0000-0002-5393-0389","contributorId":300367,"corporation":false,"usgs":false,"family":"Rosas-Carbajal","given":"Marina","email":"","affiliations":[{"id":65092,"text":"Université de Paris","active":true,"usgs":false}],"preferred":false,"id":860108,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ryan, Amy","contributorId":300368,"corporation":false,"usgs":false,"family":"Ryan","given":"Amy","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":860109,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Troll, Valentin R.","contributorId":300369,"corporation":false,"usgs":false,"family":"Troll","given":"Valentin","email":"","middleInitial":"R.","affiliations":[{"id":37671,"text":"Uppsala University","active":true,"usgs":false}],"preferred":false,"id":860110,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Villeneuve, Marlene C. 0000-0001-6001-0786","orcid":"https://orcid.org/0000-0001-6001-0786","contributorId":300370,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Marlene","email":"","middleInitial":"C.","affiliations":[{"id":65093,"text":"Montanuniversität Leoben","active":true,"usgs":false}],"preferred":false,"id":860111,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Walter, Thomas R.","contributorId":300371,"corporation":false,"usgs":false,"family":"Walter","given":"Thomas R.","affiliations":[{"id":39797,"text":"GFZ German Research Centre for Geosciences","active":true,"usgs":false}],"preferred":false,"id":860112,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70238685,"text":"70238685 - 2023 - Longitudinal analyses of catch-at-age data for reconstructing year-class strength, with an application to lake trout (Salvelinus namaycush) in the main basin of Lake Huron","interactions":[],"lastModifiedDate":"2023-01-18T17:23:24.019675","indexId":"70238685","displayToPublicDate":"2022-11-29T06:48:14","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Longitudinal analyses of catch-at-age data for reconstructing year-class strength, with an application to lake trout (<i>Salvelinus namaycush</i>) in the main basin of Lake Huron","title":"Longitudinal analyses of catch-at-age data for reconstructing year-class strength, with an application to lake trout (Salvelinus namaycush) in the main basin of Lake Huron","docAbstract":"<div id=\"abstracts\" data-extent=\"frontmatter\"><div class=\"core-container\"><div>We investigated using longitudinal models to reconstruct year-class strength (YCS) from catch-at-age data, with an example application to lake trout (<i>Salvelinus namaycush</i>) in the main basin of Lake Huron. The best model structure depended on the age range used for model implementation. The YCS trajectory from the full age range (3–30 years) was similar to the trajectory from a narrow age range that approximated the age of recruitment to the fishing gears (5–7 years), but YCS estimates from the full age range included additional variations due to time-dependent selectivity and mortality. When using ages younger or older than the likely ages of recruitment, YCS estimates did not represent recruitment abundances and were also biased by trends in age-specific selectivity and mortality across years. Longitudinal YCS estimates are likely more robust than single-age recruitment indices, which are often subject to interannual changes in catchability and selectivity. Our findings provide guidance for future applications of the longitudinal YCS reconstruction that in turn may inform and supplement more comprehensive research and management programs for understanding fish recruitment dynamics.</div></div></div>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2022-0140","usgsCitation":"He, J.X., Honsey, A.E., Staples, D.F., Bence, J., and Claramunt, T.L., 2023, Longitudinal analyses of catch-at-age data for reconstructing year-class strength, with an application to lake trout (Salvelinus namaycush) in the main basin of Lake Huron: Canadian Journal of Fisheries and Aquatic Sciences, v. 80, no. 1, p. 183-194, https://doi.org/10.1139/cjfas-2022-0140.","productDescription":"12 p.","startPage":"183","endPage":"194","ipdsId":"IP-141874","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":445195,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2022-0140","text":"Publisher Index Page"},{"id":410046,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Huron","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.76832469460116,\n              46.293576597554534\n            ],\n            [\n              -84.76832469460116,\n              42.93351105858869\n            ],\n            [\n              -80.6831455271525,\n              42.93351105858869\n            ],\n            [\n              -80.6831455271525,\n              46.293576597554534\n            ],\n            [\n              -84.76832469460116,\n              46.293576597554534\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"80","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"He, Ji X.","contributorId":181528,"corporation":false,"usgs":false,"family":"He","given":"Ji","email":"","middleInitial":"X.","affiliations":[],"preferred":false,"id":858269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Honsey, Andrew Edgar 0000-0001-7535-1321","orcid":"https://orcid.org/0000-0001-7535-1321","contributorId":295468,"corporation":false,"usgs":true,"family":"Honsey","given":"Andrew","email":"","middleInitial":"Edgar","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":858270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Staples, David F.","contributorId":150561,"corporation":false,"usgs":false,"family":"Staples","given":"David","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":858271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bence, James R.","contributorId":95026,"corporation":false,"usgs":false,"family":"Bence","given":"James R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":858272,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Claramunt, Tracy L.","contributorId":215447,"corporation":false,"usgs":false,"family":"Claramunt","given":"Tracy","email":"","middleInitial":"L.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":858273,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70256610,"text":"70256610 - 2023 - Using fiber-optic distributed temperature sensing in fisheries applications: An example from the Ozark Highlands","interactions":[],"lastModifiedDate":"2024-08-12T22:52:34.750915","indexId":"70256610","displayToPublicDate":"2022-11-28T17:44:47","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Using fiber-optic distributed temperature sensing in fisheries applications: An example from the Ozark Highlands","docAbstract":"<div id=\"preview-section-abstract\"><div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0010\" class=\"abstract author\"><div id=\"abs0010\"><p id=\"sp0035\"><span>Studies of thermal selection by organisms, including fishes, are common and provide data that are useful for conservation and management. Advances in temperature sensing technology have improved these studies; however, the benefits of new technology (e.g., increased accuracy and greater deployment flexibility) should be carefully considered and compared to disadvantages (e.g., higher costs and training requirements). Fiber-optic distributed temperature sensing (FO-DTS) has become more common in aquatic applications and may provide a novel and useful method of relating thermal patchiness to habitat selection by fishes or other&nbsp;aquatic organisms. We present a&nbsp;case study&nbsp;using FO-DTS to conduct a microhabitat-scale resource selection study using stream fishes of the Ozark Highland ecoregion in the south-central United States. We describe the setup and deployment of FO-DTS and how it was integrated into traditional&nbsp;microhabitat&nbsp;survey methods at three stream sites that were repeatedly surveyed over consecutive days. We successfully used FO-DTS to characterize thermal selection by Neosho Bass&nbsp;</span><span>Micropterus<i>&nbsp;velox</i></span><span>&nbsp;</span>at our sites and conclude that the technology would be applicable to similar, microhabitat-scale evaluations. We then compare costs, benefits, and disadvantages of FO-DTS to other sensing methods that could have been used to complete our study. We found that FO-DTS provided accurate measures and greater coverage compared to most alternatives but that equipment costs were far greater. We provide suggestions for additional fisheries applications where FO-DTS may be useful while acknowledging that in some instances, the upfront costs of the technology may outweigh the potential benefits.</p></div></div></div></div><div id=\"preview-section-introduction\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2022.106542","usgsCitation":"Wolf, S.L., Swedberg, D.A., Tanner, E.P., Fuhlendorf, S., and Brewer, S.K., 2023, Using fiber-optic distributed temperature sensing in fisheries applications: An example from the Ozark Highlands: Fisheries Research, v. 258, 106542, https://doi.org/10.1016/j.fishres.2022.106542.","productDescription":"106542","ipdsId":"IP-140955","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432573,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"258","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wolf, Skylar L.","contributorId":341359,"corporation":false,"usgs":false,"family":"Wolf","given":"Skylar","email":"","middleInitial":"L.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swedberg, Dusty A.","contributorId":341360,"corporation":false,"usgs":false,"family":"Swedberg","given":"Dusty","email":"","middleInitial":"A.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908296,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tanner, Evan P.","contributorId":341361,"corporation":false,"usgs":false,"family":"Tanner","given":"Evan","email":"","middleInitial":"P.","affiliations":[{"id":13724,"text":"Texas A&M University-Kingsville","active":true,"usgs":false}],"preferred":false,"id":908297,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuhlendorf, Samuel D.","contributorId":341362,"corporation":false,"usgs":false,"family":"Fuhlendorf","given":"Samuel D.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908298,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":908299,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70238737,"text":"70238737 - 2023 - Towards a unified drag coefficient formula for quantifying wave energy reduction by salt marshes","interactions":[],"lastModifiedDate":"2022-12-15T16:01:07.181311","indexId":"70238737","displayToPublicDate":"2022-11-27T06:44:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Towards a unified drag coefficient formula for quantifying wave energy reduction by salt marshes","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"d1e1297\" class=\"abstract author\"><div id=\"d1e1300\"><p id=\"d1e1301\"><span>Coastal regions are susceptible to increasing flood risks amid climate change. Coastal wetlands play an important role in mitigating coastal hazards. Vegetation exerts a drag force to the flow and dampens storm surges and wind waves. The prediction of wave attenuation by vegetation typically relies on a pre-determined drag coefficient&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-7-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>C</mi></mrow><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>D</mi></mrow></msub></math>\"><span class=\"MJX_Assistive_MathML\">C<sub>D</sub></span></span></span><span>. Existing&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-8-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>C</mi></mrow><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>D</mi></mrow></msub></math>\"><span class=\"MJX_Assistive_MathML\">C<sub>D</sub></span></span></span><span>&nbsp;formulas are subject to vegetation biomechanical properties, especially the flexibility. Accounting for vegetation flexibility through the effective plant height (EPH), we propose and validate a species-independent relationship between&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-9-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>C</mi></mrow><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>D</mi></mrow></msub></math>\"><span class=\"MJX_Assistive_MathML\">C<sub>D</sub></span></span></span><span>&nbsp;and the Reynolds number&nbsp;</span><i><span class=\"math\"><span id=\"MathJax-Element-10-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>R</mi><mi is=&quot;true&quot;>e</mi></mrow></math>\"><span class=\"MJX_Assistive_MathML\">Re</span></span></span></i><span>&nbsp;based on three independent datasets that cover a wide range of hydrodynamic conditions and vegetation traits. The proposed&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-11-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mrow is=&quot;true&quot;><msub is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>C</mi></mrow><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>D</mi></mrow></msub><mo linebreak=&quot;goodbreak&quot; linebreakstyle=&quot;after&quot; is=&quot;true&quot;>&amp;#x2212;</mo><mi is=&quot;true&quot;>R</mi><mi is=&quot;true&quot;>e</mi></mrow></math>\"><span class=\"MJX_Assistive_MathML\">C<sub>D</sub>−<i>Re</i></span></span></span><span>&nbsp;relationship, used together with EPH, allows for predicting wave attenuation in salt marshes with high accuracy. Furthermore, a total of 308,000 numerical experiments with diverse wave conditions are conducted using the proposed&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-12-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mrow is=&quot;true&quot;><msub is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>C</mi></mrow><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>D</mi></mrow></msub><mo linebreak=&quot;goodbreak&quot; linebreakstyle=&quot;after&quot; is=&quot;true&quot;>&amp;#x2212;</mo><mi is=&quot;true&quot;>R</mi><mi is=&quot;true&quot;>e</mi></mrow></math>\"><span class=\"MJX_Assistive_MathML\">C<sub>D</sub>−<i>Re</i></span></span></span><span>&nbsp;relationship and EPH to quantify the wave attenuation capacity of two typical salt mash species:&nbsp;</span><i>Elymus athericus</i><span>&nbsp;(highly flexible) and&nbsp;</span><i>Spartina alterniflora</i><span>&nbsp;(relatively rigid). It is found that wave attenuation is controlled by wave height to water depth ratio and EPH to water depth ratio. When swaying in large waves in shallow to intermediate water depth, a 50-m-long&nbsp;</span><i>Elymus athericus</i><span>&nbsp;field may lose up to 30% capacity for wave attenuation. As wave height increases, highly flexible vegetation causes reduced wave attenuation, whereas relatively rigid vegetation induces increased wave attenuation. The leaf contribution to wave attenuation is highly dependent on the leaf rigidity. It is recommended that leaf properties, especially its Young’s modulus be collected in future field experiments.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2022.104256","usgsCitation":"Zhu, L., Chen, Q., Ding, Y., Jafari, N., Wang, H., and Johnson, B.D., 2023, Towards a unified drag coefficient formula for quantifying wave energy reduction by salt marshes: Coastal Engineering, v. 180, 104256, 14 p., https://doi.org/10.1016/j.coastaleng.2022.104256.","productDescription":"104256, 14 p.","ipdsId":"IP-121483","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":445202,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2022.104256","text":"Publisher Index Page"},{"id":410152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"180","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhu, Ling 0000-0003-0261-6848","orcid":"https://orcid.org/0000-0003-0261-6848","contributorId":222169,"corporation":false,"usgs":false,"family":"Zhu","given":"Ling","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":858451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":858452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ding, Yan","contributorId":299723,"corporation":false,"usgs":false,"family":"Ding","given":"Yan","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":858453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jafari, Navid H.","contributorId":214730,"corporation":false,"usgs":false,"family":"Jafari","given":"Navid H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":858454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":221902,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":858455,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Bradley D.","contributorId":299724,"corporation":false,"usgs":false,"family":"Johnson","given":"Bradley","email":"","middleInitial":"D.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":858456,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70254592,"text":"70254592 - 2023 - The Far-Field imprint of the late Paleozoic Ice Age, its demise, and the onset of a dust-house climate across the Eastern Shelf of the Midland Basin, Texas","interactions":[],"lastModifiedDate":"2024-06-04T11:38:15.455109","indexId":"70254592","displayToPublicDate":"2022-11-25T06:35:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1848,"text":"Gondwana Research","active":true,"publicationSubtype":{"id":10}},"title":"The Far-Field imprint of the late Paleozoic Ice Age, its demise, and the onset of a dust-house climate across the Eastern Shelf of the Midland Basin, Texas","docAbstract":"<div id=\"ab015\" class=\"abstract author\"><div id=\"as015\"><p id=\"sp0015\">The late Paleozoic is a period of pronounced climatic and tectonic change, characterized by the onset and disappearance of continental-scale glaciers across polar Gondwana, the formation of Pangea, and widespread large igneous province volcanism. The low-latitude equatorial tropics are assumed to be places of persistent warm and wet climatic conditions throughout the Phanerozoic, which through intense silicate weathering, exert a major influence on Earth’s climate via the consumption of atmospheric carbon through carbonic hydrolytic weathering, formation of clay minerals and deliverability of alkalinity to ocean basins. Here we investigate the late Paleozoic sedimentary record of the Eastern Shelf of the Midland Basin in order to refine the climatic and provenance record of this region. The Eastern Shelf of the Midland Basin was situated within the equatorial tropics throughout the late Paleozoic and was connected to the open ocean through a network of fluvial systems that drained into the marine Midland Basin. We present new U-Pb zircon geochronology (19 samples, 2591 analyses) and sedimentary petrography (11 samples, 5800 grain counts), which we integrate with previously published paleobotany, paleosol chemistry and clay mineralogy to provide a holistic climate and tectonic record from this region. We observe major changes in sedimentary processes that we attribute to the formation of Pangea, eustatic changes linked to a dynamic high-latitude glaciation and teleconnections with low latitude hydrology, and a long-term shift in the Earth climate system all of which result in a dynamic sediment provenance history. Late Pennsylvanian and earliest Permian deposits are enriched in zircons with local affinity and interpreted to reflect local uplift and repeat incision across the basin margin, the latter a result of glacioeustatic forcing during an “everwet” climate. A major paleoenvironmental shift occurs in the late early Permian, which is reflected by the transition from fluvial to mixed fluvial-aeolian and ultimately aeolian dominant sedimentation by the late Permian. The transition from fluvial to aeolian dominant sedimentation is accompanied by a change in clay chemistry, sedimentary rock textual maturity, paleosol morphology and a threefold increase in Paleozoic zircons in the mid to late Permian strata. Widespread loess deposits across equatorial Pangea during the Permian have been used to argue for the possibility of equatorial glaciers situated in highland settings during the early Permian. Conversely, our data suggest initiation of a substantial component of aeolian deposition across the field areas, which is coincident with widespread ice loss across high latitude Gondwana, and ultimately highlights the teleconnections between high latitude glaciation and the low latitude hydrologic cycle.</p></div></div><div id=\"ab005\" class=\"abstract graphical\" lang=\"en\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gr.2022.11.004","usgsCitation":"Griffis, N.P., Tabor, N., Stockli, D., and Stockli, L., 2023, The Far-Field imprint of the late Paleozoic Ice Age, its demise, and the onset of a dust-house climate across the Eastern Shelf of the Midland Basin, Texas: Gondwana Research, v. 115, p. 17-36, https://doi.org/10.1016/j.gr.2022.11.004.","productDescription":"20 p.","startPage":"17","endPage":"36","ipdsId":"IP-140504","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":445206,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gr.2022.11.004","text":"Publisher Index Page"},{"id":429491,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Midland Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -108.1009038432658,\n              37.54785246377509\n            ],\n            [\n              -108.1009038432658,\n              28.65565552971603\n            ],\n            [\n              -97.46613821826628,\n              28.65565552971603\n            ],\n            [\n              -97.46613821826628,\n              37.54785246377509\n            ],\n            [\n              -108.1009038432658,\n              37.54785246377509\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"115","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Griffis, Neil Patrick 0000-0002-2506-7549","orcid":"https://orcid.org/0000-0002-2506-7549","contributorId":330218,"corporation":false,"usgs":true,"family":"Griffis","given":"Neil","email":"","middleInitial":"Patrick","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":902041,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tabor, Neil","contributorId":337120,"corporation":false,"usgs":false,"family":"Tabor","given":"Neil","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":902042,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stockli, Daniel","contributorId":337121,"corporation":false,"usgs":false,"family":"Stockli","given":"Daniel","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":902043,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stockli, Lisa","contributorId":337122,"corporation":false,"usgs":false,"family":"Stockli","given":"Lisa","email":"","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":902044,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70238909,"text":"70238909 - 2023 - Addressing detection uncertainty in Bombus affinis (Hymenoptera: Apidae) surveys can improve inferences made from monitoring","interactions":[],"lastModifiedDate":"2023-03-01T17:03:18.36297","indexId":"70238909","displayToPublicDate":"2022-11-22T09:32:15","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1536,"text":"Environmental Entomology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Addressing detection uncertainty in <i>Bombus affinis</i> (Hymenoptera: Apidae) surveys can improve inferences made from monitoring","title":"Addressing detection uncertainty in Bombus affinis (Hymenoptera: Apidae) surveys can improve inferences made from monitoring","docAbstract":"<p><span>The U.S. Fish and Wildlife Service developed national guidelines to track species recovery of the endangered rusty patched bumble bee [</span><i>Bombus affinis</i><span>&nbsp;Cresson (Hymenoptera: Apidae)] and to investigate changes in species occupancy across space and time. As with other native bee monitoring efforts, managers have specifically acknowledged the need to address species detection uncertainty and determine the sampling effort required to infer species absence within sites. We used single-season, single-species occupancy models fit to field data collected in four states to estimate imperfect detection of&nbsp;</span><i>B. affinis</i><span>&nbsp;and to determine the survey effort required to achieve high confidence of species detection. Our analysis revealed a precipitous, seasonal, decline in&nbsp;</span><i>B. affinis</i><span>&nbsp;detection probability throughout the July through September sampling window in 2021. We estimated that six, 30-min surveys conducted in early July are required to achieve a 95% cumulative detection probability, whereas &gt;10 surveys would be required in early August to achieve the same level of confidence. Our analysis also showed&nbsp;</span><i>B. affinis</i><span>&nbsp;was less likely to be detected during hot and humid days and at patches of reduced habitat quality.&nbsp;</span><i>Bombus affinis</i><span>&nbsp;was frequently observed on&nbsp;</span><i>Monarda fistulosa</i><span>&nbsp;(Lamiales: Lamiaceae), followed by [</span><i>Pycnanthemum virginianum</i><span>&nbsp;Rob. and Fernald (Lamiales: Lamiaceae)]</span><i>, Eutrochium maculatum</i><span>&nbsp;Lamont (Asterales: Asteraceae), and&nbsp;</span><i>Veronicastrum virginicum</i><span>&nbsp;Farw. (Lamiales: Plantaginaceae). Although our research is focused on&nbsp;</span><i>B. affinis</i><span>, it is relevant for monitoring other bumble bees of conservation concern, such as&nbsp;</span><i>B. occidentalis</i><span>&nbsp;Greene (Hymenoptera: Apidae) and&nbsp;</span><i>B. terricola</i><span>&nbsp;Kirby (Hymenoptera: Apidae) for which monitoring efforts have been recently initiated and occupancy is a variable of conservation interest.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/ee/nvac090","usgsCitation":"Otto, C., Schrage, A., Bailey, L., Mola, J.M., Smith, T.A., Pearse, I., Simanonok, S.C., and Grundel, R., 2023, Addressing detection uncertainty in Bombus affinis (Hymenoptera: Apidae) surveys can improve inferences made from monitoring: Environmental Entomology, v. 52, no. 1, p. 108-118, https://doi.org/10.1093/ee/nvac090.","productDescription":"11 p.","startPage":"108","endPage":"118","ipdsId":"IP-142627","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":445215,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ee/nvac090","text":"Publisher Index Page"},{"id":435557,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KCT9HS","text":"USGS data release","linkHelpText":"Dataset: Addressing detection uncertainty in Bombus affinis (Hymenoptera: Apidae) surveys can improve inferences made from monitoring"},{"id":410629,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Wisconsin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -87.61000381938868,\n              44.138214784257\n            ],\n            [\n              -88.52996382924658,\n              44.640505673991015\n            ],\n            [\n              -93.72931662152843,\n              45.66035772126932\n            ],\n            [\n              -93.75045115668195,\n              44.31147648906321\n            ],\n            [\n              -92.0347046113481,\n              42.72707579471009\n            ],\n            [\n              -90.46310774538665,\n              40.647918214493586\n            ],\n            [\n              -89.24054201736095,\n              40.18878234558147\n            ],\n            [\n              -87.5653590374349,\n              40.3979986055748\n            ],\n            [\n              -87.52603349320947,\n              41.44947118667892\n            ],\n            [\n              -87.61000381938868,\n              44.138214784257\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"52","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":859123,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schrage, Alma","contributorId":299957,"corporation":false,"usgs":false,"family":"Schrage","given":"Alma","email":"","affiliations":[{"id":38050,"text":"Contractor","active":true,"usgs":false}],"preferred":false,"id":859124,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bailey, Larissa L.","contributorId":229353,"corporation":false,"usgs":false,"family":"Bailey","given":"Larissa L.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":859125,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mola, John Michael 0000-0002-5394-9071","orcid":"https://orcid.org/0000-0002-5394-9071","contributorId":224281,"corporation":false,"usgs":true,"family":"Mola","given":"John","email":"","middleInitial":"Michael","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":859126,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Tamara A.","contributorId":257977,"corporation":false,"usgs":false,"family":"Smith","given":"Tamara","email":"","middleInitial":"A.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":859127,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":211154,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":859128,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Simanonok, Stacy C. 0000-0002-0287-3871","orcid":"https://orcid.org/0000-0002-0287-3871","contributorId":229607,"corporation":false,"usgs":true,"family":"Simanonok","given":"Stacy","email":"","middleInitial":"C.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":859129,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grundel, Ralph 0000-0002-2949-7087 rgrundel@usgs.gov","orcid":"https://orcid.org/0000-0002-2949-7087","contributorId":2444,"corporation":false,"usgs":true,"family":"Grundel","given":"Ralph","email":"rgrundel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":859130,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70238616,"text":"70238616 - 2023 - Geophysical data provide three dimensional insights into porphyry copper systems in the Silverton caldera, Colorado, USA","interactions":[],"lastModifiedDate":"2022-12-01T14:03:23.274569","indexId":"70238616","displayToPublicDate":"2022-11-22T07:56:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Geophysical data provide three dimensional insights into porphyry copper systems in the Silverton caldera, Colorado, USA","docAbstract":"<p><span>The Silverton caldera in southwest Colorado, USA hosts polymetallic veins and pervasively altered rocks indicative of porphyry copper systems. Nearly a kilometer of erosion has exposed multiple levels of the hydrothermal systems from shallow lithocaps down to quartz-sericite-pyrite veins. New airborne electromagnetic and magnetic survey data are integrated with previous alteration mapping and porphyry models to show the subsurface geophysical response of shallow to deep levels of the porphyry system. Qualitative map views show lateral changes in the magnetization and resistivity of the hydrothermally altered rocks. The volcanic terrain exhibits high magnetization and high amplitude anomalies map near-surface plutonic rocks associated with porphyry systems. Magnetic susceptibility measurements on outcrops of hydrothermally altered rocks indicate magnetite content decreases upward and outward from the source intrusions where magnetic anomaly lows are observed over the lithocaps. The resistivity maps highlight hydrothermal alteration as resistivity lows with exception being rocks having propylitic alteration. Quantitative resistivity models show low resistivity zones with an apparent thickness around 50–150&nbsp;m beneath quartz-sericite-pyrite veins interpreted to be the result of supergene processes that may continue today, and the calculated magnetic source depths occur near the top of this zone. The resistivity models also show rocks having propylitic, silicic, and quartz-alunite-pyrophyllite assemblages exhibit high resistivity with depth, and argillic alteration assemblages had high resistivity due to high quartz content. This integrated approach presented in a three-dimensional environment provides guidance when exploring for porphyry copper systems in less exposed terrains.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2022.105223","usgsCitation":"Anderson, E., Yager, D., Deszcz-Pan, M., Hoogenboom, B.E., Rodriguez, B.D., and Smith, B., 2023, Geophysical data provide three dimensional insights into porphyry copper systems in the Silverton caldera, Colorado, USA: Ore Geology Reviews, v. 152, 105223, 22 p., https://doi.org/10.1016/j.oregeorev.2022.105223.","productDescription":"105223, 22 p.","ipdsId":"IP-139706","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":445219,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.oregeorev.2022.105223","text":"Publisher Index Page"},{"id":435558,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99JRNU2","text":"USGS data release","linkHelpText":"Magnetic susceptibility measurements on hydrothermally altered rocks in the Silverton caldera, southwest Colorado"},{"id":409918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Silverton caldera","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -108.41198468872895,\n              38.21942984890151\n            ],\n            [\n              -108.41198468872895,\n              37.34604421849235\n            ],\n            [\n              -107.19637481288558,\n              37.34604421849235\n            ],\n            [\n              -107.19637481288558,\n              38.21942984890151\n            ],\n            [\n              -108.41198468872895,\n              38.21942984890151\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"152","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Eric D. 0000-0002-0138-6166","orcid":"https://orcid.org/0000-0002-0138-6166","contributorId":202072,"corporation":false,"usgs":true,"family":"Anderson","given":"Eric D.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":858106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yager, Douglas 0000-0001-5074-4022","orcid":"https://orcid.org/0000-0001-5074-4022","contributorId":202073,"corporation":false,"usgs":true,"family":"Yager","given":"Douglas","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":858107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deszcz-Pan, Maria 0000-0002-6298-5314 maryla@usgs.gov","orcid":"https://orcid.org/0000-0002-6298-5314","contributorId":1263,"corporation":false,"usgs":true,"family":"Deszcz-Pan","given":"Maria","email":"maryla@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":858108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoogenboom, Bennett Eugene 0000-0001-8096-3533","orcid":"https://orcid.org/0000-0001-8096-3533","contributorId":239871,"corporation":false,"usgs":true,"family":"Hoogenboom","given":"Bennett","email":"","middleInitial":"Eugene","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":858109,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rodriguez, Brian D. 0000-0002-2263-611X brod@usgs.gov","orcid":"https://orcid.org/0000-0002-2263-611X","contributorId":836,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Brian","email":"brod@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":858110,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Bruce 0000-0002-1643-2997","orcid":"https://orcid.org/0000-0002-1643-2997","contributorId":214824,"corporation":false,"usgs":true,"family":"Smith","given":"Bruce","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":858111,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70243131,"text":"70243131 - 2023 - A near four-decade time series shows the Hawaiian Islands have been browning since the 1980s","interactions":[],"lastModifiedDate":"2023-05-01T11:33:05.007675","indexId":"70243131","displayToPublicDate":"2022-11-22T06:30:54","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":"A near four-decade time series shows the Hawaiian Islands have been browning since the 1980s","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>The Hawaiian Islands have been identified as a global biodiversity hotspot. We examine the Normalized Difference Vegetation Index (NDVI) using Climate Data Records products (0.05 × 0.05°) to identify significant differences in NDVI between neutral El Niño-Southern Oscillation years (1984, 2019) and significant long-term changes over the entire time series (1982–2019) for the Hawaiian Islands and six land cover classes. Overall, there has been a significant decline in NDVI (i.e., browning) across the Hawaiian Islands from 1982 to 2019 with the islands of Lāna’i and Hawai’i experiencing the greatest decreases in NDVI (≥44%). All land cover classes significantly decreased in NDVI for most months, especially during the wet season month of March. Native vegetation cover across all islands also experienced significant declines in NDVI, with the leeward, southwestern side of the island of Hawai’i experiencing the greatest declines. The long-term trends in the annual total precipitation and annual mean Palmer Drought Severity Index (PDSI) for 1982–2019 on the Hawaiian Islands show significant concurrent declines. Primarily positive correlations between the native ecosystem NDVI and precipitation imply that significant decreases in precipitation may exacerbate the decrease in NDVI of native ecosystems. NDVI-PDSI correlations were primarily negative on the windward side of the islands and positive on the leeward sides, suggesting a higher sensitivity to drought for leeward native ecosystems. Multi-decadal time series and spatially explicit data for native landscapes provide natural resource managers with long-term trends and monthly changes associated with vegetation health and stability.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s00267-022-01749-x","usgsCitation":"Madson, A., Dimson, M., Fortini, L., Kawelo, K., Tickin, T., Keir, M., Dong, C., Ma, Z., Beilman, D.W., Kay, K., Pando Ocon, J., Gallerani, E., Pau, S., and Gillespie, T., 2023, A near four-decade time series shows the Hawaiian Islands have been browning since the 1980s: Environmental Management, v. 71, p. 965-980, https://doi.org/10.1007/s00267-022-01749-x.","productDescription":"16 p.","startPage":"965","endPage":"980","ipdsId":"IP-138766","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":445227,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Angeles","active":true,"usgs":false}],"preferred":false,"id":871219,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Pau, Stephanie","contributorId":190208,"corporation":false,"usgs":false,"family":"Pau","given":"Stephanie","email":"","affiliations":[],"preferred":false,"id":871220,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Gillespie, Thomas W","contributorId":304639,"corporation":false,"usgs":false,"family":"Gillespie","given":"Thomas W","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":871221,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70256618,"text":"70256618 - 2023 - Accounting for spatial heterogeneity in visual obstruction in line-transect distance sampling of gopher tortoises","interactions":[],"lastModifiedDate":"2024-08-27T14:47:33.790307","indexId":"70256618","displayToPublicDate":"2022-11-21T09:38:37","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":"Accounting for spatial heterogeneity in visual obstruction in line-transect distance sampling of gopher tortoises","docAbstract":"<p><span>Line-transect distance sampling (LTDS) surveys are commonly used to estimate abundance of animals or objects. In terrestrial LTDS surveys of gopher tortoise (</span><i>Gopherus polyphemus</i><span>) burrows, the presence of ground-level vegetation substantially decreases detection of burrows of all sizes, but no field or analytical methods exist to control for spatially heterogeneous vegetation obstruction as a source of variation in detection. We propose the addition of a simple measurement of ground-level vegetation that serves as a covariate for the detection function. We present a Bayesian hierarchical model in which covariates burrow width and nearby vegetation height help to account for detection bias and improve precision of estimated density. We investigate the performance of this covariate by simulation and by using real LTDS data collected before and after application of prescribed fire. We collected data in 2018 at the Jones Center at Ichauway in Newton, Georgia, USA. Across all simulations, our model including both covariates produced the most accurate density point estimates of any of the models tested. For our case study, our Bayesian model with vegetation covariates tended to produce similar estimates of density before and after burns. Our study indicates that any level of spatial variation in vegetation obstruction decreases detection of burrows and may lead to underestimation in population size (≤68%) and proportion of individuals with small burrow sizes (≤32%) when not considered during analysis. Our work is extensible to other terrestrial sampling efforts where systematic measurement of a spatially distributed obstructing feature is feasible during the LTDS survey.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22338","usgsCitation":"Gaya, H.E., Smith, L., and Moore, C.T., 2023, Accounting for spatial heterogeneity in visual obstruction in line-transect distance sampling of gopher tortoises: Journal of Wildlife Management, v. 87, no. 2, e22338, 18 p., https://doi.org/10.1002/jwmg.22338.","productDescription":"e22338, 18 p.","ipdsId":"IP-138680","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445229,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22338","text":"Publisher Index Page"},{"id":433197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","county":"Baker County","city":"Newton","otherGeospatial":"Jones Center at Ichauway","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.5442497881046,\n              31.26474310157134\n            ],\n            [\n              -84.5442497881046,\n              31.19461870802469\n            ],\n            [\n              -84.4520518322151,\n              31.19461870802469\n            ],\n            [\n              -84.4520518322151,\n              31.26474310157134\n            ],\n            [\n              -84.5442497881046,\n              31.26474310157134\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"87","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Gaya, Heather E.","contributorId":341387,"corporation":false,"usgs":false,"family":"Gaya","given":"Heather","email":"","middleInitial":"E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":908335,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Lora L.","contributorId":341388,"corporation":false,"usgs":false,"family":"Smith","given":"Lora L.","affiliations":[{"id":81731,"text":"Jones Center at Ichauway","active":true,"usgs":false}],"preferred":false,"id":908336,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908337,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70248276,"text":"70248276 - 2023 - Animal tracing with sulfur isotopes: Spatial segregation and climate variability in Africa likely contribute to population trends of a migratory songbird","interactions":[],"lastModifiedDate":"2023-09-06T11:52:06.683712","indexId":"70248276","displayToPublicDate":"2022-11-21T06:48:50","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":"Animal tracing with sulfur isotopes: Spatial segregation and climate variability in Africa likely contribute to population trends of a migratory songbird","docAbstract":"<ol class=\"\"><li>Climatic conditions affect animals but range-wide impacts at the population level remain largely unknown, especially in migratory species. However, studying climate–population relationships is still challenging in small migrants due to a lack of efficient and cost-effective geographic tracking method.</li><li>Spatial distribution patterns of environmental stable isotopes (so called ‘isoscapes’) generally overcome these limitations but none of the currently available isoscapes provide a substantial longitudinal gradient in species-rich sub-Saharan Africa. In this region, sulphur (<i>δ</i><sup>34</sup>S) has not been sufficiently explored on a larger scale.</li><li>We developed a<span>&nbsp;</span><i>δ</i><sup>34</sup>S isoscape to trace animal origins in sub-Saharan Africa by coupling known-origin samples from tracked migratory birds with continental remotely sensed environmental data building on environment–<i>δ</i><sup>34</sup>S relationships using a flexible machine learning technique. Furthermore, we link population-specific nonbreeding grounds with interannual climatic variation that might translate to breeding population trends.</li><li>The predicted<span>&nbsp;</span><i>δ</i><sup>34</sup>S isotopic map featured east–west and coast-to-inland isotopic gradients and was applied to predict nonbreeding grounds of three breeding populations of Eurasian Reed Warblers<span>&nbsp;</span><i>Acrocephalus scirpaceus</i><span>&nbsp;</span>with two distinct migratory phenotypes. Breeding populations as well as migratory phenotypes exhibited large-scale segregation within the African nonbreeding range. These regions also differed substantially in the interannual climatic variation, with higher interannual variability in the eastern part of the range during 2001–2012. Over the same period, the eastern European breeding population seemed to have experienced a more steep decline in population size.</li><li>The link between migratory patterns and large-scale climatic variability appears important to better understand population trajectories in many declining migratory animals. We believe animal tracing using sulphur isotopes will facilitate these efforts and offers manifold ecological and forensic applications in the biodiversity hotspot of sub-Saharan Africa.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2656.13848","usgsCitation":"Brlik, V., Prochazka, P., Hansson, B., Stricker, C.A., Yohannes, E., Powell, R.L., and Wunder, M., 2023, Animal tracing with sulfur isotopes: Spatial segregation and climate variability in Africa likely contribute to population trends of a migratory songbird: Journal of Animal Ecology, v. 92, no. 7, p. 1320-1331, https://doi.org/10.1111/1365-2656.13848.","productDescription":"12 p.","startPage":"1320","endPage":"1331","ipdsId":"IP-139107","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":420539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -16.51755488992501,\n              22.062534969958534\n            ],\n            [\n              -16.51755488992501,\n              -6.524152699051768\n            ],\n            [\n              51.83202578130056,\n              -6.524152699051768\n            ],\n            [\n              51.83202578130056,\n              22.062534969958534\n            ],\n            [\n              -16.51755488992501,\n              22.062534969958534\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"92","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Brlik, Vojtech","contributorId":329410,"corporation":false,"usgs":false,"family":"Brlik","given":"Vojtech","affiliations":[{"id":37178,"text":"Charles University","active":true,"usgs":false}],"preferred":false,"id":882217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prochazka, Petr","contributorId":329411,"corporation":false,"usgs":false,"family":"Prochazka","given":"Petr","affiliations":[{"id":17790,"text":"Czech Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":882218,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansson, Bengt","contributorId":329412,"corporation":false,"usgs":false,"family":"Hansson","given":"Bengt","email":"","affiliations":[{"id":13428,"text":"Lund University","active":true,"usgs":false}],"preferred":false,"id":882219,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":882220,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yohannes, Elizabeth","contributorId":329413,"corporation":false,"usgs":false,"family":"Yohannes","given":"Elizabeth","email":"","affiliations":[{"id":55536,"text":"University of Konstanz","active":true,"usgs":false}],"preferred":false,"id":882221,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Powell, Rebecca L","contributorId":329414,"corporation":false,"usgs":false,"family":"Powell","given":"Rebecca","email":"","middleInitial":"L","affiliations":[{"id":12651,"text":"University of Denver","active":true,"usgs":false}],"preferred":false,"id":882222,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wunder, Michael B.","contributorId":65406,"corporation":false,"usgs":false,"family":"Wunder","given":"Michael B.","affiliations":[{"id":6674,"text":"Department of Integrative Biology, University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":882223,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70250311,"text":"70250311 - 2023 - A practical guide to understanding and validating complex models using data simulations","interactions":[],"lastModifiedDate":"2023-12-01T13:10:09.553573","indexId":"70250311","displayToPublicDate":"2022-11-18T07:07:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A practical guide to understanding and validating complex models using data simulations","docAbstract":"<ol class=\"\"><li>Biologists routinely fit novel and complex statistical models to push the limits of our understanding. Examples include, but are not limited to, flexible Bayesian approaches (e.g. BUGS, stan), frequentist and likelihood-based approaches (e.g. packages<span>&nbsp;</span><span class=\"smallCaps\">lme4</span>) and machine learning methods.</li><li>These software and programs afford the user greater control and flexibility in tailoring complex hierarchical models. However, this level of control and flexibility places a higher degree of responsibility on the user to evaluate the robustness of their statistical inference. To determine how often biologists are running model diagnostics on hierarchical models, we reviewed 50 recently published papers in 2021 in the journal<span>&nbsp;</span><i>Nature Ecology &amp; Evolution</i>, and we found that the majority of published papers did<span>&nbsp;</span><i>not</i><span>&nbsp;</span>report any validation of their hierarchical models, making it difficult for the reader to assess the robustness of their inference. This lack of reporting likely stems from a lack of standardized guidance for best practices and standard methods.</li><li>Here, we provide a guide to understanding and validating complex models using data simulations. To determine how often biologists use data simulation techniques, we also reviewed 50 recently published papers in 2021 in the journal<span>&nbsp;</span><i>Methods Ecology &amp; Evolution</i>. We found that 78% of the papers that proposed a new estimation technique, package or model used simulations or generated data in some capacity (18 of 23 papers); but very few of those papers (5 of 23 papers) included either a demonstration that the code could recover realistic estimates for a dataset with known parameters or a demonstration of the statistical properties of the approach. To distil the variety of simulations techniques and their uses, we provide a taxonomy of simulation studies based on the intended inference. We also encourage authors to include a basic validation study whenever novel statistical models are used, which in general, is easy to implement.</li><li>Simulating data helps a researcher gain a deeper understanding of the models and their assumptions and establish the reliability of their estimation approaches. Wider adoption of data simulations by biologists can improve statistical inference, reliability and open science practices.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.14030","usgsCitation":"DiRenzo, G.V., Hanks, E., and Miller, D., 2023, A practical guide to understanding and validating complex models using data simulations: Methods in Ecology and Evolution, v. 14, no. 1, p. 203-217, https://doi.org/10.1111/2041-210X.14030.","productDescription":"15 p.","startPage":"203","endPage":"217","ipdsId":"IP-138387","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":445239,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.14030","text":"Publisher Index Page"},{"id":435559,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99B0IJ7","text":"USGS data release","linkHelpText":"Simulations to understand and validate models"},{"id":423142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":889406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanks, Ephraim","contributorId":332094,"corporation":false,"usgs":false,"family":"Hanks","given":"Ephraim","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":889407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, David A. W.","contributorId":332095,"corporation":false,"usgs":false,"family":"Miller","given":"David A. W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":889408,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70238803,"text":"70238803 - 2023 - A review of supervised learning methods for classifying animal behavioural states from environmental features","interactions":[],"lastModifiedDate":"2023-01-18T17:24:36.527931","indexId":"70238803","displayToPublicDate":"2022-11-16T07:46:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A review of supervised learning methods for classifying animal behavioural states from environmental features","docAbstract":"<div class=\"article-section__content en main\"><ol class=\"\"><li>Accurately predicting behavioural modes of animals in response to environmental features is important for ecology and conservation. Supervised learning (SL) methods are increasingly common in animal movement ecology for classifying behavioural modes. However, few examples exist of applying SL to classify polytomous animal behaviour from environmental features especially in the context of millions of animal observations.</li><li>We review SL methods (weighted<span>&nbsp;</span><i>k</i>-nearest neighbours; neural nets; random forests; and boosted classification trees with XGBoost) for classifying polytomous animal behaviour from environmental predictors. We also describe tuning parameter selection and assessment strategies, approaches for visualizing relationships between predictors and class outputs, and computational considerations. We demonstrate these methods by predicting three categories of risk to bald eagles from colliding with wind turbines using, as predictors, 12 environmental state features associated with 1.7 million GPS telemetry data points from 57 eagles.</li><li>Of the SL methods we considered, XGBoost yielded the most accurate model with 86.2% classification accuracy and pairwise-averaged area under the ROC curve of 90.6. Computational time of XGBoost scaled better to large data than any other SL method. We also show how SHAP values integrated in the R package (<span class=\"smallCaps\">xgboost</span>) facilitate investigation of variable relationships and importance.</li><li>For big data applications, XGBoost appears to provide superior classification accuracy and computational efficiency. Our results suggest XGBoost should be considered as an early modelling option in situations where the intent is to classify millions of animal behaviour observations from environmental predictors and to understand relationships between those predictors and movement behaviours. We also offer a tutorial to assist researchers in implementing this method.</li></ol></div>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.14019","usgsCitation":"Bergen, S., Huso, M., Duerr, A.E., Braham, M.A., Schmuecker, S., Miller, T.A., and Katzner, T., 2023, A review of supervised learning methods for classifying animal behavioural states from environmental features: Methods in Ecology and Evolution, v. 14, no. 1, p. 189-202, https://doi.org/10.1111/2041-210X.14019.","productDescription":"14 p.","startPage":"189","endPage":"202","ipdsId":"IP-137834","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":445244,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.14019","text":"Publisher Index Page"},{"id":410360,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Bergen, Silas","contributorId":288432,"corporation":false,"usgs":false,"family":"Bergen","given":"Silas","email":"","affiliations":[{"id":61757,"text":"Winona State University","active":true,"usgs":false}],"preferred":false,"id":858757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huso, Manuela 0000-0003-4687-6625 mhuso@usgs.gov","orcid":"https://orcid.org/0000-0003-4687-6625","contributorId":223969,"corporation":false,"usgs":true,"family":"Huso","given":"Manuela","email":"mhuso@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":858758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duerr, Adam E.","contributorId":102324,"corporation":false,"usgs":true,"family":"Duerr","given":"Adam","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":858759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braham, Missy A","contributorId":288433,"corporation":false,"usgs":false,"family":"Braham","given":"Missy","email":"","middleInitial":"A","affiliations":[{"id":61759,"text":"Conservation Science Global, Inc.","active":true,"usgs":false}],"preferred":false,"id":858760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmuecker, Sara","contributorId":213247,"corporation":false,"usgs":false,"family":"Schmuecker","given":"Sara","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":858761,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Tricia A.","contributorId":190591,"corporation":false,"usgs":false,"family":"Miller","given":"Tricia","email":"","middleInitial":"A.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":858762,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":858763,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70239408,"text":"70239408 - 2023 - Life-cycle model reveals sensitive life stages and evaluates recovery options for a dwindling Pacific salmon population","interactions":[],"lastModifiedDate":"2023-03-01T17:09:22.001565","indexId":"70239408","displayToPublicDate":"2022-11-15T06:51:44","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Life-cycle model reveals sensitive life stages and evaluates recovery options for a dwindling Pacific salmon population","docAbstract":"<div id=\"article__content\" class=\"col-sm-12 col-md-8 col-lg-8 article__content article-row-left\"><div class=\"article__body \"><div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Population models, using empirical survival rates estimates for different life stages, can help managers explore whether various management options could stabilize a declining population or restore it to former levels of abundance. Here we used two decades of data on five life stages of the Cedar River, USA Sockeye Salmon,<span>&nbsp;</span><i>Oncorhynchus nerka</i>, population to create and parameterize a life-cycle model. This formerly large but unproductive population is now in steep decline, despite hatchery enhancement. We gathered population-specific data on survival during five stages: 1) egg-to-fry, 2) fry-to-presmolt, 3) presmolt-to-adult return from the ocean, 4) adult<span>&nbsp;</span><i>en route</i><span>&nbsp;</span>from the ocean to the spawning grounds, and 5) reproduction. We ground-truthed the model to ensure its fit to the data, and then we modified survival and other parameters during various stages to examine future scenarios. Our analyses revealed that low survival of juveniles in Lake Washington (stage 2: averaging only 3% over the last 20 years), survival of adults returning to fresh water to spawn (stage 4), and survival of adults on spawning grounds to reproduce (stage 5) are likely limiting factors. Combined increases in these stages and others (specifically, the proportion of fish taken into the hatchery to be spawned) might also recover the population. As in other integrated hatchery populations, managers must weigh options relating to balancing the fraction of natural- and hatchery-origin fish, and our results showed that increasing the fraction of fish taken into the hatchery alone will not recover the population. Our model brings together population-specific data to help managers weigh conservation strategies and understand which stages and habitats are most limiting and how much survival must increase to achieve recovery targets. By extension, our analyses also reveal the utility of such models in other cases where stage-specific data are available.</p></div></div></div></div>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10859","usgsCitation":"Kendall, N.W., Unrein, J.R., Volk, C., Beauchamp, D., Fresh, K.L., and Quinn, T.P., 2023, Life-cycle model reveals sensitive life stages and evaluates recovery options for a dwindling Pacific salmon population: North American Journal of Fisheries Management, v. 43, no. 1, p. 203-230, https://doi.org/10.1002/nafm.10859.","productDescription":"28 p.","startPage":"203","endPage":"230","ipdsId":"IP-137770","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":467133,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/nafm.10859","text":"External Repository"},{"id":411778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kendall, Neala W.","contributorId":288624,"corporation":false,"usgs":false,"family":"Kendall","given":"Neala","email":"","middleInitial":"W.","affiliations":[{"id":61815,"text":"wafg","active":true,"usgs":false}],"preferred":false,"id":861483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Unrein, Julia R.","contributorId":172777,"corporation":false,"usgs":false,"family":"Unrein","given":"Julia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":861484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Volk, Carol","contributorId":300802,"corporation":false,"usgs":false,"family":"Volk","given":"Carol","affiliations":[{"id":35354,"text":"Seattle Public Utilities","active":true,"usgs":false}],"preferred":false,"id":861485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":861486,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fresh, Kurt L.","contributorId":98597,"corporation":false,"usgs":false,"family":"Fresh","given":"Kurt","email":"","middleInitial":"L.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":861487,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Quinn, Thomas P.","contributorId":167272,"corporation":false,"usgs":false,"family":"Quinn","given":"Thomas","email":"","middleInitial":"P.","affiliations":[{"id":24671,"text":"School of Aquatic and Fsiery Sciences, UW, Box 355020, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":861488,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70239296,"text":"70239296 - 2023 - An interactive viewer to improve operational aftershock forecasts","interactions":[],"lastModifiedDate":"2023-01-06T14:43:02.358938","indexId":"70239296","displayToPublicDate":"2022-11-14T08:40:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"An interactive viewer to improve operational aftershock forecasts","docAbstract":"<p><span>The U.S. Geological Survey (USGS) issues forecasts for aftershocks about 20&nbsp;minutes after most earthquakes above M&nbsp;5 in the United States and its territories, and updates these forecasts 75 times during the first year. Most of the forecasts are issued automatically, but some forecasts require manual intervention to maintain accuracy. It is important to identify the sequences whose forecasts will benefit from a modified approach so the USGS can provide accurate information to the public. The oaftools R package (</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf11\">Paris and Michael, 2022</a><span>) includes functions that analyze and plot earthquake sequences and their forecasts to identify which sequences require such intervention. The package includes the Operational Aftershock Forecast (OAF) Viewer, which incorporates the functions into an interactive web environment that can be used to explore aftershock sequences. The OAF Viewer starts with a global map and table of mainshocks. After a mainshock has been selected, the map and a new table show its aftershocks and the OAF Viewer generates five analytical plots: (1)&nbsp;magnitude–time, which is used to look for patterns in the data; (2)&nbsp;cumulative number, to see how the productivity of the sequence compares to a&nbsp;</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf13\">Reasenberg and Jones (1989)</a><span>&nbsp;aftershock model over time; (3)&nbsp;magnitude–frequency, to compare the ratio of large to small magnitudes and extrapolate to higher magnitudes with sparse data and lower magnitudes with incomplete data; (4)&nbsp;forecast success, to compare the forecasts with observations for a sequence; and (5)&nbsp;parameter–time, which examines the temporal evolution of the forecast model parameters. The user can interact with the functions provided by the oaftools package through the OAF Viewer or by incorporating the functions into their own analysis methods. The OAF Viewer will help seismologists understand complexities in the data, communicate with the public and emergency managers, and improve the OAF system by maintaining operational awareness.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220220108","usgsCitation":"Paris, G.M., and Michael, A.J., 2023, An interactive viewer to improve operational aftershock forecasts: Seismological Research Letters, v. 94, no. 1, p. 473-484, https://doi.org/10.1785/0220220108.","productDescription":"12 p.","startPage":"473","endPage":"484","ipdsId":"IP-138814","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":435560,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PZTYEN","text":"USGS data release","linkHelpText":"OAF Tools - R package"},{"id":411488,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Paris, Gabrielle Madison 0000-0001-5008-1441","orcid":"https://orcid.org/0000-0001-5008-1441","contributorId":300636,"corporation":false,"usgs":true,"family":"Paris","given":"Gabrielle","email":"","middleInitial":"Madison","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":861018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Michael, Andrew J. 0000-0002-2403-5019 michael@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-5019","contributorId":1280,"corporation":false,"usgs":true,"family":"Michael","given":"Andrew","email":"michael@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":861019,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70238623,"text":"70238623 - 2023 - Habitat associations of riverine fishes among rocky shoals","interactions":[],"lastModifiedDate":"2023-03-15T14:29:14.633881","indexId":"70238623","displayToPublicDate":"2022-11-14T07:09:41","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Habitat associations of riverine fishes among rocky shoals","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Understanding species' associations with physical habitat conditions is a fundamental goal of ecology. For organisms that occupy lotic ecosystems, relationships to streamflow are of particular importance, but these associations are unstudied for most species. We tested the predictability of fish–microhabitat relationships in river shoals (shallow, rocky areas with relatively swift water flow) using a large data set from the Conasauga River in Georgia, USA. Our objective was to assess the consistency of species-specific relationships with flow-dependent variables (depth, velocity, Reynolds number and Froude number) while accounting for other microhabitat variables (e.g. vegetation). We used data from 8285 seine-sets collected during late summer or autumn at 26 sites over 12 years to relate occurrence and counts of 22 fish species to habitat variables using generalised linear multiple regression models. Results showed that microhabitat models explained a substantial amount of the variation in counts for some species, although other species were poorly predicted. We classified 16 species as velocity specialists and nine species as depth specialists, with six species specialised for depth and velocity and three species classified as depth and velocity generalists. The variability in habitat associations that we observed suggests that species will be unevenly affected by anthropogenic activities that alter flows.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/eff.12690","usgsCitation":"Baynes, A.Y., Freeman, M., McKay, S.K., and Wenger, S., 2023, Habitat associations of riverine fishes among rocky shoals: Ecology of Freshwater Fish, v. 32, no. 2, p. 336-347, https://doi.org/10.1111/eff.12690.","productDescription":"10 p.","startPage":"336","endPage":"347","ipdsId":"IP-144264","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":445253,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eff.12690","text":"Publisher Index Page"},{"id":409984,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Conasauga River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -85.05244590331915,\n              34.995585633321085\n            ],\n            [\n              -85.05244590331915,\n              34.557353805927164\n            ],\n            [\n              -84.68480239587811,\n              34.557353805927164\n            ],\n            [\n              -84.68480239587811,\n              34.995585633321085\n            ],\n            [\n              -85.05244590331915,\n              34.995585633321085\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"32","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Baynes, Anna Y.","contributorId":299585,"corporation":false,"usgs":false,"family":"Baynes","given":"Anna","email":"","middleInitial":"Y.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":858134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":858135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKay, S. Kyle","contributorId":169086,"corporation":false,"usgs":false,"family":"McKay","given":"S.","email":"","middleInitial":"Kyle","affiliations":[],"preferred":false,"id":858136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":858137,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70238547,"text":"70238547 - 2023 - High resolution spatiotemporal patterns of flow at the landscape scale in montane non-perennial streams","interactions":[],"lastModifiedDate":"2023-02-02T17:47:42.428852","indexId":"70238547","displayToPublicDate":"2022-11-14T06:43:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"High resolution spatiotemporal patterns of flow at the landscape scale in montane non-perennial streams","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Intermittent and ephemeral streams in dryland environments support diverse assemblages of aquatic and terrestrial life. Understanding when and where water flows provide insights into the availability of water, its response to external controlling factors, and potential sensitivity to climate change and a host of human activities. Knowledge regarding the timing of drying/wetting cycles can also be useful to map critical habitats for species and ecosystems that rely on these temporary water sources. However, identifying the locations and monitoring the timing of streamflow and channel sediment moisture remains a challenging endeavor. In this paper, we analyzed daily conductivity from 37 sensors distributed along 10 streams across an arid mountain front in Arizona (United States) to assess spatiotemporal patterns in flow permanence, defined as the timing and extent of water in streams. Conductivity sensors provide information on surface flow and sediment moisture, supporting a stream classification based on seasonal flow dynamics. Our results provide insight into flow responses to seasonal rainfall, highlighting stream reaches very reactive to rainfall versus those demonstrating more stable streamflow. The strength of stream responses to precipitation are explored in the context of surficial geology. In summary, conductivity data can be used to map potential stream habitat for water-dependent species in both space and time, while also providing the basis upon which sensitivity to ongoing climate change can be evaluated.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/rra.4076","usgsCitation":"Sabathier, R., Singer, M.B., Stella, J., Roberts, D.A., Caylor, K.K., Jaeger, K.L., and Olden, J., 2023, High resolution spatiotemporal patterns of flow at the landscape scale in montane non-perennial streams: River Research and Applications, v. 39, no. 2, p. 225-240, https://doi.org/10.1002/rra.4076.","productDescription":"16 p.","startPage":"225","endPage":"240","ipdsId":"IP-143158","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":445255,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.4076","text":"Publisher Index Page"},{"id":409785,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Huachuca Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -110.40493965719584,\n              31.547876369215373\n            ],\n            [\n              -110.40493965719584,\n              31.33957123936571\n            ],\n            [\n              -110.21158797775463,\n              31.33957123936571\n            ],\n            [\n              -110.21158797775463,\n              31.547876369215373\n            ],\n            [\n              -110.40493965719584,\n              31.547876369215373\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"39","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Sabathier, Romy 0000-0001-9401-7871","orcid":"https://orcid.org/0000-0001-9401-7871","contributorId":299448,"corporation":false,"usgs":false,"family":"Sabathier","given":"Romy","email":"","affiliations":[{"id":17940,"text":"Cardiff University","active":true,"usgs":false}],"preferred":false,"id":857826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Singer, Michael Bliss 0000-0002-6899-2224","orcid":"https://orcid.org/0000-0002-6899-2224","contributorId":299449,"corporation":false,"usgs":false,"family":"Singer","given":"Michael","email":"","middleInitial":"Bliss","affiliations":[{"id":17940,"text":"Cardiff University","active":true,"usgs":false}],"preferred":false,"id":857827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stella, John C","contributorId":149423,"corporation":false,"usgs":false,"family":"Stella","given":"John C","affiliations":[{"id":17732,"text":"Professor, Dept of Forest & Natural Resources Mgmt, SUNY at ESF","active":true,"usgs":false}],"preferred":false,"id":857828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roberts, Dar A.","contributorId":100503,"corporation":false,"usgs":false,"family":"Roberts","given":"Dar","email":"","middleInitial":"A.","affiliations":[{"id":12804,"text":"Univ. of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":857829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caylor, Kelly K.","contributorId":245242,"corporation":false,"usgs":false,"family":"Caylor","given":"Kelly","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":857830,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jaeger, Kristin L. 0000-0002-1209-8506","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":206935,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":857831,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Olden, Julian 0000-0003-2143-1187","orcid":"https://orcid.org/0000-0003-2143-1187","contributorId":296007,"corporation":false,"usgs":false,"family":"Olden","given":"Julian","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":857832,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70238543,"text":"70238543 - 2023 - Estrogenic activity response to best management practice implementation in agricultural watersheds in the Chesapeake Bay watershed","interactions":[],"lastModifiedDate":"2022-11-29T13:21:58.482355","indexId":"70238543","displayToPublicDate":"2022-11-13T07:19:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Estrogenic activity response to best management practice implementation in agricultural watersheds in the Chesapeake Bay watershed","docAbstract":"<div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\">Best management practices (BMPs) have been predominantly used throughout the Chesapeake Bay watershed (CBW) to reduce nutrients and sediments entering streams, rivers, and the bay. These practices have been successful in reducing loads entering the estuary and have shown the potential to reduce other contaminants (pesticides, hormonally active compounds, pathogens) in localized studies and modeled load estimates. However, further understanding of relationships between BMPs and non-nutrient contaminant reductions at regional scales using sampled data would be beneficial. Total estrogenic activity was measured in surface water samples collected over a decade (2008–2018) in 211 undeveloped NHDPlus V2.1 watersheds within the CBW. Bayesian hierarchical modeling between total estrogenic activity and landscape predictors including landcover, runoff, BMP intensity, and a BMP*agriculture intensity interaction term indicates a 96% posterior probability that BMP intensity on agricultural land is reducing total estrogenic activity. Additionally, watersheds with high agriculture and low BMPs had a 49% posterior probability of exceeding an effects-based threshold in aquatic organisms of 1&nbsp;ng/L but only a 1% posterior probability of exceeding this threshold in high-agriculture, high-BMP watersheds.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2022.116734","usgsCitation":"Gordon, S.E., Wagner, T., Smalling, K., and Devereux, O., 2023, Estrogenic activity response to best management practice implementation in agricultural watersheds in the Chesapeake Bay watershed: Journal of Environmental Management, v. 326, no. Part A, 116734, 9 p., https://doi.org/10.1016/j.jenvman.2022.116734.","productDescription":"116734, 9 p.","ipdsId":"IP-143827","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":445257,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2022.116734","text":"Publisher Index Page"},{"id":409790,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.1904296875,\n              38.41916639395372\n            ],\n        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          [\n              -75.1904296875,\n              38.41916639395372\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"326","issue":"Part A","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gordon, Stephanie E. 0000-0002-6292-2612 sgordon@usgs.gov","orcid":"https://orcid.org/0000-0002-6292-2612","contributorId":200931,"corporation":false,"usgs":true,"family":"Gordon","given":"Stephanie","email":"sgordon@usgs.gov","middleInitial":"E.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":857806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Tyler 0000-0003-1726-016X","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":299446,"corporation":false,"usgs":false,"family":"Wagner","given":"Tyler","affiliations":[{"id":64845,"text":"U.S. Geological Survey, Pennsylvania Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":857807,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":857808,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Devereux, Olivia H. 0000-0002-3911-3307","orcid":"https://orcid.org/0000-0002-3911-3307","contributorId":198108,"corporation":false,"usgs":false,"family":"Devereux","given":"Olivia H.","affiliations":[],"preferred":false,"id":857809,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70256620,"text":"70256620 - 2023 - The effect of scent lures on detection is not equitable among sympatric species","interactions":[],"lastModifiedDate":"2024-08-27T14:51:35.039219","indexId":"70256620","displayToPublicDate":"2022-11-11T09:48:36","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"The effect of scent lures on detection is not equitable among sympatric species","docAbstract":"<p><strong>Context:<span>&nbsp;</span></strong>Camera trapping is an effective tool for cost-efficient monitoring of species over large temporal and spatial scales and it is becoming an increasingly popular method for investigating wildlife communities and trophic interactions. However, camera trapping targeting rare and elusive species can be hampered by low detection rates, which can decrease the accuracy and precision of results from common analytical approaches (e.g., occupancy modeling, capture-recapture). Consequently, researchers often employ attractants to increase detection without accounting for how attractants influence detection of species among trophic levels.</p><p><strong>Aims:<span>&nbsp;</span></strong>We aimed to evaluate the influences of a commonly used non-species-specific olfactory lure (i.e. sardines) and sampling design on detection of four species (i.e. bobcat [<i>Lynx rufus</i>], coyote [<i>Canis latrans</i>], raccoon [<i>Procyon lotor</i>], and eastern cottontail [<i>Sylvilagus floridanus</i>]) that represented a range of foraging guilds in an agricultural landscape.</p><p><strong>Methods:<span>&nbsp;</span></strong>We set 180 camera stations, each for ∼28&nbsp;days, during the summer of 2019. We set cameras with one of three lure treatments: (1) olfactory lure, (2) no olfactory lure, or (3) olfactory lure only during the latter half of the survey. We evaluated the influence of the lure at three temporal scales of detection (i.e. daily probability of detection, independent sequences per daily detection, and triggers per independent sequence).</p><p><strong>Key results:<span>&nbsp;</span></strong>The lure tended to positively influence detection of coyotes and raccoons but negatively influenced detection of bobcats and eastern cottontails. The influence of the lure varied among temporal scales of detection.</p><p><strong>Conclusions:<span>&nbsp;</span></strong>Scent lures can differentially influence detection of species within or among tropic levels, and the influence of a scent lure may vary among temporal scales.</p><p><strong>Implications:<span>&nbsp;</span></strong>Our results demonstrate the importance of evaluating the influence of an attractant for each focal species when using camera data to conduct multi-species or community analyses, accounting for variation in sampling strategies across cameras, and identifying the appropriate species-specific temporal resolution for assessing variation in detection data. Furthermore, we highlight that care should be taken when using camera data as an index of relative abundance (e.g. as is commonly done with prey species) when there is variation in the use of lures across cameras.</p>","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WR22094","usgsCitation":"Dart, M.M., Perkins, L., Jenks, J., Hatfield, G., and Lonsinger, R.C., 2023, The effect of scent lures on detection is not equitable among sympatric species: Wildlife Research, v. 50, no. 3, p. 190-200, https://doi.org/10.1071/WR22094.","productDescription":"11 p.","startPage":"190","endPage":"200","ipdsId":"IP-135401","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433198,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Dart, Marlin M.","contributorId":340675,"corporation":false,"usgs":false,"family":"Dart","given":"Marlin","email":"","middleInitial":"M.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":908346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perkins, Lora B.","contributorId":224968,"corporation":false,"usgs":false,"family":"Perkins","given":"Lora B.","affiliations":[{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":908347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jenks, Jonathan A.","contributorId":264322,"corporation":false,"usgs":false,"family":"Jenks","given":"Jonathan A.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":908348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatfield, Gary","contributorId":341397,"corporation":false,"usgs":false,"family":"Hatfield","given":"Gary","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":908349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lonsinger, Robert Charles 0000-0002-1040-7299","orcid":"https://orcid.org/0000-0002-1040-7299","contributorId":340524,"corporation":false,"usgs":true,"family":"Lonsinger","given":"Robert","email":"","middleInitial":"Charles","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908350,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70238549,"text":"70238549 - 2023 - Geochemistry of the Cretaceous Mowry Shale in the Wind River Basin, Wyoming","interactions":[],"lastModifiedDate":"2023-07-11T15:28:59.13242","indexId":"70238549","displayToPublicDate":"2022-11-11T07:22:49","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":"Geochemistry of the Cretaceous Mowry Shale in the Wind River Basin, Wyoming","docAbstract":"<p>The siliceous nature of the Mowry Shale distinguishes it from many of the well-studied organic-rich mudstones of the Cretaceous Western Interior Seaway. Available models of organic enrichment in mudstones rarely incorporate detailed biomarker, bulk organic, inorganic, and mineralogy data. Here, we used these data to evaluate how variations in organic matter source, productivity, dilution, and preservation modulated organic matter accumulation during the deposition of the Mowry Shale, while also demonstrating the benefits of this integrated approach. An organic stable carbon isotope vertical profile for the Mowry Shale is presented to test whether the Mowry Shale was deposited during oceanic anoxic event 1d (OAE 1d), thereby contributing to organic enrichment in the Mowry Shale.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/B36382.1","usgsCitation":"French, K.L., Birdwell, J.E., and Lillis, P.G., 2023, Geochemistry of the Cretaceous Mowry Shale in the Wind River Basin, Wyoming: GSA Bulletin, v. 135, no. 7-8, p. 1899-1922, https://doi.org/10.1130/B36382.1.","productDescription":"24 p.","startPage":"1899","endPage":"1922","ipdsId":"IP-131176","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":445264,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/b36382.1","text":"Publisher Index Page"},{"id":435562,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FKDVK2","text":"USGS data release","linkHelpText":"Data release for Geochemistry of the Cretaceous Mowry Shale in the Wind River Basin, Wyoming"},{"id":409791,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Wind River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -107.00,\n              43.00\n            ],\n            [\n              -107.00,\n              42.20\n            ],\n            [\n              -106.2,\n              42.20\n            ],\n            [\n              -106.2,\n              43.00\n            ],\n            [\n              -107.00,\n              43.00\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"135","issue":"7-8","noUsgsAuthors":false,"publicationDate":"2022-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"French, Katherine L. 0000-0002-0153-8035","orcid":"https://orcid.org/0000-0002-0153-8035","contributorId":205462,"corporation":false,"usgs":true,"family":"French","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":false,"id":857833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":857834,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lillis, Paul G. 0000-0002-7508-1699 plillis@usgs.gov","orcid":"https://orcid.org/0000-0002-7508-1699","contributorId":1817,"corporation":false,"usgs":true,"family":"Lillis","given":"Paul","email":"plillis@usgs.gov","middleInitial":"G.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":857835,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70238554,"text":"70238554 - 2023 - Ecologically relevant moisture and temperature metrics for assessing dryland ecosystem dynamics","interactions":[],"lastModifiedDate":"2023-04-11T16:54:56.776638","indexId":"70238554","displayToPublicDate":"2022-11-11T06:51:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Ecologically relevant moisture and temperature metrics for assessing dryland ecosystem dynamics","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>In drylands, water-limited regions that cover ~40% of the global land surface, ecosystems are primarily controlled by access to soil moisture and exposure to simultaneously hot and dry conditions. Quantifying ecologically relevant environmental metrics is difficult in drylands because the response of vegetation to moisture and temperature conditions is not easily explained solely by climate-based metrics. To address this knowledge gap, we developed and examined 27 climate and ecological drought metrics across dryland areas of the western U.S. Included in the 27 metrics is a suite of 19 largely new “ecological drought metrics” that are designed to quantify multiple aspects of environmental limitation in drylands, including overall growing conditions, seasonal fluctuations, seasonal moisture timing, exposure to extreme drought, and recruitment potential for perennial plants. To quantify these metrics, we simulated water balance pools and fluxes of daily soil moisture at multiple depths with historical weather from 1970-2010 using the SOILWAT2 ecosystem water balance model. We assessed the relationships among these metrics and their spatial and temporal patterns. We found that the inclusion of ecological drought metrics substantially increased the dimensionality of the climate metrics dataset; the number of independent variables needed to explain 90% of the variance in the dataset increased with the addition of ecological drought metrics. Spatial patterns in overall growing conditions represented well-known differences among ecoregions, for example high temperatures and low precipitation in the southwest and cool temperatures and greater precipitation in the northeast. Seasonal fluctuation in soil water availability (SWA) was greatest in the southwest (Mojave Desert) while fluctuation in climatic water deficit (CWD) was greatest in the northwest (northern Great Basin and Columbia Plateau). Seasonal timing of moisture also differed among metrics; the timing of wet degree days (WDD), SWA and CWD were only weakly related to seasonal timing of precipitation. Plant recruitment metrics varied strongly across western drylands. In the Great Plains, recruitment events occurred more frequently and lasted longer than in the intermountain regions, where recruitment events were comparatively rare and short. These ecological drought metrics provide new insight into patterns of soil moisture and temperature that shape the structure and function of dryland ecosystems. The metrics will be useful for assessing the potential impact of climate change on dryland ecosystems and developing adaptive resource management strategies to sustain dryland ecosystem services in a changing world.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/eco.2509","usgsCitation":"Chenoweth, D.A., Schlaepfer, D.R., Chambers, J., Brown, J.L., Urza, A., Hanberry, B., Board, D., Crist, M., and Bradford, J., 2023, Ecologically relevant moisture and temperature metrics for assessing dryland ecosystem dynamics: Ecohydrology, v. 16, no. 3, e2509, https://doi.org/10.1002/eco.2509.","productDescription":"e2509","ipdsId":"IP-144651","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":445266,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eco.2509","text":"Publisher Index Page"},{"id":409787,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Chenoweth, D. 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