{"pageNumber":"523","pageRowStart":"13050","pageSize":"25","recordCount":165928,"records":[{"id":70231651,"text":"70231651 - 2021 - Linking altered flow regimes to biological condition: An example using benthic macroinvertebrates in small streams of the Chesapeake Bay watershed","interactions":[],"lastModifiedDate":"2022-05-18T15:38:14.741057","indexId":"70231651","displayToPublicDate":"2021-03-12T10:34:52","publicationYear":"2021","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":"Linking altered flow regimes to biological condition: An example using benthic macroinvertebrates in small streams of the Chesapeake Bay watershed","docAbstract":"<p><span>Regionally scaled assessments of hydrologic alteration for small streams and its effects on freshwater taxa are often inhibited by a low number of stream gages. To overcome this limitation, we paired modeled estimates of hydrologic alteration to a benthic macroinvertebrate index of biotic integrity data for 4522 stream reaches across the Chesapeake Bay watershed. Using separate random-forest models, we predicted flow status (inflated, diminished, or indeterminant) for 12 published hydrologic metrics (HMs) that characterize the main components of flow regimes. We used these models to predict each HM status for each stream reach in the watershed, and linked predictions to macroinvertebrate condition samples collected from streams with drainage areas less than 200 km</span><sup>2</sup><span>. Flow alteration was calculated as the number of HMs with inflated or diminished status and ranged from 0 (no HM inflated or diminished) to 12 (all 12 HMs inflated or diminished). When focused solely on the stream condition and flow-alteration relationship, degraded macroinvertebrate condition was, depending on the number of HMs used, 3.8–4.7 times more likely in a flow-altered site; this likelihood was over twofold higher in the urban-focused dataset (8.7–10.8), and was never significant in the agriculture-focused dataset. Logistic regression analysis using the entire dataset showed for every unit increase in flow-alteration intensity, the odds of a degraded condition increased 3.7%. Our results provide an indication of whether altered streamflow is a possible driver of degraded biological conditions, information that could help managers prioritize management actions and lead to more effective restoration efforts.</span></p>","language":"English","publisher":"Springer Link","doi":"10.1007/s00267-021-01450-5","usgsCitation":"Maloney, K.O., Carlisle, D.M., Buchanan, C., Rapp, J.L., Austin, S.H., Cashman, M.J., and Young, J.A., 2021, Linking altered flow regimes to biological condition: An example using benthic macroinvertebrates in small streams of the Chesapeake Bay watershed: Environmental Management, v. 67, p. 1171-1185, https://doi.org/10.1007/s00267-021-01450-5.","productDescription":"15 p.","startPage":"1171","endPage":"1185","ipdsId":"IP-121380","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":453098,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":843233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":843234,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buchanan, Claire 0000-0001-5627-448X","orcid":"https://orcid.org/0000-0001-5627-448X","contributorId":291854,"corporation":false,"usgs":false,"family":"Buchanan","given":"Claire","email":"","affiliations":[{"id":39005,"text":"ICPRB","active":true,"usgs":false}],"preferred":false,"id":843235,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rapp, Jennifer L. 0000-0003-2253-9886 jrapp@usgs.gov","orcid":"https://orcid.org/0000-0003-2253-9886","contributorId":197342,"corporation":false,"usgs":true,"family":"Rapp","given":"Jennifer","email":"jrapp@usgs.gov","middleInitial":"L.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":843236,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Austin, Samuel H. 0000-0001-5626-023X saustin@usgs.gov","orcid":"https://orcid.org/0000-0001-5626-023X","contributorId":153,"corporation":false,"usgs":true,"family":"Austin","given":"Samuel","email":"saustin@usgs.gov","middleInitial":"H.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":843237,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cashman, Matthew J. 0000-0002-6635-4309","orcid":"https://orcid.org/0000-0002-6635-4309","contributorId":203315,"corporation":false,"usgs":true,"family":"Cashman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":843238,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Young, John A. 0000-0002-4500-3673 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,{"id":70229460,"text":"70229460 - 2021 - Migration distance and maternal resource allocation determine timing of birth in a large herbivore","interactions":[],"lastModifiedDate":"2022-03-09T15:38:27.235558","indexId":"70229460","displayToPublicDate":"2021-03-12T09:31:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Migration distance and maternal resource allocation determine timing of birth in a large herbivore","docAbstract":"<p><span>Birth timing is a key life-history characteristic that influences fitness and population performance. For migratory animals, however, appropriately timing birth on one seasonal range may be constrained by events occurring during other parts of the migratory cycle. We investigated how the use of capital and income resources may facilitate flexibility in reproductive phenology of migratory mule deer in western Wyoming, USA, over a 5-yr period (2015–2019). Specifically, we examined how seasonal interactions affected three interrelated life-history characteristics: fetal development, birth mass, and birth timing. Females in good nutritional condition at the onset of winter and those that migrated short distances had more developed fetuses (measured as fetal eye diameter in March). Variation in parturition date was explained largely by fetal development; however, there were up to 16&nbsp;d of plasticity in expected birth date. Plasticity in expected birth date was shaped by income resources in the form of exposure to spring green-up. Although individuals that experienced greater exposure to spring green-up were able to advance expected birth date, being born early or late with respect to fetal development had no effect on birth mass of offspring. Furthermore, we investigated the trade-offs migrating mule deer face by evaluating support for existing theory that predicts that births should be matched to local peaks in resource availability at the birth site. In contrast to this prediction, only long-distance migrants that paced migration with the flush of spring green-up, giving birth shortly after ending migration, were able to match birth with spring green-up. Shorter-distance migrants completed migration sooner and gave birth earlier, seemingly trading off more time for offspring to grow and develop over greater access to resources. Thus, movement tactic had profound downstream effects on birth timing. These findings highlight a need to reconsider classical theory on optimal birth timing, which has focused solely on conditions at the birth site.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3334","usgsCitation":"Aikens, E., Dwinnell, S., LaSharr, T., Jakopak, R., Fralick, G., Randall, J., Kaiser, R., Thonhoff, M., Kauffman, M., and Monteith, K., 2021, Migration distance and maternal resource allocation determine timing of birth in a large herbivore: Ecology, v. 102, no. 6, e03334, 12 p., https://doi.org/10.1002/ecy.3334.","productDescription":"e03334, 12 p.","ipdsId":"IP-125404","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":453100,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.3334","text":"Publisher Index Page"},{"id":396917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.98388671874999,\n              41.91045347666418\n            ],\n            [\n              -109.6875,\n              41.91045347666418\n            ],\n            [\n              -109.6875,\n              43.628123412124616\n            ],\n            [\n              -110.98388671874999,\n              43.628123412124616\n            ],\n            [\n              -110.98388671874999,\n              41.91045347666418\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"102","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-04-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Aikens, Ellen O.","contributorId":288165,"corporation":false,"usgs":false,"family":"Aikens","given":"Ellen O.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":837541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dwinnell, Samantha P.H.","contributorId":288166,"corporation":false,"usgs":false,"family":"Dwinnell","given":"Samantha P.H.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":837542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaSharr, Tayler N.","contributorId":288167,"corporation":false,"usgs":false,"family":"LaSharr","given":"Tayler N.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":837543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jakopak, Rhiannon P.","contributorId":288168,"corporation":false,"usgs":false,"family":"Jakopak","given":"Rhiannon P.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":837544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fralick, Gary L.","contributorId":288169,"corporation":false,"usgs":false,"family":"Fralick","given":"Gary L.","affiliations":[{"id":56161,"text":"wygf","active":true,"usgs":false}],"preferred":false,"id":837545,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Randall, Jill","contributorId":288170,"corporation":false,"usgs":false,"family":"Randall","given":"Jill","affiliations":[{"id":56161,"text":"wygf","active":true,"usgs":false}],"preferred":false,"id":837546,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kaiser, Rusty","contributorId":288171,"corporation":false,"usgs":false,"family":"Kaiser","given":"Rusty","affiliations":[{"id":56194,"text":"fs","active":true,"usgs":false}],"preferred":false,"id":837547,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thonhoff, Mark","contributorId":288174,"corporation":false,"usgs":false,"family":"Thonhoff","given":"Mark","affiliations":[{"id":6696,"text":"BLM","active":true,"usgs":false}],"preferred":false,"id":837548,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":837540,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Monteith, Kevin L.","contributorId":288177,"corporation":false,"usgs":false,"family":"Monteith","given":"Kevin L.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":837549,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70218491,"text":"70218491 - 2021 - Expanding the repertoire of electron acceptors for the anaerobic oxidation of methane in carbonates in the Atlantic and Pacific Ocean","interactions":[],"lastModifiedDate":"2021-09-15T13:30:53.980925","indexId":"70218491","displayToPublicDate":"2021-03-12T08:32:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1956,"text":"ISME Journal","active":true,"publicationSubtype":{"id":10}},"title":"Expanding the repertoire of electron acceptors for the anaerobic oxidation of methane in carbonates in the Atlantic and Pacific Ocean","docAbstract":"<p><span>Authigenic carbonates represent a significant microbial sink for methane, yet little is known about the microbiome responsible for the methane removal. We identify carbonate microbiomes distributed over 21 locations hosted by seven different cold seeps in the Pacific and Atlantic Oceans by carrying out a gene-based survey using 16S rRNA- and&nbsp;</span><i>mcr</i><span>A gene sequencing coupled with metagenomic analyses. Based on 16S rRNA gene amplicon analyses, these sites were dominated by bacteria affiliated to the Firmicutes, Alpha- and Gammaproteobacteria. ANME-1 and -2 archaeal clades were abundant in the carbonates yet their typical syntrophic partners, sulfate-reducing bacteria, were not significantly present. Based on&nbsp;</span><i>mcrA</i><span>&nbsp;amplicon analyses, the&nbsp;</span><i>Candidatus</i><span>&nbsp;Methanoperedens clades were also highly abundant. Our metagenome analysis indicated that methane oxidizers affiliated to the ANME-1 and -2, may be capable of performing complete methane- and potentially short-chain alkane oxidation independently using oxidized sulfur and nitrogen compounds as terminal electron acceptors. Gammaproteobacteria are hypothetically capable of utilizing oxidized nitrogen compounds and may be involved in syntrophy with methane-oxidizing archaea. Carbonate structures represent a window for a more diverse utilization of electron acceptors for anaerobic methane oxidation along the Atlantic and Pacific Margin.</span></p>","language":"English","publisher":"Nature Publications","doi":"10.1038/s41396-021-00918-w","usgsCitation":"Beckmann, S., Farag, I.F., Zhao, R., Christman, G., Prouty, N.G., and Biddle, J.F., 2021, Expanding the repertoire of electron acceptors for the anaerobic oxidation of methane in carbonates in the Atlantic and Pacific Ocean: ISME Journal, v. 15, p. 2523-2536, https://doi.org/10.1038/s41396-021-00918-w.","productDescription":"14 p.","startPage":"2523","endPage":"2536","ipdsId":"IP-119545","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":453105,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41396-021-00918-w","text":"Publisher Index Page"},{"id":385081,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","noUsgsAuthors":false,"publicationDate":"2021-03-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Beckmann, Sabrina","contributorId":224434,"corporation":false,"usgs":false,"family":"Beckmann","given":"Sabrina","email":"","affiliations":[],"preferred":false,"id":811203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farag, Ibrahim F.","contributorId":252951,"corporation":false,"usgs":false,"family":"Farag","given":"Ibrahim","email":"","middleInitial":"F.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":811204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhao, Rui","contributorId":252952,"corporation":false,"usgs":false,"family":"Zhao","given":"Rui","email":"","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":811205,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christman, Glenn","contributorId":252954,"corporation":false,"usgs":false,"family":"Christman","given":"Glenn","email":"","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":811206,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Prouty, Nancy G. 0000-0002-8922-0688 nprouty@usgs.gov","orcid":"https://orcid.org/0000-0002-8922-0688","contributorId":3350,"corporation":false,"usgs":true,"family":"Prouty","given":"Nancy","email":"nprouty@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":811207,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Biddle, Jennifer F.","contributorId":224433,"corporation":false,"usgs":false,"family":"Biddle","given":"Jennifer","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":811208,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70220543,"text":"70220543 - 2021 - Multiple-scale relationships between vegetation, the wildland–urban interface, and structure loss to wildfire in California","interactions":[],"lastModifiedDate":"2021-05-20T12:08:44.207613","indexId":"70220543","displayToPublicDate":"2021-03-12T08:13:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5678,"text":"Fire","active":true,"publicationSubtype":{"id":10}},"title":"Multiple-scale relationships between vegetation, the wildland–urban interface, and structure loss to wildfire in California","docAbstract":"<p><span>Recent increases in destructive wildfires are driving a need for empirical research documenting factors that contribute to structure loss. Existing studies show that fire risk is complex and varies geographically, and the role of vegetation has been especially difficult to quantify. Here, we evaluated the relative importance of vegetation cover at local (measured through the Normalized Difference Vegetation Index) and landscape (as measured through the Wildland–Urban Interface) scales in explaining structure loss from 2013 to 2018 in California—statewide and divided across three regions. Generally, the pattern of housing relative to vegetation better explained structure loss than local-scale vegetation amount, but the results varied regionally. This is likely because exposure to fire is a necessary first condition for structure survival, and sensitivity is only relevant once the fire reaches there. The relative importance of other factors such as long-term climatic variability, distance to powerlines, and elevation also varied among regions. These suggest that effective fire risk reduction strategies may need to account for multiple factors at multiple scales. The geographical variability in results also reinforces the notion that “one size does not fit all”. Local-scale empirical research on specific vegetation characteristics relative to structure loss is needed to inform the most effective customized plan.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/fire4010012","usgsCitation":"Syphard, A.D., Rustigian-Romsos, H., and Keeley, J., 2021, Multiple-scale relationships between vegetation, the wildland–urban interface, and structure loss to wildfire in California: Fire, v. 4, no. 1, 12, 15 p., https://doi.org/10.3390/fire4010012.","productDescription":"12, 15 p.","ipdsId":"IP-127664","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":453107,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fire4010012","text":"Publisher Index Page"},{"id":385764,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.21142578125,\n              42.01665183556825\n            ],\n            [\n              -124.47509765625,\n              40.49709237269567\n            ],\n            [\n              -123.79394531249999,\n              38.92522904714054\n            ],\n            [\n              -122.49755859375,\n              37.10776507118514\n            ],\n            [\n              -120.4541015625,\n              34.470335121217474\n            ],\n            [\n              -118.32275390624999,\n              33.779147331286474\n            ],\n            [\n              -117.24609374999999,\n              32.58384932565662\n            ],\n            [\n              -114.6533203125,\n              32.76880048488168\n            ],\n            [\n              -114.5654296875,\n              32.93492866908233\n            ],\n            [\n              -114.697265625,\n              33.15594830078649\n            ],\n            [\n              -114.521484375,\n              33.97980872872457\n            ],\n            [\n              -114.08203125,\n              34.252676117101515\n            ],\n            [\n              -114.43359375,\n              34.813803317113155\n            ],\n            [\n              -120.05859375,\n              39.07890809706475\n            ],\n            [\n              -119.99267578124999,\n              42.00032514831621\n            ],\n            [\n              -124.21142578125,\n              42.01665183556825\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"4","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-03-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Syphard, Alexandra D.","contributorId":8977,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":815956,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rustigian-Romsos, Heather","contributorId":258207,"corporation":false,"usgs":false,"family":"Rustigian-Romsos","given":"Heather","email":"","affiliations":[{"id":52235,"text":"Conservation Biology Institute, Corvallis, OR 97333, USA","active":true,"usgs":false}],"preferred":false,"id":815957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keeley, Jon 0000-0002-4564-6521","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":216485,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":815958,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70218782,"text":"sir20215014 - 2021 - Extending seasonal discharge records for streamgage sites on the North Fork Fortymile and Middle Fork Fortymile Rivers, Alaska, through water year 2020","interactions":[],"lastModifiedDate":"2021-03-15T11:42:02.813757","indexId":"sir20215014","displayToPublicDate":"2021-03-12T08:09:47","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5014","displayTitle":"Extending Seasonal Discharge Records for Streamgage Sites on the North Fork Fortymile and Middle Fork Fortymile Rivers, Alaska, through Water Year 2020","title":"Extending seasonal discharge records for streamgage sites on the North Fork Fortymile and Middle Fork Fortymile Rivers, Alaska, through water year 2020","docAbstract":"<p class=\"p1\">Daily mean discharge records are needed for management of selected streams in the Fortymile River Basin. The U.S. Geological Survey, in cooperation with the U.S. Bureau of Land Management, updated a technique for estimating seasonal (partial year) discharge at two short-record streamgage sites in the basin and evaluated the accuracy of the estimates. Daily mean discharge values were estimated for May 15–September 30, 1976–82 and 2006–18, for U.S. Geological Survey streamgage sites 15330000 (North Fork Fortymile River above Middle Fork near Franklin, Alaska) and 15331000 (Middle Fork Fortymile River near mouth near Chicken, Alaska). Relations between discharge for each study streamgage and an index streamgage on the main-stem Fortymile River (15348000, Fortymile River near Steele Creek, Alaska) for concurrent seasonal periods in 2019 and 2020 were developed using the maintenance of variance extension type 3 (MOVE.3) record extension technique. The MOVE.3 regressions were used to estimate daily mean discharges at the study streamgage sites for the selected season for the longer period of record of the index streamgage. Additionally, estimated records were generated from the regressions for the concurrent seasonal periods to evaluate the accuracy of the record extension techniques. The modified Nash-Sutcliffe efficiency coefficients for the estimated records were 0.53 for the North Fork Fortymile River (15330000) and 0.70 for the Middle Fork Fortymile River (15331000) streamgages.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215014","collaboration":"Prepared in cooperation with the U.S. Bureau of Land Management","usgsCitation":"Curran, J.H., 2021, Extending seasonal discharge records for streamgage sites on the North Fork Fortymile and Middle Fork Fortymile Rivers, Alaska, through water year 2020: U.S. Geological Survey Scientific Investigations Report 2021–5014, 11 p., https://doi.org/10.3133/sir20215014.","productDescription":"Report: v, 11 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-125266","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":384327,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5014/sir20215014.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5014"},{"id":384361,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VCAOEZ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Extended seasonal discharge records for selected streamgage sites in the Fortymile River Basin, Alaska, 1976-2020"},{"id":384326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5014/coverthb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"North Fork Fortymile River, Middle Fork Fortymile River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -146.46972656249997,\n              62.91523303947614\n            ],\n            [\n              -141.0205078125,\n              62.91523303947614\n            ],\n            [\n              -141.0205078125,\n              65.60387765860433\n            ],\n            [\n              -146.46972656249997,\n              65.60387765860433\n            ],\n            [\n              -146.46972656249997,\n              62.91523303947614\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/asc/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/asc/\">Alaska Science Center</a><br>U.S. Geological Survey<br>4210 University Drive<br>Anchorage, Alaska 99508</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Extended Daily Mean Discharge Records and Error Analysis</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2021-03-12","noUsgsAuthors":false,"publicationDate":"2021-03-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Curran, Janet H. 0000-0002-3899-6275 jcurran@usgs.gov","orcid":"https://orcid.org/0000-0002-3899-6275","contributorId":690,"corporation":false,"usgs":true,"family":"Curran","given":"Janet","email":"jcurran@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":811838,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70219011,"text":"70219011 - 2021 - Gulf Coast vicariance shapes phylogeographic history of a North American freshwater mussel species complex","interactions":[],"lastModifiedDate":"2023-07-07T13:41:13.625575","indexId":"70219011","displayToPublicDate":"2021-03-12T07:23:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Gulf Coast vicariance shapes phylogeographic history of a North American freshwater mussel species complex","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><h3 id=\"jbi14066-sec-0001-title\" class=\"article-section__sub-title section1\">Aim</h3><p>Freshwater mussels share habitat and are parasites of freshwater fishes during the larval life stage. Therefore, models of fish biogeography may also explain the historical biogeography of freshwater mussels. We tested this assumption using predictions of three biogeographic models constructed for northern Gulf of Mexico drainages on a freshwater mussel species complex. Specifically, we tested (1) if speciation was due to vicariant events of fluctuating sea levels that separated lineages east‐west of the Mobile Basin (Central Gulf Coast speciation hypothesis), (2) if the timing of divergences occurred 8.5–3.5 MYA (Gulf Coast allopatric speciation model) and (3) if diversification in Mississippi River populations was recent and for evidence of population increase consistent with range expansion into northern deglaciated regions (Pleistocene glaciation model).</p><h3 id=\"jbi14066-sec-0002-title\" class=\"article-section__sub-title section1\">Location</h3><p>Eastern North America.</p><h3 id=\"jbi14066-sec-0003-title\" class=\"article-section__sub-title section1\">Taxon</h3><p>Freshwater mussels (Bivalvia: Unionidae),<span>&nbsp;</span><i>Lampsilis teres</i><span>&nbsp;</span>and<span>&nbsp;</span><i>L. floridensis</i>.</p><h3 id=\"jbi14066-sec-0004-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We collected 249 specimens from 73 localities across the group's distribution. We used three molecular markers (COI, NDI &amp; ITSI) to conduct time calibrated Bayesian phylogenetic analyses, phylogeographic analyses (AMOVA &amp; SAMOVA) and demographic analyses including Bayesian skyline plots.</p><h3 id=\"jbi14066-sec-0005-title\" class=\"article-section__sub-title section1\">Results</h3><p><i>Lampsilis teres</i><span>&nbsp;</span>and<span>&nbsp;</span><i>L. floridensis</i><span>&nbsp;</span>are allopatric species whose distributions meet at the eastern edge of the Mobile Basin. Speciation was estimated to occur in the late Miocene. Populations from isolated river systems surrounding the Gulf of Mexico are almost all monophyletic. Mississippi drainage samples formed a shallow clade with recent diversification and showed evidence of recent population expansion.</p><h3 id=\"jbi14066-sec-0006-title\" class=\"article-section__sub-title section1\">Main conclusions</h3><p>The historical biogeography of the<span>&nbsp;</span><i>L. teres</i><span>&nbsp;</span>species complex is broadly consistent with tested ichthyofaunal models. The timing of speciation and intraspecific divergences correspond to low sea‐level events suggesting that Gulf Coast sea‐level fluctuations are responsible for dispersal (sea‐level recession) and subsequent cladogenesis (sea‐level inundation). Consistent with numerous other freshwater studies, we found the Mobile Basin to be a suture zone, which may be due to the narrow, offshore continental shelf.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/jbi.14066","usgsCitation":"Keogh, S.M., Johnson, N., Williams, J.D., Randklev, C.R., and Simons, A., 2021, Gulf Coast vicariance shapes phylogeographic history of a North American freshwater mussel species complex: Journal of Biogeography, v. 48, no. 5, p. 1138-1152, https://doi.org/10.1111/jbi.14066.","productDescription":"15 p.; Data Release","startPage":"1138","endPage":"1152","ipdsId":"IP-123241","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":384498,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418746,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LI4LKX","text":"Molecular data to investigate phylogeographic patterns, species boundaries, and demographic history of a North American freshwater mussel species complex (Bivalvia: Unionidae)","linkFileType":{"id":5,"text":"html"}}],"volume":"48","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-03-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Keogh, Sean M.","contributorId":255502,"corporation":false,"usgs":false,"family":"Keogh","given":"Sean","email":"","middleInitial":"M.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":812455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Nathan 0000-0001-5167-1988","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":216879,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":812456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, James D.","contributorId":17690,"corporation":false,"usgs":false,"family":"Williams","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":812457,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Randklev, Charles R.","contributorId":202530,"corporation":false,"usgs":false,"family":"Randklev","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":812458,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Simons, Andrew","contributorId":255504,"corporation":false,"usgs":false,"family":"Simons","given":"Andrew","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":812459,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70220314,"text":"70220314 - 2021 - Potential use of the benthic foraminifers Bulimina denudata and Eggerelloides advenus in marine sediment toxicity testing","interactions":[],"lastModifiedDate":"2021-05-06T11:42:28.648048","indexId":"70220314","displayToPublicDate":"2021-03-12T07:05:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Potential use of the benthic foraminifers Bulimina denudata and Eggerelloides advenus in marine sediment toxicity testing","docAbstract":"<p><span>The benthic foraminifers&nbsp;</span><span class=\"html-italic\">Bulimina denudata</span><span>&nbsp;and&nbsp;</span><span class=\"html-italic\">Eggerelloides advenus</span><span>&nbsp;are commonly abundant in offshore regions in the Pacific Ocean, especially in waste-discharge sites. The relationship between their abundance and standard macrofaunal sediment toxicity tests (amphipod survival and sea urchin fertilization) as well as sediment chemistry analyte measurements were determined for sediments collected in 1997 in Santa Monica Bay, California, USA, an area impacted by historical sewage input from the Hyperion Outfall primarily since the late 1950s. Very few surface samples proved to be contaminated based on either toxicity or chemistry tests and the abundance of&nbsp;</span><span class=\"html-italic\">B. denudata</span><span>&nbsp;did not correlate with any of these. The abundance of&nbsp;</span><span class=\"html-italic\">E. advenus</span><span>&nbsp;also did not correlate with toxicity, but positively correlated with total solids and negatively correlated with arsenic, beryllium, chromium, lead, mercury, nickel, zinc, iron, and TOC. In contrast, several downcore samples proved to be contaminated as indicated by both toxicity and chemistry data. The abundance of&nbsp;</span><span class=\"html-italic\">B. denudata</span><span>&nbsp;positively correlated with amphipod survival and negatively correlated with arsenic, cadmium, unionized ammonia, and TOC;&nbsp;</span><span class=\"html-italic\">E. advenus</span><span>&nbsp;negatively correlated with sea urchin fertilization success as well as beryllium, cadmium, and total PCBs. As&nbsp;</span><span class=\"html-italic\">B. denudata</span><span>&nbsp;and&nbsp;</span><span class=\"html-italic\">E. advenus</span><span>&nbsp;are tolerant of polluted sediments and their relative abundances appear to track those of macrofaunal toxicity tests, their use as cost- and time-effective marine sediment toxicity tests may have validity and should be further investigated.&nbsp;</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w13060775","usgsCitation":"McGann, M., 2021, Potential use of the benthic foraminifers Bulimina denudata and Eggerelloides advenus in marine sediment toxicity testing: Water, v. 13, no. 6, 775, 33 p., https://doi.org/10.3390/w13060775.","productDescription":"775, 33 p.","ipdsId":"IP-117658","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":453114,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w13060775","text":"Publisher Index Page"},{"id":385443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"California","otherGeospatial":"Los  Angeles coast","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.58343505859374,\n              34.14590795200977\n            ],\n            [\n              -118.85009765625,\n              33.708347493688414\n            ],\n            [\n              -118.23486328125,\n              33.458942753687644\n            ],\n            [\n              -117.77618408203124,\n              33.56199537293026\n            ],\n            [\n              -118.28979492187499,\n              33.916013113401696\n            ],\n            [\n              -118.98468017578125,\n              34.15045403191448\n            ],\n            [\n              -119.34997558593749,\n              34.35023911062779\n            ],\n            [\n              -119.58343505859374,\n              34.14590795200977\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-03-12","publicationStatus":"PW","contributors":{"authors":[{"text":"McGann, Mary 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":169540,"corporation":false,"usgs":true,"family":"McGann","given":"Mary","email":"mmcgann@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":815133,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70222571,"text":"70222571 - 2021 - Extreme-event magnetic storm probabilities derived from rank statistics of historical Dst intensities for solar cycles 14-24","interactions":[],"lastModifiedDate":"2021-08-05T12:07:42.766418","indexId":"70222571","displayToPublicDate":"2021-03-12T07:04:10","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"Extreme-event magnetic storm probabilities derived from rank statistics of historical Dst intensities for solar cycles 14-24","docAbstract":"<p><span>A compilation is made of the largest and second-largest magnetic-storm-maximum intensities, −</span><i>Dst</i><sub>1</sub><span>&nbsp;and −</span><i>Dst</i><sub>2</sub><span>, for solar cycles 14–24 (1902–2016) by sampling Oulu&nbsp;</span><i>Dcx</i><span>&nbsp;for cycles 19–24, using published −</span><i>Dst</i><sub><i>m</i></sub><span>&nbsp;values for 4 intense storms in cycles 14, 15, and 18 (1903, 1909, 1921, 1946), and calculating 15 new storm-maximum −</span><i>Dst</i><sub><i>m</i></sub><span>&nbsp;values (reported here) for cycles 14–18. Three different models are fitted to the cycle-ranked −</span><i>Dst</i><sub>1</sub><span>&nbsp;and −</span><i>Dst</i><sub>2</sub><span>&nbsp;values using a maximum-likelihood algorithm: A Gumbel model, an unconstrained Generalized-Extreme-Value model, and a Weibull model constrained to have a physically justified maximum storm intensity of −</span><i>Dst</i><sub><i>m</i></sub><span>&nbsp;=&nbsp;2500&nbsp;nT. All three models are good descriptions of the data. Since the best model is not clearly revealed with standard statistical tests, inference is precluded of the source process giving rise to storm-maximum −</span><i>Dst</i><sub><i>m</i></sub><span>&nbsp;values. Of the three candidate models, the constrained Weibull gives the lowest superstorm occurrence probabilities. Using the compiled data and the constrained Weibull model, a once-per-century storm intensity is estimated to be −</span><i>Dst</i><sub>1</sub><span>&nbsp;=&nbsp;663&nbsp;nT, with a bootstrap 68% confidence interval of [497, 694] nT. Similarly, the probability that a future storm will have an intensity exceeding that of the March 1989 superstorm, −</span><i>Dst</i><sub><i>m</i></sub><span>&nbsp;&gt; 565&nbsp;nT, is 0.246 per cycle with a 68% confidence interval of [0.140, 0.311] per cycle. Noting (possibly slight) ambiguity in the rankings of storm intensities, using the same methods, but storms more intense than those identified for cycles 14–16, would yield a higher once-per-century intensity and a higher probability for a −</span><i>Dst</i><sub><i>m</i></sub><span>&nbsp;&gt;&nbsp;565&nbsp;nT storm.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020SW002579","usgsCitation":"Love, J.J., 2021, Extreme-event magnetic storm probabilities derived from rank statistics of historical Dst intensities for solar cycles 14-24: Space Weather, v. 19, no. 4, e2020SW002579, 25 p., https://doi.org/10.1029/2020SW002579.","productDescription":"e2020SW002579, 25 p.","ipdsId":"IP-124185","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":490073,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020sw002579","text":"Publisher Index Page"},{"id":387701,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820608,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70219433,"text":"70219433 - 2021 - Eastward expansion of Round Goby in New York: Assessment of detection methods and current range","interactions":[],"lastModifiedDate":"2021-04-06T12:01:57.537653","indexId":"70219433","displayToPublicDate":"2021-03-12T06:55:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Eastward expansion of Round Goby in New York: Assessment of detection methods and current range","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>The Round Goby<span>&nbsp;</span><i>Neogobius melanostomus</i><span>&nbsp;</span>has spread rapidly around the Great Lakes region since its introduction to North America in 1990. In 2014, a specimen was captured in the New York State Canal System west of Utica, prompting concerns that Round Goby would soon reach the ecologically and economically valuable watersheds of Lake Champlain and the Hudson River estuary. The establishment of Round Goby populations elsewhere has been linked to a number of negative ecological consequences, yet methods for monitoring the invasion front of this species remain limited. The objectives of this study were to assess the current distribution of Round Goby in central New York and to determine the most effective methods for monitoring the invasion front. This was achieved by concurrently using benthic trawling, seining, minnow traps, and environmental DNA (eDNA) twice annually from 2016 to 2019 at 12 sites on the canal system between Oneida Lake and the Hudson River. Of the three traditional gear types, benthic trawling was the most effective method and captured Round Goby as far east as Utica by 2019. This finding suggests only minimal eastward expansion of Round Goby occurred between 2014 and 2019. Round Goby DNA was detected in water samples during all surveys in which individuals were captured with trawling, and the estimated concentration of DNA explained 69% of the variability in trawl catch. At multiple study sites, Round Goby DNA was identified during consecutive surveys before Round Goby were first captured with trawling. This suggests that in lotic waters, eDNA has the potential to forecast or serve as a sentinel for the expansion of Round Goby to new locations. Our results demonstrate the importance of using eDNA in a repeated sampling framework and supplementing eDNA sampling with some level of effort with traditional sampling methods.</p></div></div>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10290","usgsCitation":"George, S.D., Baldigo, B.P., Rees, C., Bartron, M.L., and Winterhalter, D., 2021, Eastward expansion of Round Goby in New York: Assessment of detection methods and current range: Transactions of the American Fisheries Society, v. 150, no. 2, p. 258-273, https://doi.org/10.1002/tafs.10290.","productDescription":"16 p.","startPage":"258","endPage":"273","ipdsId":"IP-119185","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":453119,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10290","text":"Publisher Index Page"},{"id":436459,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W9TMPW","text":"USGS data release","linkHelpText":"Environmental DNA (eDNA) and Fish Capture Data from Round Goby Screening Surveys on the Eastern Erie Canal, New York (ver. 2.0, May 2024)"},{"id":384884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.251953125,\n              40.245991504199026\n            ],\n            [\n              -74.619140625,\n              40.245991504199026\n            ],\n            [\n              -74.619140625,\n              49.781264058178344\n            ],\n            [\n              -93.251953125,\n              49.781264058178344\n            ],\n            [\n              -93.251953125,\n              40.245991504199026\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"150","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-03-12","publicationStatus":"PW","contributors":{"authors":[{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rees, Christopher B.","contributorId":196308,"corporation":false,"usgs":false,"family":"Rees","given":"Christopher B.","affiliations":[],"preferred":false,"id":813543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bartron, Meredith L.","contributorId":149109,"corporation":false,"usgs":false,"family":"Bartron","given":"Meredith","email":"","middleInitial":"L.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false},{"id":26874,"text":"USFWS, Lamar, PA","active":true,"usgs":false}],"preferred":false,"id":813544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Winterhalter, Dylan R. 0000-0003-1774-8034","orcid":"https://orcid.org/0000-0003-1774-8034","contributorId":251765,"corporation":false,"usgs":true,"family":"Winterhalter","given":"Dylan R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813545,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70220895,"text":"70220895 - 2021 - Reduced quality and synchronous collapse of forage species disrupts trophic transfer during a prolonged marine heatwave","interactions":[],"lastModifiedDate":"2021-05-28T19:57:37.603265","indexId":"70220895","displayToPublicDate":"2021-03-11T14:47:21","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Reduced quality and synchronous collapse of forage species disrupts trophic transfer during a prolonged marine heatwave","docAbstract":"The Gulf of Alaska forage fish community includes a few key species that differ markedly in their timing of spawning, somatic growth and lipid storage, and in their migration behavior. This diversity in life history strategies facilitates resilience in marine food webs because it buffers predators against the naturally high variance in abundance of pelagic forage fish populations by decreasing the likelihood that all species will be scarce at the same time. During the prolonged North Pacific marine heatwave of 2014-2016, the availability and quality of at least three key forage species with different life history strategies were reduced simultaneously in the system. Capelin and sand lance occurrence in predator diets declined abruptly, and Prince William Sound herring spawning biomass declined to historically low levels. Biomass of euphausiids was also reduced, in part due to the loss of a cold-water species. Changes in age structure, growth, and energy content of capelin, sand lance, and herring were also associated with warming during the heatwave, but not all species responded in the same way. For example, spawning capelin grew faster and matured at a younger age but were shorter in length than usual, while sand lance in Prince William Sound experienced anomalously low growth rates and lipid storage in 2015-2016. Changes in forage fish populations had immediate impacts on predator populations in 2015-2016, when seabirds and marine mammals experienced shifts in distribution, mass mortality, and reproductive failures in the Gulf of Alaska. In contrast, copepod abundance increased on the shelf and in some coastal regions during the heatwave, suggesting that food availability was not a primary factor limiting forage fish populations at this time. The  reduced quality and collapse of multiple forage fish populations reduced the efficiency of energy transfer through the middle trophic level of pelagic food webs, disrupting energy flow to piscivorous pelagic predators and causing abrupt and extreme reductions in their numbers and productivity.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"The Pacific marine heatwave: Monotoring during a major perturbation in the Gulf of Alaska","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"GulfWatch Alaska","usgsCitation":"Arimitsu, M.L., Piatt, J., Hatch, S., Suryan, R., Batten, S., Bishop, M., Campbell, R., Coletti, H., Cushing, D., Gorman, K., Haught, S., Hopcroft, R., Kuletz, K., Marsteller, C.E., McKinstry, C., McGowan, D., Moran, J., Pegau, R.S., Schaefer, A., Schoen, S.K., Straley, J., and von Biela, V.R., 2021, Reduced quality and synchronous collapse of forage species disrupts trophic transfer during a prolonged marine heatwave, chap. <i>of</i> The Pacific marine heatwave: Monotoring during a major perturbation in the Gulf of Alaska, p. 3-1-3-27.","productDescription":"27 p.","startPage":"3-1","endPage":"3-27","ipdsId":"IP-114151","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":386022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":386015,"type":{"id":15,"text":"Index Page"},"url":"https://gulfwatchalaska.org/resources/reports/science-synthesis-reports/"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -153.45703125,\n              56.92099675839107\n            ],\n            [\n              -135.87890625,\n              57.231502991478926\n            ],\n            [\n              -142.3828125,\n              60.108670463036\n            ],\n            [\n              -147.216796875,\n              61.14323525084058\n            ],\n            [\n              -151.4794921875,\n              59.489726035537075\n            ],\n            [\n              -152.7978515625,\n              58.35563036280964\n            ],\n            [\n              -153.45703125,\n              56.92099675839107\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":816618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Piatt, John F. 0000-0002-4417-5748","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":244053,"corporation":false,"usgs":true,"family":"Piatt","given":"John F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":816619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hatch, Scott","contributorId":258853,"corporation":false,"usgs":false,"family":"Hatch","given":"Scott","affiliations":[{"id":52319,"text":"ISRC","active":true,"usgs":false}],"preferred":false,"id":816628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suryan, Rob","contributorId":258845,"corporation":false,"usgs":false,"family":"Suryan","given":"Rob","affiliations":[{"id":52314,"text":"NOAA NMFS Auke Bay Lab","active":true,"usgs":false}],"preferred":false,"id":816620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Batten, Sonia","contributorId":258846,"corporation":false,"usgs":false,"family":"Batten","given":"Sonia","affiliations":[{"id":52316,"text":"Marine Biological Association","active":true,"usgs":false}],"preferred":false,"id":816621,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bishop, Mary Anne","contributorId":258847,"corporation":false,"usgs":false,"family":"Bishop","given":"Mary Anne","affiliations":[{"id":13600,"text":"Prince William Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":816622,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Campbell, Rob","contributorId":258848,"corporation":false,"usgs":false,"family":"Campbell","given":"Rob","affiliations":[{"id":13600,"text":"Prince William Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":816623,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coletti, Heather","contributorId":258849,"corporation":false,"usgs":false,"family":"Coletti","given":"Heather","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":816624,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cushing, Dan","contributorId":258850,"corporation":false,"usgs":false,"family":"Cushing","given":"Dan","affiliations":[{"id":52317,"text":"Pole Star","active":true,"usgs":false}],"preferred":false,"id":816625,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gorman, Kristen","contributorId":258851,"corporation":false,"usgs":false,"family":"Gorman","given":"Kristen","affiliations":[{"id":13600,"text":"Prince William Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":816626,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Haught, 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Washington","active":true,"usgs":false}],"preferred":false,"id":816633,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Moran, John","contributorId":258858,"corporation":false,"usgs":false,"family":"Moran","given":"John","affiliations":[{"id":52314,"text":"NOAA NMFS Auke Bay Lab","active":true,"usgs":false}],"preferred":false,"id":816634,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Pegau, R. Scott","contributorId":258859,"corporation":false,"usgs":false,"family":"Pegau","given":"R.","email":"","middleInitial":"Scott","affiliations":[{"id":13600,"text":"Prince William Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":816635,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Schaefer, Anne","contributorId":258860,"corporation":false,"usgs":false,"family":"Schaefer","given":"Anne","affiliations":[{"id":13600,"text":"Prince William Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":816636,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Schoen, Sarah K. 0000-0002-5685-5185 sschoen@usgs.gov","orcid":"https://orcid.org/0000-0002-5685-5185","contributorId":5136,"corporation":false,"usgs":true,"family":"Schoen","given":"Sarah","email":"sschoen@usgs.gov","middleInitial":"K.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":816637,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Straley, Jan","contributorId":258861,"corporation":false,"usgs":false,"family":"Straley","given":"Jan","affiliations":[{"id":16298,"text":"University of Alaska Southeast","active":true,"usgs":false}],"preferred":false,"id":816638,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"von Biela, Vanessa R. 0000-0002-7139-5981 vvonbiela@usgs.gov","orcid":"https://orcid.org/0000-0002-7139-5981","contributorId":3104,"corporation":false,"usgs":true,"family":"von Biela","given":"Vanessa","email":"vvonbiela@usgs.gov","middleInitial":"R.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":816639,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}}
,{"id":70237213,"text":"70237213 - 2021 - Piping plovers demonstrate regional differences in nesting habitat selection patterns along the U.S. Atlantic coast","interactions":[],"lastModifiedDate":"2022-10-04T13:27:41.941655","indexId":"70237213","displayToPublicDate":"2021-03-11T08:15:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Piping plovers demonstrate regional differences in nesting habitat selection patterns along the U.S. Atlantic coast","docAbstract":"<p><span>Habitat studies that encompass a large portion of a species’ geographic distribution can explain characteristics that are either consistent or variable, further informing inference from more localized studies and improving management successes throughout the range. We identified landscape characteristics at Piping Plover nests at 21 sites distributed from Massachusetts to North Carolina and compared habitat selection patterns among the three designated U.S. recovery units (New England, New York–New Jersey, and Southern). Geomorphic setting, substrate type, and vegetation type and density were determined in situ at 928 Piping Plover nests (hereafter, used resource units) and 641 random points (available resource units). Elevation, beach width, Euclidean distance to ocean shoreline, and least-cost path distance to low-energy shorelines with moist substrates (commonly used as foraging habitat) were associated with used and available resource units using remotely sensed spatial data. We evaluated multivariate differences in habitat selection patterns by comparing recovery unit-specific Bayesian networks. We then further explored individual variables that drove disparities among Bayesian networks using resource selection ratios for categorical variables and Welch’s unequal variances t-tests for continuous variables. We found that relationships among variables and their connections to habitat selection were similar among recovery units, as seen in commonalities in Bayesian network structures. Furthermore, nesting Piping Plovers consistently selected mixed sand and shell, gravel, or cobble substrates as well as areas with sparse or no vegetation, irrespective of recovery unit. However, we observed significant differences among recovery units in the elevations, distances to ocean, and distances to low-energy shorelines of used resource units. Birds also exhibited increased selectivity for overwash habitats and for areas with access to low-energy shorelines along a latitudinal gradient from north to south. These results have important implications for conservation and management, including assessment of shoreline stabilization and habitat restoration planning as well as forecasting effects of climate change.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3418","usgsCitation":"Zeigler, S.L., Gutierrez, B.T., Hecht, A., Plant, N., and Sturdivant, E., 2021, Piping plovers demonstrate regional differences in nesting habitat selection patterns along the U.S. Atlantic coast: Ecosphere, v. 12, no. 3, e03418, 21 p., https://doi.org/10.1002/ecs2.3418.","productDescription":"e03418, 21 p.","ipdsId":"IP-123170","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":453120,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3418","text":"Publisher Index Page"},{"id":407856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Delaware, Maryland, Massachusetts, new Jersey, New York, North Carolina, Rhode Island, Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -78.06884765624999,\n              33.7243396617476\n            ],\n            [\n              -75.47607421875,\n              34.92197103616377\n            ],\n            [\n              -75.6298828125,\n              37.07271048132943\n            ],\n            [\n              -73.95996093749999,\n              39.87601941962116\n            ],\n            [\n              -73.54248046875,\n              40.54720023441049\n            ],\n            [\n 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Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":853647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gutierrez, Benjamin T. 0000-0002-1879-7893 bgutierrez@usgs.gov","orcid":"https://orcid.org/0000-0002-1879-7893","contributorId":2924,"corporation":false,"usgs":true,"family":"Gutierrez","given":"Benjamin","email":"bgutierrez@usgs.gov","middleInitial":"T.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":853648,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hecht, Anne","contributorId":297201,"corporation":false,"usgs":false,"family":"Hecht","given":"Anne","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":853649,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plant, Nathaniel 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,{"id":70231209,"text":"70231209 - 2021 - A study of marine temperature variations in the northern Gulf of Alaska across years of marine heatwaves and cold spells","interactions":[],"lastModifiedDate":"2022-05-03T13:37:01.222443","indexId":"70231209","displayToPublicDate":"2021-03-11T08:10:39","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":10741,"text":"Gulf Watch Alaska Long-Term Monitoring Program Synthesis Report","active":true,"publicationSubtype":{"id":3}},"chapter":"1","title":"A study of marine temperature variations in the northern Gulf of Alaska across years of marine heatwaves and cold spells","docAbstract":"<p>We use over 100 <i>in situ</i> and remotely sensed temperature datasets to investigate thermal variability within and across the intertidal nearshore, coastal and offshore waters of the northern Gulf of Alaska. For the years 1970 through 2019 we document a warming trend of 0.24±0.10 °C per decade for the coastal northern shelf (0-250 m depth average) and a Gulf-wide sea surface temperature (SST) trend of 0.25±0.11 °C per decade. The Gulf-wide SST trend in the last halfcentury is more than twice that of the 0.11±0.003 °C warming rate computed for 1900-2019. Decorrelation length scales vary regionally and correlation of synoptic scale fluctuations (less than one month) between two stations rapidly degrades with increasing station distance, accounting for less than 10% of the covariance for separations exceeding 100 km. In contrast, stations separated by as much as 500 km retain 50% of their covariance in common for seasonal and sub-seasonal fluctuations. While satellite-based measures often capture most of the daily SST anomaly in coastal and offshore waters, a significant portion of the variance (30-40%) can remain unresolved, even exceeding 75% in the nearshore realm. Similarly, the North Pacific and Gulf of Alaska leading modes of SST variability leave large fractions (25-50%) of the subseasonal thermal variance unresolved. These evaluations show the importance of in situ temperature records for studies that seek to understand mechanistic responses of marine organisms to habitat variability at biologically important time and space scales. We find that near-bottom temperature anomalies on the outer shelf vary inversely with surface temperatures and with near-bottom salinity, suggesting that thermal anomalies are also linked with nutrient flux anomalies. A case study of the recent Pacific marine heatwave and transition out of preceding cool years shows that the northern Gulf of Alaska surface temperatures (0-50 m) were elevated from 2014 to 2019 relative to the long-term record. Coastal temperatures warmed contemporaneously with offshore waters through the 2013 calendar year. In contrast, deep inner shelf waters (200-250 m) exhibited delayed warming relative to the surface and relative to deep waters offshore at the same depth. While offshore surface waters cooled from early 2014 into 1-2 Science Synthesis Final Report Gulf Watch Alaska, 2021 early 2016, the shelf continued to warm over this time as the effects of local air-sea and advective heat fluxes continued to permeate across the northern Gulf. These results highlight the importance of different heating mechanisms for surface and near-bottom waters across the northern Gulf of Alaska.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"The Pacific marine heatwave: Monotoring during a major perturbation in the Gulf of Alaska","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Exxon Valdez Oil Spill Trustee Council","usgsCitation":"Danielson, S.L., Hennon, T.D., Monson, D., Suryan, R.M., Campbell, R.W., Baird, S.J., Holderied, K., and Weingartner, T., 2021, A study of marine temperature variations in the northern Gulf of Alaska across years of marine heatwaves and cold spells: Gulf Watch Alaska Long-Term Monitoring Program Synthesis Report, 56 p.","productDescription":"56 p.","startPage":"1-1","endPage":"1-56","ipdsId":"IP-119985","costCenters":[{"id":116,"text":"Alaska Science Center Biology 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L.","contributorId":256682,"corporation":false,"usgs":false,"family":"Danielson","given":"Seth","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":842031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hennon, Tyler D.","contributorId":291317,"corporation":false,"usgs":false,"family":"Hennon","given":"Tyler","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":842032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monson, Daniel 0000-0002-4593-5673 dmonson@usgs.gov","orcid":"https://orcid.org/0000-0002-4593-5673","contributorId":196670,"corporation":false,"usgs":true,"family":"Monson","given":"Daniel","email":"dmonson@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":842033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suryan, Rob M.","contributorId":291318,"corporation":false,"usgs":false,"family":"Suryan","given":"Rob","email":"","middleInitial":"M.","affiliations":[{"id":62685,"text":"Alaska Fisheries Science Center, NOAA","active":true,"usgs":false}],"preferred":false,"id":842034,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell, Rob W.","contributorId":251805,"corporation":false,"usgs":false,"family":"Campbell","given":"Rob","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":842035,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baird, Steven J.","contributorId":12375,"corporation":false,"usgs":false,"family":"Baird","given":"Steven","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":842036,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Holderied, Kristine","contributorId":291319,"corporation":false,"usgs":false,"family":"Holderied","given":"Kristine","affiliations":[{"id":62686,"text":"Kasitsna Bay Laboratory, NOAA","active":true,"usgs":false}],"preferred":false,"id":842037,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Weingartner, Thomas","contributorId":291321,"corporation":false,"usgs":false,"family":"Weingartner","given":"Thomas","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":842038,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70225526,"text":"70225526 - 2021 - Pore water exchange-driven inorganic carbon export from intertidal salt marshes","interactions":[],"lastModifiedDate":"2021-10-20T13:06:17.578828","indexId":"70225526","displayToPublicDate":"2021-03-11T08:02:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Pore water exchange-driven inorganic carbon export from intertidal salt marshes","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Respiration in intertidal salt marshes generates dissolved inorganic carbon (DIC) that is exported to the coastal ocean by tidal exchange with the marsh platform. Understanding the link between physical drivers of water exchange and chemical flux is a key to constraining coastal wetland contributions to regional carbon budgets. The spatial and temporal (seasonal, annual) variability of marsh pore water exchange and DIC export was assessed from a microtidal salt marsh (Sage Lot Pond, Massachusetts). Spatial variability was constrained from<span>&nbsp;</span><sup>224</sup>Ra :<span>&nbsp;</span><sup>228</sup>Th disequilibria across two hydrologic units within the marsh sediments. Disequilibrium between the more soluble<span>&nbsp;</span><sup>224</sup>Ra and its sediment-bound parent<span>&nbsp;</span><sup>228</sup>Th reveals significant pore water exchange in the upper 5 cm of the marsh surface (0–36 L m<sup>−2</sup><span>&nbsp;</span>d<sup>−1</sup>) that is most intense in low marsh elevation zones, driven by tidal overtopping. Surficial sediment DIC transport ranges from 0.0 to 0.7 g C m<sup>−2</sup><span>&nbsp;</span>d<sup>−1</sup>. The sub-surface sediment horizon intersected by mean low tide was disproportionately impacted by tidal pumping (20–80 L m<sup>−2</sup><span>&nbsp;</span>d<sup>−1</sup>) and supplied a seasonal DIC flux of 1.7–5.4 g C m<sup>−2</sup><span>&nbsp;</span>d<sup>−1</sup>. Export exceeded 10 g C m<sup>−2</sup><span>&nbsp;</span>d<sup>−1</sup><span>&nbsp;</span>for another marsh unit, demonstrating that fluxes can vary substantially across salt marshes under similar conditions within the same estuary. Seasonal and annual variability in marsh pore water exchange, constrained from tidal time-series of radium isotopes, was driven in part by variability in mean sea level. Rising sea levels will further inundate high marsh elevation zones, which may lead to greater DIC export.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/lno.11721","usgsCitation":"Tamborski, J., Eagle, M.J., Kurylyk, B.L., Kroeger, K.D., Wang, Z., Henderson, P., and Charette, M., 2021, Pore water exchange-driven inorganic carbon export from intertidal salt marshes: Limnology and Oceanography, v. 66, no. 5, p. 1774-1792, https://doi.org/10.1002/lno.11721.","productDescription":"19 p.","startPage":"1774","endPage":"1792","ipdsId":"IP-124471","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"links":[{"id":453122,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/lno.11721","text":"External Repository"},{"id":436460,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MXLUZ1","text":"USGS data release","linkHelpText":"Geochemical data supporting investigation of solute and particle cycling and fluxes from two tidal wetlands on the south shore of Cape Cod, Massachusetts, 2012-19 (ver. 2.0, October 2022)"},{"id":390659,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Waquoit Bay National Estuarine Research Reserve","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -70.70320129394531,\n              41.42470861986892\n            ],\n            [\n              -70.38253784179688,\n              41.42470861986892\n            ],\n            [\n              -70.38253784179688,\n              41.6195489884308\n            ],\n            [\n              -70.70320129394531,\n              41.6195489884308\n            ],\n            [\n              -70.70320129394531,\n              41.42470861986892\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"66","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Tamborski, Joseph","contributorId":267856,"corporation":false,"usgs":false,"family":"Tamborski","given":"Joseph","email":"","affiliations":[{"id":55518,"text":"Department of Marine Chemistry & Geochemistry, Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":825433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eagle, Meagan J. 0000-0001-5072-2755 meagle@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":242890,"corporation":false,"usgs":true,"family":"Eagle","given":"Meagan","email":"meagle@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":825434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kurylyk, Barret L.","contributorId":176296,"corporation":false,"usgs":false,"family":"Kurylyk","given":"Barret","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":825435,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":825436,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Zhaoihui","contributorId":267857,"corporation":false,"usgs":false,"family":"Wang","given":"Zhaoihui","email":"","affiliations":[{"id":55518,"text":"Department of Marine Chemistry & Geochemistry, Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":825437,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Henderson, Paul","contributorId":267858,"corporation":false,"usgs":false,"family":"Henderson","given":"Paul","email":"","affiliations":[{"id":55518,"text":"Department of Marine Chemistry & Geochemistry, Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":825438,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Charette, Matthew","contributorId":247619,"corporation":false,"usgs":false,"family":"Charette","given":"Matthew","affiliations":[{"id":49599,"text":"Woods Hole Oceanographic Institution, Woods Hole, USA","active":true,"usgs":false}],"preferred":false,"id":825439,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70223211,"text":"70223211 - 2021 - Remote sensing inventory and geospatial analysis of brick kilns and clay quarrying in Kabul, Afghanistan","interactions":[],"lastModifiedDate":"2021-08-18T12:56:55.65441","indexId":"70223211","displayToPublicDate":"2021-03-11T07:54:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5207,"text":"Minerals","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing inventory and geospatial analysis of brick kilns and clay quarrying in Kabul, Afghanistan","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">Reconstruction and urban development in Kabul, Afghanistan, has prompted vast expansion of the clay quarrying and brick making industry. This study identified the extent and distribution of clay quarrying and brick kilns in the greater Kabul area between 1965 and 2018. Very high-resolution satellite imagery was interpreted to quantify and characterize the type, number, and location of brick kilns for 1965, 2004, 2011, and 2018. Geospatial analysis of kilns together with geologic data and the results of hyperspectral image analysis yielded information regarding the extent of relevant mineral resources. Finally, kernel density analysis of kiln locations for each date called attention to their shifting spatial distribution. The study found that the clay quarrying and brick making industry has expanded exponentially. The type of kilns has transitioned from artisanal style clamp kilns to small-scale Bull’s Trench Kilns (BTK), and ultimately to Fixed Chimney Bull’s Trench Kilns (FCBTK). While quarrying has occurred entirely within quaternary windblown loess and clay deposits, artisanal clamp kilns were located in fine sediments containing montmorillonite and FCBTKs have developed in sediments containing calcite and muscovite. The study’s inventory of kilns was then used to estimate kiln workforce at 27,500 workers and production at 1.579 billion bricks per year.<span>&nbsp;</span></div>","language":"English","publisher":"MDPI","doi":"10.3390/min11030296","usgsCitation":"DeWitt, J.D., Chirico, P.G., Alessi, M., and Boston, K.M., 2021, Remote sensing inventory and geospatial analysis of brick kilns and clay quarrying in Kabul, Afghanistan: Minerals, v. 3, no. 11, p. 296-316, https://doi.org/10.3390/min11030296.","productDescription":"21 p.","startPage":"296","endPage":"316","ipdsId":"IP-119633","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":453124,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/min11030296","text":"Publisher Index Page"},{"id":436461,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HMGGAM","text":"USGS data release","linkHelpText":"Point locations of brick kilns in Kabul, Afghanistan, derived from 1965, 2004, 2011, and 2018 satellite imagery"},{"id":388094,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Afghanistan","city":"Kabul","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              68.69750976562499,\n              34.252676117101515\n            ],\n            [\n              69.60937499999999,\n              34.252676117101515\n            ],\n            [\n              69.60937499999999,\n              35.04798673426734\n            ],\n            [\n              68.69750976562499,\n              35.04798673426734\n            ],\n            [\n              68.69750976562499,\n              34.252676117101515\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"3","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"DeWitt, Jessica D. 0000-0002-8281-8134 jdewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-8134","contributorId":5804,"corporation":false,"usgs":true,"family":"DeWitt","given":"Jessica","email":"jdewitt@usgs.gov","middleInitial":"D.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":821404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chirico, Peter G. 0000-0001-8375-5342","orcid":"https://orcid.org/0000-0001-8375-5342","contributorId":63838,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter","email":"","middleInitial":"G.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":821405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alessi, Marissa A. 0000-0002-1251-3108","orcid":"https://orcid.org/0000-0002-1251-3108","contributorId":264353,"corporation":false,"usgs":false,"family":"Alessi","given":"Marissa A.","affiliations":[{"id":33043,"text":"Natural Systems Analysts, Inc.","active":true,"usgs":false}],"preferred":false,"id":821406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boston, Kathleen M 0000-0003-1301-9651","orcid":"https://orcid.org/0000-0003-1301-9651","contributorId":264351,"corporation":false,"usgs":false,"family":"Boston","given":"Kathleen","email":"","middleInitial":"M","affiliations":[{"id":54446,"text":"Aperture Federal, LLC","active":true,"usgs":false}],"preferred":false,"id":821407,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70219168,"text":"70219168 - 2021 - Submarine lava deltas of the 2018 eruption of Kilauea volcano","interactions":[],"lastModifiedDate":"2021-04-08T15:27:07.976909","indexId":"70219168","displayToPublicDate":"2021-03-11T07:54:07","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Submarine lava deltas of the 2018 eruption of Kīlauea volcano","title":"Submarine lava deltas of the 2018 eruption of Kilauea volcano","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Hawaiian and other ocean island lava flows that reach the coastline can deposit significant volumes of lava in submarine deltas. The catastrophic collapse of these deltas represents one of the most significant, but least predictable, volcanic hazards at ocean islands. The volume of lava deposited below sea level in delta-forming eruptions and the mechanisms of delta construction and destruction are rarely documented. Here, we report on bathymetric surveys and ROV observations following the Kīlauea 2018 eruption that, along with a comparison to the deltas formed at Pu‘u ‘Ō‘ō over the past decade, provide new insight into delta formation. Bathymetric differencing reveals that the 2018 deltas contain more than half of the total volume of lava erupted. In addition, we find that the 2018 deltas are comprised largely of coarse-grained volcanic breccias and intact lava flows, which contrast with those at Pu‘u ‘Ō‘ō that contain a large fraction of fine-grained hyaloclastite. We attribute this difference to less efficient fragmentation of the 2018 ‘a‘ā flows leading to fragmentation by collapse rather than hydrovolcanic explosion. We suggest a mechanistic model where the characteristic grain size influences the form and stability of the delta with fine grain size deltas (Pu‘u ‘Ō‘ō) experiencing larger landslides with greater run-out supported by increased pore pressure and with coarse grain size deltas (Kīlauea 2018) experiencing smaller landslides that quickly stop as the pore pressure rapidly dissipates. This difference, if validated for other lava deltas, would provide a means to assess potential delta stability in future eruptions.</p></div></div><div id=\"Sec1-section\" class=\"c-article-section\"><br></div>","language":"English","publisher":"Springer","doi":"10.1007/s00445-020-01424-1","usgsCitation":"Soule, S.A., Zoeller, M.H., and Parcheta, C., 2021, Submarine lava deltas of the 2018 eruption of Kilauea volcano: Bulletin of Volcanology, v. 83, 23, 16 p., https://doi.org/10.1007/s00445-020-01424-1.","productDescription":"23, 16 p.","ipdsId":"IP-119021","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":453125,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-020-01424-1","text":"Publisher Index Page"},{"id":384715,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.3089141845703,\n              19.237901559805035\n            ],\n            [\n              -155.02532958984375,\n              19.237901559805035\n            ],\n            [\n              -155.02532958984375,\n              19.449759112405612\n            ],\n            [\n              -155.3089141845703,\n              19.449759112405612\n            ],\n            [\n              -155.3089141845703,\n              19.237901559805035\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"83","noUsgsAuthors":false,"publicationDate":"2021-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Soule, S. Adam 0000-0002-4691-6300","orcid":"https://orcid.org/0000-0002-4691-6300","contributorId":221052,"corporation":false,"usgs":false,"family":"Soule","given":"S.","email":"","middleInitial":"Adam","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":813097,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zoeller, Michael H. 0000-0003-4716-8567","orcid":"https://orcid.org/0000-0003-4716-8567","contributorId":214557,"corporation":false,"usgs":true,"family":"Zoeller","given":"Michael","email":"","middleInitial":"H.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":813098,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parcheta, Carolyn 0000-0001-6556-4630 cparcheta@usgs.gov","orcid":"https://orcid.org/0000-0001-6556-4630","contributorId":215617,"corporation":false,"usgs":true,"family":"Parcheta","given":"Carolyn","email":"cparcheta@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":813099,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70218812,"text":"70218812 - 2021 - ‘Unscrambling’ the drivers of egg production in Agassiz’s desert tortoise: Climate and individual attributes predict reproductive output","interactions":[],"lastModifiedDate":"2021-03-15T12:52:06.966399","indexId":"70218812","displayToPublicDate":"2021-03-11T07:43:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"‘Unscrambling’ the drivers of egg production in Agassiz’s desert tortoise: Climate and individual attributes predict reproductive output","docAbstract":"<p class=\"abstract_block\">ABSTRACT: The ‘bet hedging’ life history strategy of long-lived iteroparous species reduces short-term reproductive output to minimize the risk of reproductive failure over a lifetime. For desert-dwelling ectotherms living in variable and unpredictable environments, reproductive output is further influenced by precipitation and temperature via effects on food availability and limits on activity. We assembled multiple (n = 12) data sets on egg production for the threatened Agassiz’s desert tortoise<span>&nbsp;</span><i>Gopherus agassizii</i><span>&nbsp;</span>across its range and used these data to build a range-wide predictive model of annual reproductive output as a function of annual weather variation and individual-level attributes (body size and prior-year reproductive status). Climate variables were more robust predictors of reproductive output than individual-level attributes, with overall reproductive output positively related to prior-year precipitation and an earlier start to the spring activity season, and negatively related to spring temperature extremes (monthly temperature range in March-April). Reproductive output was highest for individuals with larger body sizes that reproduced in the previous year. Expected annual reproductive output from 1990-2018 varied from 2-5 to 6-12 eggs female<sup>-1</sup><span>&nbsp;</span>yr<sup>-1</sup><span>&nbsp;</span>, with a weak decline in expected reproductive output over this time (p = 0.02). Climate-driven environmental variation in expected reproductive output was highly correlated across all 5 Recovery Units for this species (Pearson’s r &gt; 0.9). Overall, our model suggests that climate change could strongly impact the reproductive output of Agassiz’s desert tortoise, and could have a negative population-level effect if precipitation is significantly reduced across the species’ range as predicted under some climate models.</p>","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01103","usgsCitation":"Mitchell, C.I., Friend, D., Phillips, L.T., Hunter, E., Lovich, J.E., Agha, M., Puffer, S., Cummings, K.L., Medica, P.A., Esque, T., Nussear, K.E., and Shoemaker, K.T., 2021, ‘Unscrambling’ the drivers of egg production in Agassiz’s desert tortoise: Climate and individual attributes predict reproductive output: Endangered Species Research, v. 44, p. 217-230, https://doi.org/10.3354/esr01103.","productDescription":"14 p.","startPage":"217","endPage":"230","ipdsId":"IP-121127","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":453130,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01103","text":"Publisher Index Page"},{"id":436463,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97WD6AH","text":"USGS data release","linkHelpText":"Mojave Desert Tortoise (Gopherus agassizii) Morphometrics and Egg Data from Seven Sites across the Mojave, (1997-2002)"},{"id":436462,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97XT7HF","text":"USGS data release","linkHelpText":"Agassiz's desert tortoise and egg data from the Sonoran Desert of California (1997-2000, 2015-2018)"},{"id":384375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Arizona, Nevada, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.158203125,\n              33.211116472416855\n            ],\n            [\n              -112.763671875,\n              33.211116472416855\n            ],\n            [\n              -112.763671875,\n              37.16031654673677\n            ],\n            [\n              -117.158203125,\n              37.16031654673677\n            ],\n            [\n              -117.158203125,\n              33.211116472416855\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"44","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mitchell, Corey I. 0000-0001-9479-7329","orcid":"https://orcid.org/0000-0001-9479-7329","contributorId":255287,"corporation":false,"usgs":false,"family":"Mitchell","given":"Corey","email":"","middleInitial":"I.","affiliations":[{"id":51512,"text":"Department of Geography, University of Nevada, Reno, 1664 N Virginia St, Reno, NV 89557, USA","active":true,"usgs":false}],"preferred":false,"id":812082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Friend, Derek 0000-0002-6909-8769","orcid":"https://orcid.org/0000-0002-6909-8769","contributorId":255288,"corporation":false,"usgs":false,"family":"Friend","given":"Derek","email":"","affiliations":[{"id":51512,"text":"Department of Geography, University of Nevada, Reno, 1664 N Virginia St, Reno, NV 89557, USA","active":true,"usgs":false}],"preferred":true,"id":812083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, Lauren T. 0000-0003-3110-1755","orcid":"https://orcid.org/0000-0003-3110-1755","contributorId":255289,"corporation":false,"usgs":false,"family":"Phillips","given":"Lauren","email":"","middleInitial":"T.","affiliations":[{"id":51512,"text":"Department of Geography, University of Nevada, Reno, 1664 N Virginia St, Reno, NV 89557, USA","active":true,"usgs":false}],"preferred":false,"id":812084,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunter, Elizabeth A.","contributorId":149399,"corporation":false,"usgs":false,"family":"Hunter","given":"Elizabeth A.","affiliations":[],"preferred":false,"id":812085,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":812086,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Agha, Mickey","contributorId":22235,"corporation":false,"usgs":false,"family":"Agha","given":"Mickey","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false},{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":812167,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Puffer, Shellie R. 0000-0003-4957-0963","orcid":"https://orcid.org/0000-0003-4957-0963","contributorId":193099,"corporation":false,"usgs":true,"family":"Puffer","given":"Shellie R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":812088,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cummings, Kristy L. 0000-0002-8316-5059","orcid":"https://orcid.org/0000-0002-8316-5059","contributorId":202061,"corporation":false,"usgs":true,"family":"Cummings","given":"Kristy","email":"","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":812089,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Medica, Philip A.","contributorId":55780,"corporation":false,"usgs":true,"family":"Medica","given":"Philip","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":812090,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":812168,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Nussear, Kenneth E.","contributorId":117361,"corporation":false,"usgs":false,"family":"Nussear","given":"Kenneth","email":"","middleInitial":"E.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":812092,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Shoemaker, Kevin T. 0000-0002-3789-3856","orcid":"https://orcid.org/0000-0002-3789-3856","contributorId":255290,"corporation":false,"usgs":false,"family":"Shoemaker","given":"Kevin","email":"","middleInitial":"T.","affiliations":[{"id":51513,"text":"Department of Natural Resources and Environmental Science, University of Nevada, Reno. 1664 N Virginia St, Reno, NV 89557, USA","active":true,"usgs":false}],"preferred":false,"id":812093,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70219025,"text":"70219025 - 2021 - Numerical analysis of the effect of subgrid variability in a physically based hydrological model on runoff, soil moisture, and slope stability","interactions":[],"lastModifiedDate":"2021-04-08T15:14:07.19162","indexId":"70219025","displayToPublicDate":"2021-03-11T07:13:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Numerical analysis of the effect of subgrid variability in a physically based hydrological model on runoff, soil moisture, and slope stability","docAbstract":"<p><span>In coarse resolution hydrological modeling we face the problem of subgrid variability, the effects of which are difficult to express and are often hidden in the parameterization and calibration. We present a numerical experiment with the physically based hydrological model ParFlow‐CLM with which we quantify the effect of subgrid heterogeneities in headwater catchments within the cell size typically used for regional hydrological applications. We simulate homogeneous domains and domains with subgrid heterogeneities in topography or soil thickness for two climates and soil types. The presence of side slope is the main error source, leading to large underestimation of runoff, and marginally also of evapotranspiration. The spatial distribution of soil saturation in the presence of subgrid variability in topography also leads to underestimation of landslide risk. Soil thickness is the second influential subgrid property, affecting soil moisture distribution and surface runoff formation. Results are consistent for the climates and the soil types considered. The topographic wetness index approach is tested as a way to downscale soil moisture simulations within the domain. Although this method is successful in reproducing some spatial variability and patterns, it fails when the coarse grid mean soil saturation is inaccurate or subgrid topography does not represent subsurface flow paths accurately. We conclude that ignoring subgrid variability in topography and soil thickness in coarse‐scale hydrological models may lead locally to underestimation of runoff and slope instability. Users of such models should be aware of these biases and consider ways to include subgrid effects in coarse‐scale hydrological predictions.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR027326","usgsCitation":"Leonarduzzi, E., Maxwell, R.M., Mirus, B.B., and Molnar, P., 2021, Numerical analysis of the effect of subgrid variability in a physically based hydrological model on runoff, soil moisture, and slope stability: Water Resources Research, v. 57, no. 4, e2020WR027326, 16 p., https://doi.org/10.1029/2020WR027326.","productDescription":"e2020WR027326, 16 p.","ipdsId":"IP-124808","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":453131,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2020wr027326","text":"External Repository"},{"id":384495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Leonarduzzi, E. 0000-0002-6811-9118","orcid":"https://orcid.org/0000-0002-6811-9118","contributorId":255523,"corporation":false,"usgs":false,"family":"Leonarduzzi","given":"E.","email":"","affiliations":[{"id":51571,"text":"Institute of Environmental Engineering, ETH Zurich, Switzerland; Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland","active":true,"usgs":false}],"preferred":false,"id":812489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maxwell, R. M.","contributorId":255524,"corporation":false,"usgs":false,"family":"Maxwell","given":"R.","email":"","middleInitial":"M.","affiliations":[{"id":51573,"text":"Integrated Groundwater Modeling Center and Department of Geology and Geological Engineering, Colorado School of Mines, Golden, Colorado, USA","active":true,"usgs":false}],"preferred":false,"id":812490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":812491,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Molnar, P. 0000-0001-6437-4931","orcid":"https://orcid.org/0000-0001-6437-4931","contributorId":255525,"corporation":false,"usgs":false,"family":"Molnar","given":"P.","email":"","affiliations":[{"id":51575,"text":"Institute of Environmental Engineering, ETH Zurich, Switzerland","active":true,"usgs":false}],"preferred":false,"id":812492,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70219608,"text":"70219608 - 2021 - A chemical and bio‐herbicide mixture increased exotic invaders, both targeted and non‐targeted, across a diversely invaded landscape after fire","interactions":[],"lastModifiedDate":"2021-04-15T12:11:07.23823","indexId":"70219608","displayToPublicDate":"2021-03-11T07:07:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":849,"text":"Applied Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"A chemical and bio‐herbicide mixture increased exotic invaders, both targeted and non‐targeted, across a diversely invaded landscape after fire","docAbstract":"<h3 id=\"avsc12574-sec-0001-title\" class=\"article-section__sub-title section1\">Questions</h3><p>Invasive‐plant treatments often target a single or few species, but many landscapes are diversely invaded. Exotic annual grasses (EAGs) increase wildfires and degrade native perennial plant communities in cold‐desert rangelands, and herbicides are thus sprayed to inhibit EAG germination and establishment. We asked how EAG target and non‐target species responded to an herbicide mixture sprayed over a large, topographically diverse landscape after wildfire. We focused on how whole‐community and natural EAG‐pathogen treatment responses varied over years and physical properties of sites.</p><h3 id=\"avsc12574-sec-0002-title\" class=\"article-section__sub-title section1\">Location</h3><p>Sagebrush steppe of southwest Idaho, USA.</p><h3 id=\"avsc12574-sec-0003-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We monitored plant cover and diversity in 41 pairs of plots located inside or outside areas (486&nbsp;ha total) treated with a combined aerial broadcast spray of pre‐emergent herbicide (imazapic) and weed‐suppressive bacteria (<i>Pseudomonas</i><span>&nbsp;</span><i>fluorescens</i>, “MB906”) to target EAGs after wildfires.</p><h3 id=\"avsc12574-sec-0004-title\" class=\"article-section__sub-title section1\">Results</h3><p>EAG cover and exotic species richness were initially less in treated plots but increased to levels similar to or greater than those of untreated plots by the third post‐treatment year. The EAG pathogen<span>&nbsp;</span><i>Ustilago bullata</i><span>&nbsp;</span>was not directly affected by the treatment. The treatment increased exotic perennial forb cover in all plots and exotic annual forb cover in cooler/wetter plots but reduced exotic annual forb cover in warmer/drier plots. Cover of the invasive biennial grass<span>&nbsp;</span><i>Poa bulbosa</i><span>&nbsp;</span>decreased more across study years in untreated than treated plots. Among natives, the treatment reduced perennial grass cover and annual forb presence but led to marginal increases in perennial forb cover and, on soils with less gravel, increased shrub presence.</p><h3 id=\"avsc12574-sec-0005-title\" class=\"article-section__sub-title section1\">Conclusions</h3><p>A treatment targeting a single plant functional group did not achieve lasting success in these diversely invaded communities. Spraying alone did not release native perennials sufficiently to counteract the simultaneous release of secondary invaders and the return of target invaders. Planting or seeding may also be needed to achieve management goals.</p>","language":"English","publisher":"Wiley","doi":"10.1111/avsc.12574","usgsCitation":"Lazarus, B., and Germino, M.J., 2021, A chemical and bio‐herbicide mixture increased exotic invaders, both targeted and non‐targeted, across a diversely invaded landscape after fire: Applied Vegetation Science, v. 24, no. 2, e12574, 13 p., https://doi.org/10.1111/avsc.12574.","productDescription":"e12574, 13 p.","ipdsId":"IP-123369","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":436464,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CB7C62","text":"USGS data release","linkHelpText":"Post-fire vegetation cover, plant species diversity, and Ustilago bullata infection rates at Boise River Wildlife Management Area 2018-2019"},{"id":385109,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.94970703125,\n              42.924251753870685\n            ],\n            [\n              -114.76318359375,\n              42.924251753870685\n            ],\n            [\n              -114.76318359375,\n              43.96119063892024\n            ],\n            [\n              -115.94970703125,\n              43.96119063892024\n            ],\n            [\n              -115.94970703125,\n              42.924251753870685\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"24","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Lazarus, Brynne E. 0000-0002-6352-486X","orcid":"https://orcid.org/0000-0002-6352-486X","contributorId":242732,"corporation":false,"usgs":true,"family":"Lazarus","given":"Brynne E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":814297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579 mgermino@usgs.gov","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":3298,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew","email":"mgermino@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":814298,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70218822,"text":"70218822 - 2021 - Population density and stream-habitat relations of the Yellowcheek Darter <i>(Nothonotus moorei)</i> among the headwaters of the Little Red River in Arkansas","interactions":[],"lastModifiedDate":"2021-03-16T11:45:53.545635","indexId":"70218822","displayToPublicDate":"2021-03-11T06:37:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Population density and stream-habitat relations of the Yellowcheek Darter <i>(Nothonotus moorei)</i> among the headwaters of the Little Red River in Arkansas","docAbstract":"<p><i>Nothonotus moorei</i><span>&nbsp;(Yellowcheek Darter [YCD]) is an endangered species endemic to the headwaters of the Little Red River in north-central Arkansas. Population decline, habitat loss and fragmentation, and threats from land use and seasonal drought necessitate monitoring of population density and distribution to determine ecological and habitat associations. We evaluated YCD density and associated stream-habitat variables from 9 sites in the South Fork, Archey Fork, Middle Fork, and Beech Fork of the Little Red River from March to April 2018. Yellowcheek Darters were present at all 9 sites and 19 of 23 riffles sampled. Densities were generally comparable or higher than reported in previous studies, and we collected YCD at some sites at which they were considered previously extirpated, suggesting a rather stable population and evidence of recolonization of some sites since they were last surveyed. Yellowcheek Darter density was significantly negatively related to substrate embeddedness, and the consistent relation to embeddedness in this study and other studies suggest that this species is vulnerable to sedimentation.</span></p>","language":"English","publisher":"BioOne","doi":"10.1656/058.020.0124","usgsCitation":"Driver, L., and Justus, B., 2021, Population density and stream-habitat relations of the Yellowcheek Darter <i>(Nothonotus moorei)</i> among the headwaters of the Little Red River in Arkansas: Southeastern Naturalist, v. 20, no. 1, p. 227-244, https://doi.org/10.1656/058.020.0124.","productDescription":"18 p.","startPage":"227","endPage":"244","ipdsId":"IP-095659","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":384400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Arkansas","otherGeospatial":"Little Red River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92.65869140625,\n              35.37113502280101\n            ],\n            [\n              -91.56005859375,\n              35.37113502280101\n            ],\n            [\n              -91.56005859375,\n              35.96022296929667\n            ],\n            [\n              -92.65869140625,\n              35.96022296929667\n            ],\n            [\n              -92.65869140625,\n              35.37113502280101\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"20","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Driver, Lucas 0000-0003-2549-1849","orcid":"https://orcid.org/0000-0003-2549-1849","contributorId":219176,"corporation":false,"usgs":true,"family":"Driver","given":"Lucas","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812290,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Justus, Billy 0000-0002-3458-9656 bjustus@usgs.gov","orcid":"https://orcid.org/0000-0002-3458-9656","contributorId":202148,"corporation":false,"usgs":true,"family":"Justus","given":"Billy","email":"bjustus@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812291,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70218752,"text":"ofr20211026 - 2021 - Expected warning times from the ShakeAlert earthquake early warning system for earthquakes in the Pacific Northwest","interactions":[],"lastModifiedDate":"2021-04-07T01:36:23.477755","indexId":"ofr20211026","displayToPublicDate":"2021-03-10T15:49:09","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1026","displayTitle":"Expected Warning Times from the ShakeAlert® Earthquake Early Warning System for Earthquakes in the Pacific Northwest","title":"Expected warning times from the ShakeAlert earthquake early warning system for earthquakes in the Pacific Northwest","docAbstract":"<p>The ShakeAlert® earthquake early warning system has been live since October 2019 for the testing of public alerting to mobile devices in California and will soon begin testing this modality in Oregon and Washington. The Pacific Northwest presents new challenges and opportunities for ShakeAlert owing to the different types of earthquakes that occur in the Cascadia subduction zone. Many locations in the Pacific Northwest are expected to experience shaking from shallow crustal earthquakes (similar to those in California), earthquakes that occur deep within the subducted slab, and large megathrust earthquakes that occur primarily offshore. The different geometries and maximum magnitudes associated with these types of earthquakes lead to a range of warning times that are possible between when the initial ShakeAlert Message is issued and when a user experiences strong shaking. After an earthquake begins, the strategy of the ShakeAlert system for public alerting is to warn people who are located close enough to the fault that the system estimates they will experience at least weak to moderate shaking. By alerting the public at these low levels of expected shaking, it is possible to provide sufficient warning times for some users to take protective actions before strong shaking begins. In this study, we present an analysis of past ShakeAlert Messages as well as simulations of historical earthquakes and potential future Cascadia earthquakes to quantify the range of warning times that users who experience strong or worse shaking are likely to receive. Additional applications for ShakeAlert involve initiation of automatic protective actions prior to the onset of shaking, such as slowing trains, shutting water supplies, and opening firehouse doors, which are beyond the scope of this paper. Users in the Pacific Northwest should expect that the majority of alerts they receive will be from shallow crustal and intraslab earthquakes. In these cases, users will only have a few seconds of warning before strong shaking begins. This remains true even during infrequent, offshore great (magnitude ≥8) megathrust earthquakes, where warning times will generally range from seconds to tens of seconds, depending on the user’s location and the intensity of predicted shaking that a user chooses to be alerted for, with the longest warning times of 50–80 seconds possible only for users located at considerable distance from the epicenter. ShakeAlert thus requires short, readily understood alerts stating that earthquake shaking is imminent and suggesting protective actions users should take. Extensive education and outreach efforts that emphasize the need to take actions quickly will be required for ShakeAlert to successfully reduce injuries and losses.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211026","usgsCitation":"McGuire, J.J., Smith, D.E., Frankel, A.D., Wirth, E.A., McBride, S.K., and de Groot, R.M., 2021, Expected warning times from the ShakeAlert earthquake early warning system for earthquakes in the Pacific Northwest (ver. 1.1, March 24, 2021): U.S. Geological Survey Open-File Report 2021–1026, 37 p., https://doi.org/10.3133/ofr20211026.","productDescription":"v, 37 p.","onlineOnly":"Y","ipdsId":"IP-125131","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":384638,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1026/versionHist.txt","size":"2 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 \"}}]}","edition":"Version 1.0: Marhc 10, 2021; Version 1.1: March 24, 2021","contact":"<p><a href=\"https://www.usgs.gov/centers/earthquake-science-center\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/earthquake-science-center\">Earthquake Science Center</a>—Menlo Park, Calif. Office<br>U.S. Geological Survey<br>345 Middlefield Road, MS 977<br>Menlo Park, CA 94025</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>The Shake Alert Earthquake Early Warning System</li><li>Earthquake Hazards in the Pacific Northwest</li><li>Hazard Deaggregation</li><li>Definition of Warning Times</li><li>Warning Times for Shallow Crustal Events</li><li>Warning Times for Deep Instraslab Earthquakes</li><li>Warning Times for Offshore M 7–9 Megathrust Earthquakes</li><li>Implications for EEW Users in the Pacific Northwest</li><li>Conclusions</li><li>References Cited</li><li>Appendix 1</li></ul>","publishedDate":"2021-03-10","revisedDate":"2021-03-24","noUsgsAuthors":false,"publicationDate":"2021-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166 jmcguire@whoi.edu","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":177447,"corporation":false,"usgs":false,"family":"McGuire","given":"Jeffrey","email":"jmcguire@whoi.edu","middleInitial":"J.","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":811673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Deborah E. 0000-0002-8317-7762 deborahsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8317-7762","contributorId":5670,"corporation":false,"usgs":true,"family":"Smith","given":"Deborah","email":"deborahsmith@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":811674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":1363,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":811675,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wirth, Erin A. 0000-0002-8592-4442","orcid":"https://orcid.org/0000-0002-8592-4442","contributorId":197865,"corporation":false,"usgs":true,"family":"Wirth","given":"Erin","email":"","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":811676,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McBride, Sara K. 0000-0002-8062-6542 skmcbride@usgs.gov","orcid":"https://orcid.org/0000-0002-8062-6542","contributorId":224627,"corporation":false,"usgs":true,"family":"McBride","given":"Sara","email":"skmcbride@usgs.gov","middleInitial":"K.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":811677,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"de Groot, Robert M. 0000-0001-9995-4207","orcid":"https://orcid.org/0000-0001-9995-4207","contributorId":210451,"corporation":false,"usgs":false,"family":"de Groot","given":"Robert M.","affiliations":[],"preferred":false,"id":811678,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70218729,"text":"ofr20201125 - 2021 - Sagebrush conservation strategy—Challenges to sagebrush conservation","interactions":[],"lastModifiedDate":"2021-03-30T14:41:59.299981","indexId":"ofr20201125","displayToPublicDate":"2021-03-10T15:30:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1125","displayTitle":"Sagebrush Conservation Strategy—Challenges to Sagebrush Conservation","title":"Sagebrush conservation strategy—Challenges to sagebrush conservation","docAbstract":"<p>The sagebrush (<i>Artemisia</i> spp.) biome, its wildlife, and the services and benefits it provides people and local communities are at risk. Development in the sagebrush biome, for many purposes, has resulted in multiple and often cumulative negative impacts. These impacts, ranging from simple habitat loss to complex, interactive changes in ecosystem function, continue to accelerate even as the need grows for the resources provided by this biome. This “Sagebrush Conservation Strategy—Challenges to Sagebrush Conservation,” is an overview and assessment of the challenges facing land managers and landowners in conserving sagebrush ecosystems. This strategy is intended to provide guidance so that the unparalleled collaborative efforts to conserve the iconic greater sage-grouse (<i>Centrocercus urophasianus</i>) by State and Federal agencies, Tribes, academia, nongovernmental organizations, and stakeholders can be expanded to the entire sagebrush biome to benefit the people and wildlife that depend on this ecosystem. This report is organized into 3 parts.</p><p>“Part I. Importance of the Sagebrush Biome to People and Wildlife” introduces the biome and a subset of the more than 350 species of plants and animals associated with sagebrush for which there is some level of conservation concern. These include several sagebrush obligates that have been petitioned for listing under the Endangered Species Act of 1973 (16 U.S.C. 1531 et seq.), including greater sage-grouse, Gunnison sage-grouse (<i>C. minimus</i>; listed as threatened), and pygmy rabbit (<i>Brachylagus idahoensis</i>). Other sagebrush-dependent species, such as pronghorn (<i>Antilocapra americana</i>) and mule deer (<i>Odocoileus hemionus</i>), have experienced significant population declines.</p><p>“Part II. Change Agents in the Sagebrush Biome—Extent, Impacts, and Effort to Address Them” is an overview of the variety of change agents that are causing the continued loss and degradation of sagebrush. Topics covered include altered fire regimes, invasive plant species, conifer expansion, overabundant free-roaming equids, and human land uses, including energy development, cropland conversion, infrastructure, and improper livestock grazing. Climate changes, including warmer temperatures and altered amounts and timing of precipitation, have and will likely increasingly compound negative effects to sagebrush ecosystems from all these threats.</p><p>“Part III. Current Conservation Paradigm and Other Conservation Needs for Sagebrush” begins with an overview of how sage-grouse conservation, and the associated efforts and collaborations, may be able to address threats to and restoring degraded sagebrush and habitat for other sagebrush-dependent and -associated species. Meeting conservation goals for sage-grouse, mule deer, pygmy rabbits, and other sagebrush-associated wildlife will require extensive restoration of sagebrush communities already converted or degraded by the change agents outlined in Part II of this report. Concepts, considerations, techniques for restoration, and adaptive management and monitoring are discussed to help set the stage for potential strategies to improve conditions throughout the sagebrush biome. Communication, outreach, and engagement can enhance grassroots conservation efforts and build the next generation of managers, practitioners, scientists, and communicators who will care for the sagebrush ecosystem and stimulate or sustain public participation in sagebrush conservation issues.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201125","collaboration":"Prepared in cooperation with the Western Association of Fish and Wildlife Agencies, the Bureau of Land Management, and the U.S. Fish and Wildlife Service","usgsCitation":"Remington, T.E., Deibert, P.A., Hanser, S.E., Davis, D.M., Robb, L.A., and Welty, J.L., 2021, Sagebrush conservation strategy—Challenges to sagebrush conservation: U.S. Geological Survey Open-File Report 2020–1125, 327 p., https://doi.org/10.3133/ofr20201125.","productDescription":"xxxiv, 327 p.","onlineOnly":"N","ipdsId":"IP-112519","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":384279,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1125/ofr20201125.pdf","text":"Report","size":"35.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1125"},{"id":384278,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1125/coverthb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, Nebraska, Nevada, New Mexico, North Dakota, South Dakota, Oregon, Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.0703125,\n              46.31658418182218\n            ],\n            [\n              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Geological Survey<br>2150 Centre Ave., Building C<br>Fort Collins, CO 80526-8118</p>","tableOfContents":"<ul><li>Preface</li><li>Contributors</li><li>Common and Scientific Names of Animal Species in this Report</li><li>Common and Scientific Names of Plant Species in this Report</li><li>Executive Summary</li><li><strong>PART I. Importance of the Sagebrush Biome to People and Wildlife</strong></li><li><strong>Chapter A. Introduction to the Sagebrush Biome</strong></li><li>Executive Summary</li><li>Introduction</li><li>History of the Sagebrush Biome</li><li>Sagebrush Benefits, Sagebrush Wildlife</li><li><strong>Chapter B. Human Dimensions of Sagebrush</strong></li><li>Executive Summary</li><li>Introduction</li><li>Historical Relationship of Humans to Sagebrush</li><li>Ecosystem Services</li><li>Threats</li><li><strong>Chapter C. Sagebrush Birds</strong></li><li>Executive Summary</li><li>Introduction</li><li>Habitat Selection and Dependency on Sagebrush</li><li>Population Trends and Conservation Status</li><li>Threats</li><li>Management Considerations</li><li>Acknowledgments</li><li><strong>Chapter D. Greater and Gunnison Sage-Grouse</strong></li><li>Executive Summary</li><li>Introduction</li><li>Habitat Selection and Dependency on Sagebrush</li><li>Movements and Home Ranges</li><li>Population Trends and Conservation Status</li><li>Threats</li><li>Management Considerations</li><li><strong>Chapter E. Pygmy Rabbit</strong></li><li>Executive Summary</li><li>Introduction</li><li>Habitat Selection and Dependency on Sagebrush</li><li>Movements and Home Ranges</li><li>Population Trends and Conservation Status</li><li>Threats</li><li>Management Considerations</li><li>Acknowledgments</li><li><strong>Chapter F. Pronghorn</strong></li><li>Executive Summary</li><li>Introduction</li><li>Habitat Selection and Dependency on Sagebrush</li><li>Movements and Migration</li><li>Population Trends and Conservation Status</li><li>Threats</li><li>Management Considerations</li><li><strong>Chapter G. Mule Deer</strong></li><li>Executive Summary</li><li>Introduction</li><li>Habitat Selection and Dependency on Sagebrush</li><li>Movements and Home Ranges</li><li>Population Trends and Conservation Status</li><li>Threats</li><li>Management Considerations</li><li>Acknowledgments</li><li><strong>Chapter H. Sagebrush-Dependent Small Mammals</strong></li><li>Executive Summary</li><li>Introduction</li><li>Dark Kangaroo Mouse</li><li>Great Basin and Columbia Plateau Pocket Mouse</li><li>Merriam’s Shrew</li><li>Preble’s Shrew</li><li>Ord’s Kangaroo Rat</li><li>Sagebrush Vole</li><li>Southern Idaho Ground Squirrel</li><li>Wyoming Ground Squirrel</li><li>Wyoming Pocket Gopher</li><li>White-Tailed Prairie Dog</li><li>Black-Tailed Jackrabbit</li><li><strong>Chapter I. Amphibians and Reptiles in Sagebrush</strong></li><li>Executive Summary</li><li>Introduction</li><li>Amphibians</li><li>Reptiles</li><li>Conservation Status</li><li>Threats</li><li>Management Considerations</li><li>Acknowledgments</li><li>Appendix I1. Amphibians and Reptiles that Overlap with the Sagebrush Biome</li><li><strong>Part II. Change Agents in the Sagebrush Biome—Extent, Impacts, and Efforts to Address Them</strong></li><li><strong>Chapter J. Altered Fire Regimes</strong></li><li>Executive Summary</li><li>Introduction</li><li>The Role of Wildfire in Sagebrush Ecosystems</li><li>Recent Fire Trends and Patterns</li><li>Impact of Altered Fire Regimes on Sagebrush Communities and Postfire Recovery</li><li>Impacts of Altered Fire Regimes on Wildlife</li><li>Impacts of Prescribed Fire on Wildlife</li><li>Impacts of Altered Fire Regimes on Ecosystem Services</li><li>Fire-Suppression Costs</li><li>Burned Area Emergency Stabilization and Rehabilitation Costs</li><li>Other Costs Associated with Wildfire</li><li>Current Coordination Efforts Among Federal, State, and Tribal Entities to Address Fire</li><li><strong>Chapter K. Invasive Plant Species</strong></li><li>Executive Summary</li><li>Introduction</li><li>Invasive Plant Descriptions and Regulations</li><li>Impacts of Invasive Plants on Wildlife Communities</li><li>Impacts of Invasive Plants on Human Needs and Values</li><li>Support for Invasive Plant Threat Reduction</li><li>Management for Threat Abatement</li><li>Appendix K1. Nonnative Invasive Plants in Sagebrush Ecosystems</li><li><strong>Chapter L. Climate Adaptation</strong></li><li>Executive Summary</li><li>Introduction</li><li>Climate Change Trajectories and Impacts</li><li>Plant Community Impacts</li><li>Wildlife and Livestock Impacts</li><li>Diseases and Impacts to Wildlife and Humans</li><li>Climate Change Adaptation</li><li>Current Programs and Activities</li><li>Appendix L1. A Selection of Climate Vulnerability Assessments and Adaptation Strategies Relevant to the Sagebrush Biome</li><li><strong>Chapter M. Conifer Expansion</strong></li><li>Executive Summary</li><li>Introduction</li><li>Nature and Extent of Conifer Expansion</li><li>Impact on Sagebrush Communities, Ecosystem Processes, and Wildlife Communities</li><li>Impact on Human Resource Needs and Values</li><li>Current Efforts to Address Conifer Expansion</li><li>Efficacy of Tree Removal at Restoring Ecosystem Function and Plant and Animal Communities</li><li>Potential Impact of Conifer Removal on Sagebrush Species</li><li>Acknowledgments</li><li><strong>Chapter N. Free-Roaming Equids</strong></li><li>Executive Summary</li><li>Introduction</li><li>Legal Status of Horses and Burros on Public Lands</li><li>Administrative Structure</li><li>Impacts of Free-Roaming Equids</li><li>Free-Roaming Equid Management</li><li>Free-Roaming Equid Fertility Management</li><li>Human Dimensions and Free-Roaming Equids</li><li>Management Considerations</li><li><strong>Chapter O. Mining and Energy</strong></li><li>Executive Summary</li><li>Introduction</li><li>Mining</li><li>Nonmining Energy Development</li><li>Renewable Energy Development</li><li>Reclamation Requirements for Mining and Energy Development Activities</li><li>Current Federal and State Regulatory and Mitigation Approaches</li><li>Voluntary Conservation Actions</li><li>Best Management Practices to Avoid, Minimize, or Mitigate Impacts of Mining and Energy</li><li>Mining and Energy—Key Gaps</li><li><strong>Chapter P. Land Use and Development</strong></li><li>Executive Summary</li><li>Introduction</li><li>Conversion of Sagebrush to Croplands</li><li>Federal and State Agricultural Programs</li><li>Livestock Grazing</li><li>Infrastructure</li><li>Residential Development</li><li>Recreation</li><li>Cumulative Impacts and Conclusions</li><li><strong>Part III. Current Conservation Paradigm and Other Conservation Needs for Sagebrush</strong></li><li><strong>Chapter Q. Sage-Grouse Management as an Umbrella for Conservation of Sagebrush</strong></li><li>Executive Summary</li><li>Introduction</li><li>Management of Sagebrush</li><li>Sage-Grouse Conservation as an Umbrella</li><li><strong>Chapter R. Restoration</strong></li><li>Executive Summary</li><li>Introduction</li><li>Restoration for Wildlife Conservation</li><li>Sagebrush Restoration</li><li>Landscape-Level Characterization and Prioritization</li><li>Project-Level Prioritization and Planning</li><li>Frameworks and Tools</li><li>Evaluation of Outcomes</li><li>Social and Economic Costs and Opportunities</li><li>Appendix R1. Generalized and Sagebrush-Ecosystem Specific Information Sources</li><li><strong>Chapter S. Adaptive Management and Monitoring</strong></li><li>Executive Summary</li><li>Introduction</li><li>Adaptive Management</li><li>Vegetation Monitoring</li><li>Project-Level Monitoring</li><li>State Agency Vegetation Monitoring Efforts</li><li>Remote Sensing and Geospatial Data for Monitoring</li><li>Additional Datasets for Monitoring and Adaptive Management</li><li>Challenges and Opportunities for Vegetation Monitoring</li><li>Wildlife Monitoring</li><li>Challenges and Opportunities to Implement Adaptive Management for Wildlife</li><li>Acknowledgments</li><li>Appendix S1. Comparison of Federal Monitoring Programs in Rangelands</li><li>Appendix S2. Remotely Sensed Maps of Rangeland Vegetation Available Across the Sagebrush Biome</li><li><strong>Chapter T. Communication and Public Engagement</strong></li><li>Executive Summary</li><li>Introduction</li><li>Why Communication is Essential to Sagebrush Conservation Success</li><li>Current Capacity for Communication</li><li>Brand Identity</li><li>Public Perception</li><li>Stakeholder Engagement</li><li>Collaboration with Communicators</li><li>Acknowledgments</li><li>Appendix T1. Communication Models</li><li><strong>References Cited</strong></li></ul>","publishedDate":"2021-03-11","noUsgsAuthors":false,"publicationDate":"2021-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Remington, Thomas E.","contributorId":201659,"corporation":false,"usgs":false,"family":"Remington","given":"Thomas","email":"","middleInitial":"E.","affiliations":[{"id":36225,"text":"Western Association of Fish and Wildlife Agencies","active":true,"usgs":false}],"preferred":false,"id":811999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deibert, Patricia A.","contributorId":127500,"corporation":false,"usgs":false,"family":"Deibert","given":"Patricia","email":"","middleInitial":"A.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":812000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanser, Steve E. 0000-0002-4430-2073 shanser@usgs.gov","orcid":"https://orcid.org/0000-0002-4430-2073","contributorId":152523,"corporation":false,"usgs":true,"family":"Hanser","given":"Steve","email":"shanser@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":812001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Dawn M.","contributorId":254959,"corporation":false,"usgs":false,"family":"Davis","given":"Dawn","email":"","middleInitial":"M.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":812002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robb, Leslie A.","contributorId":254960,"corporation":false,"usgs":false,"family":"Robb","given":"Leslie","email":"","middleInitial":"A.","affiliations":[{"id":36225,"text":"Western Association of Fish and Wildlife Agencies","active":true,"usgs":false}],"preferred":false,"id":812003,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Welty, Justin L. 0000-0001-7829-7324 jwelty@usgs.gov","orcid":"https://orcid.org/0000-0001-7829-7324","contributorId":4206,"corporation":false,"usgs":true,"family":"Welty","given":"Justin","email":"jwelty@usgs.gov","middleInitial":"L.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":812004,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70217783,"text":"70217783 - 2021 - Performance of the GenEst Mortality Estimator Compared to The Huso and Shoenfeld Estimators","interactions":[],"lastModifiedDate":"2021-04-19T15:43:33.892853","indexId":"70217783","displayToPublicDate":"2021-03-10T10:41:13","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":8561,"text":"AWWI Technical Report","active":true,"publicationSubtype":{"id":4}},"title":"Performance of the GenEst Mortality Estimator Compared to The Huso and Shoenfeld Estimators","docAbstract":"<p>The impacts of wind power development on bat and bird populations are commonly assessed by estimating the number of fatalities at wind power facilities through post-construction monitoring (PCM) studies. Standard methodology involves periodic carcass searches on plots beneath turbines (Strickland et al. 2011, US Fish and Wildlife Service 2012). The resulting counts are adjusted to compensate for bias due to imperfect carcass detection by searchers, removal of carcasses by scavengers or other processes (Korner-Nievergelt et al. 2011), and carcasses that may have fallen outside of searched areas. To account for the bias in counts due to imperfect detection and carcass removal, investigators typically conduct bias trial experiments to inform models of carcass detection probability. Many different estimators have been proposed that combine information about the bias trial experiments to estimate a detection probability for carcasses (g) and ultimately obtain an estimate of total mortality (M). The two estimators that have seen the most widespread use in North America recently are the Huso (Huso 2011, Huso et al. 2012) and Shoenfeld (Shoenfeld 2004; also called the Erickson estimator) estimators. GenEst (Dalthorp et al. 2018a, 2018b, 2018c) is the newest statistical estimator to become available and was designed to improve upon the Huso and Shoenfeld estimators by generalizing the key assumptions in both, and to improve comparability among new PCM studies. In addition to relaxing some of the assumptions inherent to the Huso and Shoenfeld estimators, GenEst uses a parametric bootstrap applied to a novel approach to variance estimation (Madsen et al. 2019). </p><p>The current study was undertaken to document the performance of GenEst relative to the Huso and Shoenfeld estimators. We took a simulation approach to the study because simulation data provides the basis to compare mortality estimators under conditions where the “truth” is known. The estimators were compared on three metrics: 1) bias—the tendency of an estimator to over- or under-estimate actual mortality, 2) precision—the ability of an estimator to constrain an estimate to a narrow range (measured here as the width of a 90% confidence interval [CI] around the point estimate divided by the true, known mortality), and 3) CI coverage—the probability a CI with a specified level of confidence actually includes the true level of mortality. </p><p>Although our simulations were conceived and designed—and are discussed—with respect to wind power facilities, it is important to note that the estimators and results discussed here are relevant to any post-construction fatality monitoring study that may occur (such as at solar facilities) where detection is imperfect. Although our study treats the problem of mortality estimation when detection is imperfect, it is also important to note that all of the estimators considered here are Horvitz-Thompson (Horvitz and Thompson 1952) style estimators, that is, none are designed to estimate the mortality of rare species as might be necessary under an Incidental Take Permit. The Evidence of Absence estimator (Dalthorp et al. 2017) is still the most appropriate statistical tool for rare event estimation. </p><p>The simulations cover a broad range of conditions that may occur in field studies and complete results are presented without commentary in the appendix. The main body of this report does not provide a comprehensive treatment of our results; rather, we try to identify some of the more important differences among the estimators and some conditions under which reliable mortality estimates are especially challenging.</p>","language":"English","publisher":"American Wind Wildlife Institute","usgsCitation":"Rabie, P., Riser-Espinoza, D., Studyvin, J., Dalthorp, D., and Huso, M., 2021, Performance of the GenEst Mortality Estimator Compared to The Huso and Shoenfeld Estimators: AWWI Technical Report, 29 p.","productDescription":"29 p.","ipdsId":"IP-119710","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":385197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":385196,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://awwi.org/resources/genest/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rabie, Paul","contributorId":248699,"corporation":false,"usgs":false,"family":"Rabie","given":"Paul","affiliations":[{"id":49982,"text":"WEST, Inc.","active":true,"usgs":false}],"preferred":false,"id":809635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riser-Espinoza, Daniel","contributorId":248700,"corporation":false,"usgs":false,"family":"Riser-Espinoza","given":"Daniel","email":"","affiliations":[{"id":49982,"text":"WEST, Inc.","active":true,"usgs":false}],"preferred":false,"id":809636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Studyvin, Jared","contributorId":248701,"corporation":false,"usgs":false,"family":"Studyvin","given":"Jared","affiliations":[{"id":49982,"text":"WEST, Inc.","active":true,"usgs":false}],"preferred":false,"id":809637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dalthorp, Daniel 0000-0002-4815-6309 ddalthorp@usgs.gov","orcid":"https://orcid.org/0000-0002-4815-6309","contributorId":4902,"corporation":false,"usgs":true,"family":"Dalthorp","given":"Daniel","email":"ddalthorp@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":809638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":809639,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70220298,"text":"70220298 - 2021 - Seasonal movements of muskellunge in the St. Clair – Detroit River System: Implications for multi-jurisdictional fisheries management","interactions":[],"lastModifiedDate":"2021-05-03T15:39:09.580626","indexId":"70220298","displayToPublicDate":"2021-03-10T10:33:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal movements of muskellunge in the St. Clair – Detroit River System: Implications for multi-jurisdictional fisheries management","docAbstract":"<p><span>The St. Clair-Detroit River System contains a world-class Great Lakes muskellunge (</span><i>Esox masquinongy</i><span>) fishery that has avoided the declines observed in many Great Lakes muskellunge populations. Muskellunge are an upper trophic level predator, and therefore a naturally low-density species. Limited fishery-independent data exist on which to base management decisions. To remedy this, we initiated an acoustic&nbsp;<a title=\"Learn more about telemetry from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/remote-sensing\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/remote-sensing\">telemetry</a>&nbsp;study in May of 2016, in collaboration with the Great Lakes Acoustic Telemetry Observation System. Our objective was to describe patterns of movement of muskellunge in this large and open system to better understand their spatial ecology. We acoustically tagged 133 muskellunge in the Detroit River and Lake St. Clair, and movements of 58 fish that passed our data quality control screens were analyzed. We utilized mixed modelling to assess the effects of sex, length, release location, and season on daily movement rates. We found that movement rates only differed among seasons, with highest movement rates occurring in the fall and lowest movement rates in the winter. Muskellunge tagged at different locations exhibited distinct residency patterns, and fish frequently crossed jurisdictional and waterbody boundaries. Ultimately our study highlights the scope and patterns of muskellunge movement in a large, unimpounded system and demonstrates that management of these fish would benefit from consideration of their full distribution covering multiple management jurisdictions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2020.12.006","usgsCitation":"Hessenauer, J., Harris, C., Marklevitz, S., Faust, M.D., Thorn, M.W., Utrup, B., and Hondorp, D.W., 2021, Seasonal movements of muskellunge in the St. Clair – Detroit River System: Implications for multi-jurisdictional fisheries management: Journal of Great Lakes Research, v. 47, no. 2, p. 475-485, https://doi.org/10.1016/j.jglr.2020.12.006.","productDescription":"11 p.","startPage":"475","endPage":"485","ipdsId":"IP-121684","costCenters":[{"id":324,"text":"Great Lakes Science 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Jan-Michael","contributorId":257795,"corporation":false,"usgs":false,"family":"Hessenauer","given":"Jan-Michael","email":"","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Cleyo","contributorId":257796,"corporation":false,"usgs":false,"family":"Harris","given":"Cleyo","email":"","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marklevitz, Stephen","contributorId":257797,"corporation":false,"usgs":false,"family":"Marklevitz","given":"Stephen","email":"","affiliations":[{"id":52125,"text":"Ontario Ministry of Natural Resources & Forestry","active":true,"usgs":false}],"preferred":false,"id":815042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Faust, Matthew D.","contributorId":257798,"corporation":false,"usgs":false,"family":"Faust","given":"Matthew","email":"","middleInitial":"D.","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815043,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thorn, Michael W.","contributorId":257799,"corporation":false,"usgs":false,"family":"Thorn","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":52125,"text":"Ontario Ministry of Natural Resources & Forestry","active":true,"usgs":false}],"preferred":false,"id":815044,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Utrup, Brad","contributorId":257800,"corporation":false,"usgs":false,"family":"Utrup","given":"Brad","email":"","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815045,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hondorp, Darryl W. 0000-0002-5182-1963 dhondorp@usgs.gov","orcid":"https://orcid.org/0000-0002-5182-1963","contributorId":5376,"corporation":false,"usgs":true,"family":"Hondorp","given":"Darryl","email":"dhondorp@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":815046,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70219076,"text":"70219076 - 2021 - Inclusion of pesticide transformation products is key to estimating pesticide exposures and effects in small U.S. streams","interactions":[],"lastModifiedDate":"2021-05-27T13:21:52.551307","indexId":"70219076","displayToPublicDate":"2021-03-10T10:18:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Inclusion of pesticide transformation products is key to estimating pesticide exposures and effects in small U.S. streams","docAbstract":"<p><span>Improved analytical methods can quantify hundreds of pesticide transformation products (TPs), but understanding of TP occurrence and potential toxicity in aquatic ecosystems remains limited. We quantified 108 parent pesticides and 116 TPs in more than 3 700 samples from 442 small streams in mostly urban basins across five major regions of the United States. TPs were detected nearly as frequently as parents (90 and 95% of streams, respectively); 102 TPs were detected at least once and 28 were detected in &gt;20% samples in at least one region—TPs of 9 herbicides, 2 fungicides (chlorothalonil and thiophanate-methyl), and 1 insecticide (fipronil) were the most frequently detected. TPs occurred commonly during baseflow conditions, indicating chronic environmental TP exposures to aquatic organisms and the likely importance of groundwater as a TP source. Hazard quotients based on acute aquatic-life benchmarks for invertebrates and nonvascular plants and vertebrate-centric molecular endpoints (sublethal effects) quantify the range of the potential contribution of TPs to environmental risk and highlight several TP exposure–response data gaps. A precautionary approach using equimolar substitution of parent benchmarks or endpoints for missing TP benchmarks indicates that potential aquatic effects of pesticide TPs could be underestimated by an order of magnitude or more.</span></p>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.0c06625","usgsCitation":"Mahler, B., Nowell, L.H., Sandstrom, M.W., Bradley, P., Romanok, K., Konrad, C., and Van Metre, P., 2021, Inclusion of pesticide transformation products is key to estimating pesticide exposures and effects in small U.S. streams: Environmental Science and Technology, v. 55, no. 8, p. 4740-4752, https://doi.org/10.1021/acs.est.0c06625.","productDescription":"13 p.","startPage":"4740","endPage":"4752","ipdsId":"IP-122426","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":384587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n          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,{"id":70222351,"text":"70222351 - 2021 - Commentary: The role of geodetic algorithms for earthquake early warning in Cascadia","interactions":[],"lastModifiedDate":"2021-07-22T13:59:59.372252","indexId":"70222351","displayToPublicDate":"2021-03-10T08:55:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Commentary: The role of geodetic algorithms for earthquake early warning in Cascadia","docAbstract":"<p><span>The ShakeAlert earthquake early warning (EEW) system issues public alerts in California and will soon extend to Oregon and Washington. The Cascadia subduction zone presents significant new challenges and opportunities for EEW. Initial publications suggested that EEW algorithms based on Global Navigation Satellite System (GNSS) data could provide improved warning for intraslab events and dramatically improved warning for offshore megathrust events, both of which contribute significantly to hazard in Cascadia. We find that some expectations in these publications were unrealistic, and we demonstrate that in general geodetic algorithms would not produce timely warnings for intraslab events nor warning times of two minutes or more for severe shaking from megathrust earthquakes. Nonetheless, lessons from recent earthquakes in Japan and California, for which alerts from seismic algorithms suffered from magnitude saturation and high data latencies, demonstrate the urgent need for rigorous testing of geodetic EEW as a potential complement to seismic EEW.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL092324","usgsCitation":"McGuire, J., Minson, S.E., Murray, J.R., and Brooks, B.A., 2021, Commentary: The role of geodetic algorithms for earthquake early warning in Cascadia: Geophysical Research Letters, v. 48, no. 6, e2020GL092324, 8 p., https://doi.org/10.1029/2020GL092324.","productDescription":"e2020GL092324, 8 p.","ipdsId":"IP-124207","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":453140,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doaj.org/article/246a522b3bb74e70a3b0d13a73e6fca6","text":"Publisher Index Page"},{"id":387379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Cascadia subduction zone","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -128.84765625,\n              37.16031654673677\n            ],\n            [\n              -119.88281249999999,\n              37.16031654673677\n            ],\n            [\n              -119.88281249999999,\n              48.748945343432936\n            ],\n            [\n              -128.84765625,\n              48.748945343432936\n            ],\n            [\n              -128.84765625,\n              37.16031654673677\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"48","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":219786,"corporation":false,"usgs":true,"family":"McGuire","given":"Jeffrey J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":819728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":819729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murray, Jessica R. 0000-0002-6144-1681 jrmurray@usgs.gov","orcid":"https://orcid.org/0000-0002-6144-1681","contributorId":2759,"corporation":false,"usgs":true,"family":"Murray","given":"Jessica","email":"jrmurray@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":819730,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brooks, Benjamin A. 0000-0001-7954-6281 bbrooks@usgs.gov","orcid":"https://orcid.org/0000-0001-7954-6281","contributorId":5237,"corporation":false,"usgs":true,"family":"Brooks","given":"Benjamin","email":"bbrooks@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":819731,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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