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However, the dynamics of fish populations are highly complex, and phenotypes can be influenced by many biotic and abiotic factors. Therefore, it is vital to collect robust data and explore multiple alternative hypotheses before concluding that fish populations are influenced by harvest. In their recently published manuscript, Bowles et al, Evolutionary Applications, 13(6):1128 conducted age/growth and genomic analysis of walleye (<i>Sander vitreus</i>) populations sampled 13–15&nbsp;years (1–2.5 generations) apart and hypothesized that observed phenotypic and genomic changes in this time period were likely due to harvest. Specifically, Bowles et al. (2020) documented differential declines in size-at-age in three exploited walleye populations compared to a separate, but presumably less-exploited, reference population. Additionally, they documented population genetic differentiation in one population pair, homogenization in another, and outlier loci putatively under selection across time points. Based on their phenotypic and genetic results, they hypothesized that selective harvest had led to fisheries-induced evolution (referred to as nascent changes) in the exploited populations in as little as 1–2.5 generations. We re-analyzed their data and found that (a) sizes declined across both exploited and reference populations during the time period studied and (b) observed genomic differentiation in their study was the result of inadequate data filtering, including retaining individuals with high amounts of missing data and retaining potentially undersplit and oversplit loci that created false signals of differentiation between time points. This re-analysis did not provide evidence for phenotypic or genetic changes attributable to harvest in any of the study populations, contrasting the hypotheses presented by Bowles et al. (2020). Our comment highlights the potential pitfalls associated with conducting age/growth analyses with low sample sizes and inadequately filtering genomic datasets.</p>","language":"English","publisher":"Wiley","doi":"10.1111/eva.13122","usgsCitation":"Larson, W., Isermann, D.A., and Feiner, Z.S., 2021, Incomplete bioinformatic filtering and inadequate age and growth analysis lead to an incorrect inference of harvested-induced changes: Evolutionary Applications, v. 14, no. 2, p. 278-289, https://doi.org/10.1111/eva.13122.","productDescription":"12 p.","startPage":"278","endPage":"289","ipdsId":"IP-120146","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":453614,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.13122","text":"Publisher Index 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,{"id":70230046,"text":"70230046 - 2021 - Breeding at higher latitude is associated with higher photoperiodic threshold and delayed reproductive development in a songbird","interactions":[],"lastModifiedDate":"2022-03-28T14:01:45.786634","indexId":"70230046","displayToPublicDate":"2021-02-01T08:50:10","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1907,"text":"Hormones and Behavior","active":true,"publicationSubtype":{"id":10}},"title":"Breeding at higher latitude is associated with higher photoperiodic threshold and delayed reproductive development in a songbird","docAbstract":"<p id=\"sp0040\">Many seasonally breeding animals exhibit a threshold day length (critical photoperiod; CPP) for gonadal growth, and populations breeding at higher latitudes typically have a higher CPP. Much less is known about latitudinal variation in CPP in migratory population that winter away from their breeding range and must time their reproduction to match favorable conditions at their destination. To address the relationship between migration, breeding latitude, and CPP, we held two closely related songbird populations in a common environment. One population is resident (<i>Junco hyemalis carolinensis</i>), the other winters in sympatry with the residents but migrates north to breed (<i>Junco hyemalis hyemalis</i>). We gradually increased photoperiod and measured indices of readiness to migrate (fat score, body mass) and breed (cloacal protuberance volume, baseline testosterone, and gonadotropin releasing hormone challenged testosterone). To estimate breeding latitude, we measured hydrogen isotopes in feathers grown the preceding year. As we predicted, we found a higher CPP in migrants than residents, and a higher CPP among migrants deriving from higher as opposed to lower latitudes. Migrants also terminated breeding earlier than residents, indicating a shorter breeding season. To our knowledge, this is a first demonstration of latitudinal variation in CPP-dependent reproductive timing in bird populations that co-exist in the non-breeding season but breed at different latitudes. We conclude that bird populations appear to exhibit local adaptation in reproductive timing by relying on differential CPP response that is predictive of future conditions on the breeding ground.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.yhbeh.2020.104907","usgsCitation":"Singh, D., Reed, S.M., Kimmitt, A., Alford, K.A., Stricker, C.A., Polly, P., and Ketterson, E.D., 2021, Breeding at higher latitude is associated with higher photoperiodic threshold and delayed reproductive development in a songbird: Hormones and Behavior, v. 128, 104907, 11 p., https://doi.org/10.1016/j.yhbeh.2020.104907.","productDescription":"104907, 11 p.","ipdsId":"IP-114613","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":397700,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","city":"Bloomington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -86.63818359375,\n              39.106886525487596\n            ],\n            [\n              -86.4510726928711,\n              39.106886525487596\n            ],\n            [\n              -86.4510726928711,\n              39.22959375247292\n            ],\n            [\n              -86.63818359375,\n              39.22959375247292\n            ],\n            [\n              -86.63818359375,\n              39.106886525487596\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"128","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Singh, Devraj","contributorId":289296,"corporation":false,"usgs":false,"family":"Singh","given":"Devraj","email":"","affiliations":[{"id":37145,"text":"Indiana University","active":true,"usgs":false}],"preferred":false,"id":838891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, S. M.","contributorId":289298,"corporation":false,"usgs":false,"family":"Reed","given":"S.","email":"","middleInitial":"M.","affiliations":[{"id":37145,"text":"Indiana University","active":true,"usgs":false}],"preferred":false,"id":838892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kimmitt, A. A.","contributorId":289300,"corporation":false,"usgs":false,"family":"Kimmitt","given":"A. A.","affiliations":[{"id":37145,"text":"Indiana University","active":true,"usgs":false}],"preferred":false,"id":838893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alford, K. A.","contributorId":289302,"corporation":false,"usgs":false,"family":"Alford","given":"K.","email":"","middleInitial":"A.","affiliations":[{"id":37145,"text":"Indiana University","active":true,"usgs":false}],"preferred":false,"id":838894,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":838895,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Polly, P. D.","contributorId":289305,"corporation":false,"usgs":false,"family":"Polly","given":"P. D.","affiliations":[{"id":37145,"text":"Indiana University","active":true,"usgs":false}],"preferred":false,"id":838896,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ketterson, Ellen D.","contributorId":168422,"corporation":false,"usgs":false,"family":"Ketterson","given":"Ellen","email":"","middleInitial":"D.","affiliations":[{"id":12645,"text":"Indiana University - Northwest","active":true,"usgs":false}],"preferred":false,"id":838897,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70249479,"text":"70249479 - 2021 - Volcanic seismicity beneath Chuginadak Island, Alaska (Cleveland and Tana volcanoes): Implications for magma dynamics and eruption forecasting","interactions":[],"lastModifiedDate":"2023-10-10T14:16:37.55892","indexId":"70249479","displayToPublicDate":"2021-01-30T09:10:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Volcanic seismicity beneath Chuginadak Island, Alaska (Cleveland and Tana volcanoes): Implications for magma dynamics and eruption forecasting","docAbstract":"<p><span>Cleveland and Tana are remote volcanoes located in the central Aleutian&nbsp;volcanic arc&nbsp;on the eastern end of the Islands of Four Mountains (IFM). The persistently active Mount Cleveland volcano, on the western side of Chuginadak Island, is surrounded by several closely spaced Quaternary volcanic centers including Carlisle, Herbert, Kagamil, Tana, and Uliaga, and numerous small satellite vents on Chiginadak between Cleveland and Tana. The Alaska Volcano Observatory (AVO) installed two permanent broadband&nbsp;seismometers&nbsp;on Chuginadak Island in 2014, and we operated a temporary broadband network focused on the western side of the island in 2015–2016. Collectively, these stations provided the first seismic observations of this frequently active volcano and the surrounding Holocene-aged volcanic vents. During the study period (July 2014–January 2019), eruptive activity at Cleveland was characterized by small explosions separated by periods of lava effusion that formed small domes in the volcano's summit crater. We characterize&nbsp;seismicity&nbsp;beneath Chuginadak Island through automated analysis of event waveform frequency content, development of a one-dimensional P-wave velocity model, calculation of&nbsp;earthquake hypocenters, magnitudes,&nbsp;focal mechanisms, and identification of earthquake families. This analysis reveals the full range of seismic event types expected in a highly active volcanic environment and includes Volcano-Tectonic (VT) earthquakes, Long-Period (LP) events, and explosion signals. LP events appear to cluster at shallow depth beneath the active crater of Mount Cleveland and almost all of the explosions occur without identifiable short-term (hours to days) seismic precursors. VT earthquakes beneath Mount Cleveland occur at depths of 2 to 8&nbsp;km below sea level (BSL) and range in magnitude from −0.2 to 1.8. VT focal mechanisms have horizontal P-axes that align with the regional axis of maximum stress. These observations, and a relatively slow one-dimensional&nbsp;seismic velocity&nbsp;model, are consistent with a shallow body of&nbsp;</span>magma<span>&nbsp;that is fed through a deeper conduit system. The time-history of VT earthquakes and shallow LP events suggest their occurrence may track the transfer of magma and fluids from the mid-crust to the shallow portions of the conduit system and may provide a means to anticipate future explosions and periods of dome growth. VT hypocenters also extend ~7&nbsp;km northeast of Cleveland's summit at depths of 5 to 10&nbsp;km BSL, under a group of Holocene-aged vents between Mount Cleveland and Tana. These earthquakes have vertically-oriented P-axes and a greater percentage occur in families. These observations, combined with observations of vent orientation and morphology and gas flux, suggest the area between Cleveland and Tana represents a zone of complicated volcano-tectonic interaction, similar to calderas elsewhere in the Aleutian arc. The presence of a larger volcanic system in the eastern IFM could influence&nbsp;magmatism&nbsp;and account for the multiple closely spaced volcanic centers in this region.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107182","usgsCitation":"Power, J., Roman, D., Lyons, J.J., Haney, M.M., Rasmussen, D.J., Plank, T., Nicolaysen, K., Izbekov, P., Werner, C., and Kaufman, A., 2021, Volcanic seismicity beneath Chuginadak Island, Alaska (Cleveland and Tana volcanoes): Implications for magma dynamics and eruption forecasting: Journal of Volcanology and Geothermal Research, v. 412, 107182, 18 p., https://doi.org/10.1016/j.jvolgeores.2021.107182.","productDescription":"107182, 18 p.","ipdsId":"IP-121823","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":453641,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2021.107182","text":"Publisher Index Page"},{"id":421816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Chuginadak Island, Cleveland Volcano, Tana Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -169.65098413866693,\n              52.904805932105404\n            ],\n            [\n              -169.83106863712771,\n              52.8971644246661\n            ],\n            [\n              -170.01036155537554,\n              52.86086066337441\n            ],\n            [\n              -170.01669419707966,\n              52.78767701983992\n            ],\n            [\n              -169.66364942207514,\n              52.76373370379605\n            ],\n            [\n              -169.65098413866693,\n              52.904805932105404\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"412","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Power, John 0000-0002-7233-4398","orcid":"https://orcid.org/0000-0002-7233-4398","contributorId":215240,"corporation":false,"usgs":true,"family":"Power","given":"John","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":885873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roman, Diana","contributorId":237832,"corporation":false,"usgs":false,"family":"Roman","given":"Diana","affiliations":[{"id":47620,"text":"Dept. of Terrestrial Magnetism, Carnegie Institution for Science, Washington DC 20015","active":true,"usgs":false}],"preferred":false,"id":885874,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":885875,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":885876,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rasmussen, Daniel J.","contributorId":237828,"corporation":false,"usgs":false,"family":"Rasmussen","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":47619,"text":"Lamont-Doherty Earth Observatory, Columbia University, New York, NY 10027","active":true,"usgs":false}],"preferred":false,"id":885877,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Plank, Terry","contributorId":237829,"corporation":false,"usgs":false,"family":"Plank","given":"Terry","affiliations":[{"id":47619,"text":"Lamont-Doherty Earth Observatory, Columbia University, New York, NY 10027","active":true,"usgs":false}],"preferred":false,"id":885878,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nicolaysen, K. P.","contributorId":330792,"corporation":false,"usgs":false,"family":"Nicolaysen","given":"K. P.","affiliations":[{"id":79020,"text":"Whitman College Geology Department","active":true,"usgs":false}],"preferred":false,"id":885879,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Izbekov, Pavel","contributorId":237833,"corporation":false,"usgs":false,"family":"Izbekov","given":"Pavel","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":885880,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Werner, C.","contributorId":330793,"corporation":false,"usgs":false,"family":"Werner","given":"C.","affiliations":[{"id":37768,"text":"USGS Contractor","active":true,"usgs":false}],"preferred":false,"id":885881,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kaufman, A","contributorId":330794,"corporation":false,"usgs":false,"family":"Kaufman","given":"A","email":"","affiliations":[{"id":79021,"text":"Alaska Volcano Observatory, UAFGI, Fairbanks, AK","active":true,"usgs":false}],"preferred":false,"id":885882,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70222109,"text":"70222109 - 2021 - Evaluation of a satellite-based cyanobacteria bloom detection algorithm using field-measured microcystin data","interactions":[],"lastModifiedDate":"2021-07-20T12:06:06.543146","indexId":"70222109","displayToPublicDate":"2021-01-30T07:03:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9102,"text":"Science for the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a satellite-based cyanobacteria bloom detection algorithm using field-measured microcystin data","docAbstract":"<p><span>Widespread occurrence of cyanobacterial harmful algal blooms (CyanoHABs) and the associated health effects from potential cyanotoxin exposure has led to a need for systematic and frequent screening and monitoring of lakes that are used as recreational and drinking water sources. Remote sensing-based methods are often used for synoptic and frequent monitoring of CyanoHABs. In this study, one such algorithm – a sub-component of the Cyanobacteria Index called the CI</span><sub><i>cyano</i></sub><span>, was validated for effectiveness in identifying lakes with toxin-producing blooms in 11 states across the contiguous United States over 11 bloom seasons (2005–2011, 2016–2019). A matchup data set was created using satellite data from&nbsp;<a class=\"topic-link\" title=\"Learn more about MEdium Resolution Imaging Spectrometer from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/meris\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/meris\">MEdium Resolution Imaging Spectrometer</a>&nbsp;(MERIS) and Ocean Land Colour Imager (OLCI), and nearshore, field-measured Microcystins (MCs) data as a proxy of CyanoHAB presence. While the satellite sensors cannot detect toxins, MCs are used as the indicator of health risk, and as a confirmation of cyanoHAB presence. MCs are also the most common laboratory measurement made by managers during CyanoHABs. Algorithm performance was evaluated by its ability to detect CyanoHAB ‘Presence’ or ‘Absence’, where the bloom is confirmed by the presence of the MCs. With same-day matchups, the overall accuracy of CyanoHAB detection was found to be 84% with precision and recall of 87 and 90% for bloom detection. Overall accuracy was expected to be between 77% and 87% (95% confidence) based on a bootstrapping simulation. These findings demonstrate that CI</span><sub>cyano</sub><span>&nbsp;has utility for synoptic and routine monitoring of potentially toxic cyanoHABs in lakes across the United States.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.145462","usgsCitation":"Mishra, S., Stumpf, R.P., Schaeffer, B., Werdell, P.J., Loftin, K.A., and Meredith, A., 2021, Evaluation of a satellite-based cyanobacteria bloom detection algorithm using field-measured microcystin data: Science for the Total Environment, v. 774, 145462, 12 p., https://doi.org/10.1016/j.scitotenv.2021.145462.","productDescription":"145462, 12 p.","ipdsId":"IP-124532","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":453647,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2021.145462","text":"Publisher Index Page"},{"id":387288,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"774","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mishra, Sachidananda 0000-0001-6613-3103","orcid":"https://orcid.org/0000-0001-6613-3103","contributorId":222356,"corporation":false,"usgs":false,"family":"Mishra","given":"Sachidananda","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":819557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stumpf, Richard P. 0000-0001-5531-6860","orcid":"https://orcid.org/0000-0001-5531-6860","contributorId":222357,"corporation":false,"usgs":false,"family":"Stumpf","given":"Richard","email":"","middleInitial":"P.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":819558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaeffer, Blake 0000-0001-9794-3977","orcid":"https://orcid.org/0000-0001-9794-3977","contributorId":245603,"corporation":false,"usgs":false,"family":"Schaeffer","given":"Blake","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":819559,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Werdell, P. Jeremy 0000-0002-3592-0152","orcid":"https://orcid.org/0000-0002-3592-0152","contributorId":222358,"corporation":false,"usgs":false,"family":"Werdell","given":"P.","email":"","middleInitial":"Jeremy","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":819560,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Keith A. 0000-0001-5291-876X","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":221964,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":819561,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meredith, Andrew 0000-0001-9651-7132","orcid":"https://orcid.org/0000-0001-9651-7132","contributorId":222359,"corporation":false,"usgs":false,"family":"Meredith","given":"Andrew","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":819562,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70223118,"text":"70223118 - 2021 - Knowledge inventory of foundational data products in planetary science","interactions":[],"lastModifiedDate":"2021-08-11T12:27:54.283197","indexId":"70223118","displayToPublicDate":"2021-01-29T07:26:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8607,"text":"The Planetary Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"Knowledge inventory of foundational data products in planetary science","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>Some of the key components of any Planetary Spatial Data Infrastructure (PDSI) are the data products that end-users wish to discover, access, and interrogate. One precursor to the implementation of a PSDI is a knowledge inventory that catalogs what products are available, from which data producers, and at what initially understood data qualities. We present a knowledge inventory of foundational PSDI data products: geodetic coordinate reference frames, elevation or topography, and orthoimages or orthomosaics. Additionally, we catalog the available gravity models that serve as critical data for the assessment of spatial location, spatial accuracy, and ultimately spatial efficacy. We strengthen our previously published definitions of foundational data products to assist in solidifying a common vocabulary that will improve communication about these essential data products.</p></div>","language":"English","publisher":"IOP Science","doi":"10.3847/psj/abcb94","usgsCitation":"Laura, J., and Beyer, R.A., 2021, Knowledge inventory of foundational data products in planetary science: The Planetary Science Journal, v. 2, no. 1, 18, 28 p., https://doi.org/10.3847/psj/abcb94.","productDescription":"18, 28 p.","ipdsId":"IP-115047","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":453661,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/psj/abcb94","text":"Publisher Index Page"},{"id":387838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Laura, Jason 0000-0002-1377-8159","orcid":"https://orcid.org/0000-0002-1377-8159","contributorId":222124,"corporation":false,"usgs":true,"family":"Laura","given":"Jason","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":821035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beyer, Ross A.","contributorId":264165,"corporation":false,"usgs":false,"family":"Beyer","given":"Ross","email":"","middleInitial":"A.","affiliations":[{"id":37319,"text":"SETI Institute","active":true,"usgs":false}],"preferred":false,"id":821036,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70219570,"text":"70219570 - 2021 - Comparison of detection limits estimated using single- and multi-concentration spike-based and blank-based procedures","interactions":[],"lastModifiedDate":"2021-05-27T13:23:08.289537","indexId":"70219570","displayToPublicDate":"2021-01-29T07:04:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3517,"text":"Talanta","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of detection limits estimated using single- and multi-concentration spike-based and blank-based procedures","docAbstract":"<div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\">Spike- and blank-based procedures were applied to estimate the detection limits (DLs) for example analytes from inorganic and organic methods for water samples to compare with the U.S. Environmental Protection Agency's (EPA) Method Detection Limit (MDL) procedures (revisions 1.11 and 2.0). The multi-concentration spike-based procedures ASTM Within-laboratory Critical Level (DQCALC) and EPA's Lowest Concentration Minimum Reporting Level were compared in one application, with DQCALC further applied to many methods. The blank-based DLs, MDL<sub>b99</sub><span>&nbsp;</span>(99th percentile) or MDL<sub>bY</sub><span>&nbsp;</span>(= mean blank concentration&nbsp;+&nbsp;<i>s</i>&nbsp;×&nbsp;<i>t</i>), estimated using large numbers (&gt;100) of blank samples often provide DLs that better approach or achieve the desired ≤1% false positive risk level compared to spike-based DLs. For primarily organic methods that do not provide many uncensored blank results, spike-based DQCALC or MDL rev. 2.0 are needed to simulate the blank distribution and estimate the DL. DQCALC is especially useful for estimating DLs for multi-analyte methods having very different analyte response characteristics. Time series plots of DLs estimated using different procedures reveal that DLs are dependent on the applied procedure, should not be expected to be static over time, and seem best viewed as falling over a range versus being a single value. Use of both blank- and spike-based DL procedures help inform this DL range. Data reporting conventions that censor data at a threshold and report “less than” that threshold concentration as the reporting level have unknown and potentially high false negative risk. The U.S. Geological Survey National Water Quality Laboratory's Laboratory Reporting Level (LRL) convention (applied primarily to organic methods) attempts to simultaneously minimize both the false positive and false negative risk when&nbsp;&lt;LRL is reported and data between DL and the higher LRL are allowed to be reported.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.talanta.2021.122139","usgsCitation":"Foreman, W.T., Williams, T.L., Furlong, E., Hemmerle, D., Stetson, S., Jha, V.K., Noriega, M., Decess, J.A., Reed-Parker, C., and Sandstrom, M.W., 2021, Comparison of detection limits estimated using single- and multi-concentration spike-based and blank-based procedures: Talanta, v. 228, 122139, 15 p., https://doi.org/10.1016/j.talanta.2021.122139.","productDescription":"122139, 15 p.","ipdsId":"IP-121087","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":436530,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MUSPFI","text":"USGS data release","linkHelpText":"Data from USGS National Water Quality Laboratory methods used to calculate and compare detection limits estimated using single- and multi-concentration spike-based and blank-based procedures"},{"id":385078,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"228","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Foreman, William T. 0000-0002-2530-3310 wforeman@usgs.gov","orcid":"https://orcid.org/0000-0002-2530-3310","contributorId":190786,"corporation":false,"usgs":true,"family":"Foreman","given":"William","email":"wforeman@usgs.gov","middleInitial":"T.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":814196,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Teresa Lynne 0000-0002-9507-9350","orcid":"https://orcid.org/0000-0002-9507-9350","contributorId":257407,"corporation":false,"usgs":true,"family":"Williams","given":"Teresa","email":"","middleInitial":"Lynne","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":814197,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Furlong, Edward 0000-0002-7305-4603","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":213730,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":814198,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hemmerle, Dawn 0000-0002-9495-6681","orcid":"https://orcid.org/0000-0002-9495-6681","contributorId":257409,"corporation":false,"usgs":true,"family":"Hemmerle","given":"Dawn","email":"","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":814199,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stetson, Sarah 0000-0002-4930-4748 sstetson@usgs.gov","orcid":"https://orcid.org/0000-0002-4930-4748","contributorId":216528,"corporation":false,"usgs":true,"family":"Stetson","given":"Sarah","email":"sstetson@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":814200,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jha, Virendra K. 0000-0002-1076-0738 vkjha@usgs.gov","orcid":"https://orcid.org/0000-0002-1076-0738","contributorId":257416,"corporation":false,"usgs":true,"family":"Jha","given":"Virendra","email":"vkjha@usgs.gov","middleInitial":"K.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":814205,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Noriega, Mary C 0000-0002-4426-3553","orcid":"https://orcid.org/0000-0002-4426-3553","contributorId":257413,"corporation":false,"usgs":false,"family":"Noriega","given":"Mary C","affiliations":[{"id":52011,"text":"USGS, National Water Quality Laboratory, retired","active":true,"usgs":false}],"preferred":false,"id":814201,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Decess, Jessica A 0000-0002-4202-3265","orcid":"https://orcid.org/0000-0002-4202-3265","contributorId":257414,"corporation":false,"usgs":false,"family":"Decess","given":"Jessica","email":"","middleInitial":"A","affiliations":[{"id":52014,"text":"Formerly: Cherokee Nation Technology Solutions, Denver, CO; Currently: The Medical Center of Aurora, Aurora, CO","active":true,"usgs":false}],"preferred":false,"id":814202,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reed-Parker, Carmen 0000-0001-9579-578X","orcid":"https://orcid.org/0000-0001-9579-578X","contributorId":257415,"corporation":false,"usgs":false,"family":"Reed-Parker","given":"Carmen","email":"","affiliations":[{"id":52011,"text":"USGS, National Water Quality Laboratory, retired","active":true,"usgs":false}],"preferred":false,"id":814203,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sandstrom, Mark W. 0000-0003-0006-5675 sandstro@usgs.gov","orcid":"https://orcid.org/0000-0003-0006-5675","contributorId":706,"corporation":false,"usgs":true,"family":"Sandstrom","given":"Mark","email":"sandstro@usgs.gov","middleInitial":"W.","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":37464,"text":"WMA - 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,{"id":70218170,"text":"70218170 - 2021 - Joint species distribution models of Everglades wading birds to inform restoration planning","interactions":[],"lastModifiedDate":"2023-07-07T14:08:20.276686","indexId":"70218170","displayToPublicDate":"2021-01-28T10:04:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Joint species distribution models of Everglades wading birds to inform restoration planning","docAbstract":"<p><span>Restoration of the Florida Everglades, a substantial wetland ecosystem within the United States, is one of the largest ongoing restoration projects in the world. Decision-makers and managers within the Everglades ecosystem rely on ecological models forecasting indicator wildlife response to changes in the management of water flows within the system. One such indicator of ecosystem health, the presence of wading bird communities on the landscape, is currently assessed using three species distribution models that assume perfect detection and report output on different scales that are challenging to compare against one another. We sought to use current advancements in species distribution modeling to improve models of Everglades wading bird distribution. Using a joint species distribution model that accounted for imperfect detection, we modeled the presence of nine species of wading bird simultaneously in response to annual hydrologic conditions and landscape characteristics within the Everglades system. Our resulting model improved upon the previous model in three key ways: 1) the model predicts probability of occupancy for the nine species on a scale of 0–1, making the output more intuitive and easily comparable for managers and decision-makers that must consider the responses of several species simultaneously; 2) through joint species modeling, we were able to consider rarer species within the modeling that otherwise are detected in too few numbers to fit as individual models; and 3) the model explicitly allows detection probability of species to be less than 1 which can reduce bias in the site occupancy estimates. These improvements are essential as Everglades restoration continues and managers require models that consider the impacts of water management on key indicator wildlife such as the wading bird community.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0245973","usgsCitation":"D’Acunto, L., Pearlstine, L.G., and Romanach, S., 2021, Joint species distribution models of Everglades wading birds to inform restoration planning: PLoS ONE, v. 16, no. 1, e0245973, 21 p.; Data Release, https://doi.org/10.1371/journal.pone.0245973.","productDescription":"e0245973, 21 p.; Data Release","ipdsId":"IP-119201","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":453665,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0245973","text":"Publisher Index Page"},{"id":383272,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418748,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P934K8T0","text":"EverWaders species distribution model development and output in the Greater Everglades from 2000-2009","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.419921875,\n              25.209911213827688\n            ],\n            [\n              -80.474853515625,\n              25.27450351782018\n            ],\n            [\n              -80.562744140625,\n              25.348990395713393\n            ],\n            [\n    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-80.419921875,\n              25.209911213827688\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"16","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-01-28","publicationStatus":"PW","contributors":{"authors":[{"text":"D’Acunto, Laura 0000-0001-6227-0143","orcid":"https://orcid.org/0000-0001-6227-0143","contributorId":215343,"corporation":false,"usgs":true,"family":"D’Acunto","given":"Laura","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":810303,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearlstine, Leonard G.","contributorId":34751,"corporation":false,"usgs":false,"family":"Pearlstine","given":"Leonard","email":"","middleInitial":"G.","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":810304,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanach, Stephanie 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":223479,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":810305,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70217664,"text":"sir20205121 - 2021 - Spring types and contributing aquifers from water-chemistry and multivariate statistical analyses for seeps and springs in Theodore Roosevelt National Park, North Dakota, 2018","interactions":[],"lastModifiedDate":"2021-01-28T01:29:43.632301","indexId":"sir20205121","displayToPublicDate":"2021-01-27T16:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5121","displayTitle":"Spring Types and Contributing Aquifers from Water-Chemistry and Multivariate Statistical Analyses for Seeps and Springs in Theodore Roosevelt National Park, North Dakota, 2018","title":"Spring types and contributing aquifers from water-chemistry and multivariate statistical analyses for seeps and springs in Theodore Roosevelt National Park, North Dakota, 2018","docAbstract":"<p>Water resources in Theodore Roosevelt National Park, North Dakota, support wildlife, visitors, and staff, and play a vital role in supporting the native ecology of the park. The U.S. Geological Survey, in cooperation with the National Park Service, completed field work in 2018 for a study to address concerns about water availability and possible sources of groundwater contamination for seeps and springs in Theodore Roosevelt National Park. The objective of the study was to improve hydrologic knowledge and determine the water composition of 11 seeps and springs in the park by collecting water-chemistry data at springs, streams, wells, and rain collectors.</p><p>Water samples were collected at 26 sites at springs, streams, wells, and rain collectors in the North and South Units of Theodore Roosevelt National Park. Samples in the North Unit were collected at 5 springs, 1 stream, 2 wells, and 1 rain collector. Samples in the South Unit were collected at 6 springs, 2 streams, 8 wells, and 1 rain collector. Samples from springs, streams, and wells were collected in May, July, and September 2018. Samples from rain collectors were collected when enough daily precipitation accumulated in the collectors. Sampled precipitation events during the study period were in May, June, July, August, and September 2018. Physical properties of sampled water—temperature, pH, and specific conductance—were measured in the field. Water samples were analyzed for stable isotopes of oxygen and hydrogen and for chloride concentration. Recharge rates for aquifers supplying springs were determined using precipitation volume and chloride concentrations for a 12-day period before the sample-collection date. Multivariate statistical analysis methods used on water-chemistry data included principal component analysis, cluster analysis, and end-member mixing analysis.</p><p>Water composition was used to determine the spring type and contributing aquifers for 11 springs in the North and South Units of Theodore Roosevelt National Park from analyses of water-chemistry data between May and September 2018. In the North Unit, Achenbach Spring was classified as a filtration spring with water from an unconfined part of the upper Fort Union aquifer and infiltration of precipitation. Hagen Spring, Mandal Spring, and Stevens Spring were classified as contact springs supplied by semiconfined parts of the upper Fort Union aquifer. Overlook Spring at one time may have been a natural spring or seep but now is a developed spring that behaves like a flowing artesian well completed in a confined part of the upper Fort Union aquifer. In the South Unit, six springs were classified into two spring types: filtration and contact springs. Boicourt Spring and Sheep Butte Spring were classified as filtration springs that have water supplied by unconfined parts of the upper Fort Union aquifer and infiltrated precipitation. Big Plateau Spring, Lone Tree Spring, Sheep Pasture Spring, and Southeast Corner Spring were classified as contact springs that receive waters from a semiconfined part of the upper Fort Union aquifer.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20205121","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Medler, C.J., and Eldridge, W.G., 2021, Spring types and contributing aquifers from water-chemistry and multivariate statistical analyses for seeps and springs in Theodore Roosevelt National Park, North Dakota, 2018: U.S. Geological Survey Scientific Investigations Report 2020–5121, 48 p., https://doi.org/10.3133/sir20205121.","productDescription":"Report: viii, 48 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-115769","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":382693,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5121/coverthb.jpg"},{"id":382694,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5121/sir20205121.pdf","text":"Report","size":"4.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"sir2020-5121"},{"id":382695,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS data release","linkHelpText":"USGS water data for the Nation: U.S. Geological Survey National Water Information System database"}],"country":"United States","state":"North Dakota","otherGeospatial":"Theodore Roosevelt National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.63334655761719,\n              46.87990702860922\n            ],\n            [\n              -103.29757690429686,\n              46.87990702860922\n            ],\n            [\n              -103.29757690429686,\n              47.02801434856074\n            ],\n            [\n              -103.63334655761719,\n              47.02801434856074\n            ],\n            [\n              -103.63334655761719,\n              46.87990702860922\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.48983764648438,\n              47.52832925298343\n            ],\n            [\n              -103.216552734375,\n              47.52832925298343\n            ],\n            [\n              -103.216552734375,\n              47.65428791076272\n            ],\n            [\n              -103.48983764648438,\n              47.65428791076272\n            ],\n            [\n              -103.48983764648438,\n              47.52832925298343\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.63677978515625,\n              47.22726254715105\n            ],\n            [\n              -103.60965728759764,\n              47.22726254715105\n            ],\n            [\n              -103.60965728759764,\n              47.250106104326235\n            ],\n            [\n              -103.63677978515625,\n              47.250106104326235\n            ],\n            [\n              -103.63677978515625,\n              47.22726254715105\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/dakota-water/\" data-mce-href=\"https://www.usgs.gov/centers/dakota-water/\">Dakota Water Science Center</a><br>U.S. Geological Survey<br>821 East Interstate Avenue<br>Bismarck, ND 58503<br><br>1608 Mountain View Road<br>Rapid City, SD 57702</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods for Sample Collection and Water-Chemistry Data Analysis</li><li>Water-Chemistry and Multivariate Statistical Analyses</li><li>Spring Types and Contributing Aquifers</li><li>Data and Method Limitations</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Principal Component Analysis and Cluster Analysis with Water-Chemistry Data from a 1980s National Park Service Study in Theodore Roosevelt National Park</li></ul>","publishedDate":"2021-01-27","noUsgsAuthors":false,"publicationDate":"2021-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Medler, Colton J. 0000-0001-6119-5065","orcid":"https://orcid.org/0000-0001-6119-5065","contributorId":201463,"corporation":false,"usgs":true,"family":"Medler","given":"Colton","email":"","middleInitial":"J.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809196,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eldridge, William G. 0000-0002-3562-728X","orcid":"https://orcid.org/0000-0002-3562-728X","contributorId":208529,"corporation":false,"usgs":true,"family":"Eldridge","given":"William","email":"","middleInitial":"G.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809197,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70219521,"text":"70219521 - 2021 - Stream restoration is influenced by details of engineered habitats at a headwater mine site","interactions":[],"lastModifiedDate":"2021-04-13T12:10:00.472236","indexId":"70219521","displayToPublicDate":"2021-01-27T08:31:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Stream restoration is influenced by details of engineered habitats at a headwater mine site","docAbstract":"<p><span>A lack of information regarding which ecological factors influence restoration success or failure has hindered scientifically based restoration decision-making. We focus on one headwater site to examine factors influencing divergent ecological outcomes of two post-mining stream restoration projects designed to improve instream conditions following 70 years of mining impacts. One project was designed to simulate natural stream conditions by creating a morphologically complex channel with high habitat heterogeneity (HH-reach). A second project was designed to reduce contaminants and sediment using a sand filter along a straight, armored channel, which resulted in different habitat characteristics and comparatively low habitat heterogeneity (LH-reach). Within 2 years of completion, stream habitat parameters and community composition within the HH-reach were similar to those of reference reaches. In contrast, habitat and community composition within the LH-reach differed substantially from reference reaches, even 7–8 years after project completion. We found that an interaction between low gradient and high light availability, created by the LH-reach design, facilitated a Chironomid-</span><span class=\"html-italic\">Nostoc</span><span>&nbsp;mutualism. These symbionts dominated the epilithic surface of rocks and there was little habitat for tailed frog larvae, bioavailable macroinvertebrates, and fish. After controlling for habitat quantity, potential colonizing species’ traits, and biogeographic factors, we found that habitat characteristics combined to facilitate different ecological outcomes, whereas time since treatment implementation was less influential. We demonstrate that stream communities can respond quickly to restoration of physical characteristics and increased heterogeneity, but “details matter” because interactions between the habitats we create and between the species that occupy them can be complex, unpredictable, and can influence restoration effectiveness.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/d13020048","usgsCitation":"Arkle, R.S., and Pilliod, D., 2021, Stream restoration is influenced by details of engineered habitats at a headwater mine site: Diversity, v. 13, no. 2, 48, 23 p., https://doi.org/10.3390/d13020048.","productDescription":"48, 23 p.","ipdsId":"IP-125041","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":453683,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d13020048","text":"Publisher Index Page"},{"id":385007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Meadow Creek, Stibnite Mine site","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.4230499267578,\n              44.837856183947665\n            ],\n            [\n              -115.17997741699219,\n              44.837856183947665\n            ],\n            [\n              -115.17997741699219,\n              44.967955737828085\n            ],\n            [\n              -115.4230499267578,\n              44.967955737828085\n            ],\n            [\n              -115.4230499267578,\n              44.837856183947665\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Arkle, Robert S. 0000-0003-3021-1389","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":218006,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":229349,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813923,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70217872,"text":"70217872 - 2021 - Field response and surface rupture characteristics of the 2020 M6.5 Monte Cristo Range earthquake, central Walker Lane, Nevada","interactions":[],"lastModifiedDate":"2021-03-05T21:23:20.160354","indexId":"70217872","displayToPublicDate":"2021-01-27T07:03:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Field response and surface rupture characteristics of the 2020 M6.5 Monte Cristo Range earthquake, central Walker Lane, Nevada","docAbstract":"<div class=\"article-section-wrapper js-article-section js-content-section  \"><p>The<span>&nbsp;</span><span class=\"inline-formula no-formula-id\"><span class=\"MathJax_Preview\"><span id=\"MJXp-Span-5\" class=\"MJXp-math\"><span id=\"MJXp-Span-6\" class=\"MJXp-mi MJXp-italic\">M</span></span></span></span>&nbsp;6.5 Monte Cristo Range earthquake that occurred in the central Walker Lane on 15 May 2020 was the largest earthquake in Nevada in 66 yr and resulted in a multidisciplinary scientific field response. The earthquake was the result of left‐lateral slip along largely unmapped parts of the Candelaria fault, one of a series of east–northeast‐striking faults that comprise the Mina deflection, a major right step in the north–northwest structural grain of the central Walker Lane. We describe the characteristics of the surface rupture and document distinct differences in the style and orientation of fractures produced along the 28&nbsp;km long rupture zone. Along the western part of the rupture, left‐lateral and extensional displacements occurred along northeasterly and north‐striking planes that splay off the eastern termination of the mapped Candelaria fault. To the east, extensional and right‐lateral displacements occurred along predominantly north‐striking planes that project toward well‐defined Quaternary and bedrock faults. Although, the largest left‐lateral displacement observed was<span>&nbsp;</span><span class=\"inline-formula no-formula-id\"><span class=\"MathJax_Preview\"><span id=\"MJXp-Span-7\" class=\"MJXp-math\"><span id=\"MJXp-Span-8\" class=\"MJXp-mo\">∼</span><span id=\"MJXp-Span-9\" class=\"MJXp-mn\">20</span><span id=\"MJXp-Span-10\" class=\"MJXp-mtext\">  </span><span id=\"MJXp-Span-11\" class=\"MJXp-mi\">cm</span></span></span>⁠</span>, the majority of displacements were<span>&nbsp;</span><span class=\"inline-formula no-formula-id\"><span class=\"MathJax_Preview\"><span id=\"MJXp-Span-12\" class=\"MJXp-math\"><span id=\"MJXp-Span-13\" class=\"MJXp-mo\">&lt;</span><span id=\"MJXp-Span-14\" class=\"MJXp-mn\">5</span><span id=\"MJXp-Span-15\" class=\"MJXp-mtext\">  </span><span id=\"MJXp-Span-16\" class=\"MJXp-mi\">cm</span></span></span></span><span>&nbsp;</span>and were distributed across broad zones up to 800&nbsp;m wide, which are not likely to be preserved in the geologic record. The complex pattern of surface rupture is consistent with a network of faults defined in the shallow subsurface by aftershock seismicity and suggests that slip partitioning between east‐striking left‐lateral faults and north to northwest‐striking right‐lateral faults plays an important role in accommodating northwest‐directed transtension in the central Walker Lane.</p></div>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220200371","usgsCitation":"Koehler, R.D., Dee, S., Elliott, A.J., Hatem, A.E., Pickering, A., Pierce, I., and Seitz, G., 2021, Field response and surface rupture characteristics of the 2020 M6.5 Monte Cristo Range earthquake, central Walker Lane, Nevada: Seismological Research Letters, v. 92, no. 2A, p. 823-829, https://doi.org/10.1785/0220200371.","productDescription":"7 p.","startPage":"823","endPage":"829","ipdsId":"IP-123528","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":383144,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Central Walker Lane","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.14648437499999,\n              40.48038142908172\n            ],\n            [\n              -119.970703125,\n              38.92522904714054\n            ],\n            [\n              -115.83984375,\n              35.67514743608467\n            ],\n            [\n              -115.09277343749999,\n              35.53222622770337\n            ],\n            [\n              -115.48828125000001,\n              36.914764288955936\n            ],\n            [\n              -116.806640625,\n              37.89219554724437\n            ],\n            [\n              -117.7734375,\n              38.85682013474361\n            ],\n            [\n              -118.828125,\n              39.87601941962116\n            ],\n            [\n              -120.14648437499999,\n              40.48038142908172\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"92","issue":"2A","noUsgsAuthors":false,"publicationDate":"2021-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Koehler, Richard D 0000-0003-0777-6939","orcid":"https://orcid.org/0000-0003-0777-6939","contributorId":215895,"corporation":false,"usgs":false,"family":"Koehler","given":"Richard","email":"","middleInitial":"D","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":809999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dee, Seth","contributorId":248823,"corporation":false,"usgs":false,"family":"Dee","given":"Seth","email":"","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":810000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott, Austin John 0000-0001-5924-7268","orcid":"https://orcid.org/0000-0001-5924-7268","contributorId":248824,"corporation":false,"usgs":true,"family":"Elliott","given":"Austin","email":"","middleInitial":"John","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":810001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatem, Alexandra Elise 0000-0001-7584-2235","orcid":"https://orcid.org/0000-0001-7584-2235","contributorId":225597,"corporation":false,"usgs":true,"family":"Hatem","given":"Alexandra","email":"","middleInitial":"Elise","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":810002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pickering, Alexandra 0000-0002-1281-6117","orcid":"https://orcid.org/0000-0002-1281-6117","contributorId":208275,"corporation":false,"usgs":true,"family":"Pickering","given":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":810003,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pierce, Ian","contributorId":217358,"corporation":false,"usgs":false,"family":"Pierce","given":"Ian","email":"","affiliations":[{"id":39606,"text":"Univ. of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":810004,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Seitz, Gordon G.","contributorId":17303,"corporation":false,"usgs":false,"family":"Seitz","given":"Gordon G.","affiliations":[{"id":7099,"text":"Calif. Geol. Survey","active":true,"usgs":false}],"preferred":false,"id":810005,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70218175,"text":"70218175 - 2021 - Native American fire management at an ancient wildland–urban interface in the Southwest United States","interactions":[],"lastModifiedDate":"2021-02-15T15:43:28.004603","indexId":"70218175","displayToPublicDate":"2021-01-26T09:38:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Native American fire management at an ancient wildland–urban interface in the Southwest United States","docAbstract":"<p><span>The intersection of expanding human development and wildland landscapes—the “wildland–urban interface” or WUI—is one of the most vexing contexts for fire management because it involves complex interacting systems of people and nature. Here, we document the dynamism and stability of an ancient WUI that was apparently sustainable for more than 500 y. We combine ethnography, archaeology, paleoecology, and ecological modeling to infer intensive wood and fire use by Native American ancestors of Jemez Pueblo and the consequences on fire size, fire–climate relationships, and fire intensity. Initial settlement of northern New Mexico by Jemez farmers increased fire activity within an already dynamic landscape that experienced frequent fires. Wood harvesting for domestic fuel and architectural uses and abundant, small, patchy fires created a landscape that burned often but only rarely burned extensively. Depopulation of the forested landscape due to Spanish colonial impacts resulted in a rebound of fuels accompanied by the return of widely spreading, frequent surface fires. The sequence of more than 500 y of perennial small fires and wood collecting followed by frequent “free-range” wildland surface fires made the landscape resistant to extreme fire behavior, even when climate was conducive and surface fires were large. The ancient Jemez WUI offers an alternative model for fire management in modern WUI in the western United States, and possibly other settings where local management of woody fuels through use (domestic wood collecting) coupled with small prescribed fires may make these communities both self-reliant and more resilient to wildfire hazards.</span></p>","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2018733118","usgsCitation":"Roos, C., Swetnam, T.W., Ferguson, T.J., Liebmann, M.J., Loehman, R.A., Welch, J., Margolis, E.Q., Guiterman, C.H., Hockaday, W., Aiuvalasit, M., Battillo, J., Farella, J., and Kiahtipes, C., 2021, Native American fire management at an ancient wildland–urban interface in the Southwest United States: Proceedings of the National Academy of Sciences, v. 4, no. 118, e2018733118, 11 p., https://doi.org/10.1073/pnas.2018733118.","productDescription":"e2018733118, 11 p.","ipdsId":"IP-122927","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":453702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2018733118","text":"Publisher Index Page"},{"id":383270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.9404296875,\n              31.353636941500987\n            ],\n            [\n              -108.19335937499999,\n              31.39115752282472\n            ],\n            [\n              -108.10546875,\n              31.728167146023935\n            ],\n            [\n              -102.919921875,\n              32.0639555946604\n            ],\n            [\n              -103.02978515625,\n              37.16031654673677\n            ],\n            [\n              -114.12597656249999,\n              37.125286284966805\n            ],\n            [\n              -114.169921875,\n              35.94243575255426\n            ],\n            [\n              -114.7412109375,\n              36.12012758978146\n            ],\n            [\n              -114.41162109375,\n              34.470335121217474\n            ],\n            [\n              -114.5654296875,\n              33.61461929233378\n            ],\n            [\n              -114.58740234375,\n              33.119150226768866\n            ],\n            [\n              -114.7412109375,\n              32.54681317351514\n            ],\n            [\n              -111.15966796875,\n              31.372399104880525\n            ],\n            [\n              -108.9404296875,\n              31.353636941500987\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"4","issue":"118","noUsgsAuthors":false,"publicationDate":"2021-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Roos, Christopher","contributorId":251699,"corporation":false,"usgs":false,"family":"Roos","given":"Christopher","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":810341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swetnam, Thomas W.","contributorId":191872,"corporation":false,"usgs":false,"family":"Swetnam","given":"Thomas","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":810342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferguson, T. J.","contributorId":251700,"corporation":false,"usgs":false,"family":"Ferguson","given":"T.","email":"","middleInitial":"J.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":810343,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liebmann, Matthew J.","contributorId":179334,"corporation":false,"usgs":false,"family":"Liebmann","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":810344,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":false,"id":810345,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Welch, John","contributorId":251701,"corporation":false,"usgs":false,"family":"Welch","given":"John","email":"","affiliations":[{"id":36678,"text":"Simon Fraser University","active":true,"usgs":false}],"preferred":false,"id":810346,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Margolis, Ellis Q. 0000-0002-0595-9005 emargolis@usgs.gov","orcid":"https://orcid.org/0000-0002-0595-9005","contributorId":173538,"corporation":false,"usgs":true,"family":"Margolis","given":"Ellis","email":"emargolis@usgs.gov","middleInitial":"Q.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":810347,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Guiterman, Christopher H.","contributorId":190553,"corporation":false,"usgs":false,"family":"Guiterman","given":"Christopher","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":810348,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hockaday, William","contributorId":251702,"corporation":false,"usgs":false,"family":"Hockaday","given":"William","email":"","affiliations":[{"id":13716,"text":"Baylor University","active":true,"usgs":false}],"preferred":false,"id":810349,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Aiuvalasit, Michael","contributorId":251703,"corporation":false,"usgs":false,"family":"Aiuvalasit","given":"Michael","email":"","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":810350,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Battillo, Jenna","contributorId":251704,"corporation":false,"usgs":false,"family":"Battillo","given":"Jenna","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":810351,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Farella, Joshua","contributorId":179332,"corporation":false,"usgs":false,"family":"Farella","given":"Joshua","email":"","affiliations":[],"preferred":false,"id":810352,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kiahtipes, Christopher","contributorId":251705,"corporation":false,"usgs":false,"family":"Kiahtipes","given":"Christopher","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":810353,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70217697,"text":"70217697 - 2021 - Quantifying nuisance ground motion thresholds for induced earthquakes","interactions":[],"lastModifiedDate":"2021-04-22T18:04:20.342226","indexId":"70217697","displayToPublicDate":"2021-01-25T07:40:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying nuisance ground motion thresholds for induced earthquakes","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>Hazards from induced earthquakes are a growing concern with a need for effective management. One aspect of that concern is the “nuisance” from unexpected ground motions, which have the potential to cause public alarm and discontent. In this article, we borrow earthquake engineering concepts to quantify the chance of building damage states and adapt them to quantify felt thresholds for induced earthquakes in the Central and Eastern United States. We compare binary data of felt or not-felt reports from the “Did You Feel It” database with ShakeMap ground motion intensity measures (IM) for ∼360 earthquakes. We use a Monte Carlo logistic regression to discern the likelihood of perceiving various degrees of felt intensity, given a particular IM. These best-fit nuisance functions are reported in this article and are readily transferable. Of the shaking types considered, we find that peak ground velocity tends to be the best predictor of a felt earthquake. We also find that felt thresholds tended to decrease with increasing earthquake magnitude, after M ∼3.9. We interpret this effect as related to the duration of the event, where events smaller than M 3.9 are perceived as “impulsive” to the human senses. Improved quantification of the nuisance from induced earthquake ground motions could be utilized in management of the public perception of their causal operations. Although aimed at anthropogenic earthquakes, thresholds we derive could be useful in other realms, such as establishing best practices and protocols for earthquake early warning.</p></div></div>","language":"English","publisher":"Sage Publications","doi":"10.1177/8755293020988025","usgsCitation":"Schultz, R., Quitoriano, V., Wald, D.J., and Beroza, G.C., 2021, Quantifying nuisance ground motion thresholds for induced earthquakes: Earthquake Spectra, v. 37, no. 2, p. 789-802, https://doi.org/10.1177/8755293020988025.","productDescription":"14 p.","startPage":"789","endPage":"802","ipdsId":"IP-118511","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":382753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Schultz, Ryan","contributorId":241702,"corporation":false,"usgs":false,"family":"Schultz","given":"Ryan","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":809279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quitoriano, Vince 0000-0003-4157-1101 vinceq@usgs.gov","orcid":"https://orcid.org/0000-0003-4157-1101","contributorId":2582,"corporation":false,"usgs":true,"family":"Quitoriano","given":"Vince","email":"vinceq@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":809280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":809281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beroza, Gregory C.","contributorId":191201,"corporation":false,"usgs":false,"family":"Beroza","given":"Gregory","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":809282,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227706,"text":"70227706 - 2021 - Drivers of site fidelity in ungulates","interactions":[],"lastModifiedDate":"2022-01-27T14:48:07.844313","indexId":"70227706","displayToPublicDate":"2021-01-22T08:31:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of site fidelity in ungulates","docAbstract":"<ol class=\"\"><li>While the tendency to return to previously visited locations—termed ‘site fidelity’—is common in animals, the cause of this behaviour is not well understood. One hypothesis is that site fidelity is shaped by an animal's environment, such that animals living in landscapes with predictable resources have stronger site fidelity. Site fidelity may also be conditional on the success of animals’ recent visits to that location, and it may become stronger with age as the animal accumulates experience in their landscape. Finally, differences between species, such as the way memory shapes site attractiveness, may interact with environmental drivers to modulate the strength of site fidelity.</li><li>We compared inter-year site fidelity in 669 individuals across eight ungulate species fitted with GPS collars and occupying a range of environmental conditions in North America and Africa. We used a distance-based index of site fidelity and tested hypothesized drivers of site fidelity using linear mixed effects models, while accounting for variation in annual range size.</li><li>Mule deer<span>&nbsp;</span><i>Odocoileus hemionus</i><span>&nbsp;</span>and moose<span>&nbsp;</span><i>Alces alces</i><span>&nbsp;</span>exhibited relatively strong site fidelity, while wildebeest<span>&nbsp;</span><i>Connochaetes taurinus</i><span>&nbsp;</span>and barren-ground caribou<span>&nbsp;</span><i>Rangifer tarandus granti</i><span>&nbsp;</span>had relatively weak fidelity. Site fidelity was strongest in predictable landscapes where vegetative greening occurred at regular intervals over time (i.e. high temporal contingency). Species differed in their response to spatial heterogeneity in greenness (i.e. spatial constancy). Site fidelity varied seasonally in some species, but remained constant over time in others. Elk employed a ‘win-stay, lose-switch’ strategy, in which successful resource tracking in the springtime resulted in strong site fidelity the following spring. Site fidelity did not vary with age in any species tested.</li><li>Our results provide support for the environmental hypothesis, particularly that regularity in vegetative phenology shapes the strength of site fidelity at the inter-annual scale. Large unexplained differences in site fidelity suggest that other factors, possibly species-specific differences in attraction to known sites, contribute to variation in the expression of this behaviour.</li><li>Understanding drivers of variation in site fidelity across groups of organisms living in different environments provides important behavioural context for predicting how animals will respond to environmental change.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2656.13425","usgsCitation":"Morrison, T., Merkle, J.A., Hopcraft, J., Aikens, E.O., Beck, J., Boone, R., Courtemanch, A.B., Dwinnell, S.P., Fairbanks, W.S., Griffith, B., Middleton, A.D., Monteith, K.L., Oates, B., Riotte-Lambert, L., Sawyer, H., Smith, K.T., Stabach, J.A., Taylor, K.L., and Kauffman, M., 2021, Drivers of site fidelity in ungulates: Journal of Animal Ecology, v. 90, no. 4, p. 955-966, https://doi.org/10.1111/1365-2656.13425.","productDescription":"12 p.","startPage":"955","endPage":"966","ipdsId":"IP-076551","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":453752,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.13425","text":"Publisher Index Page"},{"id":394967,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Morrison, Thomas A.","contributorId":272238,"corporation":false,"usgs":false,"family":"Morrison","given":"Thomas A.","affiliations":[{"id":56374,"text":"ug","active":true,"usgs":false}],"preferred":false,"id":831844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merkle, Jerod A.","contributorId":272239,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod","email":"","middleInitial":"A.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":831845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hopcraft, J. Grant C.","contributorId":272240,"corporation":false,"usgs":false,"family":"Hopcraft","given":"J. Grant C.","affiliations":[{"id":56374,"text":"ug","active":true,"usgs":false}],"preferred":false,"id":831846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aikens, Ellen O.","contributorId":272241,"corporation":false,"usgs":false,"family":"Aikens","given":"Ellen","email":"","middleInitial":"O.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":831847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beck, Jeffrey","contributorId":272242,"corporation":false,"usgs":false,"family":"Beck","given":"Jeffrey","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":831848,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boone, Randall","contributorId":121404,"corporation":false,"usgs":true,"family":"Boone","given":"Randall","email":"","affiliations":[],"preferred":false,"id":831953,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Courtemanch, Alyson B.","contributorId":198651,"corporation":false,"usgs":false,"family":"Courtemanch","given":"Alyson","email":"","middleInitial":"B.","affiliations":[{"id":35682,"text":"Wyoming Game and Fish Department, Jackson, WY","active":true,"usgs":false}],"preferred":false,"id":831954,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dwinnell, Samantha P.","contributorId":270427,"corporation":false,"usgs":false,"family":"Dwinnell","given":"Samantha","email":"","middleInitial":"P.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":831955,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fairbanks, W. Sue","contributorId":145758,"corporation":false,"usgs":false,"family":"Fairbanks","given":"W.","email":"","middleInitial":"Sue","affiliations":[{"id":16230,"text":"Department of Natural Resource Ecology and Management, Iowa State University, 339 Science Hall II, Ames, Iowa 50011","active":true,"usgs":false}],"preferred":false,"id":831956,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Griffith, Brad 0000-0001-8698-6859","orcid":"https://orcid.org/0000-0001-8698-6859","contributorId":82571,"corporation":false,"usgs":true,"family":"Griffith","given":"Brad","email":"","affiliations":[{"id":108,"text":"Alaska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":true,"id":831957,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Middleton, Arthur D.","contributorId":264420,"corporation":false,"usgs":false,"family":"Middleton","given":"Arthur","email":"","middleInitial":"D.","affiliations":[{"id":54468,"text":"uc","active":true,"usgs":false}],"preferred":true,"id":831958,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Monteith, Kevin L.","contributorId":83400,"corporation":false,"usgs":true,"family":"Monteith","given":"Kevin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":831959,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Oates, Brendan","contributorId":200235,"corporation":false,"usgs":false,"family":"Oates","given":"Brendan","affiliations":[],"preferred":false,"id":831960,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Riotte-Lambert, Louise","contributorId":272336,"corporation":false,"usgs":false,"family":"Riotte-Lambert","given":"Louise","email":"","affiliations":[],"preferred":false,"id":831961,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sawyer, Hall","contributorId":39930,"corporation":false,"usgs":false,"family":"Sawyer","given":"Hall","affiliations":[],"preferred":false,"id":831962,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Smith, Kurt T.","contributorId":204975,"corporation":false,"usgs":false,"family":"Smith","given":"Kurt","email":"","middleInitial":"T.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":831963,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Stabach, Jared A.","contributorId":272337,"corporation":false,"usgs":false,"family":"Stabach","given":"Jared","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":831964,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Taylor, Kaitlyn L.","contributorId":272342,"corporation":false,"usgs":false,"family":"Taylor","given":"Kaitlyn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":831965,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"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":831843,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}}
,{"id":70218015,"text":"70218015 - 2021 - Trends in precipitation chemistry across the U.S. 1985–2017: Quantifying the benefits from 30 years of Clean Air Act amendment regulation","interactions":[],"lastModifiedDate":"2021-02-12T13:30:36.619989","indexId":"70218015","displayToPublicDate":"2021-01-20T07:22:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":924,"text":"Atmospheric Environment","active":true,"publicationSubtype":{"id":10}},"title":"Trends in precipitation chemistry across the U.S. 1985–2017: Quantifying the benefits from 30 years of Clean Air Act amendment regulation","docAbstract":"<p id=\"abspara0010\">Acid rain was first recognized in the 1970s in North America and Europe as an atmospheric pollutant that was causing harm to ecosystems. In response, the U.S. Congress enacted Title IV of the Clean Air Act Amendments (CAA) in 1990 to reduce sulfur and nitrogen emissions from fossil fuel burning power plants. This study reports trends in wet-precipitation chemistry in response to emissions reductions implemented as part of the CAA. Trends were calculated for sulfate (SO<sub>4</sub>), nitrate (NO<sub>3</sub>) and ammonium (NH<sub>4</sub>) from 1985 to 2017&nbsp;at 168 stations operated by the National Atmospheric Deposition Program (NADP); stations were divided into 9 regions across the United States. Trend analyses were conducted for three time periods: Period 1 (1985–1999), Period 2 (2000–2017), and the entire study period (1985–2017). Seasonal and regional Kendall trend analyses reveal significant decreasing trends in mean wet-precipitation SO<sub>4</sub><span>&nbsp;</span>concentrations in all 9 regions during the entire study period. The largest decreasing trends in monthly mean SO<sub>4</sub><span>&nbsp;</span>precipitation-weighted concentrations were measured in the Mid-Atlantic (−1.29&nbsp;μeq/l/yr), Midwest (−1.15&nbsp;μeq/l/yr), and Northeast regions (−1.10&nbsp;μeq/l/yr). The trends in monthly mean NO<sub>3</sub><span>&nbsp;</span>concentrations were not as strong as those for SO<sub>4</sub>, but all of the regions had significant decreasing trends in NO<sub>3</sub><span>&nbsp;</span>and again the Mid-Atlantic (−0.53&nbsp;μeq/l/yr), Midwest (−0.44&nbsp;μeq/l/yr), and Northeast regions (−0.50&nbsp;μeq/l/yr) had the strongest trends. Trends were steepest during Period 2 for SO<sub>4</sub><span>&nbsp;</span>and NO<sub>3</sub>, in fact for NO<sub>3</sub><span>&nbsp;</span>86% of the stations had significant decreasing trends during Period 2 while only 8% of the stations had significant decreasing trends during Period 1. The stations with the highest concentrations of SO<sub>4</sub><span>&nbsp;</span>and NO<sub>3</sub><span>&nbsp;</span>at the beginning of the study had the strongest decreasing trends and the relations were stronger during Period 2 than Period 1. For NH<sub>4</sub>, 22% of the stations had statistically significant increasing trends in concentration during Period 1. The largest increasing trends in wet-precipitation NH<sub>4</sub><span>&nbsp;</span>concentration occurred in the North-Central region during Period 1, Period 2 and throughout the entire study. By comparison, NH<sub>4</sub><span>&nbsp;</span>trends in the Rocky-North and Rocky-South regions were about half as steep and trends in the South-Central and Midwest regions were about one-third as steep.</p><p id=\"abspara0015\">We compared trends in SO<sub>4</sub><span>&nbsp;</span>and NO<sub>3</sub><span>&nbsp;</span>concentrations from NADP stations to emissions of sulfur dioxide and nitrogen oxides, respectively to determine whether there was a relation between emissions and wet-precipitation concentration trends within proximity to NADP stations. There was a statistically significant relation (r<sup>2</sup>&nbsp;=&nbsp;0.62–0.69, p&nbsp;&lt;&nbsp;0.01) between the trend in SO<sub>4</sub><span>&nbsp;</span>concentrations at individual NADP stations and total and mean sulfur dioxide (SO<sub>2</sub>) emissions from power plants within a range of 750&nbsp;km and 1000&nbsp;km from each station. There were also significant relations between NO<sub>3</sub><span>&nbsp;</span>concentration trends at NADP stations and power plant emissions of nitrogen oxides, but they were not nearly as strong (r<sup>2</sup>&nbsp;=&nbsp;0.18–0.36, p&nbsp;&lt;&nbsp;0.01) as those for SO<sub>4</sub><span>&nbsp;</span>and were strongest for emissions within a range of 1000&nbsp;km and 1500&nbsp;km from each NADP station. Decreases in wet-precipitation SO<sub>4</sub><span>&nbsp;</span>concentrations were more consistent across regions and through time than decreases in NO<sub>3</sub><span>&nbsp;</span>and SO<sub>4</sub><span>&nbsp;</span>trends were more closely linked to stationary emissions sources than NO<sub>3</sub><span>&nbsp;</span>trends. There were statistically significant increases in NH<sub>4</sub><span>&nbsp;</span>wet-precipitation concentrations, as have been reported in previous studies, but this study found that those increases were strongest during Period 1 and were not consistent across the United States. During the first 3 years of the study period, wet-precipitation acidity was dominated by SO<sub>4</sub><span>&nbsp;</span>in 8 of the 9 regions; by 2017 NO<sub>3</sub><span>&nbsp;</span>dominated the acidity of wet-precipitation in 7 of the 9 regions. There has also been a downward shift in the NO<sub>3</sub>:NH<sub>4</sub><span>&nbsp;</span>ratio of wet-precipitation as the emissions of nitrogen oxides have declined while ammonia emissions have remained essentially constant. This shift has resulted in an increase in wet-precipitation total nitrogen concentrations in 7 of the 9 regions and indicate that efforts to control NH<sub>3</sub><span>&nbsp;</span>emissions will become increasingly important as emissions of nitrogen oxides continue to decline.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.atmosenv.2021.118219","usgsCitation":"McHale, M., Ludtke, A., Wetherbee, G.A., Burns, D., Nilles, M., and Finkelstein, J., 2021, Trends in precipitation chemistry across the U.S. 1985–2017: Quantifying the benefits from 30 years of Clean Air Act amendment regulation: Atmospheric Environment, v. 247, 118219, 14 p., https://doi.org/10.1016/j.atmosenv.2021.118219.","productDescription":"118219, 14 p.","ipdsId":"IP-121628","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing 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\"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"247","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McHale, Michael 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":177292,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ludtke, Amy 0000-0002-5532-8391","orcid":"https://orcid.org/0000-0002-5532-8391","contributorId":250681,"corporation":false,"usgs":false,"family":"Ludtke","given":"Amy","email":"","affiliations":[{"id":50221,"text":"U.S. Geological Survey - Retired","active":true,"usgs":false}],"preferred":false,"id":810227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wetherbee, Gregory A. 0000-0002-6720-2294","orcid":"https://orcid.org/0000-0002-6720-2294","contributorId":215100,"corporation":false,"usgs":true,"family":"Wetherbee","given":"Gregory","email":"","middleInitial":"A.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":810228,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":810229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nilles, Mark A. 0000-0001-7978-9451","orcid":"https://orcid.org/0000-0001-7978-9451","contributorId":250682,"corporation":false,"usgs":false,"family":"Nilles","given":"Mark A.","affiliations":[{"id":50221,"text":"U.S. Geological Survey - Retired","active":true,"usgs":false}],"preferred":false,"id":810230,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Finkelstein, Jason S. 0000-0002-7496-7236","orcid":"https://orcid.org/0000-0002-7496-7236","contributorId":202452,"corporation":false,"usgs":true,"family":"Finkelstein","given":"Jason S.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810231,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70236990,"text":"70236990 - 2021 - Zircon surface crystallization ages for the extremely reduced magmatic products of the Millennium Eruption, Changbaishan Volcano (China/North Korea)","interactions":[],"lastModifiedDate":"2022-09-27T11:59:26.646696","indexId":"70236990","displayToPublicDate":"2021-01-20T06:55:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1848,"text":"Gondwana Research","active":true,"publicationSubtype":{"id":10}},"title":"Zircon surface crystallization ages for the extremely reduced magmatic products of the Millennium Eruption, Changbaishan Volcano (China/North Korea)","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0065\"><span>The Millennium Eruption (ME) of Changbaishan&nbsp;volcano&nbsp;(Baitoushan, Paektu) at 946&nbsp;CE (Common Era) is one of the largest explosive eruptions on Earth during&nbsp;Holocene&nbsp;times. We date unpolished&nbsp;zircon&nbsp;crystal faces from diverse ME products collected from the southern side of Changbaishan volcano where the ME pumice and welded and non-welded&nbsp;pyroclastic flow&nbsp;deposits (PFD) are better exposed. All zircons from a pumice sample of the southern&nbsp;caldera&nbsp;rim and the youngest (Group 1) zircons from a welded pumiceous PFD sample yield an isochron crystallization age of 0.7&nbsp;±&nbsp;1.8&nbsp;ka (2σ). Zircons from the welded pumiceous PFD sample yield additional two age groups at ~10&nbsp;ka and&nbsp;~&nbsp;100&nbsp;ka. Zircons from a non-welded charcoal-containing PFD have only one age population at 100&nbsp;ka. Our work shows that different eruption products from ME have different zircon surface age distributions and may tap different levels of a zoned felsic&nbsp;magma chamber. In addition, the results indicate that&nbsp;ion microprobe&nbsp;U-Th dating of zircon crystal surfaces from ME pumices can effectively date the Millennium eruption age. Previously reported zircon U-series ages for Qixangzhan eruption (12.2&nbsp;±&nbsp;1.1&nbsp;ka, 2σ) and Yuanchi eruption (7.3&nbsp;±&nbsp;1.8&nbsp;ka, 2σ) at Changbaishan are also likely to date their respective eruption ages. The occurrence of 100&nbsp;ka zircons in welded and non-welded PFDs reveals an important magmatic event for the Changbaishan volcano. Zircon and Fe-rich&nbsp;clinopyroxene&nbsp;crystallized at similar temperature at 770–750&nbsp;°C, indicative of early zircon crystallization in peralkaline&nbsp;magmas. Another important result is the extremely low oxygen fugacity (fO</span><sub>2</sub>&nbsp;=&nbsp;ΔFMQ-2) of the Changbaishan samples. Minerals in ME magmas were crystallized under some of the most reducing magmatic environments on Earth. Highly reducing conditions of magmas from Changbaishan supports a continental rift setting and argues against significant involvements of subduction-related oxidizing fluids during magma genesis.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gr.2021.01.003","usgsCitation":"Zou, H., Vazquez, J.A., Zhao, Y., and Guo, Z., 2021, Zircon surface crystallization ages for the extremely reduced magmatic products of the Millennium Eruption, Changbaishan Volcano (China/North Korea): Gondwana Research, v. 92, p. 172-183, https://doi.org/10.1016/j.gr.2021.01.003.","productDescription":"12 p.","startPage":"172","endPage":"183","ipdsId":"IP-124979","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":407390,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China, North Korea","otherGeospatial":"Changbaishan Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              127.7490234375,\n              41.60722821271717\n            ],\n            [\n              128.759765625,\n              41.60722821271717\n            ],\n            [\n              128.759765625,\n              42.261049162113856\n            ],\n            [\n              127.7490234375,\n              42.261049162113856\n            ],\n            [\n              127.7490234375,\n              41.60722821271717\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"92","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zou, Haibo 0000-0001-5825-2428","orcid":"https://orcid.org/0000-0001-5825-2428","contributorId":245380,"corporation":false,"usgs":false,"family":"Zou","given":"Haibo","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":852947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":852948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhao, Yongwei 0000-0002-9466-3571","orcid":"https://orcid.org/0000-0002-9466-3571","contributorId":296948,"corporation":false,"usgs":false,"family":"Zhao","given":"Yongwei","email":"","affiliations":[{"id":49174,"text":"China Earthquake Administration","active":true,"usgs":false}],"preferred":false,"id":852949,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guo, Zipei","contributorId":296949,"corporation":false,"usgs":false,"family":"Guo","given":"Zipei","email":"","affiliations":[{"id":64250,"text":"Northwest University, Xi'an, China","active":true,"usgs":false}],"preferred":false,"id":852950,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70228723,"text":"70228723 - 2021 - Aural and visual detection of greater sage-grouse leks: Implications for population trend estimates","interactions":[],"lastModifiedDate":"2022-02-17T15:36:42.580927","indexId":"70228723","displayToPublicDate":"2021-01-19T09:28:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Aural and visual detection of greater sage-grouse leks: Implications for population trend estimates","docAbstract":"<p><span>Counts of greater sage-grouse (</span><i>Centrocercus urophasianus</i><span>) at leks have been used in harvest management, Endangered Species Act listing decisions, and land management policies for over half a century. Lek count sampling methods focus on counting male sage-grouse at known leks, primarily those observed visually from roads or vantage points, but leks are likely missed that are unknown prior to the survey and are difficult to detect while driving between known lek sites. One way to ameliorate this shortfall may be to conduct short point-count surveys at multiple stops along lek-survey routes or while driving between lek counts, thereby detecting newly established or unknown leks. To evaluate the feasibility of this approach, we estimated aural and visual detection probability of active sage-grouse leks during 1-minute point-count surveys at known distances and examined the effects of environmental factors on aural lek detection in southern Idaho, USA, 2016–2017. Our results demonstrate that field observers can aurally detect sage-grouse leks at approximately 3 times greater distances compared to detecting leks visually. The probability of hearing an active lek was highest near the peak of male and female attendance (8 Apr), within an hour of sunrise, on relatively calm and cold days, when the observer was at a higher elevation relative to the lek, and during conditions with no background noise. Detection probability declined with distance and the probability of aural detection was 0.59 at 1 km from a lek when other variables were held at their means. Hence, conducting ≥3 1-minute surveys along a lek route would be expected to detect ≥93% of all leks within 1.5 km of each survey under the average environmental conditions in our study. Our results suggest that surveys could greatly improve detection of unknown or newly established leks and can facilitate a more accurate assessment of sage-grouse population trends through lek counts. Moreover, our results demonstrate how environmental factors influence the detection of leks during surveys, and therefore which variables should be considered for inclusion in any future revisions of lek count protocols or in analyses of lek count data.&nbsp;</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21991","usgsCitation":"Riley, I., Conway, C.J., Stevens, B., and Roberts, S., 2021, Aural and visual detection of greater sage-grouse leks: Implications for population trend estimates: Journal of Wildlife Management, v. 85, no. 3, p. 508-519, https://doi.org/10.1002/jwmg.21991.","productDescription":"12 p.","startPage":"508","endPage":"519","ipdsId":"IP-113780","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":396102,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","county":"Bingham County, Blaine County, Butte County","otherGeospatial":"Big Desert area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.2855224609375,\n              43.04681263770761\n            ],\n            [\n              -112.78839111328125,\n              43.04681263770761\n            ],\n            [\n              -112.78839111328125,\n              43.42699324866588\n            ],\n            [\n              -113.2855224609375,\n              43.42699324866588\n            ],\n            [\n              -113.2855224609375,\n              43.04681263770761\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"85","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-01-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Riley, Ian P.","contributorId":279604,"corporation":false,"usgs":false,"family":"Riley","given":"Ian P.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":835200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":835199,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stevens, Bryan S.","contributorId":275853,"corporation":false,"usgs":false,"family":"Stevens","given":"Bryan S.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":835201,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roberts, Shane","contributorId":279606,"corporation":false,"usgs":false,"family":"Roberts","given":"Shane","affiliations":[{"id":56023,"text":"idfg","active":true,"usgs":false}],"preferred":false,"id":835202,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70217336,"text":"70217336 - 2021 - Habitat features predict carrying capacity of a recovering marine carnivore","interactions":[],"lastModifiedDate":"2021-01-18T17:12:30.706481","indexId":"70217336","displayToPublicDate":"2021-01-15T11:07:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Habitat features predict carrying capacity of a recovering marine carnivore","docAbstract":"<p><span>The recovery of large carnivore species from over‐exploitation can have socioecological effects; thus, reliable estimates of potential abundance and distribution represent a valuable tool for developing management objectives and recovery criteria. For sea otters (</span><i>Enhydra lutris</i><span>), as with many apex predators, equilibrium abundance is not constant across space but rather varies as a function of local habitat quality and resource dynamics, thereby complicating the extrapolation of carrying capacity (</span><i>K</i><span>) from one location to another. To overcome this challenge, we developed a state‐space model of density‐dependent population dynamics in southern sea otters (</span><i>E. l. nereis</i><span>), in which&nbsp;</span><i>K</i><span>&nbsp;is estimated as a continuously varying function of a suite of physical, biotic, and oceanographic variables, all described at fine spatial scales. We used a theta‐logistic process model that included environmental stochasticity and allowed for density‐independent mortality associated with shark bites. We used Bayesian methods to fit the model to time series of survey data, augmented by auxiliary data on cause of death in stranded otters. Our model results showed that the expected density at&nbsp;</span><i>K</i><span>&nbsp;for a given area can be predicted based on local bathymetry (depth and distance from shore), benthic substrate composition (rocky vs. soft sediments), presence of kelp canopy, net primary productivity, and whether or not the area is inside an estuary. In addition to density‐dependent reductions in growth, increased levels of shark‐bite mortality over the last decade have also acted to limit population expansion. We used the functional relationships between habitat variables and equilibrium density to project estimated values of&nbsp;</span><i>K</i><span>&nbsp;for the entire historical range of southern sea otters in California, USA, accounting for spatial variation in habitat quality. Our results suggest that California could eventually support 17,226 otters (95% CrI = 9,739–30,087). We also used the fitted model to compute candidate values of optimal sustainable population abundance (OSP) for all of California and for regions within California. We employed a simulation‐based approach to determine the abundance associated with the maximum net productivity level (MNPL) and propose that the upper quartile of the distribution of MNPL estimates (accounting for parameter uncertainty) represents an appropriate threshold value for OSP. Based on this analysis, we suggest a candidate value for OSP (for all of California) of 10,236, which represents 59.4% of projected&nbsp;</span><i>K</i><span>.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21985","usgsCitation":"Tinker, M., Yee, J.L., Laidre, K.L., Hatfield, B.B., Harris, M.D., Tomoleoni, J.A., Bell, T.W., Saarman, E., Carswell, L., and Miles, A.K., 2021, Habitat features predict carrying capacity of a recovering marine carnivore: Journal of Wildlife Management, v. 85, no. 2, p. 303-323, https://doi.org/10.1002/jwmg.21985.","productDescription":"21 p.","startPage":"303","endPage":"323","ipdsId":"IP-122195","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":453835,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21985","text":"Publisher Index Page"},{"id":382279,"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              -118.27880859375001,\n              33.815666308702774\n            ],\n            [\n              -118.740234375,\n              34.125447565116126\n            ],\n            [\n              -119.091796875,\n              34.23451236236987\n            ],\n            [\n              -119.61914062499999,\n              34.50655662164561\n            ],\n            [\n              -120.36621093749999,\n              34.56085936708384\n            ],\n            [\n              -120.69580078125001,\n              35.31736632923788\n            ],\n            [\n              -121.728515625,\n              36.474306755095235\n            ],\n            [\n              -121.70654296874999,\n              36.94989178681327\n            ],\n            [\n              -122.34374999999999,\n              37.43997405227057\n            ],\n            [\n              -121.75048828124999,\n              37.54457732085582\n            ],\n            [\n              -121.97021484374999,\n              37.96152331396614\n            ],\n            [\n              -120.7177734375,\n              38.03078569382294\n            ],\n            [\n              -121.28906250000001,\n              38.39333888832238\n            ],\n            [\n              -122.58544921875,\n              38.238180119798635\n            ],\n            [\n              -123.06884765625,\n              38.08268954483802\n            ],\n            [\n              -122.82714843749999,\n              37.666429212090605\n            ],\n            [\n              -122.54150390625,\n              37.125286284966805\n            ],\n            [\n              -122.01416015625,\n              36.77409249464195\n            ],\n            [\n              -122.1240234375,\n              36.43896124085945\n            ],\n            [\n              -121.33300781249999,\n              35.51434313431818\n            ],\n            [\n              -120.87158203125,\n              34.88593094075317\n            ],\n            [\n              -120.78369140624999,\n              34.470335121217474\n            ],\n            [\n              -120.12451171875,\n              33.687781758439364\n            ],\n            [\n              -118.27880859375001,\n              33.815666308702774\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"85","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Tinker, M. 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,{"id":70217337,"text":"70217337 - 2021 - Assessing the impact of drought on arsenic exposure from private domestic wells in the conterminous United States","interactions":[],"lastModifiedDate":"2021-02-04T14:31:23.035113","indexId":"70217337","displayToPublicDate":"2021-01-13T11:02:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the impact of drought on arsenic exposure from private domestic wells in the conterminous United States","docAbstract":"<p><span>This study assesses the potential impact of drought on arsenic exposure from private domestic wells by using a previously developed statistical model that predicts the probability of elevated arsenic concentrations (&gt;10 μg per liter) in water from domestic wells located in the conterminous United States (CONUS). The application of the model to simulate drought conditions used systematically reduced precipitation and recharge values. The drought conditions resulted in higher probabilities of elevated arsenic throughout most of the CONUS. While the increase in the probability of elevated arsenic was generally less than 10% at any one location, when considered over the entire CONUS, the increase has considerable public health implications. The population exposed to elevated arsenic from domestic wells was estimated to increase from approximately 2.7 million to 4.1 million people during drought. The model was also run using total annual precipitation and groundwater recharge values from the year 2012 when drought existed over a large extent of the CONUS. This simulation provided a method for comparing the duration of drought to changes in the predicted probability of high arsenic in domestic wells. These results suggest that the probability of exposure to arsenic concentrations greater than 10 μg per liter increases with increasing duration of drought. These findings indicate that drought has a potentially adverse impact on the arsenic hazard from domestic wells throughout the CONUS.</span></p>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.9b05835","usgsCitation":"Lombard, M.A., Daniel, J., Jeddy, Z., Hay, L., and Ayotte, J.D., 2021, Assessing the impact of drought on arsenic exposure from private domestic wells in the conterminous United States: Environmental Science & Technology, v. 55, no. 3, p. 1822-1831, https://doi.org/10.1021/acs.est.9b05835.","productDescription":"10 p.","startPage":"1822","endPage":"1831","ipdsId":"IP-109293","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":453853,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.9b05835","text":"Publisher Index Page"},{"id":436586,"rank":0,"type":{"id":30,"text":"Data 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            [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"55","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Lombard, Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":808395,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daniel, Johnni","contributorId":247808,"corporation":false,"usgs":false,"family":"Daniel","given":"Johnni","email":"","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":808396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jeddy, Zuha","contributorId":247809,"corporation":false,"usgs":false,"family":"Jeddy","given":"Zuha","email":"","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":808397,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hay, Lauren 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":205020,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":808398,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ayotte, Joseph D. 0000-0002-1892-2738 jayotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1892-2738","contributorId":149619,"corporation":false,"usgs":true,"family":"Ayotte","given":"Joseph","email":"jayotte@usgs.gov","middleInitial":"D.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808399,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70217226,"text":"70217226 - 2021 - Widespread use of the nitrification inhibitor nitrapyrin: Assessing benefits and costs to agriculture, ecosystems, and environmental health","interactions":[],"lastModifiedDate":"2021-05-03T19:21:42.325383","indexId":"70217226","displayToPublicDate":"2021-01-12T16:43:15","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":"Widespread use of the nitrification inhibitor nitrapyrin: Assessing benefits and costs to agriculture, ecosystems, and environmental health","docAbstract":"<p><span>Agricultural production and associated applications of nitrogen (N) fertilizers have increased dramatically in the last century, and current projections to 2050 show that demands will continue to increase as the human population grows. Applied in both organic and inorganic fertilizer forms, N is an essential nutrient in crop productivity. Increased fertilizer applications, however, create the potential for more N loss before plant uptake. One strategy for minimizing N loss is the use of enhanced efficiency fertilizers, fortified with a nitrification inhibitor, such as nitrapyrin. In soils and water, nitrapyrin inhibits the activity of ammonia monooxygenase, a microbial enzyme that catalyzes the first step of nitrification from ammonium to nitrite. Potential benefits of using nitrification inhibitors range from reduced nitrate leaching and nitrous oxide emissions to increased crop yield. The extent of these benefits, however, depends on environmental conditions and management practices. Thus, such benefits are not always realized. Additionally, nitrapyrin has been shown to transport off-field, and it is unknown what effects environmental nitrapyrin could have on nontarget organisms and the ecological nitrogen cycle. Here, we review the agronomic and environmental benefits and costs of nitrapyrin use and present a series of research questions and considerations to be addressed with future nitrification inhibitor research.</span></p>","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.0c05732","usgsCitation":"Woodward, E., Edwards, T.M., Givens, C.E., Kolpin, D., and Hladik, M.L., 2021, Widespread use of the nitrification inhibitor nitrapyrin: Assessing benefits and costs to agriculture, ecosystems, and environmental health: Environmental Science and Technology, v. 55, no. 3, p. 1345-1353, https://doi.org/10.1021/acs.est.0c05732.","productDescription":"9 p.","startPage":"1345","endPage":"1353","ipdsId":"IP-122016","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":382528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ja/70217226/coverthb.jpg"}],"volume":"55","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Woodward, Emily E. 0000-0001-9196-1349 ewoodward@usgs.gov","orcid":"https://orcid.org/0000-0001-9196-1349","contributorId":177364,"corporation":false,"usgs":true,"family":"Woodward","given":"Emily","email":"ewoodward@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, Thea M. 0000-0002-6176-2872","orcid":"https://orcid.org/0000-0002-6176-2872","contributorId":241635,"corporation":false,"usgs":true,"family":"Edwards","given":"Thea","email":"","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":808113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Givens, Carrie E. 0000-0003-2543-9610","orcid":"https://orcid.org/0000-0003-2543-9610","contributorId":247691,"corporation":false,"usgs":true,"family":"Givens","given":"Carrie","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808115,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":205314,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808116,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70217229,"text":"70217229 - 2021 - Comparison of specimen- and image-based morphometrics in Cisco","interactions":[],"lastModifiedDate":"2023-01-19T16:23:57.072018","indexId":"70217229","displayToPublicDate":"2021-01-12T08:14:26","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of specimen- and image-based morphometrics in Cisco","docAbstract":"<div class=\"article-section-wrapper js-article-section js-content-section  \"><p><span>Morphometric data from fish are typically generated using one of two methods: direct measurements made on a specimen or extraction of distances from a digital picture. We compared data on 12 morphometrics collected with these two methods on the same collection of Cisco&nbsp;</span><i>Coregonus artedi</i><span>&nbsp;from Lake Ontario, North America, to assess the degree of bias in measurements made directly on a specimen- vs. an image-based method. We also assessed the degree of reproducibility within the image-based method by evaluating the amount of variation between different analysts for each morphometric method. Our results indicate specific morphometrics may be more prone to bias across the two methods and between analysts. Four of 12 morphometrics evaluated showed significant deviation from a 1:1 relationship that would be expected if the imaged-based method produced accurate specimen-based measurements. Pelvic fin length and pelvic–anal fin distance had the highest between-analyst variation for image-based landmarks, indicating low reproducibility for these metrics, compared with pectoral fin or total length, which had lower between-analyst variation. Although some morphometric measurements can be accurately obtained with either method, and therefore potentially used interchangeably in studies on Cisco morphology, our findings highlight the importance of considering method bias in morphometric studies that use data collected by different methods.</span></p></div>","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/JFWM-20-029","usgsCitation":"O’Malley, B., Schmitt, J., Holden, J.P., and Weidel, B., 2021, Comparison of specimen- and image-based morphometrics in Cisco: Journal of Fish and Wildlife Management, v. 12, no. 1, p. 208-215, https://doi.org/10.3996/JFWM-20-029.","productDescription":"8 p.","startPage":"208","endPage":"215","ipdsId":"IP-118425","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":453864,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-20-029","text":"Publisher Index Page"},{"id":436587,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92B534W","text":"USGS data release","linkHelpText":"Morphometric measurements of Cisco (Coregonus artedi) from Lake Ontario 2018"},{"id":382130,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"O’Malley, Brian 0000-0001-5035-3080 bomalley@usgs.gov","orcid":"https://orcid.org/0000-0001-5035-3080","contributorId":216560,"corporation":false,"usgs":true,"family":"O’Malley","given":"Brian","email":"bomalley@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":808117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmitt, Joseph 0000-0002-8354-4067","orcid":"https://orcid.org/0000-0002-8354-4067","contributorId":221020,"corporation":false,"usgs":true,"family":"Schmitt","given":"Joseph","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":808118,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holden, Jeremy P.","contributorId":190415,"corporation":false,"usgs":false,"family":"Holden","given":"Jeremy","email":"","middleInitial":"P.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":808119,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":808120,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70263122,"text":"70263122 - 2021 - Efficient genotyping with backwards compatibility: Converting a legacy microsatellite panel for muskellunge (Esox masquinongy) to genotyping-by-sequencing chemistry","interactions":[],"lastModifiedDate":"2025-01-30T15:22:34.220838","indexId":"70263122","displayToPublicDate":"2021-01-06T09:19:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1325,"text":"Conservation Genetics Resources","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Efficient genotyping with backwards compatibility: Converting a legacy microsatellite panel for muskellunge (<i>Esox masquinongy</i>) to genotyping-by-sequencing chemistry","title":"Efficient genotyping with backwards compatibility: Converting a legacy microsatellite panel for muskellunge (Esox masquinongy) to genotyping-by-sequencing chemistry","docAbstract":"<p><span>Microsatellites have been a staple of population genetics research for over three decades, and many large datasets have been generated with these markers. Microsatellites have been used, for example, to conduct genetic monitoring and construct large multigeneration pedigrees as well as genotype thousands of individuals from a given species to create high-resolution baselines of spatial genetic structure. However, the capillary electrophoresis (CE) approach used to genotype microsatellites is inefficient compared to newer genotyping-by-sequencing (GBS) approaches, and researchers have begun transitioning away from CE. Backward compatibility between GBS and CE would facilitate a seamless transition to a more efficient chemistry, while ensuring that research based on CE panels could continue. Here, we explore the feasibility of converting a legacy panel of 15 microsatellites developed for muskellunge (</span><i>Esox masquinongy</i><span>) from CE to GBS chemistry. Muskellunge are an important sportfish in the Great Lakes region, and the existing microsatellite panel has been used to genotype thousands of samples to develop a region-wide baseline of genetic structure. We successfully converted all 15 microsatellites to GBS chemistry. GBS produced high genotyping rates (98%) and had high concordance with CE microsatellite genotypes (99%). Conversion to GBS required redesign of some primers and pairs to shorten amplicon length and adjust melting temperatures, optimization of primer concentrations, and comparisons with CE genotypes to optimize GBS genotyping parameters; however, none of these steps were especially onerous. Our results demonstrate that it is highly feasible to convert legacy CE panels to GBS, ensuring seamless continuation of important, often long-term research.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s12686-020-01185-1","usgsCitation":"Gruenthal, K., and Larson, W., 2021, Efficient genotyping with backwards compatibility: Converting a legacy microsatellite panel for muskellunge (Esox masquinongy) to genotyping-by-sequencing chemistry: Conservation Genetics Resources, v. 13, p. 151-159, https://doi.org/10.1007/s12686-020-01185-1.","productDescription":"9 p.","startPage":"151","endPage":"159","ipdsId":"IP-122376","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2021-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Gruenthal, Kristen","contributorId":349610,"corporation":false,"usgs":false,"family":"Gruenthal","given":"Kristen","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":925621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Wesley 0000-0003-4473-3401 wlarson@usgs.gov","orcid":"https://orcid.org/0000-0003-4473-3401","contributorId":199509,"corporation":false,"usgs":true,"family":"Larson","given":"Wesley","email":"wlarson@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":925620,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70217090,"text":"70217090 - 2021 - Testing which axes of species differentiation underlie covariance of phylogeographic similarity among montane sedge species","interactions":[],"lastModifiedDate":"2021-03-05T21:20:40.461814","indexId":"70217090","displayToPublicDate":"2021-01-02T06:59:51","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Testing which axes of species differentiation underlie covariance of phylogeographic similarity among montane sedge species","docAbstract":"<p><span>Co‐distributed species may exhibit similar phylogeographic patterns due to shared environmental factors or discordant patterns attributed to the influence of species‐specific traits. Although either concordant or discordant patterns could occur due to chance, stark differences in key traits (e.g., dispersal ability) may readily explain differences between species. Multiple species’ attributes may affect genetic patterns, and it is difficult to isolate the contribution of each. Here we compare the relative importance of two attributes, range size and niche breadth, in shaping the spatial structure of genetic variation in four sedge species (genus&nbsp;</span><i>Carex</i><span>) from the Rocky Mountains. Within two pairs of co‐distributed species, one species exhibits narrow niche breadth, while the other species has broad niche breadth. Furthermore, one pair of co‐distributed species has a large geographical distribution, while the other has a small distribution. The four species represent a natural experiment to tease apart how these attributes (i.e., range size and niche breadth) affect phylogeographic patterns. Investigations of genetic variation and structure revealed that range size, but not niche breadth, is related to spatial genetic covariation across species of montane sedges. Our study highlights how isolating key attributes across multiple species can inform their impact on processes driving intraspecific differentiation.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/evo.14159","usgsCitation":"Hodel, R.G., Massatti, R., Bishop, S.G., and Knowles, L.L., 2021, Testing which axes of species differentiation underlie covariance of phylogeographic similarity among montane sedge species: Molecular Ecology, v. 75, no. 23-24, p. 349-364, https://doi.org/10.1111/evo.14159.","productDescription":"16 p.","startPage":"349","endPage":"364","ipdsId":"IP-109643","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":453956,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/evo.14159","text":"External Repository"},{"id":381867,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"23-24","noUsgsAuthors":false,"publicationDate":"2021-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Hodel, Richard G.J. 0000-0002-2896-4907","orcid":"https://orcid.org/0000-0002-2896-4907","contributorId":246067,"corporation":false,"usgs":false,"family":"Hodel","given":"Richard","email":"","middleInitial":"G.J.","affiliations":[{"id":49414,"text":"Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, 48109, USA","active":true,"usgs":false}],"preferred":false,"id":807580,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Massatti, Robert 0000-0001-5854-5597","orcid":"https://orcid.org/0000-0001-5854-5597","contributorId":207294,"corporation":false,"usgs":true,"family":"Massatti","given":"Robert","email":"","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":807581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bishop, Sasha G.D.","contributorId":246068,"corporation":false,"usgs":false,"family":"Bishop","given":"Sasha","email":"","middleInitial":"G.D.","affiliations":[{"id":49414,"text":"Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, 48109, USA","active":true,"usgs":false}],"preferred":false,"id":807582,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knowles, L. Lacey","contributorId":221781,"corporation":false,"usgs":false,"family":"Knowles","given":"L.","email":"","middleInitial":"Lacey","affiliations":[{"id":40427,"text":"Department of Ecology and Evolutionary Biology, The University of Michigan, Ann Arbor, MI 41809-1079, USA","active":true,"usgs":false}],"preferred":false,"id":807583,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70215542,"text":"70215542 - 2021 - Investigation of land surface phenology detections in shrublands using multiple scale satellite data","interactions":[],"lastModifiedDate":"2024-05-17T15:52:29.667553","indexId":"70215542","displayToPublicDate":"2021-01-01T09:35:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Investigation of land surface phenology detections in shrublands using multiple scale satellite data","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0065\">Shrublands occupy about 13% of the global land surface, contain about one-third of the biodiversity, store about half of the global terrestrial carbon, and provide many ecosystem services to a large amount of world's human population and livestock. Because phenology is a sensitive indicator of the response of shrubland ecosystems to climate change, the alteration of ecosystems following species invasions, and the dynamics of shrubland ecosystem function, biodiversity, and carbon budgets, it is critical to monitor and assess phenological dynamics in shrubland ecosystems. However, most current land surface phenology (LSP) products derived from satellite data do not provide phenology detections in some semiarid shrublands where the amplitude of seasonal vegetation greenness is small. Therefore, we investigated the LSP detection using multiple spatial resolution satellite data and examined the impacts of spatial scales and shrubland ecosystem components (shrub and herb cover) on LSP detections over the western United States. Specifically, greenup onset date (GUD) in shrublands was detected from 30&nbsp;m Harmonized Landsat and Sentinel-2 (HLS) data and 500&nbsp;m Visible Infrared Imaging Radiometer Suite (VIIRS) data to quantify scale effects. The GUD spatial patterns were explored with 30&nbsp;m pixel variations in shrubland ecosystem components. The results show that GUD values varied with percent vegetation cover and shifted to earlier dates with increasing vegetation cover, demonstrating that satellite observations were not able to capture greenup onset until a threshold of green vegetation cover is reached. GUD was mostly undetectable from both HLS and VIIRS pixels with vegetation cover less than 10% and became fully detectable with vegetation covers larger than 50%. Similarly, the differences of GUD between HLS and VIIRS detections also decreased with increased vegetation cover. As a result of high shrubland heterogeneity, GUD from 30&nbsp;m HLS pixels could be partially detected within a 500&nbsp;m pixel despite GUD being undetectable from VIIRS time series. Moreover, vegetation cover heterogeneity also made it difficult for GUD at 30&nbsp;m to be aggregated to coarse scales (such as to 500&nbsp;m VIIRS pixels). These findings have significant implications to the detection and characterization of shrubland LSP responses to environmental and climate changes.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2020.112133","usgsCitation":"Peng, D., Wang, Y., Xian, G.Z., Huete, A.R., Huang, W., Shen, M., Wang, F., Yu, L., Liu, L., Xie, Q., Liu, L., and Zhang, X., 2021, Investigation of land surface phenology detections in shrublands using multiple scale satellite data: Remote Sensing of Environment, v. 252, 112133, 18 p., https://doi.org/10.1016/j.rse.2020.112133.","productDescription":"112133, 18 p.","ipdsId":"IP-122229","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":453963,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2020.112133","text":"Publisher Index Page"},{"id":379652,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.94921874999999,\n              37.579412513438385\n            ],\n            [\n              -110.91796875,\n              37.579412513438385\n            ],\n            [\n              -110.91796875,\n              41.44272637767212\n            ],\n            [\n              -117.94921874999999,\n              41.44272637767212\n            ],\n            [\n              -117.94921874999999,\n              37.579412513438385\n            ]\n          ]\n   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,{"id":70227790,"text":"70227790 - 2021 - Particle tracer analysis for submerged berm placement of dredged material near South Padre Island, Texas","interactions":[],"lastModifiedDate":"2022-01-31T15:09:18.201784","indexId":"70227790","displayToPublicDate":"2021-01-01T08:57:20","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10070,"text":"Journal of Dredging","active":true,"publicationSubtype":{"id":10}},"title":"Particle tracer analysis for submerged berm placement of dredged material near South Padre Island, Texas","docAbstract":"The fate of unconfined dredged sediment placed as a submerged “feeder” berm in the nearshore region of South Padre Island (SPI), Texas, was investigated through a particle tracer study over the duration of 15 months. Unconfined sediment feeder systems can be a desirable alternative to traditional direct beach placement of nourishment material because the feeder systems are less intrusive to the beach environment and often less expensive. Placing sediment as close to the active beach profile, as practicable, and relying on natural nearshore processes to slowly distribute the sediment to the beach can keep a finite resource within the littoral zone. One challenge with this indirect approach is predicting the short- and long-term effects on the coastal system and shoreline in light of the complex nearshore dynamics involved. This study aims at elucidating sediment transport pathways at SPI after tracer release over the feeder berm via assessment of tracer particle counts obtained from nine sediment sampling campaigns (950 surface-sediment grab samples) between August 2018 and November 2019, covering a grid of 60 seabed and 50 dry beach locations. Tracer counts were performed in the laboratory making use of the fluorescent and ferromagnetic properties of the engineered particles to separate them from other sediment material. Results indicate that although the highest tracer counts remained near the initial release site of the feeder berm during the duration of the study, appreciable amounts of tracer moved throughout the study region. Even though fluctuations of tracer migration were observed, the most prominent appearance of tracer particles outside the initial placement site occurred south and immediately west of it, indicating net alongshore and onshore transport in those directions. Relatively, few tracer particles were found on the dry beach, indicating appreciable deposition of feeder material there may take years rather than months.","language":"English","publisher":"Western Dredging Association (WEDA)","usgsCitation":"Figlus, J., Song, Y., Maglio, C.K., Friend, P.L., Poleykett, J., Engel, F.L., Schnoebelen, D.J., and Boburka, K., 2021, Particle tracer analysis for submerged berm placement of dredged material near South Padre Island, Texas: Journal of Dredging, v. 19, no. 1, p. 14-31.","productDescription":"18 p.","startPage":"14","endPage":"31","ipdsId":"IP-123798","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":395136,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":395116,"type":{"id":15,"text":"Index Page"},"url":"https://www.westerndredging.org/journal"}],"country":"United States","state":"Texas","otherGeospatial":"Gulf of Mexico, South Padre Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -97.18935012817381,\n              26.066497937896568\n            ],\n            [\n              -97.11502075195311,\n              26.066497937896568\n            ],\n            [\n              -97.11502075195311,\n              26.170074983409965\n            ],\n            [\n              -97.18935012817381,\n              26.170074983409965\n            ],\n            [\n              -97.18935012817381,\n              26.066497937896568\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"19","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Figlus, Jens","contributorId":272630,"corporation":false,"usgs":false,"family":"Figlus","given":"Jens","email":"","affiliations":[{"id":56389,"text":"Texas A&M University-Galveston","active":true,"usgs":false}],"preferred":false,"id":832256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Song, Youn-Kyung","contributorId":272631,"corporation":false,"usgs":false,"family":"Song","given":"Youn-Kyung","email":"","affiliations":[{"id":56389,"text":"Texas A&M University-Galveston","active":true,"usgs":false}],"preferred":false,"id":832257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maglio, Coraggio K.","contributorId":272632,"corporation":false,"usgs":false,"family":"Maglio","given":"Coraggio","email":"","middleInitial":"K.","affiliations":[{"id":56390,"text":"U.S. Army Corps of Engineers-Galveston District","active":true,"usgs":false}],"preferred":false,"id":832258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Friend, Patrick L.","contributorId":272633,"corporation":false,"usgs":false,"family":"Friend","given":"Patrick","email":"","middleInitial":"L.","affiliations":[{"id":56391,"text":"Partrec, Inc.","active":true,"usgs":false}],"preferred":false,"id":832259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poleykett, Jack","contributorId":272835,"corporation":false,"usgs":false,"family":"Poleykett","given":"Jack","email":"","affiliations":[{"id":56391,"text":"Partrec, Inc.","active":true,"usgs":false}],"preferred":false,"id":832307,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Engel, Frank L. 0000-0002-4253-2625","orcid":"https://orcid.org/0000-0002-4253-2625","contributorId":218208,"corporation":false,"usgs":true,"family":"Engel","given":"Frank","middleInitial":"L.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832260,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schnoebelen, Douglas James 0000-0001-7841-3188","orcid":"https://orcid.org/0000-0001-7841-3188","contributorId":240641,"corporation":false,"usgs":true,"family":"Schnoebelen","given":"Douglas","email":"","middleInitial":"James","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832261,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boburka, Kristina","contributorId":272634,"corporation":false,"usgs":false,"family":"Boburka","given":"Kristina","email":"","affiliations":[{"id":56392,"text":"City of South Padre Island, Texas","active":true,"usgs":false}],"preferred":false,"id":832262,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70218218,"text":"70218218 - 2021 - River terrace evidence of tectonic processes in the eastern North American plate interior, South Anna River, Virginia","interactions":[],"lastModifiedDate":"2021-12-10T16:22:26.132296","indexId":"70218218","displayToPublicDate":"2020-12-31T14:03:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2309,"text":"Journal of Geology","active":true,"publicationSubtype":{"id":10}},"title":"River terrace evidence of tectonic processes in the eastern North American plate interior, South Anna River, Virginia","docAbstract":"<p><span>We show that long-recognized seismicity in the central Virginia seismic zone of the eastern North American intraplate setting arises primarily from tectonic processes predicted by new, fully coupled plate tectonic geodynamic models. The study leverages much new geophysical and geologic data following the 2011 Mineral, Virginia, earthquake that ruptured a steeply dipping, northwest-verging reverse fault traversed by the South Anna River. The data are primarily assembled from a flight of six fluvial terrace geomorphic markers identified and correlated on texture, relative weathering, and numeric ages including one terrestrial cosmogenic nuclide (TCN) profile and 30 luminescence dates. Terrace thickness, stratigraphic age models, and incision rates downstream and upstream of the 2011 rupture are different. Long-term river incision rates of ∼25–30 m/My are superimposed on regional TCN-determined erosion rates of ∼8.5 m/My; however, there are at least 10 m of tectonically driven incision in the epicentral region at rates of ∼30–94 m/My. The inferred deformation resembles a hanging wall anticline above a blind reverse fault with a diffuse overlying carapace of minor brittle faults, an interpretation supported by seismology as well as bedrock and saprolite mapped across the epicentral region. These results are further supported by channel metrics that show nonuniform channel steepness (</span><i>k</i><sub>sn</sub><span>) and a predicted steady-state channel elevation different from the actual channel elevation across the epicentral region. If all of the observed deformation is a consequence of the fault that ruptured in 2011, the recurrence interval of Mineral-sized events would be ∼5.5 ky.</span></p>","language":"English","publisher":"University of Chicago Press","doi":"10.1086/712636","usgsCitation":"Pazzaglia, F.J., Malenda, H.F., McGavick, M.L., Raup, C., Carter, M.W., Berti, C., Mahan, S.A., Nelson, M., Rittenour, T.M., Counts, R., Willenbring, J.K., Germanoski, D., Peters, S.C., and Holt, W.D., 2021, River terrace evidence of tectonic processes in the eastern North American plate interior, South Anna River, Virginia: Journal of Geology, v. 129, no. 5, p. 595-624, https://doi.org/10.1086/712636.","productDescription":"30 p.","startPage":"595","endPage":"624","ipdsId":"IP-116434","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science 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