Crane chicks are dependent on parent birds for provisioning during the first few months of life, but no study has examined this provisioning in detail. In 2014 research staff at the U.S. Geological Survey, Eastern Ecological Science Center (formerly Patuxent Wildlife Research Center), in Laurel, Maryland, made multiple observations of parent whooping cranes (Grus americana) feeding or interacting with their chick during the 3 months from hatching to fledging. Both parents participated in the feeding of the chick and only 1 chick was raised by each pair of parent whooping cranes. Initially feeding frequency was low (0-20 times per hr), but as the chick absorbed its yolk sac and required food, feeding frequency increased to a high of 105 times per hour. Whooping crane parents fed their chick from 0 to 105 times per hour. Feeding frequency peaked around day 19, then decreased after the chicks reached 40 days of age but continued at a low level during the entire 3 months from hatch to fledging. Because feeding frequency observed for this study was very low at fledging, the use of feeding by alloparents as a measure of chick-alloparent bond may not be practical.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the North American crane workshop","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"15th North American Crane Workshop","conferenceDate":"January 8-11, 2020","conferenceLocation":"Lubbock TX","language":"English","publisher":"North American Crane Working Group","usgsCitation":"Olsen, G.H., 2022, Observations on Whooping Crane parental provisioning of chicks, in Proceedings of the North American crane workshop, v. 15, Lubbock TX, January 8-11, 2020, p. 123-127.","productDescription":"5 p.","startPage":"123","endPage":"127","ipdsId":"IP-128271","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":411114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":411111,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.nacwg.org/publications.html","linkFileType":{"id":5,"text":"html"}}],"volume":"15","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Olsen, Glenn H. 0000-0002-7188-6203","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":238130,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":860254,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70234293,"text":"70234293 - 2022 - An assessment of uncertainties in VS profiles obtained from microtremor observations in the phased 2018 COSMOS blind trials","interactions":[],"lastModifiedDate":"2022-09-01T14:54:40.235385","indexId":"70234293","displayToPublicDate":"2022-01-01T06:17:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"An assessment of uncertainties in VS profiles obtained from microtremor observations in the phased 2018 COSMOS blind trials","docAbstract":"Site response is a critical consideration when assessing earthquake hazards. Site characterization is key to understanding site effects as influenced by seismic site conditions of the local geology. Thus, a number of geophysical site characterization methods were developed to meet the demand for accurate and cost-effective results. As a consequence, a number of studies have been administered periodically as blind trials to evaluate the state-of-practice on-site characterization. We present results from the Consortium of Organizations for Strong Motion Observation Systems (COSMOS) blind trials, which used data recorded from surface-based microtremor array methods (MAM) at four sites where geomorphic conditions vary from deep alluvial basins to an alpine valley. Thirty-four invited analysts participated. Data were incrementally released to 17 available analysts who participated in all four phases: (1) two-station arrays, (2) sparse triangular arrays, (3) complex nested triangular or circular arrays, and (4) all available geological control site information including drill hole data. Another set of 17 analysts provided results from two sites and two phases only. Although data from one site consisted of recordings from three-component sensors, the other three sites consisted of data recorded only by vertical-component sensors. The sites cover a range of noise source distributions, ranging from one site with a highly directional microtremor wave field to others with omni-directional (azimuthally distributed) wave fields. We review results from different processing techniques (e.g., beam-forming, spatial autocorrelation, cross-correlation, or seismic interferometry) applied by the analysts and compare the effectiveness between the differing wave field distributions. We define the M index as a quality index based on estimates of the time-averaged shear-wave velocity of the upper 10 (VS10), 30 (VS30), 100 (VS100), and 300 (VS300) meters and show its usefulness in quantitative comparisons of VS profiles from multiple analysts. Our findings are expected to aid in building an evidence-based consensus on preferred cost-effective arrays and processing methodology for future studies of seismic site effects.
Cyanobacterial harmful algal blooms are an increasing threat to coastal and inland waters. These blooms can be detected using optical radiometers due to the presence of phycocyanin (PC) pigments. The spectral resolution of best-available multispectral sensors limits their ability to diagnostically detect PC in the presence of other photosynthetic pigments. To assess the role of spectral resolution in the determination of PC, a large (N = 905) database of colocated in situ radiometric spectra and PC are employed. We first examine the performance of selected widely used machine-learning (ML) models against that of benchmark algorithms for hyperspectral remote sensing reflectance ( Rrs) spectra resampled to the spectral configuration of the Hyperspectral Imager for the Coastal Ocean (HICO) with a full-width at half-maximum (FWHM) of < 6 nm. Results show that the multilayer perceptron (MLP) neural network applied to HICO spectral configurations (median errors < 65%) outperforms other ML models. This model is subsequently applied to Rrs spectra resampled to the band configuration of existing satellite instruments and of the one proposed for the next Landsat sensor. These results confirm that employing MLP models to estimate PC from hyperspectral data delivers tangible improvements compared with retrievals from multispectral data and benchmark algorithms (with median errors between ~73% and 126%) and shows promise for developing a globally applicable cyanobacteria measurement approach.
","language":"English","publisher":"IEEE","doi":"10.1109/TGRS.2021.3114635","usgsCitation":"Zolfaghari, K., Pahlevan, N., Binding, C., Gurlin, D., Simis, S.G., Verdu, A.R., Li, L., Crawford, C., VanderWoude, A., Errera, R., Zastepa, A., and Duguay, C.R., 2022, Impact of spectral resolution on quantifying cyanobacteria in lakes and reservoirs: A machine-learning assessment: IEEE Transactions in Geoscience and Remote Sensing, v. 60, 5515520, 20 p., https://doi.org/10.1109/TGRS.2021.3114635.","productDescription":"5515520, 20 p.","ipdsId":"IP-132686","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":449319,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1109/tgrs.2021.3114635","text":"Publisher Index Page"},{"id":390590,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zolfaghari, Kiana","contributorId":267804,"corporation":false,"usgs":false,"family":"Zolfaghari","given":"Kiana","email":"","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":825333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pahlevan, Nima","contributorId":267805,"corporation":false,"usgs":false,"family":"Pahlevan","given":"Nima","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":825334,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Binding, Caren","contributorId":267806,"corporation":false,"usgs":false,"family":"Binding","given":"Caren","affiliations":[],"preferred":false,"id":825335,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gurlin, Daniela","contributorId":267807,"corporation":false,"usgs":false,"family":"Gurlin","given":"Daniela","email":"","affiliations":[],"preferred":false,"id":825336,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Simis, Stefan G.H.","contributorId":267808,"corporation":false,"usgs":false,"family":"Simis","given":"Stefan","email":"","middleInitial":"G.H.","affiliations":[],"preferred":false,"id":825337,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Verdu, Antonio Ruiz","contributorId":267809,"corporation":false,"usgs":false,"family":"Verdu","given":"Antonio","email":"","middleInitial":"Ruiz","affiliations":[],"preferred":false,"id":825338,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Li, Lin","contributorId":267810,"corporation":false,"usgs":false,"family":"Li","given":"Lin","email":"","affiliations":[],"preferred":false,"id":825339,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crawford, Christopher J. 0000-0002-7145-0709 cjcrawford@usgs.gov","orcid":"https://orcid.org/0000-0002-7145-0709","contributorId":213607,"corporation":false,"usgs":true,"family":"Crawford","given":"Christopher J.","email":"cjcrawford@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":825340,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"VanderWoude, Andrea","contributorId":267811,"corporation":false,"usgs":false,"family":"VanderWoude","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":825341,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Errera, Reagan","contributorId":267812,"corporation":false,"usgs":false,"family":"Errera","given":"Reagan","email":"","affiliations":[],"preferred":false,"id":825342,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zastepa, Arthur","contributorId":267813,"corporation":false,"usgs":false,"family":"Zastepa","given":"Arthur","email":"","affiliations":[],"preferred":false,"id":825343,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Duguay, Claude R.","contributorId":267814,"corporation":false,"usgs":false,"family":"Duguay","given":"Claude","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":825344,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70262190,"text":"70262190 - 2022 - Broad-scale geographic and temporal assessment of northern long-eared bat (Myotis septentrionalis) maternity colony-landscape association","interactions":[],"lastModifiedDate":"2025-01-15T17:13:38.964566","indexId":"70262190","displayToPublicDate":"2022-01-01T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Broad-scale geographic and temporal assessment of northern long-eared bat (Myotis septentrionalis) maternity colony-landscape association","docAbstract":"As the federally threatened northern long-eared bat Myotis septentrionalis continues to decline due to white-nose syndrome (WNS) impacts, the application of effective conservation measures is needed but often hindered by the lack of ecological data. To date, recommended management practices have been adopted in part from other federally listed sympatric species such as the endangered Indiana bat M. sodalis. During the maternity season, these measures have largely focused on conservation of known day-roost habitat, often with little consideration for foraging habitat, particularly riparian areas. We examined acoustic activity of northern long-eared bats relative to day-roost and capture data at coastal and interior sites in the District of Columbia, New York, Pennsylvania, Virginia, and West Virginia, USA, over the course of 6 summers (2015-2020), where maternity activity was still documented after the initial arrival and spread of WNS. Acoustic activity of northern long-eared bats relative to forest cover decreased at the acoustic site level (fine scale) but increased at the sampling region level (coarse scale). We observed a positive association of northern long-eared bat acoustic activity with riparian areas. Additionally, we observed higher levels of activity during pregnancy through early lactation period of the reproductive cycle prior to juvenile volancy. Our findings suggest the need for more explicit inclusion of forested riparian habitats in northern long-eared bat conservation planning. Acoustic sampling in spring and early summer rather than mid- to late summer and in forested riparian areas is the most effective strategy for identifying potential active northern long-eared bat maternity colonies on the local landscape.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01170","usgsCitation":"Gorman, K., Deeley, S., Barr, E., Freeze, S., Kalen, N., Muthersbaugh, M., and Ford, W., 2022, Broad-scale geographic and temporal assessment of northern long-eared bat (Myotis septentrionalis) maternity colony-landscape association: Endangered Species Research, v. 77, p. 119-130, https://doi.org/10.3354/esr01170.","productDescription":"12 p.","startPage":"119","endPage":"130","ipdsId":"IP-129463","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467209,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01170","text":"Publisher Index Page"},{"id":466435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, New York, Pennsylvania, Virginia, and West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.63860968932777,\n 41.75751355656877\n ],\n [\n -79.25398225412287,\n 39.52289159017691\n ],\n [\n -77.93035543937282,\n 37.3515339549044\n ],\n [\n -75.77459039650464,\n 37.3515339549044\n ],\n [\n -75.87176521681832,\n 39.47700295265774\n ],\n [\n -74.87678100280708,\n 40.46398555372922\n ],\n [\n -73.88179678879584,\n 41.450968154800705\n ],\n [\n -76.63860968932777,\n 41.75751355656877\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"77","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gorman, Katherine M.","contributorId":348401,"corporation":false,"usgs":false,"family":"Gorman","given":"Katherine M.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":923435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deeley, Sabrina M.","contributorId":348402,"corporation":false,"usgs":false,"family":"Deeley","given":"Sabrina M.","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":923436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barr, Elaine L.","contributorId":348403,"corporation":false,"usgs":false,"family":"Barr","given":"Elaine L.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":923437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freeze, Samuel R.","contributorId":348404,"corporation":false,"usgs":false,"family":"Freeze","given":"Samuel R.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":923438,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kalen, Nicholas","contributorId":348405,"corporation":false,"usgs":false,"family":"Kalen","given":"Nicholas","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":923439,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muthersbaugh, Michael S.","contributorId":348406,"corporation":false,"usgs":false,"family":"Muthersbaugh","given":"Michael S.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":923440,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. 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As these bats become rare and difficult to capture, additional day-roost assessments to inform management may fill gaps in our understanding, particularly in habitats and regions where such roosts have never been surveyed. Over 2 summers, we radio-tracked 16 individuals from a maternity colony on Long Island, NY, in a small forested patch surrounded by development and ocean. These bats disproportionately selected small, suppressed Robinia pseudoacacia (Black Locust) trees or snags for roosting. Generally, roosts occurred within the interior or edges of this forest patch, rather than surrounding suburbia, reinforcing the hypothesis that Northern Long-eared Bats are forest adapted. Our study shows even small tracts of forest in coastal, urban areas may have conservation value in providing day-roost and foraging habitat.
","language":"English","publisher":"BioOne","doi":"10.1656/045.029.0201","usgsCitation":"Gorman, K., Barr, E., Nocera, T., and Ford, W., 2022, Characteristics of day-roosts used by the Northern Long-eared Bat (Myotis septentrionalis) in coastal New York: Northeastern Naturalist, v. 29, no. 2, p. 153-170, https://doi.org/10.1656/045.029.0201.","productDescription":"18 p.","startPage":"153","endPage":"170","ipdsId":"IP-136323","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467208,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/115419","text":"External Repository"},{"id":466440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"William Floyd Estate","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.72251752158608,\n 40.84983594633641\n ],\n [\n -72.72251752158608,\n 40.79368888019977\n ],\n [\n -72.58103774780037,\n 40.79368888019977\n ],\n [\n -72.58103774780037,\n 40.84983594633641\n ],\n [\n -72.72251752158608,\n 40.84983594633641\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gorman, Katherine M.","contributorId":348338,"corporation":false,"usgs":false,"family":"Gorman","given":"Katherine M.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":923374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barr, Elaine L.","contributorId":348339,"corporation":false,"usgs":false,"family":"Barr","given":"Elaine L.","affiliations":[{"id":83337,"text":"Ohio River Islands National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":923375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nocera, Tomas","contributorId":348341,"corporation":false,"usgs":false,"family":"Nocera","given":"Tomas","affiliations":[{"id":83338,"text":"U.S. Army Garrison Fort Belvoir","active":true,"usgs":false}],"preferred":false,"id":923376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. 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In the southeastern U.S., much grassland and open savanna habitat has been converted to timber production or agriculture, neither of which typically provides habitat for breeding or wintering grassland birds. Powerline right-of-ways could provide suitable habitat for many grassland species as these areas are maintained to be treeless. We studied the population dynamics of Henslow’s Sparrows (Centronyx henslowii) wintering in powerline right-of-ways in southeastern Georgia through an 11-year mark-recapture study. We used a robust design Cormack-Jolly-Seber model to estimate probability of detection and apparent survival. Abundance varied substantially among years at each site, with density varying from 1.7 to 8.5 birds/ha. Within-year detection probability was moderately high at 28% (24-33%, 95% credible interval [CI]), but apparent survival was very low at 13% (9-17%, 95% CI). This low apparent survival was likely due to low return rates (and not necessarily low survival). However, birds that did return to the study sites had extremely high site fidelity, with 82% of across-year recaptures < 200 m apart. This apparent incongruity between low apparent survival rates (likely due to emigration from the study sites) and high site fidelity for returning individuals could be explained by the dependability of the right-of-way habitat, which differs from typically patchy and temporally variable grassland and savanna wintering habitats. Dependable habitat may allow for higher site fidelity than this species would otherwise have, potentially resulting in the high densities we observed. Thousands of miles of right-of-ways in Georgia, and other southeastern states, could be managed to maximize potential habitat for declining grassland bird species.
","language":"English","publisher":"Resilience Alliance","doi":"10.5751/jfo-00077-930109","usgsCitation":"Hunter, E.A., Dwire, A., and Schneider, T., 2022, Demography and site fidelity of a grassland bird, the Henslow’s Sparrow, in powerline right-of-way habitat: Journal of Field Ornithology, v. 93, no. 1, 9, 8 p., https://doi.org/10.5751/jfo-00077-930109.","productDescription":"9, 8 p.","ipdsId":"IP-135429","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467210,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/jfo-00077-930109","text":"Publisher Index Page"},{"id":465998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Moody Forest Wildlife Management Area, Paulks Pasture Wildlife Management Area, Townsend Wildlife Management 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trend of the terrestrial carbon sink. Nevertheless, our understanding of the seasonal dynamics of dryland ecosystem carbon uptake through photosynthesis [gross primary productivity (GPP)] remains relatively limited due in part to the limited availability of long-term data and unique challenges associated with satellite remote sensing across dryland ecosystems. Here, we comprehensively evaluated longstanding and emerging satellite vegetation proxies in their ability to capture seasonal dryland GPP dynamics. Specifically, we evaluated: 1) reflectance-based proxies normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), near infrared reflectance index (NIRv), and kernel NDVI (kNDVI) from the MODerate resolution Imaging Spectroradiometer (MODIS); and 2) newly available physiologically-based proxy solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI). As a performance benchmark, we used GPP estimates from a robust network of 21 western United States eddy covariance tower sites that span representative gradients in dryland ecosystem climate and functional composition. We found that NIRv and SIF were the best performing GPP proxies and captured complementary aspects of seasonal GPP dynamics across dryland ecosystem types. NIRv offered better performance than the other proxies across relatively low-productivity, sparsely non-evergreen vegetated sites (R2 = 0.59 ± 0.13); whereas SIF best captured seasonal dynamics across relatively high-productivity sites, including evergreen-dominated sites (R2 = 0.74 ± 0.07). Notably, across grass-dominated sites, all reflectance-based proxies (NDVI, SAVI, NIRv and kNDVI) showed significant seasonal bias (hysteresis) that strengthened with the total fraction of woody vegetation cover, likely due to seasonal patterns in woody vegetation reflectance that are unrelated to or decoupled from GPP. Future efforts to fully integrate the complementary strengths of NIRv and SIF could significantly improve our understanding and representation of dryland GPP dynamics in satellite-based models.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2021.112858","usgsCitation":"Wang, X., Biederman, J.A., Knowles, J.F., Scott, R.L., Turner, A.J., Dannenberg, M.P., Kohler, P., Frankenberg, C., Litvak, M.E., Flerchinger, G.N., Law, B.E., Kwon, H., Reed, S., Parton, W.J., Barron-Gafford, G.A., and Smith, W.K., 2022, Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics: Remote Sensing of the Environment, v. 270, 112858, 11 p., https://doi.org/10.1016/j.rse.2021.112858.","productDescription":"112858, 11 p.","ipdsId":"IP-133234","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":449323,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1981744","text":"Publisher Index 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J","contributorId":271092,"corporation":false,"usgs":false,"family":"Turner","given":"Alexander","email":"","middleInitial":"J","affiliations":[{"id":56276,"text":"Department of Atmospheric Sciences, University of Washington, Seattle, WA, USA","active":true,"usgs":false}],"preferred":false,"id":830800,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dannenberg, Matthew P.","contributorId":239668,"corporation":false,"usgs":false,"family":"Dannenberg","given":"Matthew","email":"","middleInitial":"P.","affiliations":[{"id":47960,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ; Geographical and Sustainability Services, University of Iowa, Iowa City, IA","active":true,"usgs":false}],"preferred":false,"id":830801,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kohler, Philipp","contributorId":271093,"corporation":false,"usgs":false,"family":"Kohler","given":"Philipp","email":"","affiliations":[{"id":33000,"text":"Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA","active":true,"usgs":false}],"preferred":false,"id":830802,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Frankenberg, Christian","contributorId":271094,"corporation":false,"usgs":false,"family":"Frankenberg","given":"Christian","email":"","affiliations":[{"id":33000,"text":"Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA","active":true,"usgs":false}],"preferred":false,"id":830803,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Litvak, Marcy E","contributorId":271095,"corporation":false,"usgs":false,"family":"Litvak","given":"Marcy","email":"","middleInitial":"E","affiliations":[{"id":34162,"text":"Department of Biology, University of New Mexico, Albuquerque, NM, USA","active":true,"usgs":false}],"preferred":false,"id":830804,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Flerchinger, Gerald N.","contributorId":257377,"corporation":false,"usgs":false,"family":"Flerchinger","given":"Gerald","email":"","middleInitial":"N.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":830805,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Law, Beverly E.","contributorId":222527,"corporation":false,"usgs":false,"family":"Law","given":"Beverly","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":830806,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kwon, Hyojung","contributorId":271096,"corporation":false,"usgs":false,"family":"Kwon","given":"Hyojung","email":"","affiliations":[{"id":56277,"text":"Department of Forest Ecosystems and Society, College of Forestry, Oregon State University, Corvallis, OR, USA","active":true,"usgs":false}],"preferred":false,"id":830807,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830808,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Parton, William J","contributorId":271097,"corporation":false,"usgs":false,"family":"Parton","given":"William","email":"","middleInitial":"J","affiliations":[{"id":16129,"text":"Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, USA","active":true,"usgs":false}],"preferred":false,"id":830809,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Barron-Gafford, Greg A.","contributorId":19058,"corporation":false,"usgs":false,"family":"Barron-Gafford","given":"Greg","email":"","middleInitial":"A.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":830810,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Smith, William K. 0000-0002-5785-6489","orcid":"https://orcid.org/0000-0002-5785-6489","contributorId":239667,"corporation":false,"usgs":false,"family":"Smith","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":47959,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":830811,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70227508,"text":"70227508 - 2022 - Nitrogen reductions have decreased hypoxia in the Chesapeake Bay: Evidence from empirical and numerical modeling","interactions":[],"lastModifiedDate":"2022-01-20T13:30:49.473216","indexId":"70227508","displayToPublicDate":"2021-12-31T07:30:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Nitrogen reductions have decreased hypoxia in the Chesapeake Bay: Evidence from empirical and numerical modeling","docAbstract":"Seasonal hypoxia is a characteristic feature of the Chesapeake Bay due to anthropogenic nutrient input from agriculture and urbanization throughout the watershed. Although coordinated management efforts since 1985 have reduced nutrient inputs to the Bay, oxygen concentrations at depth in the summer still frequently fail to meet water quality standards that have been set to protect critical estuarine living resources. To quantify the impact of watershed nitrogen reductions on Bay hypoxia during a recent period including both average discharge and extremely wet years (2016–2019), this study employed both statistical and three-dimensional (3-D) numerical modeling analyses. Numerical model results suggest that if the nitrogen reductions since 1985 had not occurred, annual hypoxic volumes (O2 < 3 mg L−1) would have been ~50–120% greater during the average discharge years of 2016–2017 and ~20–50% greater during the wet years of 2018–2019. The effect was even greater for O2 < 1 mg L−1, where annual volumes would have been ~80–280% greater in 2016–2017 and ~30–100% greater in 2018–2019. These results were supported by statistical analysis of empirical data, though the magnitude of improvement due to nitrogen reductions was greater in the numerical modeling results than in the statistical analysis. This discrepancy is largely accounted for by warming in the Bay that has exacerbated hypoxia and offset roughly 6–34% of the improvement from nitrogen reductions. Although these results may reassure policymakers and stakeholders that their efforts to reduce hypoxia have improved ecosystem health in the Bay, they also indicate that greater reductions are needed to counteract the ever-increasing impacts of climate change.
Predators can shift their diets and even selectivity in response to changing environmental conditions. Since the early 2000s, Lake Huron experienced major food-web shifts that have caused changes in the prey availability and quality for consumers at multiple trophic levels. Previous studies have reported declining energetic condition for key planktivorous fishes, such as bloater (Coregonus hoyi) and rainbow smelt (Osmerus mordax), which play a key role in supporting commercially and recreationally important piscivorous fishes. To improve understanding of how changes in the invertebrate prey community have influenced foraging by rainbow smelt and bloater, we processed diets and calculated selectivity along two transects in Lake Huron during 2012. Diet proportions for both species varied seasonally and consisted of mostly calanoid copepods during spring and summer, specifically Leptodiaptomus sicilis and diaptomid copepodites, and Daphnia galeata mendotae in autumn. Bloater selectivity varied primarily by season and transect with Limnocalanus macrurus or Mysis diluviana as the most preferred prey during spring, Chironomidae pupae or L. sicilis during summer, and Chironomidae pupae or Mysis during autumn. Rainbow smelt selectivity was consistent across seasons and transects with Mysis being the species most commonly selected and Bythotrephes longimanus the second most. Both fish species selected for relatively large invertebrate prey, but declining densities of Mysis and the benthic amphipod Diporeia have caused fish to consume smaller prey with much lower energy density. Our results illustrate how food-web changes underlie the reduced energetic condition of bloater and rainbow smelt, which ultimately reduces the growth potential for recreationally and commercially important piscivorous fish.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fooweb.2021.e00215","usgsCitation":"Dieter, P.M., Bunnell, D., and Warner, D.M., 2022, Seasonal variability of invertebrate prey diet and selectivity of the dominant forage fishes in Lake Huron: Food Webs, v. 30, p. 1-10, https://doi.org/10.1016/j.fooweb.2021.e00215.","productDescription":"e00215, 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-128401","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":436020,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LFPAMF","text":"USGS data release","linkHelpText":"Zooplankton, Benthos, Mysis, and fish diet data from northern Lake Huron in 2012"},{"id":393700,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.0673828125,\n 46.34692761055676\n ],\n [\n -84.72656249999999,\n 46.057985244793024\n ],\n [\n -84.72656249999999,\n 45.79816953017265\n ],\n [\n -83.69384765625,\n 43.5326204268101\n ],\n [\n -82.37548828125,\n 43.052833917627936\n ],\n [\n -81.67236328125,\n 43.42100882994726\n ],\n [\n -80.0244140625,\n 44.62175409623324\n ],\n [\n -79.8046875,\n 44.824708282300236\n ],\n [\n -80.70556640625,\n 46.057985244793024\n ],\n [\n -84.0673828125,\n 46.34692761055676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dieter, Patricia M 0000-0003-1686-2679 pdieter@usgs.gov","orcid":"https://orcid.org/0000-0003-1686-2679","contributorId":270688,"corporation":false,"usgs":true,"family":"Dieter","given":"Patricia","email":"pdieter@usgs.gov","middleInitial":"M","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":829766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David 0000-0003-3521-7747","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":245523,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":829767,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, David M. 0000-0003-4939-5368 dmwarner@usgs.gov","orcid":"https://orcid.org/0000-0003-4939-5368","contributorId":2986,"corporation":false,"usgs":true,"family":"Warner","given":"David","email":"dmwarner@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":829768,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227176,"text":"70227176 - 2022 - Food, beverage, and feedstock processing facility wastewater: A unique and underappreciated source of contaminants to U.S. streams","interactions":[],"lastModifiedDate":"2022-02-15T16:19:12.225859","indexId":"70227176","displayToPublicDate":"2021-12-30T08:50:43","publicationYear":"2022","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":"Food, beverage, and feedstock processing facility wastewater: A unique and underappreciated source of contaminants to U.S. streams","docAbstract":"Process wastewaters from food, beverage, and feedstock facilities, although regulated, are an under-investigated environmental contaminant source. Food process wastewaters (FPWWs) from 23 facilities in 17 U.S. states were sampled and documented for a plethora of chemical and microbial contaminants. Of the 576 analyzed organics, 184 (32%) were detected at least once, with concentrations as large as 143 μg L–1 (6:2 fluorotelomer sulfonic acid), and as many as 47 were detected in a single FPWW sample. Cumulative per/polyfluoroalkyl substance concentrations up to 185 μg L–1 and large pesticide transformation product concentrations (e.g., methomyl oxime, 40 μg L–1; clothianidin TMG, 2.02 μg L–1) were observed. Despite 48% of FPWW undergoing disinfection treatment prior to discharge, bacteria resistant to third-generation antibiotics were found in each facility type, and multiple bacterial groups were detected in all samples, including total coliforms. The exposure–activity ratios and toxicity quotients exceeded 1.0 in 13 and 22% of samples, respectively, indicating potential biological effects and toxicity to vertebrates and invertebrates associated with the discharge of FPWW. Organic contaminant profiles of FPWW differed from previously reported contaminant profiles of municipal effluents and urban storm water, indicating that FPWW is another important source of chemical and microbial contaminant mixtures discharged into receiving surface waters.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.1c06821","usgsCitation":"Hubbard, L.E., Kolpin, D., Givens, C.E., Blackwell, B.D., Bradley, P., Gray, J., Lane, R.F., Masoner, J.R., McCleskey, R., Romanok, K., Sandstrom, M.W., Smalling, K., and Villeneuve, D., 2022, Food, beverage, and feedstock processing facility wastewater: A unique and underappreciated source of contaminants to U.S. streams: Environmental Science & Technology, v. 56, no. 2, p. 1028-1040, https://doi.org/10.1021/acs.est.1c06821.","productDescription":"13 p.","startPage":"1028","endPage":"1040","ipdsId":"IP-130265","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest 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\"}}]}","volume":"56","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Hubbard, Laura E. 0000-0003-3813-1500 lhubbard@usgs.gov","orcid":"https://orcid.org/0000-0003-3813-1500","contributorId":4221,"corporation":false,"usgs":true,"family":"Hubbard","given":"Laura","email":"lhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":205652,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829922,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Givens, Carrie E. 0000-0003-2543-9610","orcid":"https://orcid.org/0000-0003-2543-9610","contributorId":270741,"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":829923,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blackwell, Bradley D. 0000-0003-1296-4539","orcid":"https://orcid.org/0000-0003-1296-4539","contributorId":198381,"corporation":false,"usgs":false,"family":"Blackwell","given":"Bradley","email":"","middleInitial":"D.","affiliations":[{"id":18090,"text":"U.S. Environmental Protection Agency, Gulf Ecology Division, Gulf Breeze, FL","active":true,"usgs":false}],"preferred":false,"id":829924,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":221226,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829925,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gray, James L. 0000-0002-0807-5635","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":202726,"corporation":false,"usgs":true,"family":"Gray","given":"James L.","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":829926,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lane, Rachael F. 0000-0001-9202-0612","orcid":"https://orcid.org/0000-0001-9202-0612","contributorId":222471,"corporation":false,"usgs":true,"family":"Lane","given":"Rachael","email":"","middleInitial":"F.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":829927,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Masoner, Jason R. 0000-0002-4829-6379 jmasoner@usgs.gov","orcid":"https://orcid.org/0000-0002-4829-6379","contributorId":3193,"corporation":false,"usgs":true,"family":"Masoner","given":"Jason","email":"jmasoner@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829928,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":205663,"corporation":false,"usgs":true,"family":"McCleskey","given":"R. Blaine","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":829929,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Romanok, Kristin M. 0000-0002-8472-8765","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":221227,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829930,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"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":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","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":829931,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829932,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Villeneuve, Daniel L. 0000-0003-2801-0203","orcid":"https://orcid.org/0000-0003-2801-0203","contributorId":219631,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Daniel L.","affiliations":[{"id":39312,"text":"U.S. EPA","active":true,"usgs":false}],"preferred":false,"id":829933,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70227324,"text":"70227324 - 2022 - Acoustic and genetic data can reduce uncertainty regarding populations of migratory tree-roosting bats impacted by wind energy","interactions":[],"lastModifiedDate":"2022-01-10T13:10:25.611928","indexId":"70227324","displayToPublicDate":"2021-12-30T07:06:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5762,"text":"Animals","active":true,"publicationSubtype":{"id":10}},"title":"Acoustic and genetic data can reduce uncertainty regarding populations of migratory tree-roosting bats impacted by wind energy","docAbstract":"Plants are critical mediators of terrestrial mass and energy fluxes, and their structural and functional traits have profound impacts on local and global climate, biogeochemistry, biodiversity, and hydrology. Yet Earth System Models (ESMs), our most powerful tools for predicting the effects of humans on the coupled biosphere-atmosphere system, simplify the incredible diversity of land plants into a handful of coarse categories of ‘Plant Functional Types’ (PFTs) that often fail to capture ecological dynamics such as biome distributions. The inclusion of more realistic functional diversity is a recognized goal for ESMs, yet there is currently no consistent, widely accepted way to add diversity to models, i.e. to determine what new PFTs to add and with what data to constrain their parameters. We review approaches to representing plant diversity in ESMs and draw on recent ecological and evolutionary findings to present an evolution-based functional type approach for further disaggregating functional diversity. Specifically, the prevalence of niche conservatism, or the tendency of closely related taxa to retain similar ecological and functional attributes through evolutionary time, reveals that evolutionary relatedness is a powerful framework for summarizing functional similarities and differences among plant types. We advocate that Plant Functional Types based on dominant evolutionary lineages (‘Lineage Functional Types’) will provide an ecologically defensible, tractable, and scalable framework for representing plant diversity in next-generation ESMs, with the potential to improve parameterization, process representation, and model benchmarking. We highlight how the importance of evolutionary history for plant function can unify the work of disparate fields to improve predictive modeling of the Earth system.
Frequency‐dependent horizontal‐to‐vertical spectral ratios (HVSRs) of Fourier amplitudes from three‐component recordings can provide useful information for site response modeling. However, such information is not incorporated into most ground‐motion models, including those from Next‐Generation Attenuation projects, which instead use the time‐averaged shear‐wave velocity (
Considering reservoirs as linear fragments in a basin's river network could improve understanding, predictability, and management efficiency. We looked for general cascading spatial patterns across five categories of reservoir attributes: land cover, morphology and hydrology, fish habitat, fish assemblages, and fisheries. Attributes were pulled from various databases for large reservoirs (>100 ha) located in the United States. 16 widely distributed river basins, each including a minimum of 15 large reservoirs, were selected for analysis. Using analysis of covariance with basin as the class variable, we tested each attribute as a linear function of catchment area, which is an index of reservoir position in the basin. The majority of reservoir attributes displayed log-linear patterns as catchment area increased, indicating that reservoirs act as members of a larger network just as river reaches do. Several patterns were detected including attributes with no apparent lengthwise arrangement along the basin; cascading spatial patterns in which attributes increase or decrease from upstream to downstream within a basin; and attributes that increase with catchment area in some basins, decrease in others, or may simply remain constant throughout the basin. We conclude that each pattern may have different implications for management, and that the effectiveness with which most management activities influence reservoirs is likely to increase or decrease along river basins.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021WR029910","usgsCitation":"Faucheux, N., Sample, A., Aldridge, C., Norris, D., Owens, C., Starnes, V.R., VanderBloemen, S., and Miranda, L.E., 2022, Reservoir attributes display cascading spatial patterns along river basins: Water Resources Research, v. 58, no. 1, e2021WR029910, 14 p., https://doi.org/10.1029/2021WR029910.","productDescription":"e2021WR029910, 14 p.","ipdsId":"IP-119850","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433562,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Faucheux, N.M.","contributorId":341806,"corporation":false,"usgs":false,"family":"Faucheux","given":"N.M.","affiliations":[{"id":81792,"text":"Mississippi State Uni","active":true,"usgs":false}],"preferred":false,"id":908915,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sample, A.R.","contributorId":341807,"corporation":false,"usgs":false,"family":"Sample","given":"A.R.","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":908916,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aldridge, C.A.","contributorId":275883,"corporation":false,"usgs":false,"family":"Aldridge","given":"C.A.","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":908917,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Norris, D.M.","contributorId":341780,"corporation":false,"usgs":false,"family":"Norris","given":"D.M.","email":"","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":908918,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Owens, C.","contributorId":341808,"corporation":false,"usgs":false,"family":"Owens","given":"C.","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":908919,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Starnes, Victoria R.","contributorId":343988,"corporation":false,"usgs":false,"family":"Starnes","given":"Victoria","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":908920,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"VanderBloemen, S.","contributorId":341810,"corporation":false,"usgs":false,"family":"VanderBloemen","given":"S.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":908921,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908922,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70227360,"text":"70227360 - 2022 - Modeling the occurrence of M ∼ 5 caldera collapse-related earthquakes in Kīlauea volcano, Hawai'i","interactions":[],"lastModifiedDate":"2022-01-11T12:58:57.121497","indexId":"70227360","displayToPublicDate":"2021-12-28T06:56:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the occurrence of M ∼ 5 caldera collapse-related earthquakes in Kīlauea volcano, Hawai'i","docAbstract":"During the 2018 Kīlauea eruption and caldera collapse, M ∼ 5 caldera collapse earthquakes occurred almost daily from mid-May until the beginning of August. While caldera collapses happen infrequently, the collapse-related seismicity damaged nearby structures, and so these events should be included in a complete seismic hazard assessment. Here, we present an approach to forecast the seismic hazard of the collapse earthquakes. We model their occurrence by combining a Poisson distribution for the number of collapses with a negative binomial for the number of earthquakes in a collapse, based on observations at Kīlauea. This rate model is then combined with a ground motion model to assess the seismic hazard posed by caldera collapse events. The rate model is non-Poisson but a Poisson model is adequate for low exceedance probabilities (e.g., <10% in 50 years). This approach could be generalized to model the hazard from earthquakes triggered by other underlying processes.
Land management decisions need context about how landscapes will respond to different circumstances or actions. As ecologists’ understanding of nonlinear ecological dynamics has evolved into state-and-transition models (STMs), they have put more emphasis on defining and mapping the soil, geomorphological, and climate parameters that mediate these dynamics. The US Department of Agriculture Natural Resources Conservation Service ecological site descriptions (ESDs) have become the foremost system in classifying lands into ecological units based on STMs. However, an exhaustive inventory of ESDs has proved challenging to complete in the United States, and there have been questions about the consistency of detail in areas completed and the ability to objectively support some assertions made in existing ESDs. To address these issues, this study examines ESDs in the diverse Upper Colorado River region, where ESDs are only partially complete, to look at quantitative approaches to generalizing ecological site concepts based on unifying underlying soil, geomorphology, and climate patterns. Using existing ESDs and vegetation monitoring plot data, results show that a simple hierarchical soil geomorphic unit (SGU) framework based on topographic mediation of moisture, soil salinity, soil depth, slope, rock content, and soil texture can represent much of the ecological dynamics cataloged in ESDs. Analyses of reference plant production data, ecological state attribution, and regional monitoring data show that the new SGUs represent more variation than common climate parameters. This study also included predictively mapping SGUs at 30-m resolution (Kappa of 0.53, 74% agreement with top two predictions in validation). An optimized combination of SGUs with climate zones derived from an aridity index and maximum temperature of the hottest month resulted in an ecological site group framework that condensed over 826 unique ecological site records at various stages of completeness in the regional soil survey down to 35 intuitive and mappable ecological site groups.
From a management perspective, reptiles are relatively novel invasive taxa. Few methods for reptile control have been developed and very little is known about their effectiveness for reducing reptile populations, particularly when the goal is eradication. Many reptiles, and especially snakes, are cryptic, secretive, and undergo extended periods of inactivity, traits that decrease detection probabilities and create challenges in estimating population size or evaluating management effects. The brown treesnake (Boiga irregularis) is a notorious invasive species that continues to cause major ecological and economic harm following their introduction to the island of Guam after World War II. They have been the subject of intensive research on the effectiveness of various techniques to control snakes, including the first ever aerial system for the distribution of toxic acetaminophen baits for reptile control. We provide a cohort-based life table for a cryptic and invasive reptile undergoing extended population control using toxic baits from March 2017–2020. We also evaluated the effects of single (toxic bait) versus multi-tool (toxic bait and live trapping) management efforts on population trajectories, and estimated which population vital rates are most important for influencing population growth or decline in a treated landscape. Treatment of the population with acetaminophen-laced baits resulted in an immediate reduction followed by a gradual population decline that suggested that eradication was the probable outcome given sufficient treatment time but that the period of treatment was decades in magnitude. Inclusion of live trapping reduced the predicted time required to achieve eradication by more than half. Preventing the transition of 1,000-mm snout-vent length (SVL) females to larger sizes was predicted to have the greatest effect on population reduction based on integral projection modeling. Our results suggest that toxic baits are capable of eradicating brown treesnakes in an enclosure, although inclusion of trapping reduced overall treatment time required. Tools that effectively target females >1,000 mm SVL may have the greatest effect on reducing overall treatment timelines.
The uranium (U) content, and more recently, the ratio between 238U and 235U in black shales are commonly applied as a proxy to determine redox conditions and infer organic-richness. Uranium contents typically display a linear relationship with total organic carbon (TOC) in shales. This relationship is due to the processes and mechanisms responsible for the incorporation of U into the sediment during the deposition and remineralization of organic matter. This U/TOC relationship can vary, however, and some shales display uncharacteristically low U content despite having high TOC content, while others show large enrichments of U relative to TOC. Here we examine the U to TOC ratios and U-isotope compositions of three Upper Devonian-Lower Mississippian shales: the Woodford Shale, the Cleveland Shale, and the Bakken Shale, with two study sites in Oklahoma, one site in eastern Kentucky, and three sites in eastern Montana and western North Dakota, respectively. The U/TOC ratios of each shale are distinct from one another exhibiting average ratios ranging from 3 in the Cleveland Shale, to over 10 in the Bakken Shale. The distinct geochemical composition of the three shales suggests that, although lithologically similar, each study site represents a markedly different and dynamic depositional environment. The low average U/TOC (~3) along with the relatively high δ238U values (~0.03‰) of the Cleveland Shale core suggests deposition along the basin margin under normal marine conditions with periods of reduced bottom water oxygenation, likely due to fluctuations in the location of the pycnocline. The Woodford Shale on the other hand, shows higher U/TOC ratios (~4, George core, ~9, Poe core) and δ238U (~0.02‰ average, George core, ~0.06‰ average, Poe core), which suggests an unrestricted setting with intermittent euxinic conditions. In contrast, high U/TOC ratios (2–15), and very high δ238U values (up to 0.55‰) in the Bakken Shale cores indicate intense metal draw-down into sediments under sulfidic waters. The results show that when the U/TOC ratios and U-isotopic compositions of each studied shale are compared to modern anoxic basins and upwelling areas, it allows for an enhanced understanding of the paleoenvironmental conditions such as basin restriction and redox state of waters within the Late Devonian epicontinental seas of North America.
Acoustic source inversions estimate the mass flow rate of volcanic explosions or yield of chemical explosions and provide insight into potential source directionality. However, the limitations of applying these methods to complex sources and their ability to resolve a stable solution have not been investigated in detail. We perform synthetic infrasound waveform inversions that use 3-D Green’s functions for a variety of idealized and realistic deployment scenarios using both a flat plane and Yasur volcano, Vanuatu as examples. We investigate the ability of various scenarios to retrieve the input source functions and relative amplitudes for monopole and multipole (monopole and dipole) inversions. Infrasound waveform inversions appear to be a robust method to quantify mass flow rates from simple sources (monopole) using deployments of infrasound sensors placed around a source, but care should be taken when analyzing and interpreting results from more complex acoustic sources (multipole) that have significant directional components. In the examples we consider the solution is stable for monopole inversions with a signal-to-noise ratio greater than five and the dipole component is small. For most scenarios investigated, the vertical dipole component of the multipole explosion source is poorly constrained and can impact the ability to recover the other source term components. Because multipole inversions are ill-posed for many deployments, a low residual does not necessarily mean the proper source vector has been recovered. Synthetic studies can help investigate the limitations and place bounds on information that may be missing using monopole and multipole inversions for potentially directional sources.
Rio Grande Rise (RGR) is an intraplate oceanic elevation in the South Atlantic Ocean that formed at a hotspot on the Mid-Atlantic Ridge during the Cretaceous. In spreading center and hotspot environments, ironstones form mainly by biomineralization of reduced Fe from hydrothermal fluids or oxidation of sulfide deposits. However, RGR has been considered aseismic and volcanically inactive for the past 46 Ma. Here, we investigate the origin of ironstones collected from the summit of RGR using multiple techniques: petrographic observations, X-ray diffraction, U-Th/He geochronology, and chemical composition. The ironstones from RGR consist of finely laminated goethite containing igneous rock fragments, carbonate fluorapatite, and calcite. Our results suggest that Fe oxyhydroxides were precipitated by Fe-oxidizing bacteria forming bacterial mats. The bacterial Fe mats underwent compaction, dewatering, goethite crystallization, and cementation that created the ironstone deposits. U-Th/He geochronology reveals protracted goethite minimum ages extending from the late Miocene to the Quaternary, probably due to multiple generations of mats, slow mineralization rates, and Fe-oxide dissolution-reprecipitation cycles. Flame-like goethite structures underneath FeMn crusts and a chimney-shaped goethite sample with a central channel indicate that the dewatering fluid flowed upward through the deposits, or a thermal fluid source may have been introduced from below the ironstone deposits. High Fe/Mn ratios, low trace metals contents (Ni + Co + Cu), and very low Fe/REY ratios suggest ironstone precipitation from a hydrothermal fluid; however, REYSN plots and bivariate CeSN /CeSN⁎ versus YSN/HoSN and CeSN /CeSN⁎ versus Nd plots are inconclusive, and a proximal source of magma was unlikely during the period of mat formation. Given this evidence, we hypothesize that a geothermal circulation system may have facilitated ironstone mineralization at RGR.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2021.106716","usgsCitation":"Benites, M., Hein, J.R., Mizell, K., Farley, K.A., Treffkorn, J., and Jovane, L., 2022, Geochemical insights into formation of enigmatic ironstones from Rio Grande rise, South Atlantic Ocean: Marine Geology, v. 444, 106716, 18 p., https://doi.org/10.1016/j.margeo.2021.106716.","productDescription":"106716, 18 p.","ipdsId":"IP-135576","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":489032,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://dx.doi.org/10.1016/j.margeo.2021.106716","text":"External Repository"},{"id":393858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Rio Grande rise, South Atlantic Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -40,\n -35\n ],\n [\n -30,\n -35\n ],\n [\n -30,\n -29\n ],\n [\n -40,\n -29\n ],\n [\n -40,\n -35\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"444","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Benites, Mariana","contributorId":259240,"corporation":false,"usgs":false,"family":"Benites","given":"Mariana","email":"","affiliations":[{"id":48623,"text":"University of Sao Paulo","active":true,"usgs":false}],"preferred":false,"id":829998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hein, James R. 0000-0002-5321-899X jhein@usgs.gov","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":140835,"corporation":false,"usgs":true,"family":"Hein","given":"James","email":"jhein@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":829999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mizell, Kira 0000-0002-5066-787X kmizell@usgs.gov","orcid":"https://orcid.org/0000-0002-5066-787X","contributorId":4914,"corporation":false,"usgs":true,"family":"Mizell","given":"Kira","email":"kmizell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":830000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farley, Kenneth A.","contributorId":204209,"corporation":false,"usgs":false,"family":"Farley","given":"Kenneth","email":"","middleInitial":"A.","affiliations":[{"id":36877,"text":"Cal Tech","active":true,"usgs":false}],"preferred":false,"id":830001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Treffkorn, Jonathon 0000-0002-4953-8245","orcid":"https://orcid.org/0000-0002-4953-8245","contributorId":270768,"corporation":false,"usgs":false,"family":"Treffkorn","given":"Jonathon","email":"","affiliations":[{"id":7218,"text":"California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":830002,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jovane, Luigi 0000-0003-4348-4714","orcid":"https://orcid.org/0000-0003-4348-4714","contributorId":259243,"corporation":false,"usgs":false,"family":"Jovane","given":"Luigi","email":"","affiliations":[{"id":48623,"text":"University of Sao Paulo","active":true,"usgs":false}],"preferred":false,"id":830003,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229818,"text":"70229818 - 2022 - Effects of salinity and a glucocorticoid antagonist, RU486, on waterborne aldosterone and corticosterone of northern leopard frog larvae","interactions":[],"lastModifiedDate":"2022-03-18T14:20:11.565813","indexId":"70229818","displayToPublicDate":"2021-12-24T09:17:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1738,"text":"General and Comparative Endocrinology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of salinity and a glucocorticoid antagonist, RU486, on waterborne aldosterone and corticosterone of northern leopard frog larvae","docAbstract":"Increased salinity is an emerging contaminant of concern for aquatic taxa. For amphibians exposed to salinity, there is scarce information about the physiological effects and changes in osmoregulatory hormones such as corticosterone (CORT) and aldosterone (ALDO). Recent studies have quantified effects of salinity on CORT physiology of amphibians based on waterborne hormone collection methods, but much less is known about ALDO in iono- and osmoregulation of amphibians. We re-assayed waterborne hormone samples from a previous study to investigate effects of salinity (sodium chloride, NaCl) and a glucocorticoid receptor antagonist (RU486) on ALDO of northern leopard frog (Rana pipiens) larvae. We also investigated relationships between ALDO and CORT. Waterborne ALDO marginally decreased with increasing salinity and was, unexpectedly, positively correlated with baseline and stress-induced waterborne CORT. Importantly, ALDO increased when larvae were exposed to RU486, suggesting that RU486 may also suppress mineralocorticoid receptors or that negative feedback of ALDO is mediated through glucocorticoid receptors. Alternatively, CORT increases with RU486 treatment and might be a substrate for ALDO synthesis, which could account for increases in ALDO with RU486 treatment and the correlation between CORT and ALDO. ALDO was negatively correlated with percent water, such that larvae secreting more ALDO retained less water. Although sample sizes were limited and further validation and studies are warranted, our findings expand our understanding of adrenal steroid responses to salinization in amphibians and proposes new hypotheses regarding the co-regulation of ALDO and CORT.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ygcen.2021.113972","usgsCitation":"Tornabene, B., Breuner, C., Hossack, B., and Crespi, E.J., 2022, Effects of salinity and a glucocorticoid antagonist, RU486, on waterborne aldosterone and corticosterone of northern leopard frog larvae: General and Comparative Endocrinology, v. 317, 113972, 6 p., https://doi.org/10.1016/j.ygcen.2021.113972.","productDescription":"113972, 6 p.","ipdsId":"IP-133771","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":449356,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ygcen.2021.113972","text":"Publisher Index Page"},{"id":397304,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"317","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tornabene, Brian J.","contributorId":200041,"corporation":false,"usgs":false,"family":"Tornabene","given":"Brian J.","affiliations":[],"preferred":false,"id":838469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breuner, Creagh W","contributorId":241893,"corporation":false,"usgs":false,"family":"Breuner","given":"Creagh W","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":838470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":838471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crespi, Erica J","contributorId":260876,"corporation":false,"usgs":false,"family":"Crespi","given":"Erica","email":"","middleInitial":"J","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":838472,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70231535,"text":"70231535 - 2022 - Temperatures of the Lacus Mortis region of the Moon","interactions":[],"lastModifiedDate":"2022-05-12T13:27:31.347235","indexId":"70231535","displayToPublicDate":"2021-12-24T08:24:06","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Temperatures of the Lacus Mortis region of the Moon","docAbstract":"Over 11 years of data acquired by the Diviner Lunar Radiometer Experiment instrument aboard Lunar Reconnaissance Orbiter have been compiled into a comprehensive data set of surface temperatures in the Lacus Mortis region which includes the landing ellipse of the Astrobotic Mission One lander mission. These data provide diurnal brightness temperatures at 128 pixels per degree (ppd) spatial resolution and 0.1 hr of local time resolution. From this data set, we highlight several features that display variations in radiative and thermophysical properties in the Lacus Mortis region and characterize the temperatures of the Astrobotic Mission One landing ellipse. We identify distinctly contrasting properties of materials in the walls of Bürg crater, hummocks of materials on the southeast margin of the mare basalts, and materials exposed or excavated by impacts. Additionally, we describe an exceptionally rocky fault scarp that predates the formation of Bürg crater suggesting the observed boulders are replenished on a timescale <1 Ga. Within the Astrobotic landing ellipse, temperatures are observed to range from ∼88 to ∼359 K with sunrise and sunset local times constrained to 5.8–6.3 hr and 17.8 and 18.1 hr respectively.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EA001966","usgsCitation":"Williams, J., Greenhagen, B.T., Bennett, K.A., Paige, D., Kumari, N., Ahrens, C., Rubanenko, L., Powell, T., Prem, P., Blewett, D.T., Russell, P., Hayne, P.O., and Sullivan, M., 2022, Temperatures of the Lacus Mortis region of the Moon: Earth and Space Science, v. 9, no. 2, e2021EA001966, 17 p., https://doi.org/10.1029/2021EA001966.","productDescription":"e2021EA001966, 17 p.","ipdsId":"IP-130804","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":449361,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021ea001966","text":"Publisher Index Page"},{"id":400575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lacus Mortis region, 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mixtures in three recurring surface blooms within one lake","docAbstract":"Cyanobacteria can produce numerous secondary metabolites (cyanotoxins) with various toxicities, yet data on cyanotoxins in many lakes are limited. Moreover, little research is available on complex relations among cyanobacteria that produce toxins. Therefore, we studied cyanobacteria and 19 cyanotoxins at three sites with recurring blooms in Kabetogama Lake (USA). Seven of 19 toxins were detected in various combinations. Anabaenopeptin A and B were detected in every sample. Microcystin-YR was detected more frequently than microcystin-LR, unlike other lakes in the region. Microcystin-YR concentrations, however, generally were low; two samples exceeded drinking water guidelines and no samples exceeded recreational guidelines. Anabaenopeptins correlated with six cyanobacterial taxa, most of which lack available literature on peptide production. The potential toxin producing cyanobacteria, Microcystis, was significantly correlated to microcystin-YR. Pseudanabaena sp. and Synechococcus sp. had strong negative correlations with several toxins that may indicate competition or stress between organisms. Non-metric multidimensional scaling identified three cyanobacterial pairs that may reflect symbiotic or antagonistic relations. This study highlights interactions among cyanobacteria and multiple cyanotoxins and the methods used may be useful for uncovering additional patterns in cyanobacteria communities in other systems, leading to further understanding of how those interactions lead to toxin production.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhazmat.2021.128142","usgsCitation":"Christensen, V., Olds, H., Norland, J.E., and Khan, E., 2022, Phytoplankton community interactions and cyanotoxin mixtures in three recurring surface blooms within one lake: Journal of Hazardous Materials, v. 427, 128142, 12 p., https://doi.org/10.1016/j.jhazmat.2021.128142.","productDescription":"128142, 12 p.","ipdsId":"IP-128039","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":394575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Kabetogama Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.11805725097656,\n 48.4105166936892\n ],\n [\n -92.779541015625,\n 48.4105166936892\n ],\n [\n -92.779541015625,\n 48.537977131982025\n ],\n [\n -93.11805725097656,\n 48.537977131982025\n ],\n [\n -93.11805725097656,\n 48.4105166936892\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"427","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Christensen, Victoria 0000-0003-4166-7461","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":220548,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":831205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olds, Hayley T. 0000-0002-6701-6459 htemplar@usgs.gov","orcid":"https://orcid.org/0000-0002-6701-6459","contributorId":5002,"corporation":false,"usgs":true,"family":"Olds","given":"Hayley T.","email":"htemplar@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":831206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Norland, Jack E.","contributorId":214257,"corporation":false,"usgs":false,"family":"Norland","given":"Jack","email":"","middleInitial":"E.","affiliations":[{"id":39001,"text":"School of Natural Resources Sciences, North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":831207,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Khan, Eakalak","contributorId":220550,"corporation":false,"usgs":false,"family":"Khan","given":"Eakalak","email":"","affiliations":[{"id":40182,"text":"University of Nevada Las Vegas","active":true,"usgs":false}],"preferred":false,"id":831208,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}