The most recent comprehensive estimates of Northern Spotted Owl (Strix occidentalis caurina) natal dispersal distances were reported in 2002. Since then, Northern Spotted Owl populations have experienced substantial demographic changes, with potential attendant changes in natal dispersal distances, including temporal or geographic trends. We analyzed the natal dispersal of Northern Spotted Owls during 1985–2012 in Oregon and Washington, USA (n = 1,534 dispersal events), to determine current natal dispersal distances and to evaluate potential trends that may inform management actions. Mean net dispersal distance (natal site to site of first attempted breeding) was 23.8 km +- 19.2 km SD, with females dispersing ~50% farther than males. Net dispersal distance varied by ecoregion (Washington Coast and Cascades, Washington Eastern Cascades, Oregon Coast Range, Oregon and California Cascades, and Oregon and California Klamath) but declined similarly in all ecoregions over time (~1 km yr^-1 ). Dispersal direction also varied by ecoregion, following coarse-scale forest habitat configuration, and was bimodal (north–south) in the Oregon Coast Range, south–southwest in the Oregon and California Cascades, and showed little directionality in the Washington Eastern Cascades, Washington Coast and Cascades, and Oregon and California Klamath. Long-distance dispersal events (.50 km) also varied by ecoregion (mean: 62.3–99.5 km), with most long-distance dispersal (8% of dispersers; distances up to 177 km) originating in southern ecoregions. We found no direct relationship between Barred Owl (Strix varia) detections near natal or settling locations and dispersal distance. These findings, particularly the declining trend of dispersal distances, may inform management actions aimed toward conservation of the Northern Spotted Owl.
","language":"English","publisher":"BioOne","doi":"10.1650/CONDOR-17-164.1","usgsCitation":"Hollenbeck, J., Haig, S.M., Forsman, E.D., and Wiens, D., 2019, Geographic variation in natal dispersal of Northern Spotted Owls over 28 years: The Condor, v. 120, no. 3, p. 530-542, https://doi.org/10.1650/CONDOR-17-164.1.","productDescription":"13 p.","startPage":"530","endPage":"542","ipdsId":"IP-093377","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":364874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.73876953125,\n 48.4146186174932\n ],\n [\n -124.73876953125,\n 47.96050238891509\n ],\n [\n -124.23339843749999,\n 47.27922900257082\n ],\n [\n -123.96972656249999,\n 45.874712248904764\n ],\n [\n -124.12353515624999,\n 44.62175409623324\n ],\n [\n -124.23339843749999,\n 43.5326204268101\n ],\n [\n -124.5849609375,\n 42.84375132629021\n ],\n [\n -124.3212890625,\n 41.918628865183045\n ],\n [\n -120.36621093749999,\n 42.032974332441405\n ],\n [\n -120.16845703125,\n 45.66012730272194\n ],\n [\n -119.091796875,\n 48.980216985374994\n ],\n [\n -123.24462890625,\n 48.980216985374994\n ],\n [\n -122.98095703125,\n 48.76343113791796\n ],\n [\n -123.1787109375,\n 48.66194284607006\n ],\n [\n -123.11279296875001,\n 48.32703913063476\n ],\n [\n -123.3544921875,\n 48.23930899024907\n ],\n [\n -124.73876953125,\n 48.4146186174932\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"120","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hollenbeck, Jeff 0000-0001-6481-5354","orcid":"https://orcid.org/0000-0001-6481-5354","contributorId":216400,"corporation":false,"usgs":true,"family":"Hollenbeck","given":"Jeff","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":764715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":764716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forsman, Eric D.","contributorId":96792,"corporation":false,"usgs":false,"family":"Forsman","given":"Eric","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":764717,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiens, David 0000-0002-2020-038X jwiens@usgs.gov","orcid":"https://orcid.org/0000-0002-2020-038X","contributorId":167538,"corporation":false,"usgs":true,"family":"Wiens","given":"David","email":"jwiens@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":764718,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203817,"text":"70203817 - 2019 - Geographic variation in the intensity of warming and phenological mismatch between Arctic shorebirds and invertebrates","interactions":[],"lastModifiedDate":"2019-11-13T13:22:24","indexId":"70203817","displayToPublicDate":"2019-06-08T10:09:42","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"Geographic variation in the intensity of warming and phenological mismatch between Arctic shorebirds and invertebrates","docAbstract":"Responses to climate change can vary across functional groups and trophic levels, leading to a temporal decoupling of trophic interactions or ‘phenological mismatches.’ Despite a growing number of single-species studies that identified phenological mismatches as a nearly universal consequence of climate change, we have a limited understanding of the spatial variation in the intensity of this phenomenon nor what influences this variation. In this study, we tested for geographic patterns in phenological mismatches between six species of shorebirds and their invertebrate prey at ten sites spread across ~13º latitude and ~84º longitude in the Arctic over three years. At each site, we quantified the phenological mismatch between shorebirds and their invertebrate prey at: 1) an individual nest level, as the difference in days between the seasonal peak in food and the peak demand by chicks, and 2) a population level, as the overlapped area under fitted curves for total daily biomass of invertebrates and dates of the peak demand by chicks. We tested whether the intensity of past climatic change observed at each site corresponded with the extent of phenological mismatch and used Structural Equation Modeling to test for causal relationships among: 1) environmental factors, including geographic location and current climatic conditions, 2) the timing of invertebrate emergence and the breeding phenology of shorebirds, and 3) the phenological mismatch between the two trophic levels. The extent of phenological mismatch varied more among different sites than among different species within each site. A greater extent of phenological mismatch at both the individual-nest and population-levels coincided with changes in the timing of snowmelt as well as the potential dissociation of long-term snow phenology from changes in temperature. The timing of snowmelt also affected the shape of the food and demand curves, which determined the extent of phenological mismatch at the population level. Finally, we found larger mismatches at more easterly longitudes, which may be affecting the population dynamics of shorebirds, as two of our study species show regional population declines in only the eastern part of their range. This suggests that phenological mismatches may be resulting in demographic consequences for arctic-nesting birds.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecm.1383","usgsCitation":"Kwon, E., Weiser, E.L., Lanctot, R.B., Brown, S.C., Gates, H.R., Gilchrist, H.G., Kendall, S.J., David B. Lank, Joseph R. Liebezeit, McKinnon, L., Erica Nol, Payer, D.C., Rausch, J., Saalfeld, S.T., Rinella, D.J., Senner, N.R., Smith, P., Ward, D., Wissman, R.C., and Sandercock, B.K., 2019, Geographic variation in the intensity of warming and phenological mismatch between Arctic shorebirds and invertebrates: Ecological Monographs, v. 89, no. 4, e01383, https://doi.org/10.1002/ecm.1383.","productDescription":"e01383","ipdsId":"IP-068533","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":467549,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11250/2607430","text":"External Repository"},{"id":364696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska","otherGeospatial":"North American Arctic","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.2734375,\n 58.03137242177637\n ],\n [\n -92.197265625,\n 58.03137242177637\n ],\n [\n -92.197265625,\n 59.17592824927136\n ],\n [\n -95.2734375,\n 59.17592824927136\n ],\n [\n -95.2734375,\n 58.03137242177637\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.671875,\n 63.60721668033077\n ],\n [\n -81.34277343749999,\n 63.60721668033077\n ],\n [\n -81.34277343749999,\n 64.49172504435471\n ],\n [\n -83.671875,\n 64.49172504435471\n ],\n [\n -83.671875,\n 63.60721668033077\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -131.923828125,\n 69.83962194067463\n ],\n [\n -159.08203125,\n 71.63599288330609\n ],\n [\n -159.169921875,\n 71.32895017791999\n ],\n [\n -157.32421875,\n 70.64176873584621\n ],\n [\n -148.271484375,\n 69.7485511291223\n ],\n [\n -139.921875,\n 68.9110048456202\n ],\n [\n -132.1875,\n 68.75231494434473\n ],\n [\n -131.923828125,\n 69.83962194067463\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -167.51953124999997,\n 64.28275952823394\n ],\n [\n -164.8828125,\n 64.28275952823394\n ],\n [\n -164.8828125,\n 65.18303007291382\n ],\n [\n -167.51953124999997,\n 65.18303007291382\n ],\n [\n -167.51953124999997,\n 64.28275952823394\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.59765625,\n 66.19600891267761\n ],\n [\n -160.13671875,\n 66.19600891267761\n ],\n [\n -160.13671875,\n 67.33986082559095\n ],\n [\n -162.59765625,\n 67.33986082559095\n ],\n [\n -162.59765625,\n 66.19600891267761\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"89","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Kwon, Enubi","contributorId":216232,"corporation":false,"usgs":false,"family":"Kwon","given":"Enubi","email":"","affiliations":[{"id":33062,"text":"Division of Biology, Kansas State University","active":true,"usgs":false}],"preferred":false,"id":764254,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weiser, Emily L. 0000-0003-1598-659X","orcid":"https://orcid.org/0000-0003-1598-659X","contributorId":213770,"corporation":false,"usgs":true,"family":"Weiser","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":764294,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lanctot, Richard B.","contributorId":31894,"corporation":false,"usgs":true,"family":"Lanctot","given":"Richard","email":"","middleInitial":"B.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false},{"id":135,"text":"Biological Resources Division","active":false,"usgs":true},{"id":7029,"text":"Queen's University, Kingston, Ontario, Canada","active":true,"usgs":false},{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":764295,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Stephen C. 0000-0002-0421-1660","orcid":"https://orcid.org/0000-0002-0421-1660","contributorId":208214,"corporation":false,"usgs":false,"family":"Brown","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":37764,"text":"Shorebird Recovery Program","active":true,"usgs":false}],"preferred":false,"id":764296,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gates, H. 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Lank","contributorId":203668,"corporation":false,"usgs":false,"family":"David B. Lank","affiliations":[{"id":36678,"text":"Simon Fraser University","active":true,"usgs":false}],"preferred":false,"id":764300,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Joseph R. Liebezeit","contributorId":203669,"corporation":false,"usgs":false,"family":"Joseph R. Liebezeit","affiliations":[{"id":36680,"text":"Audubon Society of Portland","active":true,"usgs":false}],"preferred":false,"id":764301,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McKinnon, Laura","contributorId":169353,"corporation":false,"usgs":false,"family":"McKinnon","given":"Laura","email":"","affiliations":[],"preferred":false,"id":764302,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Erica Nol","contributorId":203671,"corporation":false,"usgs":false,"family":"Erica Nol","affiliations":[{"id":36679,"text":"Trent University","active":true,"usgs":false}],"preferred":false,"id":764303,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Payer, David C.","contributorId":7495,"corporation":false,"usgs":false,"family":"Payer","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":764304,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Rausch, Jennie","contributorId":203672,"corporation":false,"usgs":false,"family":"Rausch","given":"Jennie","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":764305,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Saalfeld, Sarah T.","contributorId":208223,"corporation":false,"usgs":false,"family":"Saalfeld","given":"Sarah","email":"","middleInitial":"T.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":764306,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Rinella, Daniel J.","contributorId":69048,"corporation":false,"usgs":true,"family":"Rinella","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":764307,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Senner, Nathan R.","contributorId":140465,"corporation":false,"usgs":false,"family":"Senner","given":"Nathan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":764308,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Ward, David 0000-0002-3355-0637","orcid":"https://orcid.org/0000-0002-3355-0637","contributorId":216231,"corporation":false,"usgs":true,"family":"Ward","given":"David","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":764253,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Smith, Paul A.","contributorId":73477,"corporation":false,"usgs":true,"family":"Smith","given":"Paul A.","affiliations":[],"preferred":false,"id":764309,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Wissman, Robert C.","contributorId":89119,"corporation":false,"usgs":true,"family":"Wissman","given":"Robert","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":764310,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Sandercock, Brett K.","contributorId":95816,"corporation":false,"usgs":true,"family":"Sandercock","given":"Brett","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":764311,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70202636,"text":"sir20195015 - 2019 - Evaluation of land subsidence and ground failures at Bicycle Basin, Fort Irwin National Training Center, California, 1992–2017","interactions":[],"lastModifiedDate":"2019-06-26T13:06:37","indexId":"sir20195015","displayToPublicDate":"2019-06-05T08:40:10","publicationYear":"2019","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":"2019-5015","displayTitle":"Evaluation of Land Subsidence and Ground Failures at Bicycle Basin, Fort Irwin National Training Center, California, 1992–2017","title":"Evaluation of land subsidence and ground failures at Bicycle Basin, Fort Irwin National Training Center, California, 1992–2017","docAbstract":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Dispersal shapes demographic processes and therefore is fundamental to understanding biological, ecological, and evolutionary processes acting within populations. However, assessing population connectivity in scoters (Melanitta sp.) is challenging as these species have large spatial distributions that span remote landscapes, have varying nesting distributions (disjunct vs. continuous), exhibit unknown levels of dispersal, and vary in the timing of the formation of pair bonds (winter vs. fall/spring migration) that may influence the distribution of genetic diversity. Here, we used double‐digest restriction‐associated DNA sequence (ddRAD) and microsatellite genotype data to assess population structure within the three North American species of scoter (black scoter, M. americana; white‐winged scoter, M. deglandi; surf scoter, M. perspicillata), and between their European congeners (common scoter, M. nigra; velvet scoter, M. fusca). We uncovered no or weak genomic structure (ddRAD ΦST < 0.019; microsatellite FST < 0.004) within North America but high levels of structure among European congeners (ddRAD ΦST > 0.155, microsatellite FST > 0.086). The pattern of limited genomic structure within North America is shared with other sea duck species and is often attributed to male‐biased dispersal. Further, migratory tendencies (east vs. west) of female surf and white‐winged scoters in central Canada are known to vary across years, providing additional opportunities for intracontinental dispersal and a mechanism for the maintenance of genomic connectivity across North America. In contrast, the black scoter had relatively elevated levels of divergence between Alaska and Atlantic sites and a second genetic cluster found in Alaska at ddRAD loci was concordant with its disjunct breeding distribution suggestive of a dispersal barrier (behavioral or physical). Although scoter populations appear to be connected through a dispersal network, a small percentage (<4%) of ddRAD loci had elevated divergence which may be useful in linking areas (nesting, molting, staging, and wintering) throughout the annual cycle.
Porosity is one of the most important parameters to assess in-place oil or gas in reservoirs, and to evaluate recovery from enhanced production operations. Since it is relatively well-established to determine porosity using different laboratory and field methods, its value is usually determined at many locations across a reservoir as part of the common practice to capture reservoir heterogeneity and the variability in values. This suite of measurements and the distribution of values are most valuable for probabilistic reservoir assessments, and for spatial modeling if the exact data locations are known.
Despite the importance of individual measurements to set the range of values for probabilistic studies, it is not always possible to access these data due to confidentiality. In most cases, commercial or publicly available databases that assessments may rely on usually report only mean values of porosity, like any other reservoir data, or they may not report a value at all. This makes both quantifying the mean value and the uncertainty around it difficult for probabilistic assessments.
In this study, the TORIS (Tertiary Oil Recovery Information System) dataset of the National Petroleum Council and the U.S. Department of Energy was used to model porosity and the uncertainty around predicted values. TORIS is an integrated dataset of production data, reservoir properties, and project databases of crude oil reservoirs in the United States. The model presented in the paper was based on ANCOVA (Analysis of Co-Variance) of data from 1038 reservoirs from the TORIS dataset for porosity prediction, validation and testing for quantitative and qualitative parameters that may be readily available in most cases, and to estimate uncertainty around the mean values. This model also explored association of porosity values to different parameters, and to different depositional systems and diagenetic overprint conditions. Furthermore, an ANN (Artificial Neural Network) model was created to compare the predicted values of both models. Results showed that the ANN model was able to represent more of the variability, however it lacked the insights that might be gained from the ANCOVA model.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.petrol.2019.05.071","usgsCitation":"Karacan, C.O., 2019, An ANCOVA model for porosity and its uncertainty for oil reservoirs based on TORIS dataset: Journal of Petroleum Science and Engineering, 24 p., https://doi.org/10.1016/j.petrol.2019.05.071.","productDescription":"24 p.","ipdsId":"IP-103341","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":364378,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364371,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S092041051930525X"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":763708,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70216096,"text":"70216096 - 2019 - Estimating connectivity of hard clam (Mercenaria mercenaria) and eastern oyster (Crassostrea virginica) larvae in Barnegat Bay","interactions":[],"lastModifiedDate":"2020-11-04T16:44:24.630283","indexId":"70216096","displayToPublicDate":"2019-06-01T10:39:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Estimating connectivity of hard clam (Mercenaria mercenaria) and eastern oyster (Crassostrea virginica) larvae in Barnegat Bay","docAbstract":"Concentrations and emissions of greenhouse gases CO2, CH4, and N2O commonly are examined individually in aquatic environments in which each is expected to be relatively important; however, their co-occurrence and dynamic interactions in fluvial settings could provide important information about their controlling biogeochemical processes and potential contributions to global climate change. Spatial and temporal variability of CH4, N2O, and CO2 concentrations were measured from June 1999 to September 2003 in two nitrate-rich (40–1200 μM) streams draining agricultural land in the midwestern USA that differed ~13-fold in flow. Seasonal (biweekly), diel (hourly), and transport-oriented (reach-scale) sampling approaches were compared. Dissolved gas concentrations exceeded atmospheric equilibrium values up to 700- and 16-fold, for CH4 and N2O, respectively. Mean concentrations were higher in the larger stream than in the smaller stream. In both streams, CH4 emissions were generally higher in summer-fall and negatively correlated with flow and NO3− concentration while N2O emissions were generally higher in winter/spring and positively correlated with flow and NO3−. In the small stream, diel variations in the concentrations, emissions, and isotopic compositions of CH4, N2O, and NO2− resulted from diel variations in sources, sinks, and air-water gas exchange velocities. Seasonal mean total (CH4 + N2O) area-normalized emission rates, expressed as CO2 warming potential equivalents, were similar for the two streams, but the total reach-scale emission rate for the larger stream, including CO2, was about 2.9 times that of the smaller stream (131.6 vs 46.0 kg CO2 equivalents km−1 day−1, respectively). The CH4contribution to this flux was 9–28%, despite the relatively high NO3−and O2 concentrations in the streams, indicating contributions from upwelling groundwater or reactions in streambed sediment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.05.374","usgsCitation":"Smith, R.L., and Bohlke, J., 2019, Methane and nitrous oxide temporal and spatial variability in two midwestern USA streams containing high nitrate concentrations: Science of the Total Environment, v. 685, p. 574-588, https://doi.org/10.1016/j.scitotenv.2019.05.374.","productDescription":"15 p.","startPage":"574","endPage":"588","ipdsId":"IP-080054","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467581,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2019.05.374","text":"Publisher Index Page"},{"id":437440,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TH8KWZ","text":"USGS data release","linkHelpText":"Methane and nitrous oxide temporal and spatial concentrations in the Iroquois River and Sugar Creek in Northwestern Indiana and Northeastern Illinois, 1999-2003."},{"id":364586,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana","otherGeospatial":"Iroquois River, Sugar Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.8961181640625,\n 40.46993497635156\n ],\n [\n -87.11334228515625,\n 40.46993497635156\n ],\n [\n -87.11334228515625,\n 40.89067715064627\n ],\n [\n -87.8961181640625,\n 40.89067715064627\n ],\n [\n -87.8961181640625,\n 40.46993497635156\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"685","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Richard L. 0000-0002-3829-0125 rlsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-3829-0125","contributorId":1592,"corporation":false,"usgs":true,"family":"Smith","given":"Richard","email":"rlsmith@usgs.gov","middleInitial":"L.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":764011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":764012,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70206266,"text":"70206266 - 2019 - Mortality of Tufted puffins (Fratercula cirrhata) and other alcids during an unusual mortality event in the eastern Bering Sea","interactions":[],"lastModifiedDate":"2019-10-29T08:38:17","indexId":"70206266","displayToPublicDate":"2019-05-29T08:36:33","publicationYear":"2019","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":"Mortality of Tufted puffins (Fratercula cirrhata) and other alcids during an unusual mortality event in the eastern Bering Sea","docAbstract":"Mass mortality events are increasing in frequency and magnitude, potentially linked with ongoing climate change. In October 2016 through January 2017, St. Paul Island situated at the shelf-edge of the Bering Sea, Alaska, experienced a mortality event of alcids (family: Alcidae), with over 350 carcasses recovered. Almost three-quarters of the carcasses were unscavenged, a rate much higher than in baseline surveys (17%), suggesting that a sudden, large deposition event overwhelmed local scavenger populations. Based on the observation that carcasses were not observed on the neighboring island of St. George, we bounded the at-sea distribution of moribund birds, and estimated all species mortality at 8,000 to 22,000 birds. The event was particularly anomalous given the late fall/winter timing of the event when low numbers of beached birds are typical; and the predominance of Tufted puffins (Fratercula cirrhata, 79% of carcass finds) and Crested auklets (Aethia cristatella, 11% of carcass finds), species that were nearly absent from long-term baseline surveys. Collected specimens were disease-free and severely emaciated, suggesting starvation as the ultimate cause of mortality. The majority (95%, N = 245) of Tufted puffins were regrowing flight feathers, indicating a potential contribution of molt stress. Immediately prior to this event, shifts in zooplankton community composition and forage fish distribution and energy density were documented in the eastern Bering Sea following a period of elevated sea surface temperatures, evidence cumulatively suggestive of a bottom-up shift in seabird prey availability. We posit that shifts in prey composition and distribution pushing birds outside of their normal fall migration pattern, combined with the onset of molt, resulted in this mortality event","language":"English","publisher":"PLos ONE","doi":"10.1371/journal.pone.0216532","usgsCitation":"Jones, T., Divine, L.M., Renner, H., Knowles, S., Lefebvre, K.A., Burgess, H.K., Wright, C., and Parrish, J.K., 2019, Mortality of Tufted puffins (Fratercula cirrhata) and other alcids during an unusual mortality event in the eastern Bering Sea: PLoS ONE, v. 14, no. 5, e0216532, 23 p., https://doi.org/10.1371/journal.pone.0216532.","productDescription":"e0216532, 23 p.","ipdsId":"IP-101916","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":467586,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0216532","text":"Publisher Index Page"},{"id":368694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bering Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -182.98828124999997,\n 49.15296965617042\n ],\n [\n -147.3046875,\n 49.15296965617042\n ],\n [\n -147.3046875,\n 62.59334083012024\n ],\n [\n -182.98828124999997,\n 62.59334083012024\n ],\n [\n -182.98828124999997,\n 49.15296965617042\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"5","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Timothy","contributorId":220052,"corporation":false,"usgs":false,"family":"Jones","given":"Timothy","email":"","affiliations":[{"id":40123,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, United States of America","active":true,"usgs":false}],"preferred":false,"id":773997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Divine, Laura M.","contributorId":220056,"corporation":false,"usgs":false,"family":"Divine","given":"Laura","email":"","middleInitial":"M.","affiliations":[{"id":40124,"text":"Aleut Community of St. Paul Island Ecosystem Conservation Office, St. Paul, Pribilof Islands, Alaska, United States of America","active":true,"usgs":false}],"preferred":false,"id":774001,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Renner, Heather","contributorId":200807,"corporation":false,"usgs":false,"family":"Renner","given":"Heather","affiliations":[],"preferred":false,"id":774002,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knowles, Susan 0000-0002-0254-6491 sknowles@usgs.gov","orcid":"https://orcid.org/0000-0002-0254-6491","contributorId":5254,"corporation":false,"usgs":true,"family":"Knowles","given":"Susan","email":"sknowles@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":773996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lefebvre, Kathi A.","contributorId":220057,"corporation":false,"usgs":false,"family":"Lefebvre","given":"Kathi","email":"","middleInitial":"A.","affiliations":[{"id":40125,"text":"Environmental and Fisheries Sciences Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, Washington, United States of America","active":true,"usgs":false}],"preferred":false,"id":774003,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burgess, Hillary K.","contributorId":220053,"corporation":false,"usgs":false,"family":"Burgess","given":"Hillary","email":"","middleInitial":"K.","affiliations":[{"id":40123,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, United States of America","active":true,"usgs":false}],"preferred":false,"id":773998,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wright, Charlie","contributorId":220054,"corporation":false,"usgs":false,"family":"Wright","given":"Charlie","email":"","affiliations":[{"id":40123,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, United States of America","active":true,"usgs":false}],"preferred":false,"id":773999,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Parrish, Julia K.","contributorId":220055,"corporation":false,"usgs":false,"family":"Parrish","given":"Julia","email":"","middleInitial":"K.","affiliations":[{"id":40123,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, United States of America","active":true,"usgs":false}],"preferred":false,"id":774000,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203733,"text":"70203733 - 2019 - Ross Ice Shelf response to climate driven by the tectonic imprint on seafloor bathymetry","interactions":[],"lastModifiedDate":"2019-06-07T14:40:03","indexId":"70203733","displayToPublicDate":"2019-05-27T14:23:35","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Ross Ice Shelf response to climate driven by the tectonic imprint on seafloor bathymetry","docAbstract":"Ocean melting has thinned Antarctica's ice shelves at an increasing rate over the past two decades, leading to loss of grounded ice. The Ross Ice Shelf is currently close to steady state but geological records indicate that it can disintegrate rapidly, which would accelerate grounded ice loss from catchments equivalent to 11.6 m of global sea level rise. Here, we use data from the ROSETTA-Ice airborne survey and new ocean simulations, to identify the principal threats to Ross Ice Shelf stability. We locate the tectonic boundary between East and West Antarctica from magnetic anomalies and use gravity data to generate a new high-resolution map of sub-ice-shelf bathymetry. The tectonic imprint on bathymetry constrains sub-ice-shelf ocean circulation, protecting the ice shelf grounding line from moderate changes in global ocean heat content. In contrast, local, seasonal production of warm upper-ocean water near the ice front drives rapid ice shelf melting east of Ross Island, where thinning would lead to faster grounded ice loss from both East and West Antarctic ice sheets. We confirm high modelled melt rates in this region using ROSETTA-Ice radar data. Our findings highlight the significance of both the tectonic framework and local ocean-atmosphere exchange processes near the ice front in determining the future of the Antarctic Ice Sheet.","language":"English","publisher":"Springer Nature Publishing AG","doi":"10.1038/s41561-019-0370-2","usgsCitation":"Tinto, K., Padman, L., Siddoway, C.S., Springer, M., Fricker, H., Das, I., Caratori Tontini, F., Porter, D., Frearson, N., Howard, S., Siegfried, M., Mosbeux, C., Becker, M., Bertinato, C., Boghosian, A., Brady, N., Burton, B.L., Chu, W., Cordero, S., Dhakal, T., Dong, L., Gustafson, C., Keeshin, S., Locke, C., Lockett, A., O'Brien, G., Spergel, J., Starke, S., Tankersley, M., Wearing, M., and Bell, R.E., 2019, Ross Ice Shelf response to climate driven by the tectonic imprint on seafloor bathymetry: Nature Geoscience, v. 12, p. 441-449, https://doi.org/10.1038/s41561-019-0370-2.","productDescription":"9 p.","startPage":"441","endPage":"449","ipdsId":"IP-103834","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":364522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, Ross Ice Shelf","volume":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Tinto, K J","contributorId":216084,"corporation":false,"usgs":false,"family":"Tinto","given":"K J","affiliations":[{"id":39364,"text":"Columbia University LDEO","active":true,"usgs":false}],"preferred":false,"id":763859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Padman, L","contributorId":216085,"corporation":false,"usgs":false,"family":"Padman","given":"L","email":"","affiliations":[{"id":39365,"text":"Earth & Space Research","active":true,"usgs":false}],"preferred":false,"id":763860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Siddoway, C S","contributorId":216086,"corporation":false,"usgs":false,"family":"Siddoway","given":"C","email":"","middleInitial":"S","affiliations":[{"id":37163,"text":"Colorado College","active":true,"usgs":false}],"preferred":false,"id":763861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Springer, M.R.","contributorId":216087,"corporation":false,"usgs":false,"family":"Springer","given":"M.R.","email":"","affiliations":[{"id":39366,"text":"Earth and Space Research","active":true,"usgs":false}],"preferred":false,"id":763862,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fricker, H.A.","contributorId":216088,"corporation":false,"usgs":false,"family":"Fricker","given":"H.A.","email":"","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":763863,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Das, I.","contributorId":216089,"corporation":false,"usgs":false,"family":"Das","given":"I.","email":"","affiliations":[{"id":39367,"text":"Columbia University, LDEO","active":true,"usgs":false}],"preferred":false,"id":763864,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Caratori Tontini, F.","contributorId":216090,"corporation":false,"usgs":false,"family":"Caratori Tontini","given":"F.","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":763865,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Porter, D.F.","contributorId":216091,"corporation":false,"usgs":false,"family":"Porter","given":"D.F.","email":"","affiliations":[{"id":39367,"text":"Columbia University, LDEO","active":true,"usgs":false}],"preferred":false,"id":763866,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Frearson, N.P.","contributorId":216092,"corporation":false,"usgs":false,"family":"Frearson","given":"N.P.","email":"","affiliations":[{"id":39367,"text":"Columbia University, LDEO","active":true,"usgs":false}],"preferred":false,"id":763867,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Howard, S. 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A.","contributorId":216105,"corporation":false,"usgs":false,"family":"Lockett","given":"A.","email":"","affiliations":[{"id":37163,"text":"Colorado College","active":true,"usgs":false}],"preferred":false,"id":763882,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"O'Brien, G.","contributorId":216106,"corporation":false,"usgs":false,"family":"O'Brien","given":"G.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":763883,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Spergel, J.J.","contributorId":216107,"corporation":false,"usgs":false,"family":"Spergel","given":"J.J.","email":"","affiliations":[{"id":39367,"text":"Columbia University, LDEO","active":true,"usgs":false}],"preferred":false,"id":763884,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Starke, S.E.","contributorId":216108,"corporation":false,"usgs":false,"family":"Starke","given":"S.E.","email":"","affiliations":[{"id":39367,"text":"Columbia University, LDEO","active":true,"usgs":false}],"preferred":false,"id":763885,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Tankersley, M.","contributorId":216109,"corporation":false,"usgs":false,"family":"Tankersley","given":"M.","email":"","affiliations":[{"id":37163,"text":"Colorado College","active":true,"usgs":false}],"preferred":false,"id":763886,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Wearing, M.","contributorId":216110,"corporation":false,"usgs":false,"family":"Wearing","given":"M.","email":"","affiliations":[{"id":39367,"text":"Columbia University, LDEO","active":true,"usgs":false}],"preferred":false,"id":763887,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Bell, R. E.","contributorId":216111,"corporation":false,"usgs":false,"family":"Bell","given":"R.","email":"","middleInitial":"E.","affiliations":[{"id":39367,"text":"Columbia University, LDEO","active":true,"usgs":false}],"preferred":false,"id":763888,"contributorType":{"id":1,"text":"Authors"},"rank":31}]}} ,{"id":70215293,"text":"70215293 - 2019 - Predicting hydrologic disturbance of streams using species occurrence data","interactions":[],"lastModifiedDate":"2020-10-14T15:39:43.431592","indexId":"70215293","displayToPublicDate":"2019-05-25T10:32:10","publicationYear":"2019","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":"Predicting hydrologic disturbance of streams using species occurrence data","docAbstract":"Aquatic organisms have adapted over evolutionary time-scales to hydrologic variability represented by the natural flow regime of rivers and streams in their unimpaired state. Rapid landscape change coupled with growing human demand for water have altered natural flow regimes of many rivers and streams on a global scale. Climate non-stationarity is expected to further intensify hydrologic variability, placing increased pressure on aquatic communities. Using a machine learning approach and georeferenced species occurrence data, we modeled and mapped spatial patterns of hydrologic disturbance for streams in Arkansas, Missouri, and eastern Oklahoma. Random forest (RF) models trained on fish community data, hydrologic, and landscape metrics for gaged streams in the National Hydrography (NHDPlusV2) database were used to predict a hydrologic disturbance index (HDI) for ungaged streams. The HDI is part of the USGS Geospatial Attributes of Gages for Evaluating Streamflow (GAGESII) database and is a composite index of watershed-scale disturbance from anthropogenic stressors. Fish presence/absence data had similar overall model prediction accuracy (77%; 95% CI: 0.74, 0.80) as flow variables (76%; CI: 0.73, 0.80). Including topographic variables increased the RF prediction accuracy of both the fish (90%; CI: 0.88, 0.92) and flow models (86%; CI: 0.84, 0.89). Spatial patterns of hydrologic disturbance suggest distinct ecohydrological regions exist where conservation actions may be focused. Streams with low HDI were predominately located in the Ozark Highlands, Boston Mountains, and Ouachita Mountains. Correlation analysis of HDI by flow regime showed groundwater stable streams had the lowest disturbance frequency, with over 50% of stream reaches with low HDI located in forested land cover. HDI was highest for big rivers, intermittent runoff streams and streams in areas of agricultural land use. Our results show long-term georeferenced biological data can provide a valuable resource for predictive modeling of hydrologic disturbance for ungaged rivers and streams.
Avian avulavirus (commonly known as avian paramyxovirus-1 or APMV-1) can cause disease of varying severity in both domestic and wild birds. Understanding how viruses move among hosts and geography would be useful for informing prevention and control efforts. A Bayesian statistical framework was employed to estimate the evolutionary history of 1602 complete fusion gene APMV-1 sequences collected from 1970 to 2016 in order to infer viral transmission between avian host orders and diffusion among geographic regions. Ancestral states were estimated with a non-reversible continuous-time Markov chain model, allowing transition rates between discrete states to be calculated. The evolutionary analyses were stratified by APMV-1 classes I (n = 198) and II (n = 1404), and only those sequences collected between 2006 and 2016 were allowed to contribute host and location information to the viral migration networks.
While the current data was unable to assess impact of host domestication status on APMV-1 diffusion, these analyses supported the sharing of APMV-1 among divergent host taxa. The highest supported transition rate for both classes existed from domestic chickens to Anseriformes (class I:6.18 transitions/year, 95% highest posterior density (HPD) 0.31–20.02, Bayes factor (BF) = 367.2; class II:2.88 transitions/year, 95%HPD 1.9–4.06, BF = 34,582.9). Further, among class II viruses, domestic chickens also acted as a source for Columbiformes (BF = 34,582.9), other Galliformes (BF = 34,582.9), and Psittaciformes (BF = 34,582.9). Columbiformes was also a highly supported source to Anseriformes (BF = 322.0) and domestic chickens (BF = 402.6). Additionally, our results provide support for the diffusion of viruses among continents and regions, but no interhemispheric viral exchange between 2006 and 2016. Among class II viruses, the highest transition rates were estimated from South Asia to the Middle East (1.21 transitions/year; 95%HPD 0.36–2.45; BF = 67,107.8), from Europe to East Asia (1.17 transitions/year; 95%HPD 0.12–2.61; BF = 436.2) and from Europe to Africa (1.06 transitions/year, 95%HPD 0.07–2.51; BF = 169.3).
While migration appears to occur infrequently, geographic movement may be important in determining viral diversification and population structure. In contrast, inter-order transmission of APMV-1 may occur readily, but most events are transient with few lineages persisting in novel hosts.
Waterfowl are the natural hosts of avian influenza virus (AIV), and through migration spread the virus worldwide. Most AIVs carried by wild waterfowl are low pathogenic strains; however, Goose/Guangdong/1996 lineage clade 2.3.4.4 H5 highly pathogenic (HP) AIV now appears to be endemic in wild birds in much of the Eastern Hemisphere. Most research efforts studying AIV pathogenicity in waterfowl thus far have been directed toward dabbling ducks. In order to better understand the role of diving ducks in AIV ecology, we previously characterized the pathogenesis of clade 2.3.4.4 H5 HPAIV in lesser scaup (Aythya affinis). In an effort to further elucidate AIV infection in diving ducks, the relative susceptibility and pathogenesis of two North American lineage H7 HPAIV isolates from the most recent outbreaks in the United States was investigated. Lesser scaup were inoculated with either A/turkey/IN/1403-1/2016 H7N8 or A/chicken/TN/17-007147-2/2017 H7N9 HPAIV by the intranasal route. The approximate 50% bird infectious dose (BID50) of the H7N8 isolate was determined to be 103 50% egg infectious doses (EID50), and the BID50 of the H7N9 isolate was determined to be <102 EID50, indicating some variation in adaptation between the two isolates. No mortality or clinical disease was observed in either group except for elevated body temperatures at 2 and 4 days postinoculation (DPI). Virus shedding was detected up to 14 DPI from both groups, and there was a trend for shedding to have a longer duration and at higher titer levels from the cloacal route. These results demonstrate that lesser scaup are susceptible to both H7 lineages of HPAIV, and similar to dabbling duck species, they shed virus for long periods relative to gallinaceous birds and don't present with clinical disease.
Eastern carpenter bees, Xylocopa virginica (L.) (Hymenoptera: Apidae), are among the most abundant native bee visitors to highbush blueberry, Vaccinium corymbosum L., flowers in the northeastern United States, and they sometimes display corolla-slitting behavior to rob nectar. We studied foraging behavior of X. virginica on 14 blueberry cultivars in an experimental planting in Rhode Island, and assessed factors related to slitting frequency, and the effects of slitting on fruit set and blueberry quality. Among 14 cultivars in bloom, an average of 35% (range 16–67%) of flowers were slit in 2017, and 39% (range 20–62%) in 2018. Factors that affected the proportion of corollas slit included cultivar, anther length, flower volume, and number of days in bloom at or above 15°C. Corolla slitting did not affect fruit set. Average weight and percent soluble solids of fruit resulting from slit and non-slit corollas did not differ significantly in two early- (‘Bluehaven’, ‘Earliblue’), two mid- (‘Collins’, ‘Bluecrop’), and two late-season (‘Herbert’, ‘Lateblue’) ripening cultivars in 2017. In 2018, average fruit weight and percent soluble solids resulting from slit and non-slit flowers did not differ significantly in most cultivars, but slit corollas resulted in berries with greater mass in two cultivars, ‘Bluehaven’ and ‘Collins’. ‘Collins’ fruit from non-slit corollas had a significantly higher percentage of soluble solids at maturity than fruit from slit corollas in 2018. Corolla slitting and nectar robbery by X. virginica did not have a significant negative effect on fruit quality under the described growing conditions and pollinator community.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/ee/nvz055","usgsCitation":"Tucker, S.K., Ginsberg, H., and Alm, S.R., 2019, Effect of corolla slitting and nectar robbery by the Eastern Carpenter Bee (Hymenoptera: Apidae) on fruit quality of Vaccinium corymbosum, L.; (Ericales: Ericaceae).: Environmental Entomology, v. 48, no. 3, p. 718-726, https://doi.org/10.1093/ee/nvz055.","productDescription":"9 p.","startPage":"718","endPage":"726","ipdsId":"IP-104445","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467612,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ee/nvz055","text":"Publisher Index Page"},{"id":364524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Rhode 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Island\",\"nation\":\"USA \"}}]}","volume":"48","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Tucker, Sara K","contributorId":216119,"corporation":false,"usgs":false,"family":"Tucker","given":"Sara","email":"","middleInitial":"K","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":763919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":763918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alm, Steven R.","contributorId":177872,"corporation":false,"usgs":false,"family":"Alm","given":"Steven","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":763920,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203460,"text":"70203460 - 2019 - Assessment of coal mine methane (CMM) and abandoned mine methane (AMM) resource potential of longwall mine panels: example from Northern Appalachian Basin, USA","interactions":[],"lastModifiedDate":"2019-05-15T15:06:14","indexId":"70203460","displayToPublicDate":"2019-05-15T14:42:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of coal mine methane (CMM) and abandoned mine methane (AMM) resource potential of longwall mine panels: example from Northern Appalachian Basin, USA","docAbstract":"\"Coal mine methane (CMM) and abandoned mine methane (AMM), are by-products of underground coal mining. The quantity and the emission rate of CMM and AMM may vary depending on the type of mine, gas content of the mined coal seam, and gas sourced from strata and coal beds in overlying and underlying formations affected by mining. Therefore, if a mine has the potential of accumulating gas after being abandoned and sealed properly, methane may be produced and used as an energy source to serve to local communities around the mine. Producing AMM also prevents methane, which is a potent greenhouse gas, from leaking to the atmosphere through seals, shaft plugs or surface cracks. \nOne of the technical barriers in front of investments to economical utilization of CMM and AMM is the difficulty to predict how much methane may be available in the gas emission zone (GEZ) as a resource during mining, and after the panels are sealed and the mine is abandoned. Another difficulty is to estimate how much of the potential methane resource can be produced, and its production feasibility with boreholes, such as gob gas ventholes (GGV) converted to capture AMM.\nIn this study, a comparative assessment is presented to address the issues stated above. The assessment was conducted on two adjacent panels of a longwall mine that operated until 2016 in the Pennsylvania section of the Northern Appalachian Basin. The study is based on two approaches that might be used depending on the availability of data, extensive or minimal. The first approach uses an extensive geological data set, geostatistics, and measured shaft gas emission and GGV production values that were collected while the panel(s) were active to assess the AMM resource. The second approach uses a minimal amount of geologic data and its uncertainty as probabilistic distributions as well as predicted during-mining emissions using a publicly available software. Results showed that both approaches provide relatively comparable estimates of AMM resources and AMM recovery potential using wellbores. The differences in assessed quantities are mostly due to the characteristics of the two methods. In that regard, this paper can be considered as guidance to choose the assessment approach based on data availability.\n\"","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2019.04.005","collaboration":"none","usgsCitation":"Karacan, C.O., and Warwick, P., 2019, Assessment of coal mine methane (CMM) and abandoned mine methane (AMM) resource potential of longwall mine panels: example from Northern Appalachian Basin, USA: International Journal of Coal Geology, v. 208, p. 37-53, https://doi.org/10.1016/j.coal.2019.04.005.","productDescription":"17 p.","startPage":"37","endPage":"53","ipdsId":"IP-103342","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":363934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern Appalachian Basin","volume":"208","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":762770,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warwick, Peter D. 0000-0002-3152-7783","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":205928,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":762771,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70202335,"text":"ofr20191016 - 2019 - Analysis for agreement of the Northern Gulf of Mexico topobathymetric digital elevation model with 3-Dimensional Elevation Program 1/3 arc-second digital elevation models","interactions":[],"lastModifiedDate":"2019-05-14T11:43:13","indexId":"ofr20191016","displayToPublicDate":"2019-05-13T11:35:20","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1016","displayTitle":"Analysis for Agreement of the Northern Gulf of Mexico Topobathymetric Digital Elevation Model with 3-Dimensional Elevation Program 1/3 Arc-Second Digital Elevation Models","title":"Analysis for agreement of the Northern Gulf of Mexico topobathymetric digital elevation model with 3-Dimensional Elevation Program 1/3 arc-second digital elevation models","docAbstract":"Topographical differencing and edge-matching analyses were used to evaluate agreement of the Coastal National Elevation Database Applications Project’s Northern Gulf of Mexico topobathymetric digital elevation model (TBDEM) with The National Map 3-Dimensional Elevation Program (3DEP) 1/3 arc-second digital elevation models (DEMs). In addition to topographic map products provided through the National Geospatial Program, the model integrates bathymetric and topobathymetric datasets for three-dimensional (3D) mapping of rivers, lakes, and bays in the upland and intertidal wetlands to offshore environments in coastal zones from the border between Texas and Louisiana to east of Mobile Bay, Alabama.
Contoured elevation differences between the Northern Gulf of Mexico TBDEM and the 3DEP 1/3 arc-second DEMs indicate that 85 percent of elevation data in the Northern Gulf of Mexico TBDEM agree (no difference for contoured elevations) between 95 and 100 percent with 3DEP 1/3 arc-second DEMs. Edge matching differences between adjacent Northern Gulf of Mexico TBDEM source projects or between the TBDEM and 3DEP DEMs indicate most seams between integrated and 3DEP DEMs are smooth. Where seams did not match, most differences were in the range of tenths to hundredths of a meter. Valid differences that are greater than plus or minus 2 meters in areas of bathymetric data are found in the Mississippi River, Atchafalaya River, Lower Atchafalaya River, Wax Lake Pass channel, the Vermilion Bay bathymetric datasets, and where topobathymetric datasets are integrated in the model. Areas with positive or negative outlier difference elevations seem to be a result of site conditions that affect light detection and ranging (lidar) waveform return signals, misclassification of surface features, or possibly because of interpolation required to develop a smooth elevation surface. Results of this analysis provide information to help understand model parameters and agreement of the Northern Gulf of Mexico TBDEM developed using different data types from different sources with The National Map 3DEP DEMs.
Inclusion of bathymetric and topobathymetric data types in the 3DEP aligns with the mission to respond to growing needs for a wide range of three-dimensional representations of the Nation and supports the U.S. Geological Survey strategy for developing a National Terrain Model to provide hydrographic and elevation data that extend the elevation surface below water bodies. The 3D Nation Requirements and Benefits Study sponsored by the U.S. Geological Survey and National Oceanic and Atmospheric Administration to assess local to regional Tribal, State, and Federal technical requirements, needs, and benefits for using topographic and bathymetric 3DEP elevation data will be used to help develop and refine future program alternatives for 3D elevation data that include a category for bathymetry and topobathymetry. At the time of this report (2019), 3DEP acquisition is specific to topographic lidar that meets lidar DEM specifications and which requires surface-water feature areas to be hydroflattened. Cataloging bathymetric and topobathymetric DEMs as part of the 3DEP will require new specifications for acoustic, lidar, merged acoustic and lidar, and possibly other bathymetric and topobathymetric survey data types.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191016","usgsCitation":"Miller-Corbett, C., 2019, Analysis for agreement of the Northern Gulf of Mexico topobathymetric digital elevation model with 3-Dimensional Elevation Program 1/3 arc-second digital elevation models: U.S. Geological Survey Open-File Report 2019–1016, 44 p., https://doi.org/10.3133/ofr20191016.","productDescription":"vi, 43 p.","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-081383","costCenters":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"links":[{"id":363655,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1016/ofr20191016.pdf","text":"Report","size":"16.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1016"},{"id":363654,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1016/coverthb.jpg"}],"country":"United States","state":"Alabama, Florida, Louisiana, Mississippi, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.48193359375,\n 28.43971381702788\n ],\n [\n -84.13330078125,\n 28.43971381702788\n ],\n [\n -84.13330078125,\n 31.39115752282472\n ],\n [\n -96.48193359375,\n 31.39115752282472\n ],\n [\n -96.48193359375,\n 28.43971381702788\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Emperor geese (Anser canagicus) are endemic to coastal areas within Beringia and have previously been found to have antibodies to or to be infected with influenza A viruses (IAVs) in Alaska. In this study, we use virological, serological and tracking data to further elucidate the role of emperor geese in the ecology of IAVs in Beringia during the non‐breeding period. Specifically, we assess evidence for: (a) active IAV infection during spring staging, autumn staging and wintering periods; (b) infection with novel Eurasian‐origin or interhemispheric reassortant viruses; (c) contemporary movement of geese between East Asia and North America; (d) previous exposure to viruses of 14 haemagglutinin subtypes, including Eurasian lineage highly pathogenic (HP) H5 IAVs; and (e) subtype‐specific antibody seroconversion and seroreversion. Emperor geese were found to shed IAVs, including interhemispheric reassortant viruses, throughout the non‐breeding period; migrate between Alaska and the Russian Far East prior to and following remigial moult; have antibodies reactive to a diversity of IAVs including, in a few instances, Eurasian lineage HP H5 IAVs; and exhibit relatively broad and stable patterns of population immunity among breeding females. Results of this study suggest that emperor geese may play an important role in the maintenance and dispersal of IAVs within Beringia during the non‐breeding period and provide information that may be used to further optimize surveillance activities focused on the early detection of Eurasian‐origin IAVs in North America.
","language":"English","publisher":"Wiley","doi":"10.1111/tbed.13226","usgsCitation":"Ramey, A.M., Uher-Koch, B.D., Reeves, A.B., Schmutz, J.A., Poulson, R., and Stallknecht, D.E., 2019, Emperor geese (Anser canagicus) are exposed to a diversity of influenza A viruses, are infected during the non-breeding period and contribute to intercontinental viral dispersal: Transboundary and Emerging Diseases, v. 66, no. 5, p. 1958-1970, https://doi.org/10.1111/tbed.13226.","productDescription":"13 P.","startPage":"1958","endPage":"1970","ipdsId":"IP-106647","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":467622,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/tbed.13226","text":"Publisher Index Page"},{"id":437465,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VFN3JD","text":"USGS data release","linkHelpText":"Influenza A Virus Data from Emperor Geese, Alaska"},{"id":364698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","state":"Alaska","volume":"66","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":764260,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Uher-Koch, Brian D. 0000-0002-1885-0260 buher-koch@usgs.gov","orcid":"https://orcid.org/0000-0002-1885-0260","contributorId":5117,"corporation":false,"usgs":true,"family":"Uher-Koch","given":"Brian","email":"buher-koch@usgs.gov","middleInitial":"D.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":764261,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":764262,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":764263,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poulson, Rebecca L.","contributorId":198807,"corporation":false,"usgs":false,"family":"Poulson","given":"Rebecca L.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":764264,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stallknecht, David E.","contributorId":14323,"corporation":false,"usgs":false,"family":"Stallknecht","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":764265,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227670,"text":"70227670 - 2019 - Genetic variation among island and continental populations of Burrowing Owl (Athene cunicularia) subspecies in North America","interactions":[],"lastModifiedDate":"2022-01-26T16:00:00.916345","indexId":"70227670","displayToPublicDate":"2019-05-09T09:54:31","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Genetic variation among island and continental populations of Burrowing Owl (Athene cunicularia) subspecies in North America","title":"Genetic variation among island and continental populations of Burrowing Owl (Athene cunicularia) subspecies in North America","docAbstract":"Burrowing Owls (Athene cunicularia) have a large geographic range spanning both North and South America and resident populations occur on many islands in the eastern Pacific Ocean and the Caribbean Sea. Many owl populations are isolated and disjunct from other populations, but studies on genetic variation within and among populations are limited. We characterized DNA microsatellite variation in populations varying in size and geographic isolation in the Florida (A. c. floridana), the Western (A. c. hypugaea), and the Clarion (A. c. rostrata) subspecies of the Burrowing Owl. We also characterized genetic variation in a geographically isolated population of the western subspecies in central Mexico (near Texcoco Lake). Clarion Burrowing Owls had no intrapopulation variation (i.e., fixation) at 5 out of 11 microsatellite loci, a likely outcome of genetic drift in an isolated and small population. The Florida subspecies had only polymorphic loci but had reduced levels of genetic variation compared with the more-widespread western subspecies that occurs throughout western North America. Despite the extensive geographic distribution of the Western Burrowing Owl, we found genetic differentiation between the panmictic population north of the Trans-Mexican Volcanic Belt and the resident Texcoco Lake population in central Mexico.
","language":"English","publisher":"The Raptor Research Foundation, Inc","doi":"10.3356/JRR-18-00002","usgsCitation":"Macias-Duarte, A., Conway, C.J., Holroyd, G.L., Valdez-Gomez, H.E., and Culver, M., 2019, Genetic variation among island and continental populations of Burrowing Owl (Athene cunicularia) subspecies in North America: Journal of Raptor Research, v. 53, no. 2, p. 127-133, https://doi.org/10.3356/JRR-18-00002.","productDescription":"7 p.","startPage":"127","endPage":"133","ipdsId":"IP-057792","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":467626,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3356/jrr-18-00002","text":"Publisher Index Page"},{"id":394870,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.0234375,\n 24.686952411999155\n ],\n [\n -79.541015625,\n 24.686952411999155\n ],\n [\n -79.541015625,\n 29.99300228455108\n ],\n [\n -84.0234375,\n 29.99300228455108\n ],\n [\n -84.0234375,\n 24.686952411999155\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.22265625000001,\n 18.312810846425442\n ],\n [\n -94.658203125,\n 18.312810846425442\n ],\n [\n -94.658203125,\n 55.178867663281984\n ],\n [\n -123.22265625000001,\n 55.178867663281984\n ],\n [\n -123.22265625000001,\n 18.312810846425442\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"53","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Macias-Duarte, Alberto","contributorId":70605,"corporation":false,"usgs":true,"family":"Macias-Duarte","given":"Alberto","email":"","affiliations":[],"preferred":false,"id":831674,"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":831673,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holroyd, Geoffrey L.","contributorId":272179,"corporation":false,"usgs":false,"family":"Holroyd","given":"Geoffrey","email":"","middleInitial":"L.","affiliations":[{"id":56364,"text":"environ canada","active":true,"usgs":false}],"preferred":false,"id":831675,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valdez-Gomez, Hector E.","contributorId":272180,"corporation":false,"usgs":false,"family":"Valdez-Gomez","given":"Hector","email":"","middleInitial":"E.","affiliations":[{"id":56365,"text":"Universidad Autónoma de Nuevo León,","active":true,"usgs":false}],"preferred":false,"id":831676,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Culver, Melanie 0000-0001-5380-3059 mculver@usgs.gov","orcid":"https://orcid.org/0000-0001-5380-3059","contributorId":197693,"corporation":false,"usgs":true,"family":"Culver","given":"Melanie","email":"mculver@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":831677,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210517,"text":"70210517 - 2019 - Connections between Eocene Lakes Uinta and Gosiute with emphasis on the infilling stage of Lake Uinta in Piceance Basin","interactions":[],"lastModifiedDate":"2020-06-08T19:55:17.412524","indexId":"70210517","displayToPublicDate":"2019-05-08T14:50:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2789,"text":"Mountain Geologist","active":true,"publicationSubtype":{"id":10}},"title":"Connections between Eocene Lakes Uinta and Gosiute with emphasis on the infilling stage of Lake Uinta in Piceance Basin","docAbstract":"Late in its history, Eocene saline Lake Gosiute in the Greater Green River Basin, Wyoming and Colorado was progressively filled from north to south with coarse volcaniclastic sediments. During the infilling, Lake Gosiute began to drain southward across the Axial arch into saline Lake Uinta in the Piceance and Uinta Basins, Colorado and Utah (about 49 Ma) causing Lake Gosiute to freshen. Once Lake Gosiute was filled entirely (about 48 Ma), volcaniclastic sediments spilled over into Lake Uinta. The first coarse volcanic sediments entered the north part of Lake Uinta near the present-day mouth of Yellow Creek 15 miles south of the Axial arch during deposition of the Mahogany oil shale zone. There is evidence that a south-flowing river entered Lake Uinta from the Axial arch starting early in the history of the Lake and prior to substantial outflow from Lake Gosiute began. A petrographic study of sandstones from this period is consistent with an Axial arch source. It is likely that the outflow channel occupied this pre-existing drainage. Determining when outflow from Lake Gosiute began to move through this pre-existing channel is difficult as mainly mud-sized sediments would have entered Lake Uinta from Lake Gosiute prior to infilling. In addition, reliable dates for most of the strata deposited in Lake Uinta are lacking.\nA partial section of Lake Uinta strata is preserved at Deep Channel Creek about 10 mi south of the Axial arch. Here the R-6 oil shale zone, below the Mahogany zone, has graded into fluvial strata–the only place in the basin where this zone is not lacustrine. In addition, the underlying L-5 zone is atypically sandy. We propose that Lake Gosiute began to drain into Lake Uinta starting at about the beginning of deposition of the L-5 oil shale zone increasing the input of sediments into the northern part of Lake Uinta. Mud-sized sediments could have come from Lake Gosiute, but the coarser sediments likely came from the Axial arch.\nVolcaniclastic sediments produced a rapidly prograding deltaic complex that ultimately filled in much if not all of the eastern part of Lake Uinta. The first volcanic sediments to reach the deep depocenter were mainly fine-grained turbidites but ultimately the depocenter was largely filled by slumps off the over-steepened delta front. A petrographic study of the volcaniclastic sandstones indicates that the Absaroka volcanic field in northwest Wyoming is the likely source of the volcanic fraction.","language":"English","publisher":"Rocky Mountain Association of Geologists","doi":"10.31582/rmag.mg.56.2.x","usgsCitation":"Johnson, R.C., Birdwell, J.E., Brownfield, M.E., Mercier, T.J., and Hansley, P.L., 2019, Connections between Eocene Lakes Uinta and Gosiute with emphasis on the infilling stage of Lake Uinta in Piceance Basin: Mountain Geologist, v. 56, no. 2, p. 143-183, https://doi.org/10.31582/rmag.mg.56.2.x.","productDescription":"41 p.","startPage":"143","endPage":"183","ipdsId":"IP-104194","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":375425,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Unite States","state":"Colorado, Utah","otherGeospatial":"Uinta Basin, Piceance Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.95068359374999,\n 38.58252615935333\n ],\n [\n -106.435546875,\n 38.54816542304656\n ],\n [\n -106.435546875,\n 40.96330795307353\n ],\n [\n -111.90673828125,\n 40.79717741518766\n ],\n [\n -111.95068359374999,\n 38.58252615935333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-05-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Ronald C. 0000-0002-6197-5165 rcjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-6197-5165","contributorId":1550,"corporation":false,"usgs":true,"family":"Johnson","given":"Ronald","email":"rcjohnson@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":790492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":790493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":790494,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mercier, Tracey J. 0000-0002-8232-525X tmercier@usgs.gov","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":2847,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey","email":"tmercier@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":790495,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansley, Paula L.","contributorId":225137,"corporation":false,"usgs":false,"family":"Hansley","given":"Paula","email":"","middleInitial":"L.","affiliations":[{"id":41044,"text":"Petrographic Consultants International, Inc","active":true,"usgs":false}],"preferred":false,"id":790496,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203359,"text":"70203359 - 2019 - Geology of the Cornwall Quadrangle, Virginia ","interactions":[],"lastModifiedDate":"2020-03-31T13:14:11","indexId":"70203359","displayToPublicDate":"2019-05-07T13:34:55","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"184","title":"Geology of the Cornwall Quadrangle, Virginia ","docAbstract":"No abstract available.
","language":"English","publisher":"DMME","usgsCitation":"Heller, M.J., Carter, M.W., Wilkes, G., and Coiner, R., 2019, Geology of the Cornwall Quadrangle, Virginia , iv, 17 p.","productDescription":"iv, 17 p.","numberOfPages":"23","ipdsId":"IP-091026","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":363568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":363567,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://dmme.virginia.gov/commercedocs/PUB_184.pdf"}],"country":"United States","state":"Virginia","county":"Amherst County, Rockbridge County","otherGeospatial":"Cornwell Quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.375,\n 37.75\n ],\n [\n -79.25,\n 37.75\n ],\n [\n -79.25,\n 37.875\n ],\n [\n -79.375,\n 37.875\n ],\n [\n -79.375,\n 37.75\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Heller, Matthew J.","contributorId":205633,"corporation":false,"usgs":false,"family":"Heller","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":33611,"text":"Virginia Division of Geology and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":762296,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, Mark W. 0000-0003-0460-7638 mcarter@usgs.gov","orcid":"https://orcid.org/0000-0003-0460-7638","contributorId":4808,"corporation":false,"usgs":true,"family":"Carter","given":"Mark","email":"mcarter@usgs.gov","middleInitial":"W.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":762297,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilkes, G.P.","contributorId":69163,"corporation":false,"usgs":true,"family":"Wilkes","given":"G.P.","email":"","affiliations":[],"preferred":false,"id":762298,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coiner, R.L.","contributorId":64212,"corporation":false,"usgs":true,"family":"Coiner","given":"R.L.","email":"","affiliations":[],"preferred":false,"id":762299,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203379,"text":"70203379 - 2019 - Resurgence of cisco (Coregonus artedi) population levels in Lake Michigan","interactions":[],"lastModifiedDate":"2019-08-15T12:06:16","indexId":"70203379","displayToPublicDate":"2019-05-07T13:28:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Resurgence of cisco (Coregonus artedi) population levels in Lake Michigan","docAbstract":"In recent decades, many factors that were linked with the decline of Great Lakes cisco (Coregonus artedi) populations have subsided. The goal of this study was to investigate where cisco exist in Lake Michigan and evaluate evidence for recovery including when, where, and to what extent it is occurring. We evaluated datasets from several independent monitoring efforts that did and did not target cisco. We also evaluated trends in commercial and recreational catches of cisco. Across these datasets, there was strong evidence of a sustained recovery of cisco stocks that began in Lake Michigan in the mid-2000s. Fall gill net surveys and commercial fisheries provided reasonable indications of a population recovery in the northeast by 2011. Further south, Ludington Pump Storage barrier net monitoring also recorded increasing numbers of cisco starting in 2011. Recreational harvest estimates were valuable in evaluating spatial distributions but were less valuable as an early signal of abundance shifts. Measures of the recreational harvest of cisco most notably increased in 2014. The highest catch rates and harvest occurred in Grand Traverse Bay and northern Lake Michigan as evidenced by recreational, commercial, and fall netting surveys. Observations of cisco are expanding and have increased in intensity along the eastern shore of Lake Michigan south to Muskegon in both fishery dependent and independent surveys. The similarity in trends from all data sources indicate that cisco abundance has increased, and their range within the basin continues to expand.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2019.04.004","usgsCitation":"Claramunt, R.M., Smith, J., Donner, K., Povolo, A., Herbert, M.E., Galarowicz, T., Claramunt, T.L., DeBoe, S., Stott, W., and Jonas, J.L., 2019, Resurgence of cisco (Coregonus artedi) population levels in Lake Michigan: Journal of Great Lakes Research, v. 45, no. 4, p. 821-829, https://doi.org/10.1016/j.jglr.2019.04.004.","productDescription":"9 p.","startPage":"821","endPage":"829","ipdsId":"IP-102582","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":363647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Lake Michigan, Grand Traverse Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.462158203125,\n 42.755079545072135\n ],\n [\n -84.5068359375,\n 42.755079545072135\n ],\n [\n -84.5068359375,\n 46.24824991289166\n ],\n [\n -87.462158203125,\n 46.24824991289166\n ],\n [\n -87.462158203125,\n 42.755079545072135\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Claramunt, Randall M.","contributorId":190497,"corporation":false,"usgs":false,"family":"Claramunt","given":"Randall","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":762397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Jason","contributorId":215444,"corporation":false,"usgs":false,"family":"Smith","given":"Jason","affiliations":[{"id":39249,"text":"Little Traverse Band of Odawa Indians","active":true,"usgs":false}],"preferred":false,"id":762398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donner, Kevin","contributorId":190499,"corporation":false,"usgs":false,"family":"Donner","given":"Kevin","affiliations":[{"id":33110,"text":"Little Traverse Bay Bands of Odawa Indians","active":true,"usgs":false}],"preferred":false,"id":762399,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Povolo, Annalise","contributorId":215445,"corporation":false,"usgs":false,"family":"Povolo","given":"Annalise","email":"","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":762400,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herbert, Matthew E.","contributorId":189192,"corporation":false,"usgs":false,"family":"Herbert","given":"Matthew","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":762401,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Galarowicz, Tracy","contributorId":215446,"corporation":false,"usgs":false,"family":"Galarowicz","given":"Tracy","email":"","affiliations":[{"id":13588,"text":"Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":762402,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Claramunt, Tracy L.","contributorId":215447,"corporation":false,"usgs":false,"family":"Claramunt","given":"Tracy","email":"","middleInitial":"L.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":762403,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"DeBoe, Scott","contributorId":215448,"corporation":false,"usgs":false,"family":"DeBoe","given":"Scott","email":"","affiliations":[{"id":39250,"text":"Consumers Energy","active":true,"usgs":false}],"preferred":false,"id":762404,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stott, Wendylee 0000-0002-5252-4901 wstott@usgs.gov","orcid":"https://orcid.org/0000-0002-5252-4901","contributorId":191249,"corporation":false,"usgs":true,"family":"Stott","given":"Wendylee","email":"wstott@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":762396,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jonas, Jory L.","contributorId":215449,"corporation":false,"usgs":false,"family":"Jonas","given":"Jory","email":"","middleInitial":"L.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":762405,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70203340,"text":"70203340 - 2019 - Resilience of benthic macroinvertebrates to extreme floods in a Catskill Mountain river, New York, USA: Implications for water quality monitoring and assessment","interactions":[],"lastModifiedDate":"2023-03-28T15:01:01.548244","indexId":"70203340","displayToPublicDate":"2019-05-07T09:32:26","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Resilience of benthic macroinvertebrates to extreme floods in a Catskill Mountain river, New York, USA: Implications for water quality monitoring and assessment","docAbstract":"Changes in the timing, magnitude, frequency, and duration of extreme hydrologic events are becoming apparent and could disrupt species assemblages and stream ecosystems across the Northeastern United States. Between August 28 and 29 of 2011, an average of 31 cm of rain from Tropical Storm Irene fell across Eastern New York State in less than 24 h and caused historic flooding in numerous streams of the Catskill Mountain Region. Peak discharges exceeded the 0.01 annual exceedance probability (> 100 year flood) in many Catskill Mountain streams. Approximately one week later, the remnants of Tropical Storm Lee deposited another 19 cm of rain onto saturated soils and caused additional flooding. Data from annual benthic macroinvertebrate surveys completed at 5 sites in the Upper Esopus Creek, a premier trout stream in the region, during August 2009–2011 (before the floods) were compared to data collected from the same sites in September 2011, November 2011, March 2012 and August 2012 (after the floods). The impact, rate of recovery and the factors which might affect the resilience of benthic macroinvertebrate communities were evaluated. The results of biological water quality assessment metrics immediately after the floods resembled those of highly polluted waters, yet severe floods were the only disturbance. Prior to the floods, standard biological assessment metrics showed that communities were not impacted and water quality was pristine. A large decrease in macroinvertebrate density was evident in the September 2011 surveys following the floods and bioassessment metrics reflected highly degraded water quality conditions. Most community metrics rebounded in 3–7 months (November 2011 and March 2012), and full recovery was evident in 12 months (August 2012) which suggests that macroinvertebrate assemblages are relatively resilient to the effects of extreme floods in these low-order streams. Therefore, macroinvertebrate samples collected from a flood-impacted stream before full recovery occurs might reflect loss of diversity and abundance from the flood disturbance and incorrectly attribute the impact to impaired water quality. The strong short-term impacts and the relatively rapid recovery of macroinvertebrate communities following catastrophic floods have important ramifications for routine bioassessment programs considering changing hydrologic regimes in streams across the Northeast and elsewhere.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2019.04.057","usgsCitation":"Smith, A.J., Baldigo, B.P., Duffy, B.T., George, S.D., and Dresser, B., 2019, Resilience of benthic macroinvertebrates to extreme floods in a Catskill Mountain river, New York, USA: Implications for water quality monitoring and assessment: Ecological Indicators, v. 104, p. 107-115, https://doi.org/10.1016/j.ecolind.2019.04.057.","productDescription":"9 p.","startPage":"107","endPage":"115","ipdsId":"IP-088586","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":363550,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Upper Esopus Creek watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.8774721023475,\n 42.15605300055455\n ],\n [\n -74.8774721023475,\n 41.85645574280821\n ],\n [\n -74.24721282626231,\n 41.85645574280821\n ],\n [\n -74.24721282626231,\n 42.15605300055455\n ],\n [\n -74.8774721023475,\n 42.15605300055455\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"104","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Alexander J.","contributorId":168509,"corporation":false,"usgs":false,"family":"Smith","given":"Alexander","email":"","middleInitial":"J.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":762212,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":762211,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duffy, Brian T","contributorId":215384,"corporation":false,"usgs":false,"family":"Duffy","given":"Brian","email":"","middleInitial":"T","affiliations":[{"id":39232,"text":"Research Scientist, NY State Dept of Environmental Conservation, Albany NY","active":true,"usgs":false}],"preferred":false,"id":762213,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":762214,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dresser, Brian","contributorId":215385,"corporation":false,"usgs":false,"family":"Dresser","given":"Brian","email":"","affiliations":[{"id":39233,"text":"Retired, NY State Dept of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":762215,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203214,"text":"ofr20191047 - 2019 - Groundwater quality in the Sacramento Metropolitan shallow aquifer, California","interactions":[],"lastModifiedDate":"2019-05-07T08:45:05","indexId":"ofr20191047","displayToPublicDate":"2019-05-02T13:50:12","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1047","displayTitle":"Groundwater quality in the Sacramento Metropolitan Shallow Aquifer, California","title":"Groundwater quality in the Sacramento Metropolitan shallow aquifer, California","docAbstract":"The Sacramento metropolitan (SacMetro) study unit covers approximately 3,250 square kilometers of the Central Valley along the eastern edge of the northern and southern ends of the San Joaquin and Sacramento Valleys, respectively. Groundwater withdrawals supply a significant portion of the water-resource needs of the region. In the southern portion of the study unit, groundwater accounts for nearly 90 percent of water demand in the area (South Area Water Council, 2011).
Groundwater sampled in the SacMetro study unit comes from alluvial aquifers primarily composed of sediments derived from the Sierra Nevada Mountains to the east. Recharge to the groundwater system is primarily from the streams draining the Sierra Nevada, and from precipitation and infiltration of applied irrigation water (California Department of Water Resources, 2003). The public-supply aquifer system assessments of this area in 2005 found elevated concentrations of inorganic constituents including arsenic, iron, and manganese as well as of solvents in some wells (Bennett and others, 2010; 2011).
This study was designed to provide a statistically representative assessment of the quality of groundwater resources used for domestic drinking water in the SacMetro study unit. A complete listing of what was measured, including the sampling results, are presented in Bennett and others, 2019. A total of 49 wells were sampled between July 2017 and November 2017 (Bennett and others, 2019). The wells in the study were 32–160 meters deep, and water levels were 1–62 meters below land surface.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191047","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Bennett, G.L. 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California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819