Hydrous pyrolysis was applied to four low-maturity aliquots from the Utica, Excello, Monterey, and Niobrara Shale Formations in North America to create artificial maturation sequences, which could be used to study the impact of maturation on geochemical and microstructural properties. Modified Rock-Eval pyrolysis, reflectance, organic petrology, and Fourier transform infrared spectroscopy (FTIR) were employed to analyze their geochemical properties, while gas adsorption (CO2 and N2) was used to characterize their pore structures (pores < 200 nm). Organic petrography using white and blue light (fluorescence) before and after hydrous pyrolysis showed that amorphous organic matter cracked into solid bitumen, oil, and gas during hydrous pyrolysis. A reduction of the CH2/CH3 ratio in hydrous pyrolysis residues was observed from FTIR analysis. Rock-Eval pyrolysis showed that kerogens in the four samples were dissimilar, and hydrous pyrolysis residues showed smaller hydrogen index and Sh2 values than starting materials. Results from CO2 and N2 gas adsorption analysis showed that pore structures (micropore volume, micropore surface area, meso-macropore volume, and meso-macropore surface area) changed significantly during hydrous pyrolysis. However, changes in pore structure were dissimilar among the four samples, which was attributed to different activation energies of organic matter. A thermodynamic fractal model showed a decrease in fractal dimensions of Utica, Monterey, and Excello after hydrous pyrolysis, indicating a decrease in surface roughness. The pore size heterogeneity in the Utica sample increased as hydrous pyrolysis temperature increased, whereas the pore size heterogeneity distributions in the Monterey and Excello decreased based on the N2 adsorption data.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.energyfuels.9b02389","usgsCitation":"Liu, K., Ostadhassan, M., Hackley, P.C., Gentzis, T., Zou, J., Yuan, Y., Carvajal-Ortiz, H., Rezaee, R., and Bubach, B., 2019, Experimental study on the impact of thermal maturity on shale microstructures using hydrous pyrolysis: Energy & Fuels, v. 33, no. 10, p. 9702-9719, https://doi.org/10.1021/acs.energyfuels.9b02389.","productDescription":"18 p.","startPage":"9702","endPage":"9719","ipdsId":"IP-103911","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":379391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"10","noUsgsAuthors":false,"publicationDate":"2019-09-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Kouqi","contributorId":243145,"corporation":false,"usgs":false,"family":"Liu","given":"Kouqi","email":"","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":801610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ostadhassan, M.","contributorId":243146,"corporation":false,"usgs":false,"family":"Ostadhassan","given":"M.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":801611,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":801612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gentzis, T.","contributorId":243147,"corporation":false,"usgs":false,"family":"Gentzis","given":"T.","affiliations":[{"id":39779,"text":"Core Laboratories","active":true,"usgs":false}],"preferred":false,"id":801613,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zou, J.","contributorId":243148,"corporation":false,"usgs":false,"family":"Zou","given":"J.","affiliations":[{"id":48648,"text":"Department of Petroleum Engineering, Curtin University","active":true,"usgs":false}],"preferred":false,"id":801614,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yuan, Y.","contributorId":243149,"corporation":false,"usgs":false,"family":"Yuan","given":"Y.","affiliations":[{"id":48648,"text":"Department of Petroleum Engineering, Curtin University","active":true,"usgs":false}],"preferred":false,"id":801615,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carvajal-Ortiz, H.","contributorId":243150,"corporation":false,"usgs":false,"family":"Carvajal-Ortiz","given":"H.","affiliations":[{"id":39779,"text":"Core Laboratories","active":true,"usgs":false}],"preferred":false,"id":801616,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rezaee, R.","contributorId":243151,"corporation":false,"usgs":false,"family":"Rezaee","given":"R.","email":"","affiliations":[{"id":48648,"text":"Department of Petroleum Engineering, Curtin University","active":true,"usgs":false}],"preferred":false,"id":801617,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bubach, B.","contributorId":243152,"corporation":false,"usgs":false,"family":"Bubach","given":"B.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":801618,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70205500,"text":"sim3438 - 2019 - Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in Miami-Dade County, Florida, 2018","interactions":[],"lastModifiedDate":"2019-09-26T08:02:35","indexId":"sim3438","displayToPublicDate":"2019-09-25T14:58:55","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3438","displayTitle":"Map of the Approximate Inland Extent of Saltwater at the Base of the Biscayne Aquifer in Miami-Dade County, Florida, 2018","title":"Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in Miami-Dade County, Florida, 2018","docAbstract":"The inland extent of saltwater at the base of the Biscayne aquifer in eastern Miami-Dade County, Florida, was mapped in 2011, and it was mapped in the Model Land Area in 2016. The saltwater interface has continued to move inland in some areas and is now near several active well fields. An updated approximation of the inland extent of saltwater has been created by using data collected during March 8–December 13, 2018, from 111 monitoring wells open to the Biscayne aquifer near its base. Chloride concentrations in water samples from the monitoring wells and bulk conductivity from geophysical logs and measurements of the specific conductance of groundwater were used to approximate the position of the isochlor representing a chloride concentration of 1,000 milligrams per liter (mg/L) at the base of the Biscayne aquifer.
An average rate of saltwater interface movement of about 102 meters per year in the Model Land Area along SW 360 Street was estimated from the approximated dates of arrival of the 250-, 500-, and 1,000-mg/L isochlors at wells TPGW-7L (2013–2014) and ACI-MW-05-FS (2017–2018). This estimate assumes that the interface is traveling in a path parallel to an imaginary line connecting the two monitoring wells.
Of the 111 wells from which data were used, 80 wells have open intervals of ≤ 4 meters, 20 of the wells have open intervals that range from 4.3 to 39.6 meters, and the lengths of the open intervals could not be determined in 11 wells. Studies have shown that long open intervals might allow water from various depths to mix under ambient or pumped conditions, which in turn could alter the maximum chloride concentration sampled in the well, or it might change the depth at which the maximum specific conductance is measured within a well, relative to its depth in the aquifer. The approximation of the inland extent of the saltwater interface and the estimated rate of movement of the interface are dependent on the quality of existing data. Improved estimates could be obtained by installing uniformly designed monitoring wells in systematic transects extending landward of the advancing saltwater interface. To achieve this goal, Miami-Dade County and some other organizations are routinely adding new monitoring wells with short open intervals and replacing poorly designed or positioned monitoring wells to improve spatial coverage of the network.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3438","collaboration":"Prepared in cooperation with Miami-Dade County","usgsCitation":"Prinos, S.T., 2019, Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in Miami-Dade County, Florida, 2018: U.S. Geological Survey Scientific Investigations Map 3438, 10-p. pamphlet, 1 sheet, https://doi.org/10.3133/sim3438.","productDescription":"Pamphlet: vii, 10 p.; 1 Plate: 35.8 x 46.0 inches; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-107371","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":367675,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3438/sim3438.pdf","text":"Sheet","size":"898 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3438"},{"id":367674,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3438/coverthb3.jpg"},{"id":367676,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3438/sim3438_pamphlet.pdf","text":"Pamphlet","size":"857 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3438 Pamphlet"},{"id":367677,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZIC1O4","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data Pertaining to Mapping the Approximate Inland Extent of Saltwater at the Base of the Biscayne Aquifer in Miami-Dade County, Florida, 2018"}],"country":"United States","state":"Florida","county":"Miami-Dade County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.8538818359375,\n 25.095548539604252\n ],\n [\n -79.9969482421875,\n 25.095548539604252\n ],\n [\n -79.9969482421875,\n 26.892679095908164\n ],\n [\n -80.8538818359375,\n 26.892679095908164\n ],\n [\n -80.8538818359375,\n 25.095548539604252\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Although streamflow is widely recognized as a controlling factor in stream health, empirical relations between indicators of anthropogenic modification of streamflow and ecological indicators have been elusive. The objective of this report is to build upon specific findings reported in recent publications by providing a library of empirical models that describe the relations between streamflow modification and indicators of biological integrity. Biological monitoring data from 812 streams and rivers across the United States were matched with sites where daily streamflow was also monitored by the U.S. Geological Survey. Of these sites, 118 were sampled by the U.S. Geological Survey along gradients of streamflow modification within 3 regional focus studies. The integrity of invertebrate and fish communities was expressed as a binary variable, “impaired” or “unimpaired,” signifying whether or not the composition and structure of the biological community was statistically reduced relative to regional reference sites. Streamflow modification at each gaged site was quantified with 509 streamflow statistics scaled to express the ratio of observed streamflow conditions to site-specific expected conditions in the absence of human influences on watershed hydrology. For each region, generalized additive modeling was used to examine relations between each indicator of streamflow modification and indicators of biological integrity (response variable). In every region examined, statistically defensible and ecologically realistic relations were found between indicators of streamflow modification and indicators of biological integrity. These findings can aid practitioners and managers seeking to (1) propose empirically based hypotheses about the specific components of streamflow regimes that are critical to aquatic communities, which can subsequently be explored in detail in a region or river basin of interest; and (2) predict biological responses to anthropogenic modification of specific components of the streamflow regime.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191088","usgsCitation":"Carlisle, D.M., Grantham, T.E., Eng, K., Wolock, D.M., 2019, Regional-scale associations between indicators of biological integrity and indicators of streamflow modification: U.S. Geological Survey Open-File Report 2019–1088, 10 p., https://doi.org/10.3133/ofr20191088.\n","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-097828","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":367467,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O2ZV0M","linkHelpText":"Regional-scale Model Predictions of the Relation Between Biological Integrity and Streamflow Modification"},{"id":367452,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1088/ofr20191088.pdf","text":"Report","size":"12.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1088"},{"id":367451,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1088/coverthb.jpg"}],"contact":"Director, USGS Kansas Water Science Center
1217 Biltmore Drive
Lawrence, KS 66049
785-842-9909
Organisms that move across ecosystem boundaries connect food webs in apparently disparate locations. As part of their life cycle, aquatic insects transition from aquatic larvae to terrestrial adults, thereby linking freshwater ecosystem processes and terrestrial insectivore dynamics. These linkages are strongly affected by contamination of freshwater ecosystems, which can reduce production of adult aquatic insects (i.e., emergence), increase contaminant concentrations in adult insect tissues, and alter contaminant flux to terrestrial ecosystems. Despite the potential impact of contaminants on adult aquatic insects, little is known about predicting these effects. Here, I develop a heuristic model based on contaminant properties and ecotoxicological principles to predict the effects of various classes of aquatic contaminants on adult aquatic insects and discuss implications for terrestrial insectivores living near contaminated freshwaters. The main finding is that contaminant classes vary greatly in how their biologically-mediated effects on aquatic insects affect terrestrial insectivores. Highly bioaccumulative contaminants that are well retained during metamorphosis, like polychlorinated biphenyls (PCBs), are often non-toxic to aquatic insect larvae at concentrations commonly found in the environment. Such contaminants flux from aquatic ecosystems in large quantities in the bodies of emerging adult aquatic insects and expose terrestrial insectivores to toxic levels of pollution. On the other hand, contaminants that are less bioaccumulative, excreted during metamorphosis, and more toxic to insects, like trace metals, tend to affect terrestrial insectivores by reducing production of adult aquatic insects on which they prey. Management applications of this model illustrate type and severity of risk of aquatic contaminants to consumers of adult aquatic insects.
","language":"English","publisher":"University of Chicago Press Journals","doi":"10.1086/705997","usgsCitation":"Kraus, J.M., 2019, Contaminants in linked aquatic–terrestrial ecosystems: Predicting effects of aquatic pollution on adult aquatic insects and terrestrial insectivores: Freshwater Science, v. 38, no. 4, p. 919-927, https://doi.org/10.1086/705997.","productDescription":"9 p.","startPage":"919","endPage":"927","ipdsId":"IP-101646","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":367780,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kraus, Johanna M. 0000-0002-9513-4129 jkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-9513-4129","contributorId":4834,"corporation":false,"usgs":true,"family":"Kraus","given":"Johanna","email":"jkraus@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":771698,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70205561,"text":"70205561 - 2019 - Growth drivers of Bakken oil well productivity","interactions":[],"lastModifiedDate":"2020-05-05T16:31:34.428529","indexId":"70205561","displayToPublicDate":"2019-09-23T10:26:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2832,"text":"Natural Resources Research","onlineIssn":"1573-8981","printIssn":"1520-7439","active":true,"publicationSubtype":{"id":10}},"title":"Growth drivers of Bakken oil well productivity","docAbstract":"This paper identifies the drivers of the phenomenal growth in productivity in hydraulically fractured horizontal oil wells producing from the middle member of the Bakken Formation in North Dakota. The data show a strong underlying spatial component and somewhat weaker temporal component. Drivers of the spatial component are favorable reservoir conditions. The temporal component of well productivity growth is driven by increasing the number of fracture treatments and by increasing the volume of proppant and injection fluids used on a per fracture treatment basis. Random Forest, a non-parametric modeling procedure often applied in the context of machine learning, is used to identify the relative importance of geologic and well-completion factors that have driven the growth in Bakken well productivity. The findings of this study suggest that a significant part of the well productivity increases during the period from 2010 to 2015 have been the result of improved well-site selection. For the more recent period, that is from 2015 through 2017, part of the improved well productivity has resulted from substantial increases in the proppant and injection fluids used per stage and per well.","language":"English","publisher":"Springer","doi":"10.1007/s11053-019-09559-5","usgsCitation":"Attanasi, E., and Freeman, P., 2019, Growth drivers of Bakken oil well productivity: Natural Resources Research, v. 29, p. 1471-1486, https://doi.org/10.1007/s11053-019-09559-5.","productDescription":"16 p.","startPage":"1471","endPage":"1486","ipdsId":"IP-103552","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":459755,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11053-019-09559-5","text":"Publisher Index Page"},{"id":367691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota, South Dakota","otherGeospatial":"Bakken Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.20654296875,\n 48.98742700601184\n ],\n [\n -109.127197265625,\n 49.009050809382046\n ],\n [\n -109.083251953125,\n 48.05605376398125\n ],\n [\n -108.1494140625,\n 47.87214396888731\n ],\n [\n -103.304443359375,\n 44.84029065139799\n ],\n [\n -101.66748046874999,\n 44.84808025602074\n ],\n [\n -100.184326171875,\n 45.236217535866025\n ],\n [\n -99.283447265625,\n 46.66451741754235\n ],\n [\n -99.107666015625,\n 47.61356975397398\n ],\n [\n -99.20654296875,\n 48.98742700601184\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Attanasi, Emil D. 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":198728,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil D.","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":771653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Philip A. 0000-0002-0863-7431","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":206294,"corporation":false,"usgs":true,"family":"Freeman","given":"Philip A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":771654,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70217821,"text":"70217821 - 2019 - Where’s the rock: Using convolutional neural networks to improve land cover classification","interactions":[],"lastModifiedDate":"2021-02-04T13:29:44.832983","indexId":"70217821","displayToPublicDate":"2019-09-21T08:29:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Where’s the rock: Using convolutional neural networks to improve land cover classification","docAbstract":"While machine learning techniques have been increasingly applied to land cover classification problems, these techniques have not focused on separating exposed bare rock from soil covered areas. Therefore, we built a convolutional neural network (CNN) to differentiate exposed bare rock (rock) from soil cover (other). We made a training dataset by mapping exposed rock at eight test sites across the Sierra Nevada Mountains (California, USA) using USDA’s 0.6 m National Aerial Inventory Program (NAIP) orthoimagery. These areas were then used to train and test the CNN. The resulting machine learning approach classifies bare rock in NAIP orthoimagery with a 0.95
We diagnosed leptospirosis in six northern sea otters (Enhydra lutris kenyoni) that stranded on beaches in Washington, US in 2002. Significant gross findings included cyanotic oral mucous membranes, renal swelling, congestion or pale streaks on the cut surface of the lobules, hematuria, dehydration, lymphadenopathy, pulmonary congestion and rarely adrenal hemorrhage and congestion. Histopathology showed lymphoplasmacytic tubulointerstitial nephritis with intraluminal spirochetes and immunoreactivity to leptospiral antigens in the renal tubules and interstitium. qPCR using kidney or urine for the leptospiral lipL32 gene was positive with cycle threshold values indicative of abundant or moderate amounts of nucleic acid. A microscopic agglutination test showed the highest serum antibody titer to serovar Pomona and titers to serovars Autumnalis, Bratislava, Hebdomadis, Grippo, Ictero, Pyrogenes, Ballum, Canicola, and Hardjo. While antibodies to Leptospira interrogans have been previously detected in sea otters, there are no reports of disease or descriptions of pathology.
","language":"English","publisher":"Wildlife Disease Association ","doi":"10.7589/2019-05-112","usgsCitation":"Knowles, S., Lynch, D., and Thomas, N.J., 2019, Leptospirosis in Northern Sea Otters (Enhydra lutris kenyoni) from Washington: Journal of Wildlife Diseases, v. 56, no. 2, p. 466-471, https://doi.org/10.7589/2019-05-112.","productDescription":"6 p.","startPage":"466","endPage":"471","ipdsId":"IP-106498","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":373166,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Priorities for the Nation—The U.S. Geological Survey Next Generation Water Observing System","title":"Water priorities for the nation—The U.S. Geological Survey next generation water observing system","docAbstract":"The challenges of providing safe and sustainable water supplies for human and ecological uses and protecting lives and property during water emergencies are well recognized. The U.S. Geological Survey (USGS) plays an essential role in meeting these challenges through its observational networks and renowned water science and research activities (National Academies of Science, Engineering, and Medicine, 2018). Substantial advances in water science, together with emerging breakthroughs in technical and computational capabilities, have led the USGS to develop a Next Generation Water Observing System (NGWOS). The NGWOS will provide real-time data on water quantity and quality in more affordable and rapid ways than previously possible, and in more locations. The data will be served through a modernized USGS National Water Information System that will be coupled to advanced modeling tools to inform daily water operations, decision-making during water emergencies (like floods, droughts, and contaminant spills), assessments of past trends in water quantity and quality, and forecasts of future water availability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193046","usgsCitation":"Eberts, S.M., Wagner, C.R., and Woodside, M.D., 2019, Water priorities for the Nation—The U.S. Geological Survey Next Generation Water Observing System: U.S. Geological Survey Fact Sheet 2019–3046, 2 p., https://doi.org/10.3133/fs20193046.","productDescription":"2 p.","onlineOnly":"Y","ipdsId":"IP-109916","costCenters":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"links":[{"id":366749,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3046/coverthb.jpg"},{"id":367487,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3046/fs20193046.pdf","text":"Report","size":"2.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2019-3046"}],"contact":"U.S. Geological Survey
Water Resources Mission Area
Groundwater and Streamflow Information Program
3916 Sunset Ridge Road
Raleigh, North Carolina 26707
In engineering seismology, the time‐averaged shear‐wave velocity (VS) of the upper 30 m of the crust (VS30) is the primary parameter used in ground‐motion models to predict seismic site effects. VS30 is typically derived from in situ recordings of VS, although proxy‐based approaches (using geologic and/or geomorphometric classifications) are provisionally adopted when measurement‐based VS30 are sparse or not readily available. Despite the acceptance of proxy approaches, there are limited studies that examine the empirical relationships between VS30 and topographic attributes measured from various length scales and different resolutions of the digital elevation model. In this study, we examine the relationships between compiled VS30 measurements from 218 sites in southern California and topographic metrics of slope and relief measured over various length scales. We find that the correlations between topographic metrics and VS30 are weak but statistically significant. The correlations are improved when topographic slopes and relief are measured over length scales longer than typical hillslopes and VS30 sites are separated by different geologic groups. This is likely because VS30, especially on the rock sites, is better reflected in topographic metrics that capture large‐scale topographic relief, as well as landscape positions such as hilltops and valley bottoms.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120190076","usgsCitation":"Lin, J., Moon, S., Yong, A., Meng, L., and Davies, P., 2019, Length-scale-dependent relationships between VS30 and topographic slopes in southern California: Bulletin of the Seismological Society of America, v. 109, no. 6, p. 2614-2625, https://doi.org/10.1785/0120190076.","productDescription":"12 p.","startPage":"2614","endPage":"2625","ipdsId":"IP-104595","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119,\n 34.8\n ],\n [\n -119,\n 33.875\n ],\n [\n -116.25,\n 33.875\n ],\n [\n -116.25,\n 34.8\n ],\n [\n -119,\n 34.8\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"109","issue":"6","noUsgsAuthors":false,"publicationDate":"2019-09-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Lin, Jessica","contributorId":351141,"corporation":false,"usgs":false,"family":"Lin","given":"Jessica","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":927974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moon, Seulgi 0000-0001-5207-1781","orcid":"https://orcid.org/0000-0001-5207-1781","contributorId":264625,"corporation":false,"usgs":false,"family":"Moon","given":"Seulgi","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":927975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yong, Alan 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":204730,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meng, Lingseng","contributorId":351143,"corporation":false,"usgs":false,"family":"Meng","given":"Lingseng","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":927977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davies, Paul","contributorId":351144,"corporation":false,"usgs":false,"family":"Davies","given":"Paul","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":927978,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70205389,"text":"70205389 - 2019 - Sediment and organic carbon transport and deposition driven by internal tides along Monterey Canyon, offshore California","interactions":[],"lastModifiedDate":"2019-11-13T13:40:12","indexId":"70205389","displayToPublicDate":"2019-09-17T08:43:48","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1370,"text":"Deep-Sea Research Part I: Oceanographic Research Papers","active":true,"publicationSubtype":{"id":10}},"title":"Sediment and organic carbon transport and deposition driven by internal tides along Monterey Canyon, offshore California","docAbstract":"Submarine canyons provide globally important conduits for sediment and organic carbon transport into the deep-sea. Using a novel dataset from Monterey Canyon, offshore central California, that includes an extensive array of water column sampling devices, we address how fine-grained sediment and organic carbon are transported, mixed, fractionated, and buried along a submarine canyon. Anderson-type sediment traps were deployed 10 to 300 meters above the seafloor on moorings anchored between 278–1849 m water depths along the axial channel of Monterey Canyon during three consecutive 6-month deployments (2015–2017). Tidal currents within the canyon suspended and transported fine-grained sediment and organic carbon that were captured in sediment traps, which show apparent patterns and composition of sediment and organic carbon transport along the canyon. High sediment accumulation rates in traps increased up-canyon and near the seafloor with fine-scale (<1 cm) layering that was increasingly distinctive in CT scans. There was no along-canyon trend in the organic carbon composition (percent modern carbon and isotopic signatures) among trap locations, suggesting mixing. Organic carbon content (weight percent total organic carbon) and excess 210Pb activities (dpm/g) increased down-canyon, reflecting reduced flux of sediment and organic carbon into traps. Differing organic carbon signatures in traps compared with previous measurements of seabed deposits along Monterey Canyon suggest that canyon deposits may not reflect organic carbon available to organisms and transported through the canyon with internal tides. Organic carbon burial efficiency estimates from comparing core and trap samples are low (~26% or much less), suggesting that the modern upper Monterey Canyon may not be an effective sink for carbon in biogeochemical and CO2 cycling. Organic carbon isotopic signatures appear more marine in traps that sample from the water column than in cores that sample seafloor deposits, likely owing to the influence of sediment density flow events on deposits and preferential consumption of relatively fresh marine organic carbon on the seafloor that was largely prevented in preserved traps. Along-canyon sediment and organic carbon transport by internal tides likely occurs in many modern global submarine canyons, but canyon deposits and remaining organic carbon appear to preferentially reflect episodic sediment density flow events unrelated to internal tides. This study provides a quantified example and conceptual schematic for internal-tide-related sediment and organic carbon transport, mixing, and burial trends along a submarine canyon that are likely to have common global aspects.","language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr.2019.103108","usgsCitation":"Maier, K.L., Rosenberger, K.J., Paull, C.K., Gwiazda, R., Gales, J., Lorenson, T., Barry, J., Talling, P.J., McGann, M., Xu, J., Lundsten, E.M., Anderson, K., Litvin, S., Parsons, D., Clare, M., Simmons, S., Sumner, E., and Cartigny, M.J., 2019, Sediment and organic carbon transport and deposition driven by internal tides along Monterey Canyon, offshore California: Deep-Sea Research Part I: Oceanographic Research Papers, v. 153, 103108, https://doi.org/10.1016/j.dsr.2019.103108.","productDescription":"103108","ipdsId":"IP-103300","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459788,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.1016/j.dsr.2019.103108>).","text":"Publisher Index Page"},{"id":367448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Monterey Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.30804443359375,\n 36.50301312197295\n ],\n [\n -121.73950195312499,\n 36.50301312197295\n ],\n [\n -121.73950195312499,\n 37.070519031125826\n ],\n [\n -122.30804443359375,\n 37.070519031125826\n ],\n [\n -122.30804443359375,\n 36.50301312197295\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"153","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maier, Katherine L. 0000-0003-2908-3340","orcid":"https://orcid.org/0000-0003-2908-3340","contributorId":206421,"corporation":false,"usgs":false,"family":"Maier","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":37324,"text":"Monterey Bay Aquarium Research Institute","active":true,"usgs":false}],"preferred":false,"id":771004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology 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Jenny","contributorId":216506,"corporation":false,"usgs":false,"family":"Gales","given":"Jenny","email":"","affiliations":[{"id":39461,"text":"University of Plymouth, UK","active":true,"usgs":false}],"preferred":false,"id":771007,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lorenson, Thomas 0000-0001-7669-2873 tlorenson@usgs.gov","orcid":"https://orcid.org/0000-0001-7669-2873","contributorId":174599,"corporation":false,"usgs":true,"family":"Lorenson","given":"Thomas","email":"tlorenson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":771008,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barry, James P.","contributorId":140935,"corporation":false,"usgs":false,"family":"Barry","given":"James P.","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":771009,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Talling, Peter J.","contributorId":195515,"corporation":false,"usgs":false,"family":"Talling","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":771010,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McGann, Mary 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":169540,"corporation":false,"usgs":true,"family":"McGann","given":"Mary","email":"mmcgann@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":771011,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Xu, Jingping","contributorId":195514,"corporation":false,"usgs":false,"family":"Xu","given":"Jingping","affiliations":[],"preferred":false,"id":771012,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lundsten, Eve M.","contributorId":147191,"corporation":false,"usgs":false,"family":"Lundsten","given":"Eve","email":"","middleInitial":"M.","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":771013,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Anderson, Krystle","contributorId":147192,"corporation":false,"usgs":false,"family":"Anderson","given":"Krystle","email":"","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":771014,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Litvin, Steven","contributorId":219014,"corporation":false,"usgs":false,"family":"Litvin","given":"Steven","email":"","affiliations":[{"id":37324,"text":"Monterey Bay Aquarium Research Institute","active":true,"usgs":false}],"preferred":false,"id":771015,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Parsons, Daniel","contributorId":216508,"corporation":false,"usgs":false,"family":"Parsons","given":"Daniel","affiliations":[{"id":39462,"text":"University of Hull, UK","active":true,"usgs":false}],"preferred":false,"id":771016,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Clare, Michael","contributorId":213585,"corporation":false,"usgs":false,"family":"Clare","given":"Michael","email":"","affiliations":[{"id":38805,"text":"National Oceanography Centre, University of Southampton Waterfront Campus, European Way, Southampton, SO14 3ZH, United 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J.B.","contributorId":195513,"corporation":false,"usgs":false,"family":"Cartigny","given":"Matthieu","email":"","middleInitial":"J.B.","affiliations":[],"preferred":false,"id":771020,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70205435,"text":"70205435 - 2019 - Reporting the limits of detection and quantification for environmental DNA assays","interactions":[],"lastModifiedDate":"2020-08-04T13:44:26.547842","indexId":"70205435","displayToPublicDate":"2019-09-16T17:33:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5840,"text":"Environmental DNA","active":true,"publicationSubtype":{"id":10}},"title":"Reporting the limits of detection and quantification for environmental DNA assays","docAbstract":"Environmental DNA (eDNA) analysis is increasingly being used to detect the presence and relative abundance of rare species, especially invasive or imperiled aquatic species. The rapid progress in the eDNA field has resulted in numerous studies impacting conservation and management actions. However, standardization of eDNA methods and reporting across the field is yet to be fully established, with one area being the calculation and interpretation of assay limit of detection (LOD) and limit of quantification (LOQ).
Here, we propose establishing consistent methods for determining and reporting of LOD and LOQ for single‐species quantitative PCR (qPCR) eDNA studies.
We utilize datasets from multiple cooperating laboratories to demonstrate both a discrete threshold approach and a curve‐fitting modeling approach for determining LODs and LOQs for eDNA qPCR assays. We also provide details of an R script developed and applied for the modeling method.
Ultimately, standardization of how LOD and LOQ are determined, interpreted, and reported for eDNA assays will allow for more informed interpretation of assay results, more meaningful interlaboratory comparisons of experiments, and enhanced capacity for assessing the relative technical quality and performance of different eDNA qPCR assays.
The System-Wide Assessment and Monitoring Program (SWAMP) has been envisioned as a long-term monitoring program to ensure a comprehensive network of coastal data collection activities is in place to support the development, implementation, and adaptive management of the coastal protection and restoration program within coastal Louisiana. The Coastwide Reference Monitoring System (CRMS) and Barrier Island Comprehensive Monitoring (BICM) programs have been implemented under SWAMP, while other aspects of system dynamics, including offshore and inland water-body boundary conditions, nontidal freshwater habitats, riverine conditions, risk status, and protection performance, are not presently the subject of CPRA-coordinated (Coastal Protection and Restoration Authority) monitoring. In order to implement these additional aspects of SWAMP, CPRA partnered with The Water Institute of the Gulf and others to develop 1) a programmatic monitoring plan for evaluating the effectiveness of the coastal protection and restoration program on a coastwide scale, and 2) basinwide monitoring plans that will incorporate the elements of the programmatic plan with specific data collection activities designed to capture effects within the basin. Monitoring plans were developed for Barataria Basin, Pontchartrain Region (includes Breton Sound, Pontchartrain and Mississippi River Delta Basins), and the western basins (Calcasieu-Sabine, Mermentau, Teche-Vermilion, Atchafalaya, and Terrebonne) for both the natural and human systems using a process to identify the monitoring variables, objectives, and sampling design. The monitoring variables and objectives identified fall under the general categories of weather and climate, biotic integrity, water quality, hydrology, physical terrain, population and demographics, housing and community characteristics, economy and employment, ecosystem dependency, residential properties protection, and critical infrastructure and essential services protection. A rigorous statistical analysis, examination of modeling needs, and thorough reviews of previous planning and monitoring efforts were conducted to develop the sampling designs for the natural and human system monitoring plans. The plan relies heavily on the use of existing data, thus, coordination with other agencies (e.g., LDEQ , LDWF) and CPRA’s existing monitoring programs (e.g., BICM, CRMS) is critical to the plan’s success. Implementation of the plans will require development of quality control and quality assurance protocols, specific standardized operating procedures for each of the data collection efforts, a data management plan, and a reporting framework to contribute to decision making and reducing uncertainty in management actions.
","language":"English","publisher":"Water Institute of the Gulf","usgsCitation":"Hemmerling, S., Baustian, M., Bienn, H., Dausman, A., Grace, A., Grimley, L., McInnis, A., Vingiello, M., Vu, H., Sable, S., Gentile, B., Lafargue, P., Hijuelos, A., Piazza, S., Stagg, C., Raynie, R., Haywood, E., and Khalid, S., 2019, Monitoring plans for Louisiana’s system-wide assessment and monitoring program (SWAMP). 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Huy","contributorId":221280,"corporation":false,"usgs":false,"family":"Vu","given":"Huy","email":"","affiliations":[],"preferred":false,"id":777622,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sable, Shaye","contributorId":147275,"corporation":false,"usgs":false,"family":"Sable","given":"Shaye","affiliations":[{"id":16816,"text":"Dynamic Solutions, Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":777623,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gentile, Britt","contributorId":221281,"corporation":false,"usgs":false,"family":"Gentile","given":"Britt","email":"","affiliations":[],"preferred":false,"id":777624,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lafargue, Phillip","contributorId":221282,"corporation":false,"usgs":false,"family":"Lafargue","given":"Phillip","email":"","affiliations":[],"preferred":false,"id":777625,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hijuelos, Ann 0000-0003-0922-6754","orcid":"https://orcid.org/0000-0003-0922-6754","contributorId":201525,"corporation":false,"usgs":true,"family":"Hijuelos","given":"Ann","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":777626,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Piazza, Sarai 0000-0001-6962-9008 piazzas@usgs.gov","orcid":"https://orcid.org/0000-0001-6962-9008","contributorId":169024,"corporation":false,"usgs":true,"family":"Piazza","given":"Sarai","email":"piazzas@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":777627,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Stagg, Camille 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":206064,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":777628,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Raynie, Richard C","contributorId":140898,"corporation":false,"usgs":false,"family":"Raynie","given":"Richard C","affiliations":[{"id":13608,"text":"Louisiana Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":777629,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Haywood, Edward","contributorId":194452,"corporation":false,"usgs":false,"family":"Haywood","given":"Edward","email":"","affiliations":[],"preferred":false,"id":777630,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Khalid, Syed","contributorId":221283,"corporation":false,"usgs":false,"family":"Khalid","given":"Syed","email":"","affiliations":[],"preferred":false,"id":777631,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70207203,"text":"70207203 - 2019 - Assessing beach and island habitat loss in the Chesapeake Bay and Delmarva coastal bay region, USA, through processing of Landsat TM and OLI imagery: A case study","interactions":[],"lastModifiedDate":"2019-12-13T06:21:24","indexId":"70207203","displayToPublicDate":"2019-09-16T09:52:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5098,"text":"Remote Sensing Applications: Society and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Assessing beach and island habitat loss in the Chesapeake Bay and Delmarva coastal bay region, USA, through processing of Landsat TM and OLI imagery: A case study","docAbstract":"Beaches and islands provide economic value to humans and critical habitat for breeding and foraging wildlife. These ecosystems, however, are being severely impacted by global climate change and sea level rise through increased erosion and frequency of inundation. The case study presented here aimed to document island loss in the Chesapeake Bay and Delmarva coastal bay region of the United States using image processing techniques within a GIS from 1986 to 2016. Satellite imagery from Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) sensors were processed within ArcMap 10.5 to determine spatial and temporal trends in island and beach habitat. Calculation of unweighted Cohen’s Kappa showed that classified scenes were, on average, within the range of moderate agreement between the classified Landsat scenes and the validation imagery within Google Earth (0.539). Recommendations regarding existing beach habitat management and future supplementation were created based on these results. From 1986 to 2016, island area declined by over 1,200 hectares (ha) with agriculture/open field (all open vegetated spaces) declining by nearly 82% and beach, surprisingly, increasing nearly 2%. This study was the first to document Chesapeake Bay region-wide island loss beyond the mid-2000s. The accuracy of this study was limited slightly by the 30 m spatial resolution of the imagery used. This technique may be best suited for documenting trends on large islands and along the mainland coastline.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rsase.2019.100265","usgsCitation":"Marban, P., Mullinax, J.M., Resop, J.P., and Prosser, D.J., 2019, Assessing beach and island habitat loss in the Chesapeake Bay and Delmarva coastal bay region, USA, through processing of Landsat TM and OLI imagery: A case study: Remote Sensing Applications: Society and Environment, v. 16, 100265, 10 p., https://doi.org/10.1016/j.rsase.2019.100265.","productDescription":"100265, 10 p.","ipdsId":"IP-106458","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":370203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay, Delmarva Coastal Bays","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.0638427734375,\n 39.65222681530652\n ],\n [\n -76.6790771484375,\n 39.2832938689385\n ],\n [\n -77.14599609375,\n 38.272688535980976\n ],\n [\n -76.607666015625,\n 36.83127162140714\n ],\n [\n -75.9814453125,\n 36.787291466820015\n ],\n [\n -74.8553466796875,\n 38.40194908237822\n ],\n [\n -75.0640869140625,\n 38.84826438869913\n ],\n [\n -76.0638427734375,\n 39.65222681530652\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Marban, Paul R.","contributorId":221168,"corporation":false,"usgs":false,"family":"Marban","given":"Paul R.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":777269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mullinax, Jennifer M.","contributorId":221170,"corporation":false,"usgs":false,"family":"Mullinax","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":777270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Resop, Jonathan P.","contributorId":221169,"corporation":false,"usgs":false,"family":"Resop","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":777271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prosser, Diann J. 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":221167,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":777268,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207519,"text":"70207519 - 2019 - The first 3D conductivity model of the contiguous US: Reflections on geologic structure and application to induction hazards","interactions":[],"lastModifiedDate":"2019-12-23T07:54:17","indexId":"70207519","displayToPublicDate":"2019-09-16T07:47:49","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"8","title":"The first 3D conductivity model of the contiguous US: Reflections on geologic structure and application to induction hazards","docAbstract":"Estimation of ground level geoelectric fields has been identified by the National Space Weather Action Plan as a key component of assessment and mitigation of space weather impacts on critical infrastructure. Estimates of spatially and temporally variable electric fields are used to generate statistically based hazard maps and show promise toward monitoring and responding to geomagnetic disturbances in near real‐time. One approach to geoelectric field estimation is to employ three‐dimensional (3D) Earth conductivity models. These data‐constrained conductivity models are the results of regional magnetotelluric inversions based primarily on NSF’s Earthscope USArray impedances, which to date cover ~60% of the contiguous United States. Here, we present the first‐ever composite conductivity model of the contiguous United States and describe its compilation from 3D regional conductivity models, a global mantle conductivity model, offshore bathymetry, and sediment thickness data. We discuss structures within the conductivity model and how they relate to the complex geologic tapestry of the continent. Finally, we discuss the utility of this synthesis model for estimation and mitigation of geomagnetically induced currents.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geomagnetically induced currents from the Sun to the power grid","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/9781119434412.ch8","usgsCitation":"Kelbert, A., Bedrosian, P.A., and Murphy, B., 2019, The first 3D conductivity model of the contiguous US: Reflections on geologic structure and application to induction hazards, chap. 8 of Geomagnetically induced currents from the Sun to the power grid, p. 127-151, https://doi.org/10.1002/9781119434412.ch8.","productDescription":"25 p.","startPage":"127","endPage":"151","ipdsId":"IP-100625","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":370629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.47656249999999,\n 32.24997445586331\n ],\n [\n -95.2734375,\n 23.885837699862005\n ],\n [\n -85.78125,\n 29.84064389983441\n ],\n [\n -79.8046875,\n 23.563987128451217\n ],\n [\n -79.8046875,\n 29.22889003019423\n ],\n [\n -74.8828125,\n 34.016241889667015\n ],\n [\n -66.09375,\n 42.293564192170095\n ],\n [\n -67.8515625,\n 47.27922900257082\n ],\n [\n -81.9140625,\n 42.293564192170095\n ],\n [\n -83.671875,\n 46.800059446787316\n ],\n [\n -93.1640625,\n 48.922499263758255\n ],\n [\n -122.6953125,\n 50.064191736659104\n ],\n [\n -125.5078125,\n 48.922499263758255\n ],\n [\n -126.5625,\n 40.17887331434696\n ],\n [\n -118.47656249999999,\n 32.24997445586331\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Kelbert, Anna 0000-0003-4395-398X akelbert@usgs.gov","orcid":"https://orcid.org/0000-0003-4395-398X","contributorId":184053,"corporation":false,"usgs":true,"family":"Kelbert","given":"Anna","email":"akelbert@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":778347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Benjamin S. 0000-0001-7636-3711","orcid":"https://orcid.org/0000-0001-7636-3711","contributorId":221483,"corporation":false,"usgs":false,"family":"Murphy","given":"Benjamin S.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":778348,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208839,"text":"70208839 - 2019 - Moving at the speed of flight: Dabbling duck-movement rates and the relationship with electronic tracking interval","interactions":[],"lastModifiedDate":"2020-03-03T07:37:16","indexId":"70208839","displayToPublicDate":"2019-09-16T07:33:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"Moving at the speed of flight: Dabbling duck-movement rates and the relationship with electronic tracking interval","docAbstract":"Context. Effective wildlife management requires information on habitat and resource needs, which can be estimated with movement information and modelling energetics. One necessary component of avian models is flight speeds at multiple temporal scales. Technology has limited the ability to accurately assess flight speeds, leading to estimates of questionable accuracy, many of which have not been updated in almost a century.\n\nAims. We aimed to update flight speeds of ducks, and differentiate between migratory and non-migratory flight speeds, a detail that was unclear in previous estimates. We also analysed the difference in speeds of migratory and non-migratory flights, and quantified how data collected at different temporal intervals affected estimates of flight speed.\n\nMethods. We tracked six California dabbling duck species with high spatio-temporal resolution GPS–GSM transmitters, calculated speeds of different flight types, and modelled how estimates varied by flight and data interval (30 min to 6 h).\n\nKey results. Median migratory speeds were faster (but non-significant) for the larger mallard (Anas platyrhynchos; 82.5 km h–1), northern pintail (Anas acuta; 79.0 km h–1) and gadwall (Mareca strepera; 70.6 km h–1), than the smaller-bodied northern shoveler (Spatula clypeata; 65.7 km h–1), cinnamon teal (Spatula cyanoptera; 63.5 km h–1) and American wigeon (Mareca Americana; 52 km h–1). Migratory flights were faster than non-migratory flights for all species and speeds were consistently slower with an increasing data interval.\n\nImplications. The need to balance time and energy requirements may drive different speeds for migratory and non-migratory flights. Lower speeds at longer intervals are likely to be due to a greater proportion of ‘loafing’ time included in flighted segments, demonstrating that data acquired at different intervals provide a means to evaluate and estimate behaviours that influence speed estimation. Shorter-interval data should be the most accurate, but longer-interval data may be easier to collect over lengthier timeframes, so it may be expedient to trade-off a degree of accuracy in broad-scale studies for the larger dataset. Our updated flight speeds for dabbling duck species can be used to parameterise and validate energetics models, guide management decisions regarding optimal habitat distribution, and, ultimately, improve conservation management of wetlands for waterfowl.","language":"English","publisher":"CSIRO","doi":"10.1071/WR19028","usgsCitation":"McDuie, F., Casazza, M.L., Keiter, D.A., Overton, C.T., Herzog, M.P., Feldheim, C.L., and Ackerman, J., 2019, Moving at the speed of flight: Dabbling duck-movement rates and the relationship with electronic tracking interval: Wildlife Research, v. 46, no. 6, p. 533-543, https://doi.org/10.1071/WR19028.","productDescription":"11 p.","startPage":"533","endPage":"543","ipdsId":"IP-102666","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":459806,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wr19028","text":"Publisher Index Page"},{"id":372828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"6","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McDuie, Fiona 0000-0002-1948-5613","orcid":"https://orcid.org/0000-0002-1948-5613","contributorId":222936,"corporation":false,"usgs":true,"family":"McDuie","given":"Fiona","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":783585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":783584,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keiter, David A.","contributorId":176521,"corporation":false,"usgs":false,"family":"Keiter","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":783586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":783587,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":783588,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Feldheim, Cliff L.","contributorId":206561,"corporation":false,"usgs":false,"family":"Feldheim","given":"Cliff","email":"","middleInitial":"L.","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":783589,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":783590,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70205335,"text":"70205335 - 2019 - Characterizing large earthquakes before rupture is complete","interactions":[],"lastModifiedDate":"2019-09-17T07:50:15","indexId":"70205335","displayToPublicDate":"2019-09-16T00:24:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing large earthquakes before rupture is complete","docAbstract":"Whether large and very large earthquakes are distinguishable from each other early on in the rupture process has been a subject often debated over the past several decades. Studies have shown that the frequency content of radiated seismic energy in the first few seconds of an earthquake scales with the final magnitude of the event, implying determinism. Other studies have shown that the recordings of ground displacement from small-to-moderate sized earthquakes are indistinguishable, and thus earthquakes share a universal early rupture process. Regardless of how earthquakes start, however, at some point in the rupture process events of different sizes must be distinguishable from one another. If that difference occurs early - i.e., before the rupture duration of the smaller event - this implies that earthquakes demonstrate some level of determinism. Here we show through analysis of a large database of source time functions and near-source displacement records that after an initiation phase, ruptures of M7-9 earthquakes organize into a slip pulse, the kinematic properties of which scale with magnitude. As such, early in the rupture process - after about 10s - large and very large earthquakes demonstrate different properties and can thus be distinguished.","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.aav2032","usgsCitation":"Melgar, D., and Hayes, G.P., 2019, Characterizing large earthquakes before rupture is complete: Science Advances, v. 5, no. 5, eaav2032, https://doi.org/10.1126/sciadv.aav2032.","productDescription":"eaav2032","onlineOnly":"Y","ipdsId":"IP-105666","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":459808,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.aav2032","text":"Publisher Index Page"},{"id":367424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Melgar, Diego","contributorId":193030,"corporation":false,"usgs":false,"family":"Melgar","given":"Diego","email":"","affiliations":[],"preferred":false,"id":770877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Gavin P. 0000-0003-3323-0112 ghayes@usgs.gov","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":147556,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin","email":"ghayes@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":770878,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70205336,"text":"70205336 - 2019 - Global earthquake response with imaging geodesy: recent examples from the USGS NEIC","interactions":[],"lastModifiedDate":"2019-09-16T09:14:10","indexId":"70205336","displayToPublicDate":"2019-09-15T23:12:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Global earthquake response with imaging geodesy: recent examples from the USGS NEIC","docAbstract":"The U.S. Geological Survey National Earthquake Information Center leads real-time efforts to provide rapid and accurate assessments of the impacts of global earthquakes, including estimates of ground shaking, ground failure, and the resulting human impacts. These efforts primarily rely on analysis of the seismic wavefield to characterize the source of the earthquake, which in turn informs a suite of disaster response products such as ShakeMap and PAGER. In recent years, the proliferation of rapidly acquired and openly available in-situ and remotely sensed geodetic observations has opened new avenues for responding to earthquakes around the world in the days following significant events. Geodetic observations, particularly from interferometric synthetic aperture radar (InSAR) and satellite optical imagery, provide a means to robustly constrain the dimensions and spatial complexity of earthquakes beyond what is typically possible with seismic observations alone. Here, we document recent cases where geodetic observations contributed important information to earthquake response efforts – from informing and validating seismically-derived source models to independently constraining earthquake impact products – and the conditions under which geodetic observations improve earthquake response products. We use examples from the 2013 Mw7.7 Baluchistan, Pakistan, 2014 Mw6.0 Napa, California, 2015 Mw7.8 Gorkha, Nepal, and 2018 Mw7.5 Palu, Indonesia earthquakes to highlight the varying ways geodetic observations have contributed to earthquake response efforts at the NEIC. We additionally provide a synopsis of the workflows implemented for geodetic earthquake response. As remote sensing geodetic observations become increasingly available and the frequency of satellite acquisitions continues to increase, operational earthquake geodetic imaging stands to make critical contributions to natural disaster response efforts around the world.","language":"English","publisher":"MDPI","doi":"10.3390/rs11111357","usgsCitation":"Barnhart, W.D., Hayes, G.P., and Wald, D.J., 2019, Global earthquake response with imaging geodesy: recent examples from the USGS NEIC: Remote Sensing, v. 11, no. 11, 1357, 20 p., https://doi.org/10.3390/rs11111357.","productDescription":"1357, 20 p.","onlineOnly":"Y","ipdsId":"IP-108767","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":459810,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11111357","text":"Publisher Index Page"},{"id":367423,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnhart, William D. wbarnhart@usgs.gov","contributorId":5299,"corporation":false,"usgs":true,"family":"Barnhart","given":"William","email":"wbarnhart@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":770879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Gavin P. 0000-0003-3323-0112 ghayes@usgs.gov","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":147556,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin","email":"ghayes@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":770880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":770881,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205360,"text":"70205360 - 2019 - Characterization and evaluation of controls on post-fire streamflow response across western U.S. watersheds","interactions":[],"lastModifiedDate":"2019-09-16T09:14:57","indexId":"70205360","displayToPublicDate":"2019-09-15T23:03:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Characterization and evaluation of controls on post-fire streamflow response across western U.S. watersheds","docAbstract":"This research investigates the impact of wildfires on watershed flow regimes, specifically focusing on evaluation of fire events within specified hydroclimatic regions in the western United States, and evaluating the impact of climate and geophysical variables on response. Eighty-two watersheds were identified with at least 10 years of continuous pre-fire daily streamflow records and 5 years of continuous post-fire daily flow records. Percent change in annual runoff ratio, low flows, high flows, peak flows, number of zero flow days, baseflow index, and Richards–Baker flashiness index were calculated for each watershed using pre- and post-fire periods. Independent variables were identified for each watershed and fire event, including topographic, vegetation, climate, burn severity, percent area burned, and soils data. \n\nResults show that low flows, high flows, and peak flows increase in the first 2 years following a wildfire and decrease over time. Relative response was used to scale response variables with the respective percent area of watershed burned in order to compare regional differences in watershed response. To account for variability in precipitation events, runoff ratio was used to compare runoff directly to PRISM precipitation estimates. To account for regional differences in climate patterns, watersheds were divided into nine regions, or clusters, through k-means clustering using climate data, and regression models were produced for watersheds grouped by total area burned. Watersheds in Cluster 9 (eastern California, western Nevada, Oregon) demonstrate a small negative response to observed flow regimes after fire. Cluster 8 watersheds (coastal California) display the greatest flow responses, typically within the first year following wildfire. Most other watersheds show a positive mean relative response. In addition, simple regression models show low correlation between percent watershed burned and streamflow response, implying that other watershed factors strongly influence response. \n\nSpearman correlation identified NDVI, aridity index, percent of a watershed's precipitation that falls as rain, and slope as being positively correlated with post-fire streamflow response. This metric also suggested a negative correlation between response and the soil erodibility factor, watershed area, and percent low burn severity. Regression models identified only moderate burn severity and watershed area as being consistently positively/negatively correlated, respectively, with response. The random forest model identified only slope and percent area burned as significant watershed parameters controlling response. \n\nResults will help inform post-fire runoff management decisions by helping to identify expected changes to flow regimes, as well as facilitate parameterization for model application in burned watersheds.","language":"English","publisher":"Copernicus Publications","doi":"10.5194/hess-22-1221-2018","usgsCitation":"Saxe, S., Hogue, T.S., and Hay, L., 2019, Characterization and evaluation of controls on post-fire streamflow response across western U.S. watersheds: Hydrology and Earth System Sciences, v. 22, no. 2, p. 1221-1237, https://doi.org/10.5194/hess-22-1221-2018.","productDescription":"17 p.","startPage":"1221","endPage":"1237","numberOfPages":"17","ipdsId":"IP-090164","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":459812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-22-1221-2018","text":"Publisher Index Page"},{"id":367422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"22","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Saxe, Samuel 0000-0003-1151-8908","orcid":"https://orcid.org/0000-0003-1151-8908","contributorId":215753,"corporation":false,"usgs":true,"family":"Saxe","given":"Samuel","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":770931,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hogue, Terri S.","contributorId":205175,"corporation":false,"usgs":false,"family":"Hogue","given":"Terri","email":"","middleInitial":"S.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":770932,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren E. 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":211478,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":770930,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205904,"text":"70205904 - 2019 - A process-based model of pre-eruption seismicity patterns and its use for eruption forecasting at dormant stratovolcanoes","interactions":[],"lastModifiedDate":"2019-10-28T14:27:48","indexId":"70205904","displayToPublicDate":"2019-09-15T12:48:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"A process-based model of pre-eruption seismicity patterns and its use for eruption forecasting at dormant stratovolcanoes","docAbstract":"Using long-term data sets, the eruptive size, timing and style can typically be successfully forecast for dormant volcanoes using current monitoring data and knowledge of precursory eruptive patterns. The USAID-USGS Volcano Disaster Assistance Program (VDAP) utilizes seismic data over multiple eruption cycles and across volcano types to successfully forecast eruption size, style and onset times, as well as changes within ongoing eruptions. From millions of seismic event observations, we show that seismic data, a proxy for rate-dependent strain changes in the magmatic system, combined with a process-based conceptual geologic model enables eruption forecasting, especially for stratovolcanoes dormant >20 years. We show that this model often works for some open systems, ones that sufficiently reseal to plug the conduit, and also where a deep intrusion occurs after phreatic or phreatomagmatic explosions have begun. This model is divided into four seismicity and geologic stages. We describe each of the four stages of seismicity in detail and how they relate to the ongoing geologic process of that stage: Stage 1. Deep intrusion and seismicity occurring at 10 to 40 + km depth below the volcanic edifice; Stage 2. Distal VT seismicity induced at distances from 2 to >30 km laterally from the summit by magma intruding into and inflating the upper-crustal magma storage region; Stage 3. Vent-clearing seismicity associated with the initial vent creation and clearing phase of eruptive activity. Stage 4. Repetitive event seismicity associated with the final ascent of magma from 2 km to the surface. We present 36 examples of this seismic progression from 26 volcanoes. We believe that this progression generally correlates with the magma flux and the eventual explosivity and is invaluable for forecasting eruptions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2019.03.004","usgsCitation":"White, R.A., and McCausland, W.A., 2019, A process-based model of pre-eruption seismicity patterns and its use for eruption forecasting at dormant stratovolcanoes: Journal of Volcanology and Geothermal Research, v. 382, p. 267-297, https://doi.org/10.1016/j.jvolgeores.2019.03.004.","productDescription":"31 p.","startPage":"267","endPage":"297","ipdsId":"IP-082435","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":459815,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2019.03.004","text":"Publisher Index Page"},{"id":368169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"382","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"White, Randall A. 0000-0003-4074-8577 rwhite@usgs.gov","orcid":"https://orcid.org/0000-0003-4074-8577","contributorId":1993,"corporation":false,"usgs":true,"family":"White","given":"Randall","email":"rwhite@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":772819,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCausland, Wendy A. 0000-0002-8683-1440","orcid":"https://orcid.org/0000-0002-8683-1440","contributorId":204380,"corporation":false,"usgs":true,"family":"McCausland","given":"Wendy","email":"","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":772820,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70205521,"text":"70205521 - 2019 - Relations of dissolved-oxygen variability, selected field constituents, and metabolism estimates to land use and nutrients in high-gradient Boston Mountain streams, Arkansas","interactions":[],"lastModifiedDate":"2020-09-02T12:43:52.51217","indexId":"70205521","displayToPublicDate":"2019-09-14T12:26:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Relations of dissolved-oxygen variability, selected field constituents, and metabolism estimates to land use and nutrients in high-gradient Boston Mountain streams, Arkansas","docAbstract":"Continuous monitoring data can be extremely useful for assessing water quality conditions particularly for variables that exhibit dynamic diel swings such as dissolved oxygen. As a means of evaluating dissolved oxygen criteria used by the Arkansas Department of Environmental Quality (ADEQ) for assessing this stream class, we compared continuous dissolved oxygen (DO) data collected at five small- to moderate-sized (watersheds 10-100 mi2), high-gradient streams in the Boston Mountains distributed across a land-use and nutrient condition gradient. The current DO criteria employed by ADEQ for Boston Mountains streams >10 mi2 consists of both an exceedance rate and a magnitude, in which, streams may be considered 'impaired' if greater than 10% of DO measurements during a period of record are < 6 mg/L. The 10% exceedance rate, however, is a commonly used “default” value that requires independent testing for different ecoregion stream classifications. Our findings for the five Boston Mountain streams fit a general pattern established for other aquatic systems (e.g. larger streams, low-gradient streams, and lakes) where increasing land-use intensity generally results in increased nutrient concentrations, which can lead to stream eutrophication and increased DO variability. DO concentrations were < 6 mg/L for fewer than 4% of measurements at the two sites identified “a priori” as least disturbed by nutrient and land-use indices, while concentrations at the three sites identified as moderately and most disturbed were < 6 mg/L for 20 to 33% of measurements. These findings demonstrate that the 10% exceedance rate currently employed by ADEQ was effective at identifying various degrees of DO impairment in Boston Mountain streams. Our analysis also demonstrated that continuous pH and specific conductance data and estimates of stream metabolism were helpful for associating DO variability to anthropogenic or natural origins. Considerations that were useful for examining these relationships and evaluating ADEQ’s DO criteria should be applicable to DO studies in other locations where stream and geologic characteristics are like those of the Boston Mountains.
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\"}}]}","volume":"10","issue":"191","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Justus, Billy 0000-0002-3458-9656 bjustus@usgs.gov","orcid":"https://orcid.org/0000-0002-3458-9656","contributorId":202148,"corporation":false,"usgs":true,"family":"Justus","given":"Billy","email":"bjustus@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":771493,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driver, Lucas 0000-0003-2549-1849","orcid":"https://orcid.org/0000-0003-2549-1849","contributorId":219176,"corporation":false,"usgs":true,"family":"Driver","given":"Lucas","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":771495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Green, J.J.","contributorId":219175,"corporation":false,"usgs":false,"family":"Green","given":"J.J.","email":"","affiliations":[{"id":39966,"text":"Arkansas Dept Env. Quality","active":true,"usgs":false}],"preferred":false,"id":771494,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wentz, Nathan","contributorId":219177,"corporation":false,"usgs":false,"family":"Wentz","given":"Nathan","email":"","affiliations":[{"id":39967,"text":"Arkansas Dept of Env. Quality","active":true,"usgs":false}],"preferred":false,"id":771496,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70205385,"text":"70205385 - 2019 - Physically based estimation of rainfall thresholds triggering shallow landslides in volcanic slopes of southern Italy","interactions":[],"lastModifiedDate":"2019-09-17T08:50:30","indexId":"70205385","displayToPublicDate":"2019-09-14T08:49:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Physically based estimation of rainfall thresholds triggering shallow landslides in volcanic slopes of southern Italy","docAbstract":"On the 4th and 5th of March 2005, about 100 rainfall-induced landslides occurred along volcanic slopes of Camaldoli Hill in Naples, Italy. These started as soil slips in the upper substratum of incoherent and welded volcaniclastic deposits, then evolved downslope according to debris avalanche and debris flow mechanisms. This specific case of slope instability on complex volcaniclastic deposits remains poorly characterized and understood, although similar shallow landsliding phenomena have largely been studied in other peri-volcanic areas of the Campania region underlain by carbonate bedrock. Considering the landslide hazard in this urbanized area, this study focused on quantitatively advancing the understanding of the predisposing factors and hydrological conditions contributing to the initial landslide triggering. Borehole drilling, trial pits, dynamic penetrometer tests, topographic surveys, and infiltration tests were conducted on a slope sector of Camaldoli Hill to develop a geological framework model. Undisturbed soil samples were collected for laboratory testing to further characterize hydraulic and geotechnical properties of the soil units identified. In situ soil pressure head monitoring probes were also installed. A numerical model of two-dimensional variably saturated subsurface water flow was parameterized for the monitored hillslope using field and laboratory data. Based on the observed soil pressure head dynamics, the model was calibrated by adjusting the evapotranspiration parameters. This physically based hydrologic model was combined with an infinite-slope stability analysis to reconstruct the critical unsaturated/saturated conditions leading to slope failure. This coupled hydromechanical numerical model was then used to determine intensity–duration (I-D) thresholds for landslide initiation over a range of plausible rainfall intensities and topographic slope angles for the region. The proposed approach can be conceived as a practicable method for defining a warning criterion in urbanized areas threatened by rainfall-induced shallow landslides, given the unavailability of a consistent inventory of past landslide events that prevents a rigorous empirical analysis.","language":"English","publisher":"MDPI","doi":"10.3390/w11091915","usgsCitation":"Fusco, F., De Vita, P., Mirus, B.B., Baum, R.L., Allocca, V., Tufano, R., and Calcaterra, D., 2019, Physically based estimation of rainfall thresholds triggering shallow landslides in volcanic slopes of southern Italy: Water, v. 11, no. 9, Article 1915, https://doi.org/10.3390/w11091915.","productDescription":"Article 1915","ipdsId":"IP-102857","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":459825,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w11091915","text":"Publisher Index 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PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Fusco, F. 0000-0002-6271-2228","orcid":"https://orcid.org/0000-0002-6271-2228","contributorId":219005,"corporation":false,"usgs":false,"family":"Fusco","given":"F.","email":"","affiliations":[{"id":39950,"text":"University of Napoli Federico II, Italy","active":true,"usgs":false}],"preferred":false,"id":770977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Vita, P.","contributorId":219006,"corporation":false,"usgs":false,"family":"De Vita","given":"P.","email":"","affiliations":[{"id":39950,"text":"University of Napoli Federico II, Italy","active":true,"usgs":false}],"preferred":false,"id":770978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X 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V.","contributorId":149077,"corporation":false,"usgs":false,"family":"Allocca","given":"V.","email":"","affiliations":[{"id":17631,"text":"Department of Earth, Environment and Resources Sciences, University of Naples “Federico II”, Naples, Italy.","active":true,"usgs":false}],"preferred":false,"id":770981,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tufano, R.","contributorId":219007,"corporation":false,"usgs":false,"family":"Tufano","given":"R.","email":"","affiliations":[{"id":39950,"text":"University of Napoli Federico II, Italy","active":true,"usgs":false}],"preferred":false,"id":770982,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Calcaterra, D. 0000-0002-3480-3667","orcid":"https://orcid.org/0000-0002-3480-3667","contributorId":219008,"corporation":false,"usgs":false,"family":"Calcaterra","given":"D.","email":"","affiliations":[{"id":39950,"text":"University of Napoli Federico II, Italy","active":true,"usgs":false}],"preferred":false,"id":770983,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70227523,"text":"70227523 - 2019 - Energetic status and bioelectrical impedance modeling of Arctic grayling Thymallus arcticus in interior Alaska Rivers","interactions":[],"lastModifiedDate":"2022-01-20T12:58:29.761524","indexId":"70227523","displayToPublicDate":"2019-09-14T06:53:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Energetic status and bioelectrical impedance modeling of Arctic grayling Thymallus arcticus in interior Alaska Rivers","docAbstract":"The energetic status of fishes represents energy stored as protein and lipids and reflects the ability of an individual to reproduce, migrate, and transition through life stages, ultimately influencing survival. However, traditional measurement methods, while highly accurate, are time consuming, expensive, and lethal, and nonlethal methods such as condition factor may not adequately characterize energetic status. We collected 161 Arctic grayling (Thymallus arcticus) from four interior Alaska river basins with varying hydrologic regimes during early summer and autumn seasons, and used multiple regression and model selection to evaluate the efficacy of bioelectrical impedance analysis (BIA), a nonlethal condition assessment method, to predict percent dry mass and percent lipid content estimated from proximate analysis. We found that Arctic grayling energetic status varied across seasons, by sex, and fish from sites with spawning runs of Pacific salmon had higher energy content than those from sites without salmon, potentially due to the influence of salmon-derived food subsidies. Electrical measurements explained 82% and 80% of the variability in percent dry mass and percent total lipids, respectively, and top models showed high predictive performance (observed vs. predicted root mean squared error ≤2.2%). Overall, we found the BIA approach to provide rapid, precise, and non-lethal estimates of Arctic grayling body condition. Such an approach may be useful for future work to characterize Arctic grayling bioenergetics and monitor fish condition under a rapidly changing Arctic environment.
Bivalves exhibit an astonishing diversity of sexual systems, with genetic and environmental determinants of sex, and possibly the only example of mitochondrial genes influencing sex determination pathways in animals. In contrast to all other animal species in which strict maternal inheritance (SMI) of mitochondria is the rule, bivalves possess a system known as doubly uniparental inheritance (DUI) of mitochondria in which maternal and paternal mitochondria (and their corresponding female-transmitted or F mtDNA and male-transmitted or M mtDNA genomes) are transmitted within a species. Species with DUI also possess sex-associated mtDNA-encoded proteins (in addition to the typical set of 13), which have been hypothesized to play a role in sex determination. In this study, we analyzed the sex-biased transcriptome in gonads of two closely-related freshwater mussel species with different reproductive and mitochondrial transmission modes: the gonochoric, DUI species, Utterbackia peninsularis, and the hermaphroditic, SMI species, Utterbackia imbecillis. Through comparative analysis with other DUI and non-DUI bivalve transcriptomes already available, we identify common male and female-specific genes, as well as SMI and DUI-related genes, that are probably involved in sex determination and mitochondrial inheritance in this animal group. Our results contribute to the understanding of what could be the first animal sex determination system involving the mitochondrial genome
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fgene.2019.00840","usgsCitation":"Capt, C., Renaut, S., Stewart, D., Johnson, N., and Breton, S., 2019, Putative mitochondrial sex determination in the Bivalvia: Insights from a hybrid transcriptome assembly in freshwater mussels: Frontiers in Genetics, v. 10, 840, 13 p., https://doi.org/10.3389/fgene.2019.00840.","productDescription":"840, 13 p.","ipdsId":"IP-106802","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":459830,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fgene.2019.00840","text":"Publisher Index Page"},{"id":367418,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Suwanee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.97012329101562,\n 29.569351295613394\n ],\n [\n -82.92832374572754,\n 29.569351295613394\n ],\n [\n -82.92832374572754,\n 29.606819652257347\n ],\n [\n -82.97012329101562,\n 29.606819652257347\n ],\n [\n -82.97012329101562,\n 29.569351295613394\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Capt, Charlotte","contributorId":205385,"corporation":false,"usgs":false,"family":"Capt","given":"Charlotte","email":"","affiliations":[{"id":37091,"text":"Université de Montréal","active":true,"usgs":false}],"preferred":false,"id":770832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Renaut, Sebastien","contributorId":218987,"corporation":false,"usgs":false,"family":"Renaut","given":"Sebastien","email":"","affiliations":[{"id":37091,"text":"Université de Montréal","active":true,"usgs":false}],"preferred":false,"id":770834,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Donald","contributorId":205389,"corporation":false,"usgs":false,"family":"Stewart","given":"Donald","affiliations":[{"id":37092,"text":"Acadia University","active":true,"usgs":false}],"preferred":false,"id":770835,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Nathan A. 0000-0001-5167-1988","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":218986,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":770831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Breton, Sophie 0000-0002-8286-486X","orcid":"https://orcid.org/0000-0002-8286-486X","contributorId":196560,"corporation":false,"usgs":false,"family":"Breton","given":"Sophie","email":"","affiliations":[],"preferred":false,"id":770833,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}