The New York-Pennsylvania area has a long history of hydrocarbon extraction, and the addition of shale gas extraction methods contributes to landscape disturbance borne by previously developed oil and non-shale gas resources. The main unconventional extraction method used to extract shale gas from the Marcellus Shale located in New York and Pennsylvania is hydraulic fracturing, or “fracking,” although other conventional methods are used extensively. All forms of hydrocarbon extraction disturb the surrounding landscape to some extent, primarily in the form of land clearance and degradation, road construction, and pipeline development, although the effects of these disturbances are not fully understood.
In this study, landscape-change metrics and indicators are used to analyze change in a 10-county region along the New York-Pennsylvania border—the New York counties of Allegany, Steuben, Chemung, Tioga, and Broome, and the Pennsylvania counties of McKean, Potter, Tioga, Bradford, and Susquehanna. This 10-county region was selected due to the differences in policies between the States of New York and Pennsylvania. While fracking occurred extensively in Pennsylvania over the past 10 years or more, the State of New York issued a temporary moratorium against hydraulic fracturing in 2010—citing repercussions that might affect air quality, water quality, and public health—and officially banned hydraulic fracturing in June 2015.
The quantification of landscape disturbance due to hydrocarbon extraction activities is presented in this report as land-use and land-cover (LULC) change between 2004 and 2013 and defined using specific disturbance categories (including well sites, roads, and pipelines) to compare the disturbances and changes, by county, on both sides of the New York-Pennsylvania border. The quantification was accomplished by gathering the signatures of disturbance from high-resolution aerial images, comparing the derived totals of disturbance, and then computing landscape metrics in a geographic information system (GIS) environment.
The collected data represent a summation of landscape disturbance from oil and gas development, as some of the data represented were established decades earlier. The Analytical Tools Interface for Landscape Assessments (ATtILA) software was used to calculate land-cover area and landscape metrics for each shale gas, non-shale gas, oil, and other infrastructure types associated with hydrocarbons across each county and both five-county regions in the study area. The three primary metrics used to describe changes in forest structure were (1)forest area, (2) interior forest area, and (3) forest edge area. The changes in metrics were subsequently evaluated using the Pearson correlation coefficient.
Overall, the disturbed-area footprint in the Pennsylvania region is considerably larger than the disturbed-area footprint in the New York region (13,687.9 hectares [ha] in Pennsylvania; 3,840.5 ha in New York). Disturbance per site is similar, with 1.2 disturbed ha per site in New York and 1.6 disturbed ha per site in Pennsylvania.
In the New York-Pennsylvania 10-county region, hydrocarbon-development and extraction disturbance strongly correlate with a reduction in the percentage of forest for the entire region. This observation also appears to be true in the New York five-county region for forest area. This form of disturbance in the New York five-county region shows significantly correlated changes in forest metrics (–0.4 percent total forest area), particularly in the percentage of interior forest (–1.2 percent total area) and forest edge (+0.7 percent total area). On the other hand, gas and hydrocarbon-development and extraction disturbance (1.0 percent total area) in the Pennsylvania five-county region strongly correlates with a total decline in forest area and agricultural land area (–0.8 percent combined total area) but not with either land-cover class separately.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195096","usgsCitation":"Roig-Silva, C.M., Milheim, L.E., Slonecker, E.T., Kalaly, S., and Chestnut, J., 2019, A comparison of hydrocarbon-related landscape disturbance patterns along the New York-Pennsylvania border, 2004–2013: U.S. Geological Survey Scientific Investigations Report 2019–5096, 23 p., https://doi.org/10.3133/sir20195096.","productDescription":"Report: v, 23 p.; Data Release","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091180","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":399543,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109511.htm"},{"id":380624,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2019/5096/images/"},{"id":374941,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2019/5096/sir20195096.XML"},{"id":370125,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5096/sir20195096.pdf","text":"Report","size":"3.82 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5096"},{"id":370027,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5096/coverthb.jpg"},{"id":370021,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TT4Q67","text":"USGS data release","linkHelpText":"Natural gas and oil drilling disturbance in the Marcellus Shale region of the New York-Pennsylvania border"}],"country":"United States","state":"New York, Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.9531,\n 41.4758\n ],\n [\n -75.6325,\n 41.4758\n ],\n [\n -75.6325,\n 42.5783\n ],\n [\n -78.9531,\n 42.5783\n ],\n [\n -78.9531,\n 41.4758\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
Nashville, TN Office
U.S. Geological Survey
640 Grassmere Park Drive
Nashville, TN 37211
In 2005, the U.S. Geological Survey began a cooperative study with the New York City Department of Environmental Protection to characterize the local groundwater-flow system and identify potential sources of seeps on the southern embankment of the Hillview Reservoir in southern Westchester County, New York. The earthen embankment comprises low-permeability glacial clays that were excavated from the site and rest on a veneer of low-permeability glacial deposits that overlie crystalline bedrock. At least two groundwater-flow zones—one shallow and the other deep—overlie the bedrock at the reservoir. As part of the study, slug-test data from 38 screened wells were analyzed to determine the hydraulic conductivity of the sediments in the groundwater-flow zones. Slug-test data were collected from 12 wells at the Hillview Reservoir during August 2007 and from 25 wells at the reservoir and 1 monitoring well south of the reservoir in northern Bronx County in June 2012.
Hydraulic conductivity values at the reservoir ranged from 0.0012 to 2 feet per day. On the southern embankment, hydraulic conductivity ranged from 0.0026 to 1 foot per day for wells screened in the shallow saturated zone; 0.0012 to 2 feet per day for wells screened in the deep saturated zone; and 0.021 to 0.27 foot per day for wells screened in the toe of the southern embankment, where the deep and shallow saturated zones coalesce. A hydraulic conductivity of 0.016 foot per day was determined for a well partially screened in the crystalline-bedrock aquifer, which potentially indicates an interconnection of transmissive fractures near the bedrock surface. The results of four slug-out tests are also included in this report to quality assure the hydraulic conductivity estimates from the slug-in test analysis. The results of the four slug-out tests were within 8 percent of slug-in test results, with an average of less than 2 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191102","collaboration":"Prepared in cooperation with the New York City Department of Environmental Protection","usgsCitation":"Noll, M.L., Chu, A., and Capurso, W.D., 2019, Slug-test analysis of selected wells at an earthen dam site in southern Westchester County, New York: U.S. Geological Survey Open-File Report 2019–1102, 14 p., https://doi.org/10.3133/ofr20191102.","productDescription":"Report: vi, 14 p.; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095039","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":399415,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109510.htm"},{"id":369616,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1102/coverthb.jpg"},{"id":369866,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1102/ofr20191102.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1102"},{"id":369619,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J404KW","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Data and analytical type-curve match for selected hydraulic tests in New York State"}],"country":"United States","state":"New York","county":"Westchester County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.87674808502196,\n 40.90551783054535\n ],\n [\n -73.86099815368652,\n 40.90551783054535\n ],\n [\n -73.86099815368652,\n 40.91821491609591\n ],\n [\n -73.87674808502196,\n 40.91821491609591\n ],\n [\n -73.87674808502196,\n 40.90551783054535\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
2045 Route 112, Building 4
Coram, NY 11727
Five integrator sites on streams draining mixed land-use watersheds were sampled monthly from July 2016 to June 2017. Two sites were sampled in the San Joaquin River watershed and one site was sampled in each of the Mokelumne River, Sacramento River, and Ulatis Creek watersheds.
A total of 53 out of 154 pesticides (18 herbicides, 14 insecticides, 13 fungicides, 7 breakdown products, and 1 synergist) were detected in surface-water samples and 95 percent of samples contained mixtures of 2 or more pesticides. The most frequently detected pesticides were the herbicides hexazinone, metolachlor, and diuron (present in 83 percent, 72 percent, and 67 percent of water samples, respectively), the insecticide methoxyfenozide (present in 83 percent of samples), and the fungicides boscalid and azoxystrobin (present in 67 percent and 58 percent of samples, respectively). Pesticide concentrations detected in water samples ranged from below method detection limits to 1,300 nanograms per liter (ng/L) for the insecticide chlorantraniliprole. A total of 4 pesticides (2 herbicides and 2 insecticides) were detected in suspended-sediment samples and 13 percent of suspended-sediment samples contained at least 1 pesticide. Pesticide concentrations detected in suspended-sediment samples ranged from 4.1 to 750 ng/L, both for the herbicide pendimethalin.
Six samples contained the insecticide imidacloprid at concentrations above the U.S. Environmental Protection Agency (EPA) Aquatic Life Benchmark (10 ng/L) for chronic toxicity to aquatic invertebrates. Three samples contained bifenthrin at concentrations above the EPA Aquatic Life Benchmark (1.3 ng/L) for chronic toxicity to invertebrates. One sample contained cyhalothrin at a concentration above the U.S. Aquatic Life Benchmark (3.5 ng/L) for acute toxicity to invertebrates.
Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
In 2016, the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers and the Federal Emergency Management Agency, began a study in Arkansas to investigate possible increasing trends in annual peak streamflow data and the possible resulting increase in the annual exceedance probability flood (AEPF) predictions. Temporal trends of peak streamflow were investigated at 15 selected streamgages on unregulated streams in Arkansas having 30 or more years of peak streamflow data through the 2016 water year. For the period of record at each streamgage, the Mann-Kendall trend test indicated that 14 of the 15 streamgages had no statistically significant peak streamflow trends and 1 streamgage had a statistically significant decreasing peak streamflow trend. Visual examination of the locally estimated scatterplot smoothing technique trend lines of the peak streamflow data indicated a possible increasing peak streamflow trend at 8 of the 15 streamgages since the 1990s.
A sequential series analysis of the 1-percent AEPF at each of the 15 selected streamgages was completed by selecting an initial subset of the oldest peak streamflow data from each site to estimate the initial 1-percent AEPF. This initial peak streamflow data subset was subsequently appended with 10-year increments of additional peak streamflow data until the full period of peak streamflow data was analyzed. The maximum increase in the 1-percent AEPF was 113 percent, and the maximum decrease was 31.9 percent.
Percentage differences between the AEPFs derived from regional regression equations presented in the 1995 and 2016 Arkansas flood-frequency reports were compared. The average percentage differences for the 74 selected locations indicate that the 4-, 2-, 1-, and 0.2-percent AEPFs computed using the 2016 regional regression equations were higher by 3.52, 5.10, 8.59, and 13.31 percent, respectively (25-, 50-, 100-, and 500-year recurrence interval floods), than the same percentage AEPFs computed using the 1995 regional regression equations. The average percentage differences between the 1995 and 2016 AEPFs for the 10-percent AEPF (10-year recurrence interval flood) resulted in 2016 AEPF predictions being 0.41 percent higher. For the 50- and 20-percent AEPFs (2- and 5-year recurrence interval floods), the 2016 AEPFs were less than the 1995 AEPFs by 2.53 and 0.31 percent, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195131","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and Federal Emergency Management Agency","usgsCitation":"Ensminger, P.A., and Breaker, B.K., 2019, Flood-frequency comparison from 1995 to 2016 and trends in peak streamflow in Arkansas, water years 1930–2016: U.S. Geological Survey Scientific Investigations Report 2019–5131, 20 p., https://doi.org/10.3133/sir20195131.","productDescription":"vi, 20 p.","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-087618","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":399610,"rank":3,"type":{"id":36,"text":"NGMDB Index 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640 Grassmere Park, Ste 100
Nashville, TN 37211
The Yorktown-Eastover aquifer system of the Virginia Eastern Shore consists of upper, middle, and lower confined aquifers overlain by correspondingly named confining units and underlain by the Saint Marys confining unit. Miocene- to Pliocene-age marine-shelf sediments observed in 205 boreholes include medium- to coarse-grained sand and shells that compose the aquifers and fine-grained sand, silt, and clay that compose the confining units. The upper confining unit also includes fine-grained and organic-rich back-barrier and estuarine sediments of Pleistocene age. An overlying surficial aquifer is composed mostly of Pleistocene-age nearshore sand and gravel with smaller amounts of cobbles and boulders.
In addition, Pleistocene-age sediments that fill three buried paleochannels are for the first time explicitly delineated here as distinct hydrogeologic units. Two aquifers are composed of medium- to coarse-grained fluvial sand and gravel, and an intervening confining unit is composed of fine-grained estuarine sand, silt, clay, and organic material. Aquifer and confining-unit sediments are also mixed with reworked marine-shelf sediments eroded from the sides of the paleochannels.
Hydrogeologic units of the Yorktown-Eastover aquifer system generally dip eastward, are as much as several tens of feet thick, and have an undulating configuration possibly resulting from the underlying Chesapeake Bay impact crater. Aquifers and confining units are incised by the three paleochannels along an upward-widening and eastward-lengthening series of structural “windows.” Hydrogeologic units within mainstems and branching tributaries of the paleochannels dip southeastward parallel to slopes of the paleochannels, are as much as several tens of feet thick, and laterally abut the Yorktown-Eastover aquifer system along paleochannel sidewalls. The Yorktown-Eastover aquifer system is thereby hydraulically breached by the paleochannels to alternately create barriers to or conduits for groundwater flow.
Results of previously documented aquifer tests at 58 wells indicate that transmissivity is generally greatest in young, shallow, and coarse-grained nearshore and fluvial sediments of the surficial aquifer and paleochannels. Transmissivity progressively decreases with depth in older, deeper, and finer grained marine-shelf sediments of the Yorktown-Eastover aquifer system, probably because they have undergone compaction as a result of greater overburden pressure over longer periods of time.
Compiled chloride concentrations in samples from 330 wells generally increase downward, with most of the samples collected at altitudes above −300 feet and with most concentrations less than 250 milligrams per liter. The saltwater-transition zone has a broad trough-like shape aligned with the peninsula, being relatively shallow along the coastline and deeper along the central “spine.” Because movement of the saltwater is slow, the configuration largely reflects groundwater flow prior to widespread groundwater withdrawals. Fresh groundwater has leaked downward along deep parts of the saltwater-transition zone and leaked upward along shallower parts to discharge at the coast.
The saltwater-transition zone also exhibits an anomalous ridge across the center of the peninsula. Groundwater levels indicate that the saltwater ridge formed primarily by the Exmore paleochannel acting as a large lateral collector drain. Groundwater levels were lowered, and the position of saltwater-transition zone was elevated, by a flow conduit that intercepted groundwater that otherwise would have flowed toward and discharged along the coastline.
Nearly all freshwater on the Virginia Eastern Shore is supplied by groundwater withdrawals, which have lowered water levels, altered hydraulic gradients, and created a concern for saltwater intrusion. Previous characterizations of groundwater conditions that are relied on to manage groundwater development have been limited by a lack of hydrogeologic information, particularly data on buried paleochannels that are critical to safeguarding the groundwater supply. Using recently available expanded information, the U.S. Geological Survey undertook a study in cooperation with the Virginia Department of Environmental Quality during 2016–19 to develop an improved description of the groundwater system called a “hydrogeologic framework.”
The hydrogeologic framework can aid water-supply planning and development by providing information on broad trends in aquifer configurations, hydraulic properties, and proximity to saltwater to avoid chloride contamination. Digital models to evaluate effects of groundwater withdrawals can also be improved with expanded data and capabilities to evaluate paleochannel hydraulic connections and the potential for saltwater movement.
The hydrogeologic framework is limited by the nonuniform distribution of boreholes and the subjective delineation of aquifers and confining units, including those within paleochannels that are regarded as preliminary. The configuration of the saltwater-transition zone is also regarded as preliminary because of the nonuniform distribution of groundwater samples. Low well-sampling frequency precludes characterizing movement of the saltwater-transition zone. A monitoring strategy of sampling and possibly electromagnetic-induction well logging could be used to detect saltwater movement.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195093","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"McFarland, E.R., and Beach, T.A., 2019, Hydrogeologic framework of the Virginia Eastern Shore: U.S. Geological Survey Scientific Investigations Report 2019–5093, 26 p., 13 pl., https://doi.org/10.3133/sir20195093.","productDescription":"Report: viii, 26 p.; 13 Plates: 11.00 x 17.00 inches or smaller; Data Release","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-108409","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":369803,"rank":16,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093.pdf","text":"Report","size":"3.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5093"},{"id":369731,"rank":15,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate13.pdf","text":"Plate 13","size":"352 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Locations and Numbers of Sampled Wells and Altitude of the 250-Milligram-Per-Liter Chloride-Concentration Surface on the Virginia Eastern Shore"},{"id":369730,"rank":14,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate12.pdf","text":"Plate 12","size":"332 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Upper Confining Unit on the Virginia Eastern Shore"},{"id":369725,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate07.pdf","text":"Plate 7","size":"346 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Middle Confining Unit on the Virginia Eastern Shore"},{"id":369724,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate06.pdf","text":"Plate 6","size":"340 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Middle Aquifer on the Virginia Eastern Shore"},{"id":369723,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate05.pdf","text":"Plate 5","size":"332 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Lower Confining Unit on the Virginia Eastern Shore"},{"id":399542,"rank":17,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109487.htm"},{"id":369721,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate03.pdf","text":"Plate 3","size":"323 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Saint Marys Confining Unit on the Virginia Eastern Shore"},{"id":369720,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate02.pdf","text":"Plate 2","size":"336 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Hydrogeologic Section through the Virginia Eastern Shore"},{"id":369719,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate01.pdf","text":"Plate 1","size":"339 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Locations and Numbers of Boreholes on the Virginia Eastern Shore"},{"id":369714,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MPE5SD","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Borehole hydrogeologic-unit top-surface altitudes, aquifer hydraulic properties, and groundwater-sample chloride-concentration data from 1906 through 2016 for the Virginia Eastern Shore"},{"id":369728,"rank":12,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate10.pdf","text":"Plate 10","size":"319 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Paleochannel Confining Unit on the Virginia Eastern Shore"},{"id":369727,"rank":11,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate09.pdf","text":"Plate 9","size":"316 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Paleochannel Lower Aquifer on the Virginia Eastern Shore"},{"id":369726,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate08.pdf","text":"Plate 8","size":"350 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Upper Aquifer on the Virginia Eastern Shore"},{"id":369729,"rank":13,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate11.pdf","text":"Plate 11","size":"321 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Paleochannel Upper Aquifer on the Virginia Eastern Shore"},{"id":369722,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate04.pdf","text":"Plate 4","size":"327 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Lower Aquifer on the Virginia Eastern Shore"},{"id":369709,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5093/coverthb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.058349609375,\n 37.1165261849112\n ],\n 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U.S. Geological Survey
1730 East Parham Road
Richmond, Virginia 23228
Faced with limitations in data availability, funding, and time constraints, ecologists are often tasked with making predictions beyond the range of their data. In ecological studies, it is not always obvious when and where extrapolation occurs because of the multivariate nature of the data. Previous work on identifying extrapolation has focused on univariate response data, but these methods are not directly applicable to multivariate response data, which are common in ecological investigations. In this paper, we extend previous work that identified extrapolation by applying the predictive variance from the univariate setting to the multivariate case. We propose using the trace or determinant of the predictive variance matrix to obtain a scalar value measure that, when paired with a selected cutoff value, allows for delineation between prediction and extrapolation. We illustrate our approach through an analysis of jointly modeled lake nutrients and indicators of algal biomass and water clarity in over 7000 inland lakes from across the Northeast and Mid-west US. In addition, we outline novel exploratory approaches for identifying regions of covariate space where extrapolation is more likely to occur using classification and regression trees. The use of our Multivariate Predictive Variance (MVPV) measures and multiple cutoff values when exploring the validity of predictions made from multivariate statistical models can help guide ecological inferences.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0225715","usgsCitation":"Bartley, M., Hanks, E.M., Schliep, E.M., Soranno, P.A., and Wagner, T., 2019, Identifying and characterizing extrapolation in multivariate response data: PLoS ONE, v. 14, no. 12, e0225715, 20 p., https://doi.org/10.1371/journal.pone.0225715.","productDescription":"e0225715, 20 p.","ipdsId":"IP-107783","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":459016,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0225715","text":"Publisher Index Page"},{"id":393911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"12","noUsgsAuthors":false,"publicationDate":"2019-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Bartley, Meridith L.","contributorId":270913,"corporation":false,"usgs":false,"family":"Bartley","given":"Meridith L.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":830122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanks, Ephraim M.","contributorId":178093,"corporation":false,"usgs":false,"family":"Hanks","given":"Ephraim","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":830123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schliep, Erin M.","contributorId":171525,"corporation":false,"usgs":false,"family":"Schliep","given":"Erin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":830124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Soranno, Patricia A.","contributorId":172104,"corporation":false,"usgs":false,"family":"Soranno","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":830125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":830121,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70207037,"text":"70207037 - 2019 - Evaluation of stormwater treatment vault with Coanda-effect screen for removal of solids and phosphorus in urban runoff","interactions":[],"lastModifiedDate":"2019-12-04T15:38:49","indexId":"70207037","displayToPublicDate":"2019-12-04T15:37:46","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5896,"text":"Journal of Sustainable Water in the Built Environment","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of stormwater treatment vault with Coanda-effect screen for removal of solids and phosphorus in urban runoff","docAbstract":"Catch basins commonly are used by cities as part of a stormwater management plan to remove sediment and associated contaminants from stormwater, keeping them in compliance with regulations. Recently, the city of Madison, Wisconsin modified traditional catch basins by incorporating a fine-mesh (1-mm) Coanda-effect screen into the design with the goal of increasing removal of sediment and organic matter from stormwater. The US Geological Survey (USGS), in cooperation with the City of Madison, installed a water-quality monitoring station at such a catch basin to quantify reductions in total suspended solids (TSS), volatile suspended solids (VSS), suspended sediment concentration (SSC), total phosphorus (TP), and dissolved phosphorus (DP) from urban stormwater before entering Lake Monona. A comparison of the cumulative load from 33 samples collected during the summers of 2016 and 2017 showed 23% and 45% reductions in TSS and SSC, respectively. A smaller reduction was observed for TP, 16%, whereas DP remained unchanged. Reported traditional catch basin sediment removal varies greatly, although typical removal rates are similar. Results from this study will help regulated municipalities determine whether the use of screened catch basins can help meet water-quality goals.","language":"English","publisher":"ASCE","doi":"10.1061/JSWBAY.0000892","usgsCitation":"Buer, N., and Selbig, W.R., 2019, Evaluation of stormwater treatment vault with Coanda-effect screen for removal of solids and phosphorus in urban runoff: Journal of Sustainable Water in the Built Environment, v. 6, no. 1, 04019013, 10 p., https://doi.org/10.1061/JSWBAY.0000892.","productDescription":"04019013, 10 p.","ipdsId":"IP-096348","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":459017,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1061/jswbay.0000892","text":"Publisher Index Page"},{"id":369921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Dane County","city":"Madison","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-89.0094,43.286],[-89.0084,43.2555],[-89.0094,43.2],[-89.01,43.1131],[-89.0109,43.0849],[-89.0107,43.0271],[-89.0132,42.9353],[-89.013,42.8762],[-89.0119,42.8471],[-89.132,42.8479],[-89.2488,42.8478],[-89.3689,42.8484],[-89.3688,42.8575],[-89.4832,42.858],[-89.6026,42.8575],[-89.7196,42.8587],[-89.8377,42.8598],[-89.8375,42.9471],[-89.8386,43.0317],[-89.8384,43.1181],[-89.8394,43.205],[-89.8325,43.2123],[-89.825,43.2187],[-89.8175,43.226],[-89.8125,43.2342],[-89.8088,43.2369],[-89.8012,43.2365],[-89.7874,43.2356],[-89.771,43.237],[-89.7579,43.2379],[-89.7529,43.2443],[-89.7485,43.2507],[-89.7391,43.2548],[-89.7259,43.2644],[-89.7171,43.2739],[-89.714,43.2821],[-89.7165,43.2867],[-89.7235,43.2935],[-89.7209,43.2935],[-89.6008,43.2932],[-89.4819,43.2942],[-89.3617,43.2954],[-89.3624,43.2832],[-89.246,43.2834],[-89.1271,43.2827],[-89.0094,43.286]]]},\"properties\":{\"name\":\"Dane\",\"state\":\"WI\"}}]}","volume":"6","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Buer, Nicolas 0000-0002-4369-8715","orcid":"https://orcid.org/0000-0002-4369-8715","contributorId":204808,"corporation":false,"usgs":true,"family":"Buer","given":"Nicolas","email":"","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":776592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":776593,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70215094,"text":"70215094 - 2019 - Improving predictions of fine particle immobilization in streams","interactions":[],"lastModifiedDate":"2020-10-07T20:12:43.002013","indexId":"70215094","displayToPublicDate":"2019-12-04T15:06:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Improving predictions of fine particle immobilization in streams","docAbstract":"Fine particles are critical to stream ecosystem functioning, influencing in-stream processes from pathogen transmission to carbon cycling, all of which depend on particle immobilization. However, our ability to predict particle immobilization is limited by: (1) availability of combined solute and particle tracer data and (2) identifying parameters that appropriately represent fine particle immobilization, due to the myriad of objective functions and model formulations. We found that improved predictions of the full distribution of possible fine particle residence times requires using an objective function that assesses both the peak and tailing together with solute tracers to constrain in-stream transport processes. The representation of immobilization processes was significantly improved when solute tracer data were combined with a particle model, starkly contrasting the common assumption that fine particles transport as washload. We develop a clear strategy for improving fine particle transport predictions, reshaping the potential role of fine particles in water quality management.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GL085849","usgsCitation":"Drummond, J.D., Schmadel, N., Kelleher, C., Packman, A.I., and Ward, A.S., 2019, Improving predictions of fine particle immobilization in streams: Geophysical Research Letters, v. 46, no. 23, p. 13,853-13,861, https://doi.org/10.1029/2019GL085849.","productDescription":"9 p.","startPage":"13,853","endPage":"13,861","ipdsId":"IP-114105","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":459021,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019gl085849","text":"Publisher Index Page"},{"id":379197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"23","noUsgsAuthors":false,"publicationDate":"2019-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Drummond, Jennifer D.","contributorId":191390,"corporation":false,"usgs":false,"family":"Drummond","given":"Jennifer","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":800820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmadel, Noah 0000-0002-2046-1694","orcid":"https://orcid.org/0000-0002-2046-1694","contributorId":219105,"corporation":false,"usgs":true,"family":"Schmadel","given":"Noah","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":800821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelleher, Christa","contributorId":242798,"corporation":false,"usgs":false,"family":"Kelleher","given":"Christa","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":800822,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Packman, Aaron I.","contributorId":124517,"corporation":false,"usgs":false,"family":"Packman","given":"Aaron","email":"","middleInitial":"I.","affiliations":[{"id":5041,"text":"Department of Civil and Environmental Engineering, Northwestern University, Evanston, Illinois, USA","active":true,"usgs":false}],"preferred":false,"id":800823,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ward, Adam S","contributorId":191363,"corporation":false,"usgs":false,"family":"Ward","given":"Adam","email":"","middleInitial":"S","affiliations":[],"preferred":false,"id":800824,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208455,"text":"70208455 - 2019 - Measurement of cyanobacteria bloom magnitude using satellite remote sensing","interactions":[],"lastModifiedDate":"2020-02-11T07:47:17","indexId":"70208455","displayToPublicDate":"2019-12-04T07:43:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Measurement of cyanobacteria bloom magnitude using satellite remote sensing","docAbstract":"Cyanobacterial harmful algal blooms (cyanoHABs) are a serious environmental, water quality and public health issue worldwide because of their ability to form dense biomass and produce toxins. Models and algorithms have been developed to detect and quantify cyanoHABs biomass using remotely sensed data but not for quantifying bloom magnitude, information that would guide water quality management decisions. We propose a method to quantify seasonal and annual cyanoHAB magnitude in lakes and reservoirs. The magnitude is the spatio-temporal mean of weekly or biweekly maximum cyanobacteria biomass for the season or year. CyanoHAB biomass is quantified using a standard reflectance spectral shape-based algorithm that uses data from Medium Resolution Imaging Spectrometer (MERIS). We demonstrate the method to quantify annual and seasonal cyanoHAB magnitude in Florida and Ohio respectively during 2003-2011 and rank the lakes based on median magnitude over the study period. The new method can be applied to Ocean Land Color Imager (OLCI) on Sentinel-3 data for assessment of cyanoHABs and the change over time, even with issues such as variable data acquisition frequency or sensor calibration uncertainties between satellites. CyanoHAB magnitude can support monitoring and management decision-making for recreational and drinking water sources.","language":"English","publisher":"Nature","doi":"10.1038/s41598-019-54453-y","usgsCitation":"Mishra, S., Stumpf, R.P., Schaeffer, B., Werdell, P.J., Loftin, K., and Meredith, A., 2019, Measurement of cyanobacteria bloom magnitude using satellite remote sensing: Scientific Reports, no. 1, 18310, 17 p., https://doi.org/10.1038/s41598-019-54453-y.","productDescription":"18310, 17 p.","ipdsId":"IP-111006","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":459026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-54453-y","text":"Publisher Index Page"},{"id":372207,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, 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Jeremy 0000-0002-3592-0152","orcid":"https://orcid.org/0000-0002-3592-0152","contributorId":222358,"corporation":false,"usgs":false,"family":"Werdell","given":"P.","email":"","middleInitial":"Jeremy","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":781962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Keith A. 0000-0001-5291-876X","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":205662,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":781958,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meredith, Andrew 0000-0001-9651-7132","orcid":"https://orcid.org/0000-0001-9651-7132","contributorId":222359,"corporation":false,"usgs":false,"family":"Meredith","given":"Andrew","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":781963,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70207032,"text":"70207032 - 2019 - Environmental and biological factors influence migratory Sea Lamprey catchability: Implications for tracking abundance in the Laurentian Great Lakes","interactions":[],"lastModifiedDate":"2020-07-09T14:33:55.941943","indexId":"70207032","displayToPublicDate":"2019-12-03T18:57:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Environmental and biological factors influence migratory Sea Lamprey catchability: Implications for tracking abundance in the Laurentian Great Lakes","docAbstract":"Sea Lamprey Petromyzon marinus population trends in the Great Lakes are tracked by trapping migratory adults in tributaries and using mark and recapture techniques to estimate abundance. Understanding what environmental and biological factors influence Sea Lamprey capture in tributaries is crucial to developing efficient trapping methods and reliable abundance estimates. We analyzed data from trapping sites located on eight Great Lakes tributaries using Cormack-Jolly-Seber models and examined how water temperature, discharge, sex, and length influenced Sea Lamprey apparent survival and capture probability. Sea Lamprey apparent survival was negatively associated with water temperature in all tributaries. Additionally, the odds of small Sea Lamprey (≤45 cm) remaining available to capture were 39% less (95% CI: 63% decrease – 1% increase) than large (>45 cm) lamprey odds. These observed relationships were used to investigate if bias in abundance estimates using the pooled-Petersen estimator and Jolly-Seber models was expected to be similar across trapping locations or influenced by variable environmental conditions and biological traits. Pooled-Petersen abundance estimates had a positive bias when datasets were generated from simulated populations with empirical relationships between environmental characteristics and catchability. The degree of bias depended upon changes in stream warming patterns and was not consistent among trapping locations. Jolly-Seber models using data from either weekly-batch-marked or uniquely-marked individuals generated abundance estimate with low bias when data quality was high, but performed poorly in scenarios with few recaptured Sea Lamprey. This research can promote improved Sea Lamprey monitoring efforts by providing insight into the reliability of the pooled-Petersen abundance estimator as a tool for tracking Sea Lamprey populations and demonstrating the limitations of adopting more robust methods when data are sparse.","language":"English","publisher":"U.S. Fish and Wildlife Scientific Journals","doi":"10.3996/022019-JFWM-013","usgsCitation":"Lewandoski, S.A., Bravener, G.A., Hrodey, P.J., and Miehls, S.M., 2019, Environmental and biological factors influence migratory Sea Lamprey catchability: Implications for tracking abundance in the Laurentian Great Lakes: Journal of Fish and Wildlife Management, v. 11, no. 1, p. 68-79, https://doi.org/10.3996/022019-JFWM-013.","productDescription":"12 p.","startPage":"68","endPage":"79","ipdsId":"IP-112927","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":459029,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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A","contributorId":174546,"corporation":false,"usgs":false,"family":"Bravener","given":"Gale","email":"","middleInitial":"A","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":776579,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hrodey, Peter J.","contributorId":205578,"corporation":false,"usgs":false,"family":"Hrodey","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":6599,"text":"U.S. Fish and Wildlife Service, Marquette Biological Station","active":true,"usgs":false}],"preferred":false,"id":776580,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miehls, Scott M. 0000-0002-5546-1854 smiehls@usgs.gov","orcid":"https://orcid.org/0000-0002-5546-1854","contributorId":5007,"corporation":false,"usgs":true,"family":"Miehls","given":"Scott","email":"smiehls@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":776577,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70206985,"text":"70206985 - 2019 - Observations of the spawning ecology of the imperiled Clear Lake Hitch Lavinia exilicauda chi","interactions":[],"lastModifiedDate":"2019-12-03T06:44:18","indexId":"70206985","displayToPublicDate":"2019-12-02T15:08:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1153,"text":"California Fish and Game","active":true,"publicationSubtype":{"id":10}},"title":"Observations of the spawning ecology of the imperiled Clear Lake Hitch Lavinia exilicauda chi","docAbstract":"Migrations for the purposes of reproduction are widely documented across the animal kingdom and are particularly common in fishes and other aquatic organisms (Dingle 2014). One important migration strategy in fishes is potamodromy, which is the movement from one location to another entirely within freshwater (Morais and Daverat 2016). Thurow (2016) estimated that worldwide there are approximately 13,000 potamodromous fish species. Potamodromous species as a group are also relatively imperiled, owing to the loss or destruction of the diversity of habitats often required for successful reproduction and recruitment (Thurow 2016). \nThe Clear Lake Hitch Lavinia exilicauda chi is an imperiled potamodromous cyprinid that is endemic to a single freshwater lake: Clear Lake, Lake County, California, USA. The species lives to approximately six years of age and attains a maximum size of approximately 350 mm fork length. As juveniles and adults, it feeds primarily on macroinvertebrates, including insects and zooplankton (Geary and Moyle 1980). Formerly highly abundant and a staple food for the Pomo tribes of the Clear Lake region, Clear Lake Hitch abundance is believed to have declined substantially from historical levels (California Department of Fish and Wildlife [CDFW] 2014). Presently, Clear Lake Hitch is listed as threatened under the California Endangered Species Act and has been petitioned for listing under the U.S. Endangered Species Act. \nThe purpose of this paper is to document fortuitous observations of Clear Lake Hitch spawning and holding in stream habitat to generate baseline information that is needed to manage the species. The observations facilitated addressing the following questions (1) under what water temperature and flow conditions does spawning occur?, (2) what are the major habitat features where spawning takes place?, (3) what are the fundamental aspects of spawning behavior?, (4) what is the immediate fate of eggs deposited during spawning?, and (5) when not engaged in spawning, what type of stream habitat is used by Clear Lake Hitch and do they actively feed?","language":"English","publisher":"California Department of Fish and Wildlife","collaboration":"USFWS","usgsCitation":"Feyrer, F.V., 2019, Observations of the spawning ecology of the imperiled Clear Lake Hitch Lavinia exilicauda chi: California Fish and Game, v. 105, no. 4, p. 225-232.","productDescription":"8 p.","startPage":"225","endPage":"232","ipdsId":"IP-107702","costCenters":[{"id":154,"text":"California Water Science 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Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-3073","displayTitle":"Reach-Scale Monitoring and Modeling of Rivers—Expanding Hydraulic Data Collection Beyond the Cross Section","title":"Reach-scale monitoring and modeling of rivers--Expanding hydraulic data collection beyond the cross section","docAbstract":"For over 125 years, the U.S. Geological Survey streamgage network has provided important\nhydrologic information about rivers and streams throughout the Nation. Traditional streamgage\nmethods provide reliable stage and streamflow data but typically only monitor stage at a single location in a river and require frequent calibration streamflow measurements. Direct measurements are not always feasible, therefore improved sensors and methods\nare being deployed at gages to better document streamflow conditions between measurements. The technology and techniques of reach-scale monitoring allow the U.S. Geological Survey to collect more data across the full range of streamflow without requiring that a hydrographer be present. The U.S. Geological Survey Arizona Water Science Center’s reach-scale monitoring program will enhance the Arizona streamgage network with more accurate streamflow measurements and provide more extensive streamflow records and geomorphological\ndatasets for our agency partners and the public. Reach-scale monitoring installations and techniques are applicable to streams of the western United States and likely throughout the Nation.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193073","collaboration":"Prepared in cooperation with Arizona Department of Transportation","usgsCitation":"Forbes, B.T., Bunch, C.E., DeBenedetto, G., Shaw, C.J., and Gungle, B., 2019, Reach-scale monitoring and modeling of rivers—Expanding hydraulic data collection beyond the cross section: U.S. Geological Survey Fact Sheet 2019–3073, 6p., https://doi.org/10.3133/fs20193073.","productDescription":"6 p.","ipdsId":"IP-075529","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":369839,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3073/fs20193073.pdf","text":"Report","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 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\"}}]}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
-The 2019 spring prey fish trawl survey was the most extensive fish survey ever conducted on Lake Ontario with 252 bottom trawls collecting 214,569 fish from 39 species, in main-lake and embayment habitats, at depths ranging from 5 to 225 meters (16.5 – 742.5 feet).
-Alewife distribution was similar in U.S. (southern) and Canadian (northern) portions of the lake, which differs from the previous three years of whole-lake surveys when Alewife in April were more abundant in either U.S. (2017) or Canadian (2016, 2018) waters.
-The 2019 lake-wide average biomass index for adult Alewife (Age2+) declined 29% relative to 2018.
-The lake-wide biomass index for Age-1 Alewife in 2019 (2.2 kg/ha) declined relative to 2018 (2.6 kg/ha) and was the lowest Age-1 biomass observed since whole-lake sampling began in 2016.
-The current biomass, size structure, and age structure of the adult Alewife population reflect the lower than-average Alewife reproductive success observed in the 2013- and 2014-year classes.
-Reproductive success was also lower than average in 2017 and 2018, suggesting the adult Alewife biomass may continue to decline.
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linked to the live-food trade and prayer-release rituals","docAbstract":"We provide a history of swamp eel (family Synbranchidae) introductions around the globe and report the first confirmed nonindigenous records of Amphipnous cuchia in the wild. The species, native to Asia, is documented from five sites in the USA: the Passaic River, New Jersey (2007), Lake Needwood, Maryland (2014), a stream in Pennsylvania (2015), the Tittabawassee River, Michigan (2017), and Meadow Lake, New York (2017). The international live-food trade constitutes the major introduction pathway, a conclusion based on: (1) United States Fish and Wildlife Service’s Law Enforcement Management Information System (LEMIS) database records revealing regular swamp eel imports from Asia since at least the mid-1990s; (2) surveys (2001–2018) documenting widespread distribution of live A. cuchia among ethnic food markets in the USA and Canada; (3) indications that food markets are the only source of live A. cuchia in North America; and (4) presence of live A. cuchia in markets close to introduction sites. Prayer release appears to be an important pathway component, whereby religious practitioners purchase live A. cuchia from markets and set them free. Prevalence of A. cuchia in US markets since 2001 indicates the species is the principal swamp eel imported, largely replacing members of the Asian complex Monopterus albus/javanensis. LEMIS records (July 1996–January 2017) document 972 shipments containing an estimated 832,897 live swamp eels entering the USA, although these data underestimate actual numbers due to undeclared and false reporting. LEMIS data reveal most imports originate in Bangladesh, Vietnam, and China. However, LEMIS wrongly identifies many imported swamp eels as “Monopterus albus”; none are identified as A. cuchia although specimens from Bangladesh and India are almost certainly this species. Some imported A. cuchia are erroneously declared on import forms as Anguilla bengalensis. To date, there is no evidence of A. cuchia reproduction in open waters of North America, presumably because it is a tropical-subtropical species and all introductions thus far have been in latitudes where winter water temperatures regularly fall near or below freezing.","language":"English","publisher":"REABIC","doi":"10.3391/ai.2019.14.4.14","usgsCitation":"Nico, L., Kilian, J.V., Ropicki, A.J., and Harper, M., 2019, Asian swamp eels in North America linked to the live-food trade and prayer-release rituals: Aquatic Invasions, v. 14, no. 4, p. 775-814, https://doi.org/10.3391/ai.2019.14.4.14.","productDescription":"40 p.","startPage":"775","endPage":"814","ipdsId":"IP-101553","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":459040,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/ai.2019.14.4.14","text":"Publisher Index 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J.","contributorId":220970,"corporation":false,"usgs":false,"family":"Ropicki","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":40301,"text":"Texas A&M University/Texas Sea Grant, Corpus Christi","active":true,"usgs":false}],"preferred":false,"id":776409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harper, Matthew","contributorId":220971,"corporation":false,"usgs":false,"family":"Harper","given":"Matthew","email":"","affiliations":[{"id":40302,"text":"Maryland National Capital Park and Planning Commission","active":true,"usgs":false}],"preferred":false,"id":776410,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203103,"text":"70203103 - 2019 - Aquatic cycling of mercury","interactions":[],"lastModifiedDate":"2019-12-04T17:16:12","indexId":"70203103","displayToPublicDate":"2019-12-01T17:13:56","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"1","title":"Aquatic cycling of mercury","docAbstract":"This chapter examines crucial processes in the aquatic cycling of mercury (Hg) that may lead to microbial production of neurotoxic and bioaccumulative methylmercury (MeHg), and highlights environmental conditions in the Everglades that make it ideal for MeHg production and bioaccumulation. The role of complexation of Hg2+ in surface water, especially by dissolved organic matter (DOM), in the transport of mercury to sites of microbial methylation are discussed. Photochemical reactions important in Hg cycling in surface water are also discussed. A principal focus of the chapter is on the environmental conditions that promote MeHg production, especially the role of sulfide and DOM in transport of inorganic Hg into bacteria for methylation, and the types of bacteria that have the ability to methylate Hg. Finally, perturbations to the ecosystem (e.g., fire and drought) that have important effects on Hg cycling are discussed.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Mercury and the Everglades. A synthesis and model for complex ecosystem restoration","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-32057-7_1","usgsCitation":"Orem, W.H., Krabbenhoft, D.P., Poulin, B., and Aiken, G.A., 2019, Aquatic cycling of mercury, chap. 1 of Mercury and the Everglades. A synthesis and model for complex ecosystem restoration, p. 1-12, https://doi.org/10.1007/978-3-030-32057-7_1.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-106651","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":369934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":761180,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":761181,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poulin, Brett 0000-0002-5555-7733 bpoulin@usgs.gov","orcid":"https://orcid.org/0000-0002-5555-7733","contributorId":194253,"corporation":false,"usgs":true,"family":"Poulin","given":"Brett","email":"bpoulin@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":761183,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aiken, George A 0000-0001-8454-0984","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":206312,"corporation":false,"usgs":false,"family":"Aiken","given":"George","email":"","middleInitial":"A","affiliations":[{"id":37307,"text":"formerly USGS, deceased","active":true,"usgs":false}],"preferred":false,"id":761182,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203511,"text":"70203511 - 2019 - Sulfur contamination in the Everglades, a major control on mercury methylation","interactions":[],"lastModifiedDate":"2019-12-03T12:03:22","indexId":"70203511","displayToPublicDate":"2019-12-01T11:59:49","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"2","title":"Sulfur contamination in the Everglades, a major control on mercury methylation","docAbstract":"In this chapter sulfur contamination of the Everglades and its role as a major control on methylmercury (MeHg) production is examined. Sulfate concentrations over large portions of the Everglades (60% of the ecosystem) are elevated or greatly elevated compared to background conditions of <1 mg/L. Land and water management practices in south Florida are the primary reason for the high levels of sulfate loading to the Everglades. Marshes in the northern Everglades that are highly enriched in sulfate have average concentrations of 60 mg/L, but water in canals in the Everglades Agricultural Area (EAA) contain the highest concentrations of sulfate averaging 60–70 mg/L. Studies that examined the mass balance of sulfur to the Everglades have determined that the primary sources of sulfate include: sulfur currently used in agriculture, and natural and legacy agricultural sulfur released by oxidation of organic soil within the EAA. The extensive loading of sulfate to the ecosystem increases microbial sulfate reduction, the dominant microbial process driving mercury methylation and MeHg production. The biogeochemical processes linking sulfate loading and MeHg production, however, are complex. MeHg production increases as sulfate levels rise from levels <1 mg/L up to about 20 mg/L. However, production of sulfide (a byproduct of microbial sulfate reduction) starts to inhibit MeHg production above 20 mg/L. Sulfate loading to canals in the EAA has impacted the northern Everglades the most, but the Everglades canal system can transport sulfate as far as Everglades National Park (ENP), 80 km further south. Plans to deliver more water to ENP as part of restoration may increase overall sulfate loads to the southern Everglades.
Reduction of sulfate loading should be a major goal of Everglades restoration because of the many negative effects of sulfate on the ecosystem. The ecosystem has been shown to respond quickly to reductions in sulfate loading, and strategies for reducing sulfate loading may produce positive outcomes for the Everglades in the near-term. Strategies for reducing sulfate loading will need to include: best management practices for agricultural use of sulfate, approaches to minimize soil oxidation in the EAA, and modifications to stormwater treatment areas to improve sulfate retention.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Mercury and the Everglades. A Synthesis and Model for Complex Ecosystem Restoration","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-32057-7_2","usgsCitation":"Orem, W.H., Krabbenhoft, D.P., Poulin, B., and George Aiken, 2019, Sulfur contamination in the Everglades, a major control on mercury methylation, chap. 2 of Mercury and the Everglades. A Synthesis and Model for Complex Ecosystem Restoration, p. 13-48, https://doi.org/10.1007/978-3-030-32057-7_2.","productDescription":"36 p.","startPage":"13","endPage":"48","ipdsId":"IP-106372","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":369873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.3153076171875,\n 25.075648445630527\n ],\n [\n -80.33752441406249,\n 25.075648445630527\n ],\n [\n -80.33752441406249,\n 25.854280326572407\n ],\n [\n -81.3153076171875,\n 25.854280326572407\n ],\n [\n -81.3153076171875,\n 25.075648445630527\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":762941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":762942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poulin, Brett 0000-0002-5555-7733 bpoulin@usgs.gov","orcid":"https://orcid.org/0000-0002-5555-7733","contributorId":194253,"corporation":false,"usgs":true,"family":"Poulin","given":"Brett","email":"bpoulin@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":762943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"George Aiken","contributorId":215670,"corporation":false,"usgs":false,"family":"George Aiken","affiliations":[{"id":39302,"text":"USGS WMA Boulder (Deceased)","active":true,"usgs":false}],"preferred":false,"id":762944,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207536,"text":"70207536 - 2019 - Biogeographical patterns of tunicates utilizing eelgrass as substrate in the western North Atlantic between 39o and 47o north latitude (New Jersey to Newfoundland)","interactions":[],"lastModifiedDate":"2019-12-24T11:18:10","indexId":"70207536","displayToPublicDate":"2019-12-01T11:09:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Biogeographical patterns of tunicates utilizing eelgrass as substrate in the western North Atlantic between 39o and 47o north latitude (New Jersey to Newfoundland)","title":"Biogeographical patterns of tunicates utilizing eelgrass as substrate in the western North Atlantic between 39o and 47o north latitude (New Jersey to Newfoundland)","docAbstract":"Colonization of eelgrass (Zostera marina L.) by tunicates can lead to reduced plant growth and survival. Several of the tunicate species that are found on eelgrass in the northwest Atlantic are highly aggressive colonizers, and range expansions are predicted in association with climate-change induced increases in seawater temperature. In 2017, we surveyed tunicates within eelgrass meadows at 33 sites from New Jersey to Newfoundland. Eight tunicate species were identified colonizing eelgrass, of which four were non-native and one was cryptogenic. The most common species (Botrylloides violaceus and Botryllus schlosseri) occurred from New York to Atlantic Canada. Tunicate faunas attached to eelgrass were less diverse north of Cape Cod, Massachusetts. Artificial substrates in the vicinity of the eelgrass meadows generally supported more tunicate species than did the eelgrass, but fewer species co-occurred in northern sites than southern sites. The latitudinal gradient in tunicate diversity corresponded to gradients of summertime sea surface temperature and traditional biogeographical zones in the northwest Atlantic, where Cape Cod represents a transition between cold-water and warm-water invertebrate faunas. Tunicate density in the eelgrass meadows was low, ranging generally from 1–25% cover of eelgrass shoots, suggesting that space availability does not currently limit tunicate colonization of eelgrass. This survey, along with our 2013 survey, provide a baseline for identifying future changes in tunicate distribution and abundance in northwest Atlantic eelgrass meadows.
","language":"English","publisher":"REABIC","doi":"10.3391/mbi.2019.10.4.02","usgsCitation":"Carman, M.R., Colarusso, P., Neckles, H.A., Bologna, P., Caines, S., Davidson, J.D., Evans, N.T., Fox, S., Grunden, D.W., Hoffman, S., Ma, K.C., Matheson, K., McKenzie, C., Nelson, E.P., Plaisted, H., Reddington, E., Schott, S., and Wong, M.C., 2019, Biogeographical patterns of tunicates utilizing eelgrass as substrate in the western North Atlantic between 39o and 47o north latitude (New Jersey to Newfoundland): Management of Biological Invasions, v. 10, no. 4, p. 602-616, https://doi.org/10.3391/mbi.2019.10.4.02.","productDescription":"15 p.","startPage":"602","endPage":"616","ipdsId":"IP-108765","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":459056,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2019.10.4.02","text":"Publisher Index Page"},{"id":370665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Connecticut, Maine, Massachusetts, New Brunswick, Newfoundland, New Hampshire, New Jersey, New York, Nova Scotia, Prince Edward Island, Rhode Island","otherGeospatial":"North Altantic","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -53.78906249999999,\n 46.649436163350245\n ],\n [\n -58.18359375,\n 48.48748647988415\n ],\n [\n -64.951171875,\n 46.9502622421856\n ],\n [\n -67.8076171875,\n 44.74673324024678\n ],\n [\n -70.83984375,\n 43.739352079154706\n ],\n [\n -71.2353515625,\n 42.35854391749705\n ],\n [\n -71.8505859375,\n 41.44272637767212\n ],\n [\n -73.95996093749999,\n 41.0130657870063\n ],\n [\n -75.6298828125,\n 39.027718840211605\n ],\n [\n -75.41015624999999,\n 38.13455657705411\n ],\n [\n -53.78906249999999,\n 46.649436163350245\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carman, Mary R.","contributorId":218699,"corporation":false,"usgs":false,"family":"Carman","given":"Mary","email":"","middleInitial":"R.","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":778371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Colarusso, Philip D.","contributorId":218700,"corporation":false,"usgs":false,"family":"Colarusso","given":"Philip D.","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":778372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Neckles, Hilary A. 0000-0002-5662-2314 hneckles@usgs.gov","orcid":"https://orcid.org/0000-0002-5662-2314","contributorId":3821,"corporation":false,"usgs":true,"family":"Neckles","given":"Hilary","email":"hneckles@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":778370,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bologna, Paul","contributorId":218701,"corporation":false,"usgs":false,"family":"Bologna","given":"Paul","email":"","affiliations":[{"id":36592,"text":"Montclair State University","active":true,"usgs":false}],"preferred":false,"id":778373,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caines, Scott","contributorId":218702,"corporation":false,"usgs":false,"family":"Caines","given":"Scott","email":"","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":778374,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Davidson, John D. 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K.","contributorId":218707,"corporation":false,"usgs":false,"family":"Ma","given":"Kevin","email":"","middleInitial":"C. K.","affiliations":[{"id":39893,"text":"Laval University","active":true,"usgs":false}],"preferred":false,"id":778379,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Matheson, Kyle","contributorId":167225,"corporation":false,"usgs":false,"family":"Matheson","given":"Kyle","email":"","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":778380,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McKenzie, Cynthia","contributorId":167224,"corporation":false,"usgs":false,"family":"McKenzie","given":"Cynthia","email":"","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":778381,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Nelson, Eric P.","contributorId":218708,"corporation":false,"usgs":false,"family":"Nelson","given":"Eric","email":"","middleInitial":"P.","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":778382,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Plaisted, Holly","contributorId":218709,"corporation":false,"usgs":false,"family":"Plaisted","given":"Holly","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":778383,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Reddington, Emily","contributorId":218710,"corporation":false,"usgs":false,"family":"Reddington","given":"Emily","email":"","affiliations":[{"id":39894,"text":"Great Pond Foundation","active":true,"usgs":false}],"preferred":false,"id":778384,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Schott, Stephen","contributorId":167228,"corporation":false,"usgs":false,"family":"Schott","given":"Stephen","email":"","affiliations":[{"id":24649,"text":"Cornell University Cooperative Extension","active":true,"usgs":false}],"preferred":false,"id":778385,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Wong, Melisa C.","contributorId":218711,"corporation":false,"usgs":false,"family":"Wong","given":"Melisa","email":"","middleInitial":"C.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":778386,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70215325,"text":"70215325 - 2019 - Population characteristics and the potential suppression of common carp in Lake Spokane, Washington","interactions":[],"lastModifiedDate":"2020-10-16T14:10:58.363964","indexId":"70215325","displayToPublicDate":"2019-12-01T09:06:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Population characteristics and the potential suppression of common carp in Lake Spokane, Washington","docAbstract":"Common Carp Cyprinus carpio is a nonnative species that often has deleterious effects on aquatic systems. As such, there is interest in suppressing nonnative Common Carp populations in areas where humans have introduced them. The objectives of this study were to 1) provide insight on efficient techniques for capturing Common Carp, 2) describe their population demographics and dynamics, 3) evaluate whether temperature and water elevation were related to growth and recruitment, and 4) develop an age-structured population model for evaluating different management scenarios of Common Carp removal in Lake Spokane, Washington. Catch rates of Common Carp varied among sampling gears with slightly higher catch rates in monofilament (mean ± SD; 15.5 ± 9.8 fish/net night) vs. multifilament (12.7 ± 7.3 fish/net night) gill nets. Catch rates of Common Carp with nighttime electrofishing (0.3 ± 0.4 fish/min) were higher than daytime electrofishing (0.1 ± 0.2 fish/min). Common Carp in Lake Spokane exhibited variable recruitment, rapid growth, large-length structure, high longevity (i.e., age 18 y), and low total annual mortality (17.0%). Air temperature was positively associated with annual growth increments (R2 ≤ 0.25). Neither air temperature nor water elevation was highly correlated (R2 ≤ 0.20) to recruitment of Common Carp. A Beverton–Holt yield-per-recruit model suggested that yield declined with increasing exploitation. Recruitment overfishing would occur at exploitation rates of 20–40% for all targeted minimum length categories (i.e., 150, 300, 450 mm) except 600 mm. Results from this study provide important information on the ecology of Common Carp that can be used to guide management efforts (e.g., suppression) in western systems.
How is drought expressed in Hawai‘i & USAPI? Drought is a significant climate feature in Hawai‘i and the U.S.-Affiliated Pacific Islands (USAPI), at times causing severe impacts across multiple sectors. Below average precipitation anomalies are often accompanied by higher than average temperatures and reduced cloud cover. The resulting higher insolation and evapotranspiration can magnify the effects of rainfall deficits. These altered meteorological conditions lead to decreased soil moisture, which, depending on the persistence and severity of the conditions, can cause plant stress, affecting both agricultural and natural systems. The hydrological effects of drought include reductions in streamflow, groundwater recharge, and groundwater discharge to springs, streams, and the ocean. Drought also has socioeconomic impacts, where reduced water supply and other effects of drought have negative financial consequences. For these reasons, drought has been defined from at least five different perspectives: meteorological, ecological, agricultural, hydrological, and socioeconomic drought. In this chapter, we explore how these five faces of drought are expressed in Hawai‘i and the USAPI, and how managers operating within one or more these five perspectives address drought-related stressors to their systems. Not all droughts are the same, varying with respect to duration, frequency, extent, and severity. For example, the region receives severe episodic droughts during which an area will have little or no rainfall for months, even in areas that normally have no dry season. El Niño events fall into this category, and these moderate frequency events are typically responsible for shorter-lived but intense drought events that affect large areas. Drought can also be expressed as infrequent but long duration events of moderate severity, or long-term rainfall decline where the baseline condition appears to be changing when examined on longer time scales. From the perspective of the manager, understanding drought duration, frequency, extent, and severity is critical to understanding the duration, frequency, extent and severity of the response. For example, how an agency responds to El Niño events, with a focus on large-scale but short-lived emergency response campaigns, may differ from how an agency responds to baseline change or an increase in the frequency of extended dry periods, with a focus on longer-lived institutional, infrastructure, and personnel responses. The legislative and policy environment will also respond differently to different types of drought. Understanding and characterizing meteorological drought relies on a long-term network of climate stations. Rainfall has been extensively monitored in Hawai‘i since the early 1900s owing to the expansion of plantation agriculture (Giambelluca and others 1986), while rainfall monitoring for most of the USAPI began in earnest after World War II (Polhemus 2017). Due to prevailing winds, most of Hawai‘i’s land area is characterized by a wet season from November to April and a dry season from May to October. However, important dynamic features affect climate systems of the Pacific. For example, due to their tropical location, rainfall patterns in both Hawai‘i and the USAPI are strongly controlled by large-scale modes of climate variability, including the El Niño-Southern Oscillation (ENSO). El Niño events are typically associated with drier than average winter wet seasons and wetter dry seasons, while La Niña events often result in a wetter than average wet season and a drier dry season. Many historical drought events have been attributed to El Niño events, which produce atmospheric conditions that are unfavorable for rainfall (Chu 1995). However, not all El Niño events result in drought, and effects differ depending on whether the El Niño is classified as Central Pacific (CP) or Eastern Pacific (EP) (Bai 2017; Polhemus 2017).
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Effects of drought on forests and rangelands in the United States: Translating science into management responses","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"USDA","doi":"10.2737/WO-GTR-98","usgsCitation":"Frazier, A.G., Deenik, J., Fujii, N., Funderburk, G., Giambelluca, T., Giardina, C., Helweg, D., Keener, V., Mair, D., Marra, J., McDaniel, S., Ohye, L., Oki, D.S., Parsons, E., Strauch, A., and Trauernicht, C., 2019, Managing effects of drought in Hawai’i and U.S.-affiliated Pacific Islands: General Technical Report WO-98, 27 p., https://doi.org/10.2737/WO-GTR-98.","productDescription":"27 p.","startPage":"95","endPage":"121","ipdsId":"IP-105580","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science 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Ayron","contributorId":221124,"corporation":false,"usgs":false,"family":"Strauch","given":"Ayron","email":"","affiliations":[{"id":40327,"text":"State of Hawai‘i, Department of Land and Natural Resources, Commission on Water Resource Management","active":true,"usgs":false}],"preferred":false,"id":777063,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Trauernicht, Clay","contributorId":221125,"corporation":false,"usgs":false,"family":"Trauernicht","given":"Clay","email":"","affiliations":[{"id":40329,"text":"University of Hawai‘i at Mānoa, Department of Natural Resources and Environmental Management","active":true,"usgs":false}],"preferred":false,"id":777064,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70208734,"text":"70208734 - 2019 - Frequent use of upland habitats by the endangered Hawaiian stilt (Himantopus mexicanus knudseni)","interactions":[],"lastModifiedDate":"2020-02-27T06:44:37","indexId":"70208734","displayToPublicDate":"2019-12-01T06:43:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Frequent use of upland habitats by the endangered Hawaiian stilt (Himantopus mexicanus knudseni)","docAbstract":"The Hawaiian Stilt, or Ae’o (Himantopus mexicanus knudseni), is an endangered waterbird endemic to the Hawaiian Islands. Loss of suitable wetland habitats due to anthropogenic development is a leading cause for decline, as well as the introduction of non-native predators and invasive wetland plants. This study fitted four Hawaiian Stilts with GPS satellite tags to document their use of wetland and surrounding habitats on Oahu Island. While other Hawaiian waterbirds are largely restricted to wetlands, we detected Hawaiian Stilts using heavily modified upland habitats, including developed areas, undeveloped fields, sports fields, as well as wetland habitats over a 6-month period. Overall, a high use of non-wetland habitat was observed (up to 58%), with significant differences in habitat occupancy among individual stilts and across different times of day. Wetlands were the dominant habitat occupied from morning to early afternoon, but non-wetland habitats were occupied at higher frequencies in the evening and early morning hours. Although only four birds were tracked, the extensive use of non-wetland habitat by these individuals indicates management of non-wetland habitats may be important for the conservation of this subspecies. However, more research is needed to understand how applicable these results are to other stilt popualtions across the Hawaiian Islands, and better understand the potential risks and benefits of these non-wetland habitats to stilt populations.","language":"English","publisher":"BioOne","doi":"10.1675/063.042.0408","usgsCitation":"Kawasaki, M., Hart, P.J., and Paxton, E., 2019, Frequent use of upland habitats by the endangered Hawaiian stilt (Himantopus mexicanus knudseni): Waterbirds, v. 42, no. 4, p. 431-438, https://doi.org/10.1675/063.042.0408.","productDescription":"8 p.","startPage":"431","endPage":"438","ipdsId":"IP-106610","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":437271,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RPU1X1","text":"USGS data release","linkHelpText":"Oahu Island Hawaiian stilt GPS satellite tracking data, 2017-2018"},{"id":372676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"42","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kawasaki, Martha","contributorId":222802,"corporation":false,"usgs":false,"family":"Kawasaki","given":"Martha","email":"","affiliations":[{"id":37485,"text":"University of Hawai‘i - Hilo","active":true,"usgs":false}],"preferred":false,"id":783211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hart, Patrick J.","contributorId":147728,"corporation":false,"usgs":false,"family":"Hart","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":783212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paxton, Eben H. 0000-0001-5578-7689 epaxton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":438,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben H.","email":"epaxton@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":783210,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70182770,"text":"70182770 - 2019 - Assessing North American multimodel ensemble (NMME) seasonal forecast skill to assist in the early warning of hydrometeorological extremes over East Africa","interactions":[],"lastModifiedDate":"2024-05-17T14:50:31.723618","indexId":"70182770","displayToPublicDate":"2019-12-01T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1248,"text":"Climate Dynamics","active":true,"publicationSubtype":{"id":10}},"title":"Assessing North American multimodel ensemble (NMME) seasonal forecast skill to assist in the early warning of hydrometeorological extremes over East Africa","docAbstract":"The skill of North American multimodel ensemble (NMME) seasonal forecasts in East Africa (EA), which encompasses one of the most food and water insecure areas of the world, is evaluated using deterministic, categorical, and probabilistic evaluation methods. The skill is estimated for all three primary growing seasons: March–May (MAM), July–September (JAS), and October–December (OND). It is found that the precipitation forecast skill in this region is generally limited and statistically significant over only a small part of the domain. In the case of MAM (JAS) [OND] season it exceeds the skill of climatological forecasts in parts of equatorial EA (Northern Ethiopia) [equatorial EA] for up to 2 (5) [5] months lead. Temperature forecast skill is generally much higher than precipitation forecast skill (in terms of deterministic and probabilistic skill scores) and statistically significant over a majority of the region. Over the region as a whole, temperature forecasts also exhibit greater reliability than the precipitation forecasts. The NMME ensemble forecasts are found to be more skillful and reliable than the forecast from any individual model. The results also demonstrate that for some seasons (e.g. JAS), the predictability of precipitation signals varies and is higher during certain climate events (e.g. ENSO). Finally, potential room for improvement in forecast skill is identified in some models by comparing homogeneous predictability in individual NMME models with their respective forecast skill.
","language":"English","publisher":"Springer","doi":"10.1007/s00382-016-3296-z","usgsCitation":"Shukla, S., Roberts, J., Hoell. Andrew, Funk, C., Robertson, F.R., and Kirtmann, B., 2019, Assessing North American multimodel ensemble (NMME) seasonal forecast skill to assist in the early warning of hydrometeorological extremes over East Africa: Climate Dynamics, v. 15, no. 12, p. 7411-7427, https://doi.org/10.1007/s00382-016-3296-z.","productDescription":"17 p.","startPage":"7411","endPage":"7427","ipdsId":"IP-069889","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":336787,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"East Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 22,\n -8\n ],\n [\n 52,\n -8\n ],\n [\n 52,\n 23\n ],\n [\n 22,\n 23\n ],\n [\n 22,\n -8\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"12","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-29","publicationStatus":"PW","scienceBaseUri":"58b7eba3e4b01ccd5500bae3","chorus":{"doi":"10.1007/s00382-016-3296-z","url":"http://dx.doi.org/10.1007/s00382-016-3296-z","publisher":"Springer Nature","authors":"Shukla Shraddhanand, Roberts Jason, Hoell Andrew, Funk Christopher C., Robertson Franklin, Kirtman Ben","journalName":"Climate Dynamics","publicationDate":"7/29/2016","auditedOn":"2/15/2017","publiclyAccessibleDate":"7/29/2016"},"contributors":{"authors":[{"text":"Shukla, Shraddhanand","contributorId":145802,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":673688,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberts, Jason B.","contributorId":145808,"corporation":false,"usgs":false,"family":"Roberts","given":"Jason B.","affiliations":[{"id":16239,"text":"NASA Marshall Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":673689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoell. 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Andrew","affiliations":[{"id":13549,"text":"UC Santa Barbara Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":673690,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":673687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robertson, Franklin R.","contributorId":145809,"corporation":false,"usgs":false,"family":"Robertson","given":"Franklin","email":"","middleInitial":"R.","affiliations":[{"id":16239,"text":"NASA Marshall Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":673691,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kirtmann, Benjamin","contributorId":184160,"corporation":false,"usgs":false,"family":"Kirtmann","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":673692,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70214574,"text":"70214574 - 2019 - Wave-current interaction between Hurricane Matthew wave fields and the Gulf Stream","interactions":[],"lastModifiedDate":"2020-09-30T14:08:22.311228","indexId":"70214574","displayToPublicDate":"2019-11-29T09:03:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2426,"text":"Journal of Physical Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Wave-current interaction between Hurricane Matthew wave fields and the Gulf Stream","docAbstract":"Hurricanes interact with the Gulf Stream in the South Atlantic Bight (SAB) through a wide variety of processes, which are crucial to understand for prediction of open-ocean and coastal hazards during storms. However, it remains unclear how waves are modified by large-scale ocean currents under storm conditions, when waves are aligned with the storm-driven circulation and tightly coupled to the overlying wind field. Hurricane Matthew (2016) impacted the US southeast coast, causing extensive coastal change due to large waves and elevated water levels. The hurricane traveled on the continental shelf parallel to the SAB coastline, with the right side of the hurricane directly over the Gulf Stream. Using the Coupled Ocean Atmosphere Wave Sediment Transport Modeling System, we investigate wave-current interaction between Hurricane Matthew and the Gulf Stream. The model simulates ocean currents and waves over a grid encompassing the US east coast, with varied coupling of the hydrodynamic and wave components to isolate the effect of the currents on the waves, and the effect of the Gulf Stream relative to storm-driven circulation. The Gulf Stream modifies the direction of the storm-driven currents beneath the right side of the hurricane. Waves transitioned from following currents that result in wave lengthening, through negative current gradients that result in wave steepening and dissipation. Wave-current interaction over the Gulf Stream modified maximum coastal total water levels, and changed incident wave directions at the coast by up to 20°, with strong implications for the morphodynamic response and stability of the coast to the hurricane.","language":"English","publisher":"American Meteorology Society","doi":"10.1175/JPO-D-19-0124.1","usgsCitation":"Hegermiller, C., Warner, J., Olabarrieta, M., and Sherwood, C.R., 2019, Wave-current interaction between Hurricane Matthew wave fields and the Gulf Stream: Journal of Physical Oceanography, v. 49, no. 11, p. 2883-2900, https://doi.org/10.1175/JPO-D-19-0124.1.","productDescription":"18 p.","startPage":"2883","endPage":"2900","ipdsId":"IP-109198","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459087,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jpo-d-19-0124.1","text":"Publisher Index Page"},{"id":378900,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"East Coast, Gulf Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.12109375,\n 16.97274101999902\n ],\n [\n -78.046875,\n 24.5271348225978\n ],\n [\n -73.47656249999999,\n 36.1733569352216\n ],\n [\n -65.390625,\n 44.213709909702054\n ],\n [\n -68.73046875,\n 46.07323062540835\n ],\n [\n -80.85937499999999,\n 34.016241889667015\n ],\n [\n -92.63671875,\n 32.24997445586331\n ],\n [\n -101.77734374999999,\n 25.799891182088334\n ],\n [\n -97.3828125,\n 19.145168196205297\n ],\n [\n -90.17578124999999,\n 16.29905101458183\n ],\n [\n -89.12109375,\n 16.97274101999902\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hegermiller, Christie 0000-0002-6383-7508","orcid":"https://orcid.org/0000-0002-6383-7508","contributorId":241895,"corporation":false,"usgs":true,"family":"Hegermiller","given":"Christie","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":true,"id":800130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":800131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":211373,"corporation":false,"usgs":false,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":800132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":800133,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215197,"text":"70215197 - 2019 - Separating sea and slow slip signals on the seafloor","interactions":[],"lastModifiedDate":"2020-10-12T13:02:09.265924","indexId":"70215197","displayToPublicDate":"2019-11-29T08:00:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5999,"text":"Journal of Geophysical Research- Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Separating sea and slow slip signals on the seafloor","docAbstract":"Seafloor pressure measurements hold promise for estimating vertical displacements from transient slow slip events on submarine faults. We assess the accuracy of pressure offset estimates that evolve over days to weeks and the confidence with which they may be attributed to tectonic deformation or to the ocean water column. One common approach to resolve this ambiguity assumes water column pressures vary insignificantly over the study region and are represented by stable reference site pressures. Assessing the validity of this assumption requires independent evidence. Correlations between pressures and colocated temperatures collected during the Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip experiment suggest temperatures might provide a useful independent proxy for water column pressures. We compared offsets estimated using several methods, with temperature and other proxies. The use of a temperature proxy was unsuccessful, because seafloor temperatures did not track the seasonal signal that contributes significantly to seafloor pressure changes over the slow slip event period. Regardless of the estimation method, offsets varied within a few cm around some uncertain reference level. Commonly used statistical measures are shown not to be reliable indicators of offset accuracy since offsets contribute minimally to the total variance. Offsets estimated using identical methods but with seafloor pressures simulated using a regional ocean model were larger than those derived from the data but had a similar pattern. Since the model simulates only water column processes, this suggests a significant fraction of the estimated pressure offsets are due to seasonal water column signal and are not of tectonic origin.