San Francisco gartersnakes (Thamnophis sirtalis tetrataenia) are a subspecies of common gartersnakes endemic to the San Francisco Peninsula of northern California. Because of habitat loss and collection for the pet trade, San Francisco gartersnakes were listed as endangered under the precursor to the Federal Endangered Species Act. A population of San Francisco gartersnakes resides at Mindego Ranch, San Mateo County, which is part of the Russian Ridge Open Space Preserve owned and managed by the Midpeninsula Regional Open Space District (MROSD). Because the site contained non-native fishes and American bullfrogs (Lithobates catesbeianus), MROSD implemented management to eliminate or reduce the abundance of these non-native species in 2014. We monitored the population using capture-mark-recapture techniques to document changes in the population during and following management actions. Although drought confounded some aspects of inference about the effects of management, prey and San Francisco gartersnake populations generally increased following draining of Aquatic Feature 3. Continued management of the site to keep invasive aquatic predators from recolonizing or increasing in abundance, as well as vegetation management that promotes heterogeneous grassland/shrubland near wetlands, likely would benefit this population of San Francisco gartersnakes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181063","collaboration":"Prepared in cooperation with the Midpeninsula Regional Open Space District","usgsCitation":"Kim, R., Halstead, B.J., Wylie, G.D., and Casazza, M.L., 2018, Distribution and demography of San Francisco gartersnakes (Thamnophis sirtalis tetrataenia) at Mindego Ranch, Russian Ridge Open Space Preserve, San Mateo County, California: U.S. Geological Survey Open-File Report 2018-1063, 80 p., https://doi.org/10.3133/ofr20181063.","productDescription":"viii, 80 p.","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-093147","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":353746,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1063/coverthb.jpg"},{"id":353747,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1063/ofr20181063.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1063"}],"country":"United States","state":"California","county":"San Mateo","otherGeospatial":"Mindego Ranch, Russian Ridge Open Space Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.25543022155762,\n 37.2960420634488\n ],\n [\n -122.22109794616699,\n 37.2960420634488\n ],\n [\n -122.22109794616699,\n 37.33065186897204\n ],\n [\n -122.25543022155762,\n 37.33065186897204\n ],\n [\n -122.25543022155762,\n 37.2960420634488\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The Bushy Park Reservoir is the principal water supply for 400,000 people in the greater Charleston, South Carolina, area, which includes homes as well as businesses and industries in the Bushy Park Industrial Complex. Charleston Water System and the U.S. Geological Survey conducted a cooperative study during 2013–15 to assess the circulation of Bushy Park Reservoir and its effects on water-quality conditions, specifically, recurring taste-and-odor episodes. This report describes the water-quality data collected for the study that included a combination of discrete water-column sampling at seven locations in the reservoir and longitudinal water-quality profiling surveys of the reservoir and tributaries to characterize the temporal and spatial water-quality dynamics of Bushy Park Reservoir. Water-quality profiling surveys were conducted with an autonomous underwater vehicle equipped with a multiparameter water-quality-sonde bulkhead. Data collected by the autonomous underwater vehicle included water temperature, dissolved oxygen, pH, specific conductance, turbidity, total chlorophyll as fluorescence (estimate of algal biomass), and phycocyanin as fluorescence (estimate of cyanobacteria biomass) data.
Characterization of the water-quality conditions in the reservoir included comparison to established State nutrient guidelines, identification of any spatial and seasonal variation in water-quality conditions and phytoplankton community structures, and assessment of the degree of influence of water-quality conditions related to Foster Creek and Durham Canal inflows, especially during periods of elevated taste-and-odor concentrations. Depth-profile and autonomous underwater vehicle survey data were used to identify areas within the reservoir where greater phytoplankton and cyanobacteria densities were most likely occurring.
Water-quality survey results indicated that Bushy Park Reservoir tended to stratify thermally at a depth of about 20 feet from June to early October. The stratification was limited to the deeper portions of the reservoir near the dam and often dissipated within the reservoir near the CWS intake less than a mile upstream from the dam. Where thermally stratified, a corresponding depletion of dissolved oxygen also occurred at about the same depth and resulted in an anoxic hypolimnion below the 25-foot depth and an increase in specific conductance, likely due to re-mobilized metals and phosphorus under reducing conditions. In general, chlorophyll estimated from fluorescence exhibited some spatial variation, but no strong consistent pattern or “hot spot” was observed. Phycocyanin, estimated from relative fluorescence unit output as blue-green algae cell density, periodically seemed to be greater in the upper portion of the reservoir, but those differences may be attributed to increased turbidity and the potential change in phytoplankton community structure that affects fluorescence. Increased phycocyanin was observed at about the 10-foot depth during the summer months.
A constant production of 2-methylisoborneol (MIB) near the dam and geosmin in the middle and upper portions of the reservoir appears to be occurring during the summer and early fall in the reservoir, but concentrations of these compounds tend to be between 10 and 15 nanograms per liter, which is at the Charleston Water System treatment threshold. At the Bushy Park Reservoir intake, the dominant taste-and-odor compound tended to be MIB, measured at a 2- or 3-to-1 ratio with geosmin during the summer and fall. During springtime episodes, however, when taste-and-odor compound concentrations typically are elevated above the Charleston Water System treatment threshold, the spatial distribution of geosmin concentrations greater than 15 nanograms per liter (28 to 38 nanograms per liter) was best explained by in situ production in the lower portion of the Bushy Park Reservoir near the dam rather than transport from Foster Creek. This pattern seems to indicate a possible shift in phytoplankton communities (or, at least, cyanobacteria communities) from MIB producers to geosmin producers.
The spatial and seasonal assessment of water-quality conditions in Bushy Park Reservoir identified seasonal differences in water chemistry and spatial differences between the upper and lower portions of the reservoir that correspond to the location of elevated geosmin concentrations. On the basis of the spatial and seasonal assessment of actinomycetes concentrations compared to taste-and-odor compound concentrations, cyanobacteria production likely was the dominant source of the taste-and-odor episodes rather than actinomycetes. The lack of spatial and seasonal patterns in actinomycetes concentrations did not correspond to the springtime geosmin concentrations that were elevated above the Charleston Water System treatment threshold in the lower portion of the reservoir. Additionally, actinomycetes concentrations, although ubiquitous, had a median of about 9 and maximum of about 20 colonies per milliliter, which can be considered low for elevated taste-and-odor compound production. Nonetheless, the potential exists for actinomycetes to be a secondary source of taste-and-odor production and could explain some of the ubiquitous occurrence of low-level taste-and-odor production, such as MIB concentrations, observed throughout the summer and early fall months.
When evaluated by biovolume, cyanobacteria were not the dominant phytoplankton group in Bushy Park Reservoir during the study period. Dolichospermum planctonicum (previously Anabaena planktonica ) was the dominant genera of the cyanobacteria group during spring periods. The geosmin-producing genera that were identified in the 2014 and 2015 spring communities in Bushy Park Reservoir were not observed in the 1999 and 2000 algal taxonomic data.
A more robust examination of phytoplankton species was conducted by using a multivariate analysis that identified seasonal changes in phytoplankton community structure. These seasonal phytoplankton communities appeared to be explained by seasonal changes in water chemistry and may be responsible for episodes of taste-and-odor occurrence, especially geosmin. The most probable source of geosmin identified during the study was D. planctonicum.
In a synoptic sampling event during a taste-and-odor episode in April 2015, cyanobacteria, not acinomycetes, also was indicated to be the more prevalent source of the geosmin. Although the Edisto River intake and its associated supply tunnel to the treatment facility had relatively high actinomycetes concentrations (130 and 140 colonies per milliliter, respectively) compared to the Bushy Park intake and tunnel (2 colonies per milliliter), corresponding geosmin concentrations were below 5 nanograms per liter for source water from the Edisto River intake and tunnel. Elevated geosmin concentrations above the Charleston Water System treatment threshold were identified in source waters from the Bushy Park Reservoir. The cyanobacteria community at the sampled sites in April 2015 was statistically similar to the community in the Bushy Park Reservoir in April 2014, when geosmin concentrations also were elevated. The only geosmin-producing genus identified at the Bushy Park intake, however, was D. planctonicum.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185010","collaboration":"Prepared in cooperation with Charleston Water System","usgsCitation":"Conrads, P.A., Journey, C.A., Petkewich, M.D., Lanier, T.H., and Clark, J.M., 2018, Characterization of water quality in Bushy Park Reservoir, South Carolina, 2013–15: U.S. Geological Survey Scientific Investigations Report 2018–5010, 175 p., https://doi.org/10.3133/sir20185010. ","productDescription":"xi, 175 p.","numberOfPages":"192","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087952","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":437934,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z7YOXC","text":"USGS data release","linkHelpText":"Phycocyanin, Velocity, AUV, and Profile Data for William Station Shutdown in Bushy Park Reservoir, South Carolina, 2017"},{"id":353632,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5010/sir20185010.pdf","text":"Report","size":"27.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5010"},{"id":353631,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5010/coverthb.jpg"},{"id":353639,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NG4NVX","text":"USGS data release","description":"USGS data release","linkHelpText":"Water Quality Data for Bushy Park Reservoir, South Carolina 2013–2015"}],"country":"United States","state":"South Carolina","otherGeospatial":"Bushy Park Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.364990234375,\n 32.816132537537115\n ],\n [\n -79.43939208984375,\n 32.816132537537115\n ],\n [\n -79.43939208984375,\n 33.51162942617925\n ],\n [\n -80.364990234375,\n 33.51162942617925\n ],\n [\n -80.364990234375,\n 32.816132537537115\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Altantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Conservation and management decision making in natural resources is challenging due to numerous uncertainties and unknowns, especially relating to understanding system dynamics. Adaptive resource management (ARM) is a formal process to making logical and transparent recurrent decisions when there are uncertainties about system dynamics. Despite wide recognition and calls for implementing adaptive natural resource management, applications remain limited. More common is a reactive approach to decision making, which ignores future system dynamics. This contrasts with ARM, which anticipates future dynamics of ecological process and management actions using a model-based framework. Practitioners may be reluctant to adopt ARM because of the dearth of comparative evaluations between ARM and more common approaches to making decisions. We compared the probability of meeting management objectives when managing a population under both types of decision frameworks, specifically in relation to typical uncertainties and unknowns. We use a population of Sandhill Cranes as our case study. We evaluate each decision process under varying levels of monitoring and ecological uncertainty, where the true underlying population dynamics followed a stochastic age-structured population model with environmentally driven vital rate density dependence. We found that the ARM framework outperformed the currently employed reactive decision framework to manage Sandhill Cranes in meeting the population objective across an array of scenarios. This was even the case when the candidate set of population models contained only naïve representations of the true population process. Under the reactive decision framework, we found little improvement in meeting the population objective even if monitoring uncertainty was eliminated. In contrast, if the population was monitored without error within the ARM framework, the population objective was always maintained, regardless of the population models considered. Contrary to expectation, we found that age-specific optimal harvest decisions are not always necessary to meet a population objective when population dynamics are age structured. Population managers can decrease risks and gain transparency and flexibility in management by adopting an ARM framework. If population monitoring data has high sampling variation and/or limited empirical knowledge is available for constructing mechanistic population models, ARM model sets should consider a range of mechanistic, descriptive, and predictive model types.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1734","usgsCitation":"Gerber, B.D., and Kendall, W.L., 2018, Adaptive management of animal populations with significant unknowns and uncertainties: A case study: Ecological Applications, v. 28, no. 5, p. 1325-1341, https://doi.org/10.1002/eap.1734.","productDescription":"17 p.","startPage":"1325","endPage":"1341","ipdsId":"IP-073120","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":489030,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/nrs_facpubs/84","text":"External Repository"},{"id":394876,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gerber, Brian D.","contributorId":187620,"corporation":false,"usgs":false,"family":"Gerber","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":831785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":831704,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70196508,"text":"ofr20181060 - 2018 - USA National Phenology Network observational data documentation","interactions":[],"lastModifiedDate":"2018-04-25T16:12:08","indexId":"ofr20181060","displayToPublicDate":"2018-04-25T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1060","title":"USA National Phenology Network observational data documentation","docAbstract":"The goals of the USA National Phenology Network (USA-NPN, www.usanpn.org) are to advance science, inform decisions, and communicate and connect with the public regarding phenology and species’ responses to environmental variation and climate change. The USA-NPN seeks to advance the science of phenology and facilitate ecosystem stewardship by providing phenological information freely and openly. To accomplish these goals, the USA-NPN National Coordinating Office (NCO) delivers observational data on plant and animal phenology in several formats, including minimally processed status and intensity datasets and derived phenometrics for individual plants, sites, and regions. This document describes the suite of observational data products delivered by the USA National Phenology Network, covering the period 2009–present for the United States and accessible via the Phenology Observation Portal (http://dx.doi.org/10.5066/F78S4N1V) and via an Application Programming Interface. The data described here have been used in diverse research and management applications, including over 30 publications in fields such as remote sensing, plant evolution, and resource management.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181060","usgsCitation":"Rosemartin, A., Denny, E.G., Gerst, K.L., Marsh, R.L., Posthumus, E.E., Crimmins, T.M., and Weltzin, J.F., 2018, USA National Phenology Network observational data documentation: U.S. Geological Survey Open-File Report 2018–1060, 24 p., https://doi.org/10.3133/ofr20181060.","productDescription":"Report: vi, 24 p.; Appendix tables","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085279","costCenters":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"links":[{"id":353663,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1060/coverthb.jpg"},{"id":353665,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1060/ofr20181060_appendix1tables.zip","text":"Appendix 1 Tables","size":"67 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2018-1080 Appendix 1"},{"id":353664,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1060/ofr20181060.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1080"}],"contact":"Director,
Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Dr., MS 300
Reston, VA 20192
Hurricane Sandy was a large and intense storm with high winds that caused total water levels from combined tides and storm surge to reach 4.0 m in the Atlantic Ocean and 2.5 m in Great South Bay (GSB), a back-barrier bay between Fire Island and Long Island, New York. In this study the impact of the hurricane winds and waves are examined in order to understand the flow of ocean water into the back-barrier bay and water level variations within the bay. To accomplish this goal, a high resolution hurricane wind field is used to drive the coupled Delft3D-SWAN hydrodynamic and wave models over a series of grids with the finest resolution in GSB. The processes that control water levels in the back-barrier bay are investigated by comparing the results of four cases that include: (i) tides only; (ii) tides, winds and waves with no overwash over Fire Island allowed; (iii) tides, winds, waves and limited overwash at the east end of the island; (iv) tides, winds, waves and extensive overwash along the island. The results indicate that strong local wind-driven storm surge along the bay axis had the largest influence on the total water level fluctuations during the hurricane. However, the simulations allowing for overwash have higher correlation with water level observations in GSB and suggest that island overwash provided a significant contribution of ocean water to eastern GSB during the storm. The computations indicate that overwash of 7500–10,000 m3s−1 was approximately the same as the inflow from the ocean through the major existing inlet. Overall, the model results indicate the complex variability in total water levels driven by tides, ocean storm surge, surge from local winds, and overwash that had a significant impact on the circulation in Great South Bay during Hurricane Sandy.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2018.04.003","usgsCitation":"Bennett, V.C., Mulligan, R.P., and Hapke, C.J., 2018, A numerical model investigation of the impacts of Hurricane Sandy on water level variability in Great South Bay, New York: Continental Shelf Research, v. 161, p. 1-11, https://doi.org/10.1016/j.csr.2018.04.003.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-082328","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468811,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2018.04.003","text":"Publisher Index Page"},{"id":353706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Great South Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.7,\n 40.55\n ],\n [\n -72.7,\n 40.55\n ],\n [\n -72.7,\n 40.8\n ],\n [\n -73.7,\n 40.8\n ],\n [\n -73.7,\n 40.55\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"161","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d0e4b0da30c1bfbe52","contributors":{"authors":[{"text":"Bennett, Vanessa C. C.","contributorId":204457,"corporation":false,"usgs":false,"family":"Bennett","given":"Vanessa","email":"","middleInitial":"C. C.","affiliations":[{"id":36943,"text":"Queens University","active":true,"usgs":false}],"preferred":false,"id":734015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mulligan, Ryan P.","contributorId":194423,"corporation":false,"usgs":false,"family":"Mulligan","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":35723,"text":"Queen's University - Kingston, Ontario","active":true,"usgs":false}],"preferred":false,"id":734016,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":734014,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196693,"text":"70196693 - 2018 - Remote measurement of canopy water content in giant sequoias (Sequoiadendron giganteum) during drought","interactions":[],"lastModifiedDate":"2018-04-25T10:42:11","indexId":"70196693","displayToPublicDate":"2018-04-25T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Remote measurement of canopy water content in giant sequoias (Sequoiadendron giganteum) during drought","title":"Remote measurement of canopy water content in giant sequoias (Sequoiadendron giganteum) during drought","docAbstract":"California experienced severe drought from 2012 to 2016, and there were visible changes in the forest canopy throughout the State. In 2014, unprecedented foliage dieback was recorded in giant sequoia (Sequoiadendron giganteum) trees in Sequoia National Park, in the southern California Sierra Nevada mountains. Although visible changes in sequoia canopies can be recorded, biochemical and physiological responses to drought stress in giant sequoia canopies are not well understood. Ground-based measurements provide insight into the mechanisms of drought responses in trees, but are often limited to few individuals, especially in trees of tall stature such as giant sequoia. Recent studies demonstrate that remotely measured forest canopy water content (CWC) is a general indicator of canopy response to drought, but the underpinning leaf- to canopy-level causes of observed variation in CWC remain poorly understood. We combined field and airborne remote sensing measurements taken in 2015 and 2016 to assess the biophysical responses of giant sequoias to drought. In 49 study trees, CWC was related to leaf water potential, but not to the other foliar traits, suggesting that changes in CWC were made at whole-canopy rather than leaf scales. We found a non-random, spatially varying pattern in mapped CWC, with lower CWC values at lower elevation and along the outer edges of the groves. This pattern was also observed in empirical measurements of foliage dieback from the ground, and in mapped CWC across multiple sequoia groves in this region, supporting the hypothesis that drought stress is expressed in canopy-level changes in giant sequoias. The fact that we can clearly detect a relationship between CWC and foliage dieback, even without taking into account prior variability or new leaf growth, strongly suggests that remotely sensed CWC, and changes in CWC, are a useful measure of water stress in giant sequoia, and valuable for assessing and managing these iconic forests in drought.
The Oregon Department of Transportation (ODOT) and other state departments of transportation need quantitative information about the percentages of different land cover categories above any given stream crossing in the state to assess and address roadway contributions to water-quality impairments and resulting total maximum daily loads. The U.S. Geological Survey, in cooperation with ODOT and the FHWA, added roadway and land cover information to the online StreamStats application to facilitate analysis of stormwater runoff contributions from different land covers. Analysis of 25 delineated basins with drainage areas of about 100 mi2 indicates the diversity of land covers in the Willamette Valley, Oregon. On average, agricultural, developed, and undeveloped land covers comprise 15%, 2.3%, and 82% of these basin areas. On average, these basins contained about 10 mi of state highways and 222 mi of non-state roads. The Stochastic Empirical Loading and Dilution Model was used with available water-quality data to simulate long-term yields of total phosphorus from highways, non-highway roadways, and agricultural, developed, and undeveloped areas. These yields were applied to land cover areas obtained from StreamStats for the Willamette River above Wilsonville, Oregon. This analysis indicated that highway yields were larger than yields from other land covers because highway runoff concentrations were higher than other land covers and the highway is fully impervious. However, the total highway area was a fraction of the other land covers. Accordingly, highway runoff mitigation measures can be effective for managing water quality locally, they may have limited effect on achieving basin-wide stormwater reduction goals.
Data from a long-term capture-recapture program were used to assess the status and dynamics of populations of two long-lived, federally endangered catostomids in Upper Klamath Lake, Oregon. Lost River suckers (LRS; Deltistes luxatus) and shortnose suckers (SNS; Chasmistes brevirostris) have been captured and tagged with passive integrated transponder (PIT) tags during their spawning migrations in each year since 1995. In addition, beginning in 2005, individuals that had been previously PIT-tagged were re-encountered on remote underwater antennas deployed throughout sucker spawning areas. Captures and remote encounters during the spawning season in spring 2016 were incorporated into capture-recapture analyses of population dynamics.
Cormack-Jolly-Seber (CJS) open population capture-recapture models were used to estimate annual survival probabilities, and a reverse-time analog of the CJS model was used to estimate recruitment of new individuals into the spawning populations. In addition, data on the size composition of captured fish were examined to provide corroborating evidence of recruitment. Model estimates of survival and recruitment were used to derive estimates of changes in population size over time and to determine the status of the populations through 2015. Separate analyses were done for each species and also for each subpopulation of LRS. Shortnose suckers and one subpopulation of LRS migrate into tributary rivers to spawn, whereas the other LRS subpopulation spawns at groundwater upwelling areas along the eastern shoreline of the lake.
Capture-recapture analyses indicated that with a few exceptions, the survival of males and females in both Lost River sucker subpopulations was high (greater than 0.88) from 1999 to 2015. Survival was notably lower for males from the river in 2000, 2006, and 2012, and for the shoreline areas in 2002. From 2001 to 2015, the abundance of males in the lakeshore spawning subpopulation decreased by at least 64 percent and the abundance of females decreased by at least 56 percent. Capture-recapture models suggested that the abundance of both sexes in the river spawning subpopulation of LRS had increased substantially since 2006; increases were mostly due to large estimated recruitment events in 2006 and 2008. We know that the estimates in 2006 are substantially biased in favor of recruitment because of a sampling issue. We are skeptical of the magnitude of recruitment indicated by the 2008 estimates as well because (1) few small individuals that would indicate the presence of new recruits were captured in that year, and (2) recapture probabilities in recruitment models based on just physical recaptures of fish were lower than desired for robust inferences from capture-recapture models. If we assume instead that little or no recruitment occurred for this subpopulation, the abundance of both sexes in the river spawning subpopulation likely has decreased at rates similar to the rates for the lakeshore spawning subpopulation from 2002 to 2015.
Shortnose suckers experienced lower and more variable annual survival than either LRS subpopulation. Annual survival of both sexes was relatively low in 2003, 2004, 2010, and 2012. In addition, female survival was low in 1999 and 2000 while male survival was low in 2002. Survival estimate precision in early years of the study; however, are poor. Capture-recapture models and size composition data indicate that recruitment of new individuals into the SNS spawning population was trivial from 2001 to 2005. Models indicate that more than 10 percent of the population was new recruits in a number of more recent years. As a result, capture-recapture modeling suggests that the abundance of adult spawning SNS was relatively stable from 2006 to 2010. We are skeptical of the estimated recruitment in 2006 because of the known sampling issue. We also are skeptical of the estimated recruitment in other recent years because few small individuals that would indicate the presence of new recruits were captured in any of those years, and recapture probabilities in recruitment models were low. The best-case scenario for SNS, based on capture-recapture recruitment modeling, indicates that the abundance of males in the spawning population decreased by 78 percent and the abundance of females decreased by 77 percent from 2001 to 2015. Decreases in abundance for both sexes are likely greater than these estimates indicate.
Despite relatively high survival in most years, we conclude that both species have experienced substantial decreases in the abundance of spawning adults because losses from mortality have not been balanced by recruitment of new individuals. Although capture-recapture data indicate substantial recruitment of new individuals into the spawning populations for SNS and river spawning LRS in some years, size data do not corroborate these estimates. As a result, the status of the endangered sucker populations in Upper Klamath Lake remains distressed, especially for SNS. Our monitoring program provides a robust platform for estimating vital population parameters, evaluating the status of the populations, and assessing the effectiveness of conservation and recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181064","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., Janney, E.C., Hayes, B.S., and Harris, A.C., 2018, Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2017: U.S. Geological Survey Open-File Report 2018-1064, 31 p., https://doi.org/10.3133/ofr20181064.","productDescription":"iv, 31 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-096959","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":437938,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97K04NO","text":"USGS data release","linkHelpText":"Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2023"},{"id":353417,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1064/coverthb.jpg"},{"id":353418,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1064/ofr20181064.pdf","text":"Report","size":"905 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1064"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.10067749023438,\n 42.21936476344714\n ],\n [\n -121.79992675781249,\n 42.21936476344714\n ],\n [\n -121.79992675781249,\n 42.61981257367216\n ],\n [\n -122.10067749023438,\n 42.61981257367216\n ],\n [\n -122.10067749023438,\n 42.21936476344714\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
Over regions where snow-melt runoff substantially contributes to winter-spring streamflows, warming can accelerate snow melt and reduce dry-season streamflows. However, conclusive detection of changes and attribution to anthropogenic forcing is hindered by brevity of observational records, model uncertainty, and uncertainty concerning internal variability. In this study, a detection/attribution of changes in mid-latitude North American winter-spring streamflow timing is examined using nine global climate models under multiple forcing scenarios. In this study, robustness across models, start/end dates for trends, and assumptions about internal variability is evaluated. Marginal evidence for an emerging detectable anthropogenic influence (according to four or five of nine models) is found in the north-central U.S., where winter-spring streamflows have been coming earlier. Weaker indications of detectable anthropogenic influence (three of nine models) are found in the mountainous western U.S./southwestern Canada and in extreme northeastern U.S./Canadian Maritimes. In the former region, a recent shift toward later streamflows has rendered the full-record trend toward earlier streamflows only marginally significant, with possible implications for previously published climate change detection findings for streamflow timing in this region. In the latter region, no forced model shows as large a shift toward earlier streamflow timing as the detectable observed shift. In other (including warm, snow-free) regions, observed trends are typically not detectable, although in the U.S. central plains we find detectable delays in streamflow, which are inconsistent with forced model experiments.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JCLI-D-17-0813.1","usgsCitation":"Kam, J., Knutson, T.R., and Milly, P.C., 2018, Climate model assessment of changes in winter-spring streamflow timing over North America: Journal of Climate, v. 31, p. 5581-5593, https://doi.org/10.1175/JCLI-D-17-0813.1.","productDescription":"13 p.","startPage":"5581","endPage":"5593","ipdsId":"IP-085825","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jcli-d-17-0813.1","text":"Publisher Index Page"},{"id":353675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d1e4b0da30c1bfbe60","contributors":{"authors":[{"text":"Kam, Jonghun 0000-0002-7967-7705","orcid":"https://orcid.org/0000-0002-7967-7705","contributorId":203859,"corporation":false,"usgs":false,"family":"Kam","given":"Jonghun","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":733933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knutson, Thomas R.","contributorId":204440,"corporation":false,"usgs":false,"family":"Knutson","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":36939,"text":"Geophysical Fluid Dynamics Laboratory/NOAA, Princeton, NJ, 08540","active":true,"usgs":false}],"preferred":false,"id":733934,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Milly, Paul C. D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":176836,"corporation":false,"usgs":true,"family":"Milly","given":"Paul","email":"cmilly@usgs.gov","middleInitial":"C. D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":false,"id":733932,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196680,"text":"70196680 - 2018 - The role of the upper tidal estuary in wetland blue carbon storage and flux","interactions":[],"lastModifiedDate":"2018-06-12T13:51:35","indexId":"70196680","displayToPublicDate":"2018-04-24T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"The role of the upper tidal estuary in wetland blue carbon storage and flux","docAbstract":"Carbon (C) standing stocks, C mass balance, and soil C burial in tidal freshwater forested wetlands (TFFW) and TFFW transitioning to low‐salinity marshes along the upper estuary are not typically included in “blue carbon” accounting, but may represent a significant C sink. Results from two salinity transects along the tidal Waccamaw and Savannah rivers of the US Atlantic Coast show total C standing stocks were 321‐1264 Mg C ha‐1 among all sites, generally shifting to greater soil storage as salinity increased. Carbon mass balance inputs (litterfall, woody growth, herbaceous growth, root growth, surface accumulation) minus C outputs (surface litter and root decomposition, gaseous C) over a period of up to 11 years were 340‐900 g C m‐2 yr‐1. Soil C burial was variable (7‐337 g C m‐2 yr‐1), and lateral C export was estimated as C mass balance minus soil C burial as 267‐849 g C m‐2yr‐1. This represents a large amount of C export to support aquatic biogeochemical transformations. Despite reduced C persistence within emergent vegetation, decomposition of organic matter, and higher lateral C export, total C storage increased as forests converted to marsh with salinization. These tidal river wetlands exhibited high N mineralization in salinity‐stressed forested sites and considerable P mineralization in low salinity marshes. Large C standing stocks and rates of C sequestration suggest that TFFW and oligohaline marshes are considerably important globally to coastal C dynamics and in facilitating energy transformations in areas of the world in which they occur.
","language":"English","publisher":"AGU","doi":"10.1029/2018GB005897","usgsCitation":"Krauss, K.W., Noe, G.B., Duberstein, J., Conner, W.H., Stagg, C.L., Cormier, N., Jones, M.C., Bernhardt, C.E., Lockaby, B.G., From, A.S., Doyle, T.W., Day, R.H., Ensign, S., Pierfelice, K.N., Hupp, C.R., Chow, A.T., and Whitbeck, J., 2018, The role of the upper tidal estuary in wetland blue carbon storage and flux: Global Biogeochemical Cycles, v. 32, no. 5, p. 817-839, https://doi.org/10.1029/2018GB005897.","productDescription":"23 p.","startPage":"817","endPage":"839","ipdsId":"IP-091703","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468813,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gb005897","text":"Publisher Index Page"},{"id":437936,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TM7930","text":"USGS data release","linkHelpText":"Carbon budget assessment of tidal freshwater forested wetland and oligohaline marsh ecosystems along the Waccamaw and Savannah rivers, U.S.A. (2005-2016)"},{"id":437935,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73T9FCJ","text":"USGS data release","linkHelpText":"Organic matter decomposition along coastal wetland landscape gradient from tidal freshwater forested wetland to oligohaline marsh in Southeastern U.S.A. (2010-2011)"},{"id":353677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.5,\n 33.1667\n ],\n [\n -78.8333,\n 33.1667\n ],\n [\n -78.8333,\n 33.8333\n ],\n [\n -79.5,\n 33.8333\n ],\n [\n -79.5,\n 33.1667\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.25,\n 32\n ],\n [\n -80.80307006835938,\n 32\n ],\n [\n -80.80307006835938,\n 32.3333\n ],\n [\n -81.25,\n 32.3333\n ],\n [\n -81.25,\n 32\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-16","publicationStatus":"PW","scienceBaseUri":"5afee6d1e4b0da30c1bfbe5c","contributors":{"authors":[{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":733937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory B. gnoe@usgs.gov","contributorId":131138,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":733938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duberstein, Jamie A.","contributorId":91007,"corporation":false,"usgs":false,"family":"Duberstein","given":"Jamie A.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":733939,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conner, William H.","contributorId":79376,"corporation":false,"usgs":false,"family":"Conner","given":"William","email":"","middleInitial":"H.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":733940,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stagg, Camille L. 0000-0002-1125-7253 staggc@usgs.gov","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":4111,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","email":"staggc@usgs.gov","middleInitial":"L.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":733941,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cormier, Nicole 0000-0003-2453-9900 cormiern@usgs.gov","orcid":"https://orcid.org/0000-0003-2453-9900","contributorId":4262,"corporation":false,"usgs":true,"family":"Cormier","given":"Nicole","email":"cormiern@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":733942,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Miriam C. 0000-0002-6650-7619 miriamjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":4056,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","email":"miriamjones@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":733943,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bernhardt, Christopher E. 0000-0003-0082-4731 cbernhardt@usgs.gov","orcid":"https://orcid.org/0000-0003-0082-4731","contributorId":2131,"corporation":false,"usgs":true,"family":"Bernhardt","given":"Christopher","email":"cbernhardt@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":733944,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lockaby, B. Graeme","contributorId":28510,"corporation":false,"usgs":true,"family":"Lockaby","given":"B.","email":"","middleInitial":"Graeme","affiliations":[],"preferred":false,"id":733945,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"From, Andrew S. 0000-0002-6543-2627 froma@usgs.gov","orcid":"https://orcid.org/0000-0002-6543-2627","contributorId":5038,"corporation":false,"usgs":true,"family":"From","given":"Andrew","email":"froma@usgs.gov","middleInitial":"S.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":733946,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Doyle, Thomas W. 0000-0001-5754-0671 doylet@usgs.gov","orcid":"https://orcid.org/0000-0001-5754-0671","contributorId":703,"corporation":false,"usgs":true,"family":"Doyle","given":"Thomas","email":"doylet@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":733947,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Day, Richard H. 0000-0002-5959-7054 dayr@usgs.gov","orcid":"https://orcid.org/0000-0002-5959-7054","contributorId":2427,"corporation":false,"usgs":true,"family":"Day","given":"Richard","email":"dayr@usgs.gov","middleInitial":"H.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":733948,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ensign, Scott H.","contributorId":81397,"corporation":false,"usgs":true,"family":"Ensign","given":"Scott H.","affiliations":[],"preferred":false,"id":733949,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Pierfelice, Katherine N.","contributorId":204443,"corporation":false,"usgs":false,"family":"Pierfelice","given":"Katherine","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":733950,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":733951,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Chow, Alex T.","contributorId":204442,"corporation":false,"usgs":false,"family":"Chow","given":"Alex","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":733952,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Whitbeck, Julie L.","contributorId":6698,"corporation":false,"usgs":true,"family":"Whitbeck","given":"Julie L.","affiliations":[],"preferred":false,"id":733953,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70196676,"text":"70196676 - 2018 - Rediscovery of the type series of the Acadian Masked Shrew, Sorex acadicus Gilpin, 1865 (Mammalia: Soricidae), with the designation of a neotype and a reevaluation of its taxonomic status","interactions":[],"lastModifiedDate":"2018-04-24T13:16:17","indexId":"70196676","displayToPublicDate":"2018-04-24T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3147,"text":"Proceedings of the Biological Society of Washington","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Rediscovery of the type series of the Acadian Masked Shrew, Sorex acadicus Gilpin, 1865 (Mammalia: Soricidae), with the designation of a neotype and a reevaluation of its taxonomic status","title":"Rediscovery of the type series of the Acadian Masked Shrew, Sorex acadicus Gilpin, 1865 (Mammalia: Soricidae), with the designation of a neotype and a reevaluation of its taxonomic status","docAbstract":"The name Sorex acadicus Gilpin, 1865 is currently recognized as the valid name for the Nova Scotian subspecies of the masked shrew, S. cinereus Kerr, 1792 (Mammalia: Soricidae), but a holotype for the taxon was never designated, and the location of the type series has been a mystery. The authority for this species, John Bernard Gilpin, was associated with the Nova Scotia Museum, Halifax, NS, but that institution has no Gilpin specimens in its possession, and I could find no record of Gilpin shrews in any other Canadian Museum. I recently discovered a series of Gilpin specimens in the Mammal Collection of the National Museum of Natural History, Washington, DC (USNM), some of which may have been part of the original type series of S. acadicus, and I show that these specimens best represent Gilpin's concept of the taxon. From this series, I designate a neotype for S. acadicus. I also evaluate the distinctiveness of Nova Scotian S. c. acadicus compared with S. c. cinereus from Maine, New Brunswick, and New Hampshire and determine that S. acadicus should be considered a junior synonym of S. c. cinereus.
","language":"English","publisher":"Biological Society of Washington","doi":"10.2988/17-00022","usgsCitation":"Woodman, N., 2018, Rediscovery of the type series of the Acadian Masked Shrew, Sorex acadicus Gilpin, 1865 (Mammalia: Soricidae), with the designation of a neotype and a reevaluation of its taxonomic status: Proceedings of the Biological Society of Washington, v. 131, no. 1, p. 111-131, https://doi.org/10.2988/17-00022.","productDescription":"21 p.","startPage":"111","endPage":"131","ipdsId":"IP-095646","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":353678,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"131","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d1e4b0da30c1bfbe5e","contributors":{"authors":[{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":733936,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70196559,"text":"sir20185001 - 2018 - Assessment of dissolved-selenium concentrations and loads in the lower Gunnison River Basin, Colorado, as part of the Selenium Management Program, from 2011 to 2016","interactions":[],"lastModifiedDate":"2018-06-06T13:10:09","indexId":"sir20185001","displayToPublicDate":"2018-04-23T11:40:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5001","title":"Assessment of dissolved-selenium concentrations and loads in the lower Gunnison River Basin, Colorado, as part of the Selenium Management Program, from 2011 to 2016","docAbstract":"The Gunnison Basin Selenium Management Program implemented a water-quality monitoring network in 2011 in the lower Gunnison River Basin in Colorado. Selenium is a trace element that bioaccumulates in aquatic food chains and can cause reproductive failure, deformities, and other harmful effects. This report presents the percentile values of selenium because regulatory agencies in Colorado make decisions based on the U.S. Environmental Protection Agency (EPA) Clean Water Act Section 303(d) that uses percentile values of concentration. Also presented are dissolved-selenium loads at 18 sites in the lower Gunnison River Basin for water years (WYs) 2011–2016 (October 1, 2010, through September 30, 2016). Annual dissolved-selenium loads were calculated for five sites with continuous U.S. Geological Survey (USGS) streamflow-gaging stations. Annual dissolved-selenium loads for WY 2011 through WY 2016 ranged from 179 and 391 pounds (lb) at Uncompahgre River at Colona to 11,100 and 17,300 lb at Gunnison River near Grand Junction (herein called Whitewater), respectively.
Instantaneous loads were calculated for five sites with continuous U.S. Geological Survey (USGS) streamflow-gaging stations and 13 ancillary sites where discrete water-quality sampling also took place, using discrete water-quality samples and the associated discharge measurements collected during the period. Median instantaneous loads ranged from 0.01 pound per day (lb/d) at Smith Fork near Lazear to 33.0 lb/d at Whitewater. Mean instantaneous loads ranged from 0.06 lb/d at Smith Fork near Lazear to 36.2 lb/d at Whitewater. Most tributary sites in the basin had a median instantaneous dissolved-selenium load of less than 20.0 lb/day. In general, dissolved-selenium loads at Gunnison River main-stem sites showed an increase from upstream to downstream.
The State of Colorado water-quality standard for dissolved selenium of 4.6 micrograms per liter (µg/L) was compared to the 85th percentiles for dissolved selenium at selected sites. Annual 85th percentiles for dissolved selenium were calculated for the five core sites having USGS streamflow-gaging stations using estimated dissolved-selenium concentrations from linear regression models. The 85th-percentile concentrations for WYs 2011–2016 based on this method ranged from 0.62 µg/L and 1.1µg/L at Uncompahgre River at Colona to 12.1 µg/L and 18.7 µg/L at Uncompahgre River at Delta.
The 85th percentiles for dissolved selenium also were calculated for sites with sufficient data using water-quality samples collected during WYs 2011–2016. The annual 85th-percentile concentrations based on the discrete samples ranged from 0.16 µg/L and 0.17 µg/L at Gunnison River below Gunnison Tunnel to 62.2 µg/L and 170 µg/L at Loutzenhizer Arroyo at North River Road.
A trend analysis was completed for Whitewater to determine if dissolved-selenium loads are increasing or decreasing. The trend analysis indicates a decrease of 9,100 lb from WY 1986 to WY 2016, a 40.8 percent reduction during the time period. The trend analysis for the annual dissolved-selenium load for WY 1994 to WY 2016 indicates a decrease of 6,300 lb per year, or 33.3 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185001","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Henneberg, M.F., 2018, Assessment of dissolved-selenium concentrations and loads in the lower Gunnison River Basin, Colorado, as part of the Selenium Management Program, from 2011 to 2016: U.S. Geological Survey Scientific Investigations Report 2018–5001, 23 p., https://doi.org/10.3133/ofr20185001.","productDescription":"v, 23 p.","numberOfPages":"33","onlineOnly":"Y","ipdsId":"IP-090932","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":353466,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5001/coverthb.jpg"},{"id":353467,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5001/sir20185001.pdf","text":"Report","size":"2.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5001"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.5,\n 38\n ],\n [\n -107.25,\n 38\n ],\n [\n -107.25,\n 39.25\n ],\n [\n -108.5,\n 39.25\n ],\n [\n -108.5,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
Direct covariance observations of the mean flow Reynolds stress and sonar images of the seafloor collected on a wave‐exposed inner continental shelf demonstrate that the drag exerted by the seabed on the overlying flow is consistent with boundary layer models for wave‐current interaction, provided that the orientation and anisotropy of the bed roughness are appropriately quantified. Large spatial and temporal variations in drag result from nonequilibrium ripple dynamics, ripple anisotropy, and the orientation of the ripples relative to the current. At a location in coarse sand characterized by large two‐dimensional orbital ripples, the observed drag shows a strong dependence on the relative orientation of the mean current to the ripple crests. At a contrasting location in fine sand, where more isotropic sub‐orbital ripples are observed, the sensitivity of the current to the orientation of the ripples is reduced. Further, at the coarse site under conditions when the currents are parallel to the ripple crests and the wave orbital diameter is smaller than the wavelength of the relic orbital ripples, the flow becomes hydraulically smooth. This transition is not observed at the fine site, where the observed wave orbital diameter is always greater than the wavelength of the observed sub‐orbital ripples. Paradoxically, the dominant along‐shelf flows often experience lower drag at the coarse site than at the fine site, despite the larger ripples, highlighting the complex dynamics controlling drag in wave‐exposed environments with heterogeneous roughness.
","language":"English","publisher":"AGU","doi":"10.1002/2017JC013252","usgsCitation":"Scully, M., Trowbridge, J., Sherwood, C.R., Jones, K.R., and Traykovski, P.A., 2018, Direct measurements of mean Reynolds stress and ripple roughness in the presence of energetic forcing by surface waves: Journal of Geophysical Research C: Oceans, v. 123, no. 4, p. 2494-2512, https://doi.org/10.1002/2017JC013252.","productDescription":"19 p.","startPage":"2494","endPage":"2512","ipdsId":"IP-088590","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468815,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2017jc013252","text":"External Repository"},{"id":353643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"4","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-10","publicationStatus":"PW","scienceBaseUri":"5afee6d3e4b0da30c1bfbe76","contributors":{"authors":[{"text":"Scully, Malcolm","contributorId":174993,"corporation":false,"usgs":false,"family":"Scully","given":"Malcolm","email":"","affiliations":[],"preferred":false,"id":733829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trowbridge, John","contributorId":174994,"corporation":false,"usgs":false,"family":"Trowbridge","given":"John","email":"","affiliations":[],"preferred":false,"id":733830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":733828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Katie R. 0000-0003-3373-3924","orcid":"https://orcid.org/0000-0003-3373-3924","contributorId":204379,"corporation":false,"usgs":false,"family":"Jones","given":"Katie","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":733831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Traykovski, Peter A. 0000-0002-8163-6857","orcid":"https://orcid.org/0000-0002-8163-6857","contributorId":69487,"corporation":false,"usgs":false,"family":"Traykovski","given":"Peter","email":"","middleInitial":"A.","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":733832,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196644,"text":"70196644 - 2018 - Establishment of the exotic invasive Cuban treefrog (Osteopilus septentrionalis) in Louisiana","interactions":[],"lastModifiedDate":"2018-09-20T16:33:13","indexId":"70196644","displayToPublicDate":"2018-04-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Establishment of the exotic invasive Cuban treefrog (Osteopilus septentrionalis) in Louisiana","title":"Establishment of the exotic invasive Cuban treefrog (Osteopilus septentrionalis) in Louisiana","docAbstract":"The Cuban treefrog, Osteopilus septentrionalis, is native to Cuba, the Bahamas, and the Cayman Islands, and is invasive in areas where it has been introduced and established in the Caribbean as well as Florida. Despite repeated occurrences in several states over many years, it was not believed that Cuban treefrogs had successfully established outside of Florida in the mainland United States. From mid-September to mid-November 2017, we captured and removed 367 Cuban treefrogs in just four surveys in New Orleans, Louisiana. The impacts of this population on native treefrogs in this area is unknown but possibly severe as indicated by the paucity of observations of native treefrogs during our surveys. Eradication of this seemingly established population is improbable, but continued surveys will facilitate learning about the ecology and genetics of this novel population.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-018-1732-1","usgsCitation":"Glorioso, B.M., Waddle, J.H., Muse, L.J., Jennings, N.D., Litton, M., Hamilton, J., Gergen, S., and Heckard, D., 2018, Establishment of the exotic invasive Cuban treefrog (Osteopilus septentrionalis) in Louisiana: Biological Invasions, v. 20, no. 10, p. 2707-2713, https://doi.org/10.1007/s10530-018-1732-1.","productDescription":"7 p.","startPage":"2707","endPage":"2713","ipdsId":"IP-093682","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":437939,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TM79B4","text":"USGS data release","linkHelpText":"Body measurements of the exotic invasive Cuban treefrog (Osteopilus septentrionalis) in Louisiana"},{"id":353668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","city":"New Orleans","otherGeospatial":"Audubon Zoo","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.13591289520264,\n 29.915178359464193\n ],\n [\n -90.12042045593262,\n 29.915178359464193\n ],\n [\n -90.12042045593262,\n 29.93622992067419\n ],\n [\n -90.13591289520264,\n 29.93622992067419\n ],\n [\n -90.13591289520264,\n 29.915178359464193\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"10","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-21","publicationStatus":"PW","scienceBaseUri":"5afee6d3e4b0da30c1bfbe6c","contributors":{"authors":[{"text":"Glorioso, Brad M. 0000-0002-5400-7414 gloriosob@usgs.gov","orcid":"https://orcid.org/0000-0002-5400-7414","contributorId":4241,"corporation":false,"usgs":true,"family":"Glorioso","given":"Brad","email":"gloriosob@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":733892,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waddle, J. Hardin 0000-0003-1940-2133 waddleh@usgs.gov","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":138953,"corporation":false,"usgs":true,"family":"Waddle","given":"J.","email":"waddleh@usgs.gov","middleInitial":"Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":733893,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muse, Lindy J.","contributorId":172438,"corporation":false,"usgs":false,"family":"Muse","given":"Lindy","email":"","middleInitial":"J.","affiliations":[{"id":27041,"text":"Cherokee at USGS-WARC Lafayette","active":true,"usgs":false}],"preferred":false,"id":733894,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jennings, Nicole D.","contributorId":204399,"corporation":false,"usgs":false,"family":"Jennings","given":"Nicole","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":733895,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Litton, Melanie","contributorId":204400,"corporation":false,"usgs":false,"family":"Litton","given":"Melanie","email":"","affiliations":[{"id":36933,"text":"Audubon Nature Institute","active":true,"usgs":false}],"preferred":false,"id":733896,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hamilton, Joel","contributorId":204401,"corporation":false,"usgs":false,"family":"Hamilton","given":"Joel","email":"","affiliations":[{"id":36933,"text":"Audubon Nature Institute","active":true,"usgs":false}],"preferred":false,"id":733897,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gergen, Steven","contributorId":204402,"corporation":false,"usgs":false,"family":"Gergen","given":"Steven","email":"","affiliations":[{"id":36933,"text":"Audubon Nature Institute","active":true,"usgs":false}],"preferred":false,"id":733898,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Heckard, David","contributorId":204403,"corporation":false,"usgs":false,"family":"Heckard","given":"David","email":"","affiliations":[{"id":36934,"text":"Living Desert Zoo & Gardens State Park","active":true,"usgs":false}],"preferred":false,"id":733899,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196635,"text":"70196635 - 2018 - Natural hazards in Goma and the surrounding villages, East African Rift System","interactions":[],"lastModifiedDate":"2018-07-13T13:20:40","indexId":"70196635","displayToPublicDate":"2018-04-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Natural hazards in Goma and the surrounding villages, East African Rift System","docAbstract":"The city of Goma and its surrounding villages (Democratic Republic of the Congo, DRC) are among the world’s most densely populated regions strongly affected by volcanic hazards. In 2002, Nyiragongo volcano erupted destroying 10–15% of Goma and forced a mass evacuation of the population. Hence, the ~ 1.5 million inhabitants of Goma and Gisenyi (Rwanda) continue to live with the threat of new lava flows and other eruptive hazards from this volcano. The current network of fractures extends from Nyiragongo summit to Goma and continues beneath Lake Kivu, which gives rise to the fear that an eruption could even produce an active vent within the center of Goma or within the lake. A sub-lacustrine volcanic eruption with vents in the floor of the main basin and/or Kabuno Bay of Lake Kivu could potentially release about 300 km3 of carbon dioxide (CO2) and 60 km3 of methane (CH4) dissolved in its deep waters that would be catastrophic to populations (~ 2.5 million people) along the lake shores. For the time being, ongoing hazards related to Nyiragongo and Nyamulagira volcanoes silently kill people and animals, slowly destroy the environment, and seriously harm the health of the population. They include mazuku (CO2-rich locations where people often die of asphyxiation), the highly fluoridated surface and ground waters, and other locally neglected hazards. The volcanic gas plume causes poor air quality and acid rain, which is commonly used for drinking water. Given the large number of people at risk and the continued movement of people to Goma and the surrounding villages, there is an urgent need for a thorough natural hazards assessment in the region. This paper presents a general view of natural hazards in the region around Goma based on field investigations, CO2 measurements in mazuku, and chemistry data for Lake Kivu, rivers and rainwater. The field investigations and the datasets are used in conjunction with extremely rich-historical (1897–2000) and recently published information about Nyiragongo and Nyamulagira volcanoes and Lake Kivu. We also present maps of mazuku and fractures in Goma, describe the volcanic eruption history with hazard assessment and mitigation implications, and consider social realities useful for an integrated risk management strategy.
","language":"English","publisher":"Springer","doi":"10.1007/s11069-018-3288-x","usgsCitation":"Balagizi, C.M., Kies, A., Kasereka, M.M., Tedesco, D., Yalire, M.M., and McCausland, W.A., 2018, Natural hazards in Goma and the surrounding villages, East African Rift System: Natural Hazards, v. 93, no. 1, p. 31-66, https://doi.org/10.1007/s11069-018-3288-x.","productDescription":"36 p.","startPage":"31","endPage":"66","ipdsId":"IP-061455","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":353654,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Democratic Republic of the Congo","city":"Goma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 20.1708984375,\n -5.353521355337321\n ],\n [\n 31.3330078125,\n -5.353521355337321\n ],\n [\n 31.3330078125,\n 6.18424616128059\n ],\n [\n 20.1708984375,\n 6.18424616128059\n ],\n [\n 20.1708984375,\n -5.353521355337321\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"93","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-31","publicationStatus":"PW","scienceBaseUri":"5afee6d3e4b0da30c1bfbe74","contributors":{"authors":[{"text":"Balagizi, Charles M.","contributorId":204381,"corporation":false,"usgs":false,"family":"Balagizi","given":"Charles","email":"","middleInitial":"M.","affiliations":[{"id":36925,"text":"Goma Volcano Observatory","active":true,"usgs":false}],"preferred":false,"id":733837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kies, Antoine","contributorId":204383,"corporation":false,"usgs":false,"family":"Kies","given":"Antoine","email":"","affiliations":[{"id":36926,"text":"University of Luxembourg","active":true,"usgs":false}],"preferred":false,"id":733839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kasereka, Marcellin M.","contributorId":204382,"corporation":false,"usgs":false,"family":"Kasereka","given":"Marcellin","email":"","middleInitial":"M.","affiliations":[{"id":36925,"text":"Goma Volcano Observatory","active":true,"usgs":false}],"preferred":false,"id":733838,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tedesco, Dario","contributorId":204384,"corporation":false,"usgs":false,"family":"Tedesco","given":"Dario","email":"","affiliations":[{"id":36927,"text":"Second University of Naples","active":true,"usgs":false}],"preferred":false,"id":733840,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yalire, Mathieu M.","contributorId":204385,"corporation":false,"usgs":false,"family":"Yalire","given":"Mathieu","email":"","middleInitial":"M.","affiliations":[{"id":36925,"text":"Goma Volcano Observatory","active":true,"usgs":false}],"preferred":false,"id":733841,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCausland, Wendy A. 0000-0002-8683-1440","orcid":"https://orcid.org/0000-0002-8683-1440","contributorId":204380,"corporation":false,"usgs":true,"family":"McCausland","given":"Wendy","email":"","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":733836,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196642,"text":"70196642 - 2018 - Numerical models of pore pressure and stress changes along basement faults due to wastewater injection: Applications to the 2014 Milan, Kansas Earthquake","interactions":[],"lastModifiedDate":"2018-05-21T13:09:45","indexId":"70196642","displayToPublicDate":"2018-04-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Numerical models of pore pressure and stress changes along basement faults due to wastewater injection: Applications to the 2014 Milan, Kansas Earthquake","docAbstract":"We have developed groundwater flow models to explore the possible relationship between wastewater injection and the 12 November 2014 Mw 4.8 Milan, Kansas earthquake. We calculate pore pressure increases in the uppermost crust using a suite of models in which hydraulic properties of the Arbuckle Formation and the Milan earthquake fault zone, the Milan earthquake hypocenter depth, and fault zone geometry are varied. Given pre‐earthquake injection volumes and reasonable hydrogeologic properties, significantly increasing pore pressure at the Milan hypocenter requires that most flow occur through a conductive channel (i.e., the lower Arbuckle and the fault zone) rather than a conductive 3‐D volume. For a range of reasonable lower Arbuckle and fault zone hydraulic parameters, the modeled pore pressure increase at the Milan hypocenter exceeds a minimum triggering threshold of 0.01 MPa at the time of the earthquake. Critical factors include injection into the base of the Arbuckle Formation and proximity of the injection point to a narrow fault damage zone or conductive fracture in the pre‐Cambrian basement with a hydraulic diffusivity of about 3–30 m2/s. The maximum pore pressure increase we obtain at the Milan hypocenter before the earthquake is 0.06 MPa. This suggests that the Milan earthquake occurred on a fault segment that was critically stressed prior to significant wastewater injection in the area. Given continued wastewater injection into the upper Arbuckle in the Milan region, assessment of the middle Arbuckle as a hydraulic barrier remains an important research priority.
","language":"English","publisher":"AGU","doi":"10.1002/2017GC007194","usgsCitation":"Hearn, E.H., Koltermann, C., and Rubinstein, J.R., 2018, Numerical models of pore pressure and stress changes along basement faults due to wastewater injection: Applications to the 2014 Milan, Kansas Earthquake: Geochemistry, Geophysics, Geosystems, v. 19, no. 4, p. 1178-1198, https://doi.org/10.1002/2017GC007194.","productDescription":"21 p.","startPage":"1178","endPage":"1198","ipdsId":"IP-087532","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468814,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017gc007194","text":"Publisher Index Page"},{"id":353667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98,\n 37\n ],\n [\n -97.3,\n 37\n ],\n [\n -97.3,\n 37.5\n ],\n [\n -98,\n 37.5\n ],\n [\n -98,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-16","publicationStatus":"PW","scienceBaseUri":"5afee6d3e4b0da30c1bfbe6e","contributors":{"authors":[{"text":"Hearn, Elizabeth H.","contributorId":204395,"corporation":false,"usgs":false,"family":"Hearn","given":"Elizabeth","email":"","middleInitial":"H.","affiliations":[{"id":36931,"text":"Capstone Geopysics, Portola Valley, California,","active":true,"usgs":false}],"preferred":false,"id":733890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koltermann, Christine","contributorId":204396,"corporation":false,"usgs":false,"family":"Koltermann","given":"Christine","email":"","affiliations":[{"id":36932,"text":"Pegasus Geoscience, Santa Clara, California","active":true,"usgs":false}],"preferred":false,"id":733891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubinstein, Justin R. 0000-0003-1274-6785","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":204394,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","email":"","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":733889,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196637,"text":"ofr20181037 - 2018 - Leveraging geodetic data to reduce losses from earthquakes","interactions":[],"lastModifiedDate":"2018-04-24T13:34:26","indexId":"ofr20181037","displayToPublicDate":"2018-04-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1037","title":"Leveraging geodetic data to reduce losses from earthquakes","docAbstract":"Seismic hazard assessments that are based on a variety of data and the best available science, coupled with rapid synthesis of real-time information from continuous monitoring networks to guide post-earthquake response, form a solid foundation for effective earthquake loss reduction. With this in mind, the Earthquake Hazards Program (EHP) of the U.S. Geological Survey (USGS) Natural Hazards Mission Area (NHMA) engages in a variety of undertakings, both established and emergent, in order to provide high quality products that enable stakeholders to take action in advance of and in response to earthquakes. Examples include the National Seismic Hazard Model (NSHM), development of tools for improved situational awareness such as earthquake early warning (EEW) and operational earthquake forecasting (OEF), research about induced seismicity, and new efforts to advance comprehensive subduction zone science and monitoring. Geodetic observations provide unique and complementary information directly relevant to advancing many aspects of these efforts (fig. 1). EHP scientists have long leveraged geodetic data for a range of influential studies, and they continue to develop innovative observation and analysis methods that push the boundaries of the field of geodesy as applied to natural hazards research. Given the ongoing, rapid improvement in availability, variety, and precision of geodetic measurements, considering ways to fully utilize this observational resource for earthquake loss reduction is timely and essential. This report presents strategies, and the underlying scientific rationale, by which the EHP could achieve the following outcomes:
A geodesy program that encompasses a balanced mix of activities to sustain missioncritical capabilities, grows new competencies through the continuum of fundamental to applied research, and ensures sufficient resources for these endeavors provides a foundation by which the EHP can be a leader in the application of geodesy to earthquake science. With this in mind the following objectives provide a framework to guide EHP efforts:
Maintaining a vibrant internal research program provides the foundation by which the EHP can remain an effective and trusted source for earthquake science. Exploiting abundant new data sources, evaluating and assimilating the latest science, and pursuing novel avenues of investigation are means to fulfilling the EHP’s core responsibilities and realizing the important scientific advances envisioned by its scientists. Central to the success of such a research program is engaging personnel with a breadth of competencies and a willingness and ability to adapt these to the program’s evolving priorities, enabling current staff to expand their skills and responsibilities, and planning holistically to meet shared workforce needs.
In parallel, collaboration with external partners to support scientific investigations that complement ongoing internal research enables the EHP to strengthen earthquake information products by incorporating alternative perspectives and approaches and to study topics and geographic regions that cannot be adequately covered internally.
With commensurate support from technical staff who possess diverse skills, including engineering, information technology, and proficiency in quantitative analysis combined with basic geophysical knowledge, the EHP can achieve the geodetic outcomes identified in this document.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181037","usgsCitation":"Murray, J.R., Roeloffs, E.A., Brooks, B.A., Langbein, J., Leith, W., Minson, S.E., Svarc, J., and Thatcher, W., 2018, Leveraging geodetic data to reduce losses from earthquakes: U.S. Geological Survey Open-File Report 2018–1037, 34 p., https://doi.org/10.3133/ofr20181037.","productDescription":"vi, 34 p.","numberOfPages":"43","onlineOnly":"Y","ipdsId":"IP-089859","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":353651,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1037/coverthb.jpg"},{"id":353652,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1037/ofr20181037.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1037"}],"contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
https://earthquake.usgs.gov/
In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
The Offshore of Point Conception map area is in the westernmost part of the Western Transverse Ranges geologic province, which is north of the California Continental Borderland. Significant clockwise rotation—at least 90°—since the early Miocene has been proposed for the Western Transverse Ranges province, and this region is presently undergoing north-south shortening. The offshore part of the map area lies south of the steep south and west flanks of the Santa Ynez Mountains. The crest of the range, which has a maximum elevation of about 340 m in the map area, lies about 5 km north and east of the arcuate shoreline.
The onland part of the coastal zone is remote and sparsely populated. The road to Jalama Beach County Park provides the only public coastal access in the entire map area. North of this county park, the coastal zone is part of Vandenberg Air Force Base. South of Jalama Beach County Park, most of the coastal zone is part of the Cojo-Jalama Ranch, purchased by the Nature Conservancy in December 2017. A relatively small part of the coastal zone in the eastern part of the map area lies within the privately owned Hollister Ranch. The nearest significant commercial centers are Lompoc (population, about 42,000), about 10 km north of the map area, and Goleta (population, about 30,000), about 50 km east of the map area. The Union Pacific railroad tracks run west and northwest along the coast through the entire map area, within a few hundred meters of the shoreline. The map area has a long history of petroleum exploration, and the seafloor notably includes large asphalt mounds and pockmarks that result from petroleum seepage. Several offshore gas and oil fields were discovered, and some were developed, in and on the margin of California’s State Waters.
Much of the shoreline in the Offshore of Point Conception map area is characterized by narrow beaches that have thin sediment cover above bedrock platforms, backed by low (10- to 20-m-high) cliffs that are capped by a coastal terrace. Beaches are subject to wave erosion during winter storms, followed by gradual sediment recovery or accretion in the late spring, summer, and fall months during the gentler wave climate. The map area lies in the west-central part of the Santa Barbara littoral cell, which is characterized by west-to-east transport of sediment from Point Arguello on the northwest to Hueneme and Mugu Canyons on the southeast. Sediment supply to the map area is mainly from relatively small coastal watersheds, including the Jalama Creek–Espada Creek drainage basin (about 63 km2), as well as Cañada del Jolloru, Black Canyon, Wood Canyon, Cañada del Cojo, and Barranca Honda. Coastal-watershed discharge and sediment load are highly variable, characterized by brief large events during major winter storms and long periods of low (or no) flow and minimal sediment load between storms. In recent (recorded) history, the majority of high-discharge, high-sediment-flux events have been associated with El Niño phases of the El Niño–Southern Oscillation climatic pattern.
Following the coastline, the shelf bends to the north and northwest around Point Conception, and the trend of the shelf break changes from about 298° to 241° azimuth. Shelf width ranges from about 5 km south of Point Conception to about 11 km northwest of it; the slope ranges from about 1.0° to 1.2° to about 0.7° south and northwest of Point Conception, respectively. Southwest of Point Conception, the shelf break and upper slope are incised by a 600-m-wide, 20- to 30-m-deep, south-facing trough, one of five heads of the informally named Arguello submarine canyon.
The map area is located at a major biogeographic transition zone between the east-west-trending Santa Barbara Channel region of the Southern California Bight and the northwest-trending central California coast. North of Point Conception, the coast is subjected to high wave exposure from the north, west, and south, as well as consistently strong upwelling that brings cold, nutrient-rich waters to the surface. Southeast of Point Conception, the Santa Barbara Channel is largely protected from strong north swells by Point Conception and from south swells by the Channel Islands; surface waters are warmer, and upwelling is weak and seasonal.
Seafloor habitats in the broad Santa Barbara Channel region consist of significant amounts of soft, unconsolidated sediment interspersed with isolated areas of rocky habitat that support kelp-forest communities in the nearshore and rocky-reef communities in deeper water. The potential marine benthic habitat types mapped in the Offshore of Point Conception map area are directly related to its Quaternary geologic history, geomorphology, and active sedimentary processes. These potential habitats lie primarily within the Shelf (continental shelf) but also partly within the Flank (basin flank or continental slope) megahabitats. The fairly homogeneous seafloor of sediment and low-relief bedrock provides characteristic habitat for rockfish, groundfish, crabs, shrimp, and other marine benthic organisms. Several areas of smooth sediment form nearshore terraces that have relatively steep, smooth fronts, which are attractive to groundfish. Below the steep shelf break, soft, unconsolidated sediment is interrupted by the heads of several submarine canyons, gullies, and rills, also good potential habitat for rockfish. The map area includes the large (58.3 km2) Point Conception State Marine Reserve.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181024","usgsCitation":"Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series— Offshore of Point Conception, California: U.S. Geological Survey Open-File Report 2018–1024, pamphlet 36 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181024.","productDescription":"Pamphlet: iv, 36 p.; 9 Sheets: 55.0 x 36.0 inches or smaller; Dataset; Metadata","additionalOnlineFiles":"Y","ipdsId":"IP-082855","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":437940,"rank":23,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QN64XQ","text":"USGS data release","linkHelpText":"California State Waters Map Series Data Catalog--Offshore of Point Conception, California"},{"id":353525,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet8.pdf","text":"Sheet 8","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 8","linkHelpText":"Local (Offshore of Point Conception Map Area) and Regional (Offshore from Point Conception to Hueneme Canyon) Shallow-Subsurface Geology and Structure, Santa Barbara Channel, California By Samuel Y. 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Kvitek"},{"id":353517,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1024/coverthb.jpg"}],"scale":"24000","country":"United States","state":"California","otherGeospatial":"Point Conception","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.5636,\n 34.3917\n ],\n [\n -120.3717,\n 34.3917\n ],\n [\n -120.3717,\n 34.5422\n ],\n [\n -120.5636,\n 34.5422\n ],\n [\n -120.5636,\n 34.3917\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
The map area is in the southern part of the Western Transverse Ranges geologic province, which is north of the California Continental Borderland. Significant clockwise rotation—at least 90°—since the early Miocene has been proposed for the Western Transverse Ranges province, and the region is presently undergoing north-south shortening. The offshore part of the map area lies south of the steep south flank of the Santa Ynez Mountains. The crest of the range, which has a maximum elevation of about 760 m in the map area, lies about 4 km north of the shoreline.
Gaviota is an unincorporated community that has a sparse population (less than 100), and the coastal zone is largely open space that is locally used for cattle grazing. The Union Pacific railroad tracks extend westward along the coast through the entire map area, within a few hundred meters of the shoreline. Highway 101 crosses the eastern part of the map area, also along the coast, then turns north (inland) and travels through Cañada de la Gaviota and Gaviota Pass en route to Buellton. Gaviota State Park lies at the mouth of Cañada de la Gaviota. West of Gaviota, the onland coastal zone is occupied by the Hollister Ranch, a privately owned, gated community that has no public access.
The map area has a long history of petroleum exploration and development. Several offshore gas fields were discovered and were developed by onshore directional drilling in the 1950s and 1960s. Three offshore petroleum platforms were installed in adjacent federal waters in 1976 (platform “Honda”) and 1989 (platforms “Heritage” and “Harmony”). Local offshore and onshore operations were serviced for more than a century by the Gaviota marine terminal, which is currently being decommissioned and will be abandoned in an intended transition to public open space.
The Offshore of Gaviota map area lies within the western Santa Barbara Channel region of the Southern California Bight, and it is somewhat protected from large Pacific swells from the north and northwest by Point Conception and from south and southwest swells by offshore islands and banks. Much of the shoreline in the map area is characterized by narrow beaches that have thin sediment cover, backed by low (10- to 20-m-high) cliffs that are capped by a narrow coastal terrace. Beaches are subject to wave erosion during winter storms, followed by gradual sediment recovery or accretion in the late spring, summer, and fall months during the gentler wave climate.
The map area lies in the western-central part of the Santa Barbara littoral cell, which is characterized by west-to-east transport of sediment from Point Arguello on the northwest to Hueneme and Mugu Canyons on the southeast. Sediment supply to the western and central part of the littoral cell is mainly from relatively small coastal watersheds. In the map area, sediment sources include Cañada de la Gaviota (52 km2), as well as Cañada de la Llegua, Arroyo el Bulito, Cañada de Santa Anita, Cañada de Alegria, Cañada del Agua Caliente, Cañada del Barro, Cañada del Leon, Cañada San Onofre, and many others. Coastal-watershed discharge and sediment load are highly variable, characterized by brief large events during major winter storms and long periods of low (or no) flow and minimal sediment load between storms. In recent (recorded) history, the majority of high-discharge, high-sediment-flux events have been associated with El Niño phases of the El Niño–Southern Oscillation climatic pattern.
Shelf width in the Offshore of Gaviota map area ranges from about 4.3 to 4.7 km, and shelf slopes average about 1.0° to 1.2° but are highly variable because of the presence of the large Gaviota sediment bar. This bar extends southwestward for about 9 km from the mouth of Cañada de la Gaviota to the shelf break, is as wide as 2 km, and is by far the largest shore-attached sediment bar in the Santa Barbara Channel. The shelf is underlain by bedrock and variable amounts (0 to as much as 36 m in the Gaviota bar) of upper Quaternary sediments deposited as sea level fluctuated in the late Pleistocene. The trend of the shelf break changes from about 276° to 236° azimuth over a distance of about 12 km, and it ranges in depth from about 91 m to as shallow as 62 to 73 m where significant shelf-break and upper-slope failure and landsliding has apparently occurred. The shelf break in the western part of the map area is notably embayed by the heads of three large (150- to 300-m-wide) channels that have been referred to as “the Gaviota Canyons” or as “Drake Canyon,” “Sacate Canyon,” and “Alegria Canyon.”
Seafloor habitats in the broad Santa Barbara Channel region consist of significant amounts of soft, unconsolidated sediment interspersed with isolated areas of rocky habitat that support kelp-forest communities in the nearshore and rocky-reef communities in deeper water. The potential marine benthic habitat types mapped in the Offshore of Gaviota map area are directly related to its Quaternary geologic history, geomorphology, and active sedimentary processes. These potential habitats lie primarily within the Shelf (continental shelf) but also partly within the Flank (basin flank or continental slope) megahabitats. The fairly homogeneous seafloor of sediment and low-relief bedrock provides characteristic habitat for rockfish, groundfish, crabs, shrimp, and other marine benthic organisms. Several areas of smooth sediment form nearshore terraces that have relatively steep, smooth fronts, which may be attractive to groundfish. Below the steep shelf break, soft, unconsolidated sediment is interrupted by the heads of several submarine canyons and rills, some bedrock exposures, and small carbonate mounds associated with asphalt mounds and pockmarks, also good potential habitat for rockfish. The map area includes the relatively small (5.2 km2) Kashtayit State Marine Conservation Area, which largely occupies the inner part of the Gaviota sediment bar.
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Davenport"},{"id":353504,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1023/ofr20181023_sheet8.pdf","text":"Sheet 8","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1023 Sheet 8","linkHelpText":"Local (Offshore of Gaviota Map Area) and Regional (Offshore from Point Conception to Hueneme Canyon) Shallow-Subsurface Geology and Structure, Santa Barbara Channel, California By Samuel Y. Johnson and Stephen R. Hartwell"},{"id":353503,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1023/ofr20181023_sheet7.pdf","text":"Sheet 7","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1023 Sheet 7","linkHelpText":"Seismic-Reflection Profiles, Offshore of Gaviota Map Area, California By Samuel Y. Johnson and Stephen R. Hartwell"},{"id":353502,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1023/ofr20181023_sheet6.pdf","text":"Sheet 6","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1023 Sheet 6","linkHelpText":"Marine Benthic Habitats from the Coastal and Marine Ecological Classification Standard, Offshore of Gaviota Map Area, California By Guy R. Cochrane, Stephen R. Hartwell, and Samuel Y. Johnson"},{"id":353506,"rank":10,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1023/coverthb.jpg"}],"scale":"24000","country":"United States","state":"California","city":"Gaviota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.3753,\n 34.4056\n ],\n [\n -120.1833,\n 34.4056\n ],\n [\n -120.1833,\n 34.5425\n ],\n [\n -120.3753,\n 34.5425\n ],\n [\n -120.3753,\n 34.4056\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
The bedrock geologic map of the Miles Pond and Concord quadrangles covers an area of approximately 107 square miles (276 square kilometers) in east-central Vermont and adjacent New Hampshire, north of and along the Connecticut River. This map was created as part of a larger effort to produce a new bedrock geologic map of Vermont through the collection of field data at a scale of 1:24,000. The majority of the map area consists of the Bronson Hill anticlinorium, a post-Early Devonian structure that is cored by metamorphosed Cambrian to Silurian sedimentary, volcanic, and plutonic rocks. A major feature on the map is the Monroe fault, interpreted to be a west-directed, steeply dipping Late Devonian (Acadian) thrust fault. To the west of the Monroe fault, rocks of the Connecticut Valley-Gaspé trough dominate and consist primarily of metamorphosed Silurian and Devonian sedimentary rocks. To the north, the Victory pluton intrudes the Bronson Hill anticlinorium. The Bronson Hill anticlinorium consists of the metamorphosed Albee Formation, the Ammonoosuc Volcanics, the Comerford Intrusive Complex, the Highlandcroft Granodiorite, and the Joselin Turn tonalite. The Albee Formation is an interlayered, feldspathic metasandstone and pelite that is locally sulfidic. Much of the deformed metasandstone is tectonically pinstriped. In places, one can see compositional layering that was transposed by a steeply southeast-dipping foliation. The Ammonoosuc Volcanics are lithologically complex and predominantly include interlayered and interfingered rhyolitic to basaltic volcanic and volcaniclastic rocks, as well as lesser amounts of siltstone, phyllite, graywacke, and grit. The Comerford Intrusive Complex crops out east of the Monroe fault and consists of metamorphosed gabbro, diorite, tonalite, aplitic tonalite, and crosscutting diabase dikes. Abundant mafic dikes from the Comerford Intrusive Complex intruded the Albee Formation and Ammonoosuc Volcanics east of the Monroe fault. The Highlandcroft Granodiorite and Joslin Turn tonalite plutons intruded during the Middle to Late Ordovician.
West of the Monroe fault, the Connecticut Valley-Gaspé trough consists of the Silurian and Devonian Waits River and Gile Mountain Formations. The Waits River Formation is a carbonaceous muscovite-biotite-quartz (±garnet) phyllite containing abundant beds of micaceous quartz-rich limestone. The Gile Mountain Formation consists of interlayered metasandstone and graphitic (and commonly sulfidic) slate, along with minor calcareous metasandstone and ironstone. Graded bedding is common in the Gile Mountain Formation. Rocks of the Devonian New Hampshire Plutonic Suite intruded as plutons, dikes, and sills. The largest of these is the Victory pluton, which consists of weakly foliated, biotite granite and granodiorite. The Victory pluton also intruded a large part of the Albee Formation to the north.
This report consists of a geologic map and an online geographic information systems database that includes contacts of bedrock geologic units, faults, outcrops, and structural geologic information. The geologic map is intended to serve as a foundation for applying geologic information to problems involving land use decisions, groundwater availability and quality, earth resources such as natural aggregate for construction, assessment of natural hazards, and engineering and environmental studies for waste disposal sites and construction projects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181025","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey, and the State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey","usgsCitation":"Rankin, D.W., 2018, Bedrock geologic map of the Miles Pond and Concord quadrangles, Essex and Caledonia Counties, Vermont, and Grafton County, New Hampshire: U.S. Geological Survey Open-File Report 2018–1025, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20181025.","productDescription":"1 Sheet: 34.47 x 40.58 inches; Databases; Metadata; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081110","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":353546,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1025/metadata/ofr20181025_milespond-concordnh-geologicmap.mxd","text":"Geologic Map (ArcGIS 10.5)","linkHelpText":"- Miles Pond and Concord, Vermont, and New Hampshire, Geologic Map"},{"id":353538,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1025/ofr20181025_concord-miles-pond-geologicmap10.pdf","text":"Geologic Map","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1025"},{"id":399116,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_107158.htm"},{"id":353547,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1025/metadata/ofr20181025_milespond-concordnh-metadata.zip","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Miles Pond and Concord, Vermont, and New Hampshire, Metadata"},{"id":353545,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1025/metadata/ofr20181025_milespond-concordnh.gdb.zip","text":"Database","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Miles Pond and Concord, Vermont, and New Hampshire, Geodatabase"},{"id":353544,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2018/1025/metadata/ofr20181025_milespond-concordnh-basemap.zip","text":"Base Map","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Miles Pond and Concord, Vermont, and New Hampshire, Base Map"},{"id":353537,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1025/coverthb3.jpg"}],"scale":"24000","country":"United States","state":"New Hampshire, Vermont","county":"Caledonia County, Essex County, Grafton County","otherGeospatial":"Miles Pond and Concord quadrangles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72,\n 44.375\n ],\n [\n -71.75,\n 44.375\n ],\n [\n -71.75,\n 44.5\n ],\n [\n -72,\n 44.5\n ],\n [\n -72,\n 44.375\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate
Science Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The bedrock geologic map of the Lisbon quadrangle, and parts of the Sugar Hill and East Haverhill quadrangles, Grafton County, New Hampshire, covers an area of approximately 73 square miles (189 square kilometers) in west-central New Hampshire. This map was created as part of a larger effort to produce a new bedrock geologic map of Vermont through the collection of field data at a scale of 1:24,000. A large part of the map area consists of the Bronson Hill anticlinorium, a post-Early Devonian structure that is cored by metamorphosed Cambrian to Devonian sedimentary, volcanic, and plutonic rocks.
The Bronson Hill anticlinorium is the apex of the Middle Ordovician to earliest-Silurian Bronson Hill magmatic arc that contains the Ammonoosuc Volcanics, Partridge Formation, and Oliverian Plutonic Suite, and extends from Maine, through western New Hampshire (down the eastern side of the Connecticut River), through southern New England to Long Island Sound. The deformed and partially eroded arc is locally overlain by a relatively thin Silurian section of metasedimentary rocks (Clough Quartzite and Fitch Formation) that thickens to the east. The Silurian section near Littleton is disconformably overlain by a thicker, Lower Devonian section that includes mostly metasedimentary and minor metavolcanic rocks of the Littleton Formation. The Bronson Hill anticlinorium is bisected by a series of northeast-southwest trending Mesozoic normal faults. Primarily among them is the steeply northwest-dipping Ammonoosuc fault that divides older and younger units (lower and upper sections) of the Ammonoosuc Volcanics. The Ammonoosuc Volcanics are lithologically complex and predominantly include interlayered and interfingered rhyolitic to basaltic volcanic and volcaniclastic rocks, as well as lesser amounts of slate, phyllite, ironstone, chert, sandstone, and pelite. The Albee Formation underlies the Ammonoosuc Volcanics and is predominantly composed of interbedded metamorphosed sandstone, siltstone, and phyllite.
During the Late Ordovician, a series of arc-related plutons intruded the Ammonoosuc Volcanics including the Moody Ledge pluton and the Scrag granite of Billings (1937). Subsequent plutonism related to the Acadian orogeny occurred after volcanism and deposition resulted in the Littleton Formation during the Late Devonian, including the intrusion of the Haverhill pluton and French Pond Granite found in the southern part of the map.
This report consists of a geologic map and an online geographic information systems database that includes contacts of bedrock geologic units, faults, outcrops, and structural geologic information. The geologic map is intended to serve as a foundation for applying geologic information to problems involving land use decisions, groundwater availability and quality, earth resources such as natural aggregate for construction, assessment of natural hazards, and engineering and environmental studies for waste disposal sites and construction projects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181016","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey, and the State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey","usgsCitation":"Rankin, D.W., 2018, Bedrock geologic map of the Lisbon quadrangle, and parts of the Sugar Hill and East Haverhill quadrangles, Grafton County, New Hampshire: U.S. Geological Survey Open-File Report 2018–1016, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20181016.","productDescription":"1 Sheet: 34.66 x 37.08 inches; Databases; Metadata; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-082431","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":399117,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_107159.htm"},{"id":353552,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1016/metadata/ofr20181016_lisbonnh-metadata.zip","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Lisbon, New Hampshire, Metadata"},{"id":353550,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1016/metadata/ofr20181016_lisbonnh.gdb.zip","text":"Database","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Lisbon, New Hampshire, Geodatabase"},{"id":353549,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2018/1016/metadata/ofr20181016_lisbonnh-basemap.zip","text":"Base Map","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Lisbon, New Hampshire, Base Map"},{"id":353551,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1016/metadata/ofr20181016_lisbonnh-geologicmap.mxd","text":"Geologic Map (ArcGIS 10.5)","linkHelpText":"- Lisbon, New Hampshire, Geologic Map"},{"id":353540,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1016/ofr20181016_lisbon-geologic-map.pdf","text":"Geologic Map","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1016"},{"id":353539,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1016/coverthb2.jpg"}],"scale":"24000","country":"United States","state":"New Hampshire","county":"Grafton County","otherGeospatial":"Lisbon quadrangle, Sugar Hill and East Haverhill quadrangles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72,\n 44\n ],\n [\n -71.75,\n 44\n ],\n [\n -71.75,\n 44.25\n ],\n [\n -72,\n 44.25\n ],\n [\n -72,\n 44\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate
Science Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The collection of high-frequency (in other words, “continuous”) water data has been made easier over the years because of advances in technologies to measure, transmit, store, and query large, temporally dense datasets. Commercially available, in-situ sensors and data-collection platforms—together with new techniques for data analysis—provide an opportunity to monitor water quantity and quality at time scales during which meaningful changes occur. The U.S. Geological Survey (USGS) Continuous Monitoring Workshop was held to build stronger collaboration within the Water Mission Area on the collection, interpretation, and application of continuous monitoring data; share technical approaches for the collection and management of continuous data that improves consistency and efficiency across the USGS; and explore techniques and tools for the interpretation of continuous monitoring data, which increases the value to cooperators and the public. The workshop was organized into three major themes: Collecting Continuous Data, Understanding and Using Continuous Data, and Observing and Delivering Continuous Data in the Future. Presentations each day covered a variety of related topics, with a special session at the end of each day designed to bring discussion and problem solving to the forefront.
The workshop brought together more than 70 USGS scientists and managers from across the Water Mission Area and Water Science Centers. Tools to manage, assure, control quality, and explore large streams of continuous water data are being developed by the USGS and other organizations and will be critical to making full use of these high-frequency data for research and monitoring. Disseminating continuous monitoring data and findings relevant to critical cooperator and societal issues is central to advancing the USGS networks and mission. Several important outcomes emerged from the presentations and breakout sessions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181059","usgsCitation":"Sullivan, D.J., Joiner, J.K., Caslow, K.A., Landers, M.N., Pellerin, B.A., Rasmussen, P.P., and Sheets, R.A., 2018, U.S. Geological Survey continuous monitoring workshop—Workshop summary report: U.S. Geological Survey Open-File Report 2018–1059, 29 p., https://doi.org/10.3133/ofr20181059.","productDescription":"iv, 29 p.","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092143","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":353586,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1059/coverthb.jpg"},{"id":353587,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1059/ofr20181059.pdf","text":"Report","size":"1.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1059"}],"contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
The waveforms generated by the 2014 Long Valley Caldera earthquake swarm recorded at station MLH show clear reflected waves that are often stronger than direct P and S waves. With waveform analyses, we discover that these waves are reflected at the top of a low-velocity body, which may be residual magma from the ∼767 ka caldera-forming eruption. The polarity of the reflection compared to direct P and S waves suggests that the reflection is SP waves (S from hypocenters to reflector and then convert to P waves to the surface). Because the wavefields are coherent among different earthquakes and hold high signal-to-noise ratios, we apply them to a wavefield migration method for imaging reflectors. The depth of the imaged magmatic system roof is around 8.2 km below the surface. This is consistent with previous studies. Even though we use only one station and waveforms from one earthquake swarm, the dense cluster of accurately located earthquakes provides a high-resolution image of the roof.
The Florida manatee (Trichechus manatus latirostris) has limited diversity in the immunoglobulin heavy chain. We therefore investigated the antigen receptor loci of the other arm of the adaptive immune system: the T cell receptor. Manatees are the first species from Afrotheria, a basal eutherian superorder, to have an in-depth characterization of all T cell receptor loci. By annotating the genome and expressed transcripts, we found that each chain has distinct features that correlates to their individual functions. The genomic organization also plays a role in modulating sequence conservation between species. There were extensive V subgroup synteny blocks in the TRA and TRB loci between T. m. latirostrisand human. Increased genomic locus complexity correlated to increased locus synteny. We also identified evidence for a VHD pseudogene for the first time in a eutherian mammal. These findings emphasize the value of including species within this basal eutherian radiation in comparative studies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.dci.2018.04.007","usgsCitation":"Breaux, B., Hunter, M., Cruz-Schneider, M.P., Sena, L., Bonde, R.K., and Criscitiello, M.F., 2018, The Florida manatee (Trichechus manatus latirostris) T cell receptor loci exhibit V subgroup synteny and chain-specific evolution: Developmental and Comparative Immunology, v. 85, p. 71-85, https://doi.org/10.1016/j.dci.2018.04.007.","productDescription":"15 p.","startPage":"71","endPage":"85","ipdsId":"IP-093270","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468817,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.dci.2018.04.007","text":"Publisher Index Page"},{"id":353618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"85","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d8e4b0da30c1bfbe82","contributors":{"authors":[{"text":"Breaux, Breanna","contributorId":196396,"corporation":false,"usgs":false,"family":"Breaux","given":"Breanna","email":"","affiliations":[],"preferred":false,"id":733773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunter, Margaret 0000-0002-4760-9302 mhunter@usgs.gov","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":140627,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","email":"mhunter@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":733772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cruz-Schneider, Maria Paula","contributorId":196400,"corporation":false,"usgs":false,"family":"Cruz-Schneider","given":"Maria","email":"","middleInitial":"Paula","affiliations":[],"preferred":false,"id":733774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sena, Leonardo","contributorId":196401,"corporation":false,"usgs":false,"family":"Sena","given":"Leonardo","email":"","affiliations":[],"preferred":false,"id":733775,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bonde, Robert K. 0000-0001-9179-4376 rbonde@usgs.gov","orcid":"https://orcid.org/0000-0001-9179-4376","contributorId":2675,"corporation":false,"usgs":true,"family":"Bonde","given":"Robert","email":"rbonde@usgs.gov","middleInitial":"K.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":733776,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Criscitiello, Michael F.","contributorId":196403,"corporation":false,"usgs":false,"family":"Criscitiello","given":"Michael","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":733777,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}