Sea otters are well-known tool users, employing objects such as rocks or shells to break open invertebrate prey. We used a series of generalized linear mixed effect models to examine observational data on prey capture and tool use from 211 tagged individuals from 5 geographically defined study areas throughout the sea otter’s range in California. Our best supported model was able to explain 75% of the variation in the frequency of tool use by individual sea otters with only ecological and demographic variables. In one study area, where sea otter food resources were abundant, all individuals had similar diets focusing on preferred prey items and used tools at low to moderate frequencies (4–38% of prey captures). In the remaining areas, where sea otters were food-limited, individuals specialized on different subsets of the available prey and had a wider range of average tool-use frequency (0–98% of prey captures). The prevalence of difficult-to-access prey in individual diets was a major predictor of tool use and increased the likelihood of using tools on prey that were not difficult to access as well. Age, sex, and feeding habitat also contributed to the probability of tool use but to a smaller extent. We developed a conceptual model illustrating how food abundance, the prevalence of difficult-to-access prey, and individual diet specialization interacted to determine the likelihood that individual sea otters would use tools and considered the model’s relevance to other tool-using species.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/beheco/arx011","usgsCitation":"Fujii, J.A., Ralls, K., and Tinker, M.T., 2017, Food abundance, prey morphology, and diet specialization influence individual sea otter tool use: Behavioral Ecology, v. 28, no. 5, p. 1206-1216, https://doi.org/10.1093/beheco/arx011.","productDescription":"11 p.","startPage":"1206","endPage":"1216","ipdsId":"IP-076085","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":469510,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/beheco/arx011","text":"Publisher Index Page"},{"id":345941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-21","publicationStatus":"PW","scienceBaseUri":"59c37e36e4b091459a6316e3","contributors":{"authors":[{"text":"Fujii, Jessica A. 0000-0003-4794-479X","orcid":"https://orcid.org/0000-0003-4794-479X","contributorId":196602,"corporation":false,"usgs":false,"family":"Fujii","given":"Jessica","email":"","middleInitial":"A.","affiliations":[],"preferred":true,"id":710896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ralls, Katherine","contributorId":37900,"corporation":false,"usgs":false,"family":"Ralls","given":"Katherine","email":"","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":710897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":710895,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191012,"text":"70191012 - 2017 - Ancient lakes, Pleistocene climates and river avulsions structure the phylogeography of a large but little-known rock scorpion from the Mojave and Sonoran deserts","interactions":[],"lastModifiedDate":"2017-09-20T17:23:29","indexId":"70191012","displayToPublicDate":"2017-09-20T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1019,"text":"Biological Journal of the Linnean Society","active":true,"publicationSubtype":{"id":10}},"title":"Ancient lakes, Pleistocene climates and river avulsions structure the phylogeography of a large but little-known rock scorpion from the Mojave and Sonoran deserts","docAbstract":"Recent syntheses of phylogeographical data from terrestrial animals in the Mojave and Sonoran deserts have revealed a complex history of geologic and climatic vicariance events. We studied the phylogeography of Smeringurus vachoni to see how vicariance events may have impacted a large, endemic rock scorpion. Additionally, we used the phylogeographical data to examine the validity of two subspecies of S. vachoni that were described using unconventional morphological characters. Phylogenetic, network and SAMOVA analyses indicate that S. vachoni consists of 11 clades mostly endemic to isolated desert mountain ranges. Molecular clock estimates suggest that clades diversified between the Miocene and early Pleistocene. Species distribution models predict a contraction of suitable habitat during the last glacial maximum. Landscape interpolations and Migrate-n analyses highlight areas of gene flow across the Colorado River. Smeringurus vachoni does not comprise two subspecies. Instead, the species represents at least 11 mitochondrial clades that probably diversified by vicariance associated with Pleistocene climate changes and formation of ancient lakes along the Colorado River corridor. Gene flow appears to have occurred from west to east across the Colorado River during periodic river avulsions.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/biolinnean/blx058","usgsCitation":"Graham, M.R., Wood, D.A., Henault, J.A., Valois, Z.J., and Cushing, P.E., 2017, Ancient lakes, Pleistocene climates and river avulsions structure the phylogeography of a large but little-known rock scorpion from the Mojave and Sonoran deserts: Biological Journal of the Linnean Society, v. 122, no. 1, p. 133-146, https://doi.org/10.1093/biolinnean/blx058.","productDescription":"14 p.","startPage":"133","endPage":"146","ipdsId":"IP-083197","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":345978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mojave Desert, Sonoran Desert","volume":"122","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-17","publicationStatus":"PW","scienceBaseUri":"59c37e36e4b091459a6316df","contributors":{"authors":[{"text":"Graham, Matthew R.","contributorId":196613,"corporation":false,"usgs":false,"family":"Graham","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":34649,"text":"Eastern Connectictut State University","active":true,"usgs":false}],"preferred":false,"id":710918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Dustin A. 0000-0002-7668-9911 dawood@usgs.gov","orcid":"https://orcid.org/0000-0002-7668-9911","contributorId":4179,"corporation":false,"usgs":true,"family":"Wood","given":"Dustin","email":"dawood@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":710919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henault, Jonathan A.","contributorId":196614,"corporation":false,"usgs":false,"family":"Henault","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[{"id":34649,"text":"Eastern Connectictut State University","active":true,"usgs":false}],"preferred":false,"id":710920,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valois, Zachary J.","contributorId":196615,"corporation":false,"usgs":false,"family":"Valois","given":"Zachary","email":"","middleInitial":"J.","affiliations":[{"id":34651,"text":"Utah Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":710921,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cushing, Paula E.","contributorId":196616,"corporation":false,"usgs":false,"family":"Cushing","given":"Paula","email":"","middleInitial":"E.","affiliations":[{"id":27833,"text":"Denver Museum of Nature and Science","active":true,"usgs":false}],"preferred":false,"id":710922,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70190970,"text":"70190970 - 2017 - Fatal attraction? Intraguild facilitation and suppression among predators","interactions":[],"lastModifiedDate":"2017-10-26T10:01:47","indexId":"70190970","displayToPublicDate":"2017-09-19T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5500,"text":"The American Naturalist","onlineIssn":"1537-5323","printIssn":" 0003-014","active":true,"publicationSubtype":{"id":10}},"title":"Fatal attraction? Intraguild facilitation and suppression among predators","docAbstract":"Competition and suppression are recognized as dominant forces that structure predator communities. Facilitation via carrion provisioning, however, is a ubiquitous interaction among predators that could offset the strength of suppression. Understanding the relative importance of these positive and negative interactions is necessary to anticipate community-wide responses to apex predator declines and recoveries worldwide. Using state-sponsored wolf (Canis lupus) control in Alaska as a quasi experiment, we conducted snow track surveys of apex, meso-, and small predators to test for evidence of carnivore cascades (e.g., mesopredator release). We analyzed survey data using an integrative occupancy and structural equation modeling framework to quantify the strengths of hypothesized interaction pathways, and we evaluated fine-scale spatiotemporal responses of nonapex predators to wolf activity clusters identified from radio-collar data. Contrary to the carnivore cascade hypothesis, both meso- and small predator occupancy patterns indicated guild-wide, negative responses of nonapex predators to wolf abundance variations at the landscape scale. At the local scale, however, we observed a near guild-wide, positive response of nonapex predators to localized wolf activity. Local-scale association with apex predators due to scavenging could lead to landscape patterns of mesopredator suppression, suggesting a key link between occupancy patterns and the structure of predator communities at different spatial scales.
","language":"English","publisher":"The University of Chicago Press","doi":"10.1086/693996","usgsCitation":"Sivy, K.J., Pozzanghera, C.B., Grace, J.B., and Prugh, L.R., 2017, Fatal attraction? Intraguild facilitation and suppression among predators: The American Naturalist, v. 190, no. 5, p. 663-679, https://doi.org/10.1086/693996.","productDescription":"17 p.","startPage":"663","endPage":"679","ipdsId":"IP-074486","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":345900,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"190","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59c22cb2e4b091459a61b729","contributors":{"authors":[{"text":"Sivy, Kelly J. 0000-0002-3598-3014","orcid":"https://orcid.org/0000-0002-3598-3014","contributorId":196570,"corporation":false,"usgs":false,"family":"Sivy","given":"Kelly","email":"","middleInitial":"J.","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":710789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pozzanghera, Casey B.","contributorId":196571,"corporation":false,"usgs":false,"family":"Pozzanghera","given":"Casey","email":"","middleInitial":"B.","affiliations":[{"id":34632,"text":"Boise State University, Idaho","active":true,"usgs":false}],"preferred":false,"id":710790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"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":710788,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prugh, Laura R. 0000-0001-9045-3107","orcid":"https://orcid.org/0000-0001-9045-3107","contributorId":196572,"corporation":false,"usgs":false,"family":"Prugh","given":"Laura","email":"","middleInitial":"R.","affiliations":[{"id":13194,"text":"School of Environmental and Forest Sciences, University of Washington","active":true,"usgs":false}],"preferred":false,"id":710791,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190945,"text":"70190945 - 2017 - The land-sea interface: A source of high-quality phytoplankton to support secondary production","interactions":[],"lastModifiedDate":"2017-11-29T16:30:22","indexId":"70190945","displayToPublicDate":"2017-09-19T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"The land-sea interface: A source of high-quality phytoplankton to support secondary production","docAbstract":"Coastal-estuarine systems are among the most productive marine ecosystems and their special role in producing\nharvestable fish and shellfish has been attributed to high primary production fueled by nutrient runoff\nfrom land and efficient trophic transfer. Here we ask if phytoplankton species composition and their food\nquality based on the percentage of long-chain essential fatty acids (LCEFA) is another factor contributing to\nhigh secondary production in these ecosystems. We used long-term measurements of major phytoplankton\ntaxonomic groups and estimated their content of LCEFA along the salinity gradient in coastal-estuarine ecosystems,\nwith emphasis on Chesapeake Bay and the Baltic Sea, and an oceanic transect. Our data show that\ncyanobacteria with low nutritional quality often dominate at low-salinity regions, while intermediate to\nhigher salinity regions produce diatoms and dinoflagellates that have a higher content of LCEFA and are\nthus a higher-quality food resource for consumers. Higher salinity regions have less pronounced seasonal\nchanges in the percentage of phytoplankton LCEFA compared to low salinity regions, providing a stable supply\nof nutritious phytoplankton to consumers. The phytoplankton LCEFA content is similarly high in coastal\nupwelling systems and it decreases further offshore in oligotrophic oceanic regions dominated by picophytoplankton.\nOur results from a broad range of coastal-ecosystem types show that ecosystems at the land-sea\ninterface provide a valuable service by producing phytoplankton enriched in the biochemicals essential for\nconsumers. High primary production, coupled with high quality of that production, explain why the production\nof fish and shellfish is high where land and sea meet.","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.10650","usgsCitation":"Winder, M., Carstensen, J., Galloway, A.W., Jakobsen, H.H., and Cloern, J.E., 2017, The land-sea interface: A source of high-quality phytoplankton to support secondary production: Limnology and Oceanography, v. 62, no. S1, p. S258-S271, https://doi.org/10.1002/lno.10650.","productDescription":"14 p.","startPage":"S258","endPage":"S271","onlineOnly":"N","ipdsId":"IP-071223","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":469517,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10650","text":"Publisher Index Page"},{"id":345869,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"S1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-15","publicationStatus":"PW","scienceBaseUri":"59c22cb3e4b091459a61b734","contributors":{"authors":[{"text":"Winder, Monika","contributorId":196556,"corporation":false,"usgs":false,"family":"Winder","given":"Monika","email":"","affiliations":[],"preferred":false,"id":710749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carstensen, Jacob","contributorId":79367,"corporation":false,"usgs":false,"family":"Carstensen","given":"Jacob","email":"","affiliations":[{"id":7177,"text":"Dept of Bioscience, Aahus Univ, Denmark","active":true,"usgs":false}],"preferred":false,"id":710750,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Galloway, Aaron W.E.","contributorId":172072,"corporation":false,"usgs":false,"family":"Galloway","given":"Aaron","email":"","middleInitial":"W.E.","affiliations":[],"preferred":false,"id":710751,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jakobsen, Hans H.","contributorId":196557,"corporation":false,"usgs":false,"family":"Jakobsen","given":"Hans","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":710756,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":710748,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70190788,"text":"ofr20171116 - 2017 - Morphologic evolution of the wilderness area breach at Fire Island, New York—2012–15","interactions":[],"lastModifiedDate":"2024-12-27T15:18:20.876985","indexId":"ofr20171116","displayToPublicDate":"2017-09-18T11:00:00","publicationYear":"2017","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":"2017-1116","title":"Morphologic evolution of the wilderness area breach at Fire Island, New York—2012–15","docAbstract":"Hurricane Sandy, which made landfall on October 29, 2012, near Atlantic City, New Jersey, had a significant impact on the coastal system along the south shore of Long Island, New York. A record significant wave height of 9.6 meters (m) was measured at wave buoy 44025, approximately 48 kilometers offshore of Fire Island, New York. Surge and runup during the storm resulted in extensive beach and dune erosion and breaching of the Fire Island barrier island system at two locations, including a breach that formed within the Otis Pike Fire Island High Dune Wilderness area on the eastern side of Fire Island.
The U.S. Geological Survey (USGS) has a long history of conducting morphologic change and processes research at Fire Island. One of the primary objectives of the current research effort is to understand the morphologic evolution of the barrier system on a variety of time scales (from storm scale to decade(s) to century). A number of studies that support the project objectives have been published. Prior to Hurricane Sandy, however, little information was available on specific storm-driven change in this region. The USGS received Hurricane Sandy supplemental funding (project GS2–2B: Linking Coastal Processes and Vulnerability, Fire Island, New York, Regional Study) to enhance existing research efforts at Fire Island. The existing research was greatly expanded to include inner continental shelf mapping and investigations of processes of inner shelf sediment transport; beach and dune response and recovery; and observation, analysis, and modeling of the newly formed breach in the Otis Pike High Dune Wilderness area, herein referred to as the wilderness breach. The breach formed at the site of Old Inlet, which was open from 1763 to 1825. The location of the initial island breaching does not directly correspond with topographic lows of the dunes, but instead the breach formed in the location of a cross-island boardwalk that was destroyed during Hurricane Sandy.
From 2013 to November 2015, bathymetric data were collected by the USGS St. Petersburg Coastal and Marine Science Center during three surveys of the breach channel and tidal shoals, and shoreline positions on each side of the breach (also collected by the National Park Service). Additionally, pre-storm topography/bathymetry EAARL–B light detection and ranging (lidar) data were collected by the USGS the day prior to Hurricane Sandy’s landfall. These data serve as a baseline for change analyses during four subsequent periods: June 2013, June 2014, October 2014, and May 2015. The June 2013 single-beam bathymetry data were collected in collaboration with the U.S. Army Corps of Engineers (USACE), using the Lighter Amphibious Resupply Cargo (LARC) vessel, and included the ebb shoal and breach channel. The USGS collected and processed the three additional bathymetric datasets using personal watercraft equipped with single-beam echo sounders and backpack Global Positioning System (GPS) over shallow flood shoals.
Eastern and western breach shorelines were surveyed weekly to monthly beginning on November 6, 2012 (by the National Park Service [NPS], and USGS St. Petersburg Coastal and Marine Science Center), with measurements made every few weeks for the first year and every few months after October 2013. The NPS and researchers from Stony Brook University monitored the breach by collecting field data of the breach channel bathymetry, conducting aerial photographic overflights, and performing water-quality analyses (see http://po.msrc.sunysb.edu/GSB/). The aerial photography collected and rectified by Stony Brook University is used extensively in our morphologic change description to examine changes to breach shorelines (supplementing shoreline data collected in the field), channel width, and orientation. Due to the uncertainties and the variation in survey methods, a rigorous quantitative analysis was not performed. However, average calculations of various breach metrics allow a qualitative analysis of breach development and evolution.
This report presents an overview of the data collected and a summary discussion of the observed changes to the breach system and the seasonal wave climatology associated with the breach morphodynamic response.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171116","usgsCitation":"Hapke, C.J., Nelson, T.R., Henderson, R.E., Brenner, O.T., and Miselis, J.L., 2017, Morphologic evolution of the wilderness area breach at Fire Island, New York—2012–15: U.S. Geological Survey Open-File Report 2017–1116, 17 p., https://doi.org/10.3133/ofr20171116.","productDescription":"Report: vi, 17 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-086286","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":345809,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1049","text":"Data Series 1049","description":"Data Series 1049","linkHelpText":"- Coastal bathymetry data collected in May 2015 from Fire Island, New York—Wilderness breach and shoreface"},{"id":345808,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1034","text":"Data Series 1034","description":"Data Series 1034","linkHelpText":"Bathymetry data collected in October 2014 from Fire Island, New York—The wilderness breach, shoreface, and bay"},{"id":345810,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1007","text":"Data Series 1007","description":"Data Series 1007","linkHelpText":"- Coastal bathymetry data collected in June 2014 from Fire Island, New York—The wilderness breach and shoreface"},{"id":345750,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1116/coverthb.jpg"},{"id":345805,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1116/ofr20171116.pdf","text":"Report","size":"21.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1116"},{"id":345806,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds914","text":"Data Series 914","description":"Data Series 914","linkHelpText":"- Bathymetry of Wilderness Breach at Fire Island, New York from June 2013"},{"id":345807,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7G15Z17","text":"USGS data release","description":"USGS data release","linkHelpText":"Hurricane Sandy Beach Response and Recovery at Fire Island, New York—Shoreline and Beach Profile Data, October 2012 to June 2016"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.32000732421875,\n 40.6113461833302\n ],\n [\n -72.87574768066406,\n 40.6113461833302\n ],\n [\n -72.87574768066406,\n 40.73581157695217\n ],\n [\n -73.32000732421875,\n 40.73581157695217\n ],\n [\n -73.32000732421875,\n 40.6113461833302\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
Gross primary production (GPP) is the Earth’s largest carbon flux into the terrestrial biosphere and plays a critical role in regulating atmospheric chemistry and global climate. The Moderate Resolution Imaging Spectrometer (MODIS)-MOD17 data product is a widely used remote sensing-based model that provides global estimates of spatiotemporal trends in GPP. When the MOD17 algorithm is applied to regional scale heterogeneous landscapes, input data from coarse resolution land cover and climate products may increase uncertainty in GPP estimates, especially in high productivity tropical ecosystems. We examined the influence of using locally specific land cover and high-resolution local climate input data on MOD17 estimates of GPP for the State of Hawaii, a heterogeneous and discontinuous tropical landscape. Replacing the global land cover data input product (MOD12Q1) with Hawaii-specific land cover data reduced statewide GPP estimates by ~8%, primarily because the Hawaii-specific land cover map had less vegetated land area compared to the global land cover product. Replacing coarse resolution GMAO climate data with Hawaii-specific high-resolution climate data also reduced statewide GPP estimates by ~8% because of the higher spatial variability of photosynthetically active radiation (PAR) in the Hawaii-specific climate data. The combined use of both Hawaii-specific land cover and high-resolution Hawaii climate data inputs reduced statewide GPP by ~16%, suggesting equal and independent influence on MOD17 GPP estimates. Our sensitivity analyses within a heterogeneous tropical landscape suggest that refined global land cover and climate data sets may contribute to an enhanced MOD17 product at a variety of spatial scales.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0184466","usgsCitation":"Kimball, H.L., Selmants, P., Moreno, A., W, R.S., and Giardina, C.P., 2017, Evaluating the role of land cover and climate uncertainties in computing gross primary production in Hawaiian Island ecosystems: PLoS ONE, v. 12, no. 9, e0184466; 14 p., https://doi.org/10.1371/journal.pone.0184466.","productDescription":"e0184466; 14 p.","ipdsId":"IP-090329","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":461401,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0184466","text":"Publisher Index Page"},{"id":345862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"12","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-08","publicationStatus":"PW","scienceBaseUri":"59c0db1ce4b091459a5f472a","contributors":{"authors":[{"text":"Kimball, Heather L.","contributorId":196550,"corporation":false,"usgs":false,"family":"Kimball","given":"Heather","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":710710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Selmants, Paul 0000-0001-6211-3957 pselmants@usgs.gov","orcid":"https://orcid.org/0000-0001-6211-3957","contributorId":192591,"corporation":false,"usgs":true,"family":"Selmants","given":"Paul","email":"pselmants@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":710709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moreno, Alvaro","contributorId":196551,"corporation":false,"usgs":false,"family":"Moreno","given":"Alvaro","email":"","affiliations":[],"preferred":false,"id":710711,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"W, Running Steve","contributorId":196552,"corporation":false,"usgs":false,"family":"W","given":"Running","email":"","middleInitial":"Steve","affiliations":[],"preferred":false,"id":710712,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Giardina, Christian P. 0000-0002-3431-5073","orcid":"https://orcid.org/0000-0002-3431-5073","contributorId":182695,"corporation":false,"usgs":false,"family":"Giardina","given":"Christian","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":710713,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70190856,"text":"70190856 - 2017 - Sediment unmixing using detrital geochronology","interactions":[],"lastModifiedDate":"2017-09-17T11:23:16","indexId":"70190856","displayToPublicDate":"2017-09-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Sediment unmixing using detrital geochronology","docAbstract":"Sediment mixing within sediment routing systems can exert a strong influence on the preservation of provenance signals that yield insight into the influence of environmental forcings (e.g., tectonism, climate) on the earth’s surface. Here we discuss two approaches to unmixing detrital geochronologic data in an effort to characterize complex changes in the sedimentary record. First we summarize ‘top-down’ mixing, which has been successfully employed in the past to characterize the different fractions of prescribed source distributions (‘parents’) that characterize a derived sample or set of samples (‘daughters’). Second we propose the use of ‘bottom-up’ methods, previously used primarily for grain size distributions, to model parent distributions and the abundances of these parents within a set of daughters. We demonstrate the utility of both top-down and bottom-up approaches to unmixing detrital geochronologic data within a well-constrained sediment routing system in central California. Use of a variety of goodness-of-fit metrics in top-down modeling reveals the importance of considering the range of allowable mixtures over any single best-fit mixture calculation. Bottom-up modeling of 12 daughter samples from beaches and submarine canyons yields modeled parent distributions that are remarkably similar to those expected from the geologic context of the sediment-routing system. In general, mixture modeling has potential to supplement more widely applied approaches in comparing detrital geochronologic data by casting differences between samples as differing proportions of geologically meaningful end-member provenance categories.","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2017.07.044","usgsCitation":"Sharman, G.R., and Johnstone, S., 2017, Sediment unmixing using detrital geochronology: Earth and Planetary Science Letters, v. 477, p. 183-194, https://doi.org/10.1016/j.epsl.2017.07.044.","productDescription":"8 p.","startPage":"183","endPage":"194","ipdsId":"IP-086349","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":345831,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"477","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59bf8993e4b091459a5e0873","contributors":{"authors":[{"text":"Sharman, Glenn R.","contributorId":196537,"corporation":false,"usgs":false,"family":"Sharman","given":"Glenn","email":"","middleInitial":"R.","affiliations":[{"id":34621,"text":"Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA","active":true,"usgs":false}],"preferred":false,"id":710647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnstone, Samuel 0000-0002-3945-2499 sjohnstone@usgs.gov","orcid":"https://orcid.org/0000-0002-3945-2499","contributorId":196536,"corporation":false,"usgs":true,"family":"Johnstone","given":"Samuel","email":"sjohnstone@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":710646,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187402,"text":"ds1050 - 2017 - Results of hydrologic monitoring of a landslide-prone hillslope in Portland’s West Hills, Oregon, 2006–2017","interactions":[],"lastModifiedDate":"2017-09-20T11:40:26","indexId":"ds1050","displayToPublicDate":"2017-09-15T16:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1050","title":"Results of hydrologic monitoring of a landslide-prone hillslope in Portland’s West Hills, Oregon, 2006–2017","docAbstract":"The West Hills of Portland, in the southern Tualatin Mountains, trend northwest along the west side of Portland, Oregon. These silt-mantled mountains receive significant wet-season precipitation and are prone to sliding during wet conditions, occasionally resulting in property damage or casualties. In an effort to develop a baseline for interpretive analysis of the groundwater response to rainfall, an automated monitoring system was installed in 2006 to measure rainfall, pore-water pressure, soil suction, soil-water potential, and volumetric water content at 15-minute intervals. The data show a cyclical pattern of groundwater and moisture content levels—wet from October to May and dry between June and September. Saturated soil conditions tend to last throughout the wet season. These data show the hydrologic response of the monitored area to rainfall and provide insight into the dynamics of rainfall-initiated landsliding. This report details the monitoring methods and presents data collected from January 10, 2006, through January 23, 2017.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1050","collaboration":"Prepared in cooperation with Portland State University","usgsCitation":"Smith, J.B., Godt, J.W., Baum, R.L., Coe, J.A., Ellis, W.L., Jones, E.S., and Burns, S.F., 2017, Results of hydrologic monitoring of a landslide-prone hillslope in Portland’s West Hills, Oregon, 2006–2017: U.S. Geological Survey Data Series 1050, 10 p., https://doi.org/10.3133/ds1050.","productDescription":"Report: iv, 10 p.; Data Release","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-080635","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":345599,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KK98XK","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Results of Hydrologic Monitoring of a Landslide-Prone Hillslope in Portland’s West Hills, Oregon, 2006–2017"},{"id":345590,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1050/coverthb.jpg"},{"id":345591,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1050/ds1050.pdf","text":"Report","size":"1.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1050"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Tualatin Mountains, West Hills of Portland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7372,\n 45.5214\n ],\n [\n -122.7333,\n 45.5214\n ],\n [\n -122.7333,\n 45.5233\n ],\n [\n -122.7372,\n 45.5233\n ],\n [\n -122.7372,\n 45.5214\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geologic Hazards Science Center
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Denver, CO 80225–0046
Several streams used for recreational activities, such as fishing, swimming, and boating, in Chester County, Pennsylvania, are known to have periodic elevated concentrations of fecal coliform bacteria, a type of bacteria used to indicate the potential presence of fecally related pathogens that may pose health risks to humans exposed through water contact. The availability of near real-time continuous stream discharge, turbidity, and other water-quality data for some streams in the county presents an opportunity to use surrogates to estimate near real-time concentrations of fecal coliform (FC) bacteria and thus provide some information about associated potential health risks during recreational use of streams.
The U.S. Geological Survey (USGS), in cooperation with the Chester County Health Department (CCHD) and the Chester County Water Resources Authority (CCWRA), has collected discrete stream samples for analysis of FC concentrations during March–October annually at or near five gaging stations where near real-time continuous data on stream discharge, turbidity, and water temperature have been collected since 2007 (or since 2012 at 2 of the 5 stations). In 2014, the USGS, in cooperation with the CCWRA and CCHD, began to develop regression equations to estimate FC concentrations using available near real-time continuous data. Regression equations included possible explanatory variables of stream discharge, turbidity, water temperature, and seasonal factors calculated using Julian Day with base-10 logarithmic (log) transformations of selected variables.
The regression equations were developed using the data from 2007 to 2015 (101–106 discrete bacteria samples per site) for three gaging stations on Brandywine Creek (West Branch Brandywine Creek at Modena, East Branch Brandywine Creek below Downingtown, and Brandywine Creek at Chadds Ford) and from 2012 to 2015 (37–38 discrete bacteria samples per site) for one station each on French Creek near Phoenixville and White Clay Creek near Strickersville. Fecal coliform bacteria data collected by USGS in 2016 (about nine samples per site) were used to validate the equations. The best-fit regression equations included log turbidity and seasonality factors computed using Julian Day as explanatory variables to estimate log FC concentrations at all five stream sites. The adjusted coefficient of determination for the equations ranged from 0.61 to 0.76, with the strength of the regression equations likely affected in part by the limited amount and variability of FC bacteria data. During summer months, the estimated and measured FC concentrations commonly were greater than the Pennsylvania Department of Environmental Protection established standards of 200 and 400 colonies per 100 milliliters for water contact from May through September at the 5 stream sites, with concentrations typically higher at 2 sites (White Clay Creek and West Branch Brandywine Creek at Modena) than at the other 3 sites. The estimated concentrations of FC bacteria during the summer months commonly were higher than measured concentrations and therefore could be considered cautious estimates of potential human-health risk. Additional water-quality data are needed to maintain and (or) improve the ability of regression equations to estimate FC concentrations by use of surrogate data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175075","collaboration":"Prepared in cooperation with the Chester County Health Department and Chester County Water Resources Authority","usgsCitation":"Senior, L.A., 2017, Estimated fecal coliform bacteria concentrations using near real-time continuous water-quality and streamflow data from five stream sites in Chester County, Pennsylvania, 2007–16 (ver. 1.2, March 2024): U.S. Geological Survey Scientific Investigations Report 2017–5075, 46 p., https://doi.org/10.3133/sir20175075.","productDescription":"Report: x, 46 p.; Appendix 1-5; Data Release","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-084822","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":499300,"rank":10,"type":{"id":36,"text":"NGMDB Index 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Strickersville, Pennsylvania"},{"id":345655,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5075/sir20175075_appendix4.pdf","text":"Appendix 4","size":"348 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Model Archive Summary for Best-Fit Regression Developed to Estimate Fecal Coliform Concentration at Station 01472157; French Creek near Phoenixville, Pennsylvania"},{"id":345654,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5075/sir20175075_appendix3.pdf","text":"Appendix 3","size":"429 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Model Archive Summary for Best-Fit Regression Developed to Estimate Fecal Coliform Concentration at Station 01481000; Brandywine Creek at Chadds Ford, Pennsylvania"},{"id":345653,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5075/sir20175075_appendix2.pdf","text":"Appendix 2","size":"434 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Model Archive Summary for Best-Fit Regression Developed to Estimate Fecal Coliform Concentration at Station 01480870; East Branch Brandywine Creek below Downingtown, Pennsylvania"},{"id":345650,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5075/coverthb4.jpg"},{"id":345652,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5075/sir20175075_appendix1.pdf","text":"Appendix 1","size":"505 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Model Archive Summary for Best-Fit Regression Developed to Estimate Fecal Coliform Concentration at Station 01480617; West Branch Brandywine Creek at Modena, Pennsylvania"},{"id":345651,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5075/sir20175075.pdf","text":"Report","size":"12.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5075"}],"country":"United 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1.0: September 2017; Version 1.1: April 2023; Version 1.2: March 2024","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070-2424
Dam removals with unmanaged sediment releases are good opportunities to learn about channel response to abruptly increased bed material supply. Understanding these events is important because they affect aquatic habitats and human uses of floodplains. A longstanding paradigm in geomorphology holds that response rates to landscape disturbance exponentially decay through time. However, a previous study of the Merrimack Village Dam (MVD) removal on the Souhegan River in New Hampshire, USA, showed that an exponential function poorly described the early geomorphic response. Erosion of impounded sediments there was two-phased. We had an opportunity to quantitatively test the two-phase response model proposed for MVD by extending the record there and comparing it with data from the Simkins Dam removal on the Patapsco River in Maryland, USA. The watershed sizes are the same order of magnitude (102 km2), and at both sites low-head dams were removed (~3–4 m) and ~65 000 m3 of sand-sized sediments were discharged to low-gradient reaches. Analyzing four years of repeat morphometry and sediment surveys at the Simkins site, as well as continuous discharge and turbidity data, we observed the two-phase erosion response described for MVD. In the early phase, approximately 50% of the impounded sediment at Simkins was eroded rapidly during modest flows. After incision to base level and widening, a second phase began when further erosion depended on floods large enough to go over bank and access impounded sediments more distant from the newly-formed channel. Fitting functional forms to the data for both sites, we found that two-phase exponential models with changing decay constants fit the erosion data better than single-phase models. Valley width influences the two-phase erosion responses upstream, but downstream responses appear more closely related to local gradient, sediment re-supply from the upstream impoundments, and base flows.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.4108","usgsCitation":"Collins, M.J., Snyder, N.P., Boardman, G., Banks, W.S., Andrews, M., Baker, M.E., Conlon, M., Gellis, A.C., McClain, S., Miller, A., and Wilcock, P., 2017, Channel response to sediment release: insights from a paired analysis of dam removal: Earth Surface Processes and Landforms, v. 42, no. 11, p. 1636-1651, https://doi.org/10.1002/esp.4108.","productDescription":"16 p.","startPage":"1636","endPage":"1651","ipdsId":"IP-072066","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":347228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Simkins Dam ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.79872512817383,\n 39.264689574787724\n ],\n [\n -76.70053482055663,\n 39.20671884491848\n ],\n [\n -76.69126510620117,\n 39.215630305545304\n ],\n [\n -76.78979873657227,\n 39.27213188522936\n ],\n [\n -76.79872512817383,\n 39.264689574787724\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"11","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-14","publicationStatus":"PW","scienceBaseUri":"59f05121e4b0220bbd9a1d83","contributors":{"authors":[{"text":"Collins, Mathias J.","contributorId":181551,"corporation":false,"usgs":false,"family":"Collins","given":"Mathias","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":714847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snyder, Noah P.","contributorId":198029,"corporation":false,"usgs":false,"family":"Snyder","given":"Noah","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":714848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boardman, Graham","contributorId":198030,"corporation":false,"usgs":false,"family":"Boardman","given":"Graham","email":"","affiliations":[],"preferred":false,"id":714849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Banks, William S. 0000-0002-2090-8708 wsbanks@usgs.gov","orcid":"https://orcid.org/0000-0002-2090-8708","contributorId":2349,"corporation":false,"usgs":true,"family":"Banks","given":"William","email":"wsbanks@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714850,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andrews, Mary","contributorId":198031,"corporation":false,"usgs":false,"family":"Andrews","given":"Mary","email":"","affiliations":[],"preferred":false,"id":714851,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baker, Matthew E.","contributorId":42889,"corporation":false,"usgs":true,"family":"Baker","given":"Matthew","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":715151,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conlon, Maricate","contributorId":198032,"corporation":false,"usgs":false,"family":"Conlon","given":"Maricate","email":"","affiliations":[],"preferred":false,"id":714852,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714846,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McClain, Serena","contributorId":198033,"corporation":false,"usgs":false,"family":"McClain","given":"Serena","email":"","affiliations":[],"preferred":false,"id":714853,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Miller, Andrew","contributorId":196361,"corporation":false,"usgs":false,"family":"Miller","given":"Andrew","affiliations":[],"preferred":false,"id":714854,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wilcock, Peter","contributorId":198034,"corporation":false,"usgs":false,"family":"Wilcock","given":"Peter","affiliations":[],"preferred":false,"id":714855,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70190809,"text":"70190809 - 2017 - The state of the world’s mangroves in the 21st century under climate change","interactions":[],"lastModifiedDate":"2017-10-16T14:19:34","indexId":"70190809","displayToPublicDate":"2017-09-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"The state of the world’s mangroves in the 21st century under climate change","docAbstract":"Concerted mangrove research and rehabilitation efforts over the last several decades have prompted a better understanding of the important ecosystem attributes worthy of protection and a better conservation ethic toward mangrove wetlands globally. While mangroves continue to be degraded and lost in specific regions, conservation initiatives, rehabilitation efforts, natural regeneration, and climate range expansion have promoted gains in other areas, ultimately serving to curb the high mangrove habitat loss statistics from the doom and gloom of the 1980s. We highlight those trends in this article and introduce this special issue of Hydrobiologia dedicated to the important and recurring Mangrove and Macrobenthos Meeting. This collection of papers represents studies presented at the fourth such meeting (MMM4) held in St. Augustine, Florida, USA, on July 18–22, 2016. Our intent is to provide a balanced message about the global state of mangrove wetlands by describing recent reductions in net mangrove area losses and highlighting primary research studies presented at MMM4 through a collection of papers. These papers serve not only to highlight on-going global research advancements, but also provide an overview of the vast amount of data on mangrove ecosystem ecology, biology and rehabilitation that emphasizes the uniqueness of the mangrove community.
","language":"English","publisher":"Springer","doi":"10.1007/s10750-017-3331-z","usgsCitation":"Feller, I.C., Friess, D., Krauss, K.W., and Lewis, R.R., 2017, The state of the world’s mangroves in the 21st century under climate change: Hydrobiologia, v. 803, no. 1, p. 1-12, https://doi.org/10.1007/s10750-017-3331-z.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-086013","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469525,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10750-017-3331-z","text":"Publisher Index Page"},{"id":345780,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"803","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-13","publicationStatus":"PW","scienceBaseUri":"59bb9529e4b091459a57815e","contributors":{"authors":[{"text":"Feller, Ilka C.","contributorId":196519,"corporation":false,"usgs":false,"family":"Feller","given":"Ilka","email":"","middleInitial":"C.","affiliations":[{"id":28135,"text":"Smithsonian Environmental Research Center, Edgewater, MD","active":true,"usgs":false}],"preferred":false,"id":710523,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Friess, Daniel A.","contributorId":35454,"corporation":false,"usgs":false,"family":"Friess","given":"Daniel A.","affiliations":[{"id":25407,"text":"Department of Geography, National University of Singapore","active":true,"usgs":false}],"preferred":false,"id":710524,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":710522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lewis, Roy R. III","contributorId":196521,"corporation":false,"usgs":false,"family":"Lewis","given":"Roy","suffix":"III","email":"","middleInitial":"R.","affiliations":[{"id":34614,"text":"Lewis Environmental Services, Salt Springs, FL","active":true,"usgs":false}],"preferred":false,"id":710525,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190789,"text":"70190789 - 2017 - Novel analyses of long-term data provide a scientific basis for chlorophyll-a thresholds in San Francisco Bay","interactions":[],"lastModifiedDate":"2017-09-14T11:00:17","indexId":"70190789","displayToPublicDate":"2017-09-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Novel analyses of long-term data provide a scientific basis for chlorophyll-a thresholds in San Francisco Bay","docAbstract":"San Francisco Bay (SFB), USA, is highly enriched in nitrogen and phosphorus, but has been resistant to the classic symptoms of eutrophication associated with over-production of phytoplankton. Observations in recent years suggest that this resistance may be weakening, shown by: significant increases of chlorophyll-a (chl-a) and decreases of dissolved oxygen (DO), common occurrences of phytoplankton taxa that can form Harmful Algal Blooms (HAB), and algal toxins in water and mussels reaching levels of concern. As a result, managers now ask: what levels of chl-a in SFB constitute tipping points of phytoplankton biomass beyond which water quality will become degraded, requiring significant nutrient reductions to avoid impairments? We analyzed data for DO, phytoplankton species composition, chl-a, and algal toxins to derive quantitative relationships between three indicators (HAB abundance, toxin concentrations, DO) and chl-a. Quantile regressions relating HAB abundance and DO to chl-a were significant, indicating SFB is at increased risk of adverse HAB and low DO levels if chl-a continues to increase. Conditional probability analysis (CPA) showed chl-a of 13 mg m−3 as a “protective” threshold below which probabilities for exceeding alert levels for HAB abundance and toxins were reduced. This threshold was similar to chl-a of 13–16 mg m−3 that would meet a SFB-wide 80% saturation Water Quality Criterion (WQC) for DO. Higher “at risk” chl-a thresholds from 25 to 40 mg m−3 corresponded to 0.5 probability of exceeding alert levels for HAB abundance, and for DO below a WQC of 5.0 mg L−1 designated for lower South Bay (LSB) and South Bay (SB). We submit these thresholds as a basis to assess eutrophication status of SFB and to inform nutrient management actions. This approach is transferrable to other estuaries to derive chl-a thresholds protective against eutrophication.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2017.07.009","usgsCitation":"Sutula, M., Kudela, R., Hagy, J.D., Harding, L.W., Senn, D., Cloern, J.E., Bricker, S.B., Beck, M.W., and Berg, G.M., 2017, Novel analyses of long-term data provide a scientific basis for chlorophyll-a thresholds in San Francisco Bay: Estuarine, Coastal and Shelf Science, v. 197, p. 107-118, https://doi.org/10.1016/j.ecss.2017.07.009.","productDescription":"12 p.","startPage":"107","endPage":"118","ipdsId":"IP-071224","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":469523,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6134865","text":"Publisher Index Page"},{"id":345755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.62115478515625,\n 37.385435182627226\n ],\n [\n -121.35498046875,\n 37.385435182627226\n ],\n [\n -121.35498046875,\n 38.199338565983844\n ],\n [\n -122.62115478515625,\n 38.199338565983844\n ],\n [\n -122.62115478515625,\n 37.385435182627226\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"197","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59bb952de4b091459a578178","contributors":{"authors":[{"text":"Sutula, Martha","contributorId":191008,"corporation":false,"usgs":false,"family":"Sutula","given":"Martha","email":"","affiliations":[],"preferred":false,"id":710406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kudela, Raphael","contributorId":196461,"corporation":false,"usgs":false,"family":"Kudela","given":"Raphael","affiliations":[],"preferred":false,"id":710407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagy, James","contributorId":196462,"corporation":false,"usgs":false,"family":"Hagy","given":"James","affiliations":[],"preferred":false,"id":710408,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harding, Lawrence W. Jr.","contributorId":196465,"corporation":false,"usgs":false,"family":"Harding","given":"Lawrence","suffix":"Jr.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":710416,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Senn, David","contributorId":177368,"corporation":false,"usgs":false,"family":"Senn","given":"David","affiliations":[],"preferred":false,"id":710409,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":710405,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bricker, Suzanne B.","contributorId":64555,"corporation":false,"usgs":false,"family":"Bricker","given":"Suzanne","email":"","middleInitial":"B.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":710410,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Berg, Gry Mine","contributorId":196466,"corporation":false,"usgs":false,"family":"Berg","given":"Gry","email":"","middleInitial":"Mine","affiliations":[],"preferred":false,"id":710412,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Beck, Marcus W.","contributorId":172025,"corporation":false,"usgs":false,"family":"Beck","given":"Marcus","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":710413,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70190806,"text":"70190806 - 2017 - Holistic assessment of occurrence and fate of metolachlor within environmental compartments of agricultural watersheds","interactions":[],"lastModifiedDate":"2017-09-20T10:04:44","indexId":"70190806","displayToPublicDate":"2017-09-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Holistic assessment of occurrence and fate of metolachlor within environmental compartments of agricultural watersheds","docAbstract":"Background: Metolachlor [(RS)-2-Chloro-N-(2-ethyl-6-methyl-phenyl)-N-(1-methoxypropan-2-yl)acetamide] and two degradates (metolachlor ethane-sulfonic acid and metolachlor oxanilic acid) are commonly observed in surface and groundwater. The behavior and fate of these compounds were examined over a 12-year period in seven agricultural watersheds in the United States. They were quantified in air, rain, streams, overland flow, groundwater, soil water, subsurface drain water, and water at the stream/groundwater interface. The compounds were frequently detected in surface and groundwater associated with agricultural areas. A mass budget approach, based on all available data from the study and literature, was used to determine a percentage-wise generalized distribution and fate of applied parent metolachlor in typical agricultural environments.
Results: In these watersheds, about 90% of applied metolachlor was taken up by plants or degraded, 10% volatilized, and 0.3% returned as rainfall. One percent was transported to surface water, while an equal amount infiltrated into the unsaturated zone soil water. < 0.02% reached the groundwater. Subsurface flow paths resulted in greater degradation of metolachlor because degradation reactions had more time to proceed.
Conclusions: An understanding of the residence times of water in the different environmental compartments, and the important processes affecting metolachlor as it is transported along flowpaths among the environmental compartments allows for a degree of predictability of metolachlor's fate. Degradates with long half-lives can be used (in a limited capacity) as tracers of metolachlor, because of their persistence and widespread occurrence in the environment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.08.154","usgsCitation":"Rose, C.E., Coupe, R.H., Capel, P.D., and Webb, R.M., 2017, Holistic assessment of occurrence and fate of metolachlor within environmental compartments of agricultural watersheds: Science of the Total Environment, v. 612, p. 708-719, https://doi.org/10.1016/j.scitotenv.2017.08.154.","productDescription":"12 p.","startPage":"708","endPage":"719","ipdsId":"IP-077291","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":345776,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"612","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59bb952ce4b091459a578170","contributors":{"authors":[{"text":"Rose, Claire E. 0000-0002-5519-3538 cerose@usgs.gov","orcid":"https://orcid.org/0000-0002-5519-3538","contributorId":2317,"corporation":false,"usgs":true,"family":"Rose","given":"Claire","email":"cerose@usgs.gov","middleInitial":"E.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coupe, Richard H. 0000-0001-8679-1015 rhcoupe@usgs.gov","orcid":"https://orcid.org/0000-0001-8679-1015","contributorId":551,"corporation":false,"usgs":true,"family":"Coupe","given":"Richard","email":"rhcoupe@usgs.gov","middleInitial":"H.","affiliations":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Capel, Paul D. 0000-0003-1620-5185 capel@usgs.gov","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":1002,"corporation":false,"usgs":true,"family":"Capel","given":"Paul","email":"capel@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webb, Richard M. 0000-0001-9531-2207 rmwebb@usgs.gov","orcid":"https://orcid.org/0000-0001-9531-2207","contributorId":1570,"corporation":false,"usgs":true,"family":"Webb","given":"Richard","email":"rmwebb@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710483,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190802,"text":"70190802 - 2017 - Assessing coastal wetland vulnerability to sea-level rise along the northern Gulf of Mexico coast: Gaps and opportunities for developing a coordinated regional sampling network","interactions":[],"lastModifiedDate":"2017-09-14T15:55:52","indexId":"70190802","displayToPublicDate":"2017-09-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Assessing coastal wetland vulnerability to sea-level rise along the northern Gulf of Mexico coast: Gaps and opportunities for developing a coordinated regional sampling network","docAbstract":"Coastal wetland responses to sea-level rise are greatly influenced by biogeomorphic processes that affect wetland surface elevation. Small changes in elevation relative to sea level can lead to comparatively large changes in ecosystem structure, function, and stability. The surface elevation table-marker horizon (SET-MH) approach is being used globally to quantify the relative contributions of processes affecting wetland elevation change. Historically, SET-MH measurements have been obtained at local scales to address site-specific research questions. However, in the face of accelerated sea-level rise, there is an increasing need for elevation change network data that can be incorporated into regional ecological models and vulnerability assessments. In particular, there is a need for long-term, high-temporal resolution data that are strategically distributed across ecologically-relevant abiotic gradients. Here, we quantify the distribution of SET-MH stations along the northern Gulf of Mexico coast (USA) across political boundaries (states), wetland habitats, and ecologically-relevant abiotic gradients (i.e., gradients in temperature, precipitation, elevation, and relative sea-level rise). Our analyses identify areas with high SET-MH station densities as well as areas with notable gaps. Salt marshes, intermediate elevations, and colder areas with high rainfall have a high number of stations, while salt flat ecosystems, certain elevation zones, the mangrove-marsh ecotone, and hypersaline coastal areas with low rainfall have fewer stations. Due to rapid rates of wetland loss and relative sea-level rise, the state of Louisiana has the most extensive SET-MH station network in the region, and we provide several recent examples where data from Louisiana’s network have been used to assess and compare wetland vulnerability to sea-level rise. Our findings represent the first attempt to examine spatial gaps in SET-MH coverage across abiotic gradients. Our analyses can be used to transform a broadly disseminated and unplanned collection of SET-MH stations into a coordinated and strategic regional network. This regional network would provide data for predicting and preparing for the responses of coastal wetlands to accelerated sea-level rise and other aspects of global change.
","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0183431","usgsCitation":"Osland, M.J., Griffith, K.T., Larriviere, J., Feher, L.C., Cahoon, D.R., Enwright, N.M., Oster, D.A., Tirpak, J.M., Woodrey, M.S., Collini, R.C., Baustian, J.J., Breithaupt, J.L., Cherry, J., Conrad, J.R., Cormier, N., Coronado-Molina, C.A., Donoghue, J.F., Graham, S.A., Harper, J.W., Hester, M.W., Howard, R.J., Krauss, K.W., Kroes, D., Lane, R.R., McKee, K.L., Mendelssohn, I.A., Middleton, B.A., Moon, J.A., Piazza, S., Rankin, N.M., Sklar, F.H., Steyer, G.D., Swanson, K.M., Swarzenski, C.M., Vervaeke, W., Willis, J.M., and Van Wilson, K., 2017, Assessing coastal wetland vulnerability to sea-level rise along the northern Gulf of Mexico coast: Gaps and opportunities for developing a coordinated regional sampling network: PLoS ONE, v. 12, no. 9, Article e0183431; 23 p., https://doi.org/10.1371/journal.pone.0183431.","productDescription":"Article e0183431; 23 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,{"id":70194618,"text":"70194618 - 2017 - Effects of surgically implanted transmitters on reproduction and survival in mallards","interactions":[],"lastModifiedDate":"2017-12-08T10:33:57","indexId":"70194618","displayToPublicDate":"2017-09-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Effects of surgically implanted transmitters on reproduction and survival in mallards","docAbstract":"Abdominally implanted radiotransmitters have been widely used in studies of waterbird ecology; however, the longer handling times and invasiveness of surgical implantation raise important concerns about animal welfare and potential effects on data quality. Although it is difficult to assess effects of handling and marking wild animals by comparing them with unmarked controls, insights can often be obtained by evaluating variation in handling or marking techniques. Here, we used data from 243 female mallards (Anas platyrhynchos) and mallard–grey duck hybrids (A. platyrhynchos × A. superciliosa) equipped with fully encapsulated abdominally implanted radiotransmitters from 2 study sites in New Zealand during 2014–2015 to assess potential marking effects. We evaluated survival, dispersal, and reproductive effort (e.g., breeding propensity, nest initiation date, clutch size) in response to 3 different attributes of handling duration and procedures: 1) processing time, including presurgery banding, measurements, and blood sampling of unanaesthetized birds; 2) surgery time from initiation to cessation of anesthetic; and 3) total holding time from first capture until release. We found no evidence that female survival, dispersal probability, or reproductive effort were negatively affected by holding, processing, or surgery time and concluded that we collected reliable data without compromising animal welfare. Our results support previous research that techniques using fully encapsulated abdominal-implant radiotransmitters are suitable to enable researchers to obtain reliable estimates of reproductive performance and survival.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.809","usgsCitation":"Sheppard, J., Arnold, T.W., Amundson, C.L., and Klee, D., 2017, Effects of surgically implanted transmitters on reproduction and survival in mallards: Wildlife Society Bulletin, v. 41, no. 3, p. 597-604, https://doi.org/10.1002/wsb.809.","productDescription":"8 p.","startPage":"597","endPage":"604","ipdsId":"IP-076756","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":469524,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doaj.org/article/aca8693eb8bb4dda98863dc3669b1e0b","text":"Publisher Index Page"},{"id":349877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","volume":"41","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-09","publicationStatus":"PW","scienceBaseUri":"5a60fb51e4b06e28e9c22f37","contributors":{"authors":[{"text":"Sheppard, Jennifer","contributorId":201215,"corporation":false,"usgs":false,"family":"Sheppard","given":"Jennifer","affiliations":[],"preferred":false,"id":724644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arnold, Todd W.","contributorId":36058,"corporation":false,"usgs":false,"family":"Arnold","given":"Todd","email":"","middleInitial":"W.","affiliations":[{"id":12644,"text":"University of Minnesota, St. Paul","active":true,"usgs":false}],"preferred":false,"id":724645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amundson, Courtney L. 0000-0002-0166-7224 camundson@usgs.gov","orcid":"https://orcid.org/0000-0002-0166-7224","contributorId":4833,"corporation":false,"usgs":true,"family":"Amundson","given":"Courtney","email":"camundson@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":724643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klee, David","contributorId":201217,"corporation":false,"usgs":false,"family":"Klee","given":"David","email":"","affiliations":[],"preferred":false,"id":724647,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190153,"text":"ds1062 - 2017 - A reservoir morphology database for the conterminous United States","interactions":[],"lastModifiedDate":"2017-09-13T13:38:23","indexId":"ds1062","displayToPublicDate":"2017-09-13T12:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1062","title":"A reservoir morphology database for the conterminous United States","docAbstract":"The U.S. Geological Survey, in cooperation with the Reservoir Fisheries Habitat Partnership, combined multiple national databases to create one comprehensive national reservoir database and to calculate new morphological metrics for 3,828 reservoirs. These new metrics include, but are not limited to, shoreline development index, index of basin permanence, development of volume, and other descriptive metrics based on established morphometric formulas. The new database also contains modeled chemical and physical metrics. Because of the nature of the existing databases used to compile the Reservoir Morphology Database and the inherent missing data, some metrics were not populated. One comprehensive database will assist water-resource managers in their understanding of local reservoir morphology and water chemistry characteristics throughout the continental United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1062","collaboration":"Prepared in cooperation with the Reservoir Fisheries Habitat Partnership","usgsCitation":"Rodgers, K.D., 2017, A reservoir morphology database for the conterminous United States: U.S. Geological Survey Data Series 1062, https://doi.org/10.3133/ds1062.","productDescription":"HTML Document; Data Release; Appendix 1","onlineOnly":"Y","ipdsId":"IP-071730","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":345577,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GF0RQZ","text":"USGS data release","description":"USGS data release","linkHelpText":"A Reservoir Morphology Database for the Conterminous United States"},{"id":345576,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1062/index.html","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DS 1062 REport HTML"},{"id":345693,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1062/images/coverthb.png"}],"contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
401 Hardin Road
Little Rock, AR 72211
http://ar.water.usgs.gov
Deep-sea coral and sponge ecosystems are widespread throughout most of Alaska’s marine waters. In some places, such as the central and western Aleutian Islands, deep-sea coral and sponge resources can be extremely diverse and may rank among the most abundant deep-sea coral and sponge communities in the world. Many different species of fishes and invertebrates are associated with deep-sea coral and sponge communities in Alaska. Because of their biology, these benthic invertebrates are potentially impacted by climate change and ocean acidification. Deepsea coral and sponge ecosystems are also vulnerable to the effects of commercial fishing activities. Because of the size and scope of Alaska’s continental shelf and slope, the vast majority of the area has not been visually surveyed for deep-sea corals and sponges. NOAA’s Deep Sea Coral Research and Technology Program (DSCRTP) sponsored a field research program in the Alaska region between 2012–2015, referred to hereafter as the Alaska Initiative. The priorities for Alaska were derived from ongoing data needs and objectives identified by the DSCRTP, the North Pacific Fishery Management Council (NPFMC), and Essential Fish Habitat-Environmental Impact Statement (EFH-EIS) process.
This report presents the results of 15 projects conducted using DSCRTP funds from 2012-2015. Three of the projects conducted as part of the Alaska deep-sea coral and sponge initiative included dedicated at-sea cruises and fieldwork spread across multiple years. These projects were the eastern Gulf of Alaska Primnoa pacifica study, the Aleutian Islands mapping study, and the Gulf of Alaska fish productivity study. In all, there were nine separate research cruises carried out with a total of 109 at-sea days conducting research. The remaining projects either used data and samples collected by the three major fieldwork projects or were piggy-backed onto existing research programs at the Alaska Fisheries Science Center (AFSC).
","language":"English","publisher":"National Oceanic and Atmospheric Administration","usgsCitation":"Rooper, C., Stone, R.P., Etnoyer, P., Conrath, C., Reynolds, J., Greene, H.G., Williams, B., Salgado, E., Morrison, C.L., Waller, R.G., and Demopoulos, A.W., 2017, Deep-sea coral research and technology program: Alaska deep-sea coral and sponge initiative final report: NOAA Technical Memorandum NMFS-OHC-2, x, 65 p.","productDescription":"x, 65 p.","numberOfPages":"80","ipdsId":"IP-090361","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":345710,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":345701,"type":{"id":11,"text":"Document"},"url":"https://spo.nmfs.noaa.gov/sites/default/files/TM-OHC-2-FINAL.pdf"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59ba43b6e4b091459a56299f","contributors":{"authors":[{"text":"Rooper, Chris","contributorId":196431,"corporation":false,"usgs":false,"family":"Rooper","given":"Chris","affiliations":[],"preferred":false,"id":710321,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stone, Robert P.","contributorId":190569,"corporation":false,"usgs":false,"family":"Stone","given":"Robert","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":710322,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Etnoyer, Peter","contributorId":196432,"corporation":false,"usgs":false,"family":"Etnoyer","given":"Peter","affiliations":[],"preferred":false,"id":710323,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrath, Christina","contributorId":196433,"corporation":false,"usgs":false,"family":"Conrath","given":"Christina","email":"","affiliations":[],"preferred":false,"id":710324,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reynolds, Jennifer","contributorId":196434,"corporation":false,"usgs":false,"family":"Reynolds","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":710325,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Greene, H. Gary","contributorId":139063,"corporation":false,"usgs":false,"family":"Greene","given":"H.","email":"","middleInitial":"Gary","affiliations":[{"id":12639,"text":"Moss Landing Marine Labs","active":true,"usgs":false}],"preferred":false,"id":710326,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Williams, Branwen","contributorId":152572,"corporation":false,"usgs":false,"family":"Williams","given":"Branwen","email":"","affiliations":[],"preferred":false,"id":710327,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Salgado, Enrique","contributorId":196435,"corporation":false,"usgs":false,"family":"Salgado","given":"Enrique","email":"","affiliations":[],"preferred":false,"id":710328,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Morrison, Cheryl L. 0000-0001-9425-691X cmorrison@usgs.gov","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":146488,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","email":"cmorrison@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":710320,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Waller, Rhian G.","contributorId":195852,"corporation":false,"usgs":false,"family":"Waller","given":"Rhian","email":"","middleInitial":"G.","affiliations":[{"id":16143,"text":"University of Hawaii at Manoa, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":710329,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":196216,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":710330,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70190760,"text":"70190760 - 2017 - Fine-resolution repeat topographic surveying of dryland landscapes using UAS-based structure-from-motion photogrammetry: Assessing accuracy and precision against traditional ground-based erosion measurements","interactions":[],"lastModifiedDate":"2020-10-03T15:59:14.452055","indexId":"70190760","displayToPublicDate":"2017-09-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Fine-resolution repeat topographic surveying of dryland landscapes using UAS-based structure-from-motion photogrammetry: Assessing accuracy and precision against traditional ground-based erosion measurements","title":"Fine-resolution repeat topographic surveying of dryland landscapes using UAS-based structure-from-motion photogrammetry: Assessing accuracy and precision against traditional ground-based erosion measurements","docAbstract":"Structure-from-motion (SfM) photogrammetry from unmanned aerial system (UAS) imagery is an emerging tool for repeat topographic surveying of dryland erosion. These methods are particularly appealing due to the ability to cover large landscapes compared to field methods and at reduced costs and finer spatial resolution compared to airborne laser scanning. Accuracy and precision of high-resolution digital terrain models (DTMs) derived from UAS imagery have been explored in many studies, typically by comparing image coordinates to surveyed check points or LiDAR datasets. In addition to traditional check points, this study compared 5 cm resolution DTMs derived from fixed-wing UAS imagery with a traditional ground-based method of measuring soil surface change called erosion bridges. We assessed accuracy by comparing the elevation values between DTMs and erosion bridges along thirty topographic transects each 6.1 m long. Comparisons occurred at two points in time (June 2014, February 2015) which enabled us to assess vertical accuracy with 3314 data points and vertical precision (i.e., repeatability) with 1657 data points. We found strong vertical agreement (accuracy) between the methods (RMSE 2.9 and 3.2 cm in June 2014 and February 2015, respectively) and high vertical precision for the DTMs (RMSE 2.8 cm). Our results from comparing SfM-generated DTMs to check points, and strong agreement with erosion bridge measurements suggests repeat UAS imagery and SfM processing could replace erosion bridges for a more synoptic landscape assessment of shifting soil surfaces for some studies. However, while collecting the UAS imagery and generating the SfM DTMs for this study was faster than collecting erosion bridge measurements, technical challenges related to the need for ground control networks and image processing requirements must be addressed before this technique could be applied effectively to large landscapes.
","language":"English","publisher":"MPDI AG (Multidisciplinary Digital Publishing Institute)","publisherLocation":"Basel, Switzerland","doi":"10.3390/rs9050437","usgsCitation":"Gillian, J.K., Karl, J.W., Elaksher, A., and Duniway, M.C., 2017, Fine-resolution repeat topographic surveying of dryland landscapes using UAS-based structure-from-motion photogrammetry: Assessing accuracy and precision against traditional ground-based erosion measurements: Remote Sensing, v. 9, no. 5, 437, 24 p., https://doi.org/10.3390/rs9050437.","productDescription":"437, 24 p.","numberOfPages":"24","ipdsId":"IP-086200","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469526,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs9050437","text":"Publisher Index Page"},{"id":345713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-03","publicationStatus":"PW","scienceBaseUri":"59ba43b5e4b091459a56299a","contributors":{"authors":[{"text":"Gillian, Jeffrey K.","contributorId":196437,"corporation":false,"usgs":false,"family":"Gillian","given":"Jeffrey","email":"","middleInitial":"K.","affiliations":[{"id":7045,"text":"USDA-ARS Jornada Experimental Range ","active":true,"usgs":false}],"preferred":false,"id":710348,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karl, Jason W.","contributorId":191703,"corporation":false,"usgs":false,"family":"Karl","given":"Jason","email":"","middleInitial":"W.","affiliations":[{"id":7045,"text":"USDA-ARS Jornada Experimental Range ","active":true,"usgs":false}],"preferred":false,"id":710349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elaksher, Ahmed","contributorId":196438,"corporation":false,"usgs":false,"family":"Elaksher","given":"Ahmed","email":"","affiliations":[{"id":34578,"text":"Civil Engineering Department, College of Engineering, California Polytechnical State University","active":true,"usgs":false}],"preferred":false,"id":710350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":710347,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190709,"text":"70190709 - 2017 - Neotectonics of interior Alaska and the late Quaternary slip rate along the Denali fault system","interactions":[],"lastModifiedDate":"2023-11-06T17:00:22.889375","indexId":"70190709","displayToPublicDate":"2017-09-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Neotectonics of interior Alaska and the late Quaternary slip rate along the Denali fault system","docAbstract":"The neotectonics of southern Alaska (USA) are characterized by a several hundred kilometers–wide zone of dextral transpressional that spans the Alaska Range. The Denali fault system is the largest active strike-slip fault system in interior Alaska, and it produced a Mw 7.9 earthquake in 2002. To evaluate the late Quaternary slip rate on the Denali fault system, we collected samples for cosmogenic surface exposure dating from surfaces offset by the fault system. This study includes data from 107 samples at 19 sites, including 7 sites we previously reported, as well as an estimated slip rate at another site. We utilize the interpreted surface ages to provide estimated slip rates. These new slip rate data confirm that the highest late Quaternary slip rate is ∼13 mm/yr on the central Denali fault near its intersection with the eastern Denali and the Totschunda faults, with decreasing slip rate both to the east and west. The slip rate decreases westward along the central and western parts of the Denali fault system to 5 mm/yr over a length of ∼575 km. An additional site on the eastern Denali fault near Kluane Lake, Yukon, implies a slip rate of ∼2 mm/yr, based on geological considerations. The Totschunda fault has a maximum slip rate of ∼9 mm/yr. The Denali fault system is transpressional and there are active thrust faults on both the north and south sides of it. We explore four geometric models for southern Alaska tectonics to explain the slip rates along the Denali fault system and the active fault geometries: rotation, indentation, extrusion, and a combination of the three. We conclude that all three end-member models have strengths and shortcomings, and a combination of rotation, indentation, and extrusion best explains the slip rate observations.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01447.1","usgsCitation":"Haeussler, P.J., Matmon, A., Schwartz, D.P., and Seitz, G.G., 2017, Neotectonics of interior Alaska and the late Quaternary slip rate along the Denali fault system: Geosphere, v. 13, no. 5, p. 1-19, https://doi.org/10.1130/GES01447.1.","productDescription":"19 p.","startPage":"1","endPage":"19","ipdsId":"IP-090357","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":469528,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01447.1","text":"Publisher Index Page"},{"id":345684,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155,\n 62\n ],\n [\n -135,\n 62\n ],\n [\n -135,\n 64\n ],\n [\n -155,\n 64\n ],\n [\n -155,\n 62\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-09","publicationStatus":"PW","scienceBaseUri":"59ba43b8e4b091459a5629af","contributors":{"authors":[{"text":"Haeussler, Peter J. 0000-0002-1503-6247 pheuslr@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":503,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter","email":"pheuslr@usgs.gov","middleInitial":"J.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":710250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matmon, Ari","contributorId":196405,"corporation":false,"usgs":false,"family":"Matmon","given":"Ari","email":"","affiliations":[],"preferred":false,"id":710251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwartz, David P. 0000-0001-5193-9200 dschwartz@usgs.gov","orcid":"https://orcid.org/0000-0001-5193-9200","contributorId":1940,"corporation":false,"usgs":true,"family":"Schwartz","given":"David","email":"dschwartz@usgs.gov","middleInitial":"P.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":710252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seitz, Gordon G.","contributorId":139062,"corporation":false,"usgs":false,"family":"Seitz","given":"Gordon","email":"","middleInitial":"G.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":710253,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188026,"text":"sir20175047 - 2017 - Loads and yields of deicing compounds and total phosphorus in the Cambridge drinking-water source area, Massachusetts, water years 2009–15","interactions":[],"lastModifiedDate":"2022-11-02T14:10:12.709223","indexId":"sir20175047","displayToPublicDate":"2017-09-12T12:00:00","publicationYear":"2017","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":"2017-5047","title":"Loads and yields of deicing compounds and total phosphorus in the Cambridge drinking-water source area, Massachusetts, water years 2009–15","docAbstract":"The source water area for the drinking-water supply of the city of Cambridge, Massachusetts, encompasses major transportation corridors, as well as large areas of light industrial, commercial, and residential land use. Because of the large amount of roadway in the drinking-water source area, the Cambridge water supply is affected by the usage of deicing compounds and by other constituents that are flushed from such impervious areas. The U.S. Geological Survey (USGS) has monitored surface-water quality in the Cambridge Reservoir and Stony Brook Reservoir Basins, which compose the drinking-water source area, since 1997 (water year 1998) through continuous monitoring and the collection of stream-flow samples.
In a study conducted by the USGS, in cooperation with the City of Cambridge Water Department, concentrations and loads of calcium (Ca), chloride (Cl), magnesium (Mg), sodium (Na), and sulfate (SO4) were estimated from continuous records of specific conductance and streamflow for streams and tributaries at 10 continuous water-quality monitoring stations. These data were used to characterize current (2015) water-quality conditions, estimate loads and yields, and describe trends in Cl and Na in the tributaries and main-stem streams in the Cambridge Reservoir and Stony Brook Reservoir Basins. These data also were used to describe how stream-water quality is related to various basin characteristics and provide information to guide future management of the drinking-water source area.
Water samples from 2009–15 were analyzed for physical properties and concentrations of Ca, Cl, Mg, Na, potassium (K), SO4, and total phosphorus (TP). Values of physical properties and constituent concentrations varied widely, particularly in composite samples of stormflow from tributaries that have high percentages of constructed impervious areas. Median concentrations of Ca, Cl, Mg, Na, and K in samples collected from the tributaries in the Cambridge Reservoir Basin (27.2, 273, 4.7, 154.5, and 2.8 milligrams per liter (mg/L), respectively) were higher than those for the Stony Brook Reservoir Basin (22.2, 128, 4.3, 77.1, and 2.5, respectively). Differences between tributary samples for concentrations of Cl and Na were related to the percentage of developed land and constructed impervious area in the drinking-water source area. Median concentrations of SO4 in samples collected from the tributaries in the Cambridge Reservoir Basin (10.7 mg/L) were lower than those for the Stony Brook Reservoir Basin (18.0 mg/L).
Concentrations of dissolved Cl and Na in samples and those concentrations estimated from continuous records of specific conductance (particularly during base flow) often were greater than the U.S. Environmental Protection Agency (EPA) secondary drinking-water standard for Cl (250 mg/L), the chronic aquatic-life guideline for Cl (230 mg/L), and the Massachusetts Department of Environmental Protection drinking-water guideline for Na (20 mg/L). Concentrations of TP (range from 0.008 to 0.69 mg/L in all subbasins) in tributary samples did not differ substantially between the Cambridge Reservoir and Stony Brook Reservoir Basins. About one-half of the concentrations of TP in samples collected during water years 2013–15 exceeded the EPA proposed reference concentration of 0.024 mg/L.
For most tributaries, about 70 percent of the annual loads of Ca, Cl, Mg, Na, and SO4 were associated with base flow. Concentrations of major ions were negatively correlated with streamflow, indicating that these constituents were diluted during stormflow and tend to increase during the summer when streamflow is low. In contrast, between 57 and 92 percent of the annual load for TP was transported during stormflows.
Mean annual yields of Ca, Cl, Mg, Na, and SO4 in the drinking-water source area were 13, 75, 2.6, 40, and 6.9 metric tons per square kilometer, respectively, for water years 2009–15. The mean annual yield of TP in the drinking-water source area for water years 2013–15 was 0.012 metric tons per square kilometer. Yields for major ions and TP were highest in tributary subbasins adjacent to Interstate 95.
Temporal trends in mean annual concentrations for Cl and Na were not significant for water years 1998‒2015 (period of record by the USGS) for the outlet of the Cambridge Reservoir and for the main stem of Stony Brook downstream from the reservoir. Median values of base-flow concentrations of TP at three stations were higher for samples collected during base-flow conditions during water years 2005–7 than for samples collected during water years 2013–15. However, the results were not significant for statistical tests between concentrations in samples collected during storms for the same periods, indicating that the quality of stormwater remains similar.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175047","collaboration":"Prepared in cooperation with Cambridge [Massachusetts] Water Department","productDescription":"x, 52 p.","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-078822","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":345074,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5047/sir20175047.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5047"},{"id":345073,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5047/coverthb.jpg"}],"country":"United States","state":"Massachusetts","city":"Cambridge","otherGeospatial":"Cambridge Reservoir and Stony Brook Reservoir basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.3167,\n 42.433\n ],\n [\n -71.3167,\n 42.333\n ],\n [\n -71.133,\n 42.333\n ],\n [\n -71.133,\n 42.433\n ],\n [\n -71.3167,\n 42.433\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
We recently analyzed long-term (1951–2011) continental band-recovery data from lesser scaup (Aythya affinis) and demonstrated that harvest rates declined through time, but annual survival rates exhibited no such trends; moreover, annual harvest and survival rates were uncorrelated for all age-sex classes. We therefore concluded that declining fecundity was most likely responsible for recent population declines, rather than changes in harvest or survival. Lindberg et al. (2017) critiqued our conclusions, arguing that we did little more than fail to reject a null hypothesis of compensatory mortality, postulated ecologically unrealistic changes in fecundity, and failed to give sufficient consideration to additive harvest mortality. Herein, we re-summarize our original evidence indicating that harvest has been compensatory, or at most weakly additive, and demonstrate that our analysis had sufficient power to detect strongly additive mortality if it occurred. We further demonstrate that our conclusions were not confounded by population size, band loss, or individual heterogeneity, as suggested by Lindberg et al. (2017), and we provide additional support for our conjecture that low fecundity played a major role in declining scaup populations during 1983–2006. We therefore reiterate our original management recommendations: given low harvest rates and lack of demonstrable effect on scaup survival, harvest regulations could return to more liberal frameworks, and waterfowl biologists should work together to continue banding lesser scaup and use these data to explore alternative hypotheses to identify the true ecological causes of population change, given that it is unlikely to be excessive harvest.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21315","usgsCitation":"Arnold, T.W., Afton, A.D., Anteau, M.J., Koons, D.N., and Nicolai, C.A., 2017, Temporal variation in survival and recovery rates of lesser scaup: A response: Journal of Wildlife Management, v. 81, no. 7, p. 1142-1148, https://doi.org/10.1002/jwmg.21315.","productDescription":"7 p.","startPage":"1142","endPage":"1148","ipdsId":"IP-086063","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":345670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"81","issue":"7","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-28","publicationStatus":"PW","scienceBaseUri":"59b8f218e4b08b1644e0aeac","contributors":{"authors":[{"text":"Arnold, Todd W.","contributorId":36058,"corporation":false,"usgs":false,"family":"Arnold","given":"Todd","email":"","middleInitial":"W.","affiliations":[{"id":12644,"text":"University of Minnesota, St. Paul","active":true,"usgs":false}],"preferred":false,"id":710191,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Afton, Alan D. 0000-0002-0436-8588 aafton@usgs.gov","orcid":"https://orcid.org/0000-0002-0436-8588","contributorId":139582,"corporation":false,"usgs":false,"family":"Afton","given":"Alan","email":"aafton@usgs.gov","middleInitial":"D.","affiliations":[{"id":368,"text":"Louisiana Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":710192,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":710190,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koons, David N.","contributorId":28137,"corporation":false,"usgs":false,"family":"Koons","given":"David","email":"","middleInitial":"N.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":710193,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nicolai, Chris A.","contributorId":196372,"corporation":false,"usgs":false,"family":"Nicolai","given":"Chris","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":710194,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70190583,"text":"ds1066 - 2017 - Yolo Bypass Juvenile Salmon Utilization Study 2016—Summary of acoustically tagged juvenile salmon and study fish release, Sacramento River, California","interactions":[],"lastModifiedDate":"2019-11-07T12:20:50","indexId":"ds1066","displayToPublicDate":"2017-09-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1066","title":"Yolo Bypass Juvenile Salmon Utilization Study 2016—Summary of acoustically tagged juvenile salmon and study fish release, Sacramento River, California","docAbstract":"The Yolo Bypass is a flood control bypass in Sacramento Valley, California. Flood plain habitats may be used for juvenile salmon rearing, however, the potential value of such habitats can be difficult to evaluate because of the intermittent nature of inundation events. The Yolo Bypass Juvenile Salmon Utilization Study (YBUS) used acoustic telemetry to evaluate the movements and survival of juvenile salmon adjacent to and within the Yolo Bypass during the winter of 2016. This report presents numbers, size data, and release data (times, dates, and locations) for the 1,197 acoustically tagged juvenile salmon released for the YBUS from February 21 to March 18, 2016. Detailed descriptions of the surgical implantation of transmitters are also presented. These data are presented to support the collaborative, interagency analysis and reporting of the study findings.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1066","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Liedtke, T.L., and Hurst, W.R., 2017, Yolo Bypass Juvenile Salmon Utilization Study 2016—Summary of acoustically tagged juvenile salmon and study fish release, Sacramento River, California: U.S. Geological Survey Data Series 1066, 49 p., https://doi.org/10.3133/ds1066.","productDescription":"Report: iv, 49 p.; 1 Table","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-089968","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":345667,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/1066/ds1066_table5.csv","text":"Table 5","size":"84 KB","linkFileType":{"id":7,"text":"csv"},"description":"DS 1066 Table 5"},{"id":345665,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1066/coverthb.jpg"},{"id":345666,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1066/ds1066.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1066"}],"country":"United States","state":"California","city":"Sacramento","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.827392578125,\n 38.662458581979436\n ],\n [\n -121.5644073486328,\n 38.662458581979436\n ],\n [\n -121.5644073486328,\n 38.921489637879205\n ],\n [\n -121.827392578125,\n 38.921489637879205\n ],\n [\n -121.827392578125,\n 38.662458581979436\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
From July 14 to July 20, 2016, the U.S. Geological Survey, in cooperation with the City of Ithaca, New York, and the New York State Department of State, surveyed the bathymetry of the Cayuga Inlet flood-control channel and the mouths of selected tributaries to Cayuga Inlet and Cayuga Lake in Ithaca, N.Y. The flood-control channel, built by the U.S. Army Corps of Engineers between 1965 and 1970, was designed to convey flood flows from the Cayuga Inlet watershed through the City of Ithaca and minimize possible flood damages. Since that time, the channel has infrequently been maintained by dredging, and sediment accumulation and resultant shoaling have greatly decreased the conveyance of the channel and its navigational capability.
U.S. Geological Survey personnel collected bathymetric data by using an acoustic Doppler current profiler. The survey produced a dense dataset of water depths that were converted to bottom elevations. These elevations were then used to generate a geographic information system bathymetric surface. The bathymetric data and resultant bathymetric surface show the current condition of the channel and provide the information that governmental agencies charged with maintaining the Cayuga Inlet for flood-control and navigational purposes need to make informed decisions regarding future maintenance measures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171109","collaboration":"Prepared in cooperation with the City of Ithaca, New York, and the New York State Department of State","usgsCitation":"Wernly, J.F., Nystrom, E.A., and Coon, W.F., 2017, Bathymetric survey of the Cayuga Inlet flood-control channel and selected tributaries in Ithaca, New York, 2016: U.S. Geological Survey Open-File Report 2017–1109, 9 p., https://doi.org/10.3133/ofr20171109.","productDescription":"Report: v, 9 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-080379","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":438218,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K935NQ","text":"USGS data release","linkHelpText":"Geospatial dataset of bathymetric survey of the Cayuga Inlet flood-control channel and selected tributaries in Ithaca, New York, 2016"},{"id":345569,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1109/coverthb.jpg"},{"id":345570,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1109/ofr20171109.pdf","text":"Report","size":"1.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1109"},{"id":345572,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7K935NQ","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial dataset of bathymetric survey of the Cayuga Inlet flood-control channel and selected tributaries, Ithaca, N.Y., 2016"}],"country":"United States","state":"New York","city":"Ithaca","otherGeospatial":"Cayuga Inlet Flood-Control Channel ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.52423858642578,\n 42.42586409208738\n ],\n [\n -76.48801803588867,\n 42.42586409208738\n ],\n [\n -76.48801803588867,\n 42.46437270371863\n ],\n [\n -76.52423858642578,\n 42.46437270371863\n ],\n [\n -76.52423858642578,\n 42.42586409208738\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
30 Brown Road
Ithaca, NY 14850