The brain and underlying cognition may vary adaptively according to an organism’s ecology. As with all raptor species, adult American kestrels (Falco sparverius) are sexually dimorphic with females being larger than males. Related to this sexual dimorphism, kestrels display sex differences in hunting and migration, with females ranging more widely than males, suggesting possible sex differences in spatial cognition. However, hippocampus volume, the brain region responsible for spatial cognition, has not been investigated in raptors. Here, we measured hippocampus and telencephalon volumes in American kestrel hatchlings. Female hatchlings had a significantly larger hippocampus relative to the telencephalon and brain weight than males (∼12% larger), although telencephalon volume relative to brain weight and body size was similar between the sexes. The magnitude of this hippocampal sex difference is similar to that reported between male and female polygynous Microtus voles and migratory and non-migratory subspecies of Zonotrichia sparrows. Future research should determine if this sex difference in relative hippocampus volume of hatchling kestrels persists into adulthood and if similar patterns exist in other raptor species, thus potentially linking sex differences in the brain to sex differences of space use of adults in the wild.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.bbr.2018.04.037","usgsCitation":"Guigueno, M., Karouna-Renier, N., Henry, P.F., Head, J.A., Peters, L.E., Palace, V.P., Letcher, R.J., and Fernie, K.J., 2018, Female hatchling American kestrels have a larger hippocampus than males: A link with sexual size dimorphism?: Behavioural Brain Research, v. 349, p. 98-101, https://doi.org/10.1016/j.bbr.2018.04.037.","productDescription":"4 p.","startPage":"98","endPage":"101","ipdsId":"IP-092884","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468610,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.bbr.2018.04.037","text":"Publisher Index Page"},{"id":355450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"349","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e546e4b060350a15d087","contributors":{"authors":[{"text":"Guigueno, Melanie F.","contributorId":206107,"corporation":false,"usgs":false,"family":"Guigueno","given":"Melanie F.","affiliations":[{"id":37248,"text":"Environment & Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":739437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karouna-Renier, Natalie 0000-0001-7127-033X nkarouna@usgs.gov","orcid":"https://orcid.org/0000-0001-7127-033X","contributorId":200983,"corporation":false,"usgs":true,"family":"Karouna-Renier","given":"Natalie","email":"nkarouna@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":739436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henry, Paula F. P. 0000-0002-7601-5546 phenry@usgs.gov","orcid":"https://orcid.org/0000-0002-7601-5546","contributorId":4485,"corporation":false,"usgs":true,"family":"Henry","given":"Paula","email":"phenry@usgs.gov","middleInitial":"F. P.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":739440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Head, Jessica A.","contributorId":206108,"corporation":false,"usgs":false,"family":"Head","given":"Jessica","email":"","middleInitial":"A.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":739441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peters, Lisa E.","contributorId":176211,"corporation":false,"usgs":false,"family":"Peters","given":"Lisa","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":739442,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Palace, Vince P.","contributorId":176210,"corporation":false,"usgs":false,"family":"Palace","given":"Vince","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":739443,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Letcher, Robert J.","contributorId":176209,"corporation":false,"usgs":false,"family":"Letcher","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":739439,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fernie, Kimberly J.","contributorId":176208,"corporation":false,"usgs":false,"family":"Fernie","given":"Kimberly","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":739438,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70197943,"text":"70197943 - 2018 - Methylmercury dynamics in Upper Sacramento Valley rice fields with low background soil mercury levels","interactions":[],"lastModifiedDate":"2018-07-03T10:53:43","indexId":"70197943","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Methylmercury dynamics in Upper Sacramento Valley rice fields with low background soil mercury levels","docAbstract":"Few studies have considered how methylmercury (MeHg, a toxic form of Hg produced in anaerobic soils) production in rice (Oryza sativa L.) fields can affect water quality, and little is known about MeHg dynamics in rice fields. Surface water MeHg and total Hg (THg) imports, exports, and storage were studied in two commercial rice fields in the Sacramento Valley, California, where soil THg was low (25 and 57 ng g−1). The median concentration of MeHg in drainage water exiting the fields was 0.17 ng g−1 (range: <0.007–2.1 ng g−1). Compared with irrigation water, drainage water had similar MeHg concentrations, and lower THg concentrations during the growing season. Significantly elevated drainage water MeHg and THg concentrations were observed in the fallow season compared with the growing season. An analysis of surface water loads indicates that fields were net importers of both MeHg (76–110 ng m−2) and THg (1947–7224 ng m−2) during the growing season, and net exporters of MeHg (35–200 ng m−2) and THg (248–6496 ng m−2) during the fallow season. At harvest, 190 to 700 ng MeHg m−2 and 1400 to 1700 ng THg m−2 were removed from fields in rice grain. Rice straw, which contained 120 to 180 ng MeHg m−2 and 7000–10,500 ng m−2 THg was incorporated into the soil. These results indicate that efforts to reduce MeHg and THg exports in rice drainage water should focus on the fallow season. Substantial amounts of MeHg and THg were stored in plants, and these pools should be considered in future studies.
","language":"English","publisher":"ASA, CSSA, and SSSA","doi":"10.2134/jeq2017.10.0390","usgsCitation":"Tanner, K.C., Windham-Myers, L., Marvin-DiPasquale, M.C., Fleck, J., Tate, K.W., and Linquist, B.A., 2018, Methylmercury dynamics in Upper Sacramento Valley rice fields with low background soil mercury levels: Journal of Environmental Quality, v. 47, no. 4, p. 830-838, https://doi.org/10.2134/jeq2017.10.0390.","productDescription":"9 p.","startPage":"830","endPage":"838","ipdsId":"IP-086490","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":355448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e547e4b060350a15d093","contributors":{"authors":[{"text":"Tanner, K. Christy","contributorId":179307,"corporation":false,"usgs":false,"family":"Tanner","given":"K.","email":"","middleInitial":"Christy","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":739261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","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},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":739260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fleck, Jacob 0000-0002-3217-3972 jafleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-3972","contributorId":168694,"corporation":false,"usgs":true,"family":"Fleck","given":"Jacob","email":"jafleck@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739263,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tate, Kenneth W.","contributorId":179308,"corporation":false,"usgs":false,"family":"Tate","given":"Kenneth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":739264,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Linquist, Bruce A.","contributorId":179310,"corporation":false,"usgs":false,"family":"Linquist","given":"Bruce","email":"","middleInitial":"A.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":739265,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197946,"text":"sir20185089 - 2018 - Water-quality conditions with an emphasis on cyanobacteria and associated toxins and taste-and-odor compounds in the Kansas River, Kansas, July 2012 through September 2016","interactions":[],"lastModifiedDate":"2018-09-25T06:22:34","indexId":"sir20185089","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5089","title":"Water-quality conditions with an emphasis on cyanobacteria and associated toxins and taste-and-odor compounds in the Kansas River, Kansas, July 2012 through September 2016","docAbstract":"Cyanobacteria cause a multitude of water-quality concerns, including the potential to produce toxins and taste-and-odor compounds that may cause substantial economic and public health concerns, and are of particular interest in lakes, reservoirs, and rivers that are used for drinking-water supply. Extensive cyanobacterial blooms typically do not develop in the Kansas River; however, reservoirs in the lower Kansas River Basin occasionally develop blooms that may affect downstream water quality. During July 2012 through September 2016, continuous and (or) discrete water-quality data were collected at several sites (Wamego, De Soto, and three main reservoir-fed tributaries) on the Kansas River to characterize the sources, frequency and magnitude of occurrence, and causes of cyanobacteria, cyanobacterial toxins, and taste-and-odor compounds and to develop a real-time notification system of changing water-quality conditions that may affect drinking-water treatment.
Algal biomass, as estimated by chlorophyll, was consistently higher at the downstream De Soto site than the upstream Wamego site. Higher algal biomass at the De Soto site likely was caused by algal growth during downstream transport without major losses due to grazing by aquatic organisms or other processes. Algal biomass at the Wamego and De Soto sites was negatively correlated with streamflow and total and bioavailable nutrient concentrations. The negative association between algal biomass and nutrients in the Kansas River likely reflects the relatively strong positive association between nutrient concentrations and streamflows.
Cyanobacteria were relatively common in the Kansas River but rarely dominated the algal community. Like overall algal biomass, cyanobacterial abundances typically were higher at the De Soto site than the Wamego site. Cyanobacterial abundances generally peaked in late summer or early fall (July through October), with smaller peaks occasionally observed in spring (April through May). Cyanobacteria in the Kansas River rarely exceeded 20,000 cells per milliliter, the abundance at which cyanobacteria may become a concern for drinking-water treatment. Relations between cyanobacterial abundance and streamflow, turbidity, and nutrients in the Kansas River were similar to those between chlorophyll and total phytoplankton abundance, indicating the same processes that influence overall algal biomass and dynamics also are influencing cyanobacteria.
The cyanotoxin microcystin was detected in about 27 percent of the samples collected from Kansas River tributary and main-stem sites. Cylindrospermopsin was detected in one sample from the De Soto site. Microcystin occurrence and concentration were similar between the Wamego and De Soto sites. Concentrations exceeded the U.S. Environmental Protection Agency health advisory guidance values for finished drinking water of 0.3 (for bottle-fed infants and pre-school children) and 1.6 micrograms per liter (μg/L; for school-age children and adults) in 6 percent or less of samples collected. These guidance values are for finished drinking water and are not directly applicable to observed environmental concentrations but do provide a benchmark for comparison. Microcystin was detected most often and had the highest concentrations during summer. Though seasonal patterns in microcystin occurrence were generally consistent, seasonal maxima varied by an order of magnitude across years.
The taste-and-odor compounds geosmin and 2-methylisoborneol (MIB) were detected in about 78 and 43 percent of samples, respectively, collected across all sites (main stem and tributaries). Geosmin and MIB occurrence and concentration varied considerably between the Wamego and De Soto sites. Geosmin was detected in about 67 percent of Wamego samples and 81 percent of De Soto samples. The human detection threshold of 5 nanograms per liter (ng/L) was exceeded for geosmin in about 11 and 17 percent of the samples collected at the Wamego and De Soto sites, respectively. Geosmin was detected during all months of the year at both sites, and there were no clear seasonal patterns. MIB was detected less frequently in the Kansas River than geosmin and was observed in about 42 percent of Wamego samples and 33 percent of De Soto samples. Concentrations exceeded 5 ng/L in about 7 and 5 percent of samples from the Wamego and De Soto sites, respectively. As observed for geosmin, there were no clear seasonal patterns in MIB occurrence or concentration.
There seems to be a connection between microcystin detections in the Kansas River and occurrence of microcystin in upstream reservoirs (and tributary streams). Microcystin concentrations greater than 0.3 μg/L may be likely during the summer when streamflow is less than 3,000 cubic feet per second (ft3/s) and contributions from Milford Lake exceed about 30 percent of total flow in the Kansas River. Observed microcystin concentrations typically were higher at the De Soto site than the Wamego or tributary sites during 2012 through 2016, indicating cyanobacteria may continue to grow and produce microcystin once introduced to the Kansas River.
The spatial and temporal patterns in geosmin and MIB occurrence and concentration were more complex than microcystin. There were no clear connections between geosmin and MIB occurrence in the Kansas River and potential upstream reservoir (or tributary stream) sources. Likewise, there was not a clear relation between algal biomass, cyanobacteria, or actinomycetes bacteria and taste-and-odor events in the Kansas River. Geosmin and MIB were not strongly correlated with any measured environmental variable at either Kansas River site.
Continuous water-quality data may be used independently or in combination with regression models to provide information on changing water-quality conditions that may affect drinking-water treatment processes or recreational activities on the Kansas River. For example, logistic regression model outputs and continuous water-quality data may both be indicative of the potential for microcystin events. Logistic regression models that are estimating a high probability of microcystin occurrence at concentrations above 0.1 μg/L can be used as one indicator. Streamflows less than 3,000 ft3/s during upstream reservoir releases during periods with low turbidity and increased chlorophyll fluorescence, specific conductance, and pH values may also be indicative of microcystin events. Advanced or near-real-time notification may inform proactive, rather than reactive, management strategies when water-quality conditions are changing rapidly or are likely to cause cyanobacteria-related events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185089","collaboration":"Prepared in cooperation with the Kansas Water Office, the City of Lawrence, the City of Olathe, the City of Topeka, and Johnson County WaterOne","usgsCitation":"Graham, J.L., Foster, G.M., Williams, T.J., Mahoney, M.D., May, M.R., and Loftin, K.A., 2018, Water-quality conditions with an emphasis on cyanobacteria and associated toxins and taste-and-odor compounds in the Kansas River, Kansas, July 2012 through September 2016: U.S. Geological Survey Scientific Investigations Report 2018–5089, 55 p., https://doi.org/10.3133/sir20185089.","productDescription":"Report: vi, 54 p.; 6 Appendixes; 2 Data Releases","numberOfPages":"66","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-091849","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":355473,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EVITTP","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Phytoplankton data for the Kansas River and tributaries, July 2012 through February 2017"},{"id":355474,"rank":10,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P973V4A9","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Discrete water-quality data for the Kansas River and tributaries, July 2012 - September 2016"},{"id":355471,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5089/sir20185089_appendix5.pdf","text":"Appendix 5","size":"239kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5089 Appendix 5"},{"id":355465,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5089/coverthb2.jpg"},{"id":355472,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5089/sir20185089_appendix6.pdf","text":"Appendix 6","size":"701 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5089 Appendix 6"},{"id":355466,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5089/sir20185089.pdf","text":"Report","size":"3.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5089"},{"id":355467,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5089/sir20185089_appendix1.pdf","text":"Appendix 1","size":"365 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5089 Appendix 1"},{"id":355468,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5089/sir20185089_appendix2.pdf","text":"Appendix 2","size":"370 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5089 Appendix 2"},{"id":355469,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5089/sir20185089_appendix3.pdf","text":"Appendix 3","size":"377 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5089 Appendix 3"},{"id":355470,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5089/sir20185089_appendix4.pdf","text":"Appendix 4","size":"372 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5089 Appendix 4"}],"country":"United States","state":"Kansas","otherGeospatial":"Kansas River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97,\n 38.5\n ],\n [\n -94.6307373046875,\n 38.5\n ],\n [\n -94.6307373046875,\n 40\n ],\n [\n -97,\n 40\n ],\n [\n -97,\n 38.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
Hurricane Harvey made landfall near Rockport, Texas, on August 25, 2017, as a Category 4 hurricane with wind gusts exceeding 150 miles per hour. As Harvey moved inland, the forward motion of the storm slowed down and produced tremendous rainfall amounts over southeastern Texas, with 8-day rainfall amounts exceeding 60 inches in some locations, which is about 15 inches more than average annual amounts of rainfall for eastern Texas and the Texas coast. Historic flooding occurred in Texas as a result of the widespread, heavy rainfall; wind and flood damages were estimated to be $125 billion, and the storm resulted in at least 68 direct fatalities.
In the immediate aftermath of the Harvey-related flood event, the U.S. Geological Survey (USGS) and the Federal Emergency Management Agency initiated a cooperative study to evaluate the magnitude of the flood, determine the probability of occurrence, and map the extent of the flood in Texas. Seventy-four USGS streamflow-gaging stations in Texas with at least 15 years of record and no large data gaps in the period of record had a 2017 annual peak streamflow related to Harvey ranking in the top five of all annual peaks for each given station. New peaks of record streamflow were recorded at 40 of the 74 USGS streamflow-gaging stations. The number of years of peak streamflow record for the 74 analyzed streamflow-gaging stations ranged from 18 to 105, with a mean number of 55 years. The annual exceedance probability estimates for the analyzed streamflow-gaging stations ranged from less than 0.2 to 14.0 percent. USGS field crews surveyed 2,123 high-water marks to obtain water-surface elevations, in feet above the North American Vertical Datum of 1988. In some locations, several water-surface elevations were averaged to obtain 1 water-surface elevation, resulting in 1,258 water-surface elevations. Some of these high-water marks were used, along with peak-stage data from USGS streamflow-gaging stations, to create 19 inundation maps to document the areal extent of the maximum depth of the flooding. Digital datasets of the inundation area, modeling boundary, water-depth rasters, and final map products are available from the USGS data release associated with this report (https://doi.org/10.5066/F7VH5N3N).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185070","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Watson, K.M., Harwell, G.R., Wallace, D.S., Welborn, T.L., Stengel, V.G., and McDowell, J.S., 2018, Characterization of peak streamflows and flood inundation of selected areas in southeastern Texas and southwestern Louisiana from the August and September 2017 flood resulting from Hurricane Harvey: U.S. Geological Survey Scientific Investigations Report 2018–5070, 44 p., https://doi.org/10.3133/sir20185070.","productDescription":"Report: viii, 44 p.; Data Release","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095268","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":355276,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5070/sir20185070.pdf","text":"Report","size":"12.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5070"},{"id":355275,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5070/coverthb.jpg"},{"id":355277,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VH5N3N","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data used to characterize peak streamflows and flood inundation resulting from Hurricane Harvey of selected areas in southeastern Texas and southwestern Louisiana, August–September 2017"}],"country":"United States","state":"Arkansas, Louisiana, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.00830078125,\n 27.332735136859146\n ],\n [\n -92.7685546875,\n 27.332735136859146\n ],\n [\n -92.7685546875,\n 33.358061612778876\n ],\n [\n -101.00830078125,\n 33.358061612778876\n ],\n [\n -101.00830078125,\n 27.332735136859146\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
National Research Program
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025
Freshwater resources in arid and semi-arid regions are in extreme demand, which creates conflicts between needs of humans and aquatic ecosystems. The Rio Grande basin in the southwestern United States and northern Mexico exemplifies this issue, as much of its aquatic biodiversity is in peril as a result of human activities. Unionid mussels have been disproportionately impacted, though the specific factors responsible for their decline remain largely unknown. This is problematic because the Rio Grande basin harbors one federally endangered unionid mussel (Popenaias popeii, Texas Hornshell) plus two other mussel species (Potamilus metnecktayi, Salina Mucket; and Truncilla cognata, Mexican Fawnsfoot), which are also being considered for listing under the U.S. Endangered Species Act. To date, surveys for these species have not corrected for variability in detection so current range estimates may be inaccurate. Using single occupancy-modeling to estimate detection and occupancy at 115 sites along ~800 river kilometers of the Rio Grande in Texas, we found that detection probabilities were relatively high, indicating that our survey design was efficient. In contrast, the estimated occupancy was low, indicating that our focal species were likely rare within the Rio Grande drainage. In general, the predicted occupancy of our focal species was low throughout their respective ranges, indicating possible range declines. A comparison of currently occupied ranges to presumptive ranges underscores this point. The best-approximating models indicated that occupancy was influenced by habitat, water quantity and quality, and proximity to large-scale human activities, such as dams and major urban centers. We also discuss a series of conservation options that may not only improve the long-term prognosis of our focal species but also other aquatic taxa.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.03.032","usgsCitation":"Randklev, C.R., Miller, T., Hart, M., Morton, J., Johnson, N.A., Skow, K., Inoue, K., Tsakiris, E., Oetker, S., Smith, R., Robertson, C., and Lopez, R., 2018, A semi-arid river in distress: Contributing factors and recovery solutions for three imperiled freshwater mussels (Family Unionidae) endemic to the Rio Grande basin in North America: Science of the Total Environment, v. 631-632, p. 733-744, https://doi.org/10.1016/j.scitotenv.2018.03.032.","productDescription":"12 p.","startPage":"733","endPage":"744","ipdsId":"IP-091761","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":355630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Rio Grande basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { 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A&M","active":true,"usgs":false}],"preferred":false,"id":739819,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Oetker, Susan","contributorId":206216,"corporation":false,"usgs":false,"family":"Oetker","given":"Susan","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":739820,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Ryan","contributorId":206257,"corporation":false,"usgs":false,"family":"Smith","given":"Ryan","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":739911,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Robertson, Clint","contributorId":206217,"corporation":false,"usgs":false,"family":"Robertson","given":"Clint","affiliations":[{"id":37288,"text":"Texas Parks and 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The study described in this report resulted in the following significant findings:
Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
In this essay, we explore a central problem of structural geology today, and in the foreseeable future, which is the determination of constitutive laws governing rock deformation to produce geologic structures. Although laboratory experiments provide much needed data and insights about constitutive laws, these experiments cannot cover the range of conditions and compositions relevant to the formation of geologic structures. We advocate that structural geologists address this limitation by interpreting natural experiments, documented with field and microstructural data, using continuum mechanical models that enable the deduction of constitutive laws. To put this procedure into a historical context, we review the founding of structural geology by James Hutton in the late 18th century, and the seminal contributions to continuum mechanics from Newton to Cauchy that provide the tools to model geologic structures. The procedure is illustrated with two examples drawn from recent and on-going field investigations of crustal and mantle lithologies. We conclude by pointing to future research opportunities that will engage structural geologists in the pursuit of constitutive laws during the 21st century.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jsg.2018.06.006","usgsCitation":"Nevitt, J., Warren, J.M., Kumamoto, K.M., and Pollard, D.D., 2018, Using geologic structures to constrain constitutive laws not accessible in the laboratory: Journal of Structural Geology, v. 125, p. 55-63, https://doi.org/10.1016/j.jsg.2018.06.006.","productDescription":"9 p.","startPage":"55","endPage":"63","ipdsId":"IP-094175","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":355443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e547e4b060350a15d08d","contributors":{"authors":[{"text":"Nevitt, Johanna 0000-0003-3819-1773 jnevitt@usgs.gov","orcid":"https://orcid.org/0000-0003-3819-1773","contributorId":198144,"corporation":false,"usgs":true,"family":"Nevitt","given":"Johanna","email":"jnevitt@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":739409,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warren, Jessica M. 0000-0002-4046-4200","orcid":"https://orcid.org/0000-0002-4046-4200","contributorId":206098,"corporation":false,"usgs":false,"family":"Warren","given":"Jessica","email":"","middleInitial":"M.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":739410,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kumamoto, Kathryn M.","contributorId":206099,"corporation":false,"usgs":false,"family":"Kumamoto","given":"Kathryn","email":"","middleInitial":"M.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":739411,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pollard, David D.","contributorId":206100,"corporation":false,"usgs":false,"family":"Pollard","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":739412,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198075,"text":"70198075 - 2018 - Tropical wetlands in the Anthropocene: The critical role of wet-dry cycles","interactions":[],"lastModifiedDate":"2018-07-16T10:51:28","indexId":"70198075","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3427,"text":"Solutions Journal","active":true,"publicationSubtype":{"id":10}},"title":"Tropical wetlands in the Anthropocene: The critical role of wet-dry cycles","docAbstract":"In the face of climate change and increasing human water demands for agriculture, industry, and cities, the fate of wetland ecosystems in tropical wet-dry climates is threatened. To maximize biodiversity and ecological resilience, the value of the ecosystem services provided by tropical wetlands can be incorporated into regional land use and water management decisions. Environmental planners and resource managers can work to protect both the “dry” and “wet” phases of the wet-dry hydrologic cycles. These cycles have shaped and maintained these ecosystems in the past and they can be used to maximize biodiversity and resilience in the future.","language":"English","publisher":"Solutions Journal","usgsCitation":"Osland, M.J., and Middleton, B.A., 2018, Tropical wetlands in the Anthropocene: The critical role of wet-dry cycles: Solutions Journal, v. 9, no. 3, 14 p.","productDescription":"14 p.","ipdsId":"IP-096321","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":355661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":355632,"type":{"id":15,"text":"Index Page"},"url":"https://www.thesolutionsjournal.com/article/tropical-wetlands-anthropocene-critical-role-wet-dry-cycles/"}],"volume":"9","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc419e4b0f5d57878e9e9","contributors":{"authors":[{"text":"Osland, Michael J. 0000-0001-9902-8692 mosland@usgs.gov","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":3080,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","email":"mosland@usgs.gov","middleInitial":"J.","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":739913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Middleton, Beth A. 0000-0002-1220-2326 middletonb@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":2029,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","email":"middletonb@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":739914,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198027,"text":"70198027 - 2018 - Wildlife management is science based: Myth or reality?","interactions":[],"lastModifiedDate":"2018-07-16T10:54:44","indexId":"70198027","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3587,"text":"The Wildlife Professional","active":true,"publicationSubtype":{"id":10}},"title":"Wildlife management is science based: Myth or reality?","docAbstract":"In the January/February issue of The Wildlife Professional, a group of wildlife leaders discussed what they considered \"myths\" in wildlife management and invited other wildlife professionals to contribute their favorites. Here, five wildlife professionals take up that theme with their discussions of the scientific basis of wildlife management.
This paper is the second of two that describes the Coastal Storm Modeling System (CoSMoS) approach for quantifying physical hazards and socio-economic hazard exposure in coastal zones affected by sea-level rise and changing coastal storms. The modelling approach, presented in Part 1, downscales atmospheric global-scale projections to local scale coastal flood impacts by deterministically computing the combined hazards of sea-level rise, waves, storm surges, astronomic tides, fluvial discharges, and changes in shoreline positions. The method is demonstrated through an application to Southern California, United States, where the shoreline is a mix of bluffs, beaches, highly managed coastal communities, and infrastructure of high economic value. Results show that inclusion of 100-year projected coastal storms will increase flooding by 9–350% (an additional average 53.0 ± 16.0 km2) in addition to a 25–500 cm sea-level rise. The greater flooding extents translate to a 55–110% increase in residential impact and a 40–90% increase in building replacement costs. To communicate hazards and ranges in socio-economic exposures to these hazards, a set of tools were collaboratively designed and tested with stakeholders and policy makers; these tools consist of two web-based mapping and analytic applications as well as virtual reality visualizations. To reach a larger audience and enhance usability of the data, outreach and engagement included workshop-style trainings for targeted end-users and innovative applications of the virtual reality visualizations.
","language":"English","publisher":"MDPI","doi":"10.3390/jmse6030076","usgsCitation":"Erikson, L.H., Barnard, P., O'Neill, A., Wood, N.J., Jones, J.M., Finzi Hart, J., Vitousek, S., Limber, P.W., Hayden, M., Fitzgibbon, M., Lovering, J., and Foxgrover, A.C., 2018, Projected 21st century coastal flooding in the Southern California Bight. Part 2: Tools for assessing climate change-driven coastal hazards and socio-economic impacts: Journal of Marine Science and Engineering, v. 6, no. 3, p. 1-19, https://doi.org/10.3390/jmse6030076.","productDescription":"Article 76; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-098756","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468609,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse6030076","text":"Publisher Index Page"},{"id":355449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.860595703125,\n 32.52828936482526\n ],\n [\n -117.037353515625,\n 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0000-0003-0638-5776 afoxgrover@usgs.gov","orcid":"https://orcid.org/0000-0003-0638-5776","contributorId":3261,"corporation":false,"usgs":true,"family":"Foxgrover","given":"Amy","email":"afoxgrover@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739446,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70198083,"text":"70198083 - 2018 - Turning on the faucet to a healthy coast","interactions":[],"lastModifiedDate":"2018-07-13T10:02:04","indexId":"70198083","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3427,"text":"Solutions Journal","active":true,"publicationSubtype":{"id":10}},"title":"Turning on the faucet to a healthy coast","docAbstract":"Coastal re-engineering and freshwater extraction have reduced water flow into the estuaries of the world. Because of these activities, stressed coastal vegetation is especially vulnerable to die-off during droughts, contributing to a loss of human services related to storm protection, fisheries and water quality. The subsequent collapse of vegetation is often as related to the loss of flow as to the rise in salinity. The solution to the problem in regions with rapidly expanding human populations may be to apply strategically timed freshwater releases to estuaries. To be successful, the water requirements of both humans and natural environments need careful assessment. Flow management projects have been successful in reviving vegetation in a number of settings including The Everglades, Murray River, Mississippi River and Nueces River. These projects can be contentious, for example, if the projects have caused negative impacts to the oyster industry. Beyond the human services provided, flowing water has an intrinsic personal value for which many people are willing to pay.","language":"English","publisher":"Solutions Journal","usgsCitation":"Middleton, B., and Montagna, P.A., 2018, Turning on the faucet to a healthy coast: Solutions Journal, v. 9, no. 3, 14 p.","productDescription":"14 p.","ipdsId":"IP-091390","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":355662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":355646,"type":{"id":15,"text":"Index Page"},"url":"https://www.thesolutionsjournal.com/article/turning-faucet-healthy-coast/"}],"country":"United States","volume":"9","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc419e4b0f5d57878e9e7","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":206267,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":739935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Montagna, Paul A.","contributorId":177033,"corporation":false,"usgs":false,"family":"Montagna","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":739936,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198072,"text":"70198072 - 2018 - Managing conflicts in the River of Grass","interactions":[],"lastModifiedDate":"2019-12-21T09:09:49","indexId":"70198072","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3427,"text":"Solutions Journal","active":true,"publicationSubtype":{"id":10}},"title":"Managing conflicts in the River of Grass","docAbstract":"Chances are, you would not pack up and move to a new home without first researching the neighborhood, reviewing your finances, and maybe investigating schools nearby. Similarly, you would not buy the first car you find on a magazine cover without first reviewing the technical specifications, exploring your options, and perhaps taking a test drive. Even when making simple purchases online, you probably shop around, check out customer reviews, and scan seller feedback ratings.
Rarely do we act on impulse alone when faced with decisions. Rather, we typically start with a vision of what we want before gathering the necessary information, weighing our options, prioritizing our values, and evaluating possible tradeoffs. In making choices that range from lighthearted to life-changing, we use this commonsense strategy every day of our lives.
Environmental decision-making is no different. For decades, natural resource managers faced with complicated problems have made decisions by breaking them into smaller components that are easier to approach. And like our day-to day decisions, the process is ideally guided by a shared vision of the future. However, it can become complicated when multiple, seemingly disparate views on what the future should hold emerge. As Lewis Carroll once wrote, “If you don’t know where you are going, any road will get you there.”
Divining a vision of the future for the Florida Everglades and making supporting decisions is a complex undertaking. But unlike Alice thrust through the looking glass, we have tools and techniques to help us make sense of it all. The application of tools to help decision-making can move us closer to the successful restoration of this imperiled landscape.
","language":"English","publisher":"Solutions","usgsCitation":"Romanach, S.S., Beerens, J.M., Perez, L., Haider, S., and Pearlstine, L.G., 2018, Managing conflicts in the River of Grass: Solutions Journal, v. 9, no. 3, 8 p.","productDescription":"8 p.","ipdsId":"IP-087571","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":355655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":355627,"type":{"id":15,"text":"Index Page"},"url":"https://www.thesolutionsjournal.com/article/managing-conflicts-river-grass/"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.78771972656249,\n 25.06072125231416\n ],\n [\n -80.3485107421875,\n 25.06072125231416\n ],\n [\n -80.3485107421875,\n 26.185018250078308\n ],\n [\n -81.78771972656249,\n 26.185018250078308\n ],\n [\n -81.78771972656249,\n 25.06072125231416\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc41ae4b0f5d57878e9eb","contributors":{"authors":[{"text":"Romanach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":140419,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","email":"sromanach@usgs.gov","middleInitial":"S.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":739901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beerens, James M. 0000-0001-8143-916X jbeerens@usgs.gov","orcid":"https://orcid.org/0000-0001-8143-916X","contributorId":143722,"corporation":false,"usgs":true,"family":"Beerens","given":"James","email":"jbeerens@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":739902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perez, Larry","contributorId":206254,"corporation":false,"usgs":false,"family":"Perez","given":"Larry","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":739905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haider, Saira M. 0000-0001-9306-3454","orcid":"https://orcid.org/0000-0001-9306-3454","contributorId":206253,"corporation":false,"usgs":true,"family":"Haider","given":"Saira","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":739903,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pearlstine, Leonard G.","contributorId":34751,"corporation":false,"usgs":false,"family":"Pearlstine","given":"Leonard","email":"","middleInitial":"G.","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":739904,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202687,"text":"70202687 - 2018 - Metamodeling for groundwater age forecasting in the Lake Michigan Basin","interactions":[],"lastModifiedDate":"2019-03-18T16:30:22","indexId":"70202687","displayToPublicDate":"2018-07-01T16:30:14","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Metamodeling for groundwater age forecasting in the Lake Michigan Basin","docAbstract":"Groundwater age is an important indicator of groundwater susceptibility to anthropogenic contamination and a key input to statistical models for forecasting water quality. Numerical models can provide estimates of groundwater age, enabling interpretation of measured age tracers. However, to extend to national‐scale groundwater systems where numerical models are not routinely available, a more efficient metamodeling approach can provide a less precise but widely applicable estimate of groundwater age, trained to make forecasts based on predictor variables that can be measured independent of numerical models. We trained gradient‐boosted regression tree statistical metamodels to MODFLOW/MODPATH‐derived groundwater age estimates in five inset models in the Lake Michigan Basin, USA. Using high‐throughput computing, we explored an exhaustive range of tuning parameters and tested metamodels through cross validation, a 20% holdout, and a round robin approach among the five inset models withholding each inset model from training and testing on the held‐out inset model. Forecast skill—measured by Nash Sutcliffe efficiency—was high for age‐related responses in the 20% hold‐out case (ranging from 0.73 to 0.84). The round robin analysis provided the opportunity to explore extending to unmodeled areas and a greater range of skill indicated the need to evaluate when it is appropriate to apply a metamodel from one region to another. We further explored the ramifications of metamodel simplification achieved through removing predictor variables based on their estimated importance. We found that similar metamodel performance was achievable with a fraction of the candidate set of predictor variables with well construction variables being most important.
","language":"English","publisher":"AGU","doi":"10.1029/2017WR022387","usgsCitation":"Fienen, M.N., Nolan, B.T., Kauffman, L.J., and Feinstein, D.T., 2018, Metamodeling for groundwater age forecasting in the Lake Michigan Basin: Water Resources Research, v. 54, no. 7, p. 4750-4766, https://doi.org/10.1029/2017WR022387.","productDescription":"17 p.","startPage":"4750","endPage":"4766","ipdsId":"IP-096251","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":468611,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017wr022387","text":"Publisher Index Page"},{"id":437832,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7610ZMG","text":"USGS data release","linkHelpText":"Data and Scripts for Metamodeling for Groundwater Age Forecasting in the Lake Michigan Basin"},{"id":362158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Michigan Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89,\n 41.5\n ],\n [\n -84,\n 41.5\n ],\n [\n -84,\n 46.5\n ],\n [\n -89,\n 46.5\n ],\n [\n -89,\n 41.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"7","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":171511,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael","email":"mnfienen@usgs.gov","middleInitial":"N.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nolan, B. Thomas 0000-0002-6945-9659","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":8905,"corporation":false,"usgs":true,"family":"Nolan","given":"B.","email":"","middleInitial":"Thomas","affiliations":[],"preferred":true,"id":759478,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kauffman, Leon J. 0000-0003-4564-0362 lkauff@usgs.gov","orcid":"https://orcid.org/0000-0003-4564-0362","contributorId":1094,"corporation":false,"usgs":true,"family":"Kauffman","given":"Leon","email":"lkauff@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759479,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feinstein, Daniel T. 0000-0003-1151-2530 dtfeinst@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-2530","contributorId":1907,"corporation":false,"usgs":true,"family":"Feinstein","given":"Daniel","email":"dtfeinst@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759480,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200910,"text":"70200910 - 2018 - Environmental controls, emergent scaling, and predictions of greenhouse gas (GHG) fluxes in coastal salt marshes","interactions":[],"lastModifiedDate":"2018-11-14T15:03:45","indexId":"70200910","displayToPublicDate":"2018-07-01T15:03:36","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2319,"text":"Journal of Geophysical Research G: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Environmental controls, emergent scaling, and predictions of greenhouse gas (GHG) fluxes in coastal salt marshes","docAbstract":"Coastal salt marshes play an important role in mitigating global warming by removing atmospheric carbon at a high rate. We investigated the environmental controls and emergent scaling of major greenhouse gas (GHG) fluxes such as carbon dioxide (CO2) and methane (CH4) in coastal salt marshes by conducting data analytics and empirical modeling. The underlying hypothesis is that the salt marsh GHG fluxes follow emergent scaling relationships with their environmental drivers, leading to parsimonious predictive models. CO2 and CH4 fluxes, photosynthetically active radiation (PAR), air and soil temperatures, well water level, soil moisture, and porewater pH and salinity were measured during May–October 2013 from four marshes in Waquoit Bay and adjacent estuaries, MA, USA. The salt marshes exhibited high CO2 uptake and low CH4 emission, which did not significantly vary with the nitrogen loading gradient (5–126 kg · ha−1 · year−1) among the salt marshes. Soil temperature was the strongest driver of both fluxes, representing 2 and 4–5 times higher influence than PAR and salinity, respectively. Well water level, soil moisture, and pH did not have a predictive control on the GHG fluxes, although both fluxes were significantly higher during high tides than low tides. The results were leveraged to develop emergent power law‐based parsimonious scaling models to accurately predict the salt marsh GHG fluxes from PAR, soil temperature, and salinity (Nash‐Sutcliffe Efficiency = 0.80–0.91). The scaling models are available as a user‐friendly Excel spreadsheet named Coastal Wetland GHG Model to explore scenarios of GHG fluxes in tidal marshes under a changing climate and environment.
","language":"English","publisher":"AGU","doi":"10.1029/2018JG004556","usgsCitation":"Abdul-Aziz, O.I., Ishitaq, K.S., Tang, J., Moseman-Valtierra, S., Kroeger, K.D., Gonneea Eagle, M., Mora, J., and Morkeski, K., 2018, Environmental controls, emergent scaling, and predictions of greenhouse gas (GHG) fluxes in coastal salt marshes: Journal of Geophysical Research G: Biogeosciences, v. 123, no. 7, p. 2234-2256, https://doi.org/10.1029/2018JG004556.","productDescription":"23 p.","startPage":"2234","endPage":"2256","ipdsId":"IP-093072","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jg004556","text":"Publisher Index Page"},{"id":359427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.5,\n 41.54301946112854\n ],\n [\n -70.5833,\n 41.54301946112854\n ],\n [\n -70.5833,\n 41.5833\n ],\n [\n -70.5,\n 41.5833\n ],\n [\n -70.5,\n 41.54301946112854\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"7","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-28","publicationStatus":"PW","scienceBaseUri":"5bed4274e4b0b3fc5cf91c90","contributors":{"authors":[{"text":"Abdul-Aziz, Omar I.","contributorId":192386,"corporation":false,"usgs":false,"family":"Abdul-Aziz","given":"Omar","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":751228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ishitaq, Khandker S.","contributorId":210612,"corporation":false,"usgs":false,"family":"Ishitaq","given":"Khandker","email":"","middleInitial":"S.","affiliations":[{"id":38119,"text":"Ecological and Water Resources Engineering Laboratory (EWREL), Department of Civil and Environmental Engineering, West Virginia University, 395 Evansdale Drive, PO Box 6103, Morgantown, WV 26506,","active":true,"usgs":false}],"preferred":false,"id":751229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tang, Jianwu","contributorId":174890,"corporation":false,"usgs":false,"family":"Tang","given":"Jianwu","email":"","affiliations":[{"id":27818,"text":"The Ecosystems Center, Marine Biological Laboratory. Woods Hole, MA 02543.","active":true,"usgs":false}],"preferred":false,"id":751230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moseman-Valtierra, Serena","contributorId":140087,"corporation":false,"usgs":false,"family":"Moseman-Valtierra","given":"Serena","email":"","affiliations":[{"id":6923,"text":"University of Rhode Island, Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":751231,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":751232,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gonneea Eagle, Meagan 0000-0001-5072-2755 mgonneea@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":174590,"corporation":false,"usgs":true,"family":"Gonneea Eagle","given":"Meagan","email":"mgonneea@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":751233,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mora, Jordan","contributorId":208060,"corporation":false,"usgs":false,"family":"Mora","given":"Jordan","email":"","affiliations":[{"id":37699,"text":"Waquoit Bay National Estuarine Research Reserve, Waquoit, Mass","active":true,"usgs":false}],"preferred":false,"id":751234,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morkeski, Kate","contributorId":210613,"corporation":false,"usgs":false,"family":"Morkeski","given":"Kate","email":"","affiliations":[{"id":38120,"text":"Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, 266 Woods Hole Road, Woods Hole, MA 02543, USA","active":true,"usgs":false}],"preferred":false,"id":751235,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70199948,"text":"70199948 - 2018 - Biogeography of pelagic food webs in the North Pacific","interactions":[],"lastModifiedDate":"2018-10-05T14:39:26","indexId":"70199948","displayToPublicDate":"2018-07-01T14:39:18","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1660,"text":"Fisheries Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Biogeography of pelagic food webs in the North Pacific","docAbstract":"The tufted puffin (Fratercula cirrhata) is a generalist seabird that breeds throughout the North Pacific and eats more than 75 different prey species. Using puffins as samplers, we characterized the geographic variability in pelagic food webs across the subarctic North Pacific from the composition of ~10,000 tufted puffin meals (~56,000 prey items) collected at 35 colonies in the Gulf of Alaska (GoA) and Aleutian Archipelago. Cluster analysis of diet species composition suggested three distinct forage fish communities: (i) in the northern GoA, multiple age‐classes of coastal and shelf residents such as capelin, sand lance and herring dominated the food web, (ii) in the western GoA to eastern Aleutians, the shelf community was dominated by transient age‐0 walleye pollock, and (iii) in the western Aleutians, shelf‐edge and mesopelagic forage species such as squid, lanternfish, and Atka mackerel were prevalent. Geographic patterns of abundance of capelin and sand lance in tufted puffin diets were corroborated by independent research fisheries and diets of piscivorous fish, indicating that puffin diets reflect the local abundance of forage species, not just selection of favored species. Generalized additive models showed that habitat characteristics predict, in a non‐linear fashion, forage species distribution and abundance across two large marine ecosystems. We conclude that major biogeographic patterns in forage fish distribution follow gradients in key habitat features, and puffin diets reflect those patterns.
","language":"English","publisher":"Wiley","doi":"10.1111/fog.12258","usgsCitation":"Piatt, J.F., Arimitsu, M.L., Sydeman, W.J., Thompson, S.A., Renner, H., Zador, S., Douglas, D., Hatch, S., Kettle, A.B., and Williams, J.C., 2018, Biogeography of pelagic food webs in the North Pacific: Fisheries Oceanography, v. 27, no. 4, p. 366-380, https://doi.org/10.1111/fog.12258.","productDescription":"15 p.","startPage":"366","endPage":"380","ipdsId":"IP-067595","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":468614,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/fog.12258","text":"External Repository"},{"id":358187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-12","publicationStatus":"PW","scienceBaseUri":"5bc02fd7e4b0fc368eb5398f","contributors":{"authors":[{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":747424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":747425,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sydeman, William J.","contributorId":208489,"corporation":false,"usgs":false,"family":"Sydeman","given":"William","email":"","middleInitial":"J.","affiliations":[{"id":35859,"text":"Farallon Institute","active":true,"usgs":false}],"preferred":false,"id":747426,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Sarah Ann","contributorId":198394,"corporation":false,"usgs":false,"family":"Thompson","given":"Sarah","email":"","middleInitial":"Ann","affiliations":[],"preferred":false,"id":747427,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Renner, Heather","contributorId":200807,"corporation":false,"usgs":false,"family":"Renner","given":"Heather","affiliations":[],"preferred":false,"id":747428,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zador, Stephani","contributorId":60992,"corporation":false,"usgs":false,"family":"Zador","given":"Stephani","affiliations":[],"preferred":false,"id":747429,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":150115,"corporation":false,"usgs":true,"family":"Douglas","given":"David C.","email":"ddouglas@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":747430,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hatch, Scott A.","contributorId":201044,"corporation":false,"usgs":false,"family":"Hatch","given":"Scott A.","affiliations":[],"preferred":false,"id":747431,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kettle, Arthur B.","contributorId":98064,"corporation":false,"usgs":false,"family":"Kettle","given":"Arthur","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":747432,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Williams, Jeffrey C.","contributorId":126882,"corporation":false,"usgs":false,"family":"Williams","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":747433,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70200349,"text":"70200349 - 2018 - USGS quarterly wildlife mortality report July 2018","interactions":[],"lastModifiedDate":"2023-10-12T16:51:46.346671","indexId":"70200349","displayToPublicDate":"2018-07-01T14:30:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3769,"text":"Wildlife Disease Association Newsletter","active":true,"publicationSubtype":{"id":10}},"title":"USGS quarterly wildlife mortality report July 2018","docAbstract":"No abstract available.
","language":"English","publisher":"Wildlife Disease Association","usgsCitation":"Richards, B.J., Bodenstein, B., Ballmann, A., and St. Martin, M., 2018, USGS quarterly wildlife mortality report July 2018: Wildlife Disease Association Newsletter, p. 15-17.","productDescription":"3 p.","startPage":"15","endPage":"17","ipdsId":"IP-099084","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":358347,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.wildlifedisease.org/PersonifyEbusiness/Resources/Publications/Newsletter/Archive"},{"id":358352,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a984e4b034bf6a7e526a","contributors":{"authors":[{"text":"Richards, Bryan J. 0000-0001-9955-2523 brichards@usgs.gov","orcid":"https://orcid.org/0000-0001-9955-2523","contributorId":3533,"corporation":false,"usgs":true,"family":"Richards","given":"Bryan","email":"brichards@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":748454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bodenstein, Barbara L. 0000-0001-7946-0103 bbodenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-7946-0103","contributorId":189820,"corporation":false,"usgs":true,"family":"Bodenstein","given":"Barbara","email":"bbodenstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":748455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ballmann, Anne 0000-0002-0380-056X aballmann@usgs.gov","orcid":"https://orcid.org/0000-0002-0380-056X","contributorId":140319,"corporation":false,"usgs":true,"family":"Ballmann","given":"Anne","email":"aballmann@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":748456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"St. Martin, Michelle","contributorId":150114,"corporation":false,"usgs":false,"family":"St. Martin","given":"Michelle","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":748457,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237369,"text":"70237369 - 2018 - Sensitivity of streamflow to climate change in California","interactions":[],"lastModifiedDate":"2022-10-11T19:03:35.957365","indexId":"70237369","displayToPublicDate":"2018-07-01T14:00:30","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1246,"text":"Climate Change","onlineIssn":"1573-1480","printIssn":"0165-0009","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity of streamflow to climate change in California","docAbstract":"Climate change is rapidly altering the global water cycle, exposing vulnerabilities in both social and environmental systems. However, uncertainty in future climate predictions makes it difficult to design and evaluate strategies for building climate resilience. In regions such as California, characterized by stressed water-supply systems, high natural climate variability, and substantial uncertainty in future precipitation projections, alternative approaches to assessing climate risks may be useful. Here, we develop a hydrologic sensitivity approach to estimate regional streamflow responses to climate change in California. We use statistical models to predict monthly streamflow from physical catchment features and evaluate how flow changes with incremental changes in precipitation and temperature. The results indicate unique regional and monthly flow responses to climate change, with early summer flows (May - July) in interior mountain region having the greatest sensitivity to temperature and winter flow (December - March) in the xeric region having the greatest sensitivity to precipitation. When evaluated over the range of global climate model projections for mid-century (2040-2069), models generally suggest shifts in streamflow regimes towards higher wet season flows and lower dry season flows relative to historical conditions. The sensitivity analysis provides insight into catchment- and regional-scale hydrologic responses in California and complements other approaches for understanding the consequences of climatic change for water and risk management.","language":"English","publisher":"Springer","doi":"10.1007/s10584-018-2244-9","usgsCitation":"Grantham, T.E., Carlisle, D.M., McCabe, G.J., and Howard, J., 2018, Sensitivity of streamflow to climate change in California: Climate Change, v. 149, p. 427-441, https://doi.org/10.1007/s10584-018-2244-9.","productDescription":"15 p.","startPage":"427","endPage":"441","ipdsId":"IP-092091","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":408180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"149","noUsgsAuthors":false,"publicationDate":"2018-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Grantham, Theodore E. W. tgrantham@usgs.gov","contributorId":297482,"corporation":false,"usgs":false,"family":"Grantham","given":"Theodore","email":"tgrantham@usgs.gov","middleInitial":"E. W.","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":854284,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":854285,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":854286,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Howard, Jeanette K.","contributorId":297483,"corporation":false,"usgs":false,"family":"Howard","given":"Jeanette K.","affiliations":[{"id":27697,"text":"The Nature Conservency","active":true,"usgs":false}],"preferred":false,"id":854287,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198676,"text":"70198676 - 2018 - Comparative nest survival of three sympatric loon species breeding in the Arctic","interactions":[],"lastModifiedDate":"2018-08-15T13:53:17","indexId":"70198676","displayToPublicDate":"2018-07-01T13:53:12","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Comparative nest survival of three sympatric loon species breeding in the Arctic","docAbstract":"Identifying factors influencing nest survival among sympatric species is important for understanding and managing sources of variation in population dynamics of individual species. Three species of loons nest sympatrically in northern Alaska and differ in body size, life history characteristics, and population trends. We tested the effects of competition, nest site selection, and water level variations on nest survival of Pacific Gavia pacifica, yellow‐billed G. adamsii, and red‐throated loons G. stellata on the Arctic Coastal Plain in Alaska. Although overall nest survival rates did not differ between species, the factors influencing nest survival varied. Nest site selection influenced nest survival for Pacific and yellow‐billed loons, with both species having high nest survival when nesting on islands and peninsulas, likely due to a reduction in access by terrestrial predators. However, on mainland shorelines, Pacific loons had lower nest survival than yellow‐billed loons, and used a higher proportion of vegetation mats for nest sites suggesting that their smaller body size makes them less adept at nest defense. Nest site selection did not influence nest survival of red‐throated loons corresponding to our result of no nest site preferences by this species. Initiation date had a strong influence on nest survival for Pacific and yellow‐billed loons with nests laid earlier having higher survival. Pacific and yellow‐billed loon nests were susceptible to flooding due to precipitation, which contrasted with red‐throated loons that nest on smaller lakes with lower water level variations. Competition did not affect nest survival for any of the species likely due to most territorial encounters occurring prior to incubation. The only influence we found on red‐throated loon nest survival was differences among years. Our results indicate that loons chose nest sites based on predation risk and that factors influencing breeding success of closely related species may differ under similar breeding conditions.
","language":"English","publisher":"Wiley","doi":"10.1111/jav.01671","usgsCitation":"Uher-Koch, B.D., Koch, J.C., Wright, K.G., and Schmutz, J.A., 2018, Comparative nest survival of three sympatric loon species breeding in the Arctic: Journal of Avian Biology, v. 49, no. 7, p. 1-15, https://doi.org/10.1111/jav.01671.","productDescription":"e01671; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-090934","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":499979,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/5ae4f5eb63564114b5a16aec9f3f4b8a","text":"External Repository"},{"id":437834,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74F1Q0D","text":"USGS data release","linkHelpText":"Pacific (Gavia pacifica), Yellow-billed (G. adamsii), and Red-throated Loon (G. stellata) Nest Monitoring Data; National Petroleum Reserve-Alaska, 2011-2014"},{"id":356517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157,\n 70.33\n ],\n [\n -153,\n 70.33\n ],\n [\n -153,\n 71.33\n ],\n [\n -157,\n 71.33\n ],\n [\n -157,\n 70.33\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-18","publicationStatus":"PW","scienceBaseUri":"5b98a2a2e4b0702d0e842f9c","contributors":{"authors":[{"text":"Uher-Koch, Brian D. 0000-0002-1885-0260 buher-koch@usgs.gov","orcid":"https://orcid.org/0000-0002-1885-0260","contributorId":5117,"corporation":false,"usgs":true,"family":"Uher-Koch","given":"Brian","email":"buher-koch@usgs.gov","middleInitial":"D.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":742522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":742523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wright, Kenneth G.","contributorId":207044,"corporation":false,"usgs":false,"family":"Wright","given":"Kenneth","email":"","middleInitial":"G.","affiliations":[{"id":37436,"text":"Biodiversity Research Institute","active":true,"usgs":false}],"preferred":false,"id":742524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":742525,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199521,"text":"70199521 - 2018 - Advances in sensitivity analysis of uncertainty to changes in sampling density when modeling spatially correlated attributes","interactions":[],"lastModifiedDate":"2018-09-24T12:24:32","indexId":"70199521","displayToPublicDate":"2018-07-01T12:24:22","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Advances in sensitivity analysis of uncertainty to changes in sampling density when modeling spatially correlated attributes","docAbstract":"A comparative analysis of distance methods, kriging and stochastic simulation is conducted for evaluating their capabilities for predicting fluctuations in uncertainty due to changes in spatially correlated samples. It is concluded that distance methods lack the most basic capabilities to assess reliability despite their wide acceptance. In contrast, kriging and stochastic simulation offer significant improvements by considering probabilistic formulations that provide a basis on which uncertainty can be estimated in a way consistent with practices widely accepted in risk analysis. Additionally, using real thickness data of a coal bed, it is confirmed once more that stochastic simulation outperforms kriging.
","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-78999-6_19","usgsCitation":"Olea, R., 2018, Advances in sensitivity analysis of uncertainty to changes in sampling density when modeling spatially correlated attributes, p. 375-393, https://doi.org/10.1007/978-3-319-78999-6_19.","productDescription":"19 p.","startPage":"375","endPage":"393","ipdsId":"IP-081861","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":460784,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/978-3-319-78999-6_19","text":"Publisher Index Page"},{"id":357677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-26","publicationStatus":"PW","scienceBaseUri":"5bc02fd8e4b0fc368eb53991","contributors":{"authors":[{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":26436,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":745751,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70197865,"text":"70197865 - 2018 - Applying high-resolution imagery to evaluate restoration-induced changes in stream condition, Missouri River Headwaters Basin, Montana","interactions":[],"lastModifiedDate":"2018-08-07T12:15:35","indexId":"70197865","displayToPublicDate":"2018-07-01T12:15:30","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Applying high-resolution imagery to evaluate restoration-induced changes in stream condition, Missouri River Headwaters Basin, Montana","docAbstract":"Degradation of streams and associated riparian habitat across the Missouri River Headwaters Basin has motivated several stream restoration projects across the watershed. Many of these projects install a series of beaver dam analogues (BDAs) to aggrade incised streams, elevate local water tables, and create natural surface water storage by reconnecting streams with their floodplains. Satellite imagery can provide a spatially continuous mechanism to monitor the effects of these in-stream structures on stream surface area. However, remote sensing-based approaches to map narrow (e.g., <5 m wide) linear features such as streams have been under-developed relative to efforts to map other types of aquatic systems, such as wetlands or lakes. We mapped pre- and post-restoration (one to three years post-restoration) stream surface area and riparian greenness at four stream restoration sites using Worldview-2 and 3 images as well as a QuickBird-2 image. We found that panchromatic brightness and eCognition-based outputs (0.5 m resolution) provided high-accuracy maps of stream surface area (overall accuracy ranged from 91% to 99%) for streams as narrow as 1.5 m wide. Using image pairs, we were able to document increases in stream surface area immediately upstream of BDAs as well as increases in stream surface area along the restoration reach at Robb Creek, Alkali Creek and Long Creek (South). Although Long Creek (North) did not show a net increase in stream surface area along the restoration reach, we did observe an increase in riparian greenness, suggesting increased water retention adjacent to the stream. As high-resolution imagery becomes more widely collected and available, improvements in our ability to provide spatially continuous monitoring of stream systems can effectively complement more traditional field-based and gage-based datasets to inform watershed management.
","language":"English","publisher":"MDPI","doi":"10.3390/rs10060913","usgsCitation":"Vanderhoof, M.K., and Burt, C., 2018, Applying high-resolution imagery to evaluate restoration-induced changes in stream condition, Missouri River Headwaters Basin, Montana: Remote Sensing, v. 10, no. 6, p. 1-28, https://doi.org/10.3390/rs10060913.","productDescription":"Article 913; 28 p.","startPage":"1","endPage":"28","ipdsId":"IP-097220","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468616,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs10060913","text":"Publisher Index Page"},{"id":437835,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F9618G","text":"USGS data release","linkHelpText":"Data release for Applying high-resolution imagery to evaluate restoration-induced changes in stream condition, Missouri River Headwaters Basin, Montana"},{"id":356280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Missouri River Headwaters Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.4167,\n 44.5\n ],\n [\n -111.8333,\n 44.5\n ],\n [\n -111.8333,\n 45.1667\n ],\n [\n -112.4167,\n 45.1667\n ],\n [\n -112.4167,\n 44.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-09","publicationStatus":"PW","scienceBaseUri":"5b6fc41be4b0f5d57878e9ef","contributors":{"authors":[{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":738807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burt, Clifton 0000-0001-5213-800X","orcid":"https://orcid.org/0000-0001-5213-800X","contributorId":205903,"corporation":false,"usgs":false,"family":"Burt","given":"Clifton","affiliations":[],"preferred":false,"id":738808,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70200387,"text":"70200387 - 2018 - Karst hydrogeology of Tuckaleechee Cove and the western Great Smoky Mountains, Tennessee and North Carolina","interactions":[],"lastModifiedDate":"2018-11-27T11:31:31","indexId":"70200387","displayToPublicDate":"2018-07-01T11:31:24","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Karst hydrogeology of Tuckaleechee Cove and the western Great Smoky Mountains, Tennessee and North Carolina","docAbstract":"The geology of Great Smoky Mountains National Park (GRSM) in Tennessee and North Carolina is dominated by siliciclastics and metamorphic strata. However, in the western portion of GRSM, a series of carbonate fensters (windows) expose the Lower Ordovician–age section of the Knox Group, a series of dolomite and limestone units that are partially marbleized as a result of contact metamorphism from the Great Smoky fault. The fensters create opportunities for allogenic recharge to occur at points along the contact of the surrounding insoluble strata with the underlying soluble carbonates. The combination of chemically aggressive surface recharge and vertical relief has resulted in the formation of deep caves, many of which have active streams and water resources. Though the karst is limited in extent and the number of caves is fairly small, the significance of the resources is substantial, with several of the caves in the area over 150 m in depth and at least two being major bat hibernacula. In 2017, the U.S. Geological Survey (USGS) began a study to better understand the hydrologic behavior of these karst systems through hydrologic and geochemical monitoring, groundwater tracing using fluorescent dyes, and seepage runs. Stage and water-quality instrumentation was installed in two caves in GRSM, the main stream of Bull Cave, and in a sump pool in Whiteoak Blowhole, at 173 m and 70 m below land surface, respectively. Following setup of the cave sites, dye injections were conducted to determine discharge points for four of the deep cave systems on Rich Mountain and Turkeypen ridge. Results show water in these systems has an extremely rapid travel time, with tracers detected from caves to springs in less than 24 h for each of the systems. This field guide describes the complex geology, regional hydrogeology, and unique landscape characterized by high-gradient subterranean streams, carbonate fensters, and deep caves of the GRSM karst.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geology at Every Scale: Field Excursions for the 2018 GSA Southeastern Section Meeting, Geological Society of America Field Guide 50","language":"English","publisher":"Geological Society of America","doi":"10.1130/2018.0050(03)","isbn":"9780813700502","usgsCitation":"Miller, B., Bradley, M., and Brown, T.L., 2018, Karst hydrogeology of Tuckaleechee Cove and the western Great Smoky Mountains, Tennessee and North Carolina, chap. of Geology at Every Scale: Field Excursions for the 2018 GSA Southeastern Section Meeting, Geological Society of America Field Guide 50, p. 49-60, https://doi.org/10.1130/2018.0050(03).","productDescription":"12 p.","startPage":"49","endPage":"60","ipdsId":"IP-092132","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":359714,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Tennessee","otherGeospatial":"Great Smoky Mountains, Tuckaleechee Cove","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bfe65e3e4b0815414ca60fa","contributors":{"authors":[{"text":"Miller, Benjamin 0000-0003-4795-3442 bvmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-4795-3442","contributorId":197345,"corporation":false,"usgs":true,"family":"Miller","given":"Benjamin","email":"bvmiller@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradley, Mike 0000-0002-2979-265X mbradley@usgs.gov","orcid":"https://orcid.org/0000-0002-2979-265X","contributorId":582,"corporation":false,"usgs":true,"family":"Bradley","given":"Mike","email":"mbradley@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Teresa L.","contributorId":210772,"corporation":false,"usgs":false,"family":"Brown","given":"Teresa","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":751906,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198410,"text":"70198410 - 2018 - Comparison of a prepositioned areal electrofishing device and fixed underwater videography for sampling riverine fishes","interactions":[],"lastModifiedDate":"2019-03-04T11:26:20","indexId":"70198410","displayToPublicDate":"2018-07-01T11:00:20","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of a prepositioned areal electrofishing device and fixed underwater videography for sampling riverine fishes","docAbstract":"Prepositioned areal electrofishing devices (PAEDs) are used to evaluate microhabitat use by fishes because they minimize fright biases associated with traditional electrofishing techniques (e.g., boat electrofishing). Similarly, fixed underwater videography (FUV) is commonly used to minimize the effect of observers on fish behavior. The specific objectives of this research were to evaluate estimates of taxonomic occurrence and diversity between PAEDs and FUV and determine an appropriate time interval between positioning and electrifying of a PAED to reduce effects of PAED positioning on fish occurrence. Video cameras were positioned instream at 28 locations on the Kootenai River, Idaho, prior to PAED deployment such that the entire immobilization zone of the PAED was captured on camera. Following a 4-min acclimation period, cameras recorded fish behavior approximately 15 min prior to and 20 min following PAED deployment. Electrical current was applied to the PAEDs for 20 s immediately following the FUV procedure, and immobilized fishes were collected and processed. Video footage was subsampled in the laboratory, and fishes in the video were identified and enumerated in 5-s or 20-s intervals. Fixed underwater videography sampled more taxa than PAEDs at any given site. However, fishes sampled with FUV were difficult to identify, and most individuals were classified as “unidentifiable.” Consequently, direct comparisons between FUV and PAEDs are limited. Our results indicate that PAEDs should remain undisturbed for a minimum of 12 min before the equipment is electrified. Both PAEDs and FUV provide an estimate of taxonomic occurrence, but logistical and financial constraints along with project objectives must be considered when selecting between these 2 gear types. Results from this study provide information on the effectiveness of each gear type as it relates to the characterization of riverine fish assemblages at a small spatial scale.
","language":"English","publisher":"Monte L. Bean Life Science Museum, Brigham Young University","doi":"10.3398/064.078.0107","usgsCitation":"Branigan, P., Quist, M.C., Shepard, B.B., and Ireland, S.C., 2018, Comparison of a prepositioned areal electrofishing device and fixed underwater videography for sampling riverine fishes: Western North American Naturalist, v. 78, no. 1, p. 65-75, https://doi.org/10.3398/064.078.0107.","productDescription":"11 p.","startPage":"65","endPage":"75","ipdsId":"IP-076475","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488781,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarsarchive.byu.edu/wnan/vol78/iss1/6","text":"External Repository"},{"id":356132,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc41ce4b0f5d57878e9f1","contributors":{"authors":[{"text":"Branigan, Philip R.","contributorId":206650,"corporation":false,"usgs":false,"family":"Branigan","given":"Philip R.","affiliations":[{"id":37369,"text":"University of Idaho, Moscow, ID","active":true,"usgs":false}],"preferred":false,"id":741361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839 mquist@usgs.gov","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":171392,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":741360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shepard, Bradley B.","contributorId":145880,"corporation":false,"usgs":false,"family":"Shepard","given":"Bradley","email":"","middleInitial":"B.","affiliations":[{"id":6765,"text":"Montana State University, Department of Land Resources and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":741362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ireland, Susan C.","contributorId":206651,"corporation":false,"usgs":false,"family":"Ireland","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":37370,"text":"Kootenai Tribe of Idaho, Bonners Ferry, ID","active":true,"usgs":false}],"preferred":false,"id":741363,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198758,"text":"70198758 - 2018 - Message in a bottle: The story of drifting plastic in the eastern Mediterranean Sea","interactions":[],"lastModifiedDate":"2018-08-20T10:38:21","indexId":"70198758","displayToPublicDate":"2018-07-01T10:32:44","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3707,"text":"Waste Management","active":true,"publicationSubtype":{"id":10}},"title":"Message in a bottle: The story of drifting plastic in the eastern Mediterranean Sea","docAbstract":"The Mediterranean Sea is a closed basin with limited water exchange through the Strait of Gibraltar, and sites along its shores show the greatest densities of marine debris in the world. Plastic bottles, which are a growing concern due to high consumption of soft drinks and bottled water, constitute most of the floating marine debris. In this paper we present the transport mechanisms of floating marine debris to and from the Israeli coast using an experimental offshore release and recovery of plastic bottles, with the participation of citizens. Many bottles released near the beach in the south part of Israel, returned to the beach at a short distance and time from the release point. Some release locations had no bottle returns. Ten bottles, released from three locations, were recovered many dozens to hundreds of kilometers from the release point. Since most of the westward water flow in the eastern Mediterranean is subsurface, it was not surprising to find our floating debris only in the east. That makes the Levant basin in the eastern Mediterranean a collection area for floating debris.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.wasman.2018.04.034","usgsCitation":"Pasternak, G., Zviely, D., Ariel, A., Spanier, E., and Ribic, C., 2018, Message in a bottle: The story of drifting plastic in the eastern Mediterranean Sea: Waste Management, v. 77, p. 67-77, https://doi.org/10.1016/j.wasman.2018.04.034.","productDescription":"11 p.","startPage":"67","endPage":"77","ipdsId":"IP-091991","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":356620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mediterranean Sea","volume":"77","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a2a2e4b0702d0e842f9e","contributors":{"authors":[{"text":"Pasternak, Galia","contributorId":192017,"corporation":false,"usgs":false,"family":"Pasternak","given":"Galia","email":"","affiliations":[],"preferred":false,"id":743062,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zviely, Dov","contributorId":192018,"corporation":false,"usgs":false,"family":"Zviely","given":"Dov","email":"","affiliations":[],"preferred":false,"id":743063,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ariel, Asaf","contributorId":192019,"corporation":false,"usgs":false,"family":"Ariel","given":"Asaf","email":"","affiliations":[],"preferred":false,"id":743064,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spanier, Ehud","contributorId":192020,"corporation":false,"usgs":false,"family":"Spanier","given":"Ehud","email":"","affiliations":[],"preferred":false,"id":743065,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":742873,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}