The indigenous forest birds of American Samoa are increasingly threatened by changing patterns of rainfall and temperature that are associated with climate change as well as environmental stressors associated with agricultural and urban development, invasive species, and new introductions of avian diseases and disease vectors. Long term changes in their distribution, diversity, and population sizes could have significant impacts on the ecological integrity of the islands because of their critical role as pollinators and seed dispersers. We documented diversity of vector borne parasites on Tutuila and Ta‘u Islands over a 10-year period to expand earlier observations of Plasmodium, Trypanosoma, and filarial parasites, to provide better parasite identifications, and to create a better baseline for detecting new parasite introductions. We also identified potential mosquito vectors of avian Plasmodium and Trypanosoma, determined whether land clearing and habitat alterations associated with subsistence farming within the National Park of American Samoa can influence parasite prevalence, and determined whether parasite prevalence is correlated with seasonal changes in rainfall, temperature and wind speed.
\nThree taxonomically distinct lineages of Plasmodium were identified from mosquito vectors and forest birds based on partial sequence data from parasite mitochondrial genes. All three have been described from passerine and galliform birds in Australasia. Two lineages, SCEDEN01 and ORW1, had elongate gametocytes and large schizonts that were consistent with species of Plasmodium in the subgenus Giavannolaia, but were taxonomically distinct from known morphological species of Plasmodium based on a Bayesian phylogenetic analysis of a 478 bp region of the parasite cytochrome b gene. Both are candidates for description as new species. The third lineage (GALLUS02) was detected only in mosquito vectors on Tutuila and was similar in cytochrome b sequence to P. juxtanucleare, a pathogenic species of Plasmodium from chickens and other galliform birds from Australasia, Africa, and South America. Plasmodium relictum, the malarial parasite that has had such a devastating impact on Hawaiian forest birds, was not detected. We observed large, striated trypanosomes in avian hosts from both Tutuila and Ta‘u Islands that fell within the same taxonomic clade as T. corvi and T. culicavium based on 18S ribosomal DNA sequence. We also observed sheathed microfilariae with pointed tails that had some morphological similarities to microfilaria from species of Pelecitus, Struthiofilaria and Eulimdana, but identification will require recovery and examination of adult filarial worms from the connective tissue or body cavities of infected birds. We also observed one or more species of haemococcidians (Isospora, synonym = Atoxoplasma) within circulating lymphocytes from multiple avian host species.
\nOverall prevalence of Plasmodium was higher on Ta‘u (22%, 75/341) than Tutuila (9.2%, 27/294), with most infections occurring in Polynesian starlings, Samoan starlings, Wattled honeyeaters, and Cardinal honeyeaters. Prevalence was relatively constant from year to year and between seasons at individual study sites, but varied among study sites, with highest rates of infection in areas with agricultural activity at Faleasao (37.4%, 73/195, Ta‘u Island) and Amalau Valley (9.7%, 21/216, Tutuila Island). Prevalence in more remote areas of the National Park of American Samoa was lower, ranging from 1.4% (2/146) at Laufuti and Luatele on Ta‘u to 7.7% (6/78) at Olo Ridge on Tutuila. Similar trends were evident for infections with Trypanosoma and filarial worms. Overall prevalence was not influenced significantly by warmer, wet (summer) or cooler, dry (winter) season.
\nWe detected Plasmodium infections in Culex sitiens and C. quinquefasciatus through either salivary gland and midgut dissections or PCR amplification of parasite cytochrome b genes in pooled or individual samples of mosquitoes that were collected on Tutuila. Pooled or individual Aedes oceanicus, A. polynesiensis, A. tutuilae, A. upolensis, A. nocturnus, Aedes (Finlaya) (mixed pools of A. samoanus, A. oceanicus, A. tutuilae), Aedes (Stegomyia) (mixed pools of A. aegypti, A. upolensis, A. polynesiensis), and C. annulirostris were negative for Plasmodium, but we detected infections with Trypanosoma through midgut and salivary gland dissections in a single C. sitiens from Amalau Valley, Tutuila and three A. oceanicus from Faleasao, Ta‘u. Two of the A. oceanicus from Faleasao amplified successfully with Trypanosoma primers, but sequences were distinctly different from those obtained from avian hosts.
\nWe found a strong association between land use and prevalence of mosquito-transmitted parasites on Ta‘u Island with odds of being infected more than 20 times greater in agricultural plots than more remote native forest. This relationship was evident on Tutuila Island but not statistically significant because of the close proximity of study sites and observed movement of birds between native forest and agricultural land. Our data support previous studies that have suggested that Plasmodium and other vector-borne parasites are part of the indigenous parasite fauna in American Samoa. Transmission dynamics appear to be affected by environmental changes associated with land use practices.
\n","language":"English","publisher":"University of Hawaii at Hilo","publisherLocation":"Hilo, Hi","usgsCitation":"Atkinson, C.T., Utuzurrum, R.B., Seamon, J.O., Schmaedick, M.A., Lapointe, D., Apelgren, C., Egan, A.N., and Watcher-Weatherwax, W., 2016, Effects of Climate and land use on diversity, prevalence, and seasonal transmission of avian hematozoa in American Samoa: Technical Report HCSU-072, Report: iv, 47 p.","productDescription":"Report: iv, 47 p.","startPage":"1","endPage":"47","numberOfPages":"52","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072281","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"HI","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a9ad47e4b05e859bdfb8dd","contributors":{"authors":[{"text":"Atkinson, Carter T. 0000-0002-4232-5335 catkinson@usgs.gov","orcid":"https://orcid.org/0000-0002-4232-5335","contributorId":1124,"corporation":false,"usgs":true,"family":"Atkinson","given":"Carter","email":"catkinson@usgs.gov","middleInitial":"T.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":621154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Utuzurrum, Ruth B.","contributorId":167126,"corporation":false,"usgs":false,"family":"Utuzurrum","given":"Ruth","email":"","middleInitial":"B.","affiliations":[{"id":24621,"text":"Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":621156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seamon, Joshua O.","contributorId":25816,"corporation":false,"usgs":true,"family":"Seamon","given":"Joshua","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":621157,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmaedick, Mark A.","contributorId":167127,"corporation":false,"usgs":false,"family":"Schmaedick","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":24622,"text":"Division of Community and Natural Resources, American Samoa Community College","active":true,"usgs":false}],"preferred":false,"id":621158,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LaPointe, Dennis A. 0000-0002-6323-263X dlapointe@usgs.gov","orcid":"https://orcid.org/0000-0002-6323-263X","contributorId":150365,"corporation":false,"usgs":true,"family":"LaPointe","given":"Dennis","email":"dlapointe@usgs.gov","middleInitial":"A.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":621155,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Apelgren, Chloe","contributorId":140012,"corporation":false,"usgs":false,"family":"Apelgren","given":"Chloe","email":"","affiliations":[{"id":13356,"text":"University of Hawaii, Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":621159,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Egan, Ariel N.","contributorId":150954,"corporation":false,"usgs":false,"family":"Egan","given":"Ariel","email":"","middleInitial":"N.","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":621160,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Watcher-Weatherwax, William","contributorId":167128,"corporation":false,"usgs":false,"family":"Watcher-Weatherwax","given":"William","email":"","affiliations":[{"id":24621,"text":"Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":621161,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70177910,"text":"70177910 - 2016 - Geochemistry of formation waters from the Wolfcamp and “Cline” shales: Insights into brine origin, reservoir connectivity, and fluid flow in the Permian Basin, USA","interactions":[],"lastModifiedDate":"2019-05-24T08:19:21","indexId":"70177910","displayToPublicDate":"2016-01-30T19:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geochemistry of formation waters from the Wolfcamp and “Cline” shales: Insights into brine origin, reservoir connectivity, and fluid flow in the Permian Basin, USA","docAbstract":"
Despite being one of the most important oil producing provinces in the United States, information on basinal hydrogeology and fluid flow in the Permian Basin of Texas and New Mexico is lacking. The source and geochemistry of brines from the basin were investigated (Ordovician- to Guadalupian-age reservoirs) by combining previously published data from conventional reservoirs with geochemical results for 39 new produced water samples, with a focus on those from shales. Salinity of the Ca–Cl-type brines in the basin generally increases with depth reaching a maximum in Devonian (median = 154 g/L) reservoirs, followed by decreases in salinity in the Silurian (median = 77 g/L) and Ordovician (median = 70 g/L) reservoirs. Isotopic data for B, O, H, and Sr and ion chemistry indicate three major types of water. Lower salinity fluids (<70 g/L) of meteoric origin in the middle and upper Permian hydrocarbon reservoirs (1.2–2.5 km depth; Guadalupian and Leonardian age) likely represent meteoric waters that infiltrated through and dissolved halite and anhydrite in the overlying evaporite layer. Saline (>100 g/L), isotopically heavy (O and H) water in Leonardian [Permian] to Pennsylvanian reservoirs (2–3.2 km depth) is evaporated, Late Permian seawater. Water from the Permian Wolfcamp and Pennsylvanian “Cline” shales, which are isotopically similar but lower in salinity and enriched in alkalis, appear to have developed their composition due to post-illitization diffusion into the shales. Samples from the “Cline” shale are further enriched with NH4, Br, I and isotopically light B, sourced from the breakdown of marine kerogen in the unit. Lower salinity waters (<100 g/L) in Devonian and deeper reservoirs (>3 km depth), which plot near the modern local meteoric water line, are distinct from the water in overlying reservoirs. We propose that these deep meteoric waters are part of a newly identified hydrogeologic unit: the Deep Basin Meteoric Aquifer System. Chemical, isotopic, and pressure data suggest that despite over-pressuring in the Wolfcamp shale, there is little potential for vertical fluid migration to the surface environment via natural conduits.
\nSilver Lake is a 672-acre inland lake located in Oceana County, Michigan, and is a major tourist destination due to its proximity to Lake Michigan and the surrounding outdoor recreational opportunities. In recent years, Silver Lake exhibited patterns of high phosphorus concentrations, elevated chlorophyll a concentrations, and nuisance algal blooms. The U.S. Geological Survey (USGS), in cooperation with the Silver Lake Improvement Board and in collaboration with the Annis Water Resources Institute (AWRI) of Grand Valley State University, designed a study to assess the hydrologic and nutrient inputs to Silver Lake in order to identify the events and conditions that affect the nutrient chemistry and production of algal blooms in the lake. This information can inform water-resource managers in developing various management strategies to prevent or reduce the occurrence of future algal blooms.
\nUSGS and AWRI scientists collected data from November 2012 to December 2014 to provide information for future management decisions for Silver Lake. Silver Lake can be classified as a polymictic lake and has a residence time of approximately 223 days. Based on the mean lake Secchi depth, total phosphorus, and total nitrogen concentrations, Silver Lake is classified as a eutrophic lake. In-situ bioassay results indicate that algal growth in Silver Lake is colimited by both nitrogen and phosphorus. The nutrient budget for Silver Lake was calculated using the BATHTUB model based on 2 years of water-quality data collection. The BATHTUB model, developed by the U.S. Army Corps of Engineers, treats the lake as a well-mixed system with multiple inputs and outlets for both water and dissolved constituents, such as nutrients.
\nBased on results of the BATHTUB model, which were conditioned on observed concentrations and flows, the mean annual input of phosphorus to Silver Lake was approximately 1,342 pounds (lb); the mean annual input of nitrogen to Silver Lake was approximately 51,998 lb. The major measured sources of phosphorus loading to Silver Lake were groundwater and Hunter Creek, whereas the major measured sources of nitrogen to Silver Lake were Hunter Creek, groundwater, and atmospheric deposition. The largest loading of phosphorus and nitrogen to Silver Lake occurred during the spring. Minimal phosphorus deposition (if any) occurred in the lakebed sediment; however, of the nitrogen that entered Silver Lake, approximately 42.2 percent was deposited in the lakebed sediment as simulated by the BATHTUB model.
\nIn addition to measured sources, a septic load model was used to estimate the likely range of septic contribution to groundwater and adjacent surface waters. The likely septic loading scenario estimates that septic systems contribute 47.8 percent of the phosphorus to groundwater and 22.3 percent of phosphorus to Hunter Creek. These results indicate that septic systems are a major source of phosphorus loading to Silver Lake. The likely septic loading scenario indicated that septic systems account for 0.95 percent of the nitrogen load to Hunter Creek and 1.1 percent of the contribution of nitrogen to groundwater.
\nThe BATHTUB model was used to estimate future nutrient loading and eutrophication scenarios based on water-quality data collected from Silver Lake, groundwater, major tributaries, and atmospheric deposition. A separate septic load model was used to estimate the septic contribution to groundwater or directly to surface water, and the nutrient load estimates were modeled using the BATHTUB model to determine subsequent water-quality changes to Silver Lake.
\nDirector, Michigan Water Science Center
U.S. Geological Survey
6520 Mercantile Way Suite 5
Lansing, MI 48911–5991
http://mi.water.usgs.gov/
Arnold Air Force Base occupies about 40,000 acres in Coffee and Franklin Counties, Tennessee. The primary mission of Arnold Air Force Base is to provide risk-reduction information in the development of aerospace products through test and evaluation. This mission is achieved in part through test facilities at Arnold Engineering Development Complex (AEDC), which occupies about 4,000 acres in the center of Arnold Air Force Base. Arnold Air Force Base is underlain by gravel and limestone aquifers, the most productive of which is the Manchester aquifer. Several volatile organic compounds, primarily chlorinated solvents, have been identified in the groundwater at Arnold Air Force Base. In 2011, the U.S. Geological Survey, in cooperation with the U.S. Air Force, Arnold Air Force Base, completed a study of groundwater flow focused on the Arnold Engineering Development Complex area. The Arnold Engineering Development Complex area is of particular concern because within this area (1) chlorinated solvents have been identified in the groundwater, (2) the aquifers are dewatered around below-grade test facilities, and (3) there is a regional groundwater divide.
\nDuring May 2011, when water levels were near seasonal highs, water-level data were collected from 374 monitoring wells; and during September 2011, when water levels were near seasonal lows, water-level data were collected from 376 monitoring wells. Potentiometric surfaces were mapped by contouring altitudes of water levels measured in wells completed in the shallow aquifer, the upper and lower parts of the Manchester aquifer, and the Fort Payne aquifer. Water levels are generally 2 to 14 feet lower in September compared to May. The potentiometric-surface maps for all aquifers indicate a groundwater depression at the J4 test cell. Similar groundwater depressions in the shallow and upper parts of the Manchester aquifer are within the main testing area at the Arnold Engineering Development Complex at dewatering facilities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155165","collaboration":"Prepared in cooperation with the United States Air Force, Arnold Air Force Base","usgsCitation":"Haugh, C.J., and Robinson, J.A., 2016, Potentiometric surfaces of the Arnold Engineering Development Complex area, Arnold Air Force Base, Tennessee, May and September 2011: U.S. Geological Survey Scientific Investigations Report 2015–5165, 23 p., https://dx.doi.org/10.3133/sir20155165.","productDescription":"v, 28 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059351","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"links":[{"id":314981,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5165/sir20155165.pdf","text":"Report","size":"1.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5165"},{"id":314980,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5165/coverthb.jpg"}],"country":"United States","state":"Tennessee","county":"Coffee County, Franklin County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.5,\n 35\n ],\n [\n -86.5,\n 35.75\n ],\n [\n -85.5,\n 35.75\n ],\n [\n -85.5,\n 35\n ],\n [\n -86.5,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
http://tn.water.usgs.gov
The U.S. Geological Survey (USGS) installed the first gage to measure the flow of water into California’s Sacramento–San Joaquin River Delta from the Sacramento River in the late 1800s. Today, a network of 35 hydro-acoustic meters measure flow throughout the delta. This region is a critical part of California’s freshwater supply and conveyance system. With the data provided by this flow-station network—sampled every 15 minutes and updated to the web every hour—state and federal water managers make daily decisions about how much freshwater can be pumped for human use, at which locations, and when. Fish and wildlife scientists, working with water managers, also use this information to protect fish species affected by pumping and loss of habitat. The data are also used to help determine the success or failure of efforts to restore ecosystem processes in what has been called the “most managed and highly altered” watershed in the country.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153061","usgsCitation":"Burau, J.R., Ruhl, C.A., and Work, P.A., 2016, Innovation in Monitoring: The U.S. Geological Survey Sacramento-San Joaquin River Delta, California, Flow-Station Network: U.S. Geological Survey Fact Sheet 2015-3061, 6 p., https://dx.doi.org/10.3133/fs20153061.","productDescription":"6 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044692","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":315073,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3061/coverthb.jpg"},{"id":315074,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3061/fs20153061.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3061 PDF"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River, San Joaquin River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 37.75\n ],\n [\n -122,\n 38.5\n ],\n [\n -121.25,\n 38.5\n ],\n [\n -121.25,\n 37.75\n ],\n [\n -122,\n 37.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
The oldest postglacial lapilli–ash tephra recognized in sedimentary records surrounding Mount Rainier (Washington State, USA) is R tephra, a very early Holocene deposit that acts as an important stratigraphic and geochronologic marker bed. This multidisciplinary study incorporates tephrostratigraphy, radiocarbon dating, petrography, and electron microprobe analysis to characterize R tephra. Tephra samples were collected from Tipsoo Lake and a stream-cut exposure in the Cowlitz Divide area of Mount Rainier National Park. Field evidence from 25 new sites suggests that R tephra locally contains internal bedding and has a wider distribution than previously reported. Herein, we provide the first robust suite of geochemical data that characterize the tephra. Glass compositions are heterogeneous, predominantly ranging from andesite to rhyolite in ash- to lapilli-sized clasts. The mineral assemblage consists of plagioclase, orthopyroxene, clinopyroxene, and magnetite with trace apatite and ilmenite. Subaerial R tephra deposits appear more weathered in hand sample than subaqueous deposits, but weathering indices suggest negligible chemical weathering in both deposits. Statistical analysis of radiocarbon ages provides a median age for R tephra of ∼10 050 cal years BP, and a 2σ error range between 9960 and 10 130 cal years BP.
","language":"English","publisher":"NRC Research Press ","doi":"10.1139/cjes-2015-0115","usgsCitation":"Samolczyk, M., Vallance, J.W., Cubley, J., Osborn, G., and Clark, D.H., 2016, Geochemical characterization and dating of R tephra, a post-glacial marker bed in Mount Rainier National Park, Washington, U.S.A.: Canadian Journal of Earth Sciences, v. 53, no. 2, p. 202-217, https://doi.org/10.1139/cjes-2015-0115.","productDescription":"16 p. ","startPage":"202","endPage":"217","ipdsId":"IP-065487","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":336319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mt.Rainier ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.91940307617188,\n 46.67394106549699\n ],\n [\n -121.453857421875,\n 46.67394106549699\n ],\n [\n -121.453857421875,\n 46.98587362966405\n ],\n [\n -121.91940307617188,\n 46.98587362966405\n ],\n [\n -121.91940307617188,\n 46.67394106549699\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"53","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b69a41e4b01ccd54ff3f9e","contributors":{"authors":[{"text":"Samolczyk, Mary","contributorId":184093,"corporation":false,"usgs":false,"family":"Samolczyk","given":"Mary","email":"","affiliations":[],"preferred":false,"id":673531,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vallance, James W. 0000-0002-3083-5469 jvallance@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5469","contributorId":547,"corporation":false,"usgs":true,"family":"Vallance","given":"James","email":"jvallance@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":673530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cubley, Joel","contributorId":184094,"corporation":false,"usgs":false,"family":"Cubley","given":"Joel","email":"","affiliations":[],"preferred":false,"id":673532,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Osborn, Gerald","contributorId":184095,"corporation":false,"usgs":false,"family":"Osborn","given":"Gerald","email":"","affiliations":[],"preferred":false,"id":673533,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Douglas H.","contributorId":184096,"corporation":false,"usgs":false,"family":"Clark","given":"Douglas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":673534,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70162094,"text":"ofr20161006 - 2016 - The Integrated Landscape Modeling partnership - Current status and future directions","interactions":[],"lastModifiedDate":"2017-10-26T11:02:21","indexId":"ofr20161006","displayToPublicDate":"2016-01-28T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1006","title":"The Integrated Landscape Modeling partnership - Current status and future directions","docAbstract":"The Integrated Landscape Modeling (ILM) partnership is an effort by the U.S. Geological Survey (USGS) and U.S. Department of Agriculture (USDA) to identify, evaluate, and develop models to quantify services derived from ecosystems, with a focus on wetland ecosystems and conservation effects. The ILM partnership uses the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) modeling platform to facilitate regional quantifications of ecosystem services under various scenarios of land-cover change that are representative of differing conservation program and practice implementation scenarios. To date, the ILM InVEST partnership has resulted in capabilities to quantify carbon stores, amphibian habitat, plant-community diversity, and pollination services. Work to include waterfowl and grassland bird habitat quality is in progress. Initial InVEST modeling has been focused on the Prairie Pothole Region (PPR) of the United States; future efforts might encompass other regions as data availability and knowledge increase as to how functions affecting ecosystem services differ among regions.
The ILM partnership is also developing the capability for field-scale process-based modeling of depressional wetland ecosystems using the Agricultural Policy/Environmental Extender (APEX) model. Progress was made towards the development of techniques to use the APEX model for closed-basin depressional wetlands of the PPR, in addition to the open systems that the model was originally designed to simulate. The ILM partnership has matured to the stage where effects of conservation programs and practices on multiple ecosystem services can now be simulated in selected areas. Future work might include the continued development of modeling capabilities, as well as development and evaluation of differing conservation program and practice scenarios of interest to partner agencies including the USDA’s Farm Service Agency (FSA) and Natural Resources Conservation Service (NRCS). When combined, the ecosystem services modeling capabilities of InVEST and the process-based abilities of the APEX model should provide complementary information needed to meet USDA and the Department of the Interior information needs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161006","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service and Farm Service Agency","usgsCitation":"Mushet, D.M., and Scherff, E.J., 2016, The integrated landscape modeling partnership—Current status and future directions (ver. 1.1, December 2016): U.S. Geological Survey Open-File Report 2016–1006, 59 p., https://dx.doi.org/10.3133/ofr20161006.","productDescription":"72 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070297","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":314982,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1006/coverthb1.1.jpg"},{"id":332701,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1006/version_history.txt"},{"id":314983,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1006/ofr20161006.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1006"}],"country":"United States","state":"Iowa, Minnesota, Nebraska, North Dakota, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.82080078125,\n 48.99463598353408\n ],\n [\n -105.13916015625,\n 48.90805939965008\n ],\n [\n -104.83154296875,\n 48.44377831058805\n ],\n [\n -104.4140625,\n 47.945786463687185\n ],\n [\n -103.18359375,\n 47.87214396888731\n ],\n [\n -102.39257812499999,\n 47.502358951968596\n ],\n [\n -101.29394531249999,\n 47.010225655683485\n ],\n [\n -101.0302734375,\n 46.66451741754235\n ],\n [\n -100.96435546875,\n 45.87471224890479\n ],\n [\n -100.70068359374999,\n 45.27488643704894\n ],\n [\n -100.8544921875,\n 44.4808302785626\n ],\n [\n -100.30517578125,\n 43.929549935614595\n ],\n [\n -98.89892578125,\n 43.03677585761058\n ],\n [\n -97.22900390625,\n 42.84375132629021\n ],\n [\n -95.07568359375,\n 42.04929263868686\n ],\n [\n -93.955078125,\n 41.590796851056005\n ],\n [\n -93.05419921875,\n 41.57436130598913\n ],\n [\n -92.4169921875,\n 41.77131167976407\n ],\n [\n -92.35107421874999,\n 42.391008609205045\n ],\n [\n -92.74658203125,\n 43.34116005412307\n ],\n [\n -93.31787109374999,\n 43.929549935614595\n ],\n [\n -93.88916015625,\n 44.2294565683017\n ],\n [\n -94.68017578125,\n 45.413876460821086\n ],\n [\n -94.9658203125,\n 46.84516443029279\n ],\n [\n -96.6357421875,\n 48.472921272487824\n ],\n [\n -98.0859375,\n 48.951366470947725\n ],\n [\n -103.82080078125,\n 48.99463598353408\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted January 28, 2016; Version 1.1: December 30, 2016","contact":"Director, USGS Northern Prairie Wildlife Research Center
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A multidimensional model of geographic features has been developed and implemented with data from The National Map of the U.S. Geological Survey. The model, programmed in C++ and implemented as a feature library, was tested with data from the National Hydrography Dataset demonstrating the capability to handle changes in feature attributes, such as increases in chlorine concentration in a stream, and feature geometry, such as the changing shoreline of barrier islands over time. Data can be entered directly, from a comma separated file, or features with attributes and relationships can be automatically populated in the model from data in the Spatial Data Transfer Standard format.
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Evapotranspiration (ET) is an important component of micro- and macro-scale climatic processes. In agriculture, estimates of ET are frequently used to monitor droughts, schedule irrigation, and assess crop water productivity over large areas. Currently, in situ measurements of ET are difficult to scale up for regional applications, so remote sensing technology has been increasingly used to estimate crop ET. Ratio-based vegetation indices retrieved from optical remote sensing, like the Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index, and Enhanced Vegetation Index are critical components of these models, particularly for the partitioning of ET into transpiration and soil evaporation. These indices have their limitations, however, and can induce large model bias and error. In this study, micrometeorological and spectroradiometric data collected over two growing seasons in cotton, maize, and rice fields in the Central Valley of California were used to identify spectral wavelengths from 428 to 2295 nm that produced the highest correlation to and lowest error with ET, transpiration, and soil evaporation. The analysis was performed with hyperspectral narrowbands (HNBs) at 10 nm intervals and multispectral broadbands (MSBBs) commonly retrieved by Earth observation platforms. The study revealed that (1) HNB indices consistently explained more variability in ET (ΔR2 = 0.12), transpiration (ΔR2 = 0.17), and soil evaporation (ΔR2 = 0.14) than MSBB indices; (2) the relationship between transpiration using the ratio-based index most commonly used for ET modeling, NDVI, was strong (R2 = 0.51), but the hyperspectral equivalent was superior (R2 = 0.68); and (3) soil evaporation was not estimated well using ratio-based indices from the literature (highest R2 = 0.37), but could be after further evaluation, using ratio-based indices centered on 743 and 953 nm (R2 = 0.72) or 428 and 1518 nm (R2 = 0.69).
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VS30 is typically based on geophysical measurements of VS derived from invasive and noninvasive techniques at sites of interest. Owing to cost considerations, as well as logistical and environmental concerns, VS30 data are sparse or not readily available for most areas. Where data are available, VS30 values are often assembled in assorted formats that are accessible from disparate and (or) impermanent Web sites. To help remedy this situation, we compiled VS30 measurements obtained by studies funded by the U.S. Geological Survey (USGS) and other governmental agencies. Thus far, we have compiled VS30 values for 2,997 sites in the United States, along with metadata for each measurement from government-sponsored reports, Web sites, and scientific and engineering journals. Most of the data in our VS30 compilation originated from publications directly reporting the work of field investigators. A small subset (less than 20 percent) of VS30 values was previously compiled by the USGS and other research institutions. Whenever possible, VS30 originating from these earlier compilations were crosschecked against published reports. Both downhole and surface-based VS30 estimates are represented in our VS30 compilation. Most of the VS30 data are for sites in the western contiguous United States (2,141 sites), whereas 786 VS30 values are for sites in the Central and Eastern United States; 70 values are for sites in other parts of the United States, including Alaska (15 sites), Hawaii (30 sites), and Puerto Rico (25 sites). An interactive map is hosted on the primary USGS Web site for accessing VS30 data (https://earthquake.usgs.gov/data/vs30/us/).
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Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
http://earthquake.usgs.gov/
Missouri was the leading producer of lead in the United States—as well as the world—for more than a century. One of the lead sources is known as the Old Lead Belt, located in southeast Missouri. The primary ore mineral in the region is galena, which can be found both in surface deposits and underground as deep as 200 feet. More than 8.5 million tons of lead were produced from the Old Lead Belt before operations ceased in 1972. Although active lead mining has ended, the effects of mining activities still remain in the form of large mine waste piles on the landscape typically near tributaries and the main stem of the Big River, which drains the Old Lead Belt. Six large mine waste piles encompassing more than 2,800 acres, exist within the Big River Basin. These six mine waste piles have been an available source of trace element-rich suspended sediments transported by natural erosional processes downstream into the Big River.
\nA study was performed by the U.S. Geological Survey in cooperation with U.S. Environmental Protection Agency, Region 7, to calculate and characterize suspended-sediment quantity and quality within the Big River basin after reclamation of the mine waste piles ended in 2012. Streamflow and suspended sediments were quantified and sampled at two locations along a 68-mile reach of the Big River between Bonne Terre and Byrnes Mill, Missouri. The results will help regulatory agencies, such as the U.S. Environmental Protection Agency and U.S. Fish and Wildlife Service, determine impaired reaches and ecosystems for remedial and restoration efforts.
\nContinuous stream stage, water temperature, and turbidity, and discrete suspended-sediment concentration data were collected at the two sites between October 2011 and September 2013. Suspended-sediment samples were collected during various hydrologic conditions to develop a regression model between discrete suspended-sediment concentration and continuous turbidity. Suspended sediments collected during stormflow events were analyzed for concentrations of trace elements such as barium, cadmium, lead, and zinc within two sediment size fractions. Event loads and annual loads of suspended sediment and select trace elements in suspended sediments also were calculated.
\nSuspended-sediment loads computed by the regression model increased downstream from about 201,000 tons at the upstream site to about 355,000 tons at the downstream site during the study period. Stormflow-event-based (hereinafter referred to as “event-based”) suspended-sediment loads ranged from 180 to 32,000 tons at the upstream sampling site and 390 to 53,000 tons at the downstream site along the Big River. Although only seven stormflow events at the upstream site and six at the downstream site were sampled, the event-based suspended-sediment loads accounted for nearly 30 percent of the total suspended-sediment loads computed at both sites, indicating most of the suspended sediment transported through the Big River occurs during higher streamflows.
\nSediment quality guidelines, known as the threshold effect concentration and the probable effect concentration, used to assess toxicity of trace-element concentrations in sediments were compared to the cadmium, lead, and zinc concentrations in suspended sediment samples collected during stormflow events. All concentrations of cadmium, lead, and zinc in event-based suspended sediment samples exceeded the threshold and probable effect concentrations. Lead and zinc concentrations in the sediment size fraction less than 0.063 millimeters also exceeded the toxic effect threshold, above which sediment is considered to be heavily polluted causing adverse effects on sediment-dwelling organisms. Concentrations of cadmium and zinc in event-based suspended sediment samples were notably higher in samples from the upstream site than samples from the downstream site, indicating the sources of sediments enriched in these trace elements decrease in the downstream area of the watershed. The reduction in concentration of cadmium and zinc could be from dissolution of the constituents during transport or possibly a decrease in downstream source material. The lead concentration exceedance of the probable effects concentration as well as the threshold effects concentration indicates that lead-rich suspended sediments in the fraction less than 0.063 millimeters are readily available within the Big River Basin for transport. These sediments remain in the system from historical mining, and as the reclamation of mine waste piles in the upstream area of the watershed reduce additional sediment loadings, these fine sediments may be continually released as the river scours the streambed and erodes stream banks causing the lead-rich suspended sediment to remain in a state of equilibrium.
\nBarium concentrations in suspended-sediments were nearly twice as high in stormflow event samples collected at the downstream site as compared to samples from the upstream site. The source of barium in the Big River could be from Mineral Fork and Mill Creek, which flow through the historical barite (barium sulfate, also known as tiff) mining district in Washington County, and discharge into the Big River between the two study sites.
\nTotal trace-element loads and yields in suspended sediments were computed from the sampled events for each year in the study. The total barium loads in suspended sediments were higher for sampled events collected at the downstream site than the upstream site during both study years. Cadmium and zinc loads in suspended sediments were lower at the downstream site than the upstream site, although the decrease in total load was not substantial during the study period. Lead loads in suspended sediments were lower at the downstream site during the first study year, with a slightly higher load downstream in the second year though the increase from upstream to downstream was small. Event-based yields were higher at the upstream site, indicating that readily available sediment sources are closer to the upstream site where more mining affected areas are located. The estimates determined during large precipitation events indicate that large sources of suspended sediments with large concentrations of trace elements are still available for transport within the Big River.
\n","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155171","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Region 7","usgsCitation":"Barr, M.N., 2016, Surface-water quality and suspended-sediment quantity and quality within the Big River Basin, southeastern Missouri, 2011–13: U.S. Geological Survey Scientific Investigations Report 2015–5171, 39 p., https://dx.doi.org/10.3133/sir20155171.","productDescription":"vi, 39 p.","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2011-01-01","ipdsId":"IP-065903","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":314930,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5171/coverthb.jpg"},{"id":314931,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5171/sir20155171.pdf","text":"Report","size":"2.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5171"}],"country":"United States","state":"Missouri","otherGeospatial":"Big River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.80749511718749,\n 38.586820096127674\n ],\n [\n -90.6427001953125,\n 38.45789034424927\n ],\n [\n -90.582275390625,\n 38.371808917147554\n ],\n [\n -90.5767822265625,\n 38.285624966683756\n ],\n [\n -90.5877685546875,\n 38.16479533621134\n ],\n [\n -90.4779052734375,\n 38.06539235133249\n ],\n [\n -90.362548828125,\n 38.013476231041935\n ],\n [\n -90.23071289062499,\n 37.931200459333716\n ],\n [\n -90.1318359375,\n 37.84883250647402\n ],\n [\n -90.0384521484375,\n 37.814123701604466\n ],\n [\n -89.901123046875,\n 37.714244967649265\n ],\n [\n -90.0164794921875,\n 37.57505900514994\n ],\n [\n -90.208740234375,\n 37.58376576718623\n ],\n [\n -90.3900146484375,\n 37.58376576718623\n ],\n [\n -90.538330078125,\n 37.53150992479082\n ],\n [\n -90.703125,\n 37.413800350662875\n ],\n [\n -90.7635498046875,\n 37.28279464911045\n ],\n [\n -90.8404541015625,\n 37.17344871200958\n ],\n [\n -91.07666015625,\n 37.18657859524883\n ],\n [\n -91.23596191406249,\n 37.23470197166817\n ],\n [\n -91.23046875,\n 37.43997405227057\n ],\n [\n -91.109619140625,\n 37.58376576718623\n ],\n [\n -91.1920166015625,\n 37.688167468408025\n ],\n [\n -91.3238525390625,\n 37.76637243960176\n ],\n [\n -91.263427734375,\n 37.84015683604134\n ],\n [\n -91.131591796875,\n 37.883524980871336\n ],\n [\n -91.04919433593749,\n 38.03078569382294\n ],\n [\n -91.0711669921875,\n 38.12591462924157\n ],\n [\n -90.9173583984375,\n 38.16479533621134\n ],\n [\n -90.9228515625,\n 38.25974980039479\n ],\n [\n -90.9613037109375,\n 38.298559092254344\n ],\n [\n -90.999755859375,\n 38.38472766885085\n ],\n [\n -90.94482421875,\n 38.46219172306828\n ],\n [\n -90.8843994140625,\n 38.5008925889646\n ],\n [\n -90.80749511718749,\n 38.60828592850559\n ],\n [\n -90.80749511718749,\n 38.586820096127674\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"
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1400 Independence Road, MS-100
Rolla, MO 65401
Growth in unconventional oil and gas has spurred concerns on environmental impact and interest in beneficial uses of produced water (PW), especially in arid regions such as the Permian Basin, the largest U.S. tight-oil producer. To evaluate environmental impact, treatment, and reuse potential, there is a need to characterize the compositional variability of PW. Although hydraulic fracturing has caused a significant increase in shale-oil production, there are no high-resolution organic composition data for the shale-oil PW from the Permian Basin or other shale-oil plays (Eagle Ford, Bakken, etc.). PW was collected from shale-oil wells in the Midland sub-basin of the Permian Basin. Molecular characterization was conducted using high-resolution solid phase micro extraction gas chromatography time-of-flight mass spectrometry. Approximately 1400 compounds were identified, and 327 compounds had a >70% library match. PW contained alkane, cyclohexane, cyclopentane, BTEX (benzene, toluene, ethylbenzene, and xylene), alkyl benzenes, propyl-benzene, and naphthalene. PW also contained heteroatomic compounds containing nitrogen, oxygen, and sulfur. 3D van Krevelen and double bond equivalence versus carbon number analyses were used to evaluate molecular variability. Source composition, as well as solubility, controlled the distribution of volatile compounds found in shale-oil PW. The salinity also increased with depth, ranging from 105 to 162 g/L total dissolved solids. These data fill a gap for shale-oil PW composition, the associated petroleomics plots provide a fingerprinting framework, and the results for the Permian shale-oil PW suggest that partial treatment of suspended solids and organics would support some beneficial uses such as onsite reuse and bio-energy production.
","language":"English","publisher":"Pergamon Press","doi":"10.1016/j.chemosphere.2015.12.116","usgsCitation":"Khan, N.A., Engle, M.A., Dungan, B., Holguin, F.O., Xu, P., and Carroll, K., 2016, Volatile-organic molecular characterization of shale-oil produced water from the Permian Basin: Chemosphere, v. 148, p. 126-136, https://doi.org/10.1016/j.chemosphere.2015.12.116.","productDescription":"11 p.","startPage":"126","endPage":"136","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068901","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":330395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.16113281249999,\n 31.541089879585808\n ],\n [\n -101.2060546875,\n 31.541089879585808\n ],\n [\n -101.2060546875,\n 35.06597313798418\n ],\n [\n -105.16113281249999,\n 35.06597313798418\n ],\n [\n -105.16113281249999,\n 31.541089879585808\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"148","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5811c0f4e4b0f497e79a5a87","contributors":{"authors":[{"text":"Khan, Naima A.","contributorId":176304,"corporation":false,"usgs":false,"family":"Khan","given":"Naima","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":652122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engle, Mark A. 0000-0001-5258-7374 engle@usgs.gov","orcid":"https://orcid.org/0000-0001-5258-7374","contributorId":584,"corporation":false,"usgs":true,"family":"Engle","given":"Mark","email":"engle@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":652121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dungan, Barry","contributorId":176305,"corporation":false,"usgs":false,"family":"Dungan","given":"Barry","email":"","affiliations":[],"preferred":false,"id":652123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holguin, F. Omar","contributorId":176306,"corporation":false,"usgs":false,"family":"Holguin","given":"F.","email":"","middleInitial":"Omar","affiliations":[],"preferred":false,"id":652124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xu, Pei","contributorId":176302,"corporation":false,"usgs":false,"family":"Xu","given":"Pei","email":"","affiliations":[],"preferred":false,"id":652125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carroll, Kenneth C.","contributorId":176303,"corporation":false,"usgs":false,"family":"Carroll","given":"Kenneth C.","affiliations":[],"preferred":false,"id":652126,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70160739,"text":"sim3350 - 2016 - Fish assemblage composition and mapped mesohabitat features over a range of streamflows in the Middle Rio Grande, New Mexico, winter 2011-12, summer 2012","interactions":[],"lastModifiedDate":"2016-01-21T13:43:58","indexId":"sim3350","displayToPublicDate":"2016-01-21T13:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3350","title":"Fish assemblage composition and mapped mesohabitat features over a range of streamflows in the Middle Rio Grande, New Mexico, winter 2011-12, summer 2012","docAbstract":"This report documents differences in the mapped spatial extents and physical characteristics of in-channel fish habitat evaluated at the mesohabitat scale during winter 2011–12 (moderate streamflow) and summer 2012 (low streamflow) at 15 sites on the Middle Rio Grande in New Mexico starting about 3 kilometers downstream from Cochiti Dam and ending about 40 kilometers upstream from Elephant Butte Reservoir. The results of mesohabitat mapping, physical characterization, and fish assemblage surveys are summarized from the data that were collected. The report also presents general comparisons of physical mesohabitat data, such as wetted area and substrate type, and biological mesohabitat data, which included fish assemblage composition, species richness, Rio Grande silvery minnow relative abundance, and Rio Grande silvery minnow catch per unit effort.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3350","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Albuquerque District, and the U.S. Fish and Wildlife Service","usgsCitation":"Pearson, D.K., Braun, C.L., and Moring, J.B., 2015, Fish assemblage composition and mapped mesohabitat features over a range of streamflows in the Middle Rio Grande, New Mexico, winter 2011–12, summer 2012: U.S. Geological Survey Scientific Investigations Map 3350, 7 sheets, https://dx.doi.org/10.3133/sim3350.","productDescription":"7 Sheets","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-056794","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":314540,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3350/coverthb.jpg"},{"id":314541,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3350/pdf/sim3350.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3350"},{"id":314542,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3350/pdf/sim3350_sheet1.pdf","text":"Sheet 1","size":"2.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3350"},{"id":314543,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3350/pdf/sim3350_sheet2.pdf","text":"Sheet 2","size":"2.67 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3350"},{"id":314544,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3350/pdf/sim3350_sheet3.pdf","text":"Sheet 3","size":"2.68 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3350"},{"id":314545,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3350/pdf/sim3350_sheet4.pdf","text":"Sheet 4","size":"4.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3350"},{"id":314546,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3350/pdf/sim3350_sheet5.pdf","text":"Sheet 5","size":"3.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3350"},{"id":314547,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3350/pdf/sim3350_sheet6.pdf","text":"Sheet 6","size":"2.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3350"},{"id":314548,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3350/pdf/sim3350_sheet7.pdf","text":"Sheet 7","size":"1.87 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3350"}],"country":"United States","state":"New Mexico","otherGeospatial":"Middle Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.21533203125,\n 33.61461929233378\n ],\n [\n -108.21533203125,\n 36.96744946416931\n ],\n [\n -105.6884765625,\n 36.96744946416931\n ],\n [\n -105.6884765625,\n 33.61461929233378\n ],\n [\n -108.21533203125,\n 33.61461929233378\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
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Phytoplankton is an important and limiting food source in the Sacramento-San Joaquin Delta (the Delta) and San Francisco Bay; the decline of phytoplankton biomass is one possible factor in the pelagic organism decline and specifically in the decline of the protected delta smelt. The bivalves Corbicula fluminea andPotamocorbula amurensis have been shown to control phytoplankton biomass in several locations throughout the system, and their distribution and population dynamics are therefore of great interest. We were able to describe the distribution and dynamics of bivalve biomass through use of samples collected by the California Department of Water Resources (DWR) as part of a monitoring program from 1977 to 2013. As one element of DWR’s and the Bureau of Reclamation’s Environmental Monitoring Program (EMP), the DWR benthic monitoring program examines the impact of water project operations on the estuary as prescribed by a series of Water Rights Decisions mandated by the State Water Resources Control Board (SWRCB). The availability of multidecade samples allowed us to examine long-term trends in biomass, recruitment, and size of bivalves at the 15 stations sampled.
\nBiomass and grazing rate had the same basic trends, and the conclusions that we apply to biomass can be applied to grazing rate data. During winter of most years, Potamocorbula biomass was low at all locations and was near zero in the shallow San Pablo Bay station. The Potamocorbula biomass at shallow stations consistently peaked during summer and fall, but there was no consistent peak season in the deep stations. Corbicula had a much less consistent seasonal biomass pattern than Potamocorbula. However, some interannual patterns were consistent between stations. Corbicula biomass at three stations declined after 2003 (C9, D16, and D28). The Franks Tract (D19) Corbicula biomass had a baseline shift up (that is, all values were > 0) in 1985 until DWR ceased sampling at the station in 1995. Two other stations showed a similar increase in baseline but at different times; D24 shifted up after 2007 and D11 shifted up in 1991.
\nPotamocorbula recruitment (any bivalve ≤ 2.5 millimeters [mm] in length) occurred anytime between spring and fall, with bivalves at the most downstream stations in San Pablo Bay recruiting in spring and animals at the most upstream stations recruiting in fall. The bivalves at the stations between these endpoints recruited in (1) spring or (2) summer and fall (Carquinez Strait), or in some combination of two of those three seasons in Grizzly Bay. The few locations where Potamocorbula and Corbicula overlapped showed recruitment abundance opposing each other, with Potamocorbula recruits peaking during the more saline time of year and Corbicula recruits peaking during periods of lower salinities. Corbicula recruits were present throughout most of the year with some peaks in abundance, but the patterns were not seasonally consistent at any station.
\nMean size peaked in both bivalves in late summer and early fall and never got above a certain size; maximum size depended on location. The mean size of both bivalves has decreased over the years, with the size distributions throughout the Delta now skewed toward smaller, younger Corbicula (< 10 mm). The mean size of Potamocorbula has also become skewed toward the small, younger bivalves, with sizes in the range of 2–8 mm. The mean size ofPotamocorbula increased from spring to fall and decreased in winter. A similar generalization is not possible with Corbicula because seasonal patterns in size varied depending on station location. Station D24 on the Sacramento River was the only location with an increase in Corbicula mean size over the sampling period.
\nThe largest mean sized Potamocorbula were seen in the channel areas, where sizes of 15 mm were common at stations D41C, 8.1, and D6; sizes in excess of 15 mm were observed at all three D4 stations during the mid 1990s. The mean size of Potamocorbula in the shoals was ≈5–7 mm in most years in Grizzly Bay (D7) and San Pablo Bay (D41A), with an increase to > 10 mm at D7 in the wet years.
\nThe largest mean sized Corbicula were in the southern Delta (C9 ≈25 mm during 1996–97 and 2012–2013), and the smallest average sizes were in the San Joaquin River (P8 and D16). Corbicula at the upstream Sacramento River station (D24) and in the southern Delta (C9) showed similar interannual patterns in average size although the animals at C9 were consistently larger than those at D24 were. Corbicula in Franks Tract (D19) and the Old River (D28A) south of Franks Tract were also similar in size and in interannual patterns.
\nAt the few stations where Potamocorbula and Corbicula co-occur, it appears that they did not hinder each other’s growth. Both bivalves had large animals at D4, where Corbicula size increased coincident with the presence of Potamocorbula in 1987. Corbicula were observed in wet years prior to Potamocorbula’sinvasion at D7 (Grizzly Bay) and were capable of growing to significant size in wet years (> 20 mm in 1986).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161005","collaboration":"Prepared in cooperation with California Department of Water Resources","usgsCitation":"Crauder, J.S., Thompson, J.K., Parchaso, F., Anduaga, R.I., Pearson, S.A., Gehrts, K., Fuller, H., and Wells, E., 2016, Bivalve effects on the food web supporting delta smelt—A long-term study of bivalve recruitment, biomass, and grazing rate patterns with varying freshwater outflow: U.S. Geological Survey Open-File Report 2016–1005, 216 p., https://dx.doi.org/10.3133/ofr20161005.","productDescription":"xi, 216 p.","numberOfPages":"227","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070546","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":314274,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1005/ofr20161005.pdf","text":"Report","size":"3.7 MB","description":"OFR 2016-1005 PDF"},{"id":314275,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1005/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay, Sacramento-San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.51953124999999,\n 37.81737834565083\n ],\n [\n -122.51953124999999,\n 38.148597559924355\n ],\n [\n -121.30279541015624,\n 38.148597559924355\n ],\n [\n -121.30279541015624,\n 37.81737834565083\n ],\n [\n -122.51953124999999,\n 37.81737834565083\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"NRP staff, National Research Program
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Modeling streamflow is an important approach for understanding landscape-scale drivers of flow and estimating flows where there are no streamgage records. In this study conducted by the U.S. Geological Survey in cooperation with Colorado State University, the objectives were to model streamflow metrics on small, ungaged streams in the Upper Colorado River Basin and identify streams that are potentially threatened with becoming intermittent under drier climate conditions. The Upper Colorado River Basin is a region that is critical for water resources and also projected to experience large future climate shifts toward a drying climate. A random forest modeling approach was used to model the relationship between streamflow metrics and environmental variables. Flow metrics were then projected to ungaged reaches in the Upper Colorado River Basin using environmental variables for each stream, represented as raster cells, in the basin. Last, the projected random forest models of minimum flow coefficient of variation and specific mean daily flow were used to highlight streams that had greater than 61.84 percent minimum flow coefficient of variation and less than 0.096 specific mean daily flow and suggested that these streams will be most threatened to shift to intermittent flow regimes under drier climate conditions. Map projection products can help scientists, land managers, and policymakers understand current hydrology in the Upper Colorado River Basin and make informed decisions regarding water resources. With knowledge of which streams are likely to undergo significant drying in the future, managers and scientists can plan for stream-dependent ecosystems and human water users.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds974","collaboration":"Prepared in cooperation with Colorado State University","usgsCitation":"Reynolds, L.V., and Shafroth, P.B., 2016, Modeled streamflow metrics on small, ungaged stream reaches in the Upper Colorado River Basin: U.S. Geological Survey Data Series 974, 11 p., https://dx.doi.org/10.3133/ds974.","productDescription":"Report: vi, 11 p.; Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070136","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":438644,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H9938M","text":"USGS data release","linkHelpText":"Modeled Streamflow Metrics on Small, Ungaged Stream Reaches in the Upper Colorado River Basin"},{"id":314550,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F7H9938M","text":"Geospatial Data"},{"id":314505,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0974/ds974.pdf","text":"Report","size":"4.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 974"},{"id":314503,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0974/coverthb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.79638671875,\n 35.47856499535729\n ],\n [\n -113.18115234375,\n 35.55904339525896\n ],\n [\n -112.664794921875,\n 35.782170703266075\n ],\n [\n -112.203369140625,\n 35.79999392988527\n ],\n [\n -110.335693359375,\n 35.37113502280101\n ],\n [\n -106.171875,\n 34.7506398050501\n ],\n [\n -105.413818359375,\n 34.858890491257824\n ],\n [\n -104.578857421875,\n 35.22767235493586\n ],\n [\n -103.974609375,\n 36.12012758978146\n ],\n [\n -104.029541015625,\n 36.80048816579081\n ],\n [\n -104.2822265625,\n 37.74465712069939\n ],\n [\n -104.403076171875,\n 38.26406296833964\n ],\n [\n -104.38110351562499,\n 38.856820134743636\n ],\n [\n -104.27124023437499,\n 39.64799732373418\n ],\n [\n -104.04052734375,\n 40.212440718286466\n ],\n [\n -103.9306640625,\n 40.588928169693745\n ],\n [\n -104.051513671875,\n 40.79717741518769\n ],\n [\n -104.67773437499999,\n 41.623655390686395\n ],\n [\n -105.084228515625,\n 42.5611728553181\n ],\n [\n -106.12792968749999,\n 42.91620643817353\n ],\n [\n -107.303466796875,\n 43.620170616189924\n ],\n [\n -108.116455078125,\n 43.94537239244209\n ],\n [\n -108.61083984375,\n 44.276671273775186\n ],\n [\n -108.819580078125,\n 44.61393394730626\n ],\n [\n -109.16015624999999,\n 44.84029065139799\n ],\n [\n -109.53369140625,\n 44.92591837128866\n ],\n [\n -110.3466796875,\n 44.87144275016589\n ],\n [\n -110.819091796875,\n 43.96119063892024\n ],\n [\n -110.830078125,\n 41.828642001860544\n ],\n [\n -111.016845703125,\n 41.60722821271717\n ],\n [\n -111.3134765625,\n 41.46742831254425\n ],\n [\n -111.64306640625,\n 41.29431726315258\n ],\n [\n -112.03857421875,\n 40.65563874006118\n ],\n [\n -112.181396484375,\n 40.41349604970198\n ],\n [\n -113.04931640625,\n 37.95286091815649\n ],\n [\n -113.543701171875,\n 37.640334898059486\n ],\n [\n -113.851318359375,\n 37.23907530202184\n ],\n [\n -113.983154296875,\n 36.48314061639213\n ],\n [\n -113.961181640625,\n 35.79999392988527\n ],\n [\n -113.80737304687499,\n 35.43381992014202\n ],\n [\n -113.79638671875,\n 35.47856499535729\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Fort Collins Science Center
2150 Centre Avenue, Building C
Fort Collins, CO 80526-8118
https://www.fort.usgs.gov/
The objective of this study was to evaluate the effect of check dam infrastructure on soil and water conservation at the catchment scale using the Soil and Water Assessment Tool (SWAT). This paired watershed study includes a watershed treated with over 2000 check dams and a Control watershed which has none, in the West Turkey Creek watershed, Southeast Arizona, USA. SWAT was calibrated for streamflow using discharge documented during the summer of 2013 at the Control site. Model results depict the necessity to eliminate lateral flow from SWAT models of aridland environments, the urgency to standardize geospatial soils data, and the care for which modelers must document altering parameters when presenting findings. Performance was assessed using the percent bias (PBIAS), with values of ±2.34%. The calibrated model was then used to examine the impacts of check dams at the Treated watershed. Approximately 630 tons of sediment is estimated to be stored behind check dams in the Treated watershed over the 3-year simulation, increasing water quality for fish habitat. A minimum precipitation event of 15 mm was necessary to instigate the detachment of soil, sediments, or rock from the study area, which occurred 2% of the time. The resulting watershed model is useful as a predictive framework and decision-support tool to consider long-term impacts of restoration and potential for future restoration.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecohyd.2015.12.001","usgsCitation":"Norman, L.M., and Niraula, R., 2016, Model analysis of check dam impacts on long-term sediment and water budgets in southeast Arizona, USA: Ecohydrology & Hydrobiology, v. 16, no. 3, p. 125-137, https://doi.org/10.1016/j.ecohyd.2015.12.001.","productDescription":"13 p.","startPage":"125","endPage":"137","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066106","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471316,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecohyd.2015.12.001","text":"Publisher Index Page"},{"id":314538,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.9566650390625,\n 31.856564203952235\n ],\n [\n -109.9566650390625,\n 32.30802741894789\n ],\n [\n -109.22332763671875,\n 32.30802741894789\n ],\n [\n -109.22332763671875,\n 31.856564203952235\n ],\n [\n -109.9566650390625,\n 31.856564203952235\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56a0afaee4b0961cf280dbf4","contributors":{"authors":[{"text":"Norman, Laura M. 0000-0002-3696-8406 lnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":967,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","email":"lnorman@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":588956,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Niraula, Rewati","contributorId":100714,"corporation":false,"usgs":false,"family":"Niraula","given":"Rewati","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":588957,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70174296,"text":"70174296 - 2016 - Do intracoelomic telemetry transmitters alter the post-release behaviour of migratory fish?","interactions":[],"lastModifiedDate":"2017-03-14T08:35:47","indexId":"70174296","displayToPublicDate":"2016-01-20T13:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Do intracoelomic telemetry transmitters alter the post-release behaviour of migratory fish?","docAbstract":"Electronic tags have become a common tool in fish research, enhancing our understanding of how fish interact with their environment and move among different habitats, for estimating mortality and recording internal physiological states. An often-untested assumption of electronic tagging studies is that tagged fish are representative of untagged conspecifics and thus show ‘normal’ behaviour (e.g. movement rates, swimming activity, feeding). Here, we use a unique data set for potamadromous walleye (Sander vitreus) in Lake Huron and Lake Erie tributaries to assess whether the lack of appropriate controls in electronic tagging could seriously affect behavioural data. We used fish tagged in previous years and compared their migratory behaviour during the spawning season to fish tagged in a current year at the same location. The objective of the study was to determine whether intracoelomic acoustic tag implantation altered downstream movement of walleye after spawning. Fish tagged in a given season travelled slower downstream from two river spawning sites than fish tagged in previous years. Fish tagged one or two years earlier showed no differences between each other in downstream travel time, in contrast to fish tagged in a given year. Our results support notions that standard collection and intracoelomic tagging procedures can alter short-term behaviour (i.e. days, weeks, months), and as such, researchers should use caution when interpreting data collected over such time periods. Further, whenever possible, researchers should also explicitly evaluate post-tagging effects on behaviour as part of their experimental objectives.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1111/eff.12275","usgsCitation":"Wilson, A.D., Hayden, T.A., Vandergoot, C.S., Kraus, R.T., Dettmers, J.M., Cooke, S., and Krueger, C.C., 2016, Do intracoelomic telemetry transmitters alter the post-release behaviour of migratory fish?: Ecology of Freshwater Fish, v. 26, no. 2, p. 292-300, https://doi.org/10.1111/eff.12275.","productDescription":"9 p.","startPage":"292","endPage":"300","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066841","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":490014,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10026.1/11422","text":"External Repository"},{"id":324893,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Maumee Bay, Saginaw Bay","geographicExtents":"{\n \"type\": 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D.M.","contributorId":172746,"corporation":false,"usgs":false,"family":"Wilson","given":"Alexander","email":"","middleInitial":"D.M.","affiliations":[],"preferred":false,"id":641908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayden, Todd A. 0000-0002-0451-0425 thayden@usgs.gov","orcid":"https://orcid.org/0000-0002-0451-0425","contributorId":5987,"corporation":false,"usgs":true,"family":"Hayden","given":"Todd","email":"thayden@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":641909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vandergoot, Christopher S.","contributorId":71849,"corporation":false,"usgs":false,"family":"Vandergoot","given":"Christopher","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":641910,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kraus, Richard T. 0000-0003-4494-1841 rkraus@usgs.gov","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":2609,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","email":"rkraus@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":641715,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dettmers, John M.","contributorId":27395,"corporation":false,"usgs":true,"family":"Dettmers","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":641911,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":641912,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Krueger, Charles C.","contributorId":169487,"corporation":false,"usgs":false,"family":"Krueger","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":641913,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70162269,"text":"70162269 - 2016 - Ecological relevance of current water quality assessment unit designations in impaired rivers","interactions":[],"lastModifiedDate":"2016-01-20T12:11:42","indexId":"70162269","displayToPublicDate":"2016-01-20T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Ecological relevance of current water quality assessment unit designations in impaired rivers","docAbstract":"Managers often nest sections of water bodies together into assessment units (AUs) to monitor and assess water quality criteria. Ideally, AUs represent an extent of waters with similar ecological, watershed, habitat and land-use conditions and no overlapping characteristics with other waters. In the United States, AUs are typically based on political or hydrologic boundaries rather than on ecologically relevant features, so it can be difficult to detect changes in impairment status. Our goals were to evaluate if current AU designation criteria of an impaired water body in southeastern Idaho, USA that, like many U.S. waters, has three-quarters of its mainstem length divided into two AUs. We focused our evaluation in southeastern Idaho's Portneuf River, an impaired river and three-quarters of the river is divided into two AUs. We described biological and environmental conditions at multiple reaches within each AU. We used these data to (1) test if variability at the reach-scale is greater within or among AUs and, (2) to evaluate alternate AU boundaries based on multivariate analyses of reach-scale data. We found that some biological conditions had greater variability within an AU than between AUs. Multivariate analyses identified alternative, 2- and 3-group, AUs that reduced this variability. Our results suggest that the current AU designations in the mainstem Portneuf River contain ecologically distinct sections of river and that the existing AU boundaries should be reconsidered in light of the ecological conditions measured at the reach scale. Variation in biological integrity within designated AUs may complicate water quality and biological assessments, influence management decisions or affect where monitoring or mitigation resources are directed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2015.06.043","usgsCitation":"Layhee, M.J., Sepulveda, A.J., Ray, A., Mladenka, G., and Van Every, L., 2016, Ecological relevance of current water quality assessment unit designations in impaired rivers: Science of the Total Environment, v. 536, p. 198-205, https://doi.org/10.1016/j.scitotenv.2015.06.043.","productDescription":"8 p.","startPage":"198","endPage":"205","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064737","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":314522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Portneuf River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.61810302734375,\n 42.60465241823049\n ],\n [\n -112.61810302734375,\n 42.98355351219673\n ],\n [\n -111.92047119140624,\n 42.98355351219673\n ],\n [\n -111.92047119140624,\n 42.60465241823049\n ],\n [\n -112.61810302734375,\n 42.60465241823049\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"536","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56a0aface4b0961cf280dbf0","contributors":{"authors":[{"text":"Layhee, Megan J. 0000-0003-1359-1455 mlayhee@usgs.gov","orcid":"https://orcid.org/0000-0003-1359-1455","contributorId":3955,"corporation":false,"usgs":true,"family":"Layhee","given":"Megan","email":"mlayhee@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":589048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sepulveda, Adam J. 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":150628,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":589049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ray, Andrew","contributorId":101972,"corporation":false,"usgs":true,"family":"Ray","given":"Andrew","affiliations":[],"preferred":false,"id":589050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mladenka, Greg","contributorId":116680,"corporation":false,"usgs":true,"family":"Mladenka","given":"Greg","affiliations":[],"preferred":false,"id":589051,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Every, Lynn","contributorId":127352,"corporation":false,"usgs":false,"family":"Van Every","given":"Lynn","affiliations":[{"id":6912,"text":"Idaho Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":589052,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70162285,"text":"70162285 - 2016 - Sediment supply versus local hydraulic controls on sediment transport and storage in a river with large sediment loads","interactions":[],"lastModifiedDate":"2016-02-15T16:14:53","indexId":"70162285","displayToPublicDate":"2016-01-20T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Sediment supply versus local hydraulic controls on sediment transport and storage in a river with large sediment loads","docAbstract":"The Rio Grande in the Big Bend region of Texas, USA, and Chihuahua and Coahuila, Mexico, undergoes rapid geomorphic changes as a result of its large sediment supply and variable hydrology; thus, it is a useful natural laboratory to investigate the relative importance of flow strength and sediment supply in controlling alluvial channel change. We analyzed a suite of sediment transport and geomorphic data to determine the cumulative influence of different flood types on changing channel form. In this study, physically based analyses suggest that channel change in the Rio Grande is controlled by both changes in flow strength and sediment supply over different spatial and temporal scales. Channel narrowing is primarily caused by substantial deposition of sediment supplied to the Rio Grande during tributary-sourced flash floods. Tributary floods have large suspended-sediment concentrations, occur for short durations, and attenuate rapidly downstream in the Rio Grande, depositing much of their sediment in downstream reaches. Long-duration floods on the mainstem have the capacity to enlarge the Rio Grande, and these floods, released from upstream dams, can either erode or deposit sediment in the Rio Grande depending upon the antecedent in-channel sediment supply and the magnitude and duration of the flood. Geomorphic and sediment transport analyses show that the locations and rates of sand erosion and deposition during long-duration floods are most strongly controlled by spatial changes in flow strength, largely through changes in channel slope. However, spatial differences in the in-channel sediment supply regulate sediment evacuation or accumulation over time in long reaches (greater than a kilometer).
","language":"English","publisher":"Journal of Geophysical Research","doi":"10.1002/2015JF003436","usgsCitation":"Dean, D.J., Topping, D.J., Schmidt, J.C., Griffiths, R.E., and Sabol, T.A., 2016, Sediment supply versus local hydraulic controls on sediment transport and storage in a river with large sediment loads: Journal of Geophysical Research F: Earth Surface, v. 121, no. 1, p. 82-110, https://doi.org/10.1002/2015JF003436.","productDescription":"29 p.","startPage":"82","endPage":"110","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062345","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471318,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jf003436","text":"Publisher Index Page"},{"id":314520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Big Bend National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.5623779296875,\n 28.8831596093235\n ],\n [\n -104.5623779296875,\n 29.726222319395504\n ],\n [\n -102.6947021484375,\n 29.726222319395504\n ],\n [\n -102.6947021484375,\n 28.8831596093235\n ],\n [\n -104.5623779296875,\n 28.8831596093235\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-19","publicationStatus":"PW","scienceBaseUri":"56a0afafe4b0961cf280dbfa","contributors":{"authors":[{"text":"Dean, David J. 0000-0003-0203-088X djdean@usgs.gov","orcid":"https://orcid.org/0000-0003-0203-088X","contributorId":131047,"corporation":false,"usgs":true,"family":"Dean","given":"David","email":"djdean@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":589103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Topping, David J. 0000-0002-2104-4577 dtopping@usgs.gov","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":140985,"corporation":false,"usgs":true,"family":"Topping","given":"David","email":"dtopping@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":589104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmidt, John C. 0000-0002-2988-3869 jcschmidt@usgs.gov","orcid":"https://orcid.org/0000-0002-2988-3869","contributorId":1983,"corporation":false,"usgs":true,"family":"Schmidt","given":"John","email":"jcschmidt@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":589105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Griffiths, Ronald E. 0000-0003-3620-2926 rgriffiths@usgs.gov","orcid":"https://orcid.org/0000-0003-3620-2926","contributorId":162,"corporation":false,"usgs":true,"family":"Griffiths","given":"Ronald","email":"rgriffiths@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":589106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sabol, Thomas A. 0000-0002-4299-2285 tsabol@usgs.gov","orcid":"https://orcid.org/0000-0002-4299-2285","contributorId":3403,"corporation":false,"usgs":true,"family":"Sabol","given":"Thomas","email":"tsabol@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":589107,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70160037,"text":"ofr20151233 - 2016 - Salamander chytrid fungus (Batrachochytrium salamandrivorans) in the United States—Developing research, monitoring, and management strategies","interactions":[],"lastModifiedDate":"2024-03-04T19:03:16.639043","indexId":"ofr20151233","displayToPublicDate":"2016-01-20T09:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1233","title":"Salamander chytrid fungus (Batrachochytrium salamandrivorans) in the United States—Developing research, monitoring, and management strategies","docAbstract":"The recently (2013) identified pathogenic chytrid fungus, Batrachochytrium salamandrivorans (Bsal), poses a severe threat to the distribution and abundance of salamanders within the United States and Europe. Development of a response strategy for the potential, and likely, invasion of Bsal into the United States is crucial to protect global salamander biodiversity. A formal working group, led by Amphibian Research and Monitoring Initiative (ARMI) scientists from the U.S. Geological Survey (USGS) Patuxent Wildlife Research Center, Fort Collins Science Center, and Forest and Rangeland Ecosystem Science Center, was held at the USGS Powell Center for Analysis and Synthesis in Fort Collins, Colorado, United States from June 23 to June 25, 2015, to identify crucial Bsal research and monitoring needs that could inform conservation and management strategies for salamanders in the United States. Key findings of the workshop included the following: (1) the introduction of Bsal into the United States is highly probable, if not inevitable, thus requiring development of immediate short-term and long-term intervention strategies to prevent Bsal establishment and biodiversity decline; (2) management actions targeted towards pathogen containment may be ineffective in reducing the long-term spread of Bsal throughout the United States; and (3) early detection of Bsal through surveillance at key amphibian import locations, among high-risk wild populations, and through analysis of archived samples is necessary for developing management responses. Top research priorities during the preinvasion stage included the following: (1) deployment of qualified diagnostic methods for Bsal and establishment of standardized laboratory practices, (2) assessment of susceptibility for amphibian hosts (including anurans), and (3) development and evaluation of short- and long-term pathogen intervention and management strategies. Several outcomes were achieved during the workshop, including development of an organizational structure with working groups for a Bsal Task Force, creation of an initial influence diagram to aid in identifying effective management actions in the face of uncertainty, and production of a list of potential management actions and key research uncertainties. Additional products under development include a Bsal Strategic Action plan, an emergency response plan, a monitoring and surveillance program, a standardized diagnostic approach, decision models for natural resource agencies, and a reporting database for salamander mortalities. This workshop was the first international meeting to address the threat of Bsal to salamander populations in the United States, with more than 30 participants from U.S. conservation and resource management agencies (U.S. Fish and Wildlife Service, U.S. Forest Service, U.S. Department of Defense, U.S. National Park Service, and Association of Fish and Wildlife Agencies) and academic research institutions in Australia, the Netherlands, Switzerland, the United Kingdom, and the United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151233","usgsCitation":"Grant, E.H.C., Muths, E., Katz, R.A., Canessa, Stefano, Adam, M.J., Ballard, J.R., Berger, Lee, Briggs, C.J., Coleman, Jeremy, Gray, M.J., Harris, M.C., Harris, R.N., Hossack, Blake, Huyvaert, K.P., Kolby, J.E., Lips, K.R., Lovich, R.E., McCallum, H.I., Mendelson, J.R., III, Nanjappa, Priya, Olson, D.H., Powers, J.G., Richgels, K.L.D., Russell, R.E., Schmidt, B.R., Spitzen-van der Sluijs, Annemarieke, Watry, M.K., Woodhams, D.C., and White, C.L., 2016, Salamander chytrid fungus (Batrachochytrium salamandrivorans) in the United States—Developing research, monitoring, and management strategies: U.S. Geological Survey Open-File Report 2015–1233, 16 p., https://dx.doi.org/10.3133/ofr20151233.","productDescription":"v, 16 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069828","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":313292,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1233/coverthb.jpg"},{"id":313293,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1233/ofr20151233.pdf","text":"Report","size":"902 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1233"}],"contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708
And
SO Conte Anadromous Fish Research Laboratory
1 Migratory Way
Turners Falls, MA 01376
Lake Trout Salvelinus namaycush have been introduced widely throughout the western USA to enhance recreational fisheries, but high predatory demand can create challenges for management of yield and trophy fisheries alike. Lake Trout were introduced to Priest Lake, Idaho, during the 1920s, but few fishery-independent data are available to guide current or future management actions. We collected fishery-independent data to describe population dynamics and evaluate potential management scenarios using an age-structured population model. Lake Trout in Priest Lake were characterized by fast growth at young ages, which resulted in young age at maturity. However, adult growth rates and body condition were lower than for other Lake Trout populations. High rates of skipped spawning (>50%) were also observed. Model projections indicated that the population was growing (λ = 1.03). Eradication could be achieved by increasing annual mortality to 0.32, approximately twice the current rate. A protected slot length limit could increase population length-structure, but few fish grew fast enough to exit the slot. In contrast, a juvenile removal scenario targeting age-2 to age-5 Lake Trout maintained short-term harvest of trophy-length individuals while reducing overall population abundance.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/02755947.2015.1111279","usgsCitation":"Ng, E.L., Fredericks, J.P., and Quist, M.C., 2016, Population dynamics and evaluation of alternative management strategies for nonnative Lake Trout in Priest Lake, Idaho: North American Journal of Fisheries Management, v. 36, no. 1, p. 40-54, https://doi.org/10.1080/02755947.2015.1111279.","productDescription":"15 p.","startPage":"40","endPage":"54","ipdsId":"IP-065484","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":336864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Priest Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n 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P.","contributorId":166902,"corporation":false,"usgs":false,"family":"Fredericks","given":"Jim","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":680782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":680681,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70169055,"text":"70169055 - 2016 - Resprouting and seeding hypotheses: A test of the gap-dependent model using resprouting and obligate seeding subspecies of Arctostaphylos","interactions":[],"lastModifiedDate":"2016-12-16T11:06:19","indexId":"70169055","displayToPublicDate":"2016-01-18T15:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3086,"text":"Plant Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Resprouting and seeding hypotheses: A test of the gap-dependent model using resprouting and obligate seeding subspecies of Arctostaphylos","docAbstract":"Ecological factors favoring either postfire resprouting or postfire obligate seeding in plants have received considerable attention recently. Three ecological models have been proposed to explain patterns of these two life history types. In this study, we test these three models using data from California chaparral. We take an innovative approach to testing these models by not testing community or landscape patterns, but instead, investigating vegetation structure characteristic of four pairs of resprouting and (non-resprouting) obligate seeding subspecies of Arctostaphylos (Ericaceae), a dominant and diverse shrub genus in California chaparral. Data were analyzed for percentage bare ground, elevation, annual precipitation, number of fires, and time between fires and were compared independently for each subspecies pair. Results were consistently supportive of the gap-dependent model suggesting that obligate seeders are favored when post-disturbance gaps are large. Results were inconclusive or contrary to expectations for both of the other two models.
\n","language":"English","publisher":"Springer","doi":"10.1007/s11258-015-0551-z","usgsCitation":"Keeley, J.E., Parker, V.T., and Vasey, M.C., 2016, Resprouting and seeding hypotheses: A test of the gap-dependent model using resprouting and obligate seeding subspecies of Arctostaphylos: Plant Ecology, v. 217, no. 6, p. 743-750, https://doi.org/10.1007/s11258-015-0551-z.","productDescription":"8 p.","startPage":"743","endPage":"750","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068142","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":318854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"217","issue":"6","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-18","publicationStatus":"PW","scienceBaseUri":"56e7e0c2e4b0f59b85d6aad0","contributors":{"authors":[{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":622700,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parker, V. Thomas","contributorId":167557,"corporation":false,"usgs":false,"family":"Parker","given":"V.","email":"","middleInitial":"Thomas","affiliations":[{"id":24748,"text":"San Francisco State University, San Francisco, CA","active":true,"usgs":false}],"preferred":false,"id":622701,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vasey, Michael C.","contributorId":167558,"corporation":false,"usgs":false,"family":"Vasey","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":24748,"text":"San Francisco State University, San Francisco, CA","active":true,"usgs":false}],"preferred":false,"id":622702,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168445,"text":"70168445 - 2016 - Tomographic image of a seismically active volcano: Mammoth Mountain, California","interactions":[],"lastModifiedDate":"2016-02-17T08:46:58","indexId":"70168445","displayToPublicDate":"2016-01-16T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Tomographic image of a seismically active volcano: Mammoth Mountain, California","docAbstract":"
High-resolution tomographic P wave, S wave, and VP/VS velocity structure models are derived for Mammoth Mountain, California, using phase data from the Northern California Seismic Network and a temporary deployment of broadband seismometers. An anomalous volume (5.1 × 109 to 5.9 × 1010m3) of low P and low S wave velocities is imaged beneath Mammoth Mountain, extending from near the surface to a depth of ∼2 km below sea level. We infer that the reduction in seismic wave velocities is due to the presence of CO2 distributed in oblate spheroid pores with mean aspect ratio α = 1.6 × 10−3 to 7.9 × 10−3 (crack-like pores) and mean gas volume fraction ϕ = 8.1 × 10−4 to 3.4 × 10−3. The pore density parameter κ = 3ϕ/(4πα) = na3=0.11, where n is the number of pores per cubic meter and a is the mean pore equatorial radius. The total mass of CO2 is estimated to be 4.6 × 109 to 1.9 × 1011 kg. The local geological structure indicates that the CO2 contained in the pores is delivered to the surface through fractures controlled by faults and remnant foliation of the bedrock beneath Mammoth Mountain. The total volume of CO2 contained in the reservoir suggests that given an emission rate of 500 tons day−1, the reservoir could supply the emission of CO2 for ∼25–1040 years before depletion. Continued supply of CO2 from an underlying magmatic system would significantly prolong the existence of the reservoir.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB012537","usgsCitation":"Dawson, P.B., Chouet, B.A., and Pitt, A., 2016, Tomographic image of a seismically active volcano: Mammoth Mountain, California: Journal of Geophysical Research B: Solid Earth, v. 121, no. 1, p. 114-133, https://doi.org/10.1002/2015JB012537.","productDescription":"20 p.","startPage":"114","endPage":"133","numberOfPages":"20","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069204","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":471325,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012537","text":"Publisher Index Page"},{"id":318020,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mammoth Mountain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.06021118164062,\n 37.68083151896963\n ],\n [\n -119.03205871582031,\n 37.68137494751297\n ],\n [\n -118.99291992187499,\n 37.678386041261184\n ],\n [\n -118.9651107788086,\n 37.67213612088675\n ],\n [\n -118.94588470458984,\n 37.65528588731532\n ],\n [\n -118.9434814453125,\n 37.639519302998295\n ],\n [\n -118.96751403808594,\n 37.62021427322739\n ],\n [\n -118.98983001708984,\n 37.60498423376982\n ],\n [\n -119.03480529785156,\n 37.604440246103636\n ],\n [\n -119.06570434570312,\n 37.60716014465307\n ],\n [\n -119.0869903564453,\n 37.61831068887273\n ],\n [\n -119.08939361572266,\n 37.63734433906192\n ],\n [\n -119.08493041992186,\n 37.655557695625056\n ],\n [\n -119.08802032470703,\n 37.6756687492631\n ],\n [\n -119.0701675415039,\n 37.68246179265685\n ],\n [\n -119.06021118164062,\n 37.68083151896963\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-16","publicationStatus":"PW","scienceBaseUri":"56c304e0e4b0946c6520881d","contributors":{"authors":[{"text":"Dawson, Phillip B. dawson@usgs.gov","contributorId":2751,"corporation":false,"usgs":true,"family":"Dawson","given":"Phillip","email":"dawson@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":620200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chouet, Bernard A. 0000-0001-5527-0532 chouet@usgs.gov","orcid":"https://orcid.org/0000-0001-5527-0532","contributorId":3304,"corporation":false,"usgs":true,"family":"Chouet","given":"Bernard","email":"chouet@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":620201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pitt, Andrew M. pitt@usgs.gov","contributorId":3893,"corporation":false,"usgs":true,"family":"Pitt","given":"Andrew M.","email":"pitt@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":620202,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159603,"text":"ofr20151215 - 2016 - Hydrologic conditions in the South Coast aquifer, Puerto Rico, 2010–15","interactions":[],"lastModifiedDate":"2016-01-15T13:39:04","indexId":"ofr20151215","displayToPublicDate":"2016-01-15T13:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1215","title":"Hydrologic conditions in the South Coast aquifer, Puerto Rico, 2010–15","docAbstract":"In 1958, the U.S. Geological Survey began documenting hydrologic conditions, including groundwater levels, groundwater withdrawals for agricultural irrigation and public water supply, and water quality, in the South Coast aquifer, Puerto Rico. This information has improved the understanding of the water resources of the region. The hydrologic data indicate that (1) groundwater levels declined as much as 40 feet in the Salinas area and 11 feet in the Guayama area during 2012–14; (2) groundwater withdrawals for agricultural irrigation increased from 6.0 to 10.5 million gallons per day, or 75 percent, from 2010 to 2012; and (3) total groundwater withdrawals decreased from 29.3 to 23.8 million gallons per day from 2010 to 2014. The quantity and quality of water in the aquifer is primarily affected by variations in aquifer recharge as a result of changing rainfall or modes of irrigation; however, the spatial patterns and magnitude of water withdrawals for all uses have a secondary impact on the quantity and quality of water in the aquifer.
\nNational Oceanic and Atmospheric Administration data from climatological stations indicate that the 30-year normal precipitation for the period 1991–2010 in the South Coastal and Southern Slopes climatological regions was about 37.74 and 61.61 inches, respectively; the 30-year moving average precipitation for the period 1985–2014 was 37.94 and 61.80 inches, respectively, for these regions. The mean annual precipitation during 2012–14 was 13 percent below the 30-year moving average for the South Coastal climatological region and 7.7 percent below for the Southern Slopes climatological region. When rainfall is below the 30-year moving average, recharge is diminished and groundwater levels decline. Annual precipitation in the South Coast aquifer, which includes a large part of the South Coastal and Southern Slopes climatological regions, was 39.42, 37.25, and 34.89 inches per year for 2012, 2013, and 2014, respectively.
\nWater level declines reduce the thickness of freshwater in the unconfined parts of the South Coast aquifer. Additionally, the pumping-induced migration of poor-quality water from deep or seaward areas of the aquifer can contribute to reductions in the thickness of freshwater in the aquifer. The reduction in the freshwater saturated thickness of the aquifer in areas near Ponce, Juana Díaz, Salinas, and Guayama is of particular concern because the total saturated thickness of the aquifer is thinner in these areas. Total dissolved solids concentration in groundwater samples indicates a small positive trend in Ponce, Santa Isabel, Salinas, and Guayama. Diminished aquifer recharge during 2012 to 2015 and, to a lesser extent, increased groundwater withdrawals have resulted in a reduction in the freshwater saturated thickness of the aquifer. The reduction in freshwater saturated thickness of the aquifer may affect freshwater resources available for agriculture and public water supply. A prolonged time period with reduced aquifer recharge may have substantial implications for groundwater levels and fresh groundwater availability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151215","collaboration":"Prepared in cooperation with the Puerto Rico Department of Natural and Environmental Resources","usgsCitation":"Torres-González, Sigfredo, and Rodríguez, J.M., 2016, Hydrologic conditions in the South Coast aquifer, Puerto Rico, 2010–15: U.S. Geological Survey Open-File Report 2015–1215, 32 p., https://dx.doi.org/10.3133/ofr20151215.","productDescription":"v, 32 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065638","costCenters":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"links":[{"id":314149,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1215/coverthb.jpg"},{"id":314150,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1215/ofr20151215.pdf","text":"Report","size":"1.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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U.S. Geological Survey
651 Federal Drive Suite 400-15
Guaynabo, PR 00965
http://pr.water.usgs.gov/