A major focus of the U.S. Geological Survey’s Trout Lake Water, Energy, and Biogeochemical Budgets (WEBB) project is the development of a watershed model to allow predictions of hydrologic response to future conditions including land-use and climate change. The coupled groundwater/surface-water model GSFLOW was chosen for this purpose because it could easily incorporate an existing groundwater flow model and it provides for simulation of surface-water processes. The Trout Lake watershed in northern Wisconsin is underlain by a highly conductive outwash sand aquifer. In this area, streamflow is dominated by groundwater contributions; however, surface runoff occurs during intense rainfall periods and spring snowmelt. Surface runoff also occurs locally near stream/lake areas where the unsaturated zone is thin. A diverse data set, collected from 1992 to 2007 for the Trout Lake WEBB project and the co-located and NSF-funded North Temperate Lakes LTER project, includes snowpack, solar radiation, potential evapotranspiration, lake levels, groundwater levels, and streamflow. The timeseries processing software TSPROC (Doherty 2003) was used to distill the large time series data set to a smaller set of observations and summary statistics that captured the salient hydrologic information. The timeseries processing reduced hundreds of thousands of observations to less than 5,000. Model calibration included specific predictions for several lakes in the study area using the PEST parameter estimation suite of software (Doherty 2007). The calibrated model was used to simulate the hydrologic response in the study lakes to a variety of climate change scenarios culled from the IPCC Fourth Assessment Report of the Intergovernmental Panel on Climate Change (Solomon et al. 2007). Results from the simulations indicate climate change could result in substantial changes to the lake levels and components of the hydrologic budget of a seepage lake in the flow system. For a drainage lake lower in the flow system, the impacts of climate change are diminished.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Planning for an uncertain future - Monitoring, integration, and adaptation (SIR2009-5049)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"conferenceTitle":"Third interagency conference on research in the watersheds","conferenceDate":"September 8-11, 2008","conferenceLocation":"Estes Park, CO","language":"English","publisher":"U.S Geological Survey","publisherLocation":"Reston, VA","usgsCitation":"Walker, J.F., Hunt, R.J., Markstrom, S., Hay, L.E., and Doherty, J., 2009, Using a coupled groundwater/surfacewater model to predict climate-change impacts to lakes in the Trout Lake watershed, Northern Wisconsin, in Planning for an uncertain future - Monitoring, integration, and adaptation (SIR2009-5049), Estes Park, CO, September 8-11, 2008, p. 155-161.","productDescription":"6 p.","startPage":"155","endPage":"161","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":328067,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328066,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2009/5049/pdf/Walker.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c6b1b6e4b0f2f0cebe73c4","contributors":{"authors":[{"text":"Walker, John F. jfwalker@usgs.gov","contributorId":1081,"corporation":false,"usgs":true,"family":"Walker","given":"John","email":"jfwalker@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":1986,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven L.","email":"markstro@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":647524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":647525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doherty, John","contributorId":43843,"corporation":false,"usgs":true,"family":"Doherty","given":"John","affiliations":[],"preferred":false,"id":647526,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70035008,"text":"70035008 - 2009 - Iron solubility driven by speciation in dust sources to the ocean","interactions":[],"lastModifiedDate":"2018-05-02T21:25:59","indexId":"70035008","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Iron solubility driven by speciation in dust sources to the ocean","docAbstract":"Although abundant in the Earths crust, iron is present at trace concentrations in sea water and is a limiting nutrient for phytoplankton in approximately 40% of the ocean. Current literature suggests that aerosols are the primary external source of iron to offshore waters, yet controls on iron aerosol solubility remain unclear. Here we demonstrate that iron speciation (oxidation state and bonding environment) drives iron solubility in arid region soils, glacial weathering products (flour) and oil combustion products (oil fly ash). Iron speciation varies by aerosol source, with soils in arid regions dominated by ferric (oxy)hydroxides, glacial flour by primary and secondary ferrous silicates and oil fly ash by ferric sulphate salts. Variation in iron speciation produces systematic differences in iron solubility: less than 1% of the iron in arid soils was soluble, compared with 2-3% in glacial products and 77-81% in oil combustion products, which is directly linked to fractions of more soluble phases. We conclude that spatial and temporal variations in aerosol iron speciation, driven by the distribution of deserts, glaciers and fossil-fuel combustion, could have a pronounced effect on aerosol iron solubility and therefore on biological productivity and the carbon cycle in the ocean. ?? 2009 Macmillan Publishers Limited.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Nature Geoscience","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1038/ngeo501","issn":"17520894","usgsCitation":"Schroth, A., Crusius, J., Sholkovitz, E., and Bostick, B., 2009, Iron solubility driven by speciation in dust sources to the ocean: Nature Geoscience, v. 2, no. 5, p. 337-340, https://doi.org/10.1038/ngeo501.","startPage":"337","endPage":"340","numberOfPages":"4","costCenters":[],"links":[{"id":243054,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215264,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1038/ngeo501"}],"volume":"2","issue":"5","noUsgsAuthors":false,"publicationDate":"2009-04-26","publicationStatus":"PW","scienceBaseUri":"505a3ef3e4b0c8380cd64183","contributors":{"authors":[{"text":"Schroth, A.W.","contributorId":79707,"corporation":false,"usgs":true,"family":"Schroth","given":"A.W.","email":"","affiliations":[],"preferred":false,"id":448860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crusius, John 0000-0003-2554-0831 jcrusius@usgs.gov","orcid":"https://orcid.org/0000-0003-2554-0831","contributorId":2155,"corporation":false,"usgs":true,"family":"Crusius","given":"John","email":"jcrusius@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":448857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sholkovitz, E.R.","contributorId":61664,"corporation":false,"usgs":true,"family":"Sholkovitz","given":"E.R.","email":"","affiliations":[],"preferred":false,"id":448858,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bostick, B.C.","contributorId":62813,"corporation":false,"usgs":true,"family":"Bostick","given":"B.C.","email":"","affiliations":[],"preferred":false,"id":448859,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70035821,"text":"70035821 - 2009 - Sources of land-derived runoff to a coral reef-fringed embayment identified using geochemical tracers in nearshore sediment traps","interactions":[],"lastModifiedDate":"2017-11-05T09:13:21","indexId":"70035821","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Sources of land-derived runoff to a coral reef-fringed embayment identified using geochemical tracers in nearshore sediment traps","docAbstract":"Geochemical tracers, including Ba, Co, Th, 7Be, 137Cs and 210Pb, and magnetic properties were used to characterize terrestrial runoff collected in nearshore time-series sediment traps in Hanalei Bay, Kauai, during flood and dry conditions in summer 2006, and to fingerprint possible runoff sources in the lower watershed. In combination, the tracers indicate that runoff during a flood in August could have come from cultivated taro fields bordering the lower reach of the river. Land-based runoff associated with summer floods may have a greater impact on coral reef communities in Hanalei Bay than in winter because sediment persists for several months. During dry periods, sediment carried by the Hanalei River appears to have been mobilized primarily by undercutting of low 7Be, low 137Cs riverbanks composed of soil weathered from tholeiitic basalt with low Ba and Co concentrations. Following a moderate rainfall event in September, high 7Be sediment carried by the Hanalei River was probably mobilized by overland flow in the upper watershed. Ba-desorption in low-salinity coastal water limited its use to a qualitative runoff tracer in nearshore sediment. 210Pb had limited usefulness as a terrestrial tracer in the nearshore due to a large dissolved oceanic source and scavenging onto resuspended bottom sediment. 210Pb-scavenging does, however, illustrate the role resuspension could play in the accumulation of particle-reactive contaminants in nearshore sediment. Co and 137Cs were not affected by desorption or geochemical scavenging and showed the greatest potential as quantitative sediment provenance indicators in material collected in nearshore sediment traps.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2009.09.014","issn":"02727714","usgsCitation":"Takesue, R.K., Bothner, M., and Reynolds, R.L., 2009, Sources of land-derived runoff to a coral reef-fringed embayment identified using geochemical tracers in nearshore sediment traps: Estuarine, Coastal and Shelf Science, v. 85, no. 3, p. 459-471, https://doi.org/10.1016/j.ecss.2009.09.014.","startPage":"459","endPage":"471","numberOfPages":"13","costCenters":[],"links":[{"id":476247,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/3091","text":"External Repository"},{"id":243956,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"85","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b937ee4b08c986b31a4fe","contributors":{"authors":[{"text":"Takesue, Renee K. 0000-0003-1205-0825 rtakesue@usgs.gov","orcid":"https://orcid.org/0000-0003-1205-0825","contributorId":2159,"corporation":false,"usgs":true,"family":"Takesue","given":"Renee","email":"rtakesue@usgs.gov","middleInitial":"K.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":452575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bothner, Michael H. mbothner@usgs.gov","contributorId":139855,"corporation":false,"usgs":true,"family":"Bothner","given":"Michael H.","email":"mbothner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":452576,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reynolds, Richard L. 0000-0002-4572-2942 rreynolds@usgs.gov","orcid":"https://orcid.org/0000-0002-4572-2942","contributorId":441,"corporation":false,"usgs":true,"family":"Reynolds","given":"Richard","email":"rreynolds@usgs.gov","middleInitial":"L.","affiliations":[{"id":271,"text":"Federal Center","active":false,"usgs":true}],"preferred":true,"id":452577,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70035820,"text":"70035820 - 2009 - A one-dimensional heat-transport model for conduit flow in karst aquifers","interactions":[],"lastModifiedDate":"2012-03-12T17:21:49","indexId":"70035820","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A one-dimensional heat-transport model for conduit flow in karst aquifers","docAbstract":"A one-dimensional heat-transport model for conduit flow in karst aquifers is presented as an alternative to two or three-dimensional distributed-parameter models, which are data intensive and require knowledge of conduit locations. This model can be applied for cases where water temperature in a well or spring receives all or part of its water from a phreatic conduit. Heat transport in the conduit is simulated by using a physically-based heat-transport equation that accounts for inflow of diffuse flow from smaller openings and fissures in the surrounding aquifer during periods of low recharge. Additional diffuse flow that is within the zone of influence of the well or spring but has not interacted with the conduit is accounted for with a binary mixing equation to proportion these different water sources. The estimation of this proportion through inverse modeling is useful for the assessment of contaminant vulnerability and well-head or spring protection. The model was applied to 7 months of continuous temperature data for a sinking stream that recharges a conduit and a pumped well open to the Madison aquifer in western South Dakota. The simulated conduit-flow fraction to the well ranged from 2% to 31% of total flow, and simulated conduit velocity ranged from 44 to 353 m/d.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.jhydrol.2009.09.024","issn":"00221694","usgsCitation":"Long, A., and Gilcrease, P., 2009, A one-dimensional heat-transport model for conduit flow in karst aquifers: Journal of Hydrology, v. 378, no. 3-4, p. 230-239, https://doi.org/10.1016/j.jhydrol.2009.09.024.","startPage":"230","endPage":"239","numberOfPages":"10","costCenters":[],"links":[{"id":243955,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":216109,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jhydrol.2009.09.024"}],"volume":"378","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e4cae4b0c8380cd4692b","contributors":{"authors":[{"text":"Long, Andrew J.","contributorId":80023,"corporation":false,"usgs":false,"family":"Long","given":"Andrew J.","affiliations":[],"preferred":false,"id":452574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilcrease, P.C.","contributorId":58116,"corporation":false,"usgs":true,"family":"Gilcrease","given":"P.C.","email":"","affiliations":[],"preferred":false,"id":452573,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70034692,"text":"70034692 - 2009 - Water quality characterization in some birimian aquifers of the Birim Basin, Ghana","interactions":[],"lastModifiedDate":"2012-03-12T17:21:41","indexId":"70034692","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2578,"text":"KSCE Journal of Civil Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Water quality characterization in some birimian aquifers of the Birim Basin, Ghana","docAbstract":"The objective of this study was to determine the main controls on the hydrochemistry of groundwater in the study area. Mass balance modeling was used simultaneously with multivariate R-mode hierarchical cluster analysis to determine the significant sources of variation in the hydrochemistry. Two water types have been revealed in this area: (1) waters influenced more significantly by the weathering of silicate minerals from the underlying geology, and are rich in silica, sodium, calcium, bicarbonate, and magnesium ions, and (2) waters that have been influenced by the effects of fertilizers and other anthropogenic activities in the area. Mineral speciation and silicate mineral stability diagrams generated from the data suggest that montmorillonite, probably derived from the incongruent dissolution of feldspars and micas, is the most stable silicate phase in the groundwater. The apparent incongruent weathering of silicate minerals in the groundwater system has led to the enrichment of sodium, calcium, magnesium and bicarbonate ions as well as silica, leading to the supersaturation of calcite, aragonite, dolomite and quartz. Stability in the montmorillonite field suggests restricted flow conditions whereby groundwater residence time is relatively high, leading to greater contact of groundwater with the rock to enhance weathering. Cation exchange processes have also been determined to play minor roles in the hydrochemistry.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"KSCE Journal of Civil Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1007/s12205-009-0179-4","issn":"12267988","usgsCitation":"Bruce, B., Yidana, S., Anku, Y., Akabzaa, T., and Asiedu, D., 2009, Water quality characterization in some birimian aquifers of the Birim Basin, Ghana: KSCE Journal of Civil Engineering, v. 13, no. 3, p. 179-187, https://doi.org/10.1007/s12205-009-0179-4.","startPage":"179","endPage":"187","numberOfPages":"9","costCenters":[],"links":[{"id":476443,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12205-009-0179-4","text":"Publisher Index Page"},{"id":215631,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s12205-009-0179-4"},{"id":243448,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bc88fe4b08c986b32c9c0","contributors":{"authors":[{"text":"Bruce, B.-Y.","contributorId":101477,"corporation":false,"usgs":true,"family":"Bruce","given":"B.-Y.","email":"","affiliations":[],"preferred":false,"id":447063,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yidana, S.M.","contributorId":59554,"corporation":false,"usgs":true,"family":"Yidana","given":"S.M.","email":"","affiliations":[],"preferred":false,"id":447060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anku, Y.","contributorId":96083,"corporation":false,"usgs":true,"family":"Anku","given":"Y.","affiliations":[],"preferred":false,"id":447062,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Akabzaa, T.","contributorId":39580,"corporation":false,"usgs":true,"family":"Akabzaa","given":"T.","email":"","affiliations":[],"preferred":false,"id":447059,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Asiedu, D.","contributorId":76131,"corporation":false,"usgs":true,"family":"Asiedu","given":"D.","affiliations":[],"preferred":false,"id":447061,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70035686,"text":"70035686 - 2009 - A carbon, nitrogen, and sulfur elemental and isotopic study in dated sediment cores from the Louisiana Shelf","interactions":[],"lastModifiedDate":"2018-10-12T09:55:36","indexId":"70035686","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1742,"text":"Geo-Marine Letters","active":true,"publicationSubtype":{"id":10}},"title":"A carbon, nitrogen, and sulfur elemental and isotopic study in dated sediment cores from the Louisiana Shelf","docAbstract":"Three sediment cores were collected off the Mississippi River delta on the Louisiana Shelf at sites that are variably influenced by recurring, summer-time water-column hypoxia and fluvial loadings. The cores, with established chronology, were analyzed for their respective carbon, nitrogen, and sulfur elemental and isotopic composition to examine variable organic matter inputs, and to assess the sediment record for possible evidence of hypoxic events. Sediment from site MRJ03-3, which is located close to the Mississippi Canyon and generally not influenced by summer-time hypoxia, is typical of marine sediment in that it contains mostly marine algae and fine-grained material from the erosion of terrestrial C4 plants. Sediment from site MRJ03-2, located closer to the mouth of the Mississippi River and at the periphery of the hypoxic zone (annual recurrence of summer-time hypoxia >50%), is similar in composition to core MRJ03-3, but exhibits more isotopic and elemental variability down-core, suggesting that this site is more directly influenced by river discharge. Site MRJ03-5 is located in an area of recurring hypoxia (annual recurrence >75%), and is isotopically and elementally distinct from the other two cores. The carbon and nitrogen isotopic composition of this core prior to 1960 is similar to average particulate organic matter from the lower Mississippi River, and approaches the composition of C3 plants. This site likely receives a greater input of local terrestrial organic matter to the sediment. After 1960 and to the present, a gradual shift to higher values of δ13C and δ15N and lower C:N ratios suggests that algal input to these shelf sediments increased as a result of increased productivity and hypoxia. The values of C:S and δ34S reflect site-specific processes that may be influenced by the higher likelihood of recurring seasonal hypoxia. In particular, the temporal variations in the C:S and δ34S down-core are likely caused by changes in the rate of sulfate reduction, and hence the degree of hypoxia in the overlying water column. Based principally on the down-core C:N and C:S ratios and δ13C and δ34S profiles, sites MRJ03-3 and MRJ03-2 generally reflect more marine organic matter inputs, while site MRJ03-5 appears to be more influenced by terrestrial deposition.
Nitrate (NO3−) concentrations and dual isotopic composition (δ15N and δ18O) were measured during various seasons and tidal conditions in Elkhorn Slough to evaluate mixing of sources of NO3− within this California estuary. We found the isotopic composition of NO3− was influenced most heavily by mixing of two primary sources with unique isotopic signatures, a marine (Monterey Bay) and terrestrial agricultural runoff source (Old Salinas River). However, our attempt to use a simple two end‐member mixing model to calculate the relative contribution of these two NO3− sources to the Slough was complicated by periods of nonconservative behavior and/or the presence of additional sources, particularly during the dry season when NO3− concentrations were low. Although multiple linear regression generally yielded good fits to the observed data, deviations from conservative mixing were still evident. After consideration of potential alternative sources, we concluded that deviations from two end‐member mixing were most likely derived from interactions with marsh sediments in regions of the Slough where high rates of NO3− uptake and nitrification result in NO3− with low δ15N and high δ18O values. A simple steady state dual isotope model is used to illustrate the impact of cycling processes in an estuarine setting which may play a primary role in controlling NO3− isotopic composition when and where cycling rates and water residence times are high. This work expands our understanding of nitrogen and oxygen isotopes as biogeochemical tools for investigating NO3− sources and cycling in estuaries, emphasizing the role that cycling processes may play in altering isotopic composition.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2008JG000729","issn":"01480227","usgsCitation":"Wankel, S.D., Kendall, C., and Paytan, A., 2009, Using nitrate dual isotopic composition (δ15N and δ18O) as a tool for exploring sources and cycling of nitrate in an estuarine system: Elkhorn Slough, California: Journal of Geophysical Research G: Biogeosciences, v. 114, no. 1, https://doi.org/10.1029/2008JG000729.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":242926,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215148,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2008JG000729"}],"country":"United States","state":"California","otherGeospatial":"Elkhorn Slough","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.83151245117186,\n 36.79279036766672\n ],\n [\n -121.83151245117186,\n 36.88071909009633\n ],\n [\n -121.67907714843751,\n 36.88071909009633\n ],\n [\n -121.67907714843751,\n 36.79279036766672\n ],\n [\n -121.83151245117186,\n 36.79279036766672\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"114","issue":"1","noUsgsAuthors":false,"publicationDate":"2009-02-17","publicationStatus":"PW","scienceBaseUri":"505bc07fe4b08c986b32a168","contributors":{"authors":[{"text":"Wankel, Scott D.","contributorId":98076,"corporation":false,"usgs":true,"family":"Wankel","given":"Scott","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":449435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, Carol 0000-0002-0247-3405 ckendall@usgs.gov","orcid":"https://orcid.org/0000-0002-0247-3405","contributorId":1462,"corporation":false,"usgs":true,"family":"Kendall","given":"Carol","email":"ckendall@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":449434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paytan, Adina","contributorId":75242,"corporation":false,"usgs":true,"family":"Paytan","given":"Adina","affiliations":[],"preferred":false,"id":449436,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70034764,"text":"70034764 - 2009 - Reducing streamflow forecast uncertainty: Application and qualitative assessment of the upper klamath river Basin, Oregon","interactions":[],"lastModifiedDate":"2012-03-12T17:21:42","indexId":"70034764","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Reducing streamflow forecast uncertainty: Application and qualitative assessment of the upper klamath river Basin, Oregon","docAbstract":"The accuracy of streamflow forecasts depends on the uncertainty associated with future weather and the accuracy of the hydrologic model that is used to produce the forecasts. We present a method for streamflow forecasting where hydrologic model parameters are selected based on the climate state. Parameter sets for a hydrologic model are conditioned on an atmospheric pressure index defined using mean November through February (NDJF) 700-hectoPascal geopotential heights over northwestern North America [Pressure Index from Geopotential heights (PIG)]. The hydrologic model is applied in the Sprague River basin (SRB), a snowmelt-dominated basin located in the Upper Klamath basin in Oregon. In the SRB, the majority of streamflow occurs during March through May (MAM). Water years (WYs) 1980-2004 were divided into three groups based on their respective PIG values (high, medium, and low PIG). Low (high) PIG years tend to have higher (lower) than average MAM streamflow. Four parameter sets were calibrated for the SRB, each using a different set of WYs. The initial set used WYs 1995-2004 and the remaining three used WYs defined as high-, medium-, and low-PIG years. Two sets of March, April, and May streamflow volume forecasts were made using Ensemble Streamflow Prediction (ESP). The first set of ESP simulations used the initial parameter set. Because the PIG is defined using NDJF pressure heights, forecasts starting in March can be made using the PIG parameter set that corresponds with the year being forecasted. The second set of ESP simulations used the parameter set associated with the given PIG year. Comparison of the ESP sets indicates that more accuracy and less variability in volume forecasts may be possible when the ESP is conditioned using the PIG. This is especially true during the high-PIG years (low-flow years). ?? 2009 American Water Resources Association.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of the American Water Resources Association","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1111/j.1752-1688.2009.00307.x","issn":"1093474X","usgsCitation":"Hay, L., McCabe, G., Clark, M., and Risley, J.C., 2009, Reducing streamflow forecast uncertainty: Application and qualitative assessment of the upper klamath river Basin, Oregon: Journal of the American Water Resources Association, v. 45, no. 3, p. 580-596, https://doi.org/10.1111/j.1752-1688.2009.00307.x.","startPage":"580","endPage":"596","numberOfPages":"17","costCenters":[],"links":[{"id":215728,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1752-1688.2009.00307.x"},{"id":243550,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"3","noUsgsAuthors":false,"publicationDate":"2009-05-26","publicationStatus":"PW","scienceBaseUri":"50e4a3d1e4b0e8fec6cdb9b1","contributors":{"authors":[{"text":"Hay, L.E.","contributorId":54253,"corporation":false,"usgs":true,"family":"Hay","given":"L.E.","email":"","affiliations":[],"preferred":false,"id":447478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCabe, G.J. 0000-0002-9258-2997","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":12961,"corporation":false,"usgs":true,"family":"McCabe","given":"G.J.","affiliations":[],"preferred":false,"id":447476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, M.P.","contributorId":49558,"corporation":false,"usgs":true,"family":"Clark","given":"M.P.","affiliations":[],"preferred":false,"id":447477,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Risley, J. C.","contributorId":88780,"corporation":false,"usgs":true,"family":"Risley","given":"J.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":447479,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157359,"text":"70157359 - 2009 - Re-greening the Sahel: Farmer-led innovation in Burkina Faso and Niger","interactions":[],"lastModifiedDate":"2022-11-03T14:40:31.348958","indexId":"70157359","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Re-greening the Sahel: Farmer-led innovation in Burkina Faso and Niger","docAbstract":"The Sahel—the belt of land that stretches across Africa on the southern edge of the Sahara—has always been a tough place to farm. Rainfall is low and droughts are frequent. The crust of hard soil is, at times, almost impermeable, and harsh winds threaten to sweep away everything in their path. Over the past three decades, however, hundreds of thousands of farmers in Burkina Faso and Niger have transformed large swaths of the region’s arid landscape into productive agricultural land, improving food security for about 3 million people. Once-denuded landscapes are now home to abundant trees, crops, and livestock. Although rainfall has improved slightly from the mid-1990s relative to earlier decades, indications are that farmer management is a stronger determinant of land and agroforestry regeneration. Sahelian farmers achieved their success by ingeniously modifying traditional agroforestry, water, and soil-management practices. To improve water availability and soil fertility in Burkina Faso’s Central Plateau, farmers have sown crops in planting pits and built stone contour bunds, which are stones piled up in long narrow rows that follow the contours of the land in order to capture rainwater runoff and soil. These practices have helped rehabilitate between 200,000 and 300,000 hectares of land and produce an additional 80,000 tons of food per year. In southern Niger, farmers have developed innovative ways of regenerating and multiplying valuable trees whose roots already lay underneath their land, thus improving about 5 million hectares of land and producing more than 500,000 additional tons of food per year. While the specific calculations of farm-level benefits are subject to various methodological and data limitations, the order of magnitude of these benefits is high, as evidenced by the wide-scale adoption of the improved practices by large numbers of farmers. Today, the agricultural landscapes of southern Niger have considerably more tree cover than they did 30 years ago. These findings suggest a human and environmental success story at a scale not seen anywhere else in Africa. The re-greening of the Sahel began when local farmers’ practices were rediscovered and enhanced in simple, low-cost ways by innovative farmers and nongovernmental organizations. An evolving coalition of local, national, and international actors then enabled large-scale diffusion and continued use of these improved practices where they benefited farmers.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Millions fed: Proven successes in agricultural development","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"International Food Policy Research Institute","publisherLocation":"Washington, D.C.","usgsCitation":"Reij, C., Smale, M., and Tappan, G., 2009, Re-greening the Sahel: Farmer-led innovation in Burkina Faso and Niger, chap. of Millions fed: Proven successes in agricultural development, p. 53-58.","productDescription":"6 p.","startPage":"53","endPage":"58","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-017230","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":308341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Burkina Faso, Niger","otherGeospatial":"Sahel","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -4.639791446626816,\n 12.003196515232489\n ],\n [\n 2.402656235991685,\n 11.7873987296272\n ],\n [\n 2.4878954695618347,\n 12.163030586576127\n ],\n [\n 2.7609316008536666,\n 12.121141166984259\n ],\n [\n 2.845008619447526,\n 12.383962289942616\n ],\n [\n 3.5763987666831554,\n 11.69155466834269\n ],\n [\n 3.714147835620139,\n 12.482938211904909\n ],\n [\n 4.1647593507208,\n 12.967344231346672\n ],\n [\n 4.175677373790762,\n 13.308580074875522\n ],\n [\n 4.629116726525382,\n 13.681065649878107\n ],\n [\n 5.314258453018596,\n 13.669112717964893\n ],\n [\n 5.567270804933969,\n 13.893528450914417\n ],\n [\n 6.168551165202388,\n 13.65265082511118\n ],\n [\n 6.915645497012662,\n 12.908840641547556\n ],\n [\n 7.889463795826657,\n 13.267808090632585\n ],\n [\n 8.792670952213342,\n 12.780123161694846\n ],\n [\n 9.734457317706273,\n 12.750370333386343\n ],\n [\n 10.102414294734302,\n 13.08782457401577\n ],\n [\n 10.596797495544507,\n 13.266636886639915\n ],\n [\n 11.536217458619944,\n 13.31374326632114\n ],\n [\n 12.465671759189348,\n 12.965746287153678\n ],\n [\n 12.950769549,\n 13.408823496361592\n ],\n [\n 13.270561901786152,\n 13.386918579231832\n ],\n [\n 13.393622120360305,\n 13.647895652525648\n ],\n [\n 13.715280259953119,\n 13.62500855534239\n ],\n [\n 13.605282907334924,\n 14.399956023795696\n ],\n [\n 13.891786712025123,\n 14.609361153695417\n ],\n [\n 13.939083136157478,\n 14.94921484306684\n ],\n [\n 15.297791865759535,\n 16.52430535128599\n ],\n [\n 6.939416785895133,\n 20.292251009561312\n ],\n [\n 5.762243443446266,\n 19.4565137296034\n ],\n [\n 4.169868466076622,\n 19.087875076002106\n ],\n [\n 4.179408336751777,\n 17.10170017637651\n ],\n [\n 3.9495292909859643,\n 16.915273256883893\n ],\n [\n 3.9520152707567604,\n 16.36014449301412\n ],\n [\n 3.801164706436424,\n 15.76444920385778\n ],\n [\n 3.4574400012033095,\n 15.536929955205366\n ],\n [\n 1.3827137635291535,\n 15.343716797971751\n ],\n [\n 0.29845942874391085,\n 15.001971951162389\n ],\n [\n -0.12455141872584363,\n 15.164356783029021\n ],\n [\n -0.7400138646767118,\n 15.21715815077998\n ],\n [\n -1.202548752046681,\n 14.927159225215291\n ],\n [\n -1.9312730768392612,\n 14.601409217280306\n ],\n [\n -2.1235156145981193,\n 14.189835435092704\n ],\n [\n -2.3901073702563735,\n 14.41889208957214\n ],\n [\n -2.924608039688138,\n 14.084032314910203\n ],\n [\n -3.0011893361447335,\n 13.70632539188\n ],\n [\n -3.3438681823960223,\n 13.821245580762337\n ],\n [\n -3.344010438122865,\n 13.442091144329737\n ],\n [\n -3.9530504056266977,\n 13.555879200871885\n ],\n [\n -4.44772870647617,\n 13.21119891267574\n ],\n [\n -4.4094451280899705,\n 12.906160557010423\n ],\n [\n -4.63770181904934,\n 12.712907352832005\n ],\n [\n -4.5233722206737355,\n 12.406730888400205\n ],\n [\n -4.639791446626816,\n 12.003196515232489\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56012a95e4b03bc34f544424","contributors":{"editors":[{"text":"Spielman, David J.","contributorId":147837,"corporation":false,"usgs":false,"family":"Spielman","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":572852,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Pandya-Lorch, Rajul","contributorId":147838,"corporation":false,"usgs":false,"family":"Pandya-Lorch","given":"Rajul","email":"","affiliations":[],"preferred":false,"id":572853,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Reij, Chris","contributorId":147839,"corporation":false,"usgs":false,"family":"Reij","given":"Chris","email":"","affiliations":[],"preferred":false,"id":572854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smale, Melinda","contributorId":147840,"corporation":false,"usgs":false,"family":"Smale","given":"Melinda","email":"","affiliations":[],"preferred":false,"id":572855,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tappan, G. Gray 0000-0002-2240-6963","orcid":"https://orcid.org/0000-0002-2240-6963","contributorId":147662,"corporation":false,"usgs":true,"family":"Tappan","given":"G. Gray","affiliations":[],"preferred":false,"id":572856,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174154,"text":"70174154 - 2009 - Movement and habitat use of sika and white-tailed deer on Assateague Island National Seashore, Maryland","interactions":[],"lastModifiedDate":"2021-04-01T21:48:14.400798","indexId":"70174154","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":91,"text":"Technical Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/NER/NRTR—2009/140","title":"Movement and habitat use of sika and white-tailed deer on Assateague Island National Seashore, Maryland","docAbstract":"This research project was conducted to describe habitat use of sika deer (Cervus nippon) and white-tailed deer (Odocoileus virginianus) and possibly attribute the effects of ungulate herbivory to specific deer species, if spatial separation in habitat use could be identified. Sturm (2007) conducted an exclosure study to document the effect of feral horse (Equus caballus) herbivory, deer herbivory, and horse and deer herbivory combined on plant communities. Sturm (2007) found that ungulate herbivory reduced plant species richness, evenness, and diversity in the maritime forest and affected species composition in all habitats studied. Sturm (2007) also found that herbivory on some species could be directly attributable to either horse or deer. However, the effects of sika and white-tailed deer herbivory could not be separated via an exclosure study design because of the difficulty of passively excluding one deer species but not the other.
We captured white-tailed deer and sika deer in January–March of 2006 and 2007 throughout the Maryland portion of Assateague Island. Deer were fitted with radio-collars and their survival and locations monitored via ground telemetry. Up to four locations were acquired per deer each week during early (May–June) and late (August–September) growth periods for vegetation on the island. Also, we estimated deer locations during a dormant vegetation period (November– December 2006). We used these data to estimate survival and harvest rates, document movements, and model habitat use.
We captured and fitted 50 deer with radio-collars over the course of the study. Of these 50 deer, 36 were sika and 14 were white-tailed deer. Of the 36 sika deer, 10 were harvested, three were likely killed by hunters but not recovered, and one died of natural causes while giving birth. Of the 14 white-tailed deer, three were harvested, one was illegally killed, and two were censored because of study-related mortality.
Annual survival was 0.48 (95% CI = 0.16–0.82) for male white-tailed deer, 0.74 (95% CI = 0.44–0.91) for female white-tailed deer, 0.56 (95% CI = 0.35–0.75) for male sika deer, and 0.86 (95% CI = 0.70–0.94) for female sika deer. The harvest rate was 0.12 (95% CI = 0.04–0.27) for female sika deer, 0.44 (95% CI = 0.25–0.65) for male sika deer, 0.18 (95% CI = 0.05–0.51) for female white-tailed deer, and 0.38 (95% CI = 0.10–0.78) for male white-tailed deer. Annual survival rates for both species were similar to what has been observed in other populations. Unfortunately, small sample sizes for male white-tailed deer limited inferences about harvest and survival rates, but harvest rates of females for both species were similar to other published studies. Hunting was the primary cause of mortality, and outside the hunting season survival was 0.98–1.00 for all species and sexes.
We found that the home range area of sika deer was much greater than the home range area of white-tailed deer, but failed to detect any difference between sexes or among seasons. Sika deer also made long-distance movements and left the Maryland portion of Assateague Island. No sika deer left Assateague island during our study, but we did document the dispersal of a male whitetailed deer to the mainland. In their native range, sika deer have been able to readily expand populations and occupy vacant habitat (Kaji et al. 2000; Kaji et al. 2004). The long distance movements we observed on Assateague Island, especially relative to white-tailed deer, may reflect the ability of this species to exploit food resources that may be limited in quality or quantity, or both. However, we did not collect data to assess use of food resources by sika deer and whether this may have influenced long distance movements.
We found both species of deer were less likely to use a habitat the further it was located from cover, which was defined as tall shrub or forest vegetation. For every 10 m (32 ft) from cover each species of deer was 1.23–1.38 times less likely to use any given habitat.
Patterns in use of vegetation classes were similar across species and seasons. Relative to forest habitat, both species avoided dune herbaceous, disturbed lands, sand, and water categories. Both species neither avoided nor preferred developed herbaceous, low shrub, marsh herbaceous, and tall shrub categories compared to the forest category. However, there were consistent differences between the two species. During spring, white-tailed deer were more likely than sika deer to use forested, tall shrub, disturbed herbaceous, and sand areas, but were less likely to use all other habitats. During summer, habitat use was similar between the two species except that white-tailed deer tended to use forested habitat more. During winter, white-tailed deer were less likely to use dune herbaceous, low shrub, and forested habitats than sika deer.
Sturm (2007) identified differential browsing on plant species between horses and deer, but his experimental design did not permit detection of differential browsing between sika and whitetailed deer. Our study of habitat use did not provide information to identify plant species that may be differentially consumed by sika and white-tailed deer based on differences in habitat use. We envision two approaches to addressing the effects of deer browsing. One approach would be further research that identifies the food habits of both deer species at the plant species level. This would be similar to food habits research conducted by Keiper (1985) and others or could involve direct observation of food consumption by both species. However, both fecal analysis and direct observation would be time-consuming and not guaranteed to identify differences.
If the goal of ungulate population management is to protect the island ecosystem, another approach involving manipulation of deer abundance and monitoring the response of plant species known to be preferentially consumed by deer would be a more direct method of assessing effects of deer herbivory (Sturm 2007). Moreover, such an approach is not predicated on detecting differences between deer species. Direct manipulation of deer abundance could be incorporated into an adaptive management program (Williams et al. 2007) and may provide greater benefits to the management of ASIS in the long term. Harvest management decisions for white-tailed deer and sika deer are made on an ongoing basis and by coupling these decisions with a vegetative monitoring program it may be possible to reduce or minimize adverse effects of ungulate herbivory. Furthermore, management of feral horses could be incorporated into the decision process.
","language":"English","publisher":"U.S. Department of the Interior","usgsCitation":"Diefenbach, D.R., and Christensen, S., 2009, Movement and habitat use of sika and white-tailed deer on Assateague Island National Seashore, Maryland: Technical Report NPS/NER/NRTR—2009/140, xi, 110 p.","productDescription":"xi, 110 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-015092","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":325402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":384829,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://usgs-cru-individual-data.s3.amazonaws.com/drd11/tech_publications/ASIS_Deer_Rpt_NPS_NER_NRTR_2009_140reduced-1.pdf"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Assateague Island National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.22407531738281,\n 38.03078569382294\n ],\n [\n -75.17051696777344,\n 38.1399572748485\n ],\n [\n -75.11352539062499,\n 38.278078995562105\n ],\n [\n -75.091552734375,\n 38.32549778247211\n ],\n [\n -75.09979248046875,\n 38.32711378564577\n ],\n [\n -75.14923095703125,\n 38.236022799686694\n ],\n [\n -75.179443359375,\n 38.18152925835456\n ],\n [\n -75.21583557128906,\n 38.09998264736481\n ],\n [\n -75.23025512695311,\n 38.08701320402273\n ],\n [\n -75.25154113769531,\n 38.069176461951876\n ],\n [\n -75.25703430175781,\n 38.038357297980816\n ],\n [\n -75.31539916992188,\n 37.970725990064786\n ],\n [\n -75.32089233398438,\n 37.9447389942697\n ],\n [\n -75.32638549804688,\n 37.93282521519654\n ],\n [\n -75.34492492675781,\n 37.92090950501414\n ],\n [\n -75.38063049316406,\n 37.91332577499166\n ],\n [\n -75.38406372070312,\n 37.89219554724437\n ],\n [\n -75.40260314941406,\n 37.866722853218626\n ],\n [\n -75.38749694824219,\n 37.84232584933158\n ],\n [\n -75.322265625,\n 37.908991863924946\n ],\n [\n -75.2460479736328,\n 38.01564013749379\n ],\n [\n -75.22407531738281,\n 38.03078569382294\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"Technical Report: NPS/NER/NRTR—2009/140","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"578dfdb4e4b0f1bea0e0f8a9","contributors":{"authors":[{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":641001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christensen, Sonja","contributorId":171608,"corporation":false,"usgs":false,"family":"Christensen","given":"Sonja","email":"","affiliations":[{"id":16900,"text":"Massachusetts Division of Fisheries and Wildlife","active":true,"usgs":false}],"preferred":false,"id":642797,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156324,"text":"70156324 - 2009 - Ice and water on Newberry Volcano, central Oregon","interactions":[],"lastModifiedDate":"2021-11-05T15:58:28.619743","indexId":"70156324","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesNumber":"15","subseriesTitle":"Field Guide","title":"Ice and water on Newberry Volcano, central Oregon","docAbstract":"Newberry Volcano in central Oregon is dry over much of its vast area, except for the lakes in the caldera and the single creek that drains them. Despite the lack of obvious glacial striations and well-formed glacial moraines, evidence indicates that Newberry was glaciated. Meter-sized foreign blocks, commonly with smoothed shapes, are found on cinder cones as far as 7 km from the caldera rim. These cones also show evidence of shaping by flowing ice. In addition, multiple dry channels likely cut by glacial meltwater are common features of the eastern and western flanks of the volcano. On the older eastern flank of the volcano, a complex depositional and erosional history is recorded by lava flows, some of which flowed down channels, and interbedded sediments of probable glacial origin. Postglacial lava flows have subsequently filled some of the channels cut into the sediments. The evidence suggests that Newberry Volcano has been subjected to multiple glaciations.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Volcanoes to vineyards: Geologic field trips through the dynamic landscape of the Pacific Northwest","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, Colorado","isbn":"9780813700151 0813700159","usgsCitation":"Donnelly-Nolan, J.M., and Jensen, R.A., 2009, Ice and water on Newberry Volcano, central Oregon, chap. of Volcanoes to vineyards: Geologic field trips through the dynamic landscape of the Pacific Northwest, v. 15, p. 81-90.","productDescription":"10 p.","startPage":"81","endPage":"90","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-014260","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":306965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Newberry Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.35635375976562,\n 43.64601335623949\n ],\n [\n -121.35635375976562,\n 43.79588033566535\n ],\n [\n -121.08444213867186,\n 43.79588033566535\n ],\n [\n -121.08444213867186,\n 43.64601335623949\n ],\n [\n -121.35635375976562,\n 43.64601335623949\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d5a8b1e4b0518e3546a4c2","contributors":{"editors":[{"text":"O’Connor, Jim oconnor@usgs.gov","contributorId":2350,"corporation":false,"usgs":true,"family":"O’Connor","given":"Jim","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":568680,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Madin, Ian P.","contributorId":66404,"corporation":false,"usgs":true,"family":"Madin","given":"Ian","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":568681,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Dorsey, Rebecca","contributorId":140302,"corporation":false,"usgs":false,"family":"Dorsey","given":"Rebecca","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":568682,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Donnelly-Nolan, Julie M. 0000-0001-8714-9606 jdnolan@usgs.gov","orcid":"https://orcid.org/0000-0001-8714-9606","contributorId":3271,"corporation":false,"usgs":true,"family":"Donnelly-Nolan","given":"Julie","email":"jdnolan@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":568678,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jensen, Robert A.","contributorId":35469,"corporation":false,"usgs":false,"family":"Jensen","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":568679,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70037494,"text":"70037494 - 2009 - Transient dwarfism of soil fauna during the Paleocene-Eocene Thermal Maximum","interactions":[],"lastModifiedDate":"2012-03-12T17:22:09","indexId":"70037494","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3165,"text":"Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"title":"Transient dwarfism of soil fauna during the Paleocene-Eocene Thermal Maximum","docAbstract":"Soil organisms, as recorded by trace fossils in paleosols of the Willwood Formation, Wyoming, show significant body-size reductions and increased abundances during the Paleocene-Eocene Thermal Maximum (PETM). Paleobotanical, paleopedologic, and oxygen isotope studies indicate high temperatures during the PETM and sharp declines in precipitation compared with late Paleocene estimates. Insect and oligochaete burrows increase in abundance during the PETM, suggesting longer periods of soil development and improved drainage conditions. Crayfish burrows and molluscan body fossils, abundant below and above the PETM interval, are significantly less abundant during the PETM, likely because of drier floodplain conditions and lower water tables. Burrow diameters of the most abundant ichnofossils are 30-46% smaller within the PETM interval. As burrow size is a proxy for body size, significant reductions in burrow diameter suggest that their tracemakers were smaller bodied. Smaller body sizes may have resulted from higher subsurface temperatures, lower soil moisture conditions, or nutritionally deficient vegetation in the high-CO2 atmosphere inferred for the PETM. Smaller soil fauna co-occur with dwarf mammal taxa during the PETM; thus, a common forcing mechanism may have selected for small size in both above- and below-ground terrestrial communities. We predict that soil fauna have already shown reductions in size over the last 150 years of increased atmospheric CO2 and surface temperatures or that they will exhibit this pattern over the next century. We retrodict also that soil fauna across the Permian-Triassic and Triassic-Jurassic boundary events show significant size decreases because of similar forcing mechanisms driven by rapid global warming.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Proceedings of the National Academy of Sciences of the United States of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1073/pnas.0909674106","issn":"00278424","usgsCitation":"Smith, J., Hasiotis, S., Kraus, M.J., and Woody, D., 2009, Transient dwarfism of soil fauna during the Paleocene-Eocene Thermal Maximum: Proceedings of the National Academy of Sciences of the United States of America, v. 106, no. 42, p. 17655-17660, https://doi.org/10.1073/pnas.0909674106.","startPage":"17655","endPage":"17660","numberOfPages":"6","costCenters":[],"links":[{"id":476413,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2757401","text":"External Repository"},{"id":217095,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1073/pnas.0909674106"},{"id":245011,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","issue":"42","noUsgsAuthors":false,"publicationDate":"2009-10-20","publicationStatus":"PW","scienceBaseUri":"505bb6fbe4b08c986b326fa7","contributors":{"authors":[{"text":"Smith, J.J.","contributorId":106175,"corporation":false,"usgs":true,"family":"Smith","given":"J.J.","email":"","affiliations":[],"preferred":false,"id":461311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hasiotis, S.T.","contributorId":107020,"corporation":false,"usgs":true,"family":"Hasiotis","given":"S.T.","affiliations":[],"preferred":false,"id":461312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kraus, M. J.","contributorId":44605,"corporation":false,"usgs":false,"family":"Kraus","given":"M.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":461310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woody, D.T.","contributorId":39207,"corporation":false,"usgs":true,"family":"Woody","given":"D.T.","email":"","affiliations":[],"preferred":false,"id":461309,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70037451,"text":"70037451 - 2009 - Urban streams across the USA: Lessons learned from studies in 9 metropolitan areas","interactions":[],"lastModifiedDate":"2021-02-04T21:34:54.194429","indexId":"70037451","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2564,"text":"Journal of the North American Benthological Society","onlineIssn":"1937-237X","printIssn":"0887-3593","active":true,"publicationSubtype":{"id":10}},"title":"Urban streams across the USA: Lessons learned from studies in 9 metropolitan areas","docAbstract":"Studies of the effects of urbanization on stream ecosystems have usually focused on single metropolitan areas. Synthesis of the results of such studies have been useful in developing general conceptual models of the effects of urbanization, but the strength of such generalizations is enhanced by applying consistent study designs and methods to multiple metropolitan areas across large geographic scales. We summarized the results from studies of the effects of urbanization on stream ecosystems in 9 metropolitan areas across the US (Boston, Massachusetts; Raleigh, North Carolina; Atlanta, Georgia; Birmingham, Alabama; Milwaukee-Green Bay, Wisconsin; Denver, Colorado; Dallas-Fort Worth, Texas; Salt Lake City, Utah; and Portland, Oregon). These studies were conducted as part of the US Geological Survey’s National Water-Quality Assessment Program and were based on a common study design and used standard sample-collection and processing methods to facilitate comparisons among study areas. All studies included evaluations of hydrology, physical habitat, water quality, and biota (algae, macroinvertebrates, fish). Four major conclusions emerged from the studies. First, responses of hydrologic, physical-habitat, water-quality, and biotic variables to urbanization varied among metropolitan areas, except that insecticide inputs consistently increased with urbanization. Second, prior land use, primarily forest and agriculture, appeared to be the most important determinant of the response of biota to urbanization in the areas we studied. Third, little evidence was found for resistance to the effects of urbanization by macroinvertebrate assemblages, even at low levels of urbanization. Fourth, benthic macroinvertebrates have important advantages for assessing the effects of urbanization on stream ecosystems relative to algae and fishes. Overall, our results demonstrate regional differences in the effects of urbanization on stream biota and suggest additional studies to elucidate the causes of these underlying differences.
","language":"English","publisher":"University of Chicago Press","doi":"10.1899/08-153.1","usgsCitation":"Brown, L.R., Cuffney, T.F., Coles, J.F., Fitzpatrick, F., McMahon, G., Steuer, J., Bell, A.H., and May, J.T., 2009, Urban streams across the USA: Lessons learned from studies in 9 metropolitan areas: Journal of the North American Benthological Society, v. 28, no. 4, p. 1051-1069, https://doi.org/10.1899/08-153.1.","productDescription":"19 p.","startPage":"1051","endPage":"1069","numberOfPages":"19","ipdsId":"IP-008405","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":476403,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.1899/08-153.1","text":"External Repository"},{"id":245358,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Colorado, Georgia, Massachusetts, North Carolina, Oregon, Texas, Utah, Wisconsin","city":"Atlanta, Birrmingham, Boston, Dallas-Fort Worth, Denver, Milwaukee-Green Bay, Portland, Raleigh, Salt Lake City","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.70458984375,\n 33.394759218577995\n ],\n [\n -83.935546875,\n 33.394759218577995\n ],\n [\n -83.935546875,\n 34.03445260967645\n ],\n [\n -84.70458984375,\n 34.03445260967645\n ],\n [\n -84.70458984375,\n 33.394759218577995\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.03564453124999,\n 35.42486791930558\n ],\n [\n -78.33251953125,\n 35.42486791930558\n ],\n [\n -78.33251953125,\n 36.19109202182454\n ],\n [\n -79.03564453124999,\n 36.19109202182454\n ],\n [\n -79.03564453124999,\n 35.42486791930558\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.4111328125,\n 42.17968819665961\n ],\n [\n -70.94970703125,\n 42.17968819665961\n ],\n [\n -70.94970703125,\n 42.68243539838623\n ],\n [\n -71.4111328125,\n 42.68243539838623\n ],\n [\n -71.4111328125,\n 42.17968819665961\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.26416015625,\n 42.956422511073335\n ],\n [\n -87.62695312499999,\n 42.956422511073335\n ],\n [\n -87.62695312499999,\n 44.63739123445585\n ],\n [\n -88.26416015625,\n 44.63739123445585\n ],\n [\n -88.26416015625,\n 42.956422511073335\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.5146484375,\n 32.509761735919426\n ],\n [\n -96.21826171874999,\n 32.509761735919426\n ],\n [\n -96.21826171874999,\n 33.100745405144245\n ],\n [\n -97.5146484375,\n 33.100745405144245\n ],\n [\n -97.5146484375,\n 32.509761735919426\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.19238281249999,\n 40.38002840251183\n ],\n [\n -111.51123046875,\n 40.38002840251183\n ],\n [\n -111.51123046875,\n 41.21172151054787\n ],\n [\n -112.19238281249999,\n 41.21172151054787\n ],\n [\n -112.19238281249999,\n 40.38002840251183\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.98095703125,\n 45.259422036351694\n ],\n [\n -122.27783203125,\n 45.259422036351694\n ],\n [\n -122.27783203125,\n 45.73685954736049\n ],\n [\n -122.98095703125,\n 45.73685954736049\n ],\n [\n -122.98095703125,\n 45.259422036351694\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.20947265625,\n 33.15594830078649\n ],\n [\n -86.55029296875,\n 33.15594830078649\n ],\n [\n -86.55029296875,\n 33.94335994657882\n ],\n [\n -87.20947265625,\n 33.94335994657882\n ],\n [\n -87.20947265625,\n 33.15594830078649\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.35888671875,\n 39.40224434029275\n ],\n [\n -104.65576171875,\n 39.40224434029275\n ],\n [\n -104.65576171875,\n 39.9434364619742\n ],\n [\n -105.35888671875,\n 39.9434364619742\n ],\n [\n -105.35888671875,\n 39.40224434029275\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bbe18e4b08c986b3293f8","contributors":{"authors":[{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":461111,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cuffney, Thomas F. 0000-0003-1164-5560 tcuffney@usgs.gov","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":517,"corporation":false,"usgs":true,"family":"Cuffney","given":"Thomas","email":"tcuffney@usgs.gov","middleInitial":"F.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":461117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coles, James F. 0000-0002-1953-012X jcoles@usgs.gov","orcid":"https://orcid.org/0000-0002-1953-012X","contributorId":2239,"corporation":false,"usgs":true,"family":"Coles","given":"James","email":"jcoles@usgs.gov","middleInitial":"F.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":461113,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075 fafitzpa@usgs.gov","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":150001,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","email":"fafitzpa@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":461114,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McMahon, Gerard 0000-0001-7675-777X gmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7675-777X","contributorId":191488,"corporation":false,"usgs":true,"family":"McMahon","given":"Gerard","email":"gmcmahon@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":461115,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Steuer, Jeffrey","contributorId":97530,"corporation":false,"usgs":true,"family":"Steuer","given":"Jeffrey","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":461110,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bell, Amanda H. 0000-0002-7199-2145 ahbell@usgs.gov","orcid":"https://orcid.org/0000-0002-7199-2145","contributorId":1752,"corporation":false,"usgs":true,"family":"Bell","given":"Amanda","email":"ahbell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":461116,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"May, Jason T. 0000-0002-5699-2112 jasonmay@usgs.gov","orcid":"https://orcid.org/0000-0002-5699-2112","contributorId":617,"corporation":false,"usgs":true,"family":"May","given":"Jason","email":"jasonmay@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":461112,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70032753,"text":"70032753 - 2009 - A cross-site comparison of factors influencing soil nitrification rates in northeastern USA forested watersheds","interactions":[],"lastModifiedDate":"2012-03-12T17:21:23","indexId":"70032753","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"A cross-site comparison of factors influencing soil nitrification rates in northeastern USA forested watersheds","docAbstract":"Elevated N deposition is continuing on many forested landscapes around the world and our understanding of ecosystem response is incomplete. Soil processes, especially nitrification, are critical. Many studies of soil N transformations have focused on identifying relationships within a single watershed but these results are often not transferable. We studied 10 small forested research watersheds in the northeastern USA to determine if there were common factors related to soil ammonification and nitrification. Vegetation varied between mixed northern hardwoods and mixed conifers. Watershed surface soils (Oa or A horizons) were sampled at grid or transect points and analyzed for a suite of chemical characteristics. At each sampling point, vegetation and topographic metrics (field and GIS-based) were also obtained. Results were examined by watershed averages (n = 10), seasonal/watershed averages (n = 28), and individual sampling points (n = 608). Using both linear and tree regression techniques, the proportion of conifer species was the single best predictor of nitrification rates, with lower rates at higher conifer dominance. Similar to other studies, the soil C/N ratio was also a good predictor and was well correlated with conifer dominance. Unlike other studies, the presence of Acer saccharum was not by itself a strong predictor, but was when combined with the presence of Betula alleghaniensis. Topographic metrics (slope, aspect, relative elevation, and the topographic index) were not related to N transformation rates across the watersheds. Although found to be significant in other studies, neither soil pH, Ca nor Al was related to nitrification. Results showed a strong relationship between dominant vegetation, soil C, and soil C/N. ?? 2008 Springer Science+Business Media, LLC.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecosystems","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1007/s10021-008-9214-4","issn":"14329","usgsCitation":"Ross, D., Wemple, B., Jamison, A., Fredriksen, G., Shanley, J.B., Lawrence, G., Bailey, S., and Campbell, J., 2009, A cross-site comparison of factors influencing soil nitrification rates in northeastern USA forested watersheds: Ecosystems, v. 12, no. 1, p. 158-178, https://doi.org/10.1007/s10021-008-9214-4.","startPage":"158","endPage":"178","numberOfPages":"21","costCenters":[],"links":[{"id":241360,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213706,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10021-008-9214-4"}],"volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2008-11-12","publicationStatus":"PW","scienceBaseUri":"5059e3a1e4b0c8380cd46143","contributors":{"authors":[{"text":"Ross, D.S.","contributorId":33867,"corporation":false,"usgs":true,"family":"Ross","given":"D.S.","email":"","affiliations":[],"preferred":false,"id":437754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wemple, B.C.","contributorId":89331,"corporation":false,"usgs":true,"family":"Wemple","given":"B.C.","email":"","affiliations":[],"preferred":false,"id":437758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jamison, A.E.","contributorId":97692,"corporation":false,"usgs":true,"family":"Jamison","given":"A.E.","email":"","affiliations":[],"preferred":false,"id":437759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fredriksen, G.","contributorId":56434,"corporation":false,"usgs":true,"family":"Fredriksen","given":"G.","affiliations":[],"preferred":false,"id":437756,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shanley, J. B.","contributorId":52226,"corporation":false,"usgs":true,"family":"Shanley","given":"J.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":437755,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lawrence, G.B. 0000-0002-8035-2350","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":76347,"corporation":false,"usgs":true,"family":"Lawrence","given":"G.B.","affiliations":[],"preferred":false,"id":437757,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bailey, S.W.","contributorId":29113,"corporation":false,"usgs":true,"family":"Bailey","given":"S.W.","email":"","affiliations":[],"preferred":false,"id":437753,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Campbell, J.L.","contributorId":20488,"corporation":false,"usgs":true,"family":"Campbell","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":437752,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70032749,"text":"70032749 - 2009 - Forecasting the combined effects of urbanization and climate change on stream ecosystems: from impacts to management options","interactions":[],"lastModifiedDate":"2015-05-14T13:06:01","indexId":"70032749","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting the combined effects of urbanization and climate change on stream ecosystems: from impacts to management options","docAbstract":"\n
A pseudo-two-dimensional numerical model of estuarine phytoplankton growth and consumption, vertical turbulent mixing, and idealized cross-estuary transport was developed and applied to South San Francisco Bay. This estuary has two bathymetrically distinct habitat types (deep channel, shallow shoal) and associated differences in local net rates of phytoplankton growth and consumption, as well as differences in the water column's tendency to stratify. Because many physical and biological time scales relevant to algal population dynamics decrease with decreasing depth, process rates can be especially fast in the shallow water. We used the model to explore the potential significance of hydrodynamic connectivity between a channel and shoal and whether lateral transport can allow physical or biological processes (e.g. stratification, benthic grazing, light attenuation) in one sub-region to control phytoplankton biomass and bloom development in the adjacent sub-region. Model results for South San Francisco Bay suggest that lateral transport from a productive shoal can result in phytoplankton biomass accumulation in an adjacent deep, unproductive channel. The model further suggests that turbidity and benthic grazing in the shoal can control the occurrence of a bloom system-wide; whereas, turbidity, benthic grazing, and vertical density stratification in the channel are likely to only control local bloom occurrence or modify system-wide bloom magnitude. Measurements from a related field program are generally consistent with model-derived conclusions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jmarsys.2008.07.011","issn":"09247","usgsCitation":"Lucas, L., Koseff, J.R., Monismith, S., and Thompson, J., 2009, Shallow water processes govern system-wide phytoplankton bloom dynamics: A modeling study: Journal of Marine Systems, v. 75, no. 1-2, p. 70-86, https://doi.org/10.1016/j.jmarsys.2008.07.011.","productDescription":"17 p.","startPage":"70","endPage":"86","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":241516,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213853,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jmarsys.2008.07.011"}],"volume":"75","issue":"1-2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b8e46e4b08c986b318834","contributors":{"authors":[{"text":"Lucas, L.V.","contributorId":62777,"corporation":false,"usgs":true,"family":"Lucas","given":"L.V.","email":"","affiliations":[],"preferred":false,"id":436634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koseff, Jeffrey R.","contributorId":37915,"corporation":false,"usgs":false,"family":"Koseff","given":"Jeffrey","email":"","middleInitial":"R.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":436632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monismith, Stephen G.","contributorId":57228,"corporation":false,"usgs":true,"family":"Monismith","given":"Stephen G.","affiliations":[],"preferred":false,"id":436633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, J.K.","contributorId":103300,"corporation":false,"usgs":true,"family":"Thompson","given":"J.K.","email":"","affiliations":[],"preferred":false,"id":436635,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70032487,"text":"70032487 - 2009 - Phenologically-tuned MODIS NDVI-based production anomaly estimates for Zimbabwe","interactions":[],"lastModifiedDate":"2017-04-03T15:06:34","indexId":"70032487","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Phenologically-tuned MODIS NDVI-based production anomaly estimates for Zimbabwe","docAbstract":"For thirty years, simple crop water balance models have been used by the early warning community to monitor agricultural drought. These models estimate and accumulate actual crop evapotranspiration, evaluating environmental conditions based on crop water requirements. Unlike seasonal rainfall totals, these models take into account the phenology of the crop, emphasizing conditions during the peak grain filling phase of crop growth. In this paper we describe an analogous metric of crop performance based on time series of Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) imagery. A special temporal filter is used to screen for cloud contamination. Regional NDVI time series are then composited for cultivated areas, and adjusted temporally according to the timing of the rainy season. This adjustment standardizes the NDVI response vis-??-vis the expected phenological response of maize. A national time series index is then created by taking the cropped-area weighted average of the regional series. This national time series provides an effective summary of vegetation response in agricultural areas, and allows for the identification of NDVI green-up during grain filling. Onset-adjusted NDVI values following the grain filling period are well correlated with U.S. Department of Agriculture production figures, possess desirable linear characteristics, and perform better than more common indices such as maximum seasonal NDVI or seasonally averaged NDVI. Thus, just as appropriately calibrated crop water balance models can provide more information than seasonal rainfall totals, the appropriate agro-phenological filtering of NDVI can improve the utility and accuracy of space-based agricultural monitoring.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2008.08.015","issn":"00344","usgsCitation":"Funk, C., and Budde, M.E., 2009, Phenologically-tuned MODIS NDVI-based production anomaly estimates for Zimbabwe: Remote Sensing of Environment, v. 113, no. 1, p. 115-125, https://doi.org/10.1016/j.rse.2008.08.015.","productDescription":"11 p.","startPage":"115","endPage":"125","numberOfPages":"11","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":241513,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213850,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2008.08.015"}],"volume":"113","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a7889e4b0c8380cd7870d","contributors":{"authors":[{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":436426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budde, Michael E. 0000-0002-9098-2751 mbudde@usgs.gov","orcid":"https://orcid.org/0000-0002-9098-2751","contributorId":3007,"corporation":false,"usgs":true,"family":"Budde","given":"Michael","email":"mbudde@usgs.gov","middleInitial":"E.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":436425,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70033200,"text":"70033200 - 2009 - Exotic plant species associations with horse trails, old roads, and intact native communities in the Missouri Ozarks","interactions":[],"lastModifiedDate":"2013-02-21T20:53:03","indexId":"70033200","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2821,"text":"Natural Areas Journal","active":true,"publicationSubtype":{"id":10}},"title":"Exotic plant species associations with horse trails, old roads, and intact native communities in the Missouri Ozarks","docAbstract":"We compared the extent to which exotic species are associated with horse trails, old roads, and intact communities within three native vegetation types in Ozark National Scenic Riverways, Missouri. We used a general linear model procedure and a Bonferroni multiple comparison test to compare exotic species richness, exotic to native species ratios, and exotic species percent cover across three usage types (horse trails, old roads, and intact communities) and three community types (river bottoms, upland waterways, and glades). We found that both exotic species richness and the ratio of exotic species to native species were greater in plots located along horse trails than in plots located either in intact native communities or along old roads. Native community types did not differ in the number of exotic species present, but river bottoms had a significantly higher exotic to native species ratio than glades. Continued introduction of exotic plant propagules may explain why horse trails contain more exotic species than other areas in a highly disturbed landscape.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Natural Areas Journal","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Natural Areas Association","doi":"10.3375/043.029.0106","issn":"08858","usgsCitation":"Stroh, E., and Struckhoff, M., 2009, Exotic plant species associations with horse trails, old roads, and intact native communities in the Missouri Ozarks: Natural Areas Journal, v. 29, no. 1, p. 50-56, https://doi.org/10.3375/043.029.0106.","startPage":"50","endPage":"56","numberOfPages":"7","costCenters":[],"links":[{"id":240955,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":267923,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3375/043.029.0106"}],"volume":"29","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0db2e4b0c8380cd5314c","contributors":{"authors":[{"text":"Stroh, E.D.","contributorId":106717,"corporation":false,"usgs":true,"family":"Stroh","given":"E.D.","email":"","affiliations":[],"preferred":false,"id":439795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Struckhoff, M.A.","contributorId":84985,"corporation":false,"usgs":true,"family":"Struckhoff","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":439794,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70033198,"text":"70033198 - 2009 - How processing digital elevation models can affect simulated water budgets","interactions":[],"lastModifiedDate":"2012-03-12T17:21:34","indexId":"70033198","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"How processing digital elevation models can affect simulated water budgets","docAbstract":"For regional models, the shallow water table surface is often used as a source/sink boundary condition, as model grid scale precludes simulation of the water table aquifer. This approach is appropriate when the water table surface is relatively stationary. Since water table surface maps are not readily available, the elevation of the water table used in model cells is estimated via a two-step process. First, a regression equation is developed using existing land and water table elevations from wells in the area. This equation is then used to predict the water table surface for each model cell using land surface elevation available from digital elevation models (DEM). Two methods of processing DEM for estimating the land surface for each cell are commonly used (value nearest the cell centroid or mean value in the cell). This article demonstrates how these two methods of DEM processing can affect the simulated water budget. For the example presented, approximately 20% more total flow through the aquifer system is simulated if the centroid value rather than the mean value is used. This is due to the one-third greater average ground water gradients associated with the centroid value than the mean value. The results will vary depending on the particular model area topography and cell size. The use of the mean DEM value in each model cell will result in a more conservative water budget and is more appropriate because the model cell water table value should be representative of the entire cell area, not the centroid of the model cell.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ground Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1111/j.1745-6584.2008.00497.x","issn":"00174","usgsCitation":"Kuniansky, E., Lowery, M., and Campbell, B.G., 2009, How processing digital elevation models can affect simulated water budgets: Ground Water, v. 47, no. 1, p. 97-107, https://doi.org/10.1111/j.1745-6584.2008.00497.x.","startPage":"97","endPage":"107","numberOfPages":"11","costCenters":[],"links":[{"id":213310,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1745-6584.2008.00497.x"},{"id":240922,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"1","noUsgsAuthors":false,"publicationDate":"2009-01-07","publicationStatus":"PW","scienceBaseUri":"505a3254e4b0c8380cd5e70f","contributors":{"authors":[{"text":"Kuniansky, E. L.","contributorId":82342,"corporation":false,"usgs":true,"family":"Kuniansky","given":"E. L.","affiliations":[],"preferred":false,"id":439788,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowery, M.A.","contributorId":56754,"corporation":false,"usgs":true,"family":"Lowery","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":439786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell, B. G.","contributorId":68764,"corporation":false,"usgs":true,"family":"Campbell","given":"B.","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":439787,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70032309,"text":"70032309 - 2009 - Copper isotope fractionation in acid mine drainage","interactions":[],"lastModifiedDate":"2018-11-02T08:53:19","indexId":"70032309","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Copper isotope fractionation in acid mine drainage","docAbstract":"We measured the Cu isotopic composition of primary minerals and stream water affected by acid mine drainage in a mineralized watershed (Colorado, USA). The δ65Cu values (based on 65Cu/63Cu) of enargite (δ65Cu = −0.01 ± 0.10‰; 2σ) and chalcopyrite (δ65Cu = 0.16 ± 0.10‰) are within the range of reported values for terrestrial primary Cu sulfides (−1‰ < δ65Cu < 1‰). These mineral samples show lower δ65Cu values than stream waters (1.38‰ ⩽ δ65Cu ⩽ 1.69‰). The average isotopic fractionation (Δaq-min = δ65Cuaq − δ65Cumin, where the latter is measured on mineral samples from the field system), equals 1.43 ± 0.14‰ and 1.60 ± 0.14‰ for chalcopyrite and enargite, respectively. To interpret this field survey, we leached chalcopyrite and enargite in batch experiments and found that, as in the field, the leachate is enriched in 65Cu relative to chalcopyrite (1.37 ± 0.14‰) and enargite (0.98 ± 0.14‰) when microorganisms are absent. Leaching of minerals in the presence of Acidithiobacillus ferrooxidans results in smaller average fractionation in the opposite direction for chalcopyrite (
Abstract: Some sources of organic wastewater compounds (OWCs) to streams, lakes, and estuaries, including wastewater‐treatment‐plant effluent, have been well documented, but other sources, particularly wet‐weather discharges from combined‐sewer‐overflow (CSO) and urban runoff, may also be major sources of OWCs. Samples of wastewater‐treatment‐plant (WWTP) effluent, CSO effluent, urban streams, large rivers, a reference (undeveloped) stream, and Lake Champlain were collected from March to August 2006. The highest concentrations of many OWCs associated with wastewater were in WWTP‐effluent samples, but high concentrations of some OWCs in samples of CSO effluent and storm runoff from urban streams subject to leaky sewer pipes or CSOs were also detected. Total concentrations and numbers of compounds detected differed substantially among sampling sites. The highest total OWC concentrations (10‐100 μg/l) were in samples of WWTP and CSO effluent. Total OWC concentrations in samples from urban streams ranged from 0.1 to 10 μg/l, and urban stream‐stormflow samples had higher concentrations than baseflow samples because of contributions of OWCs from CSOs and leaking sewer pipes. The relations between OWC concentrations in WWTP‐effluent and those in CSO effluent and urban streams varied with the degree to which the compound is removed through normal wastewater treatment. Concentrations of compounds that are highly removed during normal wastewater treatment [including caffeine, Tris(2‐butoxyethyl)phosphate, and cholesterol] were generally similar to or higher in CSO effluent than in WWTP effluent (and ranged from around 1 to over 10 μg/l) because CSO effluent is untreated, and were higher in urban‐stream stormflow samples than in baseflow samples as a result of CSO discharge and leakage from near‐surface sources during storms. Concentrations of compounds that are poorly removed during treatment, by contrast, are higher in WWTP effluent than in CSO, due to dilution. Results indicate that CSO effluent and urban stormwaters can be a significant major source of OWCs entering large water bodies such as Burlington Bay.