The Village of Endicott, New York, is seeking an alternate source of public drinking water with the potential to supplement their current supply, which requires treatment due to legacy contamination. The southerly-draining Nanticoke Creek valley, located north of the village, was identified as a potential water source and the local stratified-drift (valley fill) aquifer was investigated to determine its hydrogeologic and water-quality characteristics.
\nNanticoke Creek and its aquifer extend from the hamlet of Glen Aubrey, N.Y., to the village of Endicott, a distance of about 15 miles, where it joins the Susquehanna River and its aquifer. The glacial sediments that comprise the stratified-drift aquifer vary in thickness and are generally underlain by glacial till over Devonian-aged shale and siltstone.
\nGroundwater is more plentiful in the northern part of the aquifer where sand and gravel deposits are generally more permeable than in the southern part of the aquifer where less-permeable unconsolidated deposits are found. Generally there is enough groundwater to supply most homeowner wells and in some cases, supply small public-water systems such as schools, mobile-home parks, and small commercial/industrial facilities. The aquifer is recharged by precipitation, runoff, and tributary streams. Most tributary streams flowing across alluvial deposits lose water to the aquifer as they flow off of their bedrock-lined channels and into the more permeable alluvial deposits at the edges of the valley.
\nThe quality of both surface water and groundwater is generally good. Some water wells do have water-quality issues related to natural constituents (manganese and iron) and several homeowners noted either the smell and (or) taste of hydrogen sulfide in their drinking water. Dissolved methane concentrations from five drinking-water wells were well below the potentially explosive value of 28 milligrams per liter. Samples from surface and groundwater met nearly all State and Federal water-quality standards for common ion and nutrient concentrations with the exception of manganese, which is common in central New York where water sourced from shale rock or glacial sediments derived from shale bedrock naturally develops higher manganese concentrations. One shallow dug well also had elevated sodium and chloride concentrations that are likely sourced from road salt runoff from two nearby roads.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145063","collaboration":"Prepared in cooperation with the Village of Endicott, New York","usgsCitation":"Kreitinger, E.A., and Kappel, W.M., 2014, Hydrogeology and water quality of the Nanticoke Creek stratified-drift aquifer, near Endicott, New York: U.S. Geological Survey Scientific Investigations Report 2014-5063, Report: v, 19 p.; Appendixes 1-1 to 1-6, https://doi.org/10.3133/sir20145063.","productDescription":"Report: v, 19 p.; Appendixes 1-1 to 1-6","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051633","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":287435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145063.jpg"},{"id":287427,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5063/appendix/sir2014-5063_appendix_table1-1.xlsx"},{"id":287425,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5063/"},{"id":287426,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5063/pdf/sir2014-5063.pdf"},{"id":287430,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5063/appendix/sir2014-5063_appendix_table1-4.xlsx"},{"id":287428,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5063/appendix/sir2014-5063_appendix_table1-2.xlsx"},{"id":287429,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5063/appendix/sir2014-5063_appendix_table1-3.xlsx"},{"id":287432,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5063/appendix/sir2014-5063_appendix_table1-5.xlsx"},{"id":287434,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5063/appendix/sir2014-5063_appendix_table1-6.xlsx"}],"scale":"150000","country":"United States","state":"New York","city":"Endicott","otherGeospatial":"Nanticoke Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.225196,42.048799 ], [ -76.225196,42.393393 ], [ -75.849501,42.393393 ], [ -75.849501,42.048799 ], [ -76.225196,42.048799 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"537dbccfe4b05ed6215c0785","contributors":{"authors":[{"text":"Kreitinger, Elizabeth A.","contributorId":47698,"corporation":false,"usgs":true,"family":"Kreitinger","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":492593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kappel, William M. 0000-0002-2382-9757 wkappel@usgs.gov","orcid":"https://orcid.org/0000-0002-2382-9757","contributorId":1074,"corporation":false,"usgs":true,"family":"Kappel","given":"William","email":"wkappel@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492592,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70099229,"text":"fs20133107 - 2014 - Water resources of De Soto Parish, Louisiana","interactions":[],"lastModifiedDate":"2014-05-27T08:41:22","indexId":"fs20133107","displayToPublicDate":"2014-05-21T07:49:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3107","title":"Water resources of De Soto Parish, Louisiana","docAbstract":"Information concerning the availability, use, and quality of water in De Soto Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://waterdata. usgs.gov/nwis) are the primary sources of the information presented here.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133107","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Prakken, L., and White, V.E., 2014, Water resources of De Soto Parish, Louisiana: U.S. Geological Survey Fact Sheet 2013-3107, 6 p., https://doi.org/10.3133/fs20133107.","productDescription":"6 p.","numberOfPages":"6","additionalOnlineFiles":"Y","ipdsId":"IP-052133","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":287367,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133107.jpg"},{"id":287360,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3107/pdf/fs2013-3107.pdf"},{"id":287332,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3107/"}],"projection":"Albers Equal-Area Conic projection","datum":"NAD 1983","country":"United States","state":"Louisiana","otherGeospatial":"De Soto Parish","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.0,31.916667 ], [ -94.0,32.333333 ], [ -93.5,32.333333 ], [ -93.5,31.916667 ], [ -94.0,31.916667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"537dbcd1e4b05ed6215c0799","contributors":{"authors":[{"text":"Prakken, Lawrence B.","contributorId":73978,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence B.","affiliations":[],"preferred":false,"id":491875,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Vincent E. 0000-0002-1660-0102 vwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-1660-0102","contributorId":5388,"corporation":false,"usgs":true,"family":"White","given":"Vincent","email":"vwhite@usgs.gov","middleInitial":"E.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":491874,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70095796,"text":"sir20145038 - 2014 - Creating a monthly time series of the potentiometric surface in the Upper Floridan aquifer, Northern Tampa Bay area, Florida, January 2000-December 2009","interactions":[],"lastModifiedDate":"2014-05-20T08:32:05","indexId":"sir20145038","displayToPublicDate":"2014-05-20T08:21:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5038","title":"Creating a monthly time series of the potentiometric surface in the Upper Floridan aquifer, Northern Tampa Bay area, Florida, January 2000-December 2009","docAbstract":"In Florida’s karst terrain, where groundwater and surface waters interact, a mapping time series of the potentiometric surface in the Upper Floridan aquifer offers a versatile metric for assessing the hydrologic condition of both the aquifer and overlying streams and wetlands. Long-term groundwater monitoring data were used to generate a monthly time series of potentiometric surfaces in the Upper Floridan aquifer over a 573-square-mile area of west-central Florida between January 2000 and December 2009. Recorded groundwater elevations were collated for 260 groundwater monitoring wells in the Northern Tampa Bay area, and a continuous time series of daily observations was created for 197 of the wells by estimating missing daily values through regression relations with other monitoring wells. Kriging was used to interpolate the monthly average potentiometric-surface elevation in the Upper Floridan aquifer over a decade. The mapping time series gives spatial and temporal coherence to groundwater monitoring data collected continuously over the decade by three different organizations, but at various frequencies. Further, the mapping time series describes the potentiometric surface beneath parts of six regionally important stream watersheds and 11 municipal well fields that collectively withdraw about 90 million gallons per day from the Upper Floridan aquifer.
\nMonthly semivariogram models were developed using monthly average groundwater levels at wells. Kriging was used to interpolate the monthly average potentiometric-surface elevations and to quantify the uncertainty in the interpolated elevations. Drawdown of the potentiometric surface within well fields was likely the cause of a characteristic decrease and then increase in the observed semivariance with increasing lag distance. This characteristic made use of the hole effect model appropriate for describing the monthly semivariograms and the interpolated surfaces. Spatial variance reflected in the monthly semivariograms decreased markedly between 2002 and 2003, timing that coincided with decreases in well-field pumping. Cross-validation results suggest that the kriging interpolation may smooth over the drawdown of the potentiometric surface near production wells.
\nThe groundwater monitoring network of 197 wells yielded an average kriging error in the potentiometric-surface elevations of 2 feet or less over approximately 70 percent of the map area. Additional data collection within the existing monitoring network of 260 wells and near selected well fields could reduce the error in individual months. Reducing the kriging error in other areas would require adding new monitoring wells. Potentiometric-surface elevations fluctuated by as much as 30 feet over the study period, and the spatially averaged elevation for the entire surface rose by about 2 feet over the decade. Monthly potentiometric-surface elevations describe the lateral groundwater flow patterns in the aquifer and are usable at a variety of spatial scales to describe vertical groundwater recharge and discharge conditions for overlying surface-water features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145038","collaboration":"Prepared in cooperation with the Southwest Florida Water Management District","usgsCitation":"Lee, T.M., and Fouad, G.G., 2014, Creating a monthly time series of the potentiometric surface in the Upper Floridan aquifer, Northern Tampa Bay area, Florida, January 2000-December 2009: U.S. Geological Survey Scientific Investigations Report 2014-5038, Report: v, 26 p.; Appendix 1-3; Animation File; Downloads, https://doi.org/10.3133/sir20145038.","productDescription":"Report: v, 26 p.; Appendix 1-3; Animation File; Downloads","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2000-01-01","temporalEnd":"2009-12-31","ipdsId":"IP-049010","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":287307,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145038.jpg"},{"id":287303,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5038/pdf/sir2014-5038.pdf"},{"id":287304,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5038/appendix"},{"id":287302,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5038/"},{"id":287305,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5038/video"},{"id":287306,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5038/downloads"}],"projection":"Universal Transverse Mercator, zone 17 north","datum":"World Geodetic System 1984","country":"United States","state":"Florida","otherGeospatial":"Northern Tampa Bay Area","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82.920685,27.897349 ], [ -82.920685,28.500075 ], [ -82.099457,28.500075 ], [ -82.099457,27.897349 ], [ -82.920685,27.897349 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"537c6b50e4b00e1e1a484822","contributors":{"authors":[{"text":"Lee, Terrie M. tmlee@usgs.gov","contributorId":2461,"corporation":false,"usgs":true,"family":"Lee","given":"Terrie","email":"tmlee@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":491437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fouad, Geoffrey G.","contributorId":101996,"corporation":false,"usgs":true,"family":"Fouad","given":"Geoffrey","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":491438,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70106982,"text":"70106982 - 2014 - Beach science in the Great Lakes","interactions":[],"lastModifiedDate":"2014-05-19T15:00:53","indexId":"70106982","displayToPublicDate":"2014-05-19T14:57:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Beach science in the Great Lakes","docAbstract":"Monitoring beach waters for human health has led to an increase and evolution of science in the Great Lakes, which includes microbiology, limnology, hydrology, meteorology, epidemiology, and metagenomics, among others. In recent years, concerns over the accuracy of water quality standards at protecting human health have led to a significant interest in understanding the risk associated with water contact in both freshwater and marine environments. Historically, surface waters have been monitored for fecal indicator bacteria (fecal coliforms, Escherichia coli, enterococci), but shortcomings of the analytical test (lengthy assay) have resulted in a re-focusing of scientific efforts to improve public health protection. Research has led to the discovery of widespread populations of fecal indicator bacteria present in natural habitats such as soils, beach sand, and stranded algae. Microbial source tracking has been used to identify the source of these bacteria and subsequently assess their impact on human health. As a result of many findings, attempts have been made to improve monitoring efficiency and efficacy with the use of empirical predictive models and molecular rapid tests. All along, beach managers have actively incorporated new findings into their monitoring programs. With the abundance of research conducted and information gained over the last 25 years, “Beach Science” has emerged, and the Great Lakes have been a focal point for much of the ground-breaking work. Here, we review the accumulated research on microbiological water quality of Great Lakes beaches and provide a historic context to the collaborative efforts that have advanced this emerging science.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2013.12.011","usgsCitation":"Nevers, M.B., Byappanahalli, M.N., Edge, T.A., and Whitman, R.L., 2014, Beach science in the Great Lakes: Journal of Great Lakes Research, v. 40, no. 1, p. 1-14, https://doi.org/10.1016/j.jglr.2013.12.011.","productDescription":"14 p.","startPage":"1","endPage":"14","numberOfPages":"14","ipdsId":"IP-052073","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":287292,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287282,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2013.12.011"}],"country":"Canada;United States","otherGeospatial":"Great Lakes","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.44,41.18 ], [ -92.44,49.28 ], [ -75.71,49.28 ], [ -75.71,41.18 ], [ -92.44,41.18 ] ] ] } } ] }","volume":"40","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"537b19d0e4b0929ba496ab26","contributors":{"authors":[{"text":"Nevers, Meredith B.","contributorId":91803,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":493826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byappanahalli, Murulee N.","contributorId":79027,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Murulee","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":493825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edge, Thomas A.","contributorId":21074,"corporation":false,"usgs":true,"family":"Edge","given":"Thomas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":493824,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitman, Richard L. rwhitman@usgs.gov","contributorId":542,"corporation":false,"usgs":true,"family":"Whitman","given":"Richard","email":"rwhitman@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":493823,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70106993,"text":"70106993 - 2014 - The distribution and extent of heavy metal accumulation in song sparrows along Arizona's upper Santa Cruz River","interactions":[],"lastModifiedDate":"2018-09-18T16:26:11","indexId":"70106993","displayToPublicDate":"2014-05-19T14:37:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"The distribution and extent of heavy metal accumulation in song sparrows along Arizona's upper Santa Cruz River","docAbstract":"Heavy metals are persistent environmental contaminants, and transport of metals into the environment poses a threat to ecosystems, as plants and wildlife are susceptible to long-term exposure, bioaccumulation, and potential toxicity. We investigated the distribution and cascading extent of heavy metal accumulation in southwestern song sparrows (Melospiza melodia fallax), a resident riparian bird species that occurs along the US/Mexico border in Arizona’s upper Santa Cruz River watershed. This study had three goals: (1) quantify the degree of heavy metal accumulation in sparrows and determine the distributional patterns among study sites, (2) compare concentrations of metals found in this study to those found in studies performed prior to a 2009 international wastewater facility upgrade, and (3) assess the condition of song sparrows among sites with differing potential levels of exposure. We examined five study sites along with a reference site that reflect different potential sources of contamination. Body mass residuals and leukocyte counts were used to assess sparrow condition. Birds at our study sites typically had higher metal concentrations than birds at the reference site. Copper, mercury, nickel, and selenium in song sparrows did exceed background levels, although most metals were below background concentrations determined from previous studies. Song sparrows generally showed lower heavy metal concentrations compared to studies conducted prior to the 2009 wastewater facility upgrade. We found no cascading effects as a result of metal exposure.","language":"English","publisher":"Springer","doi":"10.1007/s10661-014-3737-2","usgsCitation":"Lester, M.B., and van Riper, C., 2014, The distribution and extent of heavy metal accumulation in song sparrows along Arizona's upper Santa Cruz River: Environmental Monitoring and Assessment, v. 186, no. 8, p. 4779-4791, https://doi.org/10.1007/s10661-014-3737-2.","productDescription":"13 p.","startPage":"4779","endPage":"4791","numberOfPages":"13","ipdsId":"IP-045400","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":287289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287288,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10661-014-3737-2"}],"country":"United States","state":"Arizona","otherGeospatial":"Santa Cruz River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.199493,31.248617 ], [ -111.199493,31.700714 ], [ -110.500488,31.700714 ], [ -110.500488,31.248617 ], [ -111.199493,31.248617 ] ] ] } } ] }","volume":"186","issue":"8","noUsgsAuthors":false,"publicationDate":"2014-04-12","publicationStatus":"PW","scienceBaseUri":"537b19d3e4b0929ba496ab3f","contributors":{"authors":[{"text":"Lester, Michael B.","contributorId":92170,"corporation":false,"usgs":true,"family":"Lester","given":"Michael","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":493842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":493841,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70127601,"text":"70127601 - 2014 - Factors affecting public-supply well vulnerability in two karst aquifers","interactions":[],"lastModifiedDate":"2014-09-30T13:57:53","indexId":"70127601","displayToPublicDate":"2014-05-19T13:55:46","publicationYear":"2014","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":"Factors affecting public-supply well vulnerability in two karst aquifers","docAbstract":"Karst aquifers occur in a range of climatic and geologic settings. Nonetheless, they are commonly characterized by their vulnerability to water-quality impairment. Two karst aquifers, the Edwards aquifer in south-central Texas and the Upper Floridan aquifer in western Florida, were investigated to assess factors that control the movement of contaminants to public-supply wells (PSWs). The geochemistry of samples from a selected PSW or wellfield in each aquifer was compared with that from nearby monitoring wells and regional PSWs. Geochemistry results were integrated with age tracers, flow modeling, and depth-dependent data to refine aquifer conceptual models and to identify factors that affect contaminant movement to PSWs. The oxic Edwards aquifer is vertically well mixed at the selected PSW/wellfield, although regionally the aquifer is geochemically variable downdip. The mostly anoxic Upper Floridan aquifer is affected by denitrification and also is geochemically variable with depth. In spite of considerable differences in geology and hydrogeology, the two aquifers are similarly vulnerable to anthropogenic contamination. Vulnerability in studied PSWs in both aquifers is strongly influenced by rapid karst flowpaths and the dominance of young (<10 years) groundwater. Vulnerability was demonstrated by the frequent detection of similar constituents of concern in both aquifers (nitrate, atrazine, deethylatrazine, tetrachloroethene, and chloroform). Specific consideration of water-quality protection efforts, well construction and placement, and aquifer response times to land-use changes and contaminant loading are discussed, with implications for karst groundwater management.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ground Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"National Ground Water Association","publisherLocation":"Westerville, OH","doi":"10.1111/gwat.12201","usgsCitation":"Musgrove, M., Katz, B.G., Fahlquist, L.S., Crandall, C.A., and Lindgren, R.J., 2014, Factors affecting public-supply well vulnerability in two karst aquifers: Ground Water, v. 52, no. 1, p. 63-75, https://doi.org/10.1111/gwat.12201.","productDescription":"13 p.","startPage":"63","endPage":"75","numberOfPages":"13","ipdsId":"IP-052620","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":472988,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.12201","text":"Publisher Index Page"},{"id":294662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294659,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/gwat.12201/pdf"},{"id":294661,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/gwat.12201"}],"volume":"52","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-05-19","publicationStatus":"PW","scienceBaseUri":"542bc636e4b0abfb4c8097f5","chorus":{"doi":"10.1111/gwat.12201","url":"http://dx.doi.org/10.1111/gwat.12201","publisher":"Wiley-Blackwell","authors":"Musgrove MaryLynn, Katz Brian G., Fahlquist Lynne S., Crandall Christy A., Lindgren Richard J.","journalName":"Groundwater","publicationDate":"5/19/2014","auditedOn":"3/17/2016"},"contributors":{"authors":[{"text":"Musgrove, MaryLynn","contributorId":34878,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","affiliations":[],"preferred":false,"id":502506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katz, Brian G. bkatz@usgs.gov","contributorId":1093,"corporation":false,"usgs":true,"family":"Katz","given":"Brian","email":"bkatz@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":502504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fahlquist, Lynne S. 0000-0002-4993-4037 lfahlqst@usgs.gov","orcid":"https://orcid.org/0000-0002-4993-4037","contributorId":1051,"corporation":false,"usgs":true,"family":"Fahlquist","given":"Lynne","email":"lfahlqst@usgs.gov","middleInitial":"S.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":502502,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crandall, Christy A. crandall@usgs.gov","contributorId":1091,"corporation":false,"usgs":true,"family":"Crandall","given":"Christy","email":"crandall@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":502503,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindgren, Richard J. lindgren@usgs.gov","contributorId":1667,"corporation":false,"usgs":true,"family":"Lindgren","given":"Richard","email":"lindgren@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":502505,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70104799,"text":"ofr20141099 - 2014 - Mercury concentrations in water, and mercury and selenium concentrations in fish from Brownlee Reservoir and selected sites in Boise and Snake Rivers, Idaho and Oregon, 2013","interactions":[],"lastModifiedDate":"2014-05-19T12:44:06","indexId":"ofr20141099","displayToPublicDate":"2014-05-19T12:35:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1099","title":"Mercury concentrations in water, and mercury and selenium concentrations in fish from Brownlee Reservoir and selected sites in Boise and Snake Rivers, Idaho and Oregon, 2013","docAbstract":"Mercury (Hg) analyses were conducted on samples of sport fish and water collected from six sampling sites in the Boise and Snake Rivers, and Brownlee Reservoir to meet National Pollution Discharge and Elimination System (NPDES) permit requirements for the City of Boise, Idaho. A water sample was collected from each site during October and November 2013 by the City of Boise personnel and was analyzed by the Boise City Public Works Water Quality Laboratory. Total Hg concentrations in unfiltered water samples ranged from 0.73 to 1.21 nanograms per liter (ng/L) at five river sites; total Hg concentration was highest (8.78 ng/L) in a water sample from Brownlee Reservoir. All Hg concentrations in water samples were less than the EPA Hg chronic aquatic life criterion in Idaho (12 ng/L).
\nThe EPA recommended a water-quality criterion of 0.30 milligrams per kilogram (mg/kg) methylmercury (MeHg) expressed as a fish-tissue residue value (wet-weight MeHg in fish tissue). MeHg residue in fish tissue is considered to be equivalent to total Hg in fish muscle tissue and is referred to as Hg in this report. The Idaho Department of Environmental Quality adopted the EPA’s fish-tissue criterion and a reasonable potential to exceed (RPTE) threshold 20 percent lower than the criterion or greater than 0.24 mg/kg based on an average concentration of 10 fish from a receiving waterbody. NPDES permitted discharge to waters with fish having Hg concentrations exceeding 0.24 mg/kg are said to have a reasonable potential to exceed the water-quality criterion and thus are subject to additional permit obligations, such as requirements for increased monitoring and the development of a Hg minimization plan. The Idaho Fish Consumption Advisory Program (IFCAP) issues fish advisories to protect general and sensitive populations of fish consumers and has developed an action level of 0.22 mg/kg wet weight Hg in fish tissue. Fish consumption advisories are water body- and species-specific and are used to advise of allowable fish consumption from specific water bodies. The geometric mean Hg concentration of 10 fish of a single species collected from a single water body (lake or stream) in Idaho is compared to the action level to determine if a fish consumption advisory should be issued.
\nThe U.S. Geological Survey collected and analyzed individual fillets of mountain whitefish (Prosopium williamsoni), smallmouth bass (Micropterus dolomieu), and channel catfish (Ictalurus punctatus) for Hg. The median Hg concentration of 0.32 mg/kg exceeded the Idaho water-quality criterion at the site in Brownlee Reservoir. Average Hg concentrations from Brownlee Reservoir (0.32 mg/kg) and the Boise River at mouth (0.33 mg/kg) exceeded the Hg RPTE threshold (>0.24 mg/kg). IFCAP action levels also were exceeded at the sites on Brownlee Reservoir and at the mouth of the Boise River. Median Hg concentrations in fish at the remaining four river sites were less than 0.20 mg/kg with average concentrations ranging from 0.14 to 0.21 mg/kg Hg.
\nSelenium (Se) analysis also was conducted on one composite fish tissue sample per site to screen for general concentrations and to provide information for future risk assessments. Concentrations of Se ranged from 0.07 to 0.49 mg/kg wet weight; average concentrations were highest in smallmouth bass (0.40 mg/kg) and lowest in mountain whitefish (0.12 mg/kg).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141099","collaboration":"Prepared in cooperation with the City of Boise","usgsCitation":"MacCoy, D.E., 2014, Mercury concentrations in water, and mercury and selenium concentrations in fish from Brownlee Reservoir and selected sites in Boise and Snake Rivers, Idaho and Oregon, 2013: U.S. Geological Survey Open-File Report 2014-1099, iv, 26 p., https://doi.org/10.3133/ofr20141099.","productDescription":"iv, 26 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-052783","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":287286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141099.PNG"},{"id":287284,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1099/"},{"id":287285,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1099/pdf/ofr2014-1099.pdf"}],"projection":"Idaho Transverse Mercator","datum":"North American Datum of 1983","country":"United States","state":"Idaho;Oregon","otherGeospatial":"Boise River;Brownlee Reservoir;Snake River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.4013,43.1491 ], [ -117.4013,44.4965 ], [ -115.9634,44.4965 ], [ -115.9634,43.1491 ], [ -117.4013,43.1491 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"537b19d3e4b0929ba496ab3a","contributors":{"authors":[{"text":"MacCoy, Dorene E. 0000-0001-6810-4728 demaccoy@usgs.gov","orcid":"https://orcid.org/0000-0001-6810-4728","contributorId":948,"corporation":false,"usgs":true,"family":"MacCoy","given":"Dorene","email":"demaccoy@usgs.gov","middleInitial":"E.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493798,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70125431,"text":"70125431 - 2014 - Sea otters are recolonizing southern California in fits and starts","interactions":[],"lastModifiedDate":"2014-09-18T09:28:17","indexId":"70125431","displayToPublicDate":"2014-05-17T13:17:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Sea otters are recolonizing southern California in fits and starts","docAbstract":"After near extinction as a result of the fur trade in the 1700s and 1800s, the southern sea otter slowly reoccupied the core of its range in central California. Range expansion beyond central California is seen as key to full recovery of otters, but the rate of expansion has been sporadic, raising concerns about habitat quality in southern California. To describe the range expansion of sea otters from central into southern California, we used skiff surveys, aerial surveys, and archival time-depth recorders from 2004 to 2013. These observations show that range expansion began when male otters swam southeast of Point Conception (Cojo Anchorage), perhaps to seek refuge from bad weather and to feed on unexploited resources. After several years of seasonal use by male groups, females began to use the area, leading to reproduction and a secondary increase in abundance. In contrast, a second male group that moved farther down the coast to Coal Oil Point stalled and retreated. Such range expansion and contraction can be explained by the social nature of sea otters, which acts to slow dispersal away from groups. Otter densities at Cojo Anchorage are now approaching equilibrium levels reported for central California. As in central California, otters rested in and near kelp forest habitat, but used deeper water for foraging. Together, these observations suggest habitat in the Santa Barbara Channel can still support sea otters, but range expansion of otters into southern California will be episodic due to social dynamics.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecosphere","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/ES13-00394.1","usgsCitation":"Lafferty, K.D., and Tinker, M.T., 2014, Sea otters are recolonizing southern California in fits and starts: Ecosphere, v. 5, no. 5, art50; 11 p., https://doi.org/10.1890/ES13-00394.1.","productDescription":"art50; 11 p.","numberOfPages":"11","ipdsId":"IP-055028","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":472989,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es13-00394.1","text":"Publisher Index Page"},{"id":294059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293994,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/ES13-00394.1"}],"country":"United States","state":"California","otherGeospatial":"Santa Barbara Channel","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.146119,34.094231 ], [ -120.146119,34.389398 ], [ -119.633881,34.389398 ], [ -119.633881,34.094231 ], [ -120.146119,34.094231 ] ] ] } } ] }","volume":"5","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-05-06","publicationStatus":"PW","scienceBaseUri":"541a9493e4b01571b3d4cc7a","contributors":{"authors":[{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501432,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70099907,"text":"sir20145044 - 2014 - Water levels and water quality in the Sparta-Memphis aquifer (middle Claiborne aquifer) in Arkansas, spring-summer 2011","interactions":[],"lastModifiedDate":"2016-09-22T15:02:13","indexId":"sir20145044","displayToPublicDate":"2014-05-16T07:59:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5044","title":"Water levels and water quality in the Sparta-Memphis aquifer (middle Claiborne aquifer) in Arkansas, spring-summer 2011","docAbstract":"The U.S. Geological Survey, in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey, has monitored water levels in the Sparta Sand of Claiborne Group and Memphis Sand of Claiborne Group (herein referred to as “the Sparta Sand” and “the Memphis Sand,” respectively) since the 1920s. Groundwater withdrawals have increased while water levels have declined since monitoring was initiated. Herein, aquifers in the Sparta Sand and Memphis Sand will be referred to as “the Sparta-Memphis aquifer” throughout Arkansas. During the spring of 2011, 291 water levels were measured in wells completed in the Sparta-Memphis aquifer and used to produce a regional potentiometric-surface map. During the summer of 2011, groundwater-quality samples were collected and measured from 61 wells for specific conductance, pH, and temperature.
In the northern half of Arkansas, the regional direction of groundwater flow in the Sparta-Memphis aquifer is generally to the south-southeast and flows east and south in the southern half of Arkansas. The groundwater in the southern half of Arkansas flows away from the outcrop area except where affected by large depressions in the potentiometric surface. The highest and lowest water-level altitudes measured in the Sparta-Memphis aquifer were 326 feet above and 120 feet below National Geodetic Vertical Datum of 1929 (NGVD 29), respectively.
Five depressions are located in the following counties: Arkansas, Cleveland, Jefferson, Lincoln, and Prairie; Union; Cross, Poinsett, St. Francis, and Woodruff; Columbia; and Bradley. Two large depressions, centered in Jefferson and Union Counties, are the result of large withdrawals for industrial, irrigation, or public supply. The depression centered in Jefferson County has expanded in recent years into Arkansas and Prairie Counties as a result of large withdrawals for irrigation and public supply. The lowest water-level altitude measured in this depression is approximately 20 feet (ft) higher in 2011 than in 2009. The area enclosed within the 40-ft contour on the 2011 potentiometric-surface map has decreased in area, shifting north in Lincoln County and west in Arkansas County when compared with the 2009 potentiometric-surface map.
The depression in Union County is roughly circular within the -60-ft contour. The lowest water-level altitude measurement was 157 ft below NGVD 29 in 2009, with a 37-ft rise to 120 ft below NGVD 29 in 2011. The depression in Union County has diminished and encloses a smaller area than in recent years. In 1993, the -60-ft contour enclosed 632 square miles (mi2). In 2011, the -60-ft contour enclosed 375 mi2, a decrease of 41 percent from 1993. The lowest water-level altitude measurement during 2011 in the center of the depression in Union County represents a rise of 79 ft since 2003. The area enclosed by the lowest altitude contour, 120 ft below NGVD 29, on the 2011 potentiometric-surface map is less than 10 percent of the area enclosed by that same contour on the 2009 potentiometric-surface map.
A broad depression in western Poinsett and Cross Counties was first shown in the 1995 potentiometric-surface map. In 2011, the lowest water-level altitude measurement in this depression, 129 ft above NGVD 29, is 2 ft lower than in 2009. The 140-ft contour has extended southwest into northwestern St. Francis and east-central Woodruff Counties in 2011. In Columbia County in 2011, the area of the depression has decreased, with water levels rising about 1 ft since 2005 in the well with the lowest water-level altitude measurement. The depression in Bradley County in 2011 has decreased in area compared to 2007.
A water-level difference map was constructed using the difference between water-level measurements made during 2007 and 2011 at 247 wells. The differences in water level between 2007 and 2011 ranged from -17.3 to 45.4 ft, with a mean of 4.1 ft. Water levels generally declined in the northern half of the study area and generally increased in the southern half of the study area. Areas with a general decline in water levels include Lonoke and western Prairie Counties; northern Arkansas County; Miller County; and Craighead, Poinsett, Cross, and Woodruff Counties. Areas with a general rise in water levels include Lafayette, Columbia, Union, Calhoun, and Bradley Counties; Grant, Jefferson, southern Arkansas, Lincoln, Drew, and Desha Counties; and Phillips County.
Hydrographs from 183 wells with a minimum of 25 years of water-level measurements were constructed. During the period 1987–2011, county mean annual water levels generally declined. Mean annual declines were between 0.5 foot per year (ft/yr) and 0.0 ft/yr in Ashley, Chicot, Crittenden, Drew, Grant, Jefferson, Lafayette, Mississippi, Monroe, Ouachita, Phillips, Pulaski, St. Francis, and Woodruff Counties. Mean annual declines were between 1.0 ft/yr and 0.5 ft/yr in Bradley, Calhoun, Cleveland, Craighead, Cross, Desha, Lonoke, Miller, Poinsett, and Prairie Counties. Mean annual declines were between 1.5 ft/yr and 1.0 ft/yr in Arkansas, Lee, and Lincoln Counties. The county mean annual water level rose in Columbia, Dallas, and Union Counties about 0.3 ft/yr, 0.1 ft/yr, and 1.2 ft/yr, respectively.
Water samples were collected in the summer of 2011 from 61 wells completed in the Sparta-Memphis aquifer and measured onsite for specific conductance, temperature, and pH. Although there is a regional increase in specific conductance to the east and south, anomalous increases occur in some parts of the study area. Specific conductance ranged from 35 microsiemens per centimeter (μS/cm) in Ouachita County to 1,380 μS/cm in Monroe County. Relatively large specific conductance values (greater than 700 mS/cm) occur in samples from wells in Arkansas, Ashley, Clay, Monroe, Phillips, and Union Counties.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145044","collaboration":"Prepared in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey","usgsCitation":"Schrader, T., 2014, Water levels and water quality in the Sparta-Memphis aquifer (middle Claiborne aquifer) in Arkansas, spring-summer 2011: U.S. Geological Survey Scientific Investigations Report 2014-5044, Report: iv, 44 p.; 2 Plates: 14.99 x 18.98 inches and 14.99 x 19.01 inches, https://doi.org/10.3133/sir20145044.","productDescription":"Report: iv, 44 p.; 2 Plates: 14.99 x 18.98 inches and 14.99 x 19.01 inches","numberOfPages":"51","additionalOnlineFiles":"Y","ipdsId":"IP-051795","costCenters":[{"id":129,"text":"Arkansas Water Science 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Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Physiological and ecological effects of increasing temperature on fish production in lakes of Arctic Alaska","docAbstract":"Lake ecosystems in the Arctic are changing rapidly due to climate warming. Lakes are sensitive integrators of climate-induced changes and prominent features across the Arctic landscape, especially in lowland permafrost regions such as the Arctic Coastal Plain of Alaska. Despite many studies on the implications of climate warming, how fish populations will respond to lake changes is uncertain for Arctic ecosystems. Least Cisco (Coregonus sardinella) is a bellwether for Arctic lakes as an important consumer and prey resource. To explore the consequences of climate warming, we used a bioenergetics model to simulate changes in Least Cisco production under future climate scenarios for lakes on the Arctic Coastal Plain. First, we used current temperatures to fit Least Cisco consumption to observed annual growth. We then estimated growth, holding food availability, and then feeding rate constant, for future projections of temperature. Projected warmer water temperatures resulted in reduced Least Cisco production, especially for larger size classes, when food availability was held constant. While holding feeding rate constant, production of Least Cisco increased under all future scenarios with progressively more growth in warmer temperatures. Higher variability occurred with longer projections of time mirroring the expanding uncertainty in climate predictions further into the future. In addition to direct temperature effects on Least Cisco growth, we also considered changes in lake ice phenology and prey resources for Least Cisco. A shorter period of ice cover resulted in increased production, similar to warming temperatures. Altering prey quality had a larger effect on fish production in summer than winter and increased relative growth of younger rather than older age classes of Least Cisco. Overall, we predicted increased production of Least Cisco due to climate warming in lakes of Arctic Alaska. Understanding the implications of increased production of Least Cisco to the entire food web will be necessary to predict ecosystem responses in lakes of the Arctic.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology and Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley Online Library","doi":"10.1002/ece3.1080","usgsCitation":"Carey, M.P., and Zimmerman, C.E., 2014, Physiological and ecological effects of increasing temperature on fish production in lakes of Arctic Alaska: Ecology and Evolution, v. 4, no. 10, p. 1981-1993, https://doi.org/10.1002/ece3.1080.","productDescription":"13 p.","startPage":"1981","endPage":"1993","ipdsId":"IP-053143","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":472990,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1080","text":"Publisher Index Page"},{"id":287839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287838,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/ece3.1080"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic Coastal Plain","volume":"4","issue":"10","noUsgsAuthors":false,"publicationDate":"2014-04-22","publicationStatus":"PW","scienceBaseUri":"5388570ae4b0318b93124aed","contributors":{"authors":[{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":491459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":491458,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70058501,"text":"sir20105090L - 2014 - Porphyry copper assessment of eastern Australia","interactions":[{"subject":{"id":70058501,"text":"sir20105090L - 2014 - Porphyry copper assessment of eastern Australia","indexId":"sir20105090L","publicationYear":"2014","noYear":false,"chapter":"L","title":"Porphyry copper assessment of eastern Australia"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2022-12-09T20:56:23.37247","indexId":"sir20105090L","displayToPublicDate":"2014-05-15T12:44:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5090","chapter":"L","title":"Porphyry copper assessment of eastern Australia","docAbstract":"The U.S. Geological Survey (USGS) conducts national and global assessments of resources (mineral, energy, water, and biologic) to provide science in support of decision making. Mineral resource assessments provide syntheses of available information about where mineral deposits are known and suspected to occur in the Earth’s crust and which commodities may be present, together with estimates of amounts of resources that may be present in undiscovered deposits. The USGS collaborated with geologists of the Geological Survey of New South Wales and Geoscience Australia (formerly the Australian Geological Survey Organisation) on an assessment of Phanerozoic-age porphyry copper resources in Australia. Porphyry copper deposits contain about 11 percent of the identified copper resources in Australia. This study addresses resources of known porphyry copper deposits and expected resources of undiscovered porphyry copper deposits in eastern Australia.
\nA three-part form of assessment was used for estimation of undiscovered resources. Using this method, four tracts were delineated that are permissive for porphyry copper deposits. A probabilistic estimate of the expected number of deposits in each tract was prepared on the basis of existing information about geology, geochemistry, geophysics, exploration history, and mineral occurrences. Monte Carlo simulation was used to combine the estimated number of deposits with an appropriate model of grade and tonnage for porphyry copper deposits to provide a probabilistic estimate of metal content and total tonnage for undiscovered deposits.
\nThe Delamerian permissive tract comprises igneous rocks of Cambrian age in the Delamerian Orogen, which borders the western margin of the Tasmanides. The Delamerian tract contains no known porphyry copper deposits, but the Adelaide sub-tract, one of three sub-tracts that compose the Delamerian tract, contains four porphyry copper prospects. The Adelaide sub-tract is estimated to contain 2.5±2.2 undiscovered deposits in an area of about 50,700 square kilometers.
\nThe Macquarie permissive tract comprises volcanic, volcaniclastic, and minor exposed intrusive igneous rocks of the Macquarie Arc. The nine known deposits in this tract are now estimated to contain a total of about 13.5 million metric tons of copper and 1,700 metric tons of gold. This tract is estimated to contain 6.9±3.5 undiscovered deposits for a total of about 16 deposits in an area of about 41,500 square kilometers.
\nThe Yeoval permissive tract includes subequal areas of permissive volcanic and intrusive rocks of Silurian to Devonian age exposed in and around the Cowra-Buchan Rift System, which overlaps the previously accreted Macquarie Arc. The Yeoval tract contains one porphyry copper deposit and several porphyry copper prospects. This tract is estimated to contain 1.3±0.75 undiscovered porphyry copper deposits, for a total of about 2 expected deposits in an area of about 53,200 square kilometers.
\nThe East Tasmanide permissive tract includes a semi-continuous belt of plutonic and subordinate volcanic rocks along the eastern margins of Queensland and northeastern New South Wales. The East Tasmanide tract contains 14 known porphyry copper deposits and many porphyry copper prospects, which are all in the Central sub-tract. This sub-tract is expected to contain 4.8±3.3 undiscovered porphyry copper deposits, for a total of about 19 deposits in an area of about 291,000 square kilometers.
\nThis assessment estimates that 15 undiscovered deposits contain an arithmetic mean of ~21 million metric tons or more of copper in four tracts, in addition to the 24 known porphyry copper deposits that contain identified resources of ~16 million metric tons of copper. In addition to copper, the mean expected amount of undiscovered byproduct gold predicted by the simulation is ~1,500 metric tons. The probability associated with these arithmetic means is on the order of 30 percent. Median expected amounts of metals predicted by the simulations may be ~50 percent lower than mean estimates.
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Jr. grobinso@usgs.gov","contributorId":3083,"corporation":false,"usgs":true,"family":"Robinson","given":"Gilpin","suffix":"Jr.","email":"grobinso@usgs.gov","middleInitial":"R.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":487133,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zientek, Michael L. 0000-0002-8522-9626 mzientek@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":2420,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael","email":"mzientek@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":487132,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":487129,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jaireth, Subhash","contributorId":7190,"corporation":false,"usgs":true,"family":"Jaireth","given":"Subhash","email":"","affiliations":[],"preferred":false,"id":487134,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cossette, Pamela M. 0000-0002-9608-6595 pcossette@usgs.gov","orcid":"https://orcid.org/0000-0002-9608-6595","contributorId":1458,"corporation":false,"usgs":true,"family":"Cossette","given":"Pamela","email":"pcossette@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":487130,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wallis, John C.","contributorId":45755,"corporation":false,"usgs":true,"family":"Wallis","given":"John C.","affiliations":[],"preferred":false,"id":487136,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70129259,"text":"70129259 - 2014 - Hydrological controls on methylmercury distribution and flux in a tidal marsh","interactions":[],"lastModifiedDate":"2014-10-21T10:38:51","indexId":"70129259","displayToPublicDate":"2014-05-14T10:35:35","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Hydrological controls on methylmercury distribution and flux in a tidal marsh","docAbstract":"The San Francisco Estuary, California, contains mercury (Hg) contamination originating from historical regional gold and Hg mining operations. We measured hydrological and geochemical variables in a tidal marsh of the Palo Alto Baylands Nature Preserve to determine the sources, location, and magnitude of hydrological fluxes of methylmercury (MeHg), a bioavailable Hg species of ecological and health concern. Based on measured concentrations and detailed finite-element simulation of coupled surface water and saturated-unsaturated groundwater flow, we found pore water MeHg was concentrated in unsaturated pockets that persisted over tidal cycles. These pockets, occurring over 16% of the marsh plain area, corresponded to the marsh root zone. Groundwater discharge (e.g., exfiltration) to the tidal channel represented a significant source of MeHg during low tide. We found that nonchannelized flow accounted for up to 20% of the MeHg flux to the estuary. The estimated net flux of filter-passing (0.45 μm) MeHg toward estuary was 10 ± 5 ng m–2 day–1 during a single 12-h tidal cycle, suggesting an annual MeHg load of 1.17 ± 0.58 kg when the estimated flux was applied to present tidal marshes and planned marsh restorations throughout the San Francisco Estuary.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Chemical Society","publisherLocation":"Easton, PA","doi":"10.1021/es500781g","usgsCitation":"Zhang, H., Moffett, K.B., Windham-Myers, L., and Gorelick, S.M., 2014, Hydrological controls on methylmercury distribution and flux in a tidal marsh: Environmental Science & Technology, v. 48, no. 12, p. 6795-6804, https://doi.org/10.1021/es500781g.","productDescription":"10 p.","startPage":"6795","endPage":"6804","numberOfPages":"10","ipdsId":"IP-057049","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":295535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295494,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es500781g"},{"id":295495,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.acs.org/doi/abs/10.1021/es500781g"}],"volume":"48","issue":"12","noUsgsAuthors":false,"publicationDate":"2014-05-28","publicationStatus":"PW","scienceBaseUri":"544775b2e4b0f888a81b8325","contributors":{"authors":[{"text":"Zhang, Hua","contributorId":28916,"corporation":false,"usgs":true,"family":"Zhang","given":"Hua","email":"","affiliations":[],"preferred":false,"id":503589,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moffett, Kevan B.","contributorId":11976,"corporation":false,"usgs":true,"family":"Moffett","given":"Kevan","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":503588,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":503586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gorelick, Steven M.","contributorId":8784,"corporation":false,"usgs":true,"family":"Gorelick","given":"Steven","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":503587,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70077617,"text":"sir20145023 - 2014 - Status and understanding of groundwater quality in the South Coast Interior groundwater basins, 2008: California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2014-05-14T10:24:01","indexId":"sir20145023","displayToPublicDate":"2014-05-14T10:07:28","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5023","title":"Status and understanding of groundwater quality in the South Coast Interior groundwater basins, 2008: California GAMA Priority Basin Project","docAbstract":"Groundwater quality in the approximately 653-square-mile (1,691-square-kilometer) South Coast Interior Basins (SCI) study unit was investigated as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The South Coast Interior Basins study unit contains eight priority groundwater basins grouped into three study areas, Livermore, Gilroy, and Cuyama, in the Southern Coast Ranges hydrogeologic province. The GAMA Priority Basin Project is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey (USGS) and the Lawrence Livermore National Laboratory.
\n\nThe GAMA South Coast Interior Basins study was designed to provide a spatially unbiased assessment of untreated (raw) groundwater quality within the primary aquifer system, as well as a statistically consistent basis for comparing water quality between basins. The assessment was based on water-quality and ancillary data collected by the USGS from 50 wells in 2008 and on water-quality data from the California Department of Public Health (CDPH) database. The primary aquifer system was defined by the depth intervals of the wells listed in the CDPH database for the SCI study unit. The quality of groundwater in the primary aquifer system may be different from that in the shallower or deeper water-bearing zones; shallow groundwater may be more vulnerable to surficial contamination.
\n\nThe first component of this study, the status of the current quality of the groundwater resource, was assessed by using data from samples analyzed for volatile organic compounds (VOCs), pesticides, and naturally occurring inorganic constituents, such as trace elements and minor ions. This status assessment is intended to characterize the quality of groundwater resources within the primary aquifer system of the SCI study unit, not the treated drinking water delivered to consumers by water purveyors.
\n\nRelative-concentrations (sample concentration divided by the health- or aesthetic-based benchmark concentration) were used for evaluating groundwater quality for those constituents that have Federal or California regulatory or non-regulatory benchmarks for drinking-water quality. A relative-concentration greater than 1.0 indicates a concentration greater than a benchmark, and a relative-concentration less than or equal to 1.0 indicates a concentration equal to or less than a benchmark. Relative-concentrations of organic constituents and special-interest constituents were classified as “high” (relative-concentration greater than 1.0), “moderate” (relative-concentration greater than 0.1 and less than or equal to 1.0), or “low” (relative-concentration less than or equal to 0.1). Relative-concentrations of inorganic constituents were classified as “high” (relative-concentration greater than 1.0), “moderate” (relative-concentration greater than 0.5 and less than or equal to 1.0), or “low” (relative-concentration less than or equal to 0.5).
\n\nAquifer-scale proportion was used as the primary metric in the status assessment for evaluating regional-scale groundwater quality. High aquifer-scale proportion is defined as the percentage of the area of the primary aquifer system with a relative-concentration greater than 1.0 for a particular constituent or class of constituents; percentage is based on an areal rather than a volumetric basis. Moderate and low aquifer-scale proportions were defined as the areal percentage of the primary aquifer system with moderate and low relative-concentrations, respectively. Two statistical approaches—grid-based and spatially weighted—were used to evaluate aquifer-scale proportions for individual constituents and classes of constituents. Grid-based and spatially weighted estimates were comparable in the SCI study unit (within 90-percent confidence intervals).
\n\nInorganic constituents (one or more) with health-based benchmarks were detected at high relative-concentrations in 29 percent of the primary aquifer system, at moderate relative-concentrations in 37 percent, and at low relative-concentrations in 34 percent. High aquifer-scale proportions of inorganic constituents primarily reflected high aquifer-scale proportions of nitrate (14 percent), boron (8.6 percent), molybdenum (8.6 percent), and arsenic (5.7 percent). In contrast, the relative-concentrations of organic constituents (one or more) were high in 1.6 percent, moderate in 2.0 percent, and low or not detected in 96 percent of the primary aquifer system. Of the 207 organic and special-interest constituents analyzed for, 15 constituents were detected. Perchlorate was found at moderate relative-concentrations in 34 percent of the aquifer. Two organic constituents were frequently detected (in greater than 10 percent of samples): the trihalomethane chloroform and the herbicide simazine.
\n\nThe second component of this study, the understanding assessment, identified natural and human factors that may have affected groundwater quality by evaluating land use, physical characteristics of the wells, and geochemical conditions of the aquifer. This evaluation was done by using statistical tests of correlations between these potential explanatory factors and water-quality data. Concentrations of arsenic, molybdenum, and manganese were generally greater in anoxic and pre-modern groundwater than other groundwater. In contrast, concentrations of nitrate and perchlorate were significantly higher in oxic and modern groundwater. Concentrations of simazine were greater in modern than pre-modern groundwater. Chloroform detections were positively correlated with greater urban land use. Boron concentrations and chloroform detections were higher in the Livermore study area than in the other study areas of the SCI; total dissolved solids and sulfate concentrations were greater in the Cuyama study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145023","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program; Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Parsons, M.C., Kulongoski, J., and Belitz, K., 2014, Status and understanding of groundwater quality in the South Coast Interior groundwater basins, 2008: California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2014-5023, Report: x, 68 p.; Related Report, https://doi.org/10.3133/sir20145023.","productDescription":"Report: x, 68 p.; Related Report","numberOfPages":"82","additionalOnlineFiles":"Y","ipdsId":"IP-026177","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":287116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145023.jpg"},{"id":287112,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5023/"},{"id":287115,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/fs/2013/3088/"},{"id":287114,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5023/pdf/sir2014-5023.pdf"}],"projection":"Albers Equal Area Conic Projection","country":"United States","state":"California","otherGeospatial":"South Coast Interior Basins","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.01611111111111111,8.333333333333334E-4 ], [ -0.01611111111111111,0.0011111111111111111 ], [ -0.01638888888888889,0.0011111111111111111 ], [ -0.01638888888888889,8.333333333333334E-4 ], [ -0.01611111111111111,8.333333333333334E-4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53748252e4b0870f4d23cf94","contributors":{"authors":[{"text":"Parsons, Mary C. mparsons@usgs.gov","contributorId":1571,"corporation":false,"usgs":true,"family":"Parsons","given":"Mary","email":"mparsons@usgs.gov","middleInitial":"C.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":489938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":94750,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin T.","affiliations":[],"preferred":false,"id":489939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":489937,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70055689,"text":"fs20133088 - 2014 - Groundwater quality in the South Coast Interior Basins, California","interactions":[],"lastModifiedDate":"2014-09-08T10:42:46","indexId":"fs20133088","displayToPublicDate":"2014-05-14T09:46:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3088","title":"Groundwater quality in the South Coast Interior Basins, California","docAbstract":"Groundwater provides more than 40 percent of California’s drinking water. To protect this vital resource, the State of California created the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The Priority Basin Project of the GAMA Program provides a comprehensive assessment of the State’s untreated groundwater quality and increases public access to groundwater-quality information. The South Coast Interior Basins constitute one of the study units being evaluated.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133088","collaboration":"U.S. Geological Survey and the California State Water Resources Control Board","usgsCitation":"Parsons, M.C., and Belitz, K., 2014, Groundwater quality in the South Coast Interior Basins, California: U.S. Geological Survey Fact Sheet 2013-3088, Report: 4 p.; Related Report, https://doi.org/10.3133/fs20133088.","productDescription":"Report: 4 p.; Related Report","onlineOnly":"Y","ipdsId":"IP-038726","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":287107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133088.PNG"},{"id":287104,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3088/"},{"id":287105,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3088/pdf/fs2013-3088.pdf"},{"id":287106,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/sir/2014/5023"}],"country":"United States","state":"California","otherGeospatial":"South Coast Interior Basins","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.01611111111111111,8.333333333333334E-4 ], [ -0.01611111111111111,8.333333333333334E-4 ], [ -0.01638888888888889,8.333333333333334E-4 ], [ -0.01638888888888889,8.333333333333334E-4 ], [ -0.01611111111111111,8.333333333333334E-4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53748250e4b0870f4d23cf8f","contributors":{"authors":[{"text":"Parsons, Mary C. mparsons@usgs.gov","contributorId":1571,"corporation":false,"usgs":true,"family":"Parsons","given":"Mary","email":"mparsons@usgs.gov","middleInitial":"C.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486209,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70104300,"text":"70104300 - 2014 - Adaptive nest clustering and density-dependent nest survival in dabbling ducks","interactions":[],"lastModifiedDate":"2017-07-01T17:17:04","indexId":"70104300","displayToPublicDate":"2014-05-13T12:39:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2939,"text":"Oikos","active":true,"publicationSubtype":{"id":10}},"title":"Adaptive nest clustering and density-dependent nest survival in dabbling ducks","docAbstract":"Density-dependent population regulation is observed in many taxa, and understanding the mechanisms that generate density dependence is especially important for the conservation of heavily-managed species. In one such system, North American waterfowl, density dependence is often observed at continental scales, and nest predation has long been implicated as a key factor driving this pattern. However, despite extensive research on this topic, it remains unclear if and how nest density influences predation rates. Part of this confusion may have arisen because previous studies have studied density-dependent predation at relatively large spatial and temporal scales. Because the spatial distribution of nests changes throughout the season, which potentially influences predator behavior, nest survival may vary through time at relatively small spatial scales. As such, density-dependent nest predation might be more detectable at a spatially- and temporally-refined scale and this may provide new insights into nest site selection and predator foraging behavior. Here, we used three years of data on nest survival of two species of waterfowl, mallards and gadwall, to more fully explore the relationship between local nest clustering and nest survival. Throughout the season, we found that the distribution of nests was consistently clustered at small spatial scales (˜50–400 m), especially for mallard nests, and that this pattern was robust to yearly variation in nest density and the intensity of predation. We demonstrated further that local nest clustering had positive fitness consequences – nests with closer nearest neighbors were more likely to be successful, a result that is counter to the general assumption that nest predation rates increase with nest density.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Oikos","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ejnar Munksgaard","publisherLocation":"Copenhagen","doi":"10.1111/j.1600-0706.2013.00851.x","usgsCitation":"Ringelman, K.M., Eadie, J.M., and Ackerman, J., 2014, Adaptive nest clustering and density-dependent nest survival in dabbling ducks: Oikos, v. 123, no. 2, p. 239-247, https://doi.org/10.1111/j.1600-0706.2013.00851.x.","productDescription":"9 p.","startPage":"239","endPage":"247","numberOfPages":"9","ipdsId":"IP-046158","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":287088,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287087,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1600-0706.2013.00851.x"}],"country":"United States","state":"California","otherGeospatial":"Grizzly Island Wildlife Area;Suisun Marsh","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.121727,38.06149 ], [ -122.121727,38.155651 ], [ -121.885049,38.155651 ], [ -121.885049,38.06149 ], [ -122.121727,38.06149 ] ] ] } } ] }","volume":"123","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"537330d0e4b04970612788a4","contributors":{"authors":[{"text":"Ringelman, Kevin M.","contributorId":95806,"corporation":false,"usgs":true,"family":"Ringelman","given":"Kevin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":493703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eadie, John M.","contributorId":65219,"corporation":false,"usgs":false,"family":"Eadie","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":493702,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":493704,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70095522,"text":"tm6A50 - 2014 - Two graphical user interfaces for managing and analyzing MODFLOW groundwater-model scenarios","interactions":[],"lastModifiedDate":"2014-05-13T11:56:05","indexId":"tm6A50","displayToPublicDate":"2014-05-13T11:52:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A50","title":"Two graphical user interfaces for managing and analyzing MODFLOW groundwater-model scenarios","docAbstract":"Scenario Manager and Scenario Analyzer are graphical user interfaces that facilitate the use of calibrated, MODFLOW-based groundwater models for investigating possible responses to proposed stresses on a groundwater system. Scenario Manager allows a user, starting with a calibrated model, to design and run model scenarios by adding or modifying stresses simulated by the model. Scenario Analyzer facilitates the process of extracting data from model output and preparing such display elements as maps, charts, and tables. Both programs are designed for users who are familiar with the science on which groundwater modeling is based but who may not have a groundwater modeler’s expertise in building and calibrating a groundwater model from start to finish.
\nWith Scenario Manager, the user can manipulate model input to simulate withdrawal or injection wells, time-variant specified hydraulic heads, recharge, and such surface-water features as rivers and canals. Input for stresses to be simulated comes from user-provided geographic information system files and time-series data files. A Scenario Manager project can contain multiple scenarios and is self-documenting.
\nScenario Analyzer can be used to analyze output from any MODFLOW-based model; it is not limited to use with scenarios generated by Scenario Manager. Model-simulated values of hydraulic head, drawdown, solute concentration, and cell-by-cell flow rates can be presented in display elements. Map data can be represented as lines of equal value (contours) or as a gradated color fill. Charts and tables display time-series data obtained from output generated by a transient-state model run or from user-provided text files of time-series data. A display element can be based entirely on output of a single model run, or, to facilitate comparison of results of multiple scenarios, an element can be based on output from multiple model runs. Scenario Analyzer can export display elements and supporting metadata as a Portable Document Format file.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Groundwater in Book 6 Modeling Techniques","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A50","collaboration":"Prepared in cooperation with Miami-Dade County Water and Sewer Department. This report is Chapter 50 of Section A: Groundwater in Book 6 Modeling Techniques.","usgsCitation":"Banta, E., 2014, Two graphical user interfaces for managing and analyzing MODFLOW groundwater-model scenarios: U.S. Geological Survey Techniques and Methods 6-A50, Report: v, 38 p.; Software Download, https://doi.org/10.3133/tm6A50.","productDescription":"Report: v, 38 p.; Software Download","numberOfPages":"47","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049500","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":287086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm6A50.jpg"},{"id":287084,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/6a50/pdf/tm6a50.pdf"},{"id":287085,"type":{"id":7,"text":"Companion Files"},"url":"https://water.usgs.gov/software/ScenarioTools/"},{"id":287083,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/6a50/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"537330d5e4b04970612788c2","contributors":{"authors":[{"text":"Banta, Edward R.","contributorId":49820,"corporation":false,"usgs":true,"family":"Banta","given":"Edward R.","affiliations":[],"preferred":false,"id":491226,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70093712,"text":"sir20145025 - 2014 - Origins and delineation of saltwater intrusion in the Biscayne aquifer and changes in the distribution of saltwater in Miami-Dade County, Florida","interactions":[],"lastModifiedDate":"2014-05-13T10:58:13","indexId":"sir20145025","displayToPublicDate":"2014-05-13T10:50:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5025","title":"Origins and delineation of saltwater intrusion in the Biscayne aquifer and changes in the distribution of saltwater in Miami-Dade County, Florida","docAbstract":"Intrusion of saltwater into parts of the shallow karst Biscayne aquifer is a major concern for the 2.5 million residents of Miami-Dade County that rely on this aquifer as their primary drinking water supply. Saltwater intrusion of this aquifer began when the Everglades were drained to provide dry land for urban development and agriculture. The reduction in water levels caused by this drainage, combined with periodic droughts, allowed saltwater to flow inland along the base of the aquifer and to seep directly into the aquifer from the canals. The approximate inland extent of saltwater was last mapped in 1995.
\nAn examination of the inland extent of saltwater and the sources of saltwater in the aquifer was completed during 2008–2011 by using (1) all available salinity information, (2) time-series electromagnetic induction log datasets from 35 wells, (3) time-domain electromagnetic soundings collected at 79 locations, (4) a helicopter electromagnetic survey done during 2001 that was processed, calibrated, and published during the study, (5) cores and geophysical logs collected from 8 sites for stratigraphic analysis, (6) 8 new water-quality monitoring wells, and (7) analyses of 69 geochemical samples.
\nThe results of the study indicate that as of 2011 approximately 1,200 square kilometers (km2) of the mainland part of the Biscayne aquifer were intruded by saltwater. The saltwater front was mapped farther inland than it was in 1995 in eight areas totaling about 24.1 km2. In many of these areas, analyses indicated that saltwater had encroached along the base of the aquifer. The saltwater front was mapped closer to the coast than it was in 1995 in four areas totaling approximately 6.2 km2. The changes in the mapped extent of saltwater resulted from improved spatial information, actual movement of the saltwater front, or a combination of both.
\nSalinity monitoring in some of the canals in Miami-Dade County between 1988 and 2010 indicated influxes of saltwater, with maximum salinities ranging from 1.4 to 32 practical salinity units (PSU) upstream of the salinity control structures. Time-series electromagnetic induction log data from monitoring wells G–3601, G–3608, and G–3701, located adjacent to the Biscayne, Snapper Creek, and Black Creek Canals, respectively, and upstream of the salinity control structures, indicated shallow influxes of conductive water in the aquifer that likely resulted from leakage of brackish water or saltwater from these canals. The determination that saltwater influxes were recent is supported by the similarity in the oxygen and hydrogen stable isotope composition in samples from the Snapper Creek Canal, 1.6 kilometers (km) inland of a salinity control structure, and in samples from well G–3608, which is adjacent to the canal, as well as by the relative ages of the water sampled from well G–3608 and other wells open to the aquifer below the saltwater interface. Historical and recent salinity information from the Card Sound Road Canal, monitoring well FKS8 located adjacent to the canal, and the 2001 helicopter electromagnetic survey indicated that saltwater may occasionally leak from this canal as far inland as 15 km. This leakage may be prevented or reduced by a salinity control structure that was installed in May 2010. Saltwater also may have leaked from the Princeton Canal.
\nResults of geochemical sampling and analysis indicate a close correspondence between droughts and saltwater intrusion. Tritium/helium-3 apparent (piston-flow) ages determined from samples of saltwater with chloride concentrations of about 1,000 milligrams per liter (mg/L) or greater generally corresponded to a period during which droughts were frequent. Comparison of average daily air temperatures in Miami, Florida, with estimates of recharge temperatures determined from the dissolved gas composition in water samples indicated that saltwater likely entered the aquifer in April or early May when water levels are typically at their lowest during the year. Conversely, most of the samples of freshwater with chloride concentrations less than about 1,000 mg/L indicate recharge temperatures corresponding to air temperatures in mid to late May when rainfall and water levels in the aquifer increase, and the piston-flow ages of these samples correspond to wet years. The piston-flow ages of freshwater samples generally were younger than ages of samples of saltwater.
\nSaltwater samples that were depleted in boron, magnesium, potassium, sodium, and sulfate, and enriched in calcium relative to the concentrations theoretically produced by freshwater/seawater mixing, generally were found to be associated with areas where saltwater had recently intruded. The calcium to (bicarbonate + sulfate) molar ratios (Ca/(HCO3+SO4)) of these samples generally were greater than 1. Saltwater samples from some of the monitoring wells, however, indicated little or no enrichment or depletion of these ions relative to the theoretical freshwater/seawater mixing line, and the Ca/(HCO3+SO4) molar ratios of these samples generally were less than 1. Results indicated that aquifer materials are approaching equilibrium with seawater at these well locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145025","issn":"2328-0328","collaboration":"Prepared in cooperation with Miami-Dade County","usgsCitation":"Prinos, S.T., Wacker, M.A., Cunningham, K.J., and Fitterman, D.V., 2014, Origins and delineation of saltwater intrusion in the Biscayne aquifer and changes in the distribution of saltwater in Miami-Dade County, Florida: U.S. Geological Survey Scientific Investigations Report 2014-5025, Report: xi, 101 p.; Appendix 1-12: XLS and PDFs; Downloads, https://doi.org/10.3133/sir20145025.","productDescription":"Report: xi, 101 p.; Appendix 1-12: XLS and PDFs; Downloads","numberOfPages":"116","onlineOnly":"Y","ipdsId":"IP-044160","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":287078,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145025.jpg"},{"id":287074,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5025/"},{"id":287075,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5025/pdf/sir2014-5025.pdf"},{"id":287076,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5025/appendix/"},{"id":287077,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5025/downloads/"}],"country":"United States","state":"Florida","county":"Broward County;Miami-dade County","otherGeospatial":"Biscayne Aquifer","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.5,25.333333 ], [ -80.5,26.0 ], [ -80.166667,26.0 ], [ -80.166667,25.333333 ], [ -80.5,25.333333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"537330d4e4b04970612788bd","contributors":{"authors":[{"text":"Prinos, Scott T. 0000-0002-5776-8956 stprinos@usgs.gov","orcid":"https://orcid.org/0000-0002-5776-8956","contributorId":4045,"corporation":false,"usgs":true,"family":"Prinos","given":"Scott","email":"stprinos@usgs.gov","middleInitial":"T.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wacker, Michael A. mwacker@usgs.gov","contributorId":2162,"corporation":false,"usgs":true,"family":"Wacker","given":"Michael","email":"mwacker@usgs.gov","middleInitial":"A.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":490159,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cunningham, Kevin J. 0000-0002-2179-8686 kcunning@usgs.gov","orcid":"https://orcid.org/0000-0002-2179-8686","contributorId":1689,"corporation":false,"usgs":true,"family":"Cunningham","given":"Kevin","email":"kcunning@usgs.gov","middleInitial":"J.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":490158,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fitterman, David V. dfitterman@usgs.gov","contributorId":1106,"corporation":false,"usgs":true,"family":"Fitterman","given":"David","email":"dfitterman@usgs.gov","middleInitial":"V.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":490157,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70104213,"text":"70104213 - 2014 - Evaluation of sensor types and environmental controls on mapping biomass of coastal marsh emergent vegetation","interactions":[],"lastModifiedDate":"2014-05-13T10:37:49","indexId":"70104213","displayToPublicDate":"2014-05-13T10:30:00","publicationYear":"2014","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":"Evaluation of sensor types and environmental controls on mapping biomass of coastal marsh emergent vegetation","docAbstract":"There is a need to quantify large-scale plant productivity in coastal marshes to understand marsh resilience to sea level rise, to help define eligibility for carbon offset credits, and to monitor impacts from land use, eutrophication and contamination. Remote monitoring of aboveground biomass of emergent wetland vegetation will help address this need. Differences in sensor spatial resolution, bandwidth, temporal frequency and cost constrain the accuracy of biomass maps produced for management applications. In addition the use of vegetation indices to map biomass may not be effective in wetlands due to confounding effects of water inundation on spectral reflectance. To address these challenges, we used partial least squares regression to select optimal spectral features in situ and with satellite reflectance data to develop predictive models of aboveground biomass for common emergent freshwater marsh species, Typha spp. and Schoenoplectus acutus, at two restored marshes in the Sacramento–San Joaquin River Delta, California, USA. We used field spectrometer data to test model errors associated with hyperspectral narrowbands and multispectral broadbands, the influence of water inundation on prediction accuracy, and the ability to develop species specific models. We used Hyperion data, Digital Globe World View-2 (WV-2) data, and Landsat 7 data to scale up the best statistical models of biomass. Field spectrometer-based models of the full dataset showed that narrowband reflectance data predicted biomass somewhat, though not significantly better than broadband reflectance data [R2 = 0.46 and percent normalized RMSE (%RMSE) = 16% for narrowband models]. However hyperspectral first derivative reflectance spectra best predicted biomass for plots where water levels were less than 15 cm (R2 = 0.69, %RMSE = 12.6%). In species-specific models, error rates differed by species (Typha spp.: %RMSE = 18.5%; S. acutus: %RMSE = 24.9%), likely due to the more vertical structure and deeper water habitat of S. acutus. The Landsat 7 dataset (7 images) predicted biomass slightly better than the WV-2 dataset (6 images) (R2 = 0.56, %RMSE = 20.9%, compared to R2 = 0.45, RMSE = 21.5%). The Hyperion dataset (one image) was least successful in predicting biomass (R2 = 0.27, %RMSE = 33.5%). Shortwave infrared bands on 30 m-resolution Hyperion and Landsat 7 sensors aided biomass estimation; however managers need to weigh tradeoffs between cost, additional spectral information, and high spatial resolution that will identify variability in small, fragmented marshes common to the Sacramento–San Joaquin River Delta and elsewhere in the Western U.S.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2014.04.003","usgsCitation":"Byrd, K.B., O'Connell, J., Di Tommaso, S., and Kelly, M., 2014, Evaluation of sensor types and environmental controls on mapping biomass of coastal marsh emergent vegetation: Remote Sensing of Environment, v. 149, p. 166-180, https://doi.org/10.1016/j.rse.2014.04.003.","productDescription":"15 p.","startPage":"166","endPage":"180","numberOfPages":"15","ipdsId":"IP-052200","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":287071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287072,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2014.04.003"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-san Joaquin River Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.7545,37.3797 ], [ -122.7545,38.2715 ], [ -121.2455,38.2715 ], [ -121.2455,37.3797 ], [ -122.7545,37.3797 ] ] ] } } ] }","volume":"149","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"537330d2e4b04970612788ae","chorus":{"doi":"10.1016/j.rse.2014.04.003","url":"http://dx.doi.org/10.1016/j.rse.2014.04.003","publisher":"Elsevier BV","authors":"Byrd Kristin B., O'Connell Jessica L., Di Tommaso Stefania, Kelly Maggi","journalName":"Remote Sensing of Environment","publicationDate":"6/2014"},"contributors":{"authors":[{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":493639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Connell, Jessica L.","contributorId":86265,"corporation":false,"usgs":true,"family":"O'Connell","given":"Jessica L.","affiliations":[],"preferred":false,"id":493642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Di Tommaso, Stefania","contributorId":9965,"corporation":false,"usgs":true,"family":"Di Tommaso","given":"Stefania","email":"","affiliations":[],"preferred":false,"id":493640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelly, Maggi","contributorId":14275,"corporation":false,"usgs":true,"family":"Kelly","given":"Maggi","affiliations":[],"preferred":false,"id":493641,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70104614,"text":"70104614 - 2014 - Land use patterns, ecoregion, and microcystin relationships in U.S. lakes and reservoirs: a preliminary evaluation","interactions":[],"lastModifiedDate":"2018-09-18T16:07:31","indexId":"70104614","displayToPublicDate":"2014-05-13T09:32:30","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1878,"text":"Harmful Algae","active":true,"publicationSubtype":{"id":10}},"title":"Land use patterns, ecoregion, and microcystin relationships in U.S. lakes and reservoirs: a preliminary evaluation","docAbstract":"A statistically significant association was found between the concentration of total microcystin, a common class of cyanotoxins, in surface waters of lakes and reservoirs in the continental U.S. with watershed land use using data from 1156 water bodies sampled between May and October 2007 as part of the USEPA National Lakes Assessment. Nearly two thirds (65.8%) of the samples with microcystin concentrations ≥1.0 μg/L (n = 126) were limited to three nutrient and water quality-based ecoregions (Corn Belt and Northern Great Plains, Mostly Glaciated Dairy Region, South Central Cultivated Great Plains) in watersheds with strong agricultural influence. canonical correlation analysis (CCA) indicated that both microcystin concentrations and cyanobacteria abundance were positively correlated with total nitrogen, dissolved organic carbon, and temperature; correlations with total phosphorus and water clarity were not as strong. This study supports a number of regional lake studies that suggest that land use practices are related to cyanobacteria abundance, and extends the potential impacts of agricultural land use in watersheds to include the production of cyanotoxins in lakes.","language":"English","publisher":"Elsevier","doi":"10.1016/j.hal.2014.03.005","usgsCitation":"Beaver, J.R., Manis, E.E., Loftin, K.A., Graham, J.L., Pollard, A., and Mitchell, R.M., 2014, Land use patterns, ecoregion, and microcystin relationships in U.S. lakes and reservoirs: a preliminary evaluation: Harmful Algae, v. 36, p. 57-62, https://doi.org/10.1016/j.hal.2014.03.005.","productDescription":"6 p.","startPage":"57","endPage":"62","ipdsId":"IP-053193","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":287252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287201,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.hal.2014.03.005"}],"country":"United States","volume":"36","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5377178fe4b02eab8669eda0","contributors":{"authors":[{"text":"Beaver, John R.","contributorId":55345,"corporation":false,"usgs":true,"family":"Beaver","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":493745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manis, Erin E.","contributorId":82226,"corporation":false,"usgs":true,"family":"Manis","given":"Erin","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":493747,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":493743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pollard, Amina I.","contributorId":100749,"corporation":false,"usgs":true,"family":"Pollard","given":"Amina I.","affiliations":[],"preferred":false,"id":493748,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mitchell, Richard M. rwmitchell@usgs.gov","contributorId":68658,"corporation":false,"usgs":true,"family":"Mitchell","given":"Richard","email":"rwmitchell@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":493746,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70104222,"text":"70104222 - 2014 - Avian influenza virus antibodies in Pacific Coast Red Knots (Calidris canutus rufa)","interactions":[],"lastModifiedDate":"2018-01-03T14:35:46","indexId":"70104222","displayToPublicDate":"2014-05-13T08:43:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Avian influenza virus antibodies in Pacific Coast Red Knots (Calidris canutus rufa)","title":"Avian influenza virus antibodies in Pacific Coast Red Knots (Calidris canutus rufa)","docAbstract":"Prevalence of avian influenza virus (AIV) antibodies in the western Atlantic subspecies of Red Knot (Calidris canutus rufa) is among the highest for any shorebird. To assess whether the frequency of detection of AIV antibodies is high for the species in general or restricted only to C. c. rufa, we sampled the northeastern Pacific Coast subspecies of Red Knot (Calidris canutus roselaari) breeding in northwestern Alaska. Antibodies were detected in 90% of adults and none of the chicks sampled. Viral shedding was not detected in adults or chicks. These results suggest a predisposition of Red Knots to AIV infection. High antibody titers to subtypes H3 and H4 were detected, whereas low to intermediate antibody levels were found for subtypes H10 and H11. These four subtypes have previously been detected in shorebirds at Delaware Bay (at the border of New Jersey and Delaware) and in waterfowl along the Pacific Coast of North America.
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margins","interactions":[],"lastModifiedDate":"2014-12-12T14:46:55","indexId":"70104181","displayToPublicDate":"2014-05-12T14:25:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2381,"text":"Journal of Marine Systems","active":true,"publicationSubtype":{"id":10}},"title":"Comparative biogeochemistry-ecosystem-human interactions on dynamic continental margins","docAbstract":"The ocean’s continental margins face strong and rapid change, forced by a combination of direct human activity, anthropogenic CO2-induced climate change, and natural variability. Stimulated by discussions in Goa, India at the IMBER IMBIZO III, we (1) provide an overview of the drivers of biogeochemical variation and change on margins, (2) compare temporal trends in hydrographic and biogeochemical data across different margins (3) review ecosystem responses to these changes, (4) highlight the importance of margin time series for detecting and attributing change and (5) examine societal responses to changing margin biogeochemistry and ecosystems. We synthesize information over a wide range of margin settings in order to identify the commonalities and distinctions among continental margin ecosystems. Key drivers of biogeochemical variation include long-term climate cycles, CO2-induced warming, acidification, and deoxygenation, as well as sea level rise, eutrophication, hydrologic and water cycle alteration, changing land use, fishing, and species invasion. Ecosystem responses are complex and impact major margin services including primary production, fisheries production, nutrient cycling, shoreline protection, chemical buffering, and biodiversity. Despite regional differences, the societal consequences of these changes are unarguably large and mandate coherent actions to reduce, mitigate and adapt to multiple stressors on continental margins.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Marine Systems","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jmarsys.2014.04.016","usgsCitation":"Levin, L.A., Liu, K., Emeis, K., Breitburg, D.L., Cloern, J., Deutsch, C., Giani, M., Goffart, A., Hofmann, E.E., Lachkar, Z., Limburg, K., Liu, S., Montes, E., Naqvi, W., Ragueneau, O., Rabouille, C., Sarkar, S.K., Swaney, D.P., Wassman, P., and Wishner, K.F., 2014, Comparative biogeochemistry-ecosystem-human interactions on dynamic continental margins: Journal of Marine Systems, v. 141, p. 3-17, https://doi.org/10.1016/j.jmarsys.2014.04.016.","productDescription":"15 p.","startPage":"3","endPage":"17","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055816","costCenters":[{"id":438,"text":"National Research Program - Western 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Enrique","contributorId":81021,"corporation":false,"usgs":true,"family":"Montes","given":"Enrique","affiliations":[],"preferred":false,"id":493610,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Naqvi, Wajih","contributorId":94597,"corporation":false,"usgs":true,"family":"Naqvi","given":"Wajih","email":"","affiliations":[],"preferred":false,"id":493612,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Ragueneau, Olivier","contributorId":6765,"corporation":false,"usgs":true,"family":"Ragueneau","given":"Olivier","email":"","affiliations":[],"preferred":false,"id":493596,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Rabouille, Christophe","contributorId":48875,"corporation":false,"usgs":true,"family":"Rabouille","given":"Christophe","email":"","affiliations":[],"preferred":false,"id":493604,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Sarkar, Santosh Kumar","contributorId":81807,"corporation":false,"usgs":true,"family":"Sarkar","given":"Santosh","email":"","middleInitial":"Kumar","affiliations":[],"preferred":false,"id":493611,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Swaney, Dennis P.","contributorId":31312,"corporation":false,"usgs":true,"family":"Swaney","given":"Dennis","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":493599,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Wassman, Paul","contributorId":51209,"corporation":false,"usgs":true,"family":"Wassman","given":"Paul","email":"","affiliations":[],"preferred":false,"id":493605,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Wishner, Karen F.","contributorId":100746,"corporation":false,"usgs":true,"family":"Wishner","given":"Karen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":493614,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70104182,"text":"70104182 - 2014 - Phytoplankton primary production in the world's estuarine-coastal ecosystems","interactions":[],"lastModifiedDate":"2014-05-12T14:15:49","indexId":"70104182","displayToPublicDate":"2014-05-12T14:08:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Phytoplankton primary production in the world's estuarine-coastal ecosystems","docAbstract":"Estuaries are biogeochemical hot spots because they receive large inputs of nutrients and organic carbon from land and oceans to support high rates of metabolism and primary production. We synthesize published rates of annual phytoplankton primary production (APPP) in marine ecosystems influenced by connectivity to land – estuaries, bays, lagoons, fjords and inland seas. Review of the scientific literature produced a compilation of 1148 values of APPP derived from monthly incubation assays to measure carbon assimilation or oxygen production. The median value of median APPP measurements in 131 ecosystems is 185 and the mean is 252 g C m−2 yr−1, but the range is large: from −105 (net pelagic production in the Scheldt Estuary) to 1890 g C m−2 yr−1 (net phytoplankton production in Tamagawa Estuary). APPP varies up to 10-fold within ecosystems and 5-fold from year to year (but we only found eight APPP series longer than a decade so our knowledge of decadal-scale variability is limited). We use studies of individual places to build a conceptual model that integrates the mechanisms generating this large variability: nutrient supply, light limitation by turbidity, grazing by consumers, and physical processes (river inflow, ocean exchange, and inputs of heat, light and wind energy). We consider method as another source of variability because the compilation includes values derived from widely differing protocols. A simulation model shows that different methods reported in the literature can yield up to 3-fold variability depending on incubation protocols and methods for integrating measured rates over time and depth.
\nAlthough attempts have been made to upscale measures of estuarine-coastal APPP, the empirical record is inadequate for yielding reliable global estimates. The record is deficient in three ways. First, it is highly biased by the large number of measurements made in northern Europe (particularly the Baltic region) and North America. Of the 1148 reported values of APPP, 958 come from sites between 30 and 60° N; we found only 36 for sites south of 20° N. Second, of the 131 ecosystems where APPP has been reported, 37% are based on measurements at only one location during 1 year. The accuracy of these values is unknown but probably low, given the large interannual and spatial variability within ecosystems. Finally, global assessments are confounded by measurements that are not intercomparable because they were made with different methods.
\nPhytoplankton primary production along the continental margins is tightly linked to variability of water quality, biogeochemical processes including ocean–atmosphere CO2 exchange, and production at higher trophic levels including species we harvest as food. The empirical record has deficiencies that preclude reliable global assessment of this key Earth system process. We face two grand challenges to resolve these deficiencies: (1) organize and fund an international effort to use a common method and measure APPP regularly across a network of coastal sites that are globally representative and sustained over time, and (2) integrate data into a unifying model to explain the wide range of variability across ecosystems and to project responses of APPP to regional manifestations of global change as it continues to unfold.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Copernicus Publications on behalf of the European Geosciences Union","doi":"10.5194/bg-11-2477-2014","usgsCitation":"Cloern, J.E., Foster, S., and Kleckner, A., 2014, Phytoplankton primary production in the world's estuarine-coastal ecosystems: Biogeosciences, v. 11, p. 2477-2501, https://doi.org/10.5194/bg-11-2477-2014.","productDescription":"25 p.","startPage":"2477","endPage":"2501","numberOfPages":"25","ipdsId":"IP-049711","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":472998,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-11-2477-2014","text":"Publisher Index Page"},{"id":287056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287055,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/bg-11-2477-2014"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-90.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,-90.0 ], [ -180.0,-90.0 ] ] ] } } ] }","volume":"11","noUsgsAuthors":false,"publicationDate":"2014-05-07","publicationStatus":"PW","scienceBaseUri":"5371df52e4b08449547883d9","contributors":{"authors":[{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":493615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster, S.Q.","contributorId":103184,"corporation":false,"usgs":true,"family":"Foster","given":"S.Q.","email":"","affiliations":[],"preferred":false,"id":493617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kleckner, A.E.","contributorId":33627,"corporation":false,"usgs":true,"family":"Kleckner","given":"A.E.","email":"","affiliations":[],"preferred":false,"id":493616,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70099906,"text":"gip133A - 2014 - Tracking change over time: River flooding","interactions":[],"lastModifiedDate":"2017-03-28T11:14:52","indexId":"gip133A","displayToPublicDate":"2014-05-12T08:10:20","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"133","chapter":"A","title":"Tracking change over time: River flooding","docAbstract":"Landsat satellites have been capturing images of Earth from space since 1972. These images provide a long-term record of natural and human-induced changes on the global landscape. Comparing images from multiple years reveals slow and subtle changes as well as rapid and devastating ones. Landsat images are available from the Internet at no charge. Using the free software MultiSpec, students can track changes to the landscape over time—just like remote sensing scientists do!
\nThe objective of the Tracking Change Over Time lesson plan is to get students excited about studying the changing Earth. Intended for students in grades 5-8, the lesson plan is flexible and may be used as a student self-guided tutorial or as a teacher-led class lesson. Enhance students' learning of geography, map reading, earth science, and problem solving by seeing landscape changes from space.
\nThe objective of the Tracking Change Over Time lesson plan is to get students excited about studying the changing Earth. Intended for students in grades 5-8, the lesson plan is flexible and may be used as a student self-guided tutorial or as a teacher-led class lesson. Enhance students' learning of geography, map reading, earth science, and problem solving by seeing landscape changes from space.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip133A","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2014, Tracking change over time: River flooding (Originally posted: May 9, 2014; Version 2.0: March 10, 2016): U.S. Geological Survey General Information Product 133, Tracking change over time—River flooding - Teacher: 4 p.; Tracking change over time—River flooding - Student: 2 p., https://doi.org/10.3133/gip133A.","productDescription":"Tracking change over time—River flooding - Teacher: 4 p.; Tracking change over time—River flooding - Student: 2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-038840","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":318950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/gip133A.JPG"},{"id":287035,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/133a/"},{"id":287040,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/133a/pdf/gip133a_teacher.pdf","text":"Teacher","description":"Teacher"},{"id":287041,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/133a/pdf/gip133a_student.pdf","text":"Student","description":"Student"}],"country":"United States","state":"Illinois, Indiana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.51,36.97 ], [ -91.51,42.51 ], [ -84.78,42.51 ], [ -84.78,36.97 ], [ -91.51,36.97 ] ] ] } } ] }","edition":"Originally posted: May 9, 2014; Version 2.0: March 10, 2016","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5371df54e4b08449547883e8","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":535644,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}