For many years, marshes in the coastal areas from Texas to Louisiana have served as critical habitat for Anas fulvigula, the mottled duck. Mottled ducks are a priority species in the Texas/Louisiana Gulf Coast area and have been affected by critical habitat reduction. In recent years, mottled duck habitats have been threatened by natural and anthropogenic changes including urbanization, flooding, saltwater intrusion, and hydrologic alterations. These impacts are affecting the quality of habitat that is essential for the mottled duck nesting, feeding, and livelihood. Cumulative and synergistic effects of contamination and invasive species encroachment have also caused mottled duck habitat to be considered as some of the most critically endangered habitats in the United States. To help understand the environmental conditions that characterize the coastal landscape, U.S. Geological Survey researchers used an unmanned aerial system (UAS) to acquire high-resolution imagery to document current land and water spatial configuration and wetland health at McFaddin National Wildlife Refuge, Texas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191045","usgsCitation":"Jones, W.R., Hartley, S.B., Stagg, C.L., and Osland, M.J., 2019, Using UAS capabilities to help identify hummock-hollow formation and fragmentation in critical marsh habitat (Spartina patens) for mottled ducks in southeast Texas: U.S. Geological Survey Open-File Report 2019–1045, 6 p., https://doi.org/10.3133/ofr20191045.","productDescription":"6 p.","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-105924","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":365530,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1045/coverthb.jpg"},{"id":365531,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1045/ofr20191045.pdf","text":"Report","size":"4.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1045"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.66796875,\n 25.760319754713887\n ],\n [\n -93.6474609375,\n 25.760319754713887\n ],\n [\n -93.6474609375,\n 32.24997445586331\n ],\n [\n -99.66796875,\n 32.24997445586331\n ],\n [\n -99.66796875,\n 25.760319754713887\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
We surveyed the bee fauna at Napatree Point, a coastal barrier beach in southwestern Rhode Island, using bee-bowl and netting samples, and compared results to bee-bowl samples at 2 inland sites. We collected a total of 53 species and morphospecies at Napatree Point, including 5 likely Rhode Island state records and several coastal dune and sand-nesting species that were not found inland. The comparative bee-bowl samples (colored bowls with soapy water placed at the sites to collect visiting bees) captured 35 species at Napatree Point and 66 at the inland sites (which included 6 likely state records, 2 shared with Napatree). The Napatree fauna shared numerous species with the inland sites, but overall species composition differed substantially. Both Napatree and inland sites showed greatest bee activity and species richness in spring. During spring, the most common bees at Napatree were twig- and cavity-nesting species such as Ceratina dupla and Osmia simillima, and the wood-nesting Lasioglossum oblongum, while the most abundant bees inland were the soil-nesting Andrena nasonii and Augochlorella aurata. Netting samples differed from bee-bowl samples in that they captured larger species and species foraging at flowers distant from the bee-bowl transects, but they missed several diminutive species that were captured by bee bowls. Use of 2 sampling methods, therefore, provided a broader view of the bee fauna than would have been possible with a single collection method.
","language":"English","publisher":"BioOne","doi":"10.1656/045.026.0301","usgsCitation":"Rothwell, A., and Ginsberg, H., 2019, The bee fauna of coastal Napatree Point and two inland sites in southern Rhode Island: Northeastern Naturalist, v. 26, no. 3, p. 446-464, https://doi.org/10.1656/045.026.0301.","productDescription":"19 p.","startPage":"446","endPage":"464","ipdsId":"IP-100044","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":488834,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/pls_facpubs/138","text":"External Repository"},{"id":368032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Napatree Point","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.90277099609375,\n 41.30257109430557\n ],\n [\n -71.46469116210936,\n 41.352072144512924\n ],\n [\n -71.51309967041016,\n 41.50832019744722\n ],\n [\n -71.63223266601562,\n 41.48311944560493\n ],\n [\n -71.90277099609375,\n 41.30257109430557\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rothwell, Aya","contributorId":219515,"corporation":false,"usgs":false,"family":"Rothwell","given":"Aya","email":"","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":772438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":772437,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70203969,"text":"sir20195054 - 2019 - The use of continuous water-quality time-series data to compute nutrient loadings for selected Iowa streams, 2008–17","interactions":[],"lastModifiedDate":"2019-07-23T14:31:04","indexId":"sir20195054","displayToPublicDate":"2019-07-23T13:34:03","publicationYear":"2019","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":"2019-5054","displayTitle":"The Use of Continuous Water-Quality Time-Series Data to Compute Nutrient Loadings for Selected Iowa Streams, 2008–17","title":"The use of continuous water-quality time-series data to compute nutrient loadings for selected Iowa streams, 2008–17","docAbstract":"In support of nutrient reduction efforts, nitrate (as nitrate plus nitrite) and phosphorus loads and yields were computed for selected streams in Iowa based on continuously monitored sensor data for 2008–17 and 2014–17, respectively. Sample data were used to assess nitrate sensor bias and to create phosphorus-turbidity surrogate models. Where needed, nitrate loads were corrected for site-specific sensor bias, which was determined to be as high as 9.25 percent. Nitrate loads presented in this report using continuous (generally 15-minute interval) data were on average 4 percent less, but as much as 38 percent less, than annual loads computed from daily mean nitrate concentrations not corrected for sensor bias. Streamflow-based phosphorus models had poorer fit (adjusted coefficient of determination values less than 0.75) than turbidity-based models (adjusted coefficient of determination approximately 0.9). However, alternate models based on streamflow were used to obtain a more complete annual phosphorus load despite seasonal and fragmentary sensor data.
Mean annual nitrate yields for 18 selected sites (96 site-years) ranged from 1.68 to 164 pounds per square mile per day (lb/mi2/d), compared to 19.4 lb/mi2/d average statewide yield needed to achieve the nitrate-reduction goal. Mean annual phosphorus yields for selected sites on the Maquoketa River, South Raccoon River, and West Nishnabotna River range from 1.57 to 7.19 lb/mi2/d, compared to 1.06 lb/mi2/d average statewide yield needed to achieve the phosphorus-reduction goal.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195054","collaboration":"Prepared in cooperation with the Iowa Department of Natural Resources","usgsCitation":"Garrett, J.D., 2019, The use of continuous water-quality time-series data to compute nutrient loadings for selected Iowa streams, 2008–17: U.S. Geological Survey Scientific Investigations Report 2019–5054, 31 p., https://doi.org/10.3133/sir20195054.","productDescription":"Report: viii, 31 p.; Appendixes: 2","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098143","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":365814,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5054/sir20195054.pdf","text":"Report","size":"1.97 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U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
Hurricane Maria made landfall south of Yabucoa Harbor, Puerto Rico, as a category 4 hurricane with maximum sustained winds of 155 miles per hour on September 20, 2017. The hurricane devastated much of the U.S. Virgin Islands and Puerto Rico. The U.S. Geological Survey (USGS), in cooperation with Federal Emergency Management Agency, installed a temporary monitoring network of 13 water-level and barometric pressure sensors along the coast of Puerto Rico prior to the storm. In addition to the temporary sensors, the USGS maintains 99 permanent real-time streamgages and 36 real-time precipitation stations in Puerto Rico. The real-time data, updated hourly, during and after the hurricane are displayed in the USGS Flood Event Viewer (https://stn.wim.usgs.gov/FEV/#MariaSeptember2017) and in the USGS National Water Information System.
The USGS measured 181 coastal and riverine high-water marks throughout Puerto Rico after the storm. Water elevations are referenced to the Puerto Rico Vertical Datum of 2002 (PRVD02) and local datums in Puerto Rico and to the U.S. Virgin Islands Vertical Datum of 2009 (VIVD09) in the U.S. Virgin Islands. Data from the Hurricane Maria storm-tide network are available in tab-delimited, American Standard Code for Information Interchange (ASCII) format and Network Common Data Form (NetCDF) format by site for each sensor through the USGS Flood Event Viewer.
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Pyrethroids are a class of widely-used insecticides that can be transported from terrestrial applications to aquatic systems via runoff and tend to sorb to organic carbon in sediments. Pyrethroid occurrence is detrimental to stream ecosystems due to toxicity to sediment-dwelling invertebrates which are particularly at risk of pyrethroid exposure in urban streams. In this work, 49 streams located in watersheds in the northeastern United States were surveyed for nine current-use pyrethroids using two extraction methods. Total sediment concentrations were determined by exhaustive chemical extraction, while bioaccessible concentrations were determined by single-point Tenax extraction. Total and bioaccessible pyrethroid concentrations were detected in 76% and 67% of the sites, and the average sum of pyrethroids was 232 ng/g organic carbon (OC) for total and 43.8 ng/g OC for bioaccessible pyrethroids. Bifenthrin was the most commonly detected pyrethroid in streambed sediments. Sediment toxicity was assessed using 10-d Hyalella azteca bioassays, and 28% and 15% of sediments caused a decrease in H. azteca biomass and survival, respectively. A temperature-based focused toxicity identification evaluation was used to assess pyrethroids as the causal factor for toxicity. The concentrations of pyrethroids was only weakly correlated with the degree of urban land use. Sediment toxicity was predicted by total and bioaccessible pyrethroid concentrations expressed as toxic units. This work suggests that bioaccessibility-based methods, such as Tenax extraction, can be a valuable tool in assessing sediment toxicity.
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2019 - Water-budget analysis of the Upper Big Sandy Designated Ground-water Basin alluvial aquifer, Elbert, El Paso, and Lincoln Counties, Colorado, 2016","interactions":[],"lastModifiedDate":"2019-12-30T11:37:00","indexId":"sir20195049","displayToPublicDate":"2019-07-22T11:20:00","publicationYear":"2019","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":"2019-5049","displayTitle":"Water-Budget Analysis of the Upper Big Sandy Designated Groundwater Basin Alluvial Aquifer, Elbert, El Paso, and Lincoln Counties, Colorado, 2016","title":"Water-budget analysis of the Upper Big Sandy Designated Ground-water Basin alluvial aquifer, Elbert, El Paso, and Lincoln Counties, Colorado, 2016","docAbstract":"The U.S. Geological Survey in cooperation with the Colorado Water Conservation Board and the Upper Big Sandy Groundwater Management District carried out a study in 2016 to evaluate potential groundwater storage changes within the Upper Big Sandy Designated Groundwater Basin (UBSDGB) alluvial aquifer, including groundwater flow between the UBSDGB alluvial aquifer and the Denver Basin bedrock aquifers. The UBSDGB alluvial aquifer is located along the ephemeral Big Sandy Creek on the east-central edge of the Denver Basin aquifer system and covers an area of about 66,560 acres within the UBSDGB. The UBSDGB alluvial aquifer consists of unconsolidated Quaternary sand and gravel deposits that contain an unconfined (water table) groundwater system. The western three-fourths of the UBSDGB alluvial aquifer overlies the Tertiary and Cretaceous bedrock formations that compose the Denver Basin aquifer system. The updated water budget for the UBSDGB alluvial aquifer, including annual change in groundwater storage in 2016, was determined by combining water-budget information from an existing Denver Basin model for about three-fourths of the study area with best estimates for the major water-budget components for the area outside the Denver Basin aquifer system. The western part of the UBSDGB was included in the Denver Basin model (modeled area), whereas the eastern part of the UBSDGB was not included in the Denver Basin model (unmodeled area). The water-budget components were first estimated for the modeled area using outputs from the Denver Basin model, which uses the modular finite-difference groundwater flow computer model MODFLOW-2000 with 1-mile grid cells. For this study, the Denver Basin model was updated with additional data from 2004 through 2016 to generate current (2016) estimates of water consumption in the UBSDGB alluvial aquifer. A basin-specific water budget for the UBSDGB alluvial aquifer from the Denver Basin model was computed using a modeling tool called ZONEBUDGET. The modeled area groundwater budget, along with previous studies, was used to estimate a groundwater budget for the unmodeled area, and results for the modeled and unmodeled areas were combined for an overall water-budget estimate for the entire UBSDGB alluvial aquifer.
The net groundwater flow into the basin from adjacent alluvial aquifers was positive with flow entering the UBSDGB alluvial aquifer. Combining the total inflow from adjacent alluvial and the total outflow to adjacent alluvial aquifers resulted in a net flow from adjacent alluvial aquifers to UBSDGB alluvial aquifer of 5,125 acre-feet (ac-ft) in 2016. The net flow between the underlying bedrock aquifers and the UBSDGB alluvial aquifer was positive with flow entering the UBSDGB alluvial aquifer from the bedrock aquifers. The net flow from the bedrock aquifers to the UBSDGB alluvial aquifer was 347 ac-ft in 2016. Net recharge (precipitation and irrigation return flows minus evaporation) into the UBSDGB alluvial aquifer was negative with groundwater being removed from the UBSDGB alluvial aquifer over the total area of the basin. Combining the total inflow from recharge to the UBSDGB alluvial aquifer of 11,153 ac-ft in 2016 and the total evapo-transpiration of −11,656 ac-ft from the UBSDGB alluvial aquifer in 2016 resulted in a net recharge from UBSDGB alluvial aquifer of −503 ac-ft in 2016. Combining the modeled and unmodeled well pumping resulted in a total well pumping volume of −3,735 ac-ft in 2016 from the UBSDGB alluvial aquifer. The net groundwater flow to the stream network in the basin was negative with flow discharging from the UBSDGB alluvial aquifer into streams. Combining the total inflow from streams and the total outflow to streams for the UBSDGB alluvial aquifer resulted in −1,032 ac-ft in 2016 that was lost to the stream network in the UBSDGB. The net groundwater flow out of the UBSDGB was negative with flow leaving the UBSDGB alluvial aquifer. Combining the total area inflow to the basin from upgradient areas and the total area outflow from the basin for the UBSDGB alluvial aquifer resulted in a net flow out of the basin of −2,300 ac-ft. In the annual groundwater budget for 2016, groundwater storage in the UBSDGB alluvial aquifer system was removed because annual groundwater outflows from storage exceeded groundwater inflows to storage; in other words, water was removed from storage to balance the annual water budget. Combining the net flow from storage for the modeled area of 73 ac-ft and the inflow from storage for the unmodeled area of 2,025 ac-ft resulted in a net positive flow from storage of the UBSDGB alluvial aquifer of 2,098 ac-ft.
Increased pumping since 1958 in the Denver and upper Arapahoe aquifers, not necessarily in the UBSDGB, has caused a change in flow from bedrock units, which were minor or non-contributors of inflow to the UBSDGB alluvial aquifer, to receiving outflow from the UBSDGB alluvial aquifer. Since 2000, aquifer storage has been an inflow component of the water budget, which means that outflow from the modeled area exceeded inflow for the UBSDGB alluvial aquifer. Increased recharge from wetter than average years could replenish the UBSDGB alluvial aquifer. From 2003 through 2016, 13 of the 25 observation wells completed in the UBSDGB alluvial aquifer had a decline in the groundwater-level elevation with an average decline of −2.21 feet, and 12 of the 25 observation wells had an increase in the groundwater-level elevation with an average increase of 1.54 feet. In general, wells at the eastern and western edges of the UBSDGB showed an increase in groundwater-level elevation that appears related to areas of groundwater discharge from the lower Dawson and Laramie-Fox Hills bedrock aquifers to the UBSDGB alluvial aquifer. The remaining wells exhibited water-level declines. Future work could include the development of a basin-specific model to serve as a basin management tool for modeling changes in groundwater levels and storage under various future groundwater recharge and withdrawal scenarios.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20195049","collaboration":"Prepared in cooperation with the Colorado Water Conservation Board and the Upper Big Sandy Groundwater Management District","usgsCitation":"Kohn, M.S., Oden, J.H., and Arnold, L.R., 2019, Water-budget analysis of the Upper Big Sandy Designated Ground-water Basin alluvial aquifer, Elbert, El Paso, and Lincoln Counties, Colorado, 2016: U.S. Geological Survey Scientific Investigations Report 2019-5049, 25 p., https://dx.doi.org/10.3133/sir20195049.","productDescription":"Report: vi, 25 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-091541","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":365584,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5049/sir20195049.pdf","text":"Report","size":"7.12 M","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5049"},{"id":365581,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5049/coverthb.jpg"},{"id":365748,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DEOYGZ","text":"USGS data release","linkHelpText":"MODFLOW2000 model and ZONEBUDGET computer program used to simulate the Upper Big Sandy Designated Groundwater Basin alluvial aquifer, Elbert, El Paso, and Lincoln Counties, Colorado, 2016"}],"country":"United States","state":"Colorado","county":"Elbert County, El Paso County, Lincoln County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.054,38.523],[-104.1629,38.5215],[-104.2759,38.5204],[-104.2794,38.5205],[-104.2836,38.5201],[-104.3759,38.52],[-104.4971,38.5192],[-104.6071,38.5187],[-104.7171,38.5186],[-104.736,38.5183],[-104.8295,38.5183],[-104.943,38.5175],[-104.9432,38.5479],[-104.943,38.5624],[-104.9429,38.6041],[-104.9427,38.6186],[-104.9429,38.6467],[-104.9429,38.6503],[-104.9427,38.6621],[-104.9427,38.6648],[-104.9428,38.6938],[-104.9399,38.6938],[-104.9386,38.7808],[-104.939,38.7949],[-105.0671,38.7946],[-105.0674,38.8666],[-105.0502,38.8665],[-105.0296,38.8668],[-105.026,39.0413],[-105.032,39.1311],[-104.9371,39.1312],[-104.9175,39.131],[-104.8303,39.1311],[-104.6642,39.1308],[-104.6638,39.2165],[-104.664,39.3026],[-104.663,39.3892],[-104.6626,39.4762],[-104.6627,39.5665],[-104.6054,39.5663],[-104.5374,39.5655],[-104.4927,39.5636],[-104.4891,39.5636],[-104.4742,39.5629],[-104.3841,39.5627],[-104.3763,39.5631],[-104.2695,39.5639],[-104.2647,39.5638],[-104.1602,39.5646],[-104.1543,39.565],[-104.0468,39.5652],[-104.0427,39.5651],[-103.9305,39.5646],[-103.9293,39.5646],[-103.8189,39.5646],[-103.8129,39.5649],[-103.7126,39.5649],[-103.7066,39.5648],[-103.6004,39.5646],[-103.595,39.5645],[-103.4882,39.5647],[-103.4804,39.5645],[-103.3748,39.5651],[-103.3658,39.5654],[-103.2631,39.5659],[-103.253,39.5657],[-103.1533,39.5657],[-103.1539,39.475],[-103.1537,39.3879],[-103.1542,39.3009],[-103.154,39.2147],[-103.1527,39.1258],[-103.161,39.1255],[-103.1615,39.0376],[-103.1626,38.9492],[-103.163,38.863],[-103.1634,38.7765],[-103.1638,38.6912],[-103.1709,38.6909],[-103.1705,38.6837],[-103.1731,38.6796],[-103.1716,38.6111],[-103.1714,38.5236],[-103.2809,38.5224],[-103.3897,38.5239],[-103.5086,38.5236],[-103.5089,38.5159],[-103.6118,38.5171],[-103.6116,38.5225],[-103.7228,38.5223],[-103.8328,38.523],[-103.9411,38.523],[-104.054,38.523]]]},\"properties\":{\"name\":\"Elbert\",\"state\":\"CO\"}}]}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225
Rhyolite-hosted hydrothermal systems in the continental crust contain valuable energy and mineral resources that make them of special interest across several scientific disciplines. Despite extensive research on these systems, the temperature-dependence of chemical reactions between host rocks and aqueous-rich fluids and the mineralogical transformations resulting from these reactions are not well quantified. To expand our understanding of the controlling processes operating in these systems, we carried out seven laboratory experiments in which rhyolite was reacted with deionized water at 150 °C to 350 °C and 25 MPa. An additional experiment at 200 °C was carried out to examine the effect of dissolved CO2 on the reactions. The overarching goal of this experimental study was to provide new insights on the temperature-dependence of water-rock interaction in continental hydrothermal systems. We applied a wide range of chemical, isotopic and mineralogical methods to analyze the reacted rhyolite and waters, and the major observations are: (1) the rhyolite progressively hydrates with increasing temperature between 150 °C to a maximum of 8.2 wt% H2O at 275 °C; hydration then decreases until 350 °C in conjunction with the destruction of the rhyolite glass and crystallization of secondary mineral phases; (2) the ratio of molecular water (H2Om) to hydroxyl (OH−) of the water that is dissolved in the reacted rhyolite decreases from ∼7 at 150 °C to ∼4 at 250 °C; (3) the main secondary minerals formed are the zeolite ferrierite (T ≥ 275 °C); biotite, albite and cristobalite mainly form at higher experimental temperatures (T ≥ 300 °C); (4) the reacted waters are nearly saturated with respect to amorphous silica; (5) at temperatures ≥ 275 °C nearly all the chlorine is leached into solution; (6) fluorine leaching from the rhyolite gradually increases between 150 °C and 250 °C, but then gradually decreases at higher temperatures and is incorporated into a secondary mineral phase; (7) dissolved CO2 in the water enhances alkali metal cation leaching from the rhyolite; and (8) calculated Na-K and silica geothermometer temperatures differ from the experimental temperatures by varying amounts. In addition, apart from some small lithium isotope fractionation at temperatures ≤ 250 °C, the stable isotopes of boron, lithium and chlorine do not fractionate during rhyolite-water reactions, and the stable isotope compositions of these species in the reacted water are similar to those in the reactant rhyolite. These results provide new insights for a broad range of applications, including quantifying processes involving rhyolite glass hydration (obsidian hydration dating, perlite formation and discriminating secondary from magmatic water in rhyolitic matrix-glass of volcanic pyroclasts), for geothermal energy and mineral deposit exploration and for monitoring volcanoes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2019.07.012","collaboration":"University of Texas, University of Maryland, University of Bremen","usgsCitation":"Cullen, J.T., Hurwitz, S., Barnes, J.D., John C. Lassiter, Penniston-Dorland, S., Kasemann, S., and Thordsen, J., 2019, Temperature-dependent variations in mineralogy, major element chemistry and the stable isotopes of boron, lithium and chlorine resulting from hydration of rhyolite glass: Constraints from hydrothermal experiments at 150 to 350°C and 25 MPa: Geochimica et Cosmochimica Acta, v. 261, p. 269-287, https://doi.org/10.1016/j.gca.2019.07.012.","productDescription":"19 p.","startPage":"269","endPage":"287","ipdsId":"IP-106122","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":467436,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2019.07.012","text":"Publisher Index Page"},{"id":366658,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"261","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cullen, Jeffery T.","contributorId":218176,"corporation":false,"usgs":false,"family":"Cullen","given":"Jeffery","email":"","middleInitial":"T.","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":768629,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":768628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnes, Jaime D.","contributorId":218177,"corporation":false,"usgs":false,"family":"Barnes","given":"Jaime","email":"","middleInitial":"D.","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":768630,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"John C. Lassiter","contributorId":218178,"corporation":false,"usgs":false,"family":"John C. Lassiter","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":768631,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Penniston-Dorland, Sarah","contributorId":218179,"corporation":false,"usgs":false,"family":"Penniston-Dorland","given":"Sarah","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":768632,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kasemann, Simone","contributorId":218180,"corporation":false,"usgs":false,"family":"Kasemann","given":"Simone","email":"","affiliations":[{"id":24749,"text":"University of Bremen","active":true,"usgs":false}],"preferred":false,"id":768633,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thordsen, James 0000-0001-9809-0398 jthordsn@usgs.gov","orcid":"https://orcid.org/0000-0001-9809-0398","contributorId":205838,"corporation":false,"usgs":true,"family":"Thordsen","given":"James","email":"jthordsn@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":768634,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70205850,"text":"70205850 - 2019 - Long-term (37 years) impacts of low-head dams on freshwater shrimp habitat connectivity in northeastern Puerto Rico","interactions":[],"lastModifiedDate":"2019-10-08T12:45:28","indexId":"70205850","displayToPublicDate":"2019-07-19T12:43:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Long-term (37 years) impacts of low-head dams on freshwater shrimp habitat connectivity in northeastern Puerto Rico","docAbstract":"Freshwater migratory shrimp in Puerto Rico depend on watershed connectivity, from stream headwaters to the ocean, to complete their life cycle. Moreover, shrimp populations in different watersheds are known to be connected in an island-wide metapopulation. However, low-head dams paired with water intakes on streams draining the El Yunque National Forest (EYNF) reduce streamflow. Here, we examine the cumulative effects of low-head dams on shrimp habitat connectivity over 37-years across seven EYNF watersheds. We calculate total and refugia habitat connectivity (where refugia habitat is defined as predator-free upstream reaches above waterfalls > 5 m in height) at a monthly time step using a habitat-weighted index of longitudinal riverine connectivity, which incorporates location and operation of water intakes and streamflow variability. Findings indicate total and refugia habitat connectivity declined over 37 years (by 27% and 16%, respectively) as additional water intakes have been placed in lower reaches of watersheds. On a monthly time-step, the proportion of streamflow withdrawn has the largest effect on habitat connectivity, with the result that connectivity is ~17% lower during drought years than in non-drought years and ~7% lower in dry compared to wet seasons. Our analysis of this long-term dataset highlights how cumulative effects of low-head dams paired with water intakes have reduced shrimp habitat connectivity. These results underscore the importance of reducing existing withdrawal rates in EYNF, and locating intakes where effects on connectivity are minimal, if conserving shrimp habitat is a management objective.","language":"English","publisher":"Wiley","doi":"10.1002/rra.3499","usgsCitation":"Chappell, J., McKay, S.K., Freeman, M., and Pringle, C.M., 2019, Long-term (37 years) impacts of low-head dams on freshwater shrimp habitat connectivity in northeastern Puerto Rico: River Research and Applications, v. 35, no. 7, p. 1034-1043, https://doi.org/10.1002/rra.3499.","productDescription":"10 p.","startPage":"1034","endPage":"1043","ipdsId":"IP-105657","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467437,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.3499","text":"Publisher Index 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High-resolution multiproxy analysis from four sites show freshwater wetlands transitioned to mangrove environments 4–3.6 ka, followed by estuarine environments 3.4–2.8 ka, during a period of enhanced climate variability. We calculate a RSLR rate of 0.67 ± 0.1 mm yr−1 between ~4.2–2.8 ka, 4–6 times lower than current rates. Despite low RSLR rates, the rapid mangrove to estuarine transgression was facilitated by a period of prolonged droughts and frequent storms. These findings suggest that with higher and accelerating RSLR today, enhanced climate variability could further hasten the loss of mangrove-lined coastlines, compounded by the reductions in natural flow to the coast caused by water management. Climate variability is nonlinear, and when superimposed on increases in RSLR, can complicate estimated trajectories of coastal inundation for resource management and urban planning.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-019-11138-4","usgsCitation":"Jones, M., Wingard, G.L., Stackhouse, B., Keller, K., Willard, D.A., Marot, M.E., Landacre, B.D., and Bernhardt, C.E., 2019, Rapid inundation of the southern Florida coastline despite low relative sea-level rise rates during the late-Holocene: Nature Communications, v. 10, no. 1, 3231, 13 p., https://doi.org/10.1038/s41467-019-11138-4.","productDescription":"3231, 13 p.","ipdsId":"IP-099502","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":24693,"text":"Climate Research and Development","active":true,"usgs":true}],"links":[{"id":467439,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-019-11138-4","text":"Publisher Index Page"},{"id":366473,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Bahamas, Belize, Cuba, Dominican Republic, Haiti, United States, Venezuela","state":"Florida","otherGeospatial":"Florida Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.123046875,\n 26.15543796871355\n ],\n [\n -85.4296875,\n 22.024545601240337\n ],\n [\n -88.505859375,\n 18.187606552494625\n ],\n [\n -88.76953125,\n 16.003575733881327\n ],\n [\n -83.671875,\n 16.25686733062344\n ],\n [\n -66.9287109375,\n 11.43695521614319\n ],\n [\n -65.9619140625,\n 10.876464994816295\n ],\n [\n -64.51171875,\n 10.746969318460001\n ],\n [\n -68.37890625,\n 19.518375478601566\n ],\n [\n -76.46484375,\n 25.799891182088334\n ],\n [\n -77.0361328125,\n 27.176469131898898\n ],\n [\n -81.123046875,\n 26.15543796871355\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Miriam 0000-0002-6650-7619","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":201994,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":768145,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wingard, G. Lynn 0000-0002-3833-5207 lwingard@usgs.gov","orcid":"https://orcid.org/0000-0002-3833-5207","contributorId":605,"corporation":false,"usgs":true,"family":"Wingard","given":"G.","email":"lwingard@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":768146,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stackhouse, Bethany 0000-0003-0925-7120","orcid":"https://orcid.org/0000-0003-0925-7120","contributorId":218047,"corporation":false,"usgs":true,"family":"Stackhouse","given":"Bethany","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":768147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keller, Katherine 0000-0001-6915-5455","orcid":"https://orcid.org/0000-0001-6915-5455","contributorId":218048,"corporation":false,"usgs":false,"family":"Keller","given":"Katherine","email":"","affiliations":[{"id":39732,"text":"Natural Systems Analysts, Harvard University","active":true,"usgs":false}],"preferred":false,"id":768148,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Willard, Debra A. 0000-0003-4878-0942 dwillard@usgs.gov","orcid":"https://orcid.org/0000-0003-4878-0942","contributorId":2076,"corporation":false,"usgs":true,"family":"Willard","given":"Debra","email":"dwillard@usgs.gov","middleInitial":"A.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":24693,"text":"Climate Research and Development","active":true,"usgs":true}],"preferred":true,"id":768149,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marot, Marci E. 0000-0003-0504-315X mmarot@usgs.gov","orcid":"https://orcid.org/0000-0003-0504-315X","contributorId":2078,"corporation":false,"usgs":true,"family":"Marot","given":"Marci","email":"mmarot@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":768150,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Landacre, Bryan D. 0000-0002-0523-360X blandacre@usgs.gov","orcid":"https://orcid.org/0000-0002-0523-360X","contributorId":2722,"corporation":false,"usgs":true,"family":"Landacre","given":"Bryan","email":"blandacre@usgs.gov","middleInitial":"D.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":768151,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bernhardt, Christopher E. 0000-0003-0082-4731 cbernhardt@usgs.gov","orcid":"https://orcid.org/0000-0003-0082-4731","contributorId":2131,"corporation":false,"usgs":true,"family":"Bernhardt","given":"Christopher","email":"cbernhardt@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":768152,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70215389,"text":"70215389 - 2019 - Mapping irrigated cropland extent across the conterminous United States at 30 m resolution using a semi-automatic training approach on Google Earth Engine","interactions":[],"lastModifiedDate":"2024-05-16T13:57:09.889555","indexId":"70215389","displayToPublicDate":"2019-07-19T08:44:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1958,"text":"ISPRS Journal of Photogrammetry and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Mapping irrigated cropland extent across the conterminous United States at 30 m resolution using a semi-automatic training approach on Google Earth Engine","docAbstract":"Accurate and timely information on the distribution of irrigated croplands is crucial to research on agriculture, water availability, land use, and climate change. While agricultural land use has been well characterized, less attention has been paid specifically to croplands that are irrigated, in part due to the difficulty in mapping and distinguishing irrigation in satellite imagery. In this study, we developed a semi-automatic training approach to rapidly map irrigated croplands across the conterminous United States (CONUS) at 30 m resolution using Google Earth Engine. To resolve the issue of lacking nationwide training data, we generated two intermediate irrigation maps by segmenting Landsat-derived annual maximum greenness and enhanced vegetation index using county-level thresholds calibrated from an existing coarse resolution irrigation map. The resulting intermediate maps were then spatially filtered to provide a training data pool for most areas except for the upper midwestern states where we visually collected samples. We then used random samples extracted from the training pool along with remote sensing-derived features and climate variables to train ecoregion-stratified random forest classifiers for pixel-level classification. For ecoregions with a large training pool, the procedure of sample extraction, classifier training, and classification was conducted 10 times to obtain stable classification results. The resulting 2012 Landsat-based irrigation dataset (LANID) identified 23.3 million hectares of irrigated croplands in CONUS. A quantitative assessment of LANID showed superior accuracy to currently available maps, with a mean Kappa value of 0.88 (0.75–0.99), overall accuracy of 94% (87.5–99%), and producer’s and user’s accuracy of the irrigation class of 97.3% and 90.5%, respectively, at the aquifer level. Evaluation of feature importance indicated that Landsat-derived features played the primary role in classification in relatively arid regions while climate variables were important in the more humid eastern states. This methodology has the potential to produce annual irrigation maps for CONUS and provide insights into the field-level spatial and temporal aspects of irrigation.
The reactivity of co-occurring arsenic (As) and uranium (U) in mine wastes was investigated using batch reactors, microscopy, spectroscopy, and aqueous chemistry. Analyses of field samples collected in proximity to mine wastes in northeastern Arizona confirm the presence of As and U in soils and surrounding waters, as reported in a previous study from our research group. In this study, we measured As (<0.500 to 7.77 μg/L) and U (0.950 to 165 μg/L) in waters, as well as mine wastes (<20.0 to 40.0 mg/kg As and <60.0 to 110 mg/kg U) and background solids (<20.0 mg/kg As and <60.0 mg/kg U). Analysis with X-ray fluorescence (XRF) and electron microprobe show the co-occurrence of As and U with iron (Fe) and vanadium (V). These field conditions served as a foundation for additional laboratory experiments to assess the reactivity of metals in these mine wastes. Results from laboratory experiments indicate that labile and exchangeable As(V) was released to solution when solids were sequentially reacted with water and magnesium chloride (MgCl2), while limited U was released to solution with the same reactants. The predominance of As(V) in mine waste solids was confirmed by X-ray absorption near edge (XANES) analysis. Both As and U were released to solution after reaction of solids in batch experiments with HCO3−. Both X-ray photoelectron spectroscopy (XPS) and XANES analysis determined the predominance of Fe(III) in the solids. Mössbauer spectroscopy detected the presence of nano-crystalline goethite, Fe(II) and Fe(III) in (phyllo)silicates, and an unidentified mineral with parameters consistent with arsenopyrite or jarosite in the mine waste solids. Our results suggest that As and U can be released under environmentally relevant conditions in mine waste, which is applicable to risk and exposure assessment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2019.05.024","usgsCitation":"Blake, J., Avasarala, S., Ali, A., Spilde, M., Lezama-Pacheco, J., Latta, D., Artyushkova, K., Ilgen, A., Shuey, C., Nez, C., and Cerrato, J., 2019, Reactivity of As and U co-occurring in mine wastes in northeastern Arizona: Chemical Geology, v. 522, p. 26-37, https://doi.org/10.1016/j.chemgeo.2019.05.024.","productDescription":"12 p.","startPage":"26","endPage":"37","ipdsId":"IP-094541","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":467441,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1691565","text":"Publisher Index Page"},{"id":365730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365729,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2019.05.024"}],"country":"United 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Anthropogenic deposition of lead may be contributing to negative population-level effects in waterfowl and other organisms that depend on dynamic wetland habitats, particularly if they are unable to detect and differentiate levels of environmental contamination by lead. Detection of lead and behavioral response to elevated lead levels by waterfowl is poorly understood, but necessary to characterize the risk of lead-contaminated habitats. We measured the relationship between lead contamination of wetland soils and habitat use by mottled ducks (Anas fulvigula) on the Upper Texas Coast, USA. Mottled ducks have historically experienced disproportionate negative effects from lead exposure, and exhibit a unique nonmigratory life history that increases risk of exposure when inhabiting contaminated areas. We used spatial interpolation to estimate lead in wetland soils of the Texas Chenier Plain National Wildlife Refuge Complex. Soil lead levels varied across the refuge complex (0.01–1085.51 ppm), but greater lead concentrations frequently corresponded to areas with high densities of transmittered mottled ducks. We used soil lead concentration data and MaxENT species distribution models to quantify relationships among various habitat factors and locations of mottled ducks. Use of habitats with greater lead concentration increased during years of a major disturbance. Because mottled ducks use habitats with high concentrations of lead during periods of stress, have greater risk of exposure following major disturbance to the coastal marsh system, and no innate mechanism for avoiding the threat of lead exposure, we suggest the potential presence of an ecological trap of quality habitat that warrants further quantification at a population scale for mottled ducks.
The hydrothermal systems associated with the restless high-threat volcanoes at Lassen and Long Valley, California, each release large amounts of arsenic (As) to surface waters – ~6 and ~8 metric tons/yr, respectively. The hydrothermal As output can increase during volcanic unrest, as illustrated by a two-fold increase during unrest at Lassen in 2014–15. During that period of unrest, increased As concentrations and fluxes were measured up to 75 km downstream from the Lassen source, in Mill Creek near the confluence with the Sacramento River. In eastern California, the Long Valley hydrothermal system feeds into the Los Angeles Aqueduct (LAA), and the Los Angeles Department of Water and Power (LADWP) actively manages the LAA system to remove hydrothermal As. In 1980, during a series of ~Mw6 earthquakes, the discharge of a particular group of hydrothermal vents in Long Valley increased approximately 7-fold, though the total increase in As flux to the LAA system at that time is unknown. The likely mechanism for increased hydrothermal discharge in each case is permeability enhancement due to strong ground motion. A review of the global literature on earthquake hydrology suggests a worst-case scenario of a roughly 10-fold increase in permeability, with commensurate increase in the hydrothermal As flux persisting for days to months. Here we evaluate the potential impact of such increases in hydrothermal As flux on the California water-supply system.
Hydro-Eco Interactions Branch
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025
Polycyclic aromatic hydrocarbon contamination related to boat use is one of the most important water-quality issues affecting Lake Powell. High concentrations of polycyclic aromatic hydrocarbons in water are common around marinas and other areas with extensive motorboat activity because of releases of uncombusted or partially combusted oil and gasoline from boat engines. The fate of these compounds in Lake Powell is of serious environmental concern because of their toxicity and carcinogenicity and their moderate persistence once they enter the aquatic ecosystem. In 2016–17, the U.S. Geological Survey (USGS) assessed the presence and concentrations of polycyclic aromatic hydrocarbons in Lake Powell at seven sites where concentrations have historically been elevated and one site where concentrations have historically been relatively low. Semipermeable membrane devices were used to collect samples that represent time-weighted averages of polycyclic aromatic hydrocarbon concentrations in water over one-month deployment periods. Samples were collected from the epilimnion of the lake at each of the eight sampling sites during two periods of relatively high boat use (summer), and one period of relatively low boat use (spring). Twenty-eight out of 33 polycyclic aromatic hydrocarbons analyzed were detected in Lake Powell during the three sampling events. During the two summer sampling events, concentrations were generally higher, and more compounds were detected, than during the spring sampling event. Twenty-two of the polycyclic aromatic hydrocarbons analyzed in 2016–17 had previously been analyzed by the USGS in the summer of 2010 at the same 8 sites using the same collection method. Eleven of 22 compounds were detected in the summer 2010, summer 2016, and summer 2017 sampling events, and 1 was detected in the summer 2010 and summer 2017 samplings, but not in the summer 2016 sampling event. During both the current and previous sampling events, concentrations were generally higher, and more compounds were detected, at the high-use marina sites located most downstream on the lake. The consistent presence of a wide range of polycyclic aromatic hydrocarbons in the water of Lake Powell indicates chronic and (or) recent anthropogenic sources of contamination. The results from this study will provide the National Park Service with information necessary to determine if the current regulations on emission standards for personal watercraft used on Lake Powell are effective in lowering polycyclic aromatic hydrocarbon concentrations in the lake.
Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Calcium (Ca) is an essential element for almost all living organisms. Here, we examined global variation and controls of freshwater Ca concentrations, using 440 599 water samples from 43 184 inland water sites in 57 countries. We found that the global median Ca concentration was 4.0 mg L−1 with 20.7% of the water samples showing Ca concentrations ≤ 1.5 mg L−1, a threshold considered critical for the survival of many Ca-demanding organisms. Spatially, freshwater Ca concentrations were strongly and proportionally linked to carbonate alkalinity, with the highest Ca and carbonate alkalinity in waters with a pH around 8.0 and decreasing in concentrations towards lower pH. However, on a temporal scale, by analyzing decadal trends in >200 water bodies since the 1980s, we observed a frequent decoupling between carbonate alkalinity and Ca concentrations, which we attributed mainly to the influence of anthropogenic acid deposition. As acid deposition has been ameliorated, in many freshwaters carbonate alkalinity concentrations have increased or remained constant, while Ca concentrations have rapidly declined towards or even below pre-industrial conditions as a consequence of recovery from anthropogenic acidification. Thus, a paradoxical outcome of the successful remediation of acid deposition is a globally widespread freshwater Ca concentration decline towards critically low levels for many aquatic organisms.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-019-46838-w","usgsCitation":"Weyhenmeyer, G.A., Hartmann, J., Hessen, D.O., Kopáček, J., Hejzlar, J., Jacquet, S., Hamilton, S.K., Verburg, P., Leach, T.H., Schmid, M., Flaim, G., Nõges, T., Nõges, P., Wentzky, V.C., Rogora, M., Rusak, J.A., Kosten, S., Paterson, A.M., Teubner, K., Higgins, S.N., Lawrence, G.B., Kangur, K., Kokorite, I., Cerasino, L., Funk, C., Harvey, R.G., Moatar, F., Wit, H.D., and Zechmeister, T., 2019, Widespread diminishing anthropogenic effects on calcium in freshwaters: Scientific Reports, v. 9, 10450, 10 p., https://doi.org/10.1038/s41598-019-46838-w.","productDescription":"10450, 10 p.","ipdsId":"IP-101396","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":467443,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-46838-w","text":"Publisher Index 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The future of our blue planet is increasingly reliant on the services delivered by marine, coastal and inland waters and on the advancement of effective, evidence-based decisions on sustainable development. “Oceans and Society: Blue Planet” (hereafter denoted as “GEO Blue Planet”) is an initiative of the Group on Earth Observations (GEO) that aims to ensure the sustained development and use of ocean and coastal observations for the benefit of society. GEO Blue Planet works to advance and exploit synergies among the many observational programmes devoted to ocean and coastal waters; to improve engagement with a variety of stakeholders for enhancing the timeliness, quality and range of information delivered; and to raise awareness of the societal benefits of ocean observations at the public and policy levels. This paper summarizes the role of GEO Blue Planet, current activities and considerations for future directions.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/1755876X.2019.1634959","usgsCitation":"Smail, E.A., DiGiacomo, P., Seeave, S., Djavidnia, S., Celliers, L., Le Traon, P., Gault, J., Escobar-Briones, E., Plag, H., Pequignet, C., Bajona, L., Zhang, L., Pearlman, J., Steven, A., Hodge, J., Racault, F., Storlazzi, C.D., and Skirving, W., 2019, An introduction to the “Oceans and Society: Blue Planet” Initiative: Journal of Operational Oceanography, v. 12, no. suppl 2, p. s1-s11, https://doi.org/10.1080/1755876X.2019.1634959.","productDescription":"11 p.","startPage":"s1","endPage":"s11","ipdsId":"IP-100533","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":460327,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH4 flux measurements globally, initial results comparing CH4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH4 fluxes across sites ranged from −0.2 ± 0.02 g C m–2 yr–1 for an upland forest site to 114.9 ± 13.4 g C m–2 yr–1 for an estuarine freshwater marsh, with fluxes exceeding 40 g C m–2 yr–1 at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH4 flux across wetland sites globally. Water table position was positively correlated with annual CH4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH4 fluxes to ecosystem respiration increased significantly with mean site temperature. 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These trends suggest positive outcomes for tree health as related to reduced fine root mortality and nutrient loss associated with winter frost but negative outcomes as related to the northward advancement and proliferation of forest insect pests. In addition to effects on vegetation, reductions in cold temperatures and snow cover are likely to have negative impacts on the ecology of the northern forest through impacts on water, soils, and wildlife. The overall loss of coldness and snow cover may also have negative consequences for logging and forest products, vector-borne diseases and human health, recreation and tourism, and cultural practices, which together represent important social and economic dimensions for the northern forest region. These findings advance our understanding of how our changing winters may transform the socio- ecological system of a region that has been defined by the contrasting rhythm of the seasons. 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