The U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service, collected field and remotely sensed data on precipitation, evapotranspiration (ET), and soil-water content to determine available soil-water storage (AWS) at six study sites on sandy and clay soils in Cass County, North Dakota. Data were collected at all the study sites from May 1–October 31, 2016, and from May 1–October 24, 2017. Estimated daily AWS was determined using daily meteorological and potential evapotranspiration (PET) data obtained from various climate stations, and estimated monthly AWS was determined using monthly meteorological and PET data and monthly ET data determined using the Operational Simplified Surface Energy Balance model. AWS during 2016 and 2017 was determined at daily and monthly time steps because of data availability and to assess results using varying time steps. Comparisons of measured and estimated daily values of AWS at the Brewer Lake site indicated poor agreement during May–October 2016 and May–October 2017. Comparisons of measured and estimated daily values of AWS at the Embden East and Embden West sites indicated poor and fair agreement respectively. At the Lynchburg Crop and Lynchburg Grass sites, comparisons of measured and estimated daily values of AWS indicated fair and good relations, respectively, even with the possible effects of soil cracks. Mean estimated values of daily runoff plus soil percolation for the four sandy soil sites indicated that a maximum of about 19 percent of the estimated runoff plus soil percolation could be considered runoff and that the remaining 81 percent could be considered soil percolation, and for the two clay soil sites about 13 percent of the runoff plus soil percolation could have been considered runoff and about 87 percent could have been considered soil percolation. Results indicated little difference between using monthly PET or monthly ET in water-balance equations to estimate monthly AWS for the grouped sandy soil sites, and only slightly better results were obtained using monthly PET than monthly ET to estimate monthly AWS for the grouped clay soil study sites. Overall, the monthly water-balance models did not perform as well as the daily water-balance models for determining AWS at the six study sites. Additional data collection from a longer-period study and adjustments to the models may improve results from the monthly water-balance techniques.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195141","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service","usgsCitation":"Vining, K.C., 2020, Water-balance techniques for determining available soil-water storage for selected sandy and clay soil study sites in Cass County, North Dakota, 2016–17: U.S. Geological Survey Scientific Investigations Report 2019–5141, 39 p., https://doi.org/10.3133/sir20195141.","productDescription":"Report: vii, 39 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-098347","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":399616,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109584.htm"},{"id":371052,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GG2ILI","text":"USGS data 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Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
Physiological tolerances and biotic interactions along habitat gradients are thought to influence species occurrence. Distributional differences caused by such forces are particularly noticeable on tropical mountains, where high species turnover along elevational gradients occurs over relatively short distances and elevational distributions of particular species can shift among mountains. Such shifts are interpreted as evidence of the importance of spatial variation in interspecific competition and habitat or climatic gradients. To assess the relative importance of competition and compression of habitat and climatic zones in setting range limits, we examined differences in elevational ranges of forest bird species among four Bornean mountains with distinct features.
Bornean mountains Kinabalu, Mulu, Pueh and Topap Oso.
Rain forest bird communities along elevational gradients.
We surveyed the elevational ranges of rain forest birds on four mountains in Borneo to test which environmental variables—habitat zone compression or presence of likely competitors—best predicted differences in elevational ranges of species among mountains. For this purpose, we used two complementary tests: a comparison of elevational range limits between pairs of mountains, and linear mixed models with naïve occupancy as the response variable.
We found that lowland species occur higher in elevation on two small mountains compared to Mt. Mulu. This result is inconsistent with the expectation that distributions of habitats are elevationally compressed on small mountains, but is consistent with the hypothesis that a reduction in competition (likely diffuse) on short mountains, which largely lack montane specialist species, allows lowland species to occur higher in elevation. The relative influence of competition changes with elevation, and the correlation between lower range limits of montane species and the distribution of their competitors was weaker than in lowland species.
These findings provide support for the importance of biotic interactions in setting elevational range limits of tropical bird species, although abiotic gradients explain the majority of distribution patterns. Thus, models predicting range shifts under climate change scenarios must include not only climatic variables, as is currently most common, but also information on potentially resulting changes in species interactions, especially for lowland species.
","language":"English","publisher":"Wiley","doi":"10.1111/jbi.13784","usgsCitation":"Burner, R., Boyce, A., Bernasconi, D., Styring, A.R., Shakya, S.B., Boer, C., Rahman, M.A., Martin, T.E., and Sheldon, F.H., 2020, Biotic interactions help explain variation in elevational range limits of birds among Bornean mountains: Journal of Biogeography, v. 47, no. 3, p. 760-771, https://doi.org/10.1111/jbi.13784.","productDescription":"12 p.","startPage":"760","endPage":"771","ipdsId":"IP-107210","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":458196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jbi.13784","text":"Publisher Index Page"},{"id":379392,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia, Malaysia","otherGeospatial":"Borneo","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 119.17968749999999,\n 5.659718554577286\n ],\n [\n 116.89453125,\n 7.493196470122287\n ],\n [\n 113.5546875,\n 4.609278084409835\n ],\n [\n 111.09374999999999,\n 2.7235830833483856\n ],\n [\n 109.1162109375,\n 1.9771465537125772\n ],\n [\n 108.5888671875,\n 0.17578097424708533\n ],\n [\n 110.0830078125,\n -3.2063329870791315\n ],\n [\n 112.939453125,\n -3.90809888189411\n ],\n [\n 115.224609375,\n -4.258768357307995\n ],\n [\n 116.3232421875,\n -4.039617826768424\n ],\n [\n 118.95996093749999,\n 1.142502403706165\n ],\n [\n 117.7734375,\n 3.2940822283128175\n ],\n [\n 119.61914062499999,\n 5.134714634014467\n ],\n [\n 119.17968749999999,\n 5.659718554577286\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Burner, Ryan C. 0000-0002-7314-9506","orcid":"https://orcid.org/0000-0002-7314-9506","contributorId":243138,"corporation":false,"usgs":false,"family":"Burner","given":"Ryan C.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":801602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyce, Andy J.","contributorId":243139,"corporation":false,"usgs":false,"family":"Boyce","given":"Andy J.","affiliations":[{"id":48645,"text":"umt","active":true,"usgs":false}],"preferred":false,"id":801603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bernasconi, David","contributorId":243140,"corporation":false,"usgs":false,"family":"Bernasconi","given":"David","email":"","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":801604,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Styring, Alison R.","contributorId":243175,"corporation":false,"usgs":false,"family":"Styring","given":"Alison","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":801653,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shakya, Subir B.","contributorId":243141,"corporation":false,"usgs":false,"family":"Shakya","given":"Subir","email":"","middleInitial":"B.","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":801605,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boer, Chandradewana","contributorId":243142,"corporation":false,"usgs":false,"family":"Boer","given":"Chandradewana","email":"","affiliations":[{"id":48646,"text":"u m","active":true,"usgs":false}],"preferred":false,"id":801606,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rahman, Mustafa Abdul","contributorId":243143,"corporation":false,"usgs":false,"family":"Rahman","given":"Mustafa","email":"","middleInitial":"Abdul","affiliations":[{"id":48647,"text":"college sabah","active":true,"usgs":false}],"preferred":false,"id":801607,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Martin, Thomas E. 0000-0002-4028-4867 tmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-4028-4867","contributorId":1208,"corporation":false,"usgs":true,"family":"Martin","given":"Thomas","email":"tmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":801608,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sheldon, Frederick H.","contributorId":243144,"corporation":false,"usgs":false,"family":"Sheldon","given":"Frederick","email":"","middleInitial":"H.","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":801609,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70208125,"text":"70208125 - 2020 - Habitat of the endangered salt marsh harvest mouse (Reithrodontomys raviventris) in San Francisco Bay","interactions":[],"lastModifiedDate":"2020-02-06T11:44:25","indexId":"70208125","displayToPublicDate":"2020-01-07T16:40:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Habitat of the endangered salt marsh harvest mouse (Reithrodontomys raviventris) in San Francisco Bay","title":"Habitat of the endangered salt marsh harvest mouse (Reithrodontomys raviventris) in San Francisco Bay","docAbstract":"Understanding habitat associations is vital for conservation of at‐risk marsh‐endemic wildlife species, particularly those under threat from sea level rise. We modeled environmental and habitat associations of the marsh‐endemic, Federally endangered salt marsh harvest mouse (Reithrodontomys raviventris, RERA) and co‐occurrence with eight associated small mammal species from annual trap data, 1998–2014, in six estuarine marshes in North San Francisco Bay, California. Covariates included microhabitat metrics of elevation and vegetation species and cover; and landscape metrics of latitude–longitude, distance to anthropogenic features, and habitat patch size. The dominant cover was pickleweed (Salicornia pacifica) with 86% mean cover and 37 cm mean height, and bare ground with about 10% mean cover. We tested 38 variants of Bayesian network (BN) models to determine covariates that best account for presence of RERA and of all nine small mammal species. Best models had lowest complexity and highest classification accuracy. Among RERA presence models, three best BN models used covariates of latitude–longitude, distance to paved roads, and habitat patch size, with 0% error of false presence, 20% error of false nonpresence, and 20% overall error. The all‐species presence models suggested that within the pickleweed marsh environment, RERA are mostly habitat generalists. Accounting for presence of other species did not improve prediction of RERA. Habitat attributes compared between RERA and the next most frequently captured species, California vole (Microtus californicus), suggested substantial habitat overlap, with RERA habitat being somewhat higher in marsh elevation, greater in percent cover of the dominant plant species, closer to urban areas, further from agricultural areas, and, perhaps most significant, larger in continuous size of marsh patch. Findings will inform conservation management of the marsh environment for RERA by identifying best microhabitat elements, landscape attributes, and adverse interspecific interactions.
","language":"English","publisher":"Wiley-Blackwell","doi":"10.1002/ece3.5860","usgsCitation":"Marcot, B.G., Woo, I., Thorne, K., Freeman, C.M., and Guntenspergen, G.R., 2020, Habitat of the endangered salt marsh harvest mouse (Reithrodontomys raviventris) in San Francisco Bay: Ecology and Evolution, v. 0, no. 2, p. 662-677, https://doi.org/10.1002/ece3.5860.","productDescription":"16 p.","startPage":"662","endPage":"677","ipdsId":"IP-101159","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458198,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5860","text":"Publisher Index Page"},{"id":437176,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96Q5D2T","text":"USGS data release","linkHelpText":"Small mammal surveys from northern San Francisco Bay: 1998-2014"},{"id":371662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7117919921875,\n 37.82497195707114\n ],\n [\n -121.98669433593749,\n 37.82497195707114\n ],\n [\n -121.98669433593749,\n 38.190704293996504\n ],\n [\n -122.7117919921875,\n 38.190704293996504\n ],\n [\n -122.7117919921875,\n 37.82497195707114\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"0","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Marcot, Bruce G.","contributorId":152612,"corporation":false,"usgs":false,"family":"Marcot","given":"Bruce","email":"","middleInitial":"G.","affiliations":[{"id":18944,"text":"Pacific Northwest Research Station, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":780617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freeman, Chase M. 0000-0003-4211-6709 cfreeman@usgs.gov","orcid":"https://orcid.org/0000-0003-4211-6709","contributorId":150052,"corporation":false,"usgs":true,"family":"Freeman","given":"Chase","email":"cfreeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780619,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":780620,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70205181,"text":"ofr20191089 - 2020 - Remnant hardwood forest mapping within the Upper Mississippi River floodplain","interactions":[],"lastModifiedDate":"2022-04-21T18:41:17.216501","indexId":"ofr20191089","displayToPublicDate":"2020-01-07T13:45:00","publicationYear":"2020","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":"2019-1089","displayTitle":"Remnant Hardwood Forest Mapping within the Upper Mississippi River Floodplain","title":"Remnant hardwood forest mapping within the Upper Mississippi River floodplain","docAbstract":"The primary objective of the project was to locate previously unknown stands of mast-producing hardwood forest trees in the Upper Mississippi River floodplain using existing information. We located and mapped 399 previously unknown hardwood forest stands within the Mississippi River floodplain area of navigation pools 9, 10, and 11. Using color infrared images in combination with true-color imagery was useful for identifying hardwood forest stands. We recommend our result be refined by visiting the forest stands we identified to evaluate our classification rate and determine which stands are regenerating. In combination with regeneration information, our results can help better inform flood inundation modeling, which will help improve the efficacy of restoration design. Although we had some success using the best available information, to obtain more relevant observations, we recommend acquiring color infrared aerial imagery during the late fall season if providing detailed mapping of forest stands is a management priority. Imagery of this type collected in the fall, when trees may be distinguished by their differing senescence, has the potential to uniquely identify individual species or perhaps even individual trees. Gaining a better understanding of forest diversity and developing conservation strategies to preserve that diversity is timely because remaining aging trees, established before lock-and-dam installation on the Mississippi River, are nearing the end of their life expectancy.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191089","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Hanson, J.L., King, R., Hoy, E.E., 2019, Remnant hardwood forest mapping within the Upper Mississippi River floodplain: U.S. Geological Survey Open-File Report 2019–1089, 10 p., https://doi.org/10.3133/ofr20191089.","productDescription":"Report: vi, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-102264","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":399413,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109582.htm"},{"id":370698,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1089/ofr20191089.pdf","text":"Report","size":"4.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1089"},{"id":370697,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1089/coverthb.jpg"},{"id":370699,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TD9WNW","text":"USGS data release","description":"USGS Data Release","linkHelpText":"FWS McGregor District Mast Hardwood Floodplain Forest Community"}],"country":"United States","state":"Iowa, Minnesota, Wisconsin","otherGeospatial":"Upper Mississippi floodplain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.42822265625,\n 43.67581809328341\n ],\n [\n -91.5380859375,\n 43.6599240747891\n ],\n [\n -91.49414062499999,\n 43.48481212891603\n ],\n [\n -91.60400390625,\n 43.100982876188546\n ],\n [\n -91.2744140625,\n 42.65012181368022\n ],\n [\n -90.81298828125,\n 42.52069952914966\n ],\n [\n -90.37353515625,\n 42.52069952914966\n ],\n [\n -90.68115234375,\n 42.97250158602597\n ],\n [\n -90.72509765625,\n 43.30919109985686\n ],\n [\n -91.01074218749999,\n 43.61221676817573\n ],\n [\n -91.42822265625,\n 43.67581809328341\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54602
Geothermal energy is a global renewable resource that has the potential to provide a significant portion of baseload energy in many regions. In the United States, it has the potential to provide 8.5% of the electric generation capacity by the middle of the century. In general, geothermal systems require heat, permeability, and water to be viable for energy generation. However, with current technologies, only heat is strictly necessary in a native system. Engineered geothermal systems (EGS) introduce water into the subsurface at elevated pressures and reduced temperatures and enhance permeability through hydraulic and/or shear fracturing. Additionally, although moderate- to high-temperature resources currently dominate geothermal energy production, low-temperature resources have been utilized for direct-use cases. When well balanced and maintained, geothermal resources can produce significant amounts of heat and achieve long-term sustainability on the order of an estimated tens to hundreds of years.
Federal agencies need credible scientific information to determine the production and value of ecosystem services in an efficient and timely manner. The U.S. Geological Survey addresses this scientific information need through the Sustaining Environmental Capital Initiative project. The project has relied on U.S. Geological Survey expertise related to water, fisheries, advanced modeling, and economics and other social sciences to conduct eight case studies across a range of environment types, including water-based environments, deserts, sagebrush ecosystems, floodplains, and forests. The Sustaining Environmental Capital Initiative also supported the development and expansion of four tools with the intent of adding content and usability for partners’ decision-making needs. The tools are the Natural Value Resource Center, Benefit Transfer Toolkit, Riverine Environmental Flow Decision Support System, and Artificial Intelligence for Ecosystem Services modeling platform.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191117","usgsCitation":"Huber, C., Meldrum, J.R., Schuster, R.M., Ancona, Z.H., Bagstad, K.J., Beck, S.M., Carlisle, D.M., Claggett, P.R., Franco, F., Galbraith, H.S., Haefele, M., Hoelting, K.R., Hogan, D.M., Hopkins, K.G., Kern, T., Lawrence, C.B., Lischka, S., Loomis, J.B., Mueller, J.M., Noe, G.B., Pindilli, E.J., Quay, B., Semmens, D.J., Sinclair, W., Spooner, D.E., Voigt, B., and St. John White, B., 2020, Sustaining Environmental Capital Initiative summary report: U.S. Geological Survey Open-File Report 2019–1117, 23 p., https://doi.org/10.3133/ofr20191117.","productDescription":"v, 23 p.","onlineOnly":"Y","ipdsId":"IP-099772","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":370958,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1117/ofr20191117.pdf","text":"Report","size":"348 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1117"},{"id":370957,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1117/coverthb.jpg"}],"contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
Majuro Atoll in the central Pacific has high coastal vulnerability due to low-lying islands, rising sea level, high wave events, eroding shorelines, a dense population center, and limited freshwater resources. Land elevation is the primary geophysical variable that determines exposure to inundation in coastal settings. Accordingly, coastal elevation data (with accuracy information) are critical for assessments of inundation exposure. Previous research has demonstrated the importance of using high-accuracy elevation data and rigorously accounting for uncertainty in inundation assessments. A quantitative analysis of inundation exposure was conducted for Majuro Atoll, including accounting for the cumulative vertical uncertainty from the input digital elevation model (DEM) and datum transformation. The project employed a recently produced and validated DEM derived from structure-from-motion processing of very-high-resolution aerial imagery. Areas subject to marine inundation (direct hydrologic connection to the ocean) and low-lying lands (disconnected hydrologically from the ocean) were mapped and characterized for three inundation levels using deterministic and probabilistic methods. At the highest water level modeled (3.75 ft, or 1.143 m), more than 34% of the atoll study area is likely to be exposed to inundation (68% chance or greater), while more than 20% of the atoll is extremely likely to be exposed (95% chance or greater). The study demonstrates the substantial value of a high-accuracy DEM for assessing inundation exposure of low-relief islands and the enhanced information from accounting for vertical uncertainty.
","language":"English","publisher":"MDPI","doi":"10.3390/rs12010154","usgsCitation":"Gesch, D.B., Palaseanu-Lovejoy, M., Danielson, J.J., Fletcher, C., Kottermair, M., Barbee, M., and Jalandoni, A., 2020, Inundation exposure assessment for Majuro Atoll, Republic of the Marshall Islands using a high-accuracy digital elevation model: Remote Sensing, v. 12, no. 1, Article: 154, 20 p.; Data Release, https://doi.org/10.3390/rs12010154.","productDescription":"Article: 154, 20 p.; Data Release","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":458218,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12010154","text":"Publisher Index Page"},{"id":372951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":373335,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5ba9511ee4b08583a5ca09fe","text":"USGS data release","description":"USGS data release","linkHelpText":"Inundation exposure assessment for Majuro Atoll, Republic of the Marshall Islands"}],"country":"Republic of the Marshall Islands","otherGeospatial":"Majuro Atoll","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 170.98777770996094,\n 6.976183516197836\n ],\n [\n 171.43203735351562,\n 6.976183516197836\n ],\n [\n 171.43203735351562,\n 7.198319490613516\n ],\n [\n 170.98777770996094,\n 7.198319490613516\n ],\n [\n 170.98777770996094,\n 6.976183516197836\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":784036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":784037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":784038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fletcher, Charles","contributorId":192304,"corporation":false,"usgs":false,"family":"Fletcher","given":"Charles","affiliations":[],"preferred":false,"id":784039,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kottermair, Maria","contributorId":119958,"corporation":false,"usgs":true,"family":"Kottermair","given":"Maria","email":"","affiliations":[],"preferred":false,"id":784040,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barbee, Matthew 0000-0002-8929-7255","orcid":"https://orcid.org/0000-0002-8929-7255","contributorId":196651,"corporation":false,"usgs":false,"family":"Barbee","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":784041,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jalandoni, Andrea 0000-0002-4821-7183","orcid":"https://orcid.org/0000-0002-4821-7183","contributorId":196653,"corporation":false,"usgs":false,"family":"Jalandoni","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":784042,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70211340,"text":"70211340 - 2020 - Using conceptual models to relate multiparameter satellite data to subsurface volcanic processes in Latin America","interactions":[],"lastModifiedDate":"2020-09-01T13:54:44.456524","indexId":"70211340","displayToPublicDate":"2020-01-05T10:07:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Using conceptual models to relate multiparameter satellite data to subsurface volcanic processes in Latin America","docAbstract":"Satellite data have been extensively used to identify volcanic behavior. However, the physical subsurface processes causing any individual manifestation of activity can be ambiguous. We propose a classification scheme for the cause of unrest that simultaneously considers three multiparameter satellite observations. The scheme is based on characteristics of the volcanic system (open, closed, and eruptive) and unrest mechanisms (intrusion, evolution, and withdrawal) occurring at shallow depths in the volcanic system. We applied these models to satellite observations acquired at 47 of the most active volcanoes in Latin America. Of the volcanoes studied, 44 had a robust enough dataset for classification and were clustered into 4 groups and 10 subgroups with common behavioral characteristics. By identifying that these volcanoes can be clustered into a number of groupings significantly less than the number of volcanoes, we have demonstrated that commonalities in behavior patterns exist among diverse volcanic systems. Identifying volcanoes with similar characteristics underpins the use of past observations at one volcano to forecast activity at another and diverges from typical volcanic groupings, which are focused on geologic parameters (i.e., composition, volcano type, and tectonic setting). Based on satellite data alone, we have identified preeruptive intrusion prior to 15 eruptions at 12 different volcanoes, magma evolution prior to 18 eruptions at 13 volcanoes, and magma withdrawal at 3 eruptions and 3 volcanoes. Improvements to the spatial and temporal resolution are needed to make these relations robust. This classification scheme provides a framework for future automated clustering of volcanoes.
A common idea in the discussion of soil carbon processes is that litter decomposition rates and soil carbon stocks are inversely related. To test this overall hypothesis, simultaneous studies were conducted of the relationship of environmental gradients to leaf and wood decomposition, buried cloth decomposition and percent soil organic matter in Taxodium distichum swamps across the Mississippi River Alluvial Valley (MRAV) and northern Gulf of Mexico (GOM) of the US. Decomposition of leaf tissue was 6.2 to 10.9 times faster than wood tissue. Both precipitation and flooding gradients were negatively related to leaf and wood litter decomposition rates based on models developed using Stepwise General Model Selection (MRAV vs. GOM, respectively). Cotton cloth should not be used as a proxy for plant litter without prior testing because cloth responded differently than plant litter to regional environmental gradients in T. distichum swamps. The overall hypothesis was supported in the MRAV because environments with higher precipitation (climate normal) had lower rates of decomposition and higher percent soil organic matter. In the MRAV, higher levels of percent soil organic matter were related to increased 30-year climate normals (30 year averages of precipitation and air temperature comprising southward increasing PrinComp1). Soil organic carbon % in inland vs. coastal T. distichum forests of the MRAV were comparable (range = 1.5% to 26.9% vs. 9.8 to 31.5%, respectively). GOM swamps had lower rates of litter decomposition in more flooded environments. Woody T. distichum detritus had a half-life of up to 300 years in the MRAV, which points to its likely role in the maintenance of inland “teal” soil organic carbon. This unique study can contribute to the discussion of approaches to maintain environments conducive to soil carbon stock maximization.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0226998","usgsCitation":"Middleton, B.A., 2020, Trends of litter decomposition and soil organic matter stocks across forested swamp environments of the southeastern US: PLoS ONE, v. 15, no. 1, e0226998, 23 p., https://doi.org/10.1371/journal.pone.0226998.","productDescription":"e0226998, 23 p.","ipdsId":"IP-085013","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":458237,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0226998","text":"Publisher Index Page"},{"id":371401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Florida, Illinois, Louisiana, Mississippi, Missouri, Texas","otherGeospatial":"Mississippi River Alluvial Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.24218749999999,\n 37.78808138412046\n ],\n [\n -90.17578124999999,\n 37.055177106660814\n ],\n [\n -91.7578125,\n 34.52466147177172\n ],\n [\n -92.5048828125,\n 30.977609093348686\n ],\n [\n -90.2197265625,\n 28.65203063036226\n ],\n [\n -88.9013671875,\n 29.036960648558267\n ],\n [\n -89.20898437499999,\n 29.84064389983441\n ],\n [\n -91.01074218749999,\n 31.203404950917395\n ],\n [\n -88.06640625,\n 37.055177106660814\n ],\n [\n -88.24218749999999,\n 37.78808138412046\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.15234375,\n 29.38217507514529\n ],\n [\n -93.8232421875,\n 29.38217507514529\n ],\n [\n -93.8232421875,\n 31.240985378021307\n ],\n [\n -96.15234375,\n 31.240985378021307\n ],\n [\n -96.15234375,\n 29.38217507514529\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.814453125,\n 29.458731185355344\n ],\n [\n -83.583984375,\n 29.458731185355344\n ],\n [\n -83.583984375,\n 30.56226095049944\n ],\n [\n -84.814453125,\n 30.56226095049944\n ],\n [\n -84.814453125,\n 29.458731185355344\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth A. 0000-0002-1220-2326 middletonb@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":2029,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","email":"middletonb@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":779850,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70208716,"text":"70208716 - 2020 - Formation and prevention of pipe scale from acid mine drainage at Iron Mountain and Leviathan Mines, California, USA","interactions":[],"lastModifiedDate":"2020-02-25T15:17:36","indexId":"70208716","displayToPublicDate":"2020-01-03T15:14:46","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Formation and prevention of pipe scale from acid mine drainage at Iron Mountain and Leviathan Mines, California, USA","docAbstract":"Pipelines carrying acid mine drainage (AMD) to treatment plants commonly form pipe scale, an Fe(III)-rich precipitate that forms inside the pipelines and requires periodic and costly cleanout and maintenance. Pipelines at Iron Mountain Mine (IMM) and Leviathan Mine (LM) in California carry acidic water from mine sources to a treatment plant and have developed pipe scale. Samples of scale and AMD were collected from both mine sites for mineralogical, microbiological, and chemical analysis. The scale mineralogy was primarily schwertmannite with minor amounts of poorly crystalline goethite. Although the bulk composition of the scale was similar along the length of the pipeline at IMM, the number of iron-oxidizing bacteria and concentrations of associated trace elements decreased along the flow-path inside the pipeline. Laboratory batch experiments with unfiltered AMD from IMM and LM showed that Fe(II) oxidation was driven by microbial activity when the pH was <5. A remediation strategy of decreasing the pH to <2.2 was tested through geochemical modeling and laboratory experiments. These experiments indicated that scale formation could be prevented by decreasing the pH, which could be achieved at IMM by mixing source waters. However, the presence of Fe(III)-rich scale in a pipeline buffers the pH to higher values that may affect the efficacy of this remedial approach.","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2020.104521","usgsCitation":"Campbell, K.M., Alpers, C.N., and Nordstrom, D.K., 2020, Formation and prevention of pipe scale from acid mine drainage at Iron Mountain and Leviathan Mines, California, USA: Applied Geochemistry, v. 115, 104521, 14 p. , https://doi.org/10.1016/j.apgeochem.2020.104521.","productDescription":"104521, 14 p. ","ipdsId":"IP-105776","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":458240,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2020.104521","text":"Publisher Index Page"},{"id":372639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Iron Mountain and Leviathan Mines","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.10455322265625,\n 40.065460682065535\n ],\n [\n -122.53875732421875,\n 40.065460682065535\n ],\n [\n -122.53875732421875,\n 40.6723059714534\n ],\n [\n -123.10455322265625,\n 40.6723059714534\n ],\n [\n -123.10455322265625,\n 40.065460682065535\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.16296386718749,\n 38.03078569382294\n ],\n [\n -118.9215087890625,\n 38.03078569382294\n ],\n [\n -118.9215087890625,\n 38.6897975322717\n ],\n [\n -120.16296386718749,\n 38.6897975322717\n ],\n [\n -120.16296386718749,\n 38.03078569382294\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"115","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":783148,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783149,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":783150,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211922,"text":"70211922 - 2020 - Estimating bedload from suspended load and water discharge in sand bed rivers","interactions":[],"lastModifiedDate":"2020-08-11T20:13:57.981854","indexId":"70211922","displayToPublicDate":"2020-01-03T15:10:09","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Estimating bedload from suspended load and water discharge in sand bed rivers","docAbstract":"Estimates of fluvial sediment discharge from in situ instruments are an important component of large‐scale sediment budgets that track long‐term geomorphic change. Suspended sediment load can be reliably estimated using acoustic or physical sampling techniques; however, bedload is difficult to measure directly and can consequently be one of the largest sources of uncertainty in estimates of total load. We propose a physically informed predictive empirical model for bedload sand flux as a function of variables that are measured using existing acoustic or physical sampling techniques. This model depends on the assumption that concentration and grain size in suspension are in equilibrium with reach‐averaged boundary conditions. Bayesian inference is used to fit model parameters to data from eight sand‐bed rivers and to simulate bedload flux over the available gage record at one site on the Colorado River in Grand Canyon National Park. We find that the cumulative bedload flux during the 9 year period from 2008 to 2016 was 5% of the cumulative suspended sand load; however, instantaneous bedload flux ranged from as little as 1% of instantaneous suspended sand load to as much as 75% of instantaneous suspended sand load due to fluctuations in flow strength and sediment supply. Changes in bedload flux at a constant discharge are indicative of short‐term sediment supply enrichment and depletion. Long‐term average bedload flux cannot be expected to remain constant in the future as the river adjusts to changes in sediment runoff and the dam‐regulated discharge regime.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019WR025883","usgsCitation":"Ashley, T., McElroy, B., Buscombe, D., Grams, P.E., and Kaplinski, M., 2020, Estimating bedload from suspended load and water discharge in sand bed rivers: Water Resources Research, v. 56, no. 2, e2019WR025883, 25 p., https://doi.org/10.1029/2019WR025883.","productDescription":"e2019WR025883, 25 p.","ipdsId":"IP-108262","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":458242,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/essoar.10503756.1","text":"External Repository"},{"id":377386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.005126953125,\n 35.71083783530009\n ],\n [\n -111.37390136718749,\n 35.71083783530009\n ],\n [\n -111.37390136718749,\n 36.92793899776678\n ],\n [\n -114.005126953125,\n 36.92793899776678\n ],\n [\n -114.005126953125,\n 35.71083783530009\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Ashley, T.C.","contributorId":238017,"corporation":false,"usgs":false,"family":"Ashley","given":"T.C.","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":795824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McElroy, B.","contributorId":23797,"corporation":false,"usgs":true,"family":"McElroy","given":"B.","email":"","affiliations":[],"preferred":false,"id":795825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buscombe, D.","contributorId":44020,"corporation":false,"usgs":true,"family":"Buscombe","given":"D.","email":"","affiliations":[],"preferred":false,"id":795826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grams, Paul E. 0000-0002-0873-0708","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":216115,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":795827,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaplinski, M.","contributorId":31576,"corporation":false,"usgs":true,"family":"Kaplinski","given":"M.","email":"","affiliations":[],"preferred":false,"id":795828,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70264996,"text":"70264996 - 2020 - A model for the growth and development of wave-dominated deltas fed by small mountainous rivers: Insights from the Elwha River delta, Washington","interactions":[],"lastModifiedDate":"2025-03-27T15:25:17.624368","indexId":"70264996","displayToPublicDate":"2020-01-03T10:20:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3369,"text":"Sedimentology","active":true,"publicationSubtype":{"id":10}},"title":"A model for the growth and development of wave-dominated deltas fed by small mountainous rivers: Insights from the Elwha River delta, Washington","docAbstract":"Observations from ground-penetrating radar, sediment cores, elevation surveys and aerial imagery are used to understand the development of the Elwha River delta in north-western Washington, USA, which prograded as a result of two dam removals in late 2011. Swash-bar, foreshore and swale depositional elements are recognized within ground-penetrating radar profiles and sediment cores. A model for the growth and development of small mountainous river wave-dominated deltas is proposed based on observation of both the fluvial and deltaic settings. If enough sediment is available in the fluvial system, mouth-bars form after higher than average river discharge events, creating a large platform seaward of the subaqueous delta plain. Swash-bars form concurrently or within a month of mouth-bar deposition as a result of wave action. Fair-weather waves drive swash-bar migration landward and in the direction of littoral drift. The signature of swash-bar welding to the shoreline is landward-dipping reflections, as a result of overwash processes and slipface migration. However, most swash-bars are eroded by the river mouth, as only 10 of the 37 swash-bars that formed between August 2011 and July 2016 survived within the Elwha River delta. The swash-bars that do survive either amalgamate onto the shoreline or an earlier deposited swash-bar, forming a single larger barrier at the delta front. In asymmetrical deltas, the signature of swash-bar welding is more likely to be preserved on the downdrift side of the delta, where formation is more likely and accommodation behind newer swash-bars preserves older deposits. On small mountainous river deltas, welded swash-bars may be more indicative of a large sediment pulse to the system, rather than large hydrological events.
","language":"English","publisher":"Wiley","doi":"10.1111/sed.12702","usgsCitation":"Zurbuchen, J., Simms, A., Warrick, J.A., Miller, I.M., and Ritchie, A., 2020, A model for the growth and development of wave-dominated deltas fed by small mountainous rivers: Insights from the Elwha River delta, Washington: Sedimentology, v. 67, no. 5, p. 2310-2331, https://doi.org/10.1111/sed.12702.","productDescription":"22 p.","startPage":"2310","endPage":"2331","ipdsId":"IP-091098","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/sed.12702","text":"Publisher Index Page"},{"id":483949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.53500604047304,\n 48.153518237078885\n ],\n [\n -123.57618620014911,\n 48.153518237078885\n ],\n [\n -123.57618620014911,\n 48.12519411609762\n ],\n [\n -123.53500604047304,\n 48.12519411609762\n ],\n [\n -123.53500604047304,\n 48.153518237078885\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"67","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Zurbuchen, Julie","contributorId":352837,"corporation":false,"usgs":false,"family":"Zurbuchen","given":"Julie","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":932190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simms, Alexander R.","contributorId":352838,"corporation":false,"usgs":false,"family":"Simms","given":"Alexander R.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":932191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":932192,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Ian M. 0000-0002-3289-6337","orcid":"https://orcid.org/0000-0002-3289-6337","contributorId":41951,"corporation":false,"usgs":false,"family":"Miller","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":932193,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ritchie, Andrew C. 0000-0001-5826-9983","orcid":"https://orcid.org/0000-0001-5826-9983","contributorId":333630,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":932194,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208538,"text":"70208538 - 2020 - Patterns of denitrification potential in tidal freshwater forested wetlands","interactions":[],"lastModifiedDate":"2020-02-14T09:52:26","indexId":"70208538","displayToPublicDate":"2020-01-02T09:48:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Patterns of denitrification potential in tidal freshwater forested wetlands","docAbstract":"Limited evidence for spatial patterns of denitrification in tidal freshwater forested wetlands (TFFWs), seemingly due to high spatial variability in the process, is surprising considering the various spatial gradients of its biogeochemical and hydrogeomorphic controls in these ecosystems. Because certain physical environmental gradients may be useful for the prediction of denitrification in TFFWs, we measured denitrification and ecosystem attributes in hummock-hollow microtopography of TFFWs along longitudinal riverine positions (upper, middle, and lower tidal river sites, and nearby upstream nontidal forested floodplains) of the adjoining Pamunkey and Mattaponi Rivers, Virginia. We tested differences by river, site, and plot in denitrification enzyme activity (DEA) and substrate limitations of denitrification potential (DP). The Pamunkey River carries greater river nitrate concentrations, and we found less nitrate limitation of DP and greater soil nitrate in hollows of this river. DEA in tidal hummocks was positively correlated with soil organic matter, nitrogen, and carbon, with the highest rates in lower tidal sites. Hummocks also promoted greater oxygen-controlled substrate limitation of DP, whereby experimental aeration stimulated DP under subsequent inundation more in hummocks than hollows. Additionally, tidal sites had greater DEA than nontidal sites, inferred to be caused by a combination of higher moisture, organic, and nutrient content. Our results indicate that the increasing nitrogen concentrations in these rivers will increase denitrification more on the Mattaponi River by alleviating its greater nitrogen limitation compared to the Pamunkey River, and modification to sedimentation, inundation, or microtopography from sea level rise may alter denitrification gradients in TFFWs and upstream low-elevation nontidal floodplains.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-019-00663-6","usgsCitation":"Korol, A.R., and Noe, G.E., 2020, Patterns of denitrification potential in tidal freshwater forested wetlands, v. 43, no. 2, p. 329-346, https://doi.org/10.1007/s12237-019-00663-6.","productDescription":"18 p.","startPage":"329","endPage":"346","ipdsId":"IP-103254","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":372341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Mattaponi River, Pamunkey River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.31903076171875,\n 37.44106442458557\n ],\n [\n -76.76010131835938,\n 37.44106442458557\n ],\n [\n -76.76010131835938,\n 37.86943313301452\n ],\n [\n -77.31903076171875,\n 37.86943313301452\n ],\n [\n -77.31903076171875,\n 37.44106442458557\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Korol, Alicia R.","contributorId":174405,"corporation":false,"usgs":false,"family":"Korol","given":"Alicia","email":"","middleInitial":"R.","affiliations":[{"id":27449,"text":"Department of Environmental Science and Policy, George Mason University, 4400 University Drive, Fairfax, VA, 22030","active":true,"usgs":false}],"preferred":false,"id":782341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":782340,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70226609,"text":"70226609 - 2020 - Planktic foraminiferal test size and weight response to the late Pliocene environment","interactions":[],"lastModifiedDate":"2024-09-16T22:40:08.160059","indexId":"70226609","displayToPublicDate":"2020-01-02T07:05:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5790,"text":"Paleoceanography and Paleoclimatology","active":true,"publicationSubtype":{"id":10}},"title":"Planktic foraminiferal test size and weight response to the late Pliocene environment","docAbstract":"Atmospheric carbon dioxide (pCO2atm) is impacting the ocean and marine organisms directly via changes in carbonate chemistry and indirectly via a range of changes in physical parameters most dominantly temperature. To assess potential impacts of climate change on carbonate production in the open ocean, we measured size and weight of planktic foraminifers during the late Pliocene at pCO2atm concentrations comparable to today and global temperatures 2 to 3 °C warmer. Size of all foraminifers was measured at Atlantic Ocean Deep Sea Drilling Project (DSDP) Site 610, Ocean Drilling Program (ODP) Site 999, and Integrated Ocean Drilling Program (IODP) Site U1313. Test size was smaller during the Pliocene than in modern assemblages under the same environmental conditions. During the cold marine isotope stage (MIS) M2, size increased at Site 999, potentially linked to intensified stratification of the surface ocean in response to the closure of the Central American Seaway. At Site U1313, test size tracks the warming throughout the late Pliocene. Size-normalized weight (SNW) of Globigerina bulloides at Site U1313 decreased during warmer temperature intervals. SNW of Globigerinoides ruber (white) at Site 999 displays high-frequency variability not correlated to temperature. Yet during the glacial period within MIS M2, test weight was higher during higher temperatures. Our results support studies in the modern ocean, which challenge the view that carbonate chemistry is the primary driver for calcification. To better understand processes driving changes in SNW, computer tomography was used to quantify calcite to volume ratios. During interglacial periods, lower calcite volume but higher test volume suggests less suitable conditions for calcification. As this signal is not evident in SNW, subtle changes in calcification might not be observed by the weight-based method.
Pacific capelin Mallotus catervarius are planktivorous, small pelagic fish that serve an intermediate trophic role in marine food webs. Due to the lack of a directed fishery or monitoring of capelin in the Northeast Pacific, there is limited information on their distribution and abundance, and how spatio-temporal fluctuations in capelin density affects their availability as prey. To provide information on life history, spatial patterns, and population dynamics of capelin in the Gulf of Alaska (GOA), we modeled distributions of spawning habitat and larval dispersal, and synthesized spatially-indexed data from multiple, independent sources from 1996 to 2016. Potential capelin spawning areas were broadly distributed across the GOA. Models of larval drift show the GOA’s advective circulation patterns disperse capelin larvae over the continental shelf and upper slope, indicating potential connections between spawning areas and observed offshore distributions that are influenced by the location and timing of spawning. Spatial overlap in composite distributions of larval and age-1+ fish was used to identify core areas where capelin consistently occur and concentrate. Capelin primarily occupy shelf waters near the Kodiak Archipelago, and are patchily distributed across the GOA shelf and inshore waters. Interannual variations in abundance along with spatio-temporal differences in density indicates the availability of capelin to predators and monitoring surveys is highly variable in the GOA. We demonstrate that the limitations of individual data series can be compensated for by integrating multiple data sources to monitor fluctuations in distributions and abundance trends of an ecologically important species across a large marine ecosystem.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/meps13211","usgsCitation":"David W. McGowan, Goldstein, E., Arimitsu, M.L., Dreary, A., Ormseth, O., DeRobertis, A., Horne, J., Lauren Rogers, Wilson, M., Coyle, K., Holderied, K., Piatt, J.F., Stockhausen, W., and Stephani Zador, 2020, Spatial and temporal dynamics of Pacific capelin Mallotus catervarius in the Gulf of Alaska: Implications for ecosystem-based fisheries management: Marine Ecology Progress Series, v. 637, p. 117-140, https://doi.org/10.3354/meps13211.","productDescription":"24 p.","startPage":"117","endPage":"140","ipdsId":"IP-109292","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":458260,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/54053","text":"External Repository"},{"id":437180,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96XJDK3","text":"USGS data release","linkHelpText":"Inshore Catch Data for Capelin (Mallotus villosus) in the Gulf of Alaska 1996-2017"},{"id":372202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.017578125,\n 55.52863052257191\n ],\n [\n -134.912109375,\n 55.52863052257191\n ],\n [\n -134.912109375,\n 59.93300042374631\n ],\n [\n -153.017578125,\n 59.93300042374631\n ],\n [\n -153.017578125,\n 55.52863052257191\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"637","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"David W. McGowan","contributorId":222299,"corporation":false,"usgs":false,"family":"David W. McGowan","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":781827,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldstein, Esther","contributorId":222300,"corporation":false,"usgs":false,"family":"Goldstein","given":"Esther","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":781826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dreary, Alison","contributorId":222301,"corporation":false,"usgs":false,"family":"Dreary","given":"Alison","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ormseth, Olav","contributorId":222302,"corporation":false,"usgs":false,"family":"Ormseth","given":"Olav","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781830,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeRobertis, Alex","contributorId":222303,"corporation":false,"usgs":false,"family":"DeRobertis","given":"Alex","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781831,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Horne, John","contributorId":222304,"corporation":false,"usgs":false,"family":"Horne","given":"John","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":781832,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lauren Rogers","contributorId":222305,"corporation":false,"usgs":false,"family":"Lauren Rogers","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781833,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wilson, Matt","contributorId":222306,"corporation":false,"usgs":false,"family":"Wilson","given":"Matt","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781834,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Coyle, Kenneth","contributorId":222307,"corporation":false,"usgs":false,"family":"Coyle","given":"Kenneth","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":781835,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Holderied, Kris","contributorId":222308,"corporation":false,"usgs":false,"family":"Holderied","given":"Kris","affiliations":[{"id":40515,"text":"NOAA Kasitsna Bay Lab","active":true,"usgs":false}],"preferred":false,"id":781836,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":781837,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stockhausen, W.T.","contributorId":31952,"corporation":false,"usgs":true,"family":"Stockhausen","given":"W.T.","email":"","affiliations":[],"preferred":false,"id":781987,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Stephani Zador","contributorId":222309,"corporation":false,"usgs":false,"family":"Stephani Zador","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781838,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70216693,"text":"70216693 - 2020 - Improving predictions of water supply in the Rio Grande under changing climate conditions","interactions":[],"lastModifiedDate":"2021-02-18T16:04:26.417642","indexId":"70216693","displayToPublicDate":"2020-01-01T10:02:20","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5883,"text":"Cooperator Report","active":true,"publicationSubtype":{"id":1}},"title":"Improving predictions of water supply in the Rio Grande under changing climate conditions","docAbstract":"This product is a case study summarizing the original work authored by David Gutzler, Shaleene Chavarria, and Nels Bjarke. The content will be part of a collection of Case Studies shared via the Collaborative Conservation and Adaptation Strategy Toolbox (CCAST). The research featured in this case study is an analysis of historical observations and climate models developed by the US Bureau of Reclamation. The work aims to identify changes to streamflow predictability, assess future predictability, and inform the development of more reliable water supply outlooks essential for planning purposes in the Upper Rio Grande Basin.","language":"English","publisher":"CCAST","usgsCitation":"Casarez, I.R., 2020, Improving predictions of water supply in the Rio Grande under changing climate conditions: Cooperator Report, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-123347","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":383316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383315,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://usbr.maps.arcgis.com/apps/MapSeries/index.html?appid=e1174c82d65f4124872bb1fe1efa9c3b"}],"country":"United States","state":"Colorado, New Mexico","otherGeospatial":"Upper Rio Grande River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.55639648437499,\n 36.155617833818525\n ],\n [\n -104.96337890625,\n 36.155617833818525\n ],\n [\n -104.96337890625,\n 37.75334401310656\n ],\n [\n -106.55639648437499,\n 37.75334401310656\n ],\n [\n -106.55639648437499,\n 36.155617833818525\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Casarez, Ilana Renae 0000-0001-7690-3802","orcid":"https://orcid.org/0000-0001-7690-3802","contributorId":228961,"corporation":false,"usgs":true,"family":"Casarez","given":"Ilana","email":"","middleInitial":"Renae","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":805902,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70270769,"text":"70270769 - 2020 - Understanding the impacts of surface-groundwater conditions on stream fishes under altered baseflow conditions","interactions":[],"lastModifiedDate":"2025-08-27T14:30:09.606834","indexId":"70270769","displayToPublicDate":"2020-01-01T09:18:33","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"CSS-136-2020","title":"Understanding the impacts of surface-groundwater conditions on stream fishes under altered baseflow conditions","docAbstract":"Persistence of aquatic fauna depends on the conditions and connectivity of surface water and groundwater. In light of altered baseflows and both current and future predicted increases in stream temperatures, it is important to assess current thermal conditions, examine thermal responses of aquatic fauna, and evaluate water-management practices. Our study objectives were to determine (1) how changes in baseflow levels in the Kiamichi River influence hyporheic exchange, which correspondingly influences temperature at the reach scale; (2) temperature tolerances of stream fishes as a means for predicting how habitat complexity influences stream-fish populations; and (3) assess how dam releases influence the downstream temperature and dissolved oxygen regime during the low-flow period. We quantified hyporheic exchange at four reaches and, as expected, found higher groundwater exchange via transient storage occurred at the upstream sites. The net groundwater flux estimation was negative for the majority of reaches indicating that surface water is lost to groundwater during summer (i.e., losing), baseflow conditions. We determined critical thermal maximum (CTMax) for 17 stream fishes and thermal tolerances ranged 32-38°C. We determined the average thermal tolerance for two habitat fish guilds to calculate changes in thermal stress due to hypothetical reservoir release scenarios. We developed a process-based Water Quality Analysis Simulation Program model to predict downstream temperature conditions over 74-km of river in response to reservoir releases that corresponded to discharges of 0.00 (control), 0.34, 0.59, 0.76, 1.13, and 1.50 m3/s. Based on the dissolved oxygen conditions observed in 2015 and 2017 and biological oxygen demand sampling results, reservoir releases did not directly reduce dissolved oxygen concentrations in the Kiamichi River (though dissolved oxygen concentrations are limited to current water-release strategies by the managing agency). We simulated three scenarios using three water-release temperatures: 27.64°C, 26.00°C and 24.07°C that corresponded to average reservoir temperatures at gate locations on the dam. We compared the predicted temperature time series with CTMax of two fish-habitat guilds to quantify the cumulative time when stream fishes experienced severe thermal stress downstream from Sardis Reservoir. According to our simulations, reservoir releases would be capable of regulating downstream water temperature during the summer baseflow period. The 0.00 m3/s scenario resulted in 130 h of thermal stress for benthic fishes, and 73 h for mid-column fishes. As expected, thermal relief increased with increasing release magnitude and decreasing release water temperature. The 0.34 m3/s release scenario reduced thermal stress (range is simulations from the top and bottom gate) by 11-18% for mid-column fishes and 8-12% for benthic fishes with an effective distance (where the cumulative time above CTMax was reduced by half) of 1-2 km for both guilds. The 0.59 m3/s release scenario reduced thermal stress by 18-25% for mid-column fishes and 12-20% for benthic fishes with effective distances of 4-8 km and 2-7 km, respectively. Three releases representing pre-dam flow magnitudes (0.76, 1.13 and 1.50 m3/s released from top gate) reduced thermal stress up to 46% for mid-column fishes and 41% for benthic fishes with an effective distance of 13-16 km, respectively. Lastly, we quantified temperature-induced stress via whole-body cortisol concentration of six stream fishes in response to prolonged thermal exposure at two temperatures (27°C and 32°C). We found no difference in cortisol levels between temperatures for any of the six species, indicating acclimation to elevated temperatures during the test period. However, Highland Stoneroller Campostoma spadiceum expressed cortisol concentrations greater than typical basal levels at both temperatures, suggesting stress from factors other than temperature (i.e., captivity). Our results suggest different reservoir-release options could improve downstream thermal-fish habitat during the summer baseflow period.
","language":"English","doi":"10.3996/css49046075","usgsCitation":"Brewer, S., Fox, G., Zhou, Y., and Alexander, J., 2020, Understanding the impacts of surface-groundwater conditions on stream fishes under altered baseflow conditions: Cooperator Science Series CSS-136-2020, 113 p., https://doi.org/10.3996/css49046075.","productDescription":"113 p.","ipdsId":"IP-106826","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":494942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Brewer, Shannon K. 0000-0002-1537-3921","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":340552,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":947039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fox, G.","contributorId":273105,"corporation":false,"usgs":false,"family":"Fox","given":"G.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":947040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhou, Y.","contributorId":360419,"corporation":false,"usgs":false,"family":"Zhou","given":"Y.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":947041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alexander, J.","contributorId":305320,"corporation":false,"usgs":false,"family":"Alexander","given":"J.","email":"","affiliations":[],"preferred":false,"id":947042,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}