High productivity temperate wetlands that accrete peat via belowground biomass (peatlands) may be managed for climate mitigation benefits due to their global distribution and notably negative emissions of atmospheric carbon dioxide (CO2) through rapid storage of carbon (C) in anoxic soils. Net emissions of additional greenhouse gases (GHG)—methane (CH4) and nitrous oxide (N2O)—are more difficult to predict and monitor due to fine-scale temporal and spatial variability, but can potentially reverse the climate mitigation benefits resulting from CO2 uptake. To support management decisions and modeling, we collected continuous 96 hour high frequency GHG flux data for CO2, CH4 and N2O at multiple scales—static chambers (1 Hz) and eddy covariance (10 Hz)—during peak productivity in a well-studied, impounded coastal peatland in California's Sacramento Delta with high annual rates of C fluxes, sequestering 2065 ± 150 g CO2 m−2 y−1 and emitting 64.5 ± 2.4 g CH4 m−2 y−1. Chambers (n = 6) showed strong spatial variability along a hydrologic gradient from inlet to interior plots. Daily (24 hour) net CO2 uptake (NEE) was highest near inlet locations and fell dramatically along the flowpath (−25 to −3.8 to +2.64 g CO2 m−2 d−1). In contrast, daily net CH4 flux increased along the flowpath (0.39 to 0.62 to 0.88 g CH4 m−2d−1), such that sites of high daily CO2 uptake were sites of low CH4 emission. Distributed, continuous chamber data exposed five novel insights, and at least two important datagaps for wetland GHG management, including: (1) increasing dominance of CH4 ebullition fluxes (15%–32% of total) along the flowpath and (2) net negative N2O flux across all sites as measured during a 4 day period of peak biomass (−1.7 mg N2O m−2 d−1; 0.51 g CO2 eq m−2 d−1). The net negative emissions of re-established peat-accreting wetlands are notably high, but may be poorly estimated by models that do not consider within-wetland spatial variability due to water flowpaths.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/aaae74","usgsCitation":"Windham-Myers, L., Bergamaschi, B.A., Anderson, F.A., Knox, S., Miller, R., and Fujii, R., 2018, Potential for negative emissions of greenhouse gases (CO2, CH4 and N2O) through coastal peatland re-establishment: Novel insights from high frequency flux data at meter and kilometer scales: Environmental Research Letters, v. 13, no. 4, p. 1-14, https://doi.org/10.1088/1748-9326/aaae74.","productDescription":"Article 045005; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-091738","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":468152,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/aaae74","text":"Publisher Index Page"},{"id":361209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta","volume":"13","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":757069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Frank A. 0000-0002-1418-4678","orcid":"https://orcid.org/0000-0002-1418-4678","contributorId":203975,"corporation":false,"usgs":true,"family":"Anderson","given":"Frank","email":"","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knox, Sarah 0000-0003-2255-5835","orcid":"https://orcid.org/0000-0003-2255-5835","contributorId":167493,"corporation":false,"usgs":false,"family":"Knox","given":"Sarah","affiliations":[{"id":24725,"text":"Ecosystem Science Division, Department of Environmental Science","active":true,"usgs":false}],"preferred":false,"id":757072,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Robin 0000-0002-1875-0390 romiller@usgs.gov","orcid":"https://orcid.org/0000-0002-1875-0390","contributorId":213190,"corporation":false,"usgs":true,"family":"Miller","given":"Robin","email":"romiller@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757073,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fujii, Roger 0000-0002-4616-7231 rfujii@usgs.gov","orcid":"https://orcid.org/0000-0002-4616-7231","contributorId":213191,"corporation":false,"usgs":true,"family":"Fujii","given":"Roger","email":"rfujii@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757074,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70202144,"text":"70202144 - 2018 - Secular changes in Cenozoic arc magmatism recorded by trends in forearc-basin sandstone composition, Cook Inlet, southern Alaska","interactions":[],"lastModifiedDate":"2019-10-28T09:41:05","indexId":"70202144","displayToPublicDate":"2019-02-01T11:48:38","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Secular changes in Cenozoic arc magmatism recorded by trends in forearc-basin sandstone composition, Cook Inlet, southern Alaska","docAbstract":"A robust set of modal composition data (238 samples) for Eocene to Pliocene sandstone from the Cook Inlet forearc basin of southern Alaska reveals strong temporal trends in composition, particularly in the abundance of volcanic lithic grains. Field and petrographic point-count data from the northwestern side of the basin indicate that the middle Eocene West Foreland Formation was strongly influenced by nearby volcanic activity. The middle Eocene to lower Miocene Hemlock Conglomerate and Oligocene to middle Miocene Tyonek Formation have a more mature quartzose composition with limited volcanic input. The middle to upper Miocene Beluga Formation includes abundant argillaceous sedimentary lithic grains and records an upward increase in volcanogenic material. The up-section increase in volcanic detritus continues into the upper Miocene to Pliocene Sterling Formation.
These first-order observations are interpreted to primarily reflect the waxing and waning of nearby arc magmatism. Available U-Pb detrital zircon geochronologic data indicate a dramatic reduction in zircon abundance during the early Eocene, and again during the Oligocene to Miocene, suggesting the arc was nearly dormant during these intervals. The reduced arc flux may record events such as subduction of slab windows or material that resisted subduction. The earlier hiatus in volcanism began ca. 56 Ma and coincided with a widely accepted model of ridge subduction beneath south-central Alaska. The later hiatus (ca. 25–8 Ma) coincided with insertion of the leading edge of the Yakutat terrane beneath the North American continental margin, resulting in an Oligocene to Miocene episode of flat-slab subduction that extended farther to the southwest than the modern seismically imaged flat-slab region. The younger tectonic event coincided with development of some of the best petroleum reservoirs in Cook Inlet.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Tectonics, sedimentary basins, and provenance: A celebration of the career of William R. Dickinson","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2018.2540(26)","usgsCitation":"Helmold, K.P., Wartes, M.A., Gillis, R.J., LePain, D.L., Herriott, T.M., Stanley, R.G., and Wilson, M.D., 2018, Secular changes in Cenozoic arc magmatism recorded by trends in forearc-basin sandstone composition, Cook Inlet, southern Alaska, chap. of Tectonics, sedimentary basins, and provenance: A celebration of the career of William R. Dickinson, p. 591-615, https://doi.org/10.1130/2018.2540(26).","productDescription":"25 p.","startPage":"591","endPage":"615","ipdsId":"IP-092258","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":361172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Cook Inlet","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.545654296875,\n 61.60639637138628\n ],\n [\n -154.412841796875,\n 59.10266722885381\n ],\n [\n -152.501220703125,\n 58.49369382056807\n ],\n [\n -151.710205078125,\n 59.19843857520702\n ],\n [\n -150.79833984375,\n 59.772991625706695\n ],\n [\n -150.97412109375,\n 59.89444803635239\n ],\n [\n -151.622314453125,\n 59.75086102411168\n ],\n [\n -151.226806640625,\n 60.673178565817715\n ],\n [\n -150.52368164062497,\n 60.8663124746226\n ],\n [\n -148.831787109375,\n 60.83955785801797\n ],\n [\n -149.43603515625,\n 61.18032911734518\n ],\n [\n -148.787841796875,\n 61.554109444927185\n ],\n [\n -150.545654296875,\n 61.60639637138628\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Ingersoll, Raymond V.","contributorId":213185,"corporation":false,"usgs":false,"family":"Ingersoll","given":"Raymond","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":757056,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Lawton, Timothy F.","contributorId":63866,"corporation":false,"usgs":true,"family":"Lawton","given":"Timothy","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":757057,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Graham, Stephan A.","contributorId":45902,"corporation":false,"usgs":true,"family":"Graham","given":"Stephan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":757058,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Helmold, Kenneth P.","contributorId":213171,"corporation":false,"usgs":false,"family":"Helmold","given":"Kenneth","email":"","middleInitial":"P.","affiliations":[{"id":16127,"text":"Alaska Division of Oil and Gas","active":true,"usgs":false}],"preferred":false,"id":757026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wartes, Marwan A.","contributorId":213172,"corporation":false,"usgs":false,"family":"Wartes","given":"Marwan","email":"","middleInitial":"A.","affiliations":[{"id":16126,"text":"Alaska Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":757027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gillis, Robert J.","contributorId":213173,"corporation":false,"usgs":false,"family":"Gillis","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":16126,"text":"Alaska Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":757028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LePain, David L.","contributorId":191714,"corporation":false,"usgs":false,"family":"LePain","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":757029,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herriott, Trystan M.","contributorId":213174,"corporation":false,"usgs":false,"family":"Herriott","given":"Trystan","email":"","middleInitial":"M.","affiliations":[{"id":16126,"text":"Alaska Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":757030,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stanley, Richard G. 0000-0001-6192-8783 rstanley@usgs.gov","orcid":"https://orcid.org/0000-0001-6192-8783","contributorId":1832,"corporation":false,"usgs":true,"family":"Stanley","given":"Richard","email":"rstanley@usgs.gov","middleInitial":"G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":757025,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilson, Michael D.","contributorId":213175,"corporation":false,"usgs":false,"family":"Wilson","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":12586,"text":"Consultant","active":true,"usgs":false}],"preferred":false,"id":757031,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70200801,"text":"70200801 - 2018 - Controls on deep direct-use thermal energy storage (DDU-TES) in the Portland Basin, Oregon, USA","interactions":[],"lastModifiedDate":"2019-12-22T14:18:33","indexId":"70200801","displayToPublicDate":"2019-01-30T09:42:15","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Controls on deep direct-use thermal energy storage (DDU-TES) in the Portland Basin, Oregon, USA","docAbstract":"Aquifer Thermal Energy Storage is being evaluated as a complementary technology to Deep Direct-Use for the Portland Basin, Oregon, USA. Aquifers can be used to efficiently distribute and store heat for seasonal use. The use of injection-extraction well pairs precludes the need to store or dispose of large volumes of pumped groundwater or to obtain a consumptive groundwater right. Injection temperatures vary seasonally, and well pairs can operate in continuous (single direction of flow) or cyclic (seasonal reversal of flow) modes. The target injection aquifers are the lowest Columbia River Basalt Group interflow zones, which are thermally and hydraulically separated from the overlying aquifer system, minimizing heat loss. A new aquifer thermal energy storage design tool allows assessment of thermal storage and recovery using: (1) system design parameters (e.g., well spacing and pumping rate), (2) thermal and hydraulic property values, and (3) regional groundwater flow rates. In continuous mode, extracted water temperature trends towards the flow-weighted average temperature of injected water over time, with the injected signal significantly lagged and damped. By controlling well spacing and temperature of delivered water (possibly using supplemental heating) continuous mode provides steady reliable warm water to end-users year-round. In cyclic mode, there is an advectively and conductively heated zone near the hot well and a cooled zone near the cool well, with temperatures substantially above and below the flow-weighted average injection temperature, respectively. In cyclic mode, during extraction, water temperatures start high or low, depending on the well, and temperatures trend towards the average injection temperature over the season. For the Columbia River Basalt Group in the Portland Basin, the quantity and quality of heat delivered depends most strongly on operational schedule, well spacing, mode of operation, and heterogeneity of the injection horizon.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geothermal's role in today's energy: Geothermal Resources Council Annual Meeting (GRC 2018)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Burns, E.R., Cladouhos, T.T., Williams, C., and Bershaw, 2018, Controls on deep direct-use thermal energy storage (DDU-TES) in the Portland Basin, Oregon, USA, in Geothermal's role in today's energy: Geothermal Resources Council Annual Meeting (GRC 2018), v. 42, p. 132-168.","productDescription":"36 p.","startPage":"132","endPage":"168","ipdsId":"IP-098120","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":365811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365760,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.proceedings.com/42374.html"}],"country":"United States","state":"Oregon","otherGeospatial":"Portland Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.28857421875,\n 44.55133484083592\n ],\n [\n -122.34374999999999,\n 44.55133484083592\n ],\n [\n -122.34374999999999,\n 45.805828539928356\n ],\n [\n -123.28857421875,\n 45.805828539928356\n ],\n [\n -123.28857421875,\n 44.55133484083592\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":750584,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cladouhos, Trenton T.","contributorId":66801,"corporation":false,"usgs":true,"family":"Cladouhos","given":"Trenton","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":766659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, C.F. 0000-0003-2196-5496","orcid":"https://orcid.org/0000-0003-2196-5496","contributorId":20401,"corporation":false,"usgs":true,"family":"Williams","given":"C.F.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":766660,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bershaw","contributorId":217372,"corporation":false,"usgs":false,"family":"Bershaw","email":"","affiliations":[],"preferred":false,"id":766661,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202182,"text":"70202182 - 2018 - Clarification of the term “normal material” used for standard atomic weights (IUPAC Technical Report)","interactions":[],"lastModifiedDate":"2019-02-12T16:51:07","indexId":"70202182","displayToPublicDate":"2019-01-01T16:51:02","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3207,"text":"Pure and Applied Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Clarification of the term “normal material” used for standard atomic weights (IUPAC Technical Report)","docAbstract":"The standard atomic weights of the elements apply to normal materials. Since 1984, the Commission on Isotopic Abundances and Atomic Weights (Commission) has defined a normal material as:
“The material is a reasonably possible source for this element or its compounds in commerce, for industry or science; the material is not itself studied for some extraordinary anomaly and its isotopic composition has not been modified significantly in a geologically brief period.”
The term “a geologically brief period” in this definition is confusing, and confusion can be reduced by revising this definition to the following, which was accepted by the Commission on Isotopic Abundances and Atomic Weights at its meeting in Groningen, Netherlands in September 2017:
“Normal materials include all substances, except (1) those subjected to substantial deliberate, undisclosed, or inadvertent artificial isotopic modification, (2) extraterrestrial materials, and (3) isotopically anomalous specimens, such as natural nuclear reactor products from Oklo (Gabon) or other unique occurrences.”
Chronic exposure to arsenic (As) via drinking groundwater is a human health concern worldwide. Probabilities of elevated geogenic As concentrations in groundwater were predicted in complex, glacial aquifers in Minnesota, north‐central USA, a region that commonly has elevated As concentrations in well water. Maps of elevated As hazard were created for depths typical of drinking water supply and with well construction attributes common for domestic wells. Conventional variables describing aquifer properties and materials, position on the hydrologic landscape, and soil geochemistry were among the most influential for predicting the probability of elevated As. We also found that certain well construction attributes were influential in predicting As hazard. Smaller distances between the top of the well screen and overlying aquitard (proximity) and shorter well screen lengths were each associated with higher probabilities of elevated As. Influential predictor variables, which are either mapped across the region or are well construction attributes, are proxies in the model for measurable physical or geochemical causes of elevated As (e.g., redox condition, till or aquifer sediment chemistry, and water chemistry), which are not mapped across the region. Our setting shares some important characteristics with deltaic and other high‐As aquifers in Southeast Asia: late Quaternary age, complex layering of coarse‐ and fine‐grained materials, low‐As sediment concentrations, and geochemical controls on As mobilization. Translating three‐dimensional geologic and geochemical understanding of As mobility to quantifiable variables for modeling with powerful, flexible statistical tools could improve predictions and help identify safer groundwater supply options in the USA, Southeast Asia, and elsewhere.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018WR023106","usgsCitation":"Erickson, M., Elliott, S.M., Christenson, C., and Krall, A.L., 2018, Predicting geogenic arsenic in drinking water wells in glacial aquifers, north-central USA: Accounting for depth-dependent features: Water Resources Research, v. 54, no. 12, p. 10172-10187, https://doi.org/10.1029/2018WR023106.","productDescription":"16 p.","startPage":"10172","endPage":"10187","ipdsId":"IP-090485","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":468158,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018wr023106","text":"Publisher Index Page"},{"id":437637,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77H1HH8","text":"USGS data release","linkHelpText":"Groundwater arsenic data and ASCII grids for predicting elevated arsenic in northwestern and 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Our analysis is based on the 2018 IUCN Red List status of 251 listed species, augmented by provisional Red List assessments by the IUCN Tortoise and Freshwater Turtle Specialist Group (TFTSG) of 109 currently unlisted species of tortoises and freshwater turtles, as well as re-assessments of several outdated IUCN Red List assessments. Of all recognized species of turtles and tortoises, this combined analysis indicates that 20.0% are Critically Endangered (CR), 35.3% are Critically Endangered or Endangered (CR+EN), and 51.9% are Threatened (CR+EN+Vulnerable). Adjusting for the potential threat levels of Data Deficient (DD) species indicates that 56.3% of all data-sufficient species are Threatened. We calculated percentages of imperiled species and modified Average Threat Levels (ATL; ranging from Least Concern = 1 to Extinct = 8) for various taxonomic and geographic groupings. Proportionally more species in the subfamily Geoemydinae (Asian members of the family Geoemydidae) are imperiled (74.2% CR+EN, 79.0% Threatened, 3.89 ATL) compared to other taxonomic groupings, but the families Podocnemididae, Testudinidae, and Trionychidae and the superfamily Chelonioidea (marine turtles of the families Cheloniidae and Dermochelyidae) also have high percentages of imperiled species and ATLs (42.9–50.0% CR+EN, 73.8–100.0% Threatened, 3.44–4.06 ATL). The subfamily Rhinoclemmydinae (Neotropical turtles of the family Geoemydidae) and the families Kinosternidae and Pelomedusidae have the lowest percentages of imperiled species and ATLs (0%–7.4% CR+EN, 7.4%–13.3% Threatened, 1.65–1.87 ATL). Turtles from Asia have the highest percentages of imperiled species (75.0% CR+EN, 83.0% Threatened, 3.98 ATL), significantly higher than predicted based on the regional species richness, due to much higher levels of exploitation in that geographic region. The family Testudinidae has the highest ATL (4.06) of all Testudines due to the extinction of several species of giant tortoises from Indian and Pacific Ocean islands since 1500 CE. The family Testudinidae also has an ATL higher than all other larger polytypic families (≥ 5 species) of Reptilia or Amphibia. The order Testudines is, on average, more imperiled than all other larger orders (≥ 20 species) of Reptilia, Amphibia, Mammalia, or Aves, but has percentages of CR+EN and Threatened species and an ATL (2.96) similar to those of Primates and Caudata (salamanders).
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The objective of this binational application of the SPARROW model is to better understand and quantify the sources of phosphorus (P) and nitrogen (N) that contribute to regional water-quality issues like algal blooms and eutrophication in Lake Erie and other parts of the Great Lakes, as well as Lake of the Woods. Led by the IJC, a team of researchers from the National Research Council of Canada – Ocean, Coastal and River Engineering Research Centre, USGS, and IJC are extending the SPARROW modelling work previously completed for the Red-Assiniboine basin and the U.S. portions of the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy river basins to cover all of the Great Lakes, Rainy River – Lake of the Woods and RedAssiniboine basins. The current effort is termed the Midcontinent SPARROW modelling study.
This report describes the data used to develop the Midcontinent SPARROW models, specifically the sources of original data, assembling the data, and the processing and harmonization required between the U.S. and Canada data needed to produce these models. Details provided include the:
The majority of the geospatial data collection and processing was required for Canadian datasets because many of the U.S. datasets were already assembled for previous SPARROW model applications in the U.S. The task of harmonizing data between the U.S. and Canada was important to ensure consistency of the datasets used in the models. The harmonized digital stream network, delineated catchments and input data for each catchment (i.e., source and delivery variables), created for the Midcontinent SPARROW models, are available for download at url: https://doi.org/10.4224/300.0001.
","language":"English","publisher":"National Research Council Canada","doi":"10.4224/23004810","usgsCitation":"Vouk, I., Burcher, R.S., Johnston, C.M., Jenkinson, R.W., Saad, D.A., Gaiot, J.S., Benoy, G.A., Robertson, D.M., and Laitta, M., 2018, Geospatial data for developing nutrient SPARROW models for the Midcontinental region of Canada and the United States: Technical Report OCRE-TR-2018-014, 57 p., https://doi.org/10.4224/23004810.","productDescription":"57 p.","ipdsId":"IP-096418","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":360921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Vouk, Ivana 0000-0002-9134-6933","orcid":"https://orcid.org/0000-0002-9134-6933","contributorId":211795,"corporation":false,"usgs":false,"family":"Vouk","given":"Ivana","email":"","affiliations":[{"id":38321,"text":"National Research Council Canada","active":true,"usgs":false}],"preferred":false,"id":754916,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burcher, Richard S.","contributorId":211796,"corporation":false,"usgs":false,"family":"Burcher","given":"Richard","email":"","middleInitial":"S.","affiliations":[{"id":38321,"text":"National Research Council Canada","active":true,"usgs":false}],"preferred":false,"id":754918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnston, Craig M. cmjohnst@usgs.gov","contributorId":1814,"corporation":false,"usgs":true,"family":"Johnston","given":"Craig","email":"cmjohnst@usgs.gov","middleInitial":"M.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754917,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jenkinson, R. 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Preserved specimens and other botanical information that we gather today—a period future practitioners may look back on as an early stage of modern anthropogenic climate change—will be of value to conservation managers and conservation biologists in the decades and centuries ahead. Here, we present suggestions for the systematic collection, long-term curation (in museums, herbaria, and other research institutions), and maintenance of plant specimens, along with associated data and analyses on the plants and vegetation present today and in the past. The primary aim of this systematic survey is to provide information of high value to conservation researchers and managers both in the near term (the next several years) and through the century to come. Such a systematic survey would build on a strong foundation of research and adaptive management on the island. It would fill gaps in less well-studied groups of organisms and identify environmental, ecological, and cultural factors related to current patterns of distribution. It would also archive previously collected data, photographs, and other materials which would otherwise gradually degrade and become inaccessible. As a case study, we use Santa Cruz Island, California, which is managed for conservation. We are confident that the same approach may be applied to other lands and waters around the world. We argue that there is a particular need to collect and archive herbarium specimens and seeds from today's populations, activities largely overlooked in recent decades. We encourage conservation researchers and managers to consider what information will be most important for future managers and to help launch studies, monitoring programs, and collections to prepare their successors for success.
","language":"English","publisher":"Monte L. Bean Life Science Museum, Brigham Young University","doi":"10.3398/064.078.0427","usgsCitation":"Randall, J.M., McEachern, K., Knapp, J., Power, P., Junak, S., Gill, K., Knapp, D., and Guilliams, M., 2018, Informing our successors: What botanical information for Santa Cruz Island will researchers and conservation managers in the century ahead need the most?: Western North American Naturalist, v. 78, no. 4, p. 888-901, https://doi.org/10.3398/064.078.0427.","productDescription":"14 p.","startPage":"888","endPage":"901","ipdsId":"IP-087994","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":361651,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Randall, John M.","contributorId":210310,"corporation":false,"usgs":false,"family":"Randall","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":758014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McEachern, Kathryn 0000-0003-2631-8247 kathryn_mceachern@usgs.gov","orcid":"https://orcid.org/0000-0003-2631-8247","contributorId":146324,"corporation":false,"usgs":true,"family":"McEachern","given":"Kathryn","email":"kathryn_mceachern@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":758013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knapp, John","contributorId":213552,"corporation":false,"usgs":false,"family":"Knapp","given":"John","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":758015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Power, Paula","contributorId":213553,"corporation":false,"usgs":false,"family":"Power","given":"Paula","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":758016,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Junak, Steve","contributorId":213554,"corporation":false,"usgs":false,"family":"Junak","given":"Steve","email":"","affiliations":[{"id":38789,"text":"Santa Barbara Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":758017,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gill, Kristina","contributorId":213555,"corporation":false,"usgs":false,"family":"Gill","given":"Kristina","email":"","affiliations":[{"id":38789,"text":"Santa Barbara Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":758018,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Knapp, Denise","contributorId":213556,"corporation":false,"usgs":false,"family":"Knapp","given":"Denise","email":"","affiliations":[{"id":38789,"text":"Santa Barbara Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":758019,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Guilliams, Matt","contributorId":213557,"corporation":false,"usgs":false,"family":"Guilliams","given":"Matt","email":"","affiliations":[{"id":38789,"text":"Santa Barbara Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":758020,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202230,"text":"70202230 - 2018 - Grasslands","interactions":[],"lastModifiedDate":"2019-02-15T13:13:37","indexId":"70202230","displayToPublicDate":"2019-01-01T13:13:31","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Grasslands","docAbstract":"Key findings:
Alaska is the largest state in the Nation, almost one-fifth the size of the combined lower 48 United States, and is rich in natural capital resources. Alaska is often identified as being on the front lines of climate change since it is warming faster than any other state and faces a myriad of issues associated with a changing climate. The cost of infrastructure damage from a warming climate is projected to be very large, potentially ranging from $110 to $270 million per year, assuming timely repair and maintenance. Although climate change does and will continue to dramatically transform the climate and environment of the Arctic, proactive adaptation in Alaska has the potential to reduce costs associated with these impacts. This includes the dissemination of several tools, such as guidebooks to support adaptation planning, some of which focus on Indigenous communities. While many opportunities exist with a changing climate, economic prospects are not well captured in the literature at this time.
As the climate continues to warm, there is likely to be a nearly sea ice-free Arctic during the summer by mid-century. Ocean acidification is an emerging global problem that will intensify with continued carbon dioxide (CO2) emissions and negatively affects organisms. Climate change will likely affect management actions and economic drivers, including fisheries, in complex ways. The use of multiple alternative models to appropriately characterize uncertainty in future fisheries biomass trajectories and harvests could help manage these challenges. As temperature and precipitation increase across the Alaska landscape, physical and biological changes are also occurring throughout Alaska’s terrestrial ecosystems. Degradation of permafrost is expected to continue, with associated impacts to infrastructure, river and stream discharge, water quality, and fish and wildlife habitat.
Longer sea ice-free seasons, higher ground temperatures, and relative sea level rise are expected to exacerbate flooding and accelerate erosion in many regions, leading to the loss of terrestrial habitat in the future and in some cases requiring entire communities or portions of communities to relocate to safer terrain. The influence of climate change on human health in Alaska can be traced to three sources: direct exposures, indirect effects, and social or psychological disruption. Each of these will have different manifestations for Alaskans when compared to residents elsewhere in the United States. Climate change exerts indirect effects on human health in Alaska through changes to water, air, and soil and through ecosystem changes affecting disease ecology and food security, especially in rural communities.
Alaska’s rural communities are predominantly inhabited by Indigenous peoples who may be disproportionately vulnerable to socioeconomic and environmental change; however, they also have rich cultural traditions of resilience and adaptation. The impacts of climate change will likely affect all aspects of Alaska Native societies, from nutrition, infrastructure, economics, and health consequences to language, education, and the communities themselves.
The profound and diverse climate-driven changes in Alaska’s physical environment and ecosystems generate economic impacts through their effects on environmental services. These services include positive benefits directly from ecosystems (for example, food, water, and other resources), as well as services provided directly from the physical environment (for example, temperature moderation, stable ground for supporting infrastructure, and smooth surface for overland transportation). Some of these effects are relatively assured and in some cases are already occurring. Other impacts are highly uncertain, due to their dependence on the structure of global and regional economies and future human alterations to the environment decades into the future, but they could be large.
In Alaska, a range of adaptations to changing climate and related environmental conditions are underway and others have been proposed as potential actions, including measures to reduce vulnerability and risk, as well as more systemic institutional transformation.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Global Change Research Program","doi":"10.7930/NCA4.2018.CH26","usgsCitation":"Markon, C., Gray, S., Berman, M., Eerkes-Medrano, L., Hennessy, T., Huntington, H.P., Littell, J., McCammon, M., Thoman, R., and Trainor, S., 2018, Alaska, 57 p., https://doi.org/10.7930/NCA4.2018.CH26.","productDescription":"57 p.","startPage":"1185","endPage":"1241","ipdsId":"IP-103840","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"links":[{"id":360915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Reidmiller, David 0000-0001-9321-7548","orcid":"https://orcid.org/0000-0001-9321-7548","contributorId":212241,"corporation":false,"usgs":true,"family":"Reidmiller","given":"David","email":"","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":755845,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Avery, C. W.","contributorId":212242,"corporation":false,"usgs":false,"family":"Avery","given":"C.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":755846,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Easterling, D. R.","contributorId":212243,"corporation":false,"usgs":false,"family":"Easterling","given":"D.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":755847,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Kunkel, K. E.","contributorId":83626,"corporation":false,"usgs":true,"family":"Kunkel","given":"K.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":755848,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Lewis, K. L. M.","contributorId":212244,"corporation":false,"usgs":false,"family":"Lewis","given":"K.","email":"","middleInitial":"L. M.","affiliations":[],"preferred":false,"id":755849,"contributorType":{"id":2,"text":"Editors"},"rank":5},{"text":"Maycock, T. 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C.","contributorId":212246,"corporation":false,"usgs":false,"family":"Stewart","given":"B.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":755851,"contributorType":{"id":2,"text":"Editors"},"rank":7}],"authors":[{"text":"Markon, Carl","contributorId":212151,"corporation":false,"usgs":false,"family":"Markon","given":"Carl","affiliations":[{"id":38437,"text":"Retired, U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":755635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, Stephen T. 0000-0002-0959-3418 sgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0959-3418","contributorId":209851,"corporation":false,"usgs":true,"family":"Gray","given":"Stephen","email":"sgray@usgs.gov","middleInitial":"T.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":755636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berman, Matthew","contributorId":200375,"corporation":false,"usgs":false,"family":"Berman","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":755637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eerkes-Medrano, Laura 0000-0001-8413-9031","orcid":"https://orcid.org/0000-0001-8413-9031","contributorId":212152,"corporation":false,"usgs":false,"family":"Eerkes-Medrano","given":"Laura","email":"","affiliations":[{"id":16829,"text":"University of Victoria","active":true,"usgs":false}],"preferred":false,"id":755638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hennessy, Thomas","contributorId":212153,"corporation":false,"usgs":false,"family":"Hennessy","given":"Thomas","email":"","affiliations":[{"id":38438,"text":"U.S. Centers for Disease Control and Prevention","active":true,"usgs":false}],"preferred":false,"id":755639,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Huntington, Henry P. 0000-0003-2308-8677","orcid":"https://orcid.org/0000-0003-2308-8677","contributorId":212154,"corporation":false,"usgs":false,"family":"Huntington","given":"Henry","email":"","middleInitial":"P.","affiliations":[{"id":38439,"text":"Huntington Consulting","active":true,"usgs":false}],"preferred":false,"id":755640,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Littell, Jeremy S. 0000-0002-5302-8280","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":205907,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":755641,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCammon, Molly","contributorId":212155,"corporation":false,"usgs":false,"family":"McCammon","given":"Molly","email":"","affiliations":[{"id":38440,"text":"Alaska Ocean Observing System","active":true,"usgs":false}],"preferred":false,"id":755642,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thoman, Richard","contributorId":187613,"corporation":false,"usgs":false,"family":"Thoman","given":"Richard","affiliations":[],"preferred":false,"id":755643,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Trainor, Sarah 0000-0002-9911-9006","orcid":"https://orcid.org/0000-0002-9911-9006","contributorId":212156,"corporation":false,"usgs":false,"family":"Trainor","given":"Sarah","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":755644,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70201873,"text":"70201873 - 2018 - Hawai‘i and U.S.-Affiliated Pacific Islands","interactions":[],"lastModifiedDate":"2019-02-01T11:53:35","indexId":"70201873","displayToPublicDate":"2019-01-01T11:53:29","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Hawai‘i and U.S.-Affiliated Pacific Islands","docAbstract":"The U.S. Pacific Islands are culturally and environmentally diverse, treasured by the 1.9 million people who call them home. Pacific islands are particularly vulnerable to climate change impacts due to their exposure and isolation, small size, low elevation (in the case of atolls), and concentration of infrastructure and economy along the coasts.
A prevalent cause of year-to-year changes in climate patterns around the globe and in the Pacific Islands region is the El Niño–Southern Oscillation (ENSO). The El Niño and La Niña phases of ENSO can dramatically affect precipitation, air and ocean temperature, sea surface height, storminess, wave size, and trade winds. It is unknown exactly how the timing and intensity of ENSO will continue to change in the coming decades, but recent climate model results suggest a doubling in frequency of both El Niño and La Niña extremes in this century as compared to the 20th century under scenarios with more warming, including the higher scenario (RCP8.5).
On islands, all natural sources of freshwater come from rainfall received within their limited land areas. Severe droughts are common, making water shortage one of the most important climate-related risks in the region. As temperature continues to rise and cloud cover decreases in some areas, evaporation is expected to increase, causing both reduced water supply and higher water demand. Streamflow in Hawai‘i has declined over approximately the past 100 years, consistent with observed decreases in rainfall.
The impacts of sea level rise in the Pacific include coastal erosion, episodic flooding, permanent inundation, heightened exposure to marine hazards, and saltwater intrusion to surface water and groundwater systems. Sea level rise will disproportionately affect the tropical Pacific and potentially exceed the global average.
Invasive species, landscape change, habitat alteration, and reduced resilience have resulted in extinctions and diminished ecosystem function. Inundation of atolls in the coming decades is projected to impact existing on-island ecosystems. Wildlife that relies on coastal habitats will likely also be severely impacted. In Hawaiʻi, coral reefs contribute an estimated $477 million to the local economy every year. Under projected warming of approximately 0.5°F per decade, all nearshore coral reefs in the Hawai‘i and Pacific Islands region will experience annual bleaching before 2050. An ecosystem-based approach to international management of open ocean fisheries in the Pacific that incorporates climate-informed catch limits is expected to produce more realistic future harvest levels and enhance ecosystem resilience.
Indigenous communities of the Pacific derive their sense of identity from the islands. Emerging issues for Indigenous communities of the Pacific include the resilience of marine-managed areas and climate-induced human migration from their traditional lands. The rich body of traditional knowledge is place-based and localized and is useful in adaptation planning because it builds on intergenerational sharing of observations. Documenting the kinds of governance structures or decision-making hierarchies created for management of these lands and waters is also important as a learning tool that can be shared with other island communities.
Across the region, groups are coming together to minimize damage and disruption from coastal flooding and inundation as well as other climate-related impacts. Social cohesion is already strong in many communities, making it possible to work together to take action. Early intervention can lower economic, environmental, social, and cultural costs and reduce or prevent conflict and displacement from ancestral land and resources.
Agricultural production is a fundamental activity conducted on 45% of the U.S. land area, 55% of Mexico’s land area, and 7% of Canada’s land area (World Bank 2016). Because of this vast spatial extent and the strong role that land management plays in how agricultural ecosystems function, agricultural lands and activities represent a large portion of the North American carbon budget. Accordingly, improved quantification of the agricultural carbon cycle, new trends in agriculture, and added opportunities for emissions reductions provide a critical foundation for considering the relationships between agriculture and carbon cycling at local, regional, continental, and global scales. More than 145 countries have specifically included agriculture in their targets and actions for mitigating climate change (FAO 2016), and agriculture has featured particularly prominently in recent target and action commitments made by developing countries to reduce greenhouse gas (GHG) emissions (Richards et al., 2015).
Conversion of vast native forest and prairie to agriculture across North America between 1860 and 1960 resulted in carbon dioxide (CO2) fluxes to the atmosphere from biota and soils that exceeded those from fossil fuel emissions over the same period (Houghton et al., 1983). Correspondingly, soil organic carbon (SOC) declined in many soils during the 50 years following conversion from native ecosystems to production agriculture (Huggins et al., 1998; Janzen et al., 1998; Slobodian et al., 2002). Crop yields and corresponding above- and belowground biomass have steadily increased since the 1930s due to genetic and management innovations, which provide more organic input from which to build SOC ( Johnson et al., 2006; Hatfield and Walthall 2015). This, coupled with improved input-use efficiencies may reduce GHG-emissions per unit yield (GHG intensity), with additional improvements possible through management optimization (Grassini and Cassman 2012; Pittelkow et al., 2015). Options include reducing tillage, integrating perennials onto the landscape, reducing or eliminating bare-fallow land (i.e., land without living plants), adding cover crops, and enrolling lands in conservation easement programs. These options, originally proposed to control erosion, have potential co-benefits in terms of increased soil health, plant productivity, and soil carbon stabilization (Lehman et al., 2015). Conversely, returning lands previously enrolled in conservation easements (e.g., the Conservation Reserve Program [CRP] and other land set-aside efforts) to row-crop production, tillage, or aggressive harvesting of crop residues all risk degrading soil quality and exacerbating SOC loss. Of note is that the net results of land use and land management practices in an agricultural setting vary according to many factors, such as crop or production system type, soil type, climate, and the collection of practices at any given site. For example, many traditional practices followed by Indigenous people on tribal lands are based on an integrated approach to natural resource management and response to environmental change that may provide agricultural options uniquely suited to varied environmental settings (see Ch. 7: Tribal Lands, p. 303).
Agricultural land in the United States totaled 408.2 million hectares (ha) in 2014, of which 251 million ha were in permanent meadows and pastures, 152.2 million ha were in arable land, and 2.6 million ha were in permanent crops (FAOSTAT 2016). Compared with the distribution in 2007, these numbers reflect a 4.7 million ha decline in total agricultural lands, driven by declines in arable land and permanent crops but partially offset by a modest increase in permanent meadows and pastures. Although arable lands have been declining, the combined acreage of the four major crops (corn, wheat, soybeans, and cotton) has risen slightly, with increases in land planted in corn and soybeans and decreases in cotton and wheat (see Figure 5.1, p. 232). Despite the overall slight decline in agricultural land area, the value of U.S. agricultural production rose over the past decade as a result of increased production efficiency and higher prices (USDA 2017a; see also www.ers.usda.gov). Canada has about 65 million ha of agricultural land, of which about 46 million ha are arable, accounting for only about 7% of the country’s total land area (FAOSTAT 2017). Prominent crops on Canada’s arable lands include cereals (e.g., wheat, barley, and maize), oilseeds (e.g., canola and soybeans), and pulses (e.g., peas and lentils). Natural and seeded pastures available for grazing in Canada make up about 20 million ha (Legesse et al., 2016). Agricultural land in Mexico makes up 107 million ha, of which 23 million ha are arable land, 2.7 million ha are permanent crops, and 81 million ha are permanent meadows and pastures (FAOSTAT 2017). Mexico’s major crops are fruits, corn, grains, vegetables, and sugarcane.
","largerWorkTitle":"Second State of the Carbon Cycle Report (SOCCR2): A Sustained Assessment Report","language":"English","publisher":"U.S. Global Change Research Program","doi":"10.7930/SOCCR2.2018.Ch5","usgsCitation":"Hristov, A.N., Johnson, J.M., Rice, C.W., Brown, M.E., Conant, R.T., Del Grosso, S.J., Gurwick, N.P., Rotz, C., Sainju, U.M., Skinner, R.H., West, T.O., Runkle, B.R., Janzen, H., Reed, S.C., Cavallaro, N., and Shrestha, G., 2018, Agriculture, 35 p., https://doi.org/10.7930/SOCCR2.2018.Ch5.","productDescription":"35 p.","startPage":"229","endPage":"263","ipdsId":"IP-088978","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":361017,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Cavallaro, Nancy","contributorId":212784,"corporation":false,"usgs":false,"family":"Cavallaro","given":"Nancy","email":"","affiliations":[{"id":38681,"text":"USDA National Institute of Food and Agriculture","active":true,"usgs":false}],"preferred":false,"id":756665,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Shrestha, Gyami","contributorId":145521,"corporation":false,"usgs":false,"family":"Shrestha","given":"Gyami","email":"","affiliations":[],"preferred":false,"id":756666,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Birdsey, Richard","contributorId":210640,"corporation":false,"usgs":false,"family":"Birdsey","given":"Richard","affiliations":[{"id":25456,"text":"Woods Hole Research Center, Falmouth, MA, United States","active":true,"usgs":false}],"preferred":false,"id":756667,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Mayes, Melanie A.","contributorId":212782,"corporation":false,"usgs":false,"family":"Mayes","given":"Melanie","email":"","middleInitial":"A.","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":756668,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Najjar, Raymond G.","contributorId":168568,"corporation":false,"usgs":false,"family":"Najjar","given":"Raymond G.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":756669,"contributorType":{"id":2,"text":"Editors"},"rank":5},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":756670,"contributorType":{"id":2,"text":"Editors"},"rank":6},{"text":"Romero-Lankao, Patricia","contributorId":212783,"corporation":false,"usgs":false,"family":"Romero-Lankao","given":"Patricia","email":"","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":756671,"contributorType":{"id":2,"text":"Editors"},"rank":7},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":756672,"contributorType":{"id":2,"text":"Editors"},"rank":8}],"authors":[{"text":"Hristov, Alexander N.","contributorId":81334,"corporation":false,"usgs":false,"family":"Hristov","given":"Alexander","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":756545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Jane M. F.","contributorId":212804,"corporation":false,"usgs":false,"family":"Johnson","given":"Jane","email":"","middleInitial":"M. F.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":756650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rice, Charles W.","contributorId":212805,"corporation":false,"usgs":false,"family":"Rice","given":"Charles","email":"","middleInitial":"W.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":756651,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Molly E.","contributorId":62490,"corporation":false,"usgs":true,"family":"Brown","given":"Molly","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":756652,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Conant, Richard T.","contributorId":207107,"corporation":false,"usgs":false,"family":"Conant","given":"Richard","email":"","middleInitial":"T.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":756653,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Del Grosso, Stephen J.","contributorId":145477,"corporation":false,"usgs":false,"family":"Del Grosso","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":16129,"text":"Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, USA","active":true,"usgs":false}],"preferred":false,"id":756654,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gurwick, Noel P.","contributorId":212818,"corporation":false,"usgs":false,"family":"Gurwick","given":"Noel","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":756655,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rotz, C. Alan","contributorId":212819,"corporation":false,"usgs":false,"family":"Rotz","given":"C. Alan","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":756656,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sainju, Upendra M.","contributorId":212820,"corporation":false,"usgs":false,"family":"Sainju","given":"Upendra","email":"","middleInitial":"M.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":756657,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Skinner, R. Howard","contributorId":146142,"corporation":false,"usgs":false,"family":"Skinner","given":"R.","email":"","middleInitial":"Howard","affiliations":[{"id":16601,"text":"USDA-ARS, Pasture Systems and Watershed Management Unit","active":true,"usgs":false}],"preferred":false,"id":756658,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"West, Tristram O.","contributorId":39230,"corporation":false,"usgs":true,"family":"West","given":"Tristram","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":756659,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Runkle, Benjamin R. K.","contributorId":196373,"corporation":false,"usgs":false,"family":"Runkle","given":"Benjamin","email":"","middleInitial":"R. K.","affiliations":[],"preferred":false,"id":756660,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Janzen, Henry","contributorId":212821,"corporation":false,"usgs":false,"family":"Janzen","given":"Henry","email":"","affiliations":[{"id":24491,"text":"Agriculture and Agri-Food Canada","active":true,"usgs":false}],"preferred":false,"id":756661,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":756662,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Cavallaro, Nancy","contributorId":212784,"corporation":false,"usgs":false,"family":"Cavallaro","given":"Nancy","email":"","affiliations":[{"id":38681,"text":"USDA National Institute of Food and Agriculture","active":true,"usgs":false}],"preferred":false,"id":756663,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Shrestha, Gyami","contributorId":145521,"corporation":false,"usgs":false,"family":"Shrestha","given":"Gyami","email":"","affiliations":[],"preferred":false,"id":756664,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70202028,"text":"70202028 - 2018 - Groundwater modeling","interactions":[],"lastModifiedDate":"2019-02-07T10:45:21","indexId":"70202028","displayToPublicDate":"2019-01-01T10:45:06","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Groundwater modeling","docAbstract":"The state of the science and practice in groundwater modeling brings to mind highly sophisticated computer models that are running in parallel on many multi-processor machines. These models are expected to incorporate many different processes of both saturated and unsaturated groundwater flow and transport and possibly the media to which it connects, like surface waters and the atmosphere. We are increasingly aware we cannot study groundwater flow in isolation if we are to make useful predictions of, for instance, the impacts of climate change on the groundwater regime. We have come a long way.
Today we are no longer limited to equations for flow toward a well, perhaps near an infinitely long straight canal (method of images), to sandbox models in the laboratory, or to simple steady state models of flow in a single aquifer. We now have computer models that solve groundwater flow and transport in multi-aquifer settings under transient conditions and with a user-friendly graphical user interface that allows widespread use. Additionally, multi-media models are now leaving the research environment and becoming available to mainstream consultants. So in that sense the science of groundwater modeling has matured.
The practice of groundwater modeling, however, has also matured. We have come to realize that model output, being a necessary simplification of an unknowably complex natural world, has inherent limitations. That is, a model of reality is not reality itself. There is uncertainty associated with all facets of our model—parameterization, aquifer geometry and discretization, boundary conditions, and future hydrologic drivers such as future pumping regimes and climates. Today a model is now more appropriately seen as a tool that provides a quantitative framework to make supportable forecasts rather than an oracle that gives us all the answers.
In this chapter we set out to briefly review the state of the science and practice in modeling. In doing so, we augment existing assessments from the journal Groundwater (e.g., Hunt and Zheng 2012; Langevin and Panday 2012; Molz 2017a,b; White 2017), specifically in terms of modeling approach. An effective modeling approach is critical. If a modeler does not decompose the societal problem correctly, the model will not be fit-for-purpose, no matter how sophisticated the code’s capabilities. Moreover, capabilities of codes will be ever improving; good modeling practices have a timelessness that is more robust.
How best to decompose the problem and provide models that are accepted? We lay out here some approaches for today’s applied groundwater modeling. Specifically, we suggest: (1) a step-wise modeling process; (2) including a two-dimensional areal model within this process; (3) keeping abreast of industry standards; and (4) ways to increase acceptance of the models we produce.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Groundwater: State of the science and practice","language":"English","publisher":"National Groundwater Association","isbn":"1-56034-047-9","usgsCitation":"Haitjema, H.M., and Hunt, R., 2018, Groundwater modeling, chap. of Groundwater: State of the science and practice, p. 41-46.","productDescription":"6 p.","startPage":"41","endPage":"46","ipdsId":"IP-101055","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":361072,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":361067,"type":{"id":15,"text":"Index Page"},"url":"https://groundwatersolutionsgroup.com/wp-content/uploads/2018/12/Science-and-Practice_10.17_FINAL.pdf#page=45"}],"publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Haitjema, Henk M.","contributorId":74678,"corporation":false,"usgs":true,"family":"Haitjema","given":"Henk","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":756765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":208800,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[],"preferred":true,"id":756764,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70201875,"text":"70201875 - 2018 - Southeast","interactions":[],"lastModifiedDate":"2019-02-01T10:40:51","indexId":"70201875","displayToPublicDate":"2019-01-01T10:40:46","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Southeast","docAbstract":"The Southeast includes vast expanses of coastal and inland low-lying areas, the southern portion of the Appalachian Mountains, numerous high-growth metropolitan areas, and large rural expanses. These beaches and bayous, fields and forests, and cities and small towns are all at risk from a changing climate. While some climate change impacts, such as sea level rise and extreme downpours, are being acutely felt now, others, like increasing exposure to dangerous high temperatures, humidity, and new local diseases, are expected to become more significant in the coming decades. While all regional residents and communities are potentially at risk for some impacts, some communities or populations are at greater risk due to their locations, services available to them, and economic situations.
Observed warming since the mid-20th century has been uneven in the Southeast region, with average daily minimum temperatures increasing three times faster than average daily maximum temperatures. The number of extreme rainfall events is increasing. Climate model simulations of future conditions project increases in both temperature and extreme precipitation.
Trends towards a more urbanized and denser Southeast are expected to continue, creating new climate vulnerabilities. Cities across the Southeast are experiencing more and longer summer heat waves. Vector-borne diseases pose a greater risk in cities than in rural areas because of higher population densities and other human factors, and the major urban centers in the Southeast are already impacted by poor air quality during warmer months. Increasing precipitation and extreme weather events will likely impact roads, freight rail, and passenger rail, which will likely have cascading effects across the region. Infrastructure related to drinking water and wastewater treatment also has the potential to be compromised by climate-related events. Increases in extreme rainfall events and high tide coastal floods due to future climate change will impact the quality of life of permanent residents as well as tourists visiting the low-lying and coastal regions of the Southeast. Sea level rise is contributing to increased coastal flooding in the Southeast, and high tide flooding already poses daily risks to businesses, neighborhoods, infrastructure, transportation, and ecosystems in the region. There have been numerous instances of intense rainfall events that have had devastating impacts on inland communities in recent years.
The ecological resources that people depend on for livelihoods, protection, and well-being are increasingly at risk from the impacts of climate change. Sea level rise will result in the rapid conversion of coastal, terrestrial, and freshwater ecosystems to tidal saline habitats. Reductions in the frequency and intensity of cold winter temperature extremes are already allowing tropical and subtropical species to move northward and replace more temperate species. Warmer winter temperatures are also expected to facilitate the northward movement of problematic invasive species, which could transform natural systems north of their current distribution. In the future, rising temperatures and increases in the duration and intensity of drought are expected to increase wildfire occurrence and also reduce the effectiveness of prescribed fire practices.
Many in rural communities are maintaining connections to traditional livelihoods and relying on natural resources that are inherently vulnerable to climate changes. Climate trends and possible climate futures show patterns that are already impacting—and are projected to further impact—rural sectors, from agriculture and forestry to human health and labor productivity. Future temperature increases are projected to pose challenges to human health. Increases in temperatures, water stress, freeze-free days, drought, and wildfire risks, together with changing conditions for invasive species and the movement of diseases, create a number of potential risks for existing agricultural systems. Rural communities tend to be more vulnerable to these changes due to factors such as demography, occupations, earnings, literacy, and poverty incidence. In fact, a recent economic study using a higher scenario (RCP8.5) suggests that the southern and midwestern populations are likely to suffer the largest losses from future climate changes in the United States. Climate change tends to compound existing vulnerabilities and exacerbate existing inequities. Already poor regions, including those found in the Southeast, are expected to continue incurring greater losses than elsewhere in the United States.
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However, the Caribbean climate is changing and is projected to be increasingly variable as levels of greenhouse gases in the atmosphere increase.
The high percentage of coastal area relative to the total island land area in the U.S. Caribbean means that a large proportion of the region’s people, infrastructure, and economic activity are vulnerable to sea level rise, more frequent intense rainfall events and associated coastal flooding, and saltwater intrusion. High levels of exposure and sensitivity to risk in the U.S. Caribbean region are compounded by a low level of adaptive capacity, due in part to the high costs of mitigation and adaptation measures relative to the region’s gross domestic product, particularly when compared to continental U.S. coastal areas. The limited geographic and economic scale of Caribbean islands means that disruptions from extreme climate-related events, such as droughts and hurricanes, can devastate large portions of local economies and cause widespread damage to crops, water supplies, infrastructure, and other critical resources and services.
The U.S. Caribbean territories of Puerto Rico and the U.S. Virgin Islands (USVI) have distinct differences in topography, language, population size, governance, natural and human resources, and economic capacity. However, both are highly dependent on natural and built coastal assets; service-related industries account for more than 60% of the USVI economy. Beaches, affected by sea level rise and erosion, are among the main tourist attractions. In Puerto Rico, critical infrastructure (for example, drinking water pipelines and pump stations, sanitary pipelines and pump stations, wastewater treatment plants, and power plants) is vulnerable to the effects of sea level rise, storm surge, and flooding. In the USVI, infrastructure and historical buildings in the inundation zone for sea level rise include the power plants on both St. Thomas and St. Croix; schools; housing communities; the towns of Charlotte Amalie, Christiansted, and Frederiksted; and pipelines for water and sewage.
Climate change will likely result in water shortages due to an overall decrease in annual rainfall, a reduction in ecosystem services, and increased risks for agriculture, human health, wildlife, and socioeconomic development in the U.S. Caribbean. These shortages would result from some locations within the Caribbean experiencing longer dry seasons and shorter, but wetter, wet seasons in the future. Extended dry seasons are projected to increase fire likelihood. Excessive rainfall, coupled with poor construction practices, unpaved roads, and steep slopes, can exacerbate erosion rates and have adverse effects on reservoir capacity, water quality, and nearshore marine habitats.
Ocean warming poses a significant threat to the survival of corals and will likely also cause shifts in associated habitats that compose the coral reef ecosystem. Severe, repeated, or prolonged periods of high temperatures leading to extended coral bleaching can result in colony death. Ocean acidification also is likely to diminish the structural integrity of coral habitats. Studies show that major shifts in fisheries distribution and changes to the structure and composition of marine habitats adversely affect food security, shoreline protection, and economies throughout the Caribbean.
In Puerto Rico, the annual number of days with temperatures above 90°F has increased over the last four and a half decades. During that period, stroke and cardiovascular disease, which are influenced by such elevated temperatures, became the primary causes of death. Increases in average temperature and in extreme heat events will likely have detrimental effects on agricultural operations throughout the U.S. Caribbean region. Many farmers in the tropics, including the U.S. Caribbean, are considered small-holding, limited resource farmers and often lack the resources and/or capital to adapt to changing conditions.
Most Caribbean countries and territories share the need to assess risks, enable actions across scales, and assess changes in ecosystemsto inform decision-making on habitat protection under a changing climate. U.S. Caribbean islands have the potential to improve adaptation and mitigation actions by fostering stronger collaborations with Caribbean initiatives on climate change and disaster risk reduction.
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San Gabriel Channel–Lobe Transition Zone, Catalina Basin, Southern California Borderland","docAbstract":"High-resolution geophysical data across the Catalina Basin, offshore southern California, USA, reveal a complex channel–lobe transition zone (CLTZ) and provide an opportunity to characterize an entire seafloor CLTZ in a tectonically active and confined-basin setting. The seafloor morphology, distribution of depositional and erosional features, and location of depocenters in the CLTZ are controlled by shifting confinement and seafloor gradient related to inherited basement structures, active faults, and basin margins. Below a Holocene hemipelagic drape, the Catalina Basin is dominated by CLTZ and lobe sedimentation from the San Gabriel Channel, with lesser accumulations from local sediment sources limited to basin margins. The San Gabriel Channel is structurally confined as it enters the Catalina Basin and appears unable to avulse; it continues into the basin as a channel that rapidly widens, decreases in relief, and becomes scoured at its margins. A CLTZ is imaged between the confined San Gabriel channel and its terminal lobes deposited > 50 km into the basin. Narrow, apparently disconnected channels with knickpoints occur throughout the proximal and mid-CLTZ and are concentrated near basement highs and basin-bounding Quaternary-active dextral strike-slip faults. A field of small-scale erosional crescent-shaped scours (∼ 100 m length, ∼ 200 m width, up to ∼ 10 m relief across ∼ 30 km2region) occurs above a partially buried basement high that creates perturbations in seafloor gradient. Likewise, above a buried basement structure that locally increases seafloor gradient (up to 0.4°), the distal CLTZ may contain sediment waves (∼ 2–4 m wave height and ∼ 200–300 m wavelength) that are smaller than many other CLTZ examples. This study of the San Gabriel CLTZ in Catalina Basin provides high-resolution geophysical data coverage of a complete CLTZ and illustrates a tectonically controlled end-member CLTZ from the modern seafloor.
","language":"English","publisher":"SEPM","doi":"10.2110/jsr.2018.50","usgsCitation":"Maier, K.L., Roland, E., Walton, M.A., Conrad, J.E., Brothers, D., Dartnell, P., and Kluesner, J., 2018, The tectonically controlled San Gabriel Channel–Lobe Transition Zone, Catalina Basin, Southern California Borderland: Journal of Sedimentary Research, v. 88, no. 8, p. 942-959, https://doi.org/10.2110/jsr.2018.50.","productDescription":"18 p.","startPage":"942","endPage":"959","ipdsId":"IP-094240","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":361244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Catalina Basin, Southern California Borderland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.8333,\n 33\n ],\n [\n -118,\n 33\n ],\n [\n -118,\n 33.5\n ],\n [\n -118.8333,\n 33.5\n ],\n [\n -118.8333,\n 33\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"88","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Maier, Katherine L. 0000-0003-2908-3340 kcoble@usgs.gov","orcid":"https://orcid.org/0000-0003-2908-3340","contributorId":4926,"corporation":false,"usgs":true,"family":"Maier","given":"Katherine","email":"kcoble@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roland, Emily C.","contributorId":147830,"corporation":false,"usgs":false,"family":"Roland","given":"Emily C.","affiliations":[{"id":13254,"text":"University of Washington, School of Oceanography","active":true,"usgs":false}],"preferred":false,"id":757196,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walton, Maureen A. 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L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757197,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrad, James E. 0000-0001-6655-694X jconrad@usgs.gov","orcid":"https://orcid.org/0000-0001-6655-694X","contributorId":2316,"corporation":false,"usgs":true,"family":"Conrad","given":"James","email":"jconrad@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757194,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brothers, Daniel S. 0000-0001-7702-157X","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":210199,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757198,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757199,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kluesner, Jared W. 0000-0003-1701-8832","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":206367,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757200,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70197878,"text":"70197878 - 2018 - Fault displacement hazard for strike-slip faults","interactions":[],"lastModifiedDate":"2019-06-27T16:25:46","indexId":"70197878","displayToPublicDate":"2018-12-31T16:21:11","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Fault displacement hazard for strike-slip faults","docAbstract":"In this paper we summarize data, methods, and models developed for a probabilistic assessment of fault displacement hazards across the U.S. We compare earthquake displacement data and empirical fault displacement models that have been developed for normal faults, strike-slip faults, and reverse faults. In general, the data and models are similar near the center of the fault for the three faulting types, but differ near the ends with the strike-slip data being lower than the reverse and normal faulting data. We also compare these U.S. models with data and equations developed using Japanese fault displacement data. The Japan model is also similar to the U.S. models near the center of the fault but decays less rapidly near the ends of the fault. In addition, we discuss impacts of models developed to analyze off-fault strain on secondary faults, multi-strand displacement hazard, and various mapping quality factors. For our study, we show example fault displacements for a M 7 fault with recurrence of 800 and 1600 years. We conclude that a deterministic assessment of fault displacements is often higher than the probabilistic displacements for less active faults with earthquake rupture recurrence that is longer than the hazard return period of interest. Fault displacement hazard is applied in engineering applications for buildings, bridges, pipelines, and nuclear facilities. We present three applications for fault displacement hazard at nuclear facilities and important structures.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Earthquake Engineering. National Conference. 11TH 2018. (11NCEE) (12 Vols) Integrating Science, Engineering, and Policy","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Eleventh U.S. National Conference on Earthquake Engineering","conferenceDate":"June 25-29, 2018","conferenceLocation":"Los Angeles, CA","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Petersen, M.D., and Chen, R., 2018, Fault displacement hazard for strike-slip faults, in Earthquake Engineering. National Conference. 11TH 2018. (11NCEE) (12 Vols) Integrating Science, Engineering, and Policy, v. 3, Los Angeles, CA, June 25-29, 2018, p. 1794-1805.","productDescription":"12 p.","startPage":"1794","endPage":"1805","ipdsId":"IP-096800","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":365131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":738897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Rui","contributorId":187504,"corporation":false,"usgs":false,"family":"Chen","given":"Rui","email":"","affiliations":[],"preferred":false,"id":738898,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70202297,"text":"70202297 - 2018 - Little islands recording global events: Late Quaternary sea level history and paleozoogeography of Santa Barbara and Anacapa Islands, Channel Islands National Park, California","interactions":[],"lastModifiedDate":"2019-02-20T16:03:11","indexId":"70202297","displayToPublicDate":"2018-12-31T16:03:04","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Little islands recording global events: Late Quaternary sea level history and paleozoogeography of Santa Barbara and Anacapa Islands, Channel Islands National Park, California","docAbstract":"Marine terraces are common on the Pacific Coast of North America and record interglacial high-sea stands superimposed on either stable or tectonically rising crustal blocks. Despite many years of study of these landforms in southern California, little work on terraces has been conducted on the two smallest of the California Channel Islands, Santa Barbara Island (SBI) and Anacapa Island (ANA). Presented here are new field and laboratory data on the ages, paleontology, and sea level history of marine terraces of these two islands. On both islands, the lowest marine terraces have shoreline angle elevations of ∼11 m above sea level. Amino acid geochronology shows that terrace deposits on both islands host fossils of two ages, one group dating to the ∼120-ka high-sea stand and the other group likely dating to the ∼100-ka high-sea stand. A mix of fossil ages is consistent with the paleontology as well, with SBI in particular showing a faunal assemblage that includes both extralimital southern and southward-ranging species (inferred to be from the ∼120-ka high-sea stand) and extralimital northern and northward-ranging species (inferred to be from the ∼100-ka high-sea stand). Fossil mixing from these two high-sea stands supports the hypothesis that glacial isostatic adjustment (GIA) processes have left a strong imprint on the geologic record of sea level history in southern California. Nevertheless, the elevations of these terraces and that of a low terrace on Santa Cruz Island indicate that modeled GIA estimates of paleo-sea level for the peak of the last interglacial period at ∼120 ka could be too high. Future development of models of GIA effects on the Pacific Coast of North America will need to consider geologic records, such as those from SBI and ANA, in refining reconstructions of sea level history.
","language":"English","publisher":"Brigham Young University","doi":"10.3398/064.078.0403","usgsCitation":"Muhs, D., and Groves, L.T., 2018, Little islands recording global events: Late Quaternary sea level history and paleozoogeography of Santa Barbara and Anacapa Islands, Channel Islands National Park, California: Western North American Naturalist, v. 78, no. 4, p. 540-589, https://doi.org/10.3398/064.078.0403.","productDescription":"50 p.","startPage":"540","endPage":"589","ipdsId":"IP-084957","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":361393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Anacapa Island, Channel Islands National Park, Santa Barbara Island, Santa Cruz Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.95834350585936,\n 33.44633901936737\n ],\n [\n -119.00939941406249,\n 33.44633901936737\n ],\n [\n -119.00939941406249,\n 34.110667538758996\n ],\n [\n -119.95834350585936,\n 34.110667538758996\n ],\n [\n -119.95834350585936,\n 33.44633901936737\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":168575,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel R.","email":"dmuhs@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":757693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Groves, Lindsey T.","contributorId":213427,"corporation":false,"usgs":false,"family":"Groves","given":"Lindsey","email":"","middleInitial":"T.","affiliations":[{"id":12725,"text":"Natural History Museum of Los Angeles County","active":true,"usgs":false}],"preferred":false,"id":757694,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216831,"text":"70216831 - 2018 - Climate change science and modeling","interactions":[],"lastModifiedDate":"2020-12-10T21:53:51.815121","indexId":"70216831","displayToPublicDate":"2018-12-31T15:51:43","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesNumber":"NRS-181","chapter":"2","title":"Climate change science and modeling","docAbstract":"This chapter provides a brief background on climate change science, climate simulation models, and models that project the impacts of changes in climate on tree species and ecosystems. Throughout the chapter, boxes list resources for more information on each topic. A more detailed scientific review of climate change science, trends, and modeling can be found in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (IPCC 2014), and the Fourth National Climate Assessment (U.S. Global Climate Research Program [USGCRP] 2017).
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"General Technical Report NRS-181, Mid-Atlantic forest ecosystem vulnerability assessment and synthesis: A report from the Mid-Atlantic Climate Change Response Framework project","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","doi":"10.2737/NRS-GTR-181","collaboration":"USFS","usgsCitation":"Butler-Leopold, P.R., Iverson, L.R., Thompson III, F., Brandt, L.A., Handler, S.D., Janowiak, M.K., Shannon, P.D., Swanston, C.W., Bearer, S., Bryan, A., Clark, K.L., Czarnecki, G., DeSenze, P., Dijak, W.D., Fraser, J.S., Gugger, P.F., Hille, A., Hynicka, J., Jantz, C.A., Kelly, M.C., Krause, K.M., La Puma, I.P., Landau, D., Lathrop, R.G., Leites, L.P., Madlinger, E., Matthews, S.N., Ozbay, G., Peters, M.P., Prasad, A., Schmit, D.A., Shephard, C., Shirer, R., Skowronski, N.S., Steele, A., Stout, S., Thomas-Van Gundy, M., Thompson, J., Turcotte, R.M., Weinstein, D.A., and Yanez, A., 2018, Climate 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,{"id":70197879,"text":"70197879 - 2018 - Preliminary 2018 national seismic hazard model for the conterminous United States","interactions":[],"lastModifiedDate":"2019-06-27T16:19:28","indexId":"70197879","displayToPublicDate":"2018-12-31T15:51:06","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Preliminary 2018 national seismic hazard model for the conterminous United States","docAbstract":"The 2014 U.S. Geological Survey national seismic hazard model for the conterminous U.S. will be updated in 2018 and 2020 to coincide with the Building Seismic Safety Council’s Project 17 timeline for development of new building code design criteria. The two closely timed updates are planned to allow more time for the Provisions Update Committee to analyze the consequences of the hazard model changes in the design criteria. To prepare the 2018 update we held a workshop (March 7-8, 2018) with scientists and engineers to solicit feedback on the model. The 2018 model will be available for public comment during the summer of 2018. The purpose of this paper is to solicit feedback on the modeling choices and results. The 2018 NSHM considers an updated seismicity catalog and certain key changes in the way ground motions are calculated. First, we implemented new Next Generation Attenuation Relationships for the Central and Eastern North America Region and other published models that allow for the calculation of ground motions at additional periods and site classes in the central and eastern U.S. (CEUS). Second, basin depth terms were implemented in the ground motion models in select regions of the western U.S. (WUS) to account for enhanced long-period ground motions at softer soil sites overlying sedimentary basins. Preliminary results indicate higher ground motions for all periods in parts of the CEUS and for long-periods and soft soils in urban areas overlying sedimentary basins in the WUS.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Earthquake Engineering. National Conference. 11TH 2018. 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Salmon Oncorhynchus tshawytscha","title":"Efficacy of injectable tulathromycin for reduction of vertical transmission of Renibacterium salmoninarum in Spring Chinook Salmon Oncorhynchus tshawytscha","docAbstract":"Bacterial kidney disease (BKD) caused by Renibacterium salmoninarum (Rs) occurs nearly worldwide where wild or cultured salmonid fishes are present. Control of BKD is confounded by its two modes of transmission, horizontal (fish-to-fish) and vertical (from female parent to progeny via the eggs). A highly successful BKD control strategy employed in Pacific Northwest hatcheries culturing spring Chinook salmon (Oncorhynchus tshawytscha) includes: (1) injecting pre-spawning adults with a macrolide antibiotic to improve survival and reduce Rs infection levels, (2) broodstock culling of highly infected females and (3) improved fish husbandry. However, the future availability of the injectable macrolide antibiotic (erythromycin) used for adults is uncertain. This drug shortage has resulted in an urgent need to identify a replacement injectable antibiotic to ensure continued successful control of BKD. The research conducted was intended to provide information for addressing this need via preliminary tests of the safety and efficacy of a new macrolide antibiotic, injectable tulathromycin, which is sold under the trade name DRAXXIN® (Zoetis Animal Health). A long-term goal is to reduce or eliminate the use of antibiotic treatment in spring Chinook salmon hatchery culture. Non-treated females were included in the study to provide empirical data in support of this goal. A subset of pre-spawning spring Chinook salmon at Leavenworth NFH was injected on July 10, 2014 with DRAXXIN at 5 mg per kg body weight (31 fish, left pelvic fin clip). Another subset of females (30 fish, right pelvic fin clip) was left uninjected. The surviving fish (31 DRAXXIN-injected fish and 28 uninjected fish) were spawned between August 18 and September 2, 2014. Although there were apparent trends toward higher pre-spawn survival and lower Rs prevalence and levels for the DRAXXIN-injected females in comparison to the uninjected females, the differences were not statistically significant for any of the Rs assays used (P > 0.05). Based on USFWS enzyme-linked immnosorbent assay (ELISA) test results of kidney tissue samples from the spawning females, egg lots from DRAXXIN-injected and uninjected females were assigned to Rs vertical transmission risk groups (low, medium or high). A subset of 220 eyed eggs from each female was transferred to the Western Fisheries Research Center (USGS) on October 8, 2014, hatched and reared until the study was terminated on September 22, 2015. The study results provided no evidence that DRAXXIN injection of adult female Chinook salmon affected their fecundity, egg eye-up, or survival and growth of progeny fry. There was little evidence of Rs infection in progeny of either DRAXXIN-injected or uninjected females, so the effect of DRAXXIN injection on vertical transmission of Rs could not be assessed. To adequately evaluate the efficacy of DRAXXIN injection for reducing Rs vertical transmission to progeny, additional studies should be conducted with larger numbers of DRAXXIN-injected and uninjected Chinook salmon females with a greater range of Rs levels.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Elliott, D., 2018, Efficacy of injectable tulathromycin for reduction of vertical transmission of Renibacterium salmoninarum in Spring Chinook Salmon Oncorhynchus tshawytscha, 28 p.","productDescription":"28 p.","ipdsId":"IP-100904","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":368850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":366054,"type":{"id":11,"text":"Document"},"url":"https://ecos.fws.gov/ServCat/DownloadFile/163944"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Elliott, Diane","contributorId":217727,"corporation":false,"usgs":true,"family":"Elliott","given":"Diane","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":767384,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70197891,"text":"70197891 - 2018 - Developing a global earthquake risk model","interactions":[],"lastModifiedDate":"2019-06-27T15:42:28","indexId":"70197891","displayToPublicDate":"2018-12-31T15:42:15","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Developing a global earthquake risk model","docAbstract":"The understanding of earthquake risk is the first step towards the development and implementation of disaster risk reduction measures. However, in many countries, especially the countries of the developing world, earthquake risk models either do not exist or are publicly inaccessible. The Global Earthquake Model (GEM) Foundation and its partners have been supporting regional programmes and bilateral collaborations to develop a global earthquake risk model, due by the end of 2018. This paper describes how the main components (seismic hazard, exposure models and vulnerability functions) of this global effort are being collected, developed or improved. The calculations are being performed using the OpenQuake-engine, the open-source software for seismic hazard and risk calculations supported by GEM. This model will be able to provide estimates of critical risk metrics such as annualized average economic and human losses or aggregated losses for particular return periods, which are fundamental to the development of efficient and effective mitigation planning.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of 16th European Conference on Earthquake Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"16th European Conference on Earthquake Engineering","conferenceDate":"18-21 June, 2018","conferenceLocation":"Thessaloniki, Greece","language":"English","publisher":"European Association for Earthquake Engineering","usgsCitation":"Silva, V., Crowley, H., Jaiswal, K.S., Acevedo, A.B., Pittore, M., and Journey, M., 2018, Developing a global earthquake risk model, in Proceedings of 16th European Conference on Earthquake Engineering, Thessaloniki, Greece, 18-21 June, 2018, 11834; 11 p.","productDescription":"11834; 11 p.","ipdsId":"IP-094620","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":365128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Silva, Vitor","contributorId":152129,"corporation":false,"usgs":false,"family":"Silva","given":"Vitor","email":"","affiliations":[{"id":18873,"text":"University of Aveiro","active":true,"usgs":false}],"preferred":false,"id":738955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crowley, Helen","contributorId":152131,"corporation":false,"usgs":false,"family":"Crowley","given":"Helen","email":"","affiliations":[{"id":18874,"text":"EUCENTRE","active":true,"usgs":false}],"preferred":false,"id":738956,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738957,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Acevedo, Ana Beatriz","contributorId":205958,"corporation":false,"usgs":false,"family":"Acevedo","given":"Ana","email":"","middleInitial":"Beatriz","affiliations":[{"id":37198,"text":"Universidad EAFIT","active":true,"usgs":false}],"preferred":false,"id":738958,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pittore, Massimiliano","contributorId":205959,"corporation":false,"usgs":false,"family":"Pittore","given":"Massimiliano","email":"","affiliations":[{"id":27333,"text":"GFZ","active":true,"usgs":false}],"preferred":false,"id":738959,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Journey, Murray","contributorId":205960,"corporation":false,"usgs":false,"family":"Journey","given":"Murray","email":"","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":738960,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70202971,"text":"70202971 - 2018 - Basin-scale model for predicting marsh edge erosion","interactions":[],"lastModifiedDate":"2019-09-13T11:05:58","indexId":"70202971","displayToPublicDate":"2018-12-31T15:26:53","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Basin-scale model for predicting marsh edge erosion","docAbstract":"Recent attempts to relate marsh edge retreat rate to wave power have met varying levels of success. Schwimmer (2001) correlated wave power to marsh boundary retreat rates over a five-year period along sites within Rehoboth Bay, Delaware, USA. Marani et al. (2011) derived a linear relationship between volumetric retreat rate and mean wave power density using Buckingham’s theorem of dimensional analysis. Leonardi and Fagherazzi (2015) added an exponential function to the Schwimmer (2001) equation to account for variability in soil resistance and mean wave height. These equations factor in soil type, water elevation, vegetation, and macrofauna through field-calibrated empirical constants, i.e., they are not explicitly considered. Consequently, the existing capability of predicting marsh edge erosion rate as a function of wave power and soil and vegetation properties is rather limited for engineering applications. For instance, Allison et al. (2017) show that without taking the marsh platform, soil, and vegetation into account, the relationships between marsh edge erosion rates and wave power on a basin or coastal-wide scale are not strong enough statistically to serve as a useful predictive model. 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