We present the evolution over 3 months of a 2016–2017 pāhoehoe flow at Kīlauea as it changed from a narrow sheet flow into a compound lava field fed by a stable system of tubes. The portion of the flow located on Kīlauea's coastal plain was characterized using helicopter‐based visible and thermal structure‐from‐motion photogrammetry to construct a series of georeferenced digital surface models and thermal maps on eight different days. Results reveal key influences on the emplacement and evolution of such long‐lived pāhoehoe flows. This region of the flow grew by ~12 × 106 m3 with a near‐constant time‐average discharge rate of 1.2–2.7 m3/s. The development of two tube systems is captured and shows an initial nascent tube enhanced by a narrow topographic confinement, which later inflated and created a topographic inversion that modulated the emplacement of a second flow lobe with its own tube system. The analysis of breakouts at various stages of the field's life suggests that the evolution of the thermal and morphological properties of the flow surface reflect its maturity. Thermal properties of breakouts were used to expand the empirical relationship of breakout cooling to longer timescales. This study contributes to the long‐term development and validation of more accurate predictive models for pāhoehoe, required during the management of long‐lasting lava flow crises in Hawai'i and elsewhere.
Climate change is anticipated to exacerbate the extinction risk of species whose persistence is already compromised by habitat loss, invasive species, disease, or other stressors. In coastal areas of the southeastern United States (USA), many imperiled vertebrates are vulnerable to hurricanes, which climate models predict to become more severe in the 21st century. Despite this escalating threat, explicit adaptation strategies that address hurricane threats, in particular, and climate change more generally, are largely underrepresented in recovery planning and implementation. We provide a basis for stronger emphasis on strategic planning for imperiled species facing the increasing threat of catastrophic hurricanes. Our reasoning comes from observations of short‐term environmental and biological impacts of Hurricane Michael, which impacted the Gulf Coast of the southeastern USA in October 2018. During this storm, St. Marks National Wildlife Refuge, located along the northern Gulf of Mexico's coast in the panhandle region of Florida, received storm surge that was 3.0–3.6 m (NAVD88) above sea level. Storm surge pushed sea water into some ephemeral freshwater ponds used for breeding by the federally threatened frosted flatwoods salamander (Ambystoma cingulatum). After the storm, specific conductance across all ponds measured varied from 80 to 23,100 µS/cm, compared to 75 to 445 µS/cm in spring 2018. For 17 overwashed wetlands that were measured in both spring and fall 2018, posthurricane conductance observations were, on average, more than 90 times higher than in the previous spring, setting the stage for varying population responses across this coastal landscape. Importantly, we found live individual flatwoods salamanders at both overwashed and non‐overwashed sites, although we cannot yet assess the demographic consequences of this storm. We outline actions that could be incorporated into climate adaptation strategies and recovery planning for imperiled species, like A. cingulatum, that are associated with freshwater coastal wetlands in hurricane‐prone regions.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5277","usgsCitation":"Walls, S., Barichivich, W., Chandler, J., Meade, A.M., Milinichik, M., O'Donnell, K., Owens, M.E., Peacock, T., Reinman, J., Watling, R.C., and Wetsch, O.E., 2019, Seeking shelter from the storm: Conservation and management of imperiled species in a changing climate: Ecology and Evolution, v. 9, no. 12, p. 7122-7133, https://doi.org/10.1002/ece3.5277.","productDescription":"12 p.","startPage":"7122","endPage":"7133","ipdsId":"IP-104173","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":467580,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5277","text":"Publisher Index Page"},{"id":437439,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V4A2GV","text":"USGS data release","linkHelpText":"Specific conductance of flatwood salamander breeding ponds: pre- and post-Hurricane Michael, 2013-2018"},{"id":364829,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"St Mark's National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.5013427734375,\n 29.897805610155874\n ],\n [\n -83.95889282226562,\n 29.897805610155874\n ],\n [\n -83.95889282226562,\n 30.18787014479982\n ],\n [\n -84.5013427734375,\n 30.18787014479982\n ],\n [\n -84.5013427734375,\n 29.897805610155874\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"12","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Walls, Susan 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Jonathan","contributorId":216364,"corporation":false,"usgs":false,"family":"Chandler","given":"Jonathan","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":764624,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meade, Ashley M.","contributorId":216365,"corporation":false,"usgs":false,"family":"Meade","given":"Ashley","email":"","middleInitial":"M.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":764625,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Milinichik, Marysa","contributorId":216366,"corporation":false,"usgs":false,"family":"Milinichik","given":"Marysa","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":764626,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O'Donnell, Katherine 0000-0001-9023-174X","orcid":"https://orcid.org/0000-0001-9023-174X","contributorId":216367,"corporation":false,"usgs":true,"family":"O'Donnell","given":"Katherine","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":764627,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Owens, Megan E. 0000-0002-6686-6873","orcid":"https://orcid.org/0000-0002-6686-6873","contributorId":216368,"corporation":false,"usgs":false,"family":"Owens","given":"Megan","email":"","middleInitial":"E.","affiliations":[{"id":39396,"text":"Conservation Legacy","active":true,"usgs":false}],"preferred":false,"id":764628,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Peacock, Terry","contributorId":187746,"corporation":false,"usgs":false,"family":"Peacock","given":"Terry","email":"","affiliations":[],"preferred":false,"id":764629,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reinman, Joseph","contributorId":187747,"corporation":false,"usgs":false,"family":"Reinman","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":764630,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Watling, Rebecca C.","contributorId":216369,"corporation":false,"usgs":false,"family":"Watling","given":"Rebecca","email":"","middleInitial":"C.","affiliations":[{"id":39396,"text":"Conservation Legacy","active":true,"usgs":false}],"preferred":false,"id":764631,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wetsch, Olivia E.","contributorId":216370,"corporation":false,"usgs":false,"family":"Wetsch","given":"Olivia","email":"","middleInitial":"E.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":764632,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70251345,"text":"70251345 - 2019 - Variability in shelf sedimentation in response to fluvial sediment supply and coastal erosion over the past 1,000 years in Monterey Bay, CA, United States","interactions":[],"lastModifiedDate":"2024-02-07T00:55:28.857949","indexId":"70251345","displayToPublicDate":"2019-05-29T18:52:31","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Variability in shelf sedimentation in response to fluvial sediment supply and coastal erosion over the past 1,000 years in Monterey Bay, CA, United States","docAbstract":"Continental shelf environments are uniquely situated to capture some of the most dynamic processes on Earth including climatic variability and anthropogenic modifications to coastal systems. Understanding how these processes have affected sediment delivery and accumulation on the shelf in the past may provide insight into potential changes in the future. To address this, we investigated shelf sedimentation within Monterey Bay, California. Sediment cores were collected from four locations throughout the bay to capture both the modern and late Holocene sedimentological record using grain size analysis, and sediment chronologies determined from 210Pb, 137Cs, and 14C. From the grain size results we focused on the total percent sand, and established a Littoral Sand Fraction (LSF) index to assess sediment contribution from the littoral zone as a result coastal erosion. Grain size results from the multicores consistently showed an increase in sand over the past several decades (post 1970s). For the cores located within the bay proximal to three major rivers, the increase in sand corresponded to a general increase in the LSF over the same period. We attributed these trends to increased sediment contributions to the shelf due to accelerated coastal erosion in the region. This accelerated coastal erosion was likely the combined result of dam construction in the mid-twentieth century that limited fluvial supply to the coast, and a shift in climate toward wetter, stormier period. Applying these sediment characteristics back over the past ∼1,000 years we found that dry climatic periods resulted in deposits that were limited in total sand but enriched in littoral material suggesting elevated coastal erosion. During wet periods deposits were enriched in total sand but limited in littoral sand suggesting elevated fluvial supply and low erosion. Compared to the late Holocene record, the previous several decades represent a shift to a new regime, uncharacteristic of deposits over the past millennia, highlighting the impact humans have had on shelf sedimentation.
Recruitment of brown bear (Ursus arctos) offspring into a population is the product of initial cub production and subsequent survival and is a critical component of overall population status and trend. We investigated the relationship between maternal body size, body condition, and age (as a surrogate for gained experience) and recruitment of dependent offspring (≥1 yr old) in 4 Alaska, USA (2014–2017), brown bear populations using logistic regression. Body size alone was our top predictor of the presence of offspring and appeared in all top models. Our data suggest that bear size is the primary driver of productivity across all 4 study populations, with larger bears having a greater chance of being observed with offspring. The effect of body condition was likely confounded by the increased energetic costs of supporting cubs through time and had a negative relationship with recruitment. Age (experience) was positively related to recruitment. Understanding the relative importance of body size, body condition, and age on the recruitment of offspring provides insights into life-history trade-offs female bears must manage as they strive to meet the nutritional costs of cub production and rearing, while minimizing risks to themselves and their offspring. Further assessment of long-term longitudinal studies of brown bears that assess the lifetime reproductive output of individuals would be highly informative to further assess the effect of experience on recruitment and to support the management of brown bear populations for recovery, conservation, sustained yield, and ecosystem function.
","language":"English","publisher":"BioOne","doi":"10.2192/URSUS-D-18-00008.1","usgsCitation":"Hilderbrand, G., Gustine, D., Joly, K., Mangipane, B., Leacock, W., Cameron, M., Sorum, M., Mangipane, L., and Erlenbach, J., 2019, The influence of body size, condition, and age on recruitment of four Alaskan brown bear populations: Ursus, v. 2, no. 29, p. 111-118, https://doi.org/10.2192/URSUS-D-18-00008.1.","productDescription":"8 p.","startPage":"111","endPage":"118","ipdsId":"IP-081284","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":467583,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2192/ursus-d-18-00008.1","text":"Publisher Index Page"},{"id":364525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Brooks Range, Gates of the Arctic National Park & Preserve, Katmai National Park & Preserve, Kodiak National Wildlife Refuge, Lake Clark National Park & Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.33496093749997,\n 55.99838095535963\n ],\n [\n -150.9521484375,\n 55.99838095535963\n ],\n [\n -150.9521484375,\n 62.67414334669093\n ],\n [\n -158.33496093749997,\n 62.67414334669093\n ],\n [\n -158.33496093749997,\n 55.99838095535963\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.13769531249997,\n 66.31986144668052\n ],\n [\n -147.3046875,\n 66.31986144668052\n ],\n [\n -147.3046875,\n 68.70448628851169\n ],\n [\n -156.13769531249997,\n 68.70448628851169\n ],\n [\n -156.13769531249997,\n 66.31986144668052\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","issue":"29","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hilderbrand, Grant V. 0000-0002-0051-8315 ghilderbrand@usgs.gov","orcid":"https://orcid.org/0000-0002-0051-8315","contributorId":199764,"corporation":false,"usgs":true,"family":"Hilderbrand","given":"Grant V.","email":"ghilderbrand@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":false,"id":763923,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gustine, David","contributorId":200449,"corporation":false,"usgs":false,"family":"Gustine","given":"David","affiliations":[],"preferred":false,"id":763924,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Joly, Kyle","contributorId":53117,"corporation":false,"usgs":false,"family":"Joly","given":"Kyle","email":"","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":763925,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mangipane, Buck","contributorId":211731,"corporation":false,"usgs":false,"family":"Mangipane","given":"Buck","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":763926,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leacock, William","contributorId":192123,"corporation":false,"usgs":false,"family":"Leacock","given":"William","affiliations":[],"preferred":false,"id":763927,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cameron, Matthew","contributorId":204963,"corporation":false,"usgs":false,"family":"Cameron","given":"Matthew","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":763928,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sorum, Mathew","contributorId":204962,"corporation":false,"usgs":false,"family":"Sorum","given":"Mathew","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":763929,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mangipane, Lindsey","contributorId":201731,"corporation":false,"usgs":false,"family":"Mangipane","given":"Lindsey","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":763930,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Erlenbach, Joy","contributorId":200750,"corporation":false,"usgs":false,"family":"Erlenbach","given":"Joy","affiliations":[],"preferred":false,"id":763931,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70203058,"text":"sir20195033 - 2019 - Simulation of the regional groundwater-flow system in the St. Louis River basin, Minnesota","interactions":[],"lastModifiedDate":"2019-05-30T15:53:37","indexId":"sir20195033","displayToPublicDate":"2019-05-29T11:15:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5033","displayTitle":"Simulation of the Regional Groundwater-Flow System in the St. Louis River Basin, Minnesota","title":"Simulation of the regional groundwater-flow system in the St. Louis River basin, Minnesota","docAbstract":"The St. Louis River Basin (SLRB) covers 3,600 square miles in northeastern Minnesota, with headwaters in the Mesabi Range and extensive wetlands and lakes throughout the basin. To better understand the regional groundwater system in the SLRB, a two-dimensional, steady-state groundwater-flow model of the SLRB was developed by the U.S. Geological Survey, in cooperation with the Minnesota Ojibwe Bands, using the analytic-element computer code GFLOW. The parameter-estimation software suite PEST was used to obtain a best fit of the modeled to measured groundwater levels and streamflows. The calibrated regional model was locally refined to create a smaller version of the model, the central SLRB model, that was used to evaluate hydrologic effects from extensive ditching in wetlands of the central SLRB. The refinements included adding ditches that were not represented in the regional model and modifying the aquifer base elevation to be more representative of the localized area. The central SLRB model was recalibrated to better match the distribution of mapped wetlands. Two scenarios were run of the central SLRB model: one with ditches and one without ditches. The model results were compared between the two scenarios to assess the effect of ditching on the groundwater system and potential changes to hydrologic conditions that support wetlands.
Calibration of the regional SRLB model resulted in average horizontal hydraulic conductivity values of 6–39 feet per day for the glacial deposits and 3–4 feet per day for the uppermost fractured bedrock in the Biwabik Iron-Formation on the Mesabi Range. Average recharge across the calibrated model was 5.9 inches per year. Linesink resistance for the routed stream network was calibrated by using resistance categories based on the mapped soil hydrologic groups. The modeled regional groundwater-flow direction was generally to the south near the Mesabi Range topographic high and south or southwest across the rest of the basin.
The updated calibration of the central SLRB model resulted in average horizontal hydraulic conductivity values of 5–36 feet per day for the glacial deposits and 3 feet per day for the uppermost fractured Biwabik Iron-Formation of the Mesabi Range. Average recharge across the ditch scenarios was 4.1 inches per year. Comparison of the preditch and postditch model scenarios showed that ditching reduced the area where the modeled water table was within 1 foot of the land surface (a wetland hydrology indicator) in as much as 40,000 acres, or 37 percent, of mapped permanent wetlands in the SLRB. An increase in the depth to the water table in wetland areas has the potential to degrade wetland persistence or function.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195033","collaboration":"Prepared in cooperation with the Minnesota Ojibwe Bands","usgsCitation":"Haserodt, M.J., Hunt, R.J., Cowdery, T.K., Leaf, A.T., and Baker, A.C., 2019, Simulation of the regional groundwater-flow system in the St. Louis River Basin, Minnesota: U.S. Geological Survey Scientific Investigations Report 2019–5033, 41 p., https://doi.org/10.3133/sir20195033.","productDescription":"Report: vii, 41 p.; Data Release","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-103278","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":437445,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KUJ0L3","text":"USGS data release","linkHelpText":"GFLOW Groundwater Flow Model of the St. Louis River Basin, Minnesota"},{"id":437444,"rank":4,"type":{"id":30,"text":"Data 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\"}}]}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
The Upper Floridan aquifer (UFA) is the principal water source for industrial and public supply in Glynn County, Georgia. Wells in active pumping centers that tap the UFA for industries near the city of Brunswick have created an upward hydraulic-head gradient in the Floridan aquifer system, which has allowed high chloride (saline) groundwater from the Fernandina permeable zone of the Lower Floridan aquifer (LFA) to migrate upward into freshwater zones. Chloride concentrations of more than 250 milligrams per liter—the State and Federal secondary drinking-water standard—have been measured in a 2-square-mile area near downtown Brunswick.
An existing regional U.S. Geological Survey modular finite-difference groundwater-flow model (MODFLOW-2000) was modified using greater horizontal and vertical resolution to enable more detailed simulation of the effects of pumping in the vicinity of chloride contamination. Modifications to the regional model consisted of (1) limiting grid size to a maximum of 500 feet (ft) per side in the vicinity of the chloride plume; (2) representing the upper and lower Brunswick aquifers with distinct model layers; (3) similarly, representing upper and lower water-bearing zones of the UFA with distinct model layers in Glynn and Camden Counties, Ga.; and (4) establishing new hydraulic-property geographic zones in the UFA within Glynn County. The revised groundwater-flow model was calibrated to steady-state conditions that were assumed to exist during 2000 and 2004. The calibration and framework of the revised groundwater-flow model were documented in a separate report. For the current study, steady-state conditions were calibrated using October 2015 pumping rates in the Brunswick/Glynn County area as a 2015 Base Case. The 2015 Base Case simulation was used as the basis to evaluate seven groundwater-management scenarios in the Brunswick/Glynn County area.
Seven groundwater management-scenarios were developed on the basis of short- and long-term groundwater-use projections for the UFA in the Brunswick/Glynn County area. Scenarios A and B simulated additional pumping in the upper water-bearing zone (UWBZ) of the UFA at existing public-supply wells located near a chloride plume and planned public-supply wells to be constructed north of downtown Brunswick. Scenario C simulated a shutdown at Brunswick Cellulose Inc. and Pinova Inc. and the resulting deactivation of nine production wells, with a combined total pumping of 31.3 million gallons per day (Mgal/d) for the 2015 Base Case simulation. Scenario D (three scenarios) simulated 12.5, 25, and 50 percent (designated Scenarios D1, D2, and D3) of the total pumping of 31.3 Mgal/d at Brunswick Cellulose and Pinova. The objective of Scenario D was to determine pumping rates that may reverse groundwater-flow directions toward the Brunswick Cellulose well field and potentially allow groundwater with higher chloride concentration to migrate toward nearby public-supply wells. Scenario E simulated an additional pumping of 5 Mgal/d from the UWBZ of the UFA at a recently constructed production well within the Brunswick Cellulose well field.
Backward particle-tracking (MODPATH) analysis in public-supply wells located just outside the chloride plume to the north shows that predominant groundwater-flow directions are from the northeast toward the Brunswick Cellulose well field. The analysis covered 20- and 50-year periods for the 2015 Base Case and Scenario C simulations with 100 percent of backtracked particles remaining in the UWBZ and lower water-bearing zone of the UFA. Groundwater-flow directions are characterized by some vertical movement and dominant horizontal movement away from the chloride plume in the northern Brunswick area. For the 2015 Base Case simulation, the mean rate of particle movement ranged from 268 to 413 feet per year. For the Scenario C simulation, the mean rate of particle movement ranged from 89 to 182 feet per year with 50 percent of particles migrating from the chloride plume area. The rate of particle movement is influenced most by the horizontal hydraulic-head gradient in the UWBZ of the UFA.
The revised groundwater-flow model is subject to the limitations documented in the original model. In addition, the values used for the specified-head boundaries in the Floridan aquifer system for the 2004 calibrated model were based on the sparse data available and were not changed for the 2015 update to the model. These model boundaries control 80 percent of the inflows and about 60 percent of the outflows. Composite-scaled sensitivities of the model parameters indicate the revised model is most sensitive to pumping rates, followed by the horizontal hydraulic conductivity in the UFA for zones along coastal Georgia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195035","collaboration":"Prepared in cooperation with the Brunswick-Glynn County Joint Water and Sewer Commission and the Georgia Environmental Protection Division","usgsCitation":"Cherry, G.S., 2019, Simulation of groundwater flow in the Brunswick area, Georgia, for 2004 and 2015, and selected groundwater-management scenarios: U.S. Geological Survey Scientific Investigations Report 2019–5035, 70 p., https://doi.org/10.3133/sir20195035.","productDescription":"Report: vii, 70 p.; Data Release","numberOfPages":"82","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-089920","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":364052,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5035/coverthb.jpg"},{"id":364054,"rank":3,"type":{"id":30,"text":"Data 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\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
To assess the effectiveness of protected areas in two catchment scales (local and network) in conserving regionally common fluvial fishes using modelled species distributions.
Conterminous United States.
A total of 150 species were selected that were geographically widespread, abundant, non‐habitat specialists and native within nine large ecoregions. Species distribution models were developed using boosted regression trees, and modelled distributions were assessed for protection status under two alternatives: lands strictly managed for biodiversity (Highly Restricted Use) and those allowing multiple uses (Multiple Use), with protection target levels (i.e., the amount of protected area required for protection) for local and network catchments being developed from ecoregion‐based urban and agricultural land use thresholds from fish responses.
Overall, less than 2% of fluvial catchments in the conterminous USA are meeting both local and network catchment protection target levels under the Highly Restricted Use alternative, whereas 16% of catchments met protection levels for the Multiple Use alternative, with protection largely concentrated in the western USA. For common native species distributions within ecoregions, only one species had >10% of streams meeting combined local and network catchment protection target levels under the Highly Restricted Use alternative, whereas 50 distributions (~14% of species distribution models) met this level under the Multiple Use alternative.
Even for fishes considered widespread and abundant, protection levels are lacking, particularly when considering only lands that are actively managed for biodiversity. Given the increasing intensification of anthropogenic activities and substantial uncertainty associated with climate change, considering the conservation status for all species, including those currently considered common, is warranted.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.12937","usgsCitation":"Cooper, A.R., Tsang, Y., Infante, D.M., Daniel, W.M., McKerrow, A., and Wieferich, D.J., 2019, Protected areas lacking for many common fluvial fishes of the conterminous USA: Diversity and Distributions, v. 25, no. 8, p. 1289-1303, https://doi.org/10.1111/ddi.12937.","productDescription":"15 p.","startPage":"1289","endPage":"1303","ipdsId":"IP-101901","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":460377,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12937","text":"Publisher Index Page"},{"id":437447,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AHFPIN","text":"USGS data release","linkHelpText":"Ecoregion Based Aquatic Gap Distribution Models for Common Fluvial Fishes of the Conterminous 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0000-0002-7656-8474","orcid":"https://orcid.org/0000-0002-7656-8474","contributorId":215451,"corporation":false,"usgs":false,"family":"Daniel","given":"Wesley","email":"","middleInitial":"M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":805432,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":127753,"corporation":false,"usgs":true,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":805433,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wieferich, Daniel J. 0000-0003-1554-7992 dwieferich@usgs.gov","orcid":"https://orcid.org/0000-0003-1554-7992","contributorId":176205,"corporation":false,"usgs":true,"family":"Wieferich","given":"Daniel","email":"dwieferich@usgs.gov","middleInitial":"J.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":5069,"text":"Office of the AD Core Science Systems","active":true,"usgs":true}],"preferred":true,"id":805434,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203627,"text":"70203627 - 2019 - Growing pains of crowdsourced stream stage monitoring using mobile phones: The development of CrowdHydrology","interactions":[],"lastModifiedDate":"2019-05-28T11:46:37","indexId":"70203627","displayToPublicDate":"2019-05-28T09:46:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Growing pains of crowdsourced stream stage monitoring using mobile phones: The development of CrowdHydrology","docAbstract":"Citizen science-based approaches to monitor the natural environment tend to be bimodal in maturity. Older and established programs such as the Audubon’s Christmas bird count and Community Collaborative Rain, Hail, and Snow Network (CoCoRaHS) have thousands of participants across decades of observations, while less mature citizen science projects have shorter lifespans often focused on local or regional observations with tens or hundreds of participants. For the latter, it can be difficult to transition into a more mature and sustainable citizen science-based research program. This paper focuses on this transition by evaluating CrowdHydrology (ca. 2010), a citizen science project that has transitioned from a regional to national network. It evaluates the data accuracy, citizen participation, and station popularity. The CrowdHydrology network asks citizens to send in text messages of water levels in streams and lakes, which has resulted in 16,294 observations submitted by over 8,000 unique participants at 120 unique locations. Using water level data and participation records from CrowdHydrology, we analyze the expansion and citizen participation from a regional to national citizen science network. We identify barriers to participation and evaluate why some citizen science observation stations are popular while others are not. We explore our chosen contributory program model for CrowdHydrology and the influence this model has had on long-term participation. Results demonstrate a highly variable rate of contributions of citizen scientists. This paper proposes hypotheses on why many of our observations are from one-time participants and why some monitoring stations are more popular than others. Finally, we address the future expansion of the CrowdHydrology network by evaluating successful monitoring locations and growing interest of watershed groups to expand the network of gauges.","language":"English","publisher":"Frontiers in Earth Science","doi":"10.3389/feart.2019.00128","usgsCitation":"Lowry, C., Fienen, M.N., Hall, D.M., and Stepenuck, K., 2019, Growing pains of crowdsourced stream stage monitoring using mobile phones: The development of CrowdHydrology: Frontiers in Earth Science, v. 7, no. 128, 10 p., https://doi.org/10.3389/feart.2019.00128.","productDescription":"10 p.","ipdsId":"IP-107829","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":467589,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2019.00128","text":"Publisher Index 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Christopher","contributorId":215879,"corporation":false,"usgs":false,"family":"Lowry","given":"Christopher","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":763317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":171511,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael","email":"mnfienen@usgs.gov","middleInitial":"N.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":763316,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, Damon M.","contributorId":215880,"corporation":false,"usgs":false,"family":"Hall","given":"Damon","email":"","middleInitial":"M.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":763318,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stepenuck, Kristine","contributorId":215881,"corporation":false,"usgs":false,"family":"Stepenuck","given":"Kristine","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":763319,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203752,"text":"70203752 - 2019 - Explosive summit collapse of Kīlauea Volcano in 1924 preceded by a decade of crustal contamination and anomalous Pb isotope ratios","interactions":[],"lastModifiedDate":"2019-06-10T09:46:30","indexId":"70203752","displayToPublicDate":"2019-05-28T09:38:16","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Explosive summit collapse of Kīlauea Volcano in 1924 preceded by a decade of crustal contamination and anomalous Pb isotope ratios","docAbstract":"A geochemical time-series analysis of lavas from frequently active basaltic volcanoes has the potential to reveal the enigmatic mantle controls on volcanic behavior and hazards. In May 1924, the century-long lava lake within Halemaʻumaʻu pit crater at the summit of Kīlauea Volcano drained and the floor of Halemaʻumaʻu collapsed, triggering ∼3 weeks of phreatic explosions due to the interaction of groundwater with hot rock. For the next three decades, eruptions at Kīlauea were sporadic (the longest hiatus was from 1934 to 1952), small in volume, and short (typically <1 month long). Here, we show that the Pb isotope ratios of Kīlauea lava groundmass and tephra glass samples erupted from 1912 to 1954 are anomalous and unusually variable. Many of the samples have elevated 207Pb/204Pb ratios (at a given 206Pb/204Pb), ranging up to ∼0.05 higher than is typical for Kīlauea lavas. The variations in 206Pb/204Pb for samples from 1912–1913 (∼0.055), 1917–1921 (∼0.120), 1923 (∼0.065), and 1952–1954 (∼0.037) are larger over short time periods (∼1–4 yr) than observed during the Puʻu ʻŌʻō rift eruption (only ∼0.031 from 1986 to 2012). These Pb isotopic signatures resulted from variable amounts of crustal contamination (most likely by Pb-rich hydrothermal sulfide minerals with high 207Pb/204Pb ratios) as the parental magmas transited the ∼110 Ma Pacific oceanic crust. This crustal contamination was not directly related to the shallow volcanic events of 1924. Instead, mantle-driven processes at Kīlauea during the previous century—a factor of ∼2 decrease in the degree of partial melting of an increasingly refractory source—led to a decline in the magma supply rate, a major disruption of the magmatic plumbing system, and, for at least a decade prior to 1924, crustal contamination at or below the base of the volcanic edifice (>10 km). The Pb isotopic heterogeneity of the samples on short length (hand specimen to lava flow) and time (∼1–4 yr) scales can be explained by inefficient mixing as small batches of contaminated magma were delivered to the remnants of Kīlauea’s summit magma storage reservoir. Our results confirm that the Pb isotope ratios of basalts from ocean-island volcanoes may be significantly modified by assimilation of materials from the underlying oceanic crust. In particular, the 207Pb/204Pb ratio may be a sensitive tracer of such crustal contamination at Hawaiian shield volcanoes. Mauna Loa lavas display a factor of ∼5 more scatter towards higher 207Pb/204Pb at a given 206Pb/204Pb ratio than most Kīlauea lavas (excluding the samples from 1912 to 1954). This might be caused by more pervasive crustal contamination at Mauna Loa due to its lower magma supply rate over the last ∼4 kyr.
In the North Pacific, northern fulmar (Fulmarus glacialis) forms extensive colonies in few locales, which may lead to limited gene flow and locale-specific population threats. In the Atlantic, there are thousands of colonies of varying sizes and in Europe the species is considered threatened. Prior screens and classical microsatellite development in fulmar failed to provide a suite of markers adequate for population genetics studies.
The objective of this study was to isolate a suite of polymorphic microsatellite loci with sufficient variability to quantify levels of gene flow, population affinity, and identify familial relationships in fulmar. We also performed a cross-species screening of these markers in eight other species.
We used shotgun sequencing to isolate 26 novel microsatellite markers in fulmar to screen for variability using individuals from two distinct regions: the Pacific (Chagulak Island, Alaska) and the Atlantic (Hafnarey Island, Iceland).
Polymorphism was present in 24 loci in Chagulak and 23 in Hafnarey, while one locus failed to amplify in either colony. Polymorphic loci exhibited moderate levels of genetic diversity and this suite of loci uncovered genetic structuring between the regions. Among the other species screened, polymorphism was present in one to seven loci.
The loci yielded sufficient variability for use in population studies and estimation of familial relationships; as few as five loci provide resolution to determine individual identity. These markers will allow further insight into the global population dynamics and phylogeography of fulmars. We also demonstrated some markers are transferable to other species.
We estimate earthquake ground-motion variability in the central and eastern U.S. (CEUS) by varying the model parameters of a deterministic physics-based and a stochastic site-based simulation method. Utilizing a moderate-magnitude database of recordings, we simulate ground motions for larger-magnitude scenarios M6.0, 6.5, 7.0, 7.5, and 8.0. For the physics-based method, we vary the faulting mechanism, slip, stress drop, rupture velocity, source depth, and 1D velocity structure. For the stochastic method, we simulate realizations using a set of six model parameters, each of which has a pre-assigned probability distribution. The median spectral accelerations over all synthetic realizations are compared with the NGA-East models. The synthetic standard deviation for deterministic simulations ranges from approximately 0.4 to 0.85 for various magnitudes and distances, whereas that for stochastic simulations is between 0.48 and 1.04. Based on the simulation results and comparisons with NGA-East variability models, a range for ground motion variability in the CEUS is discussed.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"ICASP 13 Proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP13)","conferenceDate":"May 26-30, 2019","conferenceLocation":"Seoul, South Korea","language":"English","publisher":"Seoul National University","doi":"10.22725/ICASP13.075","usgsCitation":"Sun, X., Rezaeian, S., Clayton, B., and Hartzell, S.H., 2019, Estimation of ground motion variability in the CEUS using simulations, in ICASP 13 Proceedings, Seoul, South Korea, May 26-30, 2019, 75; 8 p., https://doi.org/10.22725/ICASP13.075.","productDescription":"75; 8 p.","ipdsId":"IP-105826","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":365065,"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":{"editors":[{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":758280,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Sun, Xiaodan","contributorId":139583,"corporation":false,"usgs":false,"family":"Sun","given":"Xiaodan","email":"","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address: TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":false,"id":758278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":758277,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clayton, Brandon S. 0000-0003-0502-7184 bclayton@usgs.gov","orcid":"https://orcid.org/0000-0003-0502-7184","contributorId":197196,"corporation":false,"usgs":true,"family":"Clayton","given":"Brandon","email":"bclayton@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":758279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":765123,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208130,"text":"70208130 - 2019 - Probabilistic seismic hazard analysis using stochastic simulated ground motions","interactions":[],"lastModifiedDate":"2020-01-31T11:16:05","indexId":"70208130","displayToPublicDate":"2019-05-26T11:10:52","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Probabilistic seismic hazard analysis using stochastic simulated ground motions","docAbstract":": In recent years, ground motion models used in probabilistic seismic hazard analyses (PSHA) have evolved from the traditional approach of using ground motion prediction equations (GMPEs) to using ground motion time series models. The purpose of this paper is to develop an approach to perform a probabilistic seismic hazard analysis using stochastic site-based simulation techniques. These techniques consist of empirical stochastic models that simulate both near-fault and far-field ground motion time series. The near-fault models consider directivity pulses, which can impose large seismic demands. The proposed approach was applied to a site located in Los Angeles Downtown and the corresponding hazard curves were developed. The results were compared to hazard curves derived for the same site from CyberShake, which uses a physics-based simulation approach, and from a traditional GMPE approach. The comparison indicated that the proposed methodology accurately describes the seismic hazard at the site at high hazard levels. The proposed approach is computationally efficient compared to the use of physics-based simulations like CyberShake.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of ICASP13","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"13th International Conference on Applications of Statistics and Probability in Civil Engineering","conferenceDate":"May 26-30, 2019","conferenceLocation":"Seoul, South Korea","language":"English","publisher":"Seoul National University","doi":"10.22725/ICASP13.235","usgsCitation":"Azar, S., Dabaghi, M., and Rezaeian, S., 2019, Probabilistic seismic hazard analysis using stochastic simulated ground motions, in Proceedings of ICASP13, Seoul, South Korea, May 26-30, 2019, 8 p., https://doi.org/10.22725/ICASP13.235.","productDescription":"8 p.","ipdsId":"IP-105873","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":371808,"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":"Azar, Sarah","contributorId":221887,"corporation":false,"usgs":false,"family":"Azar","given":"Sarah","email":"","affiliations":[{"id":40455,"text":"American University of Beirut","active":true,"usgs":false}],"preferred":false,"id":780639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dabaghi, Mayssa","contributorId":221888,"corporation":false,"usgs":false,"family":"Dabaghi","given":"Mayssa","email":"","affiliations":[{"id":40455,"text":"American University of Beirut","active":true,"usgs":false}],"preferred":false,"id":780640,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":780638,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205083,"text":"70205083 - 2019 - Mismatches between breeding phenology and resource abundance of resident alpine ptarmigan negatively affect chick survival","interactions":[],"lastModifiedDate":"2019-09-04T14:52:15","indexId":"70205083","displayToPublicDate":"2019-05-26T07:30:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Mismatches between breeding phenology and resource abundance of resident alpine ptarmigan negatively affect chick survival","docAbstract":"1. Phenological mismatches – defined here as the difference in reproductive timing of an individual relative to the availability of its food resources – occur in many avian species. Mistiming breeding activities in environments with constrained breeding windows may have severe fitness costs due to reduced opportunities for repeated breeding attempts. Therefore, species occurring in alpine environments may be particularly vulnerable. 2. We studied fitness consequences of timing of breeding in an alpine-endemic species, the white-tailed ptarmigan (Lagopus leucura), to investigate its influence on chick survival. We estimated phenological mismatch by measuring plant and arthropods used by ptarmigan in relation to their timing of breeding. 3. We monitored 120 nests and 67 broods over a three-year period (2013–2015) at three alpine study sites in the Rocky Mountains of Colorado. During this same period we actively monitored food resource abundance in brood-use areas to develop year and site specific resource phenology curves. We developed several mismatch indices from these curves that were then fit as covariates in mark-recapture chick survival models. 4. A correlation analysis between seasonal changes in arthropod and food plant abundance indicated that a normalized difference vegetation index (NDVI) was likely the best predictor for food available to hens and chicks. A survival model that included an interaction between NDVI mismatch and chick age received strong support and indicated young chicks were more susceptible to mismatch than older chicks. 5. We provide evidence that individual females of a resident alpine species can be negatively affected by phenological mismatch. Our study focused on individual females and did not examine if phenological mismatch was present at the population level. Future work in animal populations occurring in mountain systems focusing on a combination of both individual- and population- level metrics of mismatch will be beneficial.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5290","usgsCitation":"Wann, G.T., Aldridge, C.L., Seglund, A.E., Oyler-McCance, S.J., Kondratieff, B.C., and Braun, C.E., 2019, Mismatches between breeding phenology and resource abundance of resident alpine ptarmigan negatively affect chick survival: Ecology and Evolution, v. 9, no. 12, p. 7200-7212, https://doi.org/10.1002/ece3.5290.","productDescription":"13 p.","startPage":"7200","endPage":"7212","ipdsId":"IP-108042","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":467594,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5290","text":"Publisher Index Page"},{"id":367106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Wann, Gregory T 0000-0001-9076-7819","orcid":"https://orcid.org/0000-0001-9076-7819","contributorId":218685,"corporation":false,"usgs":false,"family":"Wann","given":"Gregory","email":"","middleInitial":"T","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":769909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":769908,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seglund, Amy E.","contributorId":218686,"corporation":false,"usgs":false,"family":"Seglund","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":769910,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":769913,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kondratieff, Boris C.","contributorId":24868,"corporation":false,"usgs":false,"family":"Kondratieff","given":"Boris","email":"","middleInitial":"C.","affiliations":[{"id":17860,"text":"Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":769911,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Braun, Clait E.","contributorId":200013,"corporation":false,"usgs":false,"family":"Braun","given":"Clait","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":769912,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208423,"text":"70208423 - 2019 - Implications of seismic design values for economic losses","interactions":[],"lastModifiedDate":"2020-02-10T06:51:24","indexId":"70208423","displayToPublicDate":"2019-05-26T06:50:15","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Implications of seismic design values for economic losses","docAbstract":"In the U.S., seismic design values are determined mostly through a risk-targeting process, which combines information about the expected collapse fragility of code-designed structures with seismic hazard at a site. However, this target only applies where the risk-targeted ground motions govern the design. In other areas, primarily close to active faults, seismic design values are reduced to values calculated from deterministic seismic hazard analysis, increasing seismic risk for near-fault sites by an unknown quantity. This study investigates the implications of designing buildings using deterministic and probabilistic design values in terms of earthquake-induced economic consequences. This investigation is carried out using a performance-based seismic risk assessment of modern code-designed buildings with various structural systems, following the FEMA P-58 framework. Specifically, structural responses and losses associated with code-designed systems (i.e., reinforced concrete, steel, wood light frame, and precast tilt-up buildings) considering different design values (i.e., risk-targeted, deterministic, and uniform-hazard) are assessed. This study finds that, while risk-targeted design maps specify a uniform collapse risk, they do not provide uniform risk of economic losses to modern buildings across the U.S. and are instead dependent on building type and site properties. Also, for the sites in this study governed by deterministic capping, design values in the current code may be up to 30% lower than design values derived from risk-targeted design maps, resulting in up to 40% higher expected seismic losses.","conferenceTitle":"13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP13)","conferenceDate":"May 26-30, 2019","conferenceLocation":"Seoul, South Korea","language":"English","publisher":"SNU","doi":"10.22725/ICASP13.206","usgsCitation":"Cook, D., Liel, A.B., Luco, N., Almeter, E., and Haselton, C.B., 2019, Implications of seismic design values for economic losses, 13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP13), Seoul, South Korea, May 26-30, 2019, 8 p., https://doi.org/10.22725/ICASP13.206.","productDescription":"8 p.","ipdsId":"IP-105831","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":372179,"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":"Cook, Dustin","contributorId":222296,"corporation":false,"usgs":false,"family":"Cook","given":"Dustin","email":"","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":781820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liel, Abbie B.","contributorId":184158,"corporation":false,"usgs":false,"family":"Liel","given":"Abbie","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":781821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":781819,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Almeter, Edward","contributorId":222297,"corporation":false,"usgs":false,"family":"Almeter","given":"Edward","email":"","affiliations":[{"id":40513,"text":"Haselton Baker Risk Group","active":true,"usgs":false}],"preferred":false,"id":781822,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haselton, Curt B.","contributorId":202457,"corporation":false,"usgs":false,"family":"Haselton","given":"Curt","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":781823,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70205123,"text":"70205123 - 2019 - Characterizing groundwater/surface-water interaction using hydrograph-separation techniques and groundwater-level data throughout the Mississippi Delta, USA","interactions":[],"lastModifiedDate":"2019-09-04T15:44:24","indexId":"70205123","displayToPublicDate":"2019-05-25T15:37:09","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing groundwater/surface-water interaction using hydrograph-separation techniques and groundwater-level data throughout the Mississippi Delta, USA","docAbstract":"The Mississippi Delta, located in northwest Mississippi, is an area dense with industrial-level agriculture sustained by groundwater-dependent irrigation supplied by the Mississippi River Valley Alluvial aquifer (alluvial aquifer). The Delta provides agricultural commodities across the United States and around the world. Observed declines in groundwater altitudes and streamflow contemporaneous with increases in irrigation have raised concerns about future groundwater availability and the effects of groundwater withdrawals on streamflow. To quantify the impacts of groundwater withdrawals on streamflow and increase understanding of groundwater and surface-water interaction, hydrograph-separation techniques were used to estimate baseflow and identify statistical streamflow trends. The analysis was conducted using the U.S. Geological Survey Groundwater Toolbox open-source software and daily hydrologic data provided by a spatially-distributed network of paired groundwater wells and streamgaging sites. This study found that effects of groundwater withdrawals on streamflow were observed as statistically significant reductions in baseflow in areas with substantial groundwater-altitude declines. Hydrograph-separation and trend analyses may be applicable to assess the impacts of groundwater withdrawals in altered environments and streamflow may be used as a proxy for changes in groundwater availability. Characterizing and defining hydrologic relations between groundwater and surface water will help scientists and water-resource managers refine a regional groundwater-flow model that includes the Mississippi Delta that will be used to aid water-resource managers in future decisions concerning the alluvial aquifer.","language":"English","publisher":"Springer","doi":"10.1007/s10040-019-01981-6","usgsCitation":"Killian, C.D., Asquith, W.H., Barlow, J.R., Bent, G., Kress, W., Barlow, P.M., and Schmitz, D.W., 2019, Characterizing groundwater/surface-water interaction using hydrograph-separation techniques and groundwater-level data throughout the Mississippi Delta, USA: Hydrogeology Journal, v. 27, no. 6, p. 2167-2179, https://doi.org/10.1007/s10040-019-01981-6.","productDescription":"13 p.","startPage":"2167","endPage":"2179","ipdsId":"IP-092609","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":467595,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-019-01981-6","text":"Publisher Index Page"},{"id":367194,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Illinois, Kentucky, Louisiana, Mississippi, Missouri, Tennessee","otherGeospatial":"Mississippi River Valley Alluvial Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.30810546875,\n 37.23032838760387\n ],\n [\n -88.846435546875,\n 37.67512527892127\n ],\n [\n -89.71435546875,\n 37.71859032558816\n ],\n [\n -90.439453125,\n 37.020098201368114\n ],\n [\n -92.054443359375,\n 35.02999636902566\n ],\n [\n -91.5380859375,\n 33.4039312002347\n ],\n [\n -91.95556640625,\n 32.4263401615464\n ],\n [\n -92.098388671875,\n 32.03602003973755\n ],\n [\n -91.505126953125,\n 31.475524020001806\n ],\n [\n -90.8349609375,\n 31.42866311735861\n ],\n [\n -89.791259765625,\n 33.14675022877648\n ],\n [\n -90.186767578125,\n 34.66032236481892\n ],\n [\n -88.9892578125,\n 36.76529191711624\n ],\n [\n -88.30810546875,\n 37.23032838760387\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Killian, Courtney D. 0000-0002-2137-2722","orcid":"https://orcid.org/0000-0002-2137-2722","contributorId":213990,"corporation":false,"usgs":true,"family":"Killian","given":"Courtney","email":"","middleInitial":"D.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asquith, William H. 0000-0002-7400-1861 wasquith@usgs.gov","orcid":"https://orcid.org/0000-0002-7400-1861","contributorId":1007,"corporation":false,"usgs":true,"family":"Asquith","given":"William","email":"wasquith@usgs.gov","middleInitial":"H.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barlow, Jeannie R. B. 0000-0002-0799-4656 jbarlow@usgs.gov","orcid":"https://orcid.org/0000-0002-0799-4656","contributorId":3701,"corporation":false,"usgs":true,"family":"Barlow","given":"Jeannie","email":"jbarlow@usgs.gov","middleInitial":"R. B.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bent, Gardner C. 0000-0002-5085-3146","orcid":"https://orcid.org/0000-0002-5085-3146","contributorId":205226,"corporation":false,"usgs":true,"family":"Bent","given":"Gardner C.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770120,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kress, Wade 0000-0002-6833-028X","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":203539,"corporation":false,"usgs":true,"family":"Kress","given":"Wade","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770121,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barlow, Paul M. 0000-0003-4247-6456 pbarlow@usgs.gov","orcid":"https://orcid.org/0000-0003-4247-6456","contributorId":1200,"corporation":false,"usgs":true,"family":"Barlow","given":"Paul","email":"pbarlow@usgs.gov","middleInitial":"M.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":770119,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmitz, Darrel W. 0000-0002-6154-8040","orcid":"https://orcid.org/0000-0002-6154-8040","contributorId":218742,"corporation":false,"usgs":false,"family":"Schmitz","given":"Darrel","email":"","middleInitial":"W.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":770122,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70215293,"text":"70215293 - 2019 - Predicting hydrologic disturbance of streams using species occurrence data","interactions":[],"lastModifiedDate":"2020-10-14T15:39:43.431592","indexId":"70215293","displayToPublicDate":"2019-05-25T10:32:10","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Predicting hydrologic disturbance of streams using species occurrence data","docAbstract":"Aquatic organisms have adapted over evolutionary time-scales to hydrologic variability represented by the natural flow regime of rivers and streams in their unimpaired state. Rapid landscape change coupled with growing human demand for water have altered natural flow regimes of many rivers and streams on a global scale. Climate non-stationarity is expected to further intensify hydrologic variability, placing increased pressure on aquatic communities. Using a machine learning approach and georeferenced species occurrence data, we modeled and mapped spatial patterns of hydrologic disturbance for streams in Arkansas, Missouri, and eastern Oklahoma. Random forest (RF) models trained on fish community data, hydrologic, and landscape metrics for gaged streams in the National Hydrography (NHDPlusV2) database were used to predict a hydrologic disturbance index (HDI) for ungaged streams. The HDI is part of the USGS Geospatial Attributes of Gages for Evaluating Streamflow (GAGESII) database and is a composite index of watershed-scale disturbance from anthropogenic stressors. Fish presence/absence data had similar overall model prediction accuracy (77%; 95% CI: 0.74, 0.80) as flow variables (76%; CI: 0.73, 0.80). Including topographic variables increased the RF prediction accuracy of both the fish (90%; CI: 0.88, 0.92) and flow models (86%; CI: 0.84, 0.89). Spatial patterns of hydrologic disturbance suggest distinct ecohydrological regions exist where conservation actions may be focused. Streams with low HDI were predominately located in the Ozark Highlands, Boston Mountains, and Ouachita Mountains. Correlation analysis of HDI by flow regime showed groundwater stable streams had the lowest disturbance frequency, with over 50% of stream reaches with low HDI located in forested land cover. HDI was highest for big rivers, intermittent runoff streams and streams in areas of agricultural land use. Our results show long-term georeferenced biological data can provide a valuable resource for predictive modeling of hydrologic disturbance for ungaged rivers and streams.
We evaluated relationships among hydrogeomorphology, vegetation structure and composition, and avian communities among three subreaches of the San Acacia Reach of the Middle Rio Grande (MRG) River of New Mexico. The subreaches varied in degradation, with Subreach 1 being severely entrenched and hydrologically disconnected, Subreach 2 being the least impacted, and Subreach 3 being intermediately disturbed. Avian point count and habitat surveys were conducted to determine avian community structure and abundance, geomorphic feature, surface flooding, and vegetation structure and composition. Ground-nesting birds and low shrub-nesting birds were insensitive to hydrogeomorphic changes as they do not rely on native understory but can use exotic understory or woody debris. In contrast, canopy-nesting birds required native overstory; therefore, they were sensitive to hydrogeomorphic changes as native overstory species require surface floods to germinate and establish. Additionally, native overstory did not vary as expected as the moderately impacted subreach, Subreach 3, had more native overstory (
Avian avulavirus (commonly known as avian paramyxovirus-1 or APMV-1) can cause disease of varying severity in both domestic and wild birds. Understanding how viruses move among hosts and geography would be useful for informing prevention and control efforts. A Bayesian statistical framework was employed to estimate the evolutionary history of 1602 complete fusion gene APMV-1 sequences collected from 1970 to 2016 in order to infer viral transmission between avian host orders and diffusion among geographic regions. Ancestral states were estimated with a non-reversible continuous-time Markov chain model, allowing transition rates between discrete states to be calculated. The evolutionary analyses were stratified by APMV-1 classes I (n = 198) and II (n = 1404), and only those sequences collected between 2006 and 2016 were allowed to contribute host and location information to the viral migration networks.
While the current data was unable to assess impact of host domestication status on APMV-1 diffusion, these analyses supported the sharing of APMV-1 among divergent host taxa. The highest supported transition rate for both classes existed from domestic chickens to Anseriformes (class I:6.18 transitions/year, 95% highest posterior density (HPD) 0.31–20.02, Bayes factor (BF) = 367.2; class II:2.88 transitions/year, 95%HPD 1.9–4.06, BF = 34,582.9). Further, among class II viruses, domestic chickens also acted as a source for Columbiformes (BF = 34,582.9), other Galliformes (BF = 34,582.9), and Psittaciformes (BF = 34,582.9). Columbiformes was also a highly supported source to Anseriformes (BF = 322.0) and domestic chickens (BF = 402.6). Additionally, our results provide support for the diffusion of viruses among continents and regions, but no interhemispheric viral exchange between 2006 and 2016. Among class II viruses, the highest transition rates were estimated from South Asia to the Middle East (1.21 transitions/year; 95%HPD 0.36–2.45; BF = 67,107.8), from Europe to East Asia (1.17 transitions/year; 95%HPD 0.12–2.61; BF = 436.2) and from Europe to Africa (1.06 transitions/year, 95%HPD 0.07–2.51; BF = 169.3).
While migration appears to occur infrequently, geographic movement may be important in determining viral diversification and population structure. In contrast, inter-order transmission of APMV-1 may occur readily, but most events are transient with few lineages persisting in novel hosts.
Groundwater inundation (GWI) is a particularly challenging consequence of sea-level rise (SLR), as it progressively inundates infrastructure located above and below the ground surface. Paths of flooding by GWI differ from other types of SLR flooding (i.e., wave overwash, storm-drain backflow) such that it is more difficult to mitigate, and thus requires a separate set of highly innovative adaptation strategies to manage. To spur consideration of GWI in planning, data-intensive numerical modeling methods have been developed that produce locally specific visualizations of GWI, though the accessibility of such methods is limited by extensive data requirements. Conversely, the hydrostatic (or 'bathtub') modeling approach is widely used in adaptation planning owing to easily accessed visualizations (i.e., NOAA SLR Viewer), yet its capacity to simulate GWI has never been tested. Given the separate actions necessary to mitigate GWI relative to marine overwash, this is a significant gap. Here we compare a simple hydrostatic modeling method with a more deterministic, dynamic and robust 3D numerical modeling approach to explore the effectiveness of the hydrostatic method in simulating equilibrium aquifer effects of multi-decadal sea-level rise, and in turn GWI for Honolulu, Hawai'i. We find hydrostatic modeling in the Honolulu area and likely other settings may yield similar results to numerical modeling when referencing the local mean higher-high water tide datum (generally typical of flood studies). These findings have the potential to spur preliminary understanding of GWI impacts in municipalities that lack the required data to conduct rigorous groundwater-modeling investigations. We note that the methods explored here for Honolulu do not simulate dynamic coastal processes (i.e., coastal erosion, sediment accretion or changes in land cover) and thus are most appropriately applied to regions that host heavily armored shorelines behind which GWI can develop.
","language":"English","publisher":"IOP Publishing","doi":"10.1088/2515-7620/ab21fe","usgsCitation":"Habel, S., Fletcher, C., Rotzoll, K., El-Kadi, A.I., and Oki, D., 2019, Comparison of a simple hydrostatic and a data-intensive 3D numerical modeling method of simulating sea-level rise induced groundwater inundation for Honolulu, Hawai'i, USA: Environmental Research Letters, v. 1, no. 4, 041005, 12 p., https://doi.org/10.1088/2515-7620/ab21fe.","productDescription":"041005, 12 p.","ipdsId":"IP-102017","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":467598,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/2515-7620/ab21fe","text":"Publisher Index Page"},{"id":385147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"O'ahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.04931640625,\n 21.289374355860424\n ],\n [\n -157.9010009765625,\n 21.289374355860424\n ],\n [\n -157.9010009765625,\n 21.4121622297254\n ],\n [\n -158.04931640625,\n 21.4121622297254\n ],\n [\n -158.04931640625,\n 21.289374355860424\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"1","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-05-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Habel, Shellie 0000-0001-9295-0596","orcid":"https://orcid.org/0000-0001-9295-0596","contributorId":257499,"corporation":false,"usgs":false,"family":"Habel","given":"Shellie","email":"","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":814397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fletcher, Charles H.","contributorId":257500,"corporation":false,"usgs":false,"family":"Fletcher","given":"Charles H.","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":814398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rotzoll, Kolja 0000-0002-5910-888X","orcid":"https://orcid.org/0000-0002-5910-888X","contributorId":201087,"corporation":false,"usgs":false,"family":"Rotzoll","given":"Kolja","affiliations":[],"preferred":false,"id":814399,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"El-Kadi, Aly I. 0000-0002-9623-5458","orcid":"https://orcid.org/0000-0002-9623-5458","contributorId":257501,"corporation":false,"usgs":false,"family":"El-Kadi","given":"Aly","email":"","middleInitial":"I.","affiliations":[{"id":35886,"text":"University of Hawaii at Manoa, Water Resources Research Center","active":true,"usgs":false}],"preferred":false,"id":814400,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oki, Delwyn S. 0000-0002-6913-8804","orcid":"https://orcid.org/0000-0002-6913-8804","contributorId":207735,"corporation":false,"usgs":true,"family":"Oki","given":"Delwyn S.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814401,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}