{"pageNumber":"844","pageRowStart":"21075","pageSize":"25","recordCount":184617,"records":[{"id":70197577,"text":"ofr20181097 - 2018 - Preliminary evaluation of the hydrogeology and groundwater quality of the Mississippi River Valley alluvial aquifer and Memphis aquifer at the Tennessee Valley Authority Allen Power Plants, Memphis, Shelby County, Tennessee","interactions":[],"lastModifiedDate":"2022-04-19T21:07:45.52464","indexId":"ofr20181097","displayToPublicDate":"2018-07-10T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1097","title":"Preliminary evaluation of the hydrogeology and groundwater quality of the Mississippi River Valley alluvial aquifer and Memphis aquifer at the Tennessee Valley Authority Allen Power Plants, Memphis, Shelby County, Tennessee","docAbstract":"

The hydrogeology, groundwater quality, and potential for hydraulic connection between the Mississippi River Valley alluvial aquifer and the Memphis aquifer in the area of the Tennessee Valley Authority (TVA) Allen Combined Cycle and Allen Fossil Plants in southwestern Memphis, Tennessee, were evaluated from September through December 2017. The study was designed as a preliminary assessment of the potential for leakage of groundwater from the Mississippi River Valley alluvial aquifer through the underlying upper Claiborne confining unit into the underlying Memphis aquifer at the plants. A short-term aquifer test of four of the five Memphis aquifer production wells installed at the Allen Combined Cycle Plant induced drawdown in water levels in the Mississippi River Valley alluvial aquifer, locally. The largest drawdown occurred in the eastern and southeastern parts of the TVA plants area, and generally was coincident with locations where stratigraphic data show increased thickness of and depth to the base of the alluvium and decreased thickness and inferred offset in the base of the confining unit relative to nearby locations. In contrast, stratigraphic data for most other locations at the site indicate shallower depths to the base of the alluvium and more consistent thickness of and depth to the base of the confining unit, which corresponds with areas where less drawdown was observed during the test. Water-quality results for samples from the production wells and from monitoring wells screened in the Mississippi River Valley alluvial aquifer indicate that groundwater with higher dissolved-solids concentrations and tritium from this shallow aquifer has mixed with water in the upper part of the Memphis aquifer at one of the production wells. Results of the study collectively confirm that the Mississippi River Valley alluvial and Memphis aquifers are hydraulically connected near the TVA plants area.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181097","collaboration":"Prepared for the Tennessee Valley Authority in cooperation with the University of Memphis, Center for Applied Earth Science and Engineering Research","usgsCitation":"Carmichael, J.K., Kingsbury, J.A., Larsen, Daniel, and Schoefernacker, Scott, 2018, Preliminary evaluation of the hydrogeology and groundwater quality of the Mississippi River Valley alluvial aquifer and Memphis aquifer at the Tennessee Valley Authority Allen Power Plants, Memphis, Shelby County, Tennessee: U.S. Geological Survey Open-File Report 2018–1097, 66 p., https://doi.org/10.3133/ofr20181097.","productDescription":"Report: vii, 66 p.; Data Release","numberOfPages":"78","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095383","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":355577,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LSM5YU","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-level models used to estimate drawdown in 32 monitoring wells screened in the Mississippi River Valley alluvial aquifer and 4 observation wells screened in the Memphis aquifer during an aquifer test at the Tennessee Valley Authority Allen power plants, Memphis, Shelby County, Tennessee, October 2017"},{"id":399134,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_107532.htm"},{"id":355576,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1097/ofr20181097.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1097"},{"id":355575,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1097/coverthb.jpg"}],"country":"United States","state":"Tennessee","county":"Shelby County","city":"Memphis","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.2208,\n 35.0428\n ],\n [\n -90.1211,\n 35.0428\n ],\n [\n -90.1211,\n 35.1\n ],\n [\n -90.2208,\n 35.1\n ],\n [\n -90.2208,\n 35.0428\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Lower Mississippi-Gulf Water Science Center—Tennessee
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2018-07-10","noUsgsAuthors":false,"publicationDate":"2018-07-10","publicationStatus":"PW","scienceBaseUri":"5b46e53ee4b060350a15d055","contributors":{"authors":[{"text":"Carmichael, John K. 0000-0003-1099-841X jkcarmic@usgs.gov","orcid":"https://orcid.org/0000-0003-1099-841X","contributorId":4554,"corporation":false,"usgs":true,"family":"Carmichael","given":"John","email":"jkcarmic@usgs.gov","middleInitial":"K.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kingsbury, James A. 0000-0003-4985-275X jakingsb@usgs.gov","orcid":"https://orcid.org/0000-0003-4985-275X","contributorId":883,"corporation":false,"usgs":true,"family":"Kingsbury","given":"James","email":"jakingsb@usgs.gov","middleInitial":"A.","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":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larsen, Daniel","contributorId":199300,"corporation":false,"usgs":false,"family":"Larsen","given":"Daniel","email":"","affiliations":[{"id":17864,"text":"University of Memphis","active":true,"usgs":false}],"preferred":false,"id":737821,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schoefernacker, Scott","contributorId":205566,"corporation":false,"usgs":false,"family":"Schoefernacker","given":"Scott","email":"","affiliations":[{"id":17864,"text":"University of Memphis","active":true,"usgs":false}],"preferred":false,"id":737822,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198050,"text":"70198050 - 2018 - Quantifying variance across spatial scales as part of fire regime classifications","interactions":[],"lastModifiedDate":"2018-07-12T22:54:19","indexId":"70198050","displayToPublicDate":"2018-07-10T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying variance across spatial scales as part of fire regime classifications","docAbstract":"

The emergence of large‐scale fire classifications and products informed by remote sensing data has enabled opportunities to include variability or heterogeneity as part of modern fire regime classifications. Currently, basic fire metrics such as mean fire return intervals are calculated without considering spatial variance in a management context. Fire return intervals are also only applicable at a particular grain size (defined as the spatial unit of interest) even though they are typically applied homogeneously. In this study, we utilized a 29‐yr fire occurrence database to show how spatial variance changes with respect to grain as postulated by Wiens (1989) when reporting fire patterns within the Great Plains, USA. We utilized data from the Monitoring Trends in Burn Severity database of fire occurrence for the years 1984–2012. We analyzed median numbers of fire along with their variance at four spatial grains ranging from small units (e.g., plots at 3 × 3 km resolution) to large units (e.g., landscapes at 1500 × 2700 km resolution). Median number of fire occurrences was consistently low, irrespective of grain. Despite the consistency in low median numbers of fires across grain, variance in the numbers of fires between units decreased. Variance within units, however, did not change as grain increased indicating fire‐pattern‐scale inconsistencies. Fire pattern interpretations depended entirely on the scale at which it is calculated. Given that the Great Plains region has a large disparity in fire patterns (i.e., some regions burn often, while others may never burn), fire regime classifications will benefit from including scale‐specific variance estimates as a foundation for understanding changes in fire regimes and corresponding social–ecological and policy responses.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2343","usgsCitation":"Rheinhardt, S., Fuhlendorf, S.D., Leis, S.A., Picotte, J.J., and Twidwell, D., 2018, Quantifying variance across spatial scales as part of fire regime classifications: Ecosphere, v. 9, no. 7, e02343: 12 p., https://doi.org/10.1002/ecs2.2343.","productDescription":"e02343: 12 p.","ipdsId":"IP-076490","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":468597,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2343","text":"Publisher Index Page"},{"id":355621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"7","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-10","publicationStatus":"PW","scienceBaseUri":"5b46e53ce4b060350a15d051","contributors":{"authors":[{"text":"Rheinhardt, Scholtz 0000-0002-9275-6504","orcid":"https://orcid.org/0000-0002-9275-6504","contributorId":206199,"corporation":false,"usgs":false,"family":"Rheinhardt","given":"Scholtz","email":"","affiliations":[{"id":37281,"text":"Department of Natural Resource Ecology and Management. Oklahoma State University, Stillwater, OK, 74078, USA","active":true,"usgs":false}],"preferred":false,"id":739775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuhlendorf, Samuel D.","contributorId":171488,"corporation":false,"usgs":false,"family":"Fuhlendorf","given":"Samuel","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":739777,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leis, Sherry A.","contributorId":178699,"corporation":false,"usgs":false,"family":"Leis","given":"Sherry","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":739776,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":739774,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Twidwell, Dirac","contributorId":187431,"corporation":false,"usgs":false,"family":"Twidwell","given":"Dirac","email":"","affiliations":[],"preferred":false,"id":739778,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198041,"text":"70198041 - 2018 - Bat community response to silvicultural treatments in bottomland hardwood forests managed for wildlife in the Mississippi Alluvial Valley","interactions":[],"lastModifiedDate":"2018-07-10T10:13:52","indexId":"70198041","displayToPublicDate":"2018-07-10T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Bat community response to silvicultural treatments in bottomland hardwood forests managed for wildlife in the Mississippi Alluvial Valley","docAbstract":"

Silvicultural treatments (e.g., selective timber harvests) that are prescribed to promote wildlife habitat are intended to alter the physical structure of forests to achieve conditions deemed beneficial for wildlife. Such treatments have been advocated for management of bottomland hardwood forests on public conservation lands in the Mississippi Alluvial Valley. Although some songbirds respond positively to these management actions, and wildlife-forestry indirectly promotes bat prey availability, bat response is largely unknown. Forest structure may affect bat use of bottomland forests due to differences in foraging space or roost sites. We examined the effects of silvicultural treatments that were implemented to promote wildlife habitat on bat species activity. We conducted vegetation surveys and sampled insect biomass within 64 treated and 64 reference stands located on 15 public conservation areas in Arkansas, Louisiana, and Mississippi, USA. We examined the influence of vegetation metrics and insect biomass on acoustic detections of bats during passive nocturnal surveys in these stands. Detections of bat activity were similar between silviculturally treated stands and reference stands, indicating that both managed and reference stands provide habitat for generalist and forest interior bat species. Generalist bat species (e.g., evening bats, eastern red bats, and Seminole bats) were positively associated with increased insect biomass and the amount of dead wood within a stand. Basal area of large trees was positively associated with detection of tri-colored bats and bottomland specialists (Rafinesque’s big-eared bats and myotine bats). Conversely, acoustic detection of bats was negatively associated with increased vegetative density (i.e., clutter). Managers that implement silvicultural treatments to improve desired forest conditions for wildlife can provide habitat for both generalist and forest interior bat species by providing heterogeneous forest structure that includes dead wood, high basal area of large trees, high tree species diversity, and gaps that are sufficiently thinned to allow unimpeded flight by bats.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2018.02.047","usgsCitation":"Ketzler, L.P., Comer, C.E., and Twedt, D.J., 2018, Bat community response to silvicultural treatments in bottomland hardwood forests managed for wildlife in the Mississippi Alluvial Valley: Forest Ecology and Management, v. 417, p. 40-48, https://doi.org/10.1016/j.foreco.2018.02.047.","productDescription":"9 p.","startPage":"40","endPage":"48","ipdsId":"IP-095614","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468596,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2018.02.047","text":"Publisher Index Page"},{"id":355574,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Louisiana, Mississippi","otherGeospatial":"Mississippi Alluvial Valley","volume":"417","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e53de4b060350a15d053","contributors":{"authors":[{"text":"Ketzler, Loraine P.","contributorId":187409,"corporation":false,"usgs":false,"family":"Ketzler","given":"Loraine","email":"","middleInitial":"P.","affiliations":[{"id":32360,"text":"Stephen F. Austin State University, Nacogdoches, TX","active":true,"usgs":false}],"preferred":false,"id":739759,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Comer, Christopher E.","contributorId":166690,"corporation":false,"usgs":false,"family":"Comer","given":"Christopher","email":"","middleInitial":"E.","affiliations":[{"id":32360,"text":"Stephen F. Austin State University, Nacogdoches, TX","active":true,"usgs":false}],"preferred":false,"id":739760,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Twedt, Daniel J. 0000-0003-1223-5045 dtwedt@usgs.gov","orcid":"https://orcid.org/0000-0003-1223-5045","contributorId":398,"corporation":false,"usgs":true,"family":"Twedt","given":"Daniel","email":"dtwedt@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":739761,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196535,"text":"sir20185059 - 2018 - Santa Barbara and Foothill groundwater basins Geohydrology and optimal water resources management—Developed using density dependent solute transport and optimization models","interactions":[],"lastModifiedDate":"2018-08-06T16:46:22","indexId":"sir20185059","displayToPublicDate":"2018-07-10T00:00:00","publicationYear":"2018","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":"2018-5059","title":"Santa Barbara and Foothill groundwater basins Geohydrology and optimal water resources management—Developed using density dependent solute transport and optimization models","docAbstract":"

Groundwater has been a part of the city of Santa Barbara’s water-supply portfolio since the 1800s; however, since the 1960s, the majority of the city’s water has come from local surface water, and the remainder has come from groundwater, State Water Project, recycled water, increased water conservation, and as needed, seawater desalination. Although groundwater from the Santa Barbara and Foothill groundwater basins only accounts for a small percentage of the long-term supply, it is an important source of supplemental water during times of surface-water shortages. During the late 1980s and early 1990s, production wells extracted additional groundwater to compensate for drought related water-delivery shortfalls from other sources; in response, water levels declined substantially in the Santa Barbara and Foothill groundwater basins (below sea level in the Santa Barbara groundwater basin).

In coastal basins that have groundwater extraction near shore, seawater intrusion is often a problem. Seawater intrusion in the Santa Barbara groundwater basin is thought to be more limited than in other coastal basins because of an offshore fault that acts as a partial barrier to groundwater flow. During the late 1980s and early 1990s, seawater intrusion was observed in the Santa Barbara groundwater basin, as indicated by increased chloride concentrations at several monitoring wells that ranged from 200 ft to 1,300 ft from the ocean and as close as 2,900 ft to the nearest pumping well. This demonstrated that seawater can intrude into the Santa Barbara groundwater basin when groundwater levels fall below sea level near the coast.

The city of Santa Barbara is interested in developing a better understanding of the sustainability of its groundwater supplies. In 2014, California adopted historic legislation to manage its groundwater: the Sustainable Groundwater Management Act (SGMA). The SGMA requires the development and implementation of “Groundwater Sustainability Plans” in 127 priority groundwater basins; although Santa Barbara was not a designated priority basin, the city is taking steps to achieve sustainability. Sustainability was defined in the SGMA in terms of avoiding undesirable results: significant and unreasonable groundwater-level declines, reduction in groundwater storage, seawater intrusion, water-quality degradation, land subsidence, and surface-water depletion.

In this project, a cooperative study between the U.S. Geological Survey (USGS) and the city of Santa Barbara, sustainable yield is defined as the volume of groundwater that can be pumped from storage without causing water-level drawdowns and the associated increases in seawater intrusion (as indicated by increases in measured chloride concentrations) at selected wells. In order to estimate the sustainability of Santa Barbara’s groundwater basins, a three-dimensional density-dependent groundwater-flow and solute-transport model (the Santa Barbara Flow and Transport Model, or SBFTM) was developed on the basis of an existing groundwater-flow model. To simulate seawater intrusion to the Santa Barbara Basin under various management strategies, the SBFTM uses the USGS code SEAWAT to simulate salinity transport and variable-density flow. The completed SBFTM was coupled with a management optimization tool, in this case a multi-objective evolutionary algorithm, to determine optimal pumping strategies that maximize the sustainable yield and at the same time satisfy user-defined drawdown and chloride-concentration constraints.

As part of this study, a three-dimensional hydrogeologic framework model was developed to quantify the extent and hydrogeologic characteristics of the Santa Barbara and Foothill groundwater basins and to help define the discretization and hydraulic properties used in the SBFTM. The development of the hydrogeologic framework model required the collection and reconciliation of geologic and geophysical data from existing maps, reports, and databases, along with geologic and hydrologic data from recently drilled wells. These data were integrated into a three-dimensional hydrogeologic framework model that defines the stratigraphy and geometry of the aquifer zones and the major geologic structures in the basin. The hydrogeologic framework model also quantifies the variation in sediment grain size within each aquifer zone as the percentage of coarse-grained sediment. Previous studies indicated that there are two principal water-producing zones in the Santa Barbara groundwater basin, the upper and lower producing zones; an additional thin, productive zone was identified as part of this study. This “middle producing zone” is not as areally extensive as the upper and lower producing zones and only exists in the coastal part of Storage Unit I. These producing zones are bounded at depth by less productive shallow, middle, and deep zones.

Two versions of the SBFTM were constructed: an initial-condition model and a modern transient model. The initial-condition model is a long-term transient model that simulates flow and solute-transport conditions during a period with limited anthropogenic influences preceeding the modern transient model. The simulation-transient model simulates flow and transport conditions from 1929 through 2013; however, because of data availability, the focus of the model calibration was 1972–2013. The SBFTM was calibrated to measured groundwater levels and drawdown, as well as measured chloride concentrations and change in concentrations, using a combination of automated and trial-and-error parameter-estimation techniques.

A sensitivity analysis indicated that, in general, the SBFTM was most sensitive to recharge- and pumping-distribution parameters, specifically those controlling the amount of small-catchment recharge and the distribution of water extraction by hydrogeologic layer for production wells. The model was also sensitive to parameters controlling stream-recharge rates, horizontal and vertical hydraulic conductivity, and porosity.

From 1929 to 1971, most of the water entering the area represented by the SBFTM was from creek and small-catchment recharge, and the majority of water leaving the SBFTM area was from pumping, discharge to creeks, and drains. In addition, about 37 percent of the total pumpage came from a net reduction in groundwater storage. From 1972 to 2013, the amount of water entering and leaving the SBFTM was fairly similar as that from 1929 to 1971, except the reduction in pumpage added about 17,000 acre-ft of water to storage. During this later period, there were also times of storage loss. For example, during July 1990, a month when approximately 705 acre-ft of groundwater was pumped in the study area, the pumpage was much greater than all sources of recharge combined, and about 382 acre-ft of water was removed from groundwater storage.

Simulated hydraulic heads replicated the observed data to an acceptable matching of the measured water-level, flow direction, and vertical gradients. Simulated hydrographs for selected wells were in good agreement with the measured data, with an average residual of -2.7 ft and a standard deviation of 14.5 ft, indicating that the simulated heads, on average, underestimated the observed water levels. An examination of the model fit indicated that most of the discrepancies were lower simulated heads at wells proximal to production well sites.

The simulated chloride concentrations reasonably matched the rising limbs of the measured breakthrough curves in terms of timing and magnitude; however, the simulation overestimated the chloride concentrations on the falling limbs. The overestimation of low chloride concentrations was attributed to the model overestimating the advance of the chloride front during periods of heavy pumping and underestimating the retreat of the chloride front during periods of low pumping. These simulation errors would result in a conservative response by local water managers to seawater intrusion.

The SBFTM was used to develop a collection of predictive simulations optimized to produce pumping schedules that maximize yield, subject to a set of constraints and competing objectives. The simulations were grouped as scenarios that differed in their time horizon, initial conditions for groundwater levels and chloride concentrations, as well as precipitation, which was incorporated into the model through simulated recharge. Overall, five scenarios were developed in a multi-objective framework to obtain optimal pumping rates for all of the wells managed by the city, while minimizing excessive drawdown and seawater intrusion.

For the current study, complexities in the simulation model and the optimization formulation required additional considerations. Incorporating the solute-transport equations to simulate chloride transport added a highly nonlinear process that is solved iteratively in each time step of the groundwater-flow model. These nonlinearities, coupled with the highly refined grid in the current model, creates challenges for many traditional optimization methods. Therefore, an optimization method was needed that could address nonlinear relationships as well as a very large problem size. Lastly, the optimization problem was reformulated to include multiple objectives without requiring convergence to a single solution. This approach, guided by the city’s objectives, allowed the maximum extraction of information from the complex simulation.

Borg, a multi-objective evolutionary algorithm, was chosen as the optimization algorithm for this study for several reasons: (1) it is very computationally efficient; (2) it can run in parallel; (3) it requires little user input; and (4) it can solve for multiple competing objectives. The first three points allow the algorithm to proceed toward the optimal solutions at the fastest possible rate. The fourth point is advantageous for large, complex optimization problems because it is difficult to formulate the optimization problem in a way that produces only one optimal solution.

The problem formulation consisted of four competing objectives and a constraint set in accordance with the main concerns of the city. The objectives were maximizing total pumpage, minimizing seawater intrusion, minimizing total drawdown in production wells, and minimizing the maximum drawdown. The constraints were pump capacity, meeting drinking-water standards for chloride, maintaining a specified minimum flowrate to a groundwater treatment plant, and maintaining minimum water levels in pumping wells. The decision variables either were quarterly pumpage by well or total pumpage by basin.

Five optimization scenarios were developed that allow the decision makers to evaluate a range of optimal solutions for a variety of water levels and chloride concentrations as well as potential future climatic conditions. Three scenarios (1, 2, and 5) were multi-objective optimization formulations that allowed for variations in management preferences and climatic conditions. The other two scenarios (3 and 4) were designed to examine the optimization results to answer specific questions. Scenario 1 described the best-case sustainable yield assuming a “full” basin (that is, high initial water levels) and typical climate conditions for 10 years. Scenario 2 also started with a “full” basin; however, this was followed by a 10-year drought. Scenario 3 determined if an “empty” basin (that is, low initial water levels) would recover to full conditions (1998 conditions) given climate assumptions and optimal pumping schedules from scenarios 1 and 2. Scenario 4 was designed to produce decision rules that can be used by water managers to help choose an optimal pumping schedule based on measured water-level or chloride data. Scenario 5 identified future pumping schedules based on short-term climate variations during a 2-year management horizon.

The results from scenarios 1 and 2 described the differences in maximum pumpage in the basin under typical and dry long-term climate projections, respectively. The scenario 1 results indicated the maximum 10-year pumpage of the basin was about 31,300 acre-ft under typical conditions and controlling simulated seawater intrusion and drawdowns. For scenario 2, less recharge over the 10-year dry climate produced a maximum pumpage estimate of 30,000 acre-ft to control seawater intrusion and drawdowns. The larger pumpage for scenario 1 resulted in more seawater intrusion, but less total drawdown, compared to that of scenario 2.

Results for scenarios 3 and 4 showed the basin’s response to management actions combined with climate projections. Both scenarios used the optimal pumping schedules and the 10-year climates from scenarios 1 and 2. The scenario 3 results showed that under minimal pumping, the basin did not fully recover to 1998 water levels within 10 years under either climate scenario. The relatively larger recharge from the typical climate resulted in less drawdown at coastal monitoring wells after the 10-year recovery period than that from the dry climate. The location of the seawater intrusion front was not appreciably different between the scenarios, however. Scenario 4 used the optimal results from scenarios 1 and 2 to produce decision-rule curves that illustrated the pumpage for each basin, given measured levels of chloride concentration or drawdown. This allowed the use of additional measurements at monitoring wells to assess future management decisions on the basis of the sensitivity of observations of drawdown and seawater intrusion to various pumping rates.

Scenario 5 allowed managers to investigate the effects of short-term climate variations on optimal pumping schedules. Three specific 2-year simulations were optimized: typical-to-dry (scenario 5A), dry-to-typical (scenario 5B), and dry-to-dry (scenario 5C). The most noteable result from scenario 5 was the overall reduction in optimal pumpage for most schedules in scenario 5C, when the climate is simulated as dry-to-dry. There are also many optimal pumping schedules that produced an overall increase in waterlevels over the two-year simulation period, regardless of climatic condition. Similar to scenario 2, the scenario 5C results represents conservative yield estimates under a minimal-precipitation climatic condition.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185059","collaboration":"Prepared in cooperation with the city of Santa Barbara","usgsCitation":"Nishikawa, T., ed., 2018, Santa Barbara and Foothill groundwater basins Geohydrology and optimal water resources management—Developed using density dependent solute transport and optimization models, U.S. Geological Survey, Scientific Investigations Report 2018-5059, 4 chap. (A–D), variously paged, https://doi.org/10.3133/sir20185059.","productDescription":"xiv, 384 p.","numberOfPages":"402","onlineOnly":"Y","ipdsId":"IP-063921","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":355581,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5059/sir20185059_.pdf","text":"Report","size":"81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5059"},{"id":355580,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5059/coverthb_.jpg"},{"id":356222,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74J0DF5","text":"Data release","description":"USGS Data Release","linkHelpText":"SEAWAT model used to evaluate water management issues in the Santa Barbara and Foothill groundwater basins, California"}],"country":"United States","state":"California","city":"Santa Barbara","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.94299316406249,\n 34.134541681937364\n ],\n [\n -119.10278320312499,\n 34.134541681937364\n ],\n [\n -119.10278320312499,\n 35.10193405724606\n ],\n [\n -120.94299316406249,\n 35.10193405724606\n ],\n [\n -120.94299316406249,\n 34.134541681937364\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"
Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2018-07-10","noUsgsAuthors":false,"publicationDate":"2018-07-10","publicationStatus":"PW","scienceBaseUri":"5b46e540e4b060350a15d059","contributors":{"editors":[{"text":"Nishikawa, Tracy 0000-0002-7348-3838","orcid":"https://orcid.org/0000-0002-7348-3838","contributorId":204242,"corporation":false,"usgs":true,"family":"Nishikawa","given":"Tracy","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733467,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Paulinski, Scott R. 0000-0001-6548-8164","orcid":"https://orcid.org/0000-0001-6548-8164","contributorId":204240,"corporation":false,"usgs":true,"family":"Paulinski","given":"Scott R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nishikawa, Tracy 0000-0002-7348-3838 tnish@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-3838","contributorId":1515,"corporation":false,"usgs":true,"family":"Nishikawa","given":"Tracy","email":"tnish@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cromwell, Geoffrey 0000-0001-8481-405X gcromwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8481-405X","contributorId":5920,"corporation":false,"usgs":true,"family":"Cromwell","given":"Geoffrey","email":"gcromwell@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733466,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyce, Scott E. 0000-0003-0626-9492 seboyce@usgs.gov","orcid":"https://orcid.org/0000-0003-0626-9492","contributorId":4766,"corporation":false,"usgs":true,"family":"Boyce","given":"Scott","email":"seboyce@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733464,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stanko, Zachary P. 0000-0001-7047-6846","orcid":"https://orcid.org/0000-0001-7047-6846","contributorId":204241,"corporation":false,"usgs":true,"family":"Stanko","given":"Zachary","email":"","middleInitial":"P.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733465,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196298,"text":"70196298 - 2018 - Application of electromagnetic induction to develop a precision irrigation framework to facilitate smallholder dry season farming in the Nasia-Kparigu area of northern Ghana","interactions":[],"lastModifiedDate":"2019-07-10T15:38:43","indexId":"70196298","displayToPublicDate":"2018-07-09T15:38:23","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Application of electromagnetic induction to develop a precision irrigation framework to facilitate smallholder dry season farming in the Nasia-Kparigu area of northern Ghana","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"SEG Technical Program Expanded Abstracts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEG International Exposition and 88th Annual Meeting","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/segam2018-2997867.1","usgsCitation":"Fontaine, J.M., Percy, A., Oware, E.K., Bosompemaa, P., Gbedzi, V., and Lane, J.W., 2018, Application of electromagnetic induction to develop a precision irrigation framework to facilitate smallholder dry season farming in the Nasia-Kparigu area of northern Ghana, in SEG Technical Program Expanded Abstracts, p. 2491-2495, https://doi.org/10.1190/segam2018-2997867.1.","productDescription":"5 p.","startPage":"2491","endPage":"2495","ipdsId":"IP-096664","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"links":[{"id":365468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ghana","city":"Kparigu, Nasia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -0.6588363647460938,\n 10.328092200952145\n ],\n [\n -0.8576202392578124,\n 10.208840403114372\n ],\n [\n -0.8153915405273438,\n 10.112865964329282\n ],\n [\n -0.591888427734375,\n 10.257492457069922\n ],\n [\n -0.6588363647460938,\n 10.328092200952145\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Fontaine, Jeremy M","contributorId":203748,"corporation":false,"usgs":false,"family":"Fontaine","given":"Jeremy","email":"","middleInitial":"M","affiliations":[{"id":36706,"text":"The State University of New York at Buffalo","active":true,"usgs":false}],"preferred":false,"id":732223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Percy, Alexander","contributorId":203749,"corporation":false,"usgs":false,"family":"Percy","given":"Alexander","email":"","affiliations":[{"id":36706,"text":"The State University of New York at Buffalo","active":true,"usgs":false}],"preferred":false,"id":732224,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oware, Erasmus K","contributorId":203750,"corporation":false,"usgs":false,"family":"Oware","given":"Erasmus","email":"","middleInitial":"K","affiliations":[{"id":36706,"text":"The State University of New York at Buffalo","active":true,"usgs":false}],"preferred":false,"id":732225,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bosompemaa, Patience","contributorId":203751,"corporation":false,"usgs":false,"family":"Bosompemaa","given":"Patience","email":"","affiliations":[{"id":36707,"text":"Ghana Geological Survey Authority","active":true,"usgs":false}],"preferred":false,"id":732226,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gbedzi, Vincent","contributorId":203752,"corporation":false,"usgs":false,"family":"Gbedzi","given":"Vincent","email":"","affiliations":[{"id":36708,"text":"University for Development Studies, Tamale-Ghana","active":true,"usgs":false}],"preferred":false,"id":732227,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, John W. Jr. 0000-0002-3558-243X jwlane@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":189168,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":false,"id":732222,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198033,"text":"70198033 - 2018 - Candidate products for operational earthquake forecasting illustrated using the HayWired planning scenario, including one very quick (and not‐so‐dirty) hazard‐map option","interactions":[],"lastModifiedDate":"2020-09-01T14:08:49.812533","indexId":"70198033","displayToPublicDate":"2018-07-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Candidate products for operational earthquake forecasting illustrated using the HayWired planning scenario, including one very quick (and not‐so‐dirty) hazard‐map option","docAbstract":"

In an effort to help address debates on the usefulness of operational earthquake forecasting (OEF), we illustrate a number of OEF products that could be automatically generated in near‐real time. To exemplify, we use an M\">M 7.1 mainshock on the Hayward fault, which is very similar to the U.S. Geological Survey (USGS) HayWired earthquake planning scenario. Given that there is always some background level of hazard or risk, we emphasize that probability gains (the ratio of short‐term to long‐term‐average estimates) might be of particular interest to users. We also illustrate how such gains are highly sensitive to forecast duration and latency, with the latter representing how long it takes to generate the forecast and/or to take action. The influence of fault‐based information, which has traditionally been ignored in OEF, is also evaluated using the newly developed the third Uniform California Earthquake Rupture Forecast epidemic‐type aftershock sequence (UCERF3‐ETAS) model. We find that the inclusion of faults only makes a difference for hazard and risk metrics that are dominated by large‐event likelihoods. We also show how the ShakeMap of a mainshock represents a decent estimate of the ground motions that have a 6% chance of being exceeded due to aftershocks in the week that follows. The ultimate value of these types of OEF products can only be determined in the context of specific uses, and because these vary widely, institutions responsible for providing OEF products will depend heavily on user feedback, especially when making resource‐allocation decisions.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220170241","usgsCitation":"Field, E., and Milner, K.R., 2018, Candidate products for operational earthquake forecasting illustrated using the HayWired planning scenario, including one very quick (and not‐so‐dirty) hazard‐map option: Seismological Research Letters, v. 89, no. 4, p. 1420-1434, https://doi.org/10.1785/0220170241.","productDescription":"15 p.","startPage":"1420","endPage":"1434","ipdsId":"IP-095951","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":355563,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-18","publicationStatus":"PW","scienceBaseUri":"5b46e541e4b060350a15d061","contributors":{"authors":[{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":1165,"corporation":false,"usgs":true,"family":"Field","given":"Edward H.","email":"field@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":739725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milner, Kevin R.","contributorId":63494,"corporation":false,"usgs":true,"family":"Milner","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":739726,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198039,"text":"70198039 - 2018 - A novel technique for precision geometric correction of jitter distortion for the Europa Imaging System and other rolling shutter cameras","interactions":[],"lastModifiedDate":"2018-07-16T10:47:32","indexId":"70198039","displayToPublicDate":"2018-07-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"seriesTitle":{"id":5650,"text":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","onlineIssn":"2194-9034","printIssn":"1682-1750","active":true,"publicationSubtype":{"id":19}},"title":"A novel technique for precision geometric correction of jitter distortion for the Europa Imaging System and other rolling shutter cameras","docAbstract":"

We use simulated images to demonstrate a novel technique for mitigating geometric distortions caused by platform motion (“jitter”) as two-dimensional image sensors are exposed and read out line by line (“rolling shutter”). The results indicate that the Europa Imaging System (EIS) on NASA’s Europa Clipper can likely meet its scientific goals requiring 0.1-pixel precision. We are therefore adapting the software used to demonstrate and test rolling shutter jitter correction to become part of the standard processing pipeline for EIS. The correction method will also apply to other rolling-shutter cameras, provided they have the operational flexibility to read out selected “check lines” at chosen times during the systematic readout of the frame area

","conferenceTitle":"2018 ISPRS TC III Mid-term Symposium “Developments, Technologies and Applications in Remote Sensing”","conferenceDate":"May 7-10, 2018","conferenceLocation":"Beijing, China","language":"English","publisher":"International Society for Photogrammetry & Remote Sensing","doi":"10.5194/isprs-archives-XLII-3-735-2018","usgsCitation":"Kirk, R.L., Shepherd, M., and Sides, S., 2018, A novel technique for precision geometric correction of jitter distortion for the Europa Imaging System and other rolling shutter cameras, 2018 ISPRS TC III Mid-term Symposium “Developments, Technologies and Applications in Remote Sensing”, v. XLII, no. 3, Beijing, China, May 7-10, 2018, p. 735-739, https://doi.org/10.5194/isprs-archives-XLII-3-735-2018.","productDescription":"4 p.","startPage":"735","endPage":"739","ipdsId":"IP-095328","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":468598,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/isprs-archives-xlii-3-735-2018","text":"Publisher Index Page"},{"id":355567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"XLII","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-30","publicationStatus":"PW","scienceBaseUri":"5b46e540e4b060350a15d05b","contributors":{"authors":[{"text":"Kirk, Randolph L. 0000-0003-0842-9226 rkirk@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-9226","contributorId":2765,"corporation":false,"usgs":true,"family":"Kirk","given":"Randolph","email":"rkirk@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":739748,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shepherd, Makayla 0000-0002-4101-9977","orcid":"https://orcid.org/0000-0002-4101-9977","contributorId":206191,"corporation":false,"usgs":true,"family":"Shepherd","given":"Makayla","email":"","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":739749,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sides, Stuart 0000-0002-7705-0677 ssides@usgs.gov","orcid":"https://orcid.org/0000-0002-7705-0677","contributorId":206192,"corporation":false,"usgs":true,"family":"Sides","given":"Stuart","email":"ssides@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":739750,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198034,"text":"70198034 - 2018 - A simple method for partitioning total solar radiation into diffuse/direct components in the United States","interactions":[],"lastModifiedDate":"2018-07-14T10:59:22","indexId":"70198034","displayToPublicDate":"2018-07-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5719,"text":"International Journal of Green Energy","onlineIssn":"1543-5083","printIssn":"1543-5075","active":true,"publicationSubtype":{"id":10}},"title":"A simple method for partitioning total solar radiation into diffuse/direct components in the United States","docAbstract":"Solar radiation is a major sustainable and clean energy resource, and use of solar radiation is expected to increase. The utilization efficiency of solar energy varies with the relative proportions of the direct and diffuse components that compose total solar radiation and with the slope and aspect of the irradiated surface. The purpose of this paper is to develop a simple method for estimating diffuse and direct solar radiation at sites with observation of only total solar radiation. An existing model for estimating diffuse radiation, i.e., a linear relationship between the diffuse fraction (the ratio of diffuse radiation to total solar radiation) and the clearness index (the ratio of total solar radiation to extraterrestrial radiation), is applied to 7 sites across the continental United States with observations of diffuse and total radiation. The linear model shows good monthly performance. The model parameters (slope and interception) show a strong seasonal pattern that exhibits small variation across the 7 sites; therefore, the average values of the two monthly parameters may be used for estimating diffuse radiation for other locations with observations of total radiation.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15435075.2018.1484357","usgsCitation":"Fan, J., Huang, Q., Sumner, D.M., and Wang, D., 2018, A simple method for partitioning total solar radiation into diffuse/direct components in the United States: International Journal of Green Energy, v. 15, no. 9, p. 497-506, https://doi.org/10.1080/15435075.2018.1484357.","productDescription":"10 p.","startPage":"497","endPage":"506","ipdsId":"IP-066829","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":501656,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://stars.library.ucf.edu/scopus2015/10188","text":"External Repository"},{"id":355565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"15","issue":"9","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-28","publicationStatus":"PW","scienceBaseUri":"5b46e540e4b060350a15d05f","contributors":{"authors":[{"text":"Fan, Jingjing","contributorId":206181,"corporation":false,"usgs":false,"family":"Fan","given":"Jingjing","email":"","affiliations":[{"id":37274,"text":"Xian University of Technology","active":true,"usgs":false}],"preferred":false,"id":739728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huang, Qiang","contributorId":206182,"corporation":false,"usgs":false,"family":"Huang","given":"Qiang","email":"","affiliations":[{"id":37274,"text":"Xian University of Technology","active":true,"usgs":false}],"preferred":false,"id":739729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sumner, David M. 0000-0002-2144-9304 dmsumner@usgs.gov","orcid":"https://orcid.org/0000-0002-2144-9304","contributorId":1362,"corporation":false,"usgs":true,"family":"Sumner","given":"David","email":"dmsumner@usgs.gov","middleInitial":"M.","affiliations":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true},{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Dingbao","contributorId":166993,"corporation":false,"usgs":false,"family":"Wang","given":"Dingbao","email":"","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":739730,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198028,"text":"70198028 - 2018 - On the reliability of N‐mixture models for count data","interactions":[],"lastModifiedDate":"2018-07-09T21:49:17","indexId":"70198028","displayToPublicDate":"2018-07-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1039,"text":"Biometrics","active":true,"publicationSubtype":{"id":10}},"title":"On the reliability of N‐mixture models for count data","docAbstract":"

N‐mixture models describe count data replicated in time and across sites in terms of abundance N and detectability p. They are popular because they allow inference about N while controlling for factors that influence p without the need for marking animals. Using a capture–recapture perspective, we show that the loss of information that results from not marking animals is critical, making reliable statistical modeling of N and p problematic using just count data. One cannot reliably fit a model in which the detection probabilities are distinct among repeat visits as this model is overspecified. This makes uncontrolled variation in p problematic. By counter example, we show that even if p is constant after adjusting for covariate effects (the “constant p” assumption) scientifically plausible alternative models in which N (or its expectation) is non‐identifiable or does not even exist as a parameter, lead to data that are practically indistinguishable from data generated under an N‐mixture model. This is particularly the case for sparse data as is commonly seen in applications. We conclude that under the constant p assumption reliable inference is only possible for relative abundance in the absence of questionable and/or untestable assumptions or with better quality data than seen in typical applications. Relative abundance models for counts can be readily fitted using Poisson regression in standard software such as R and are sufficiently flexible to allow controlling for p through the use covariates while simultaneously modeling variation in relative abundance. If users require estimates of absolute abundance, they should collect auxiliary data that help with estimation of p.

","language":"English","publisher":"Wiley","doi":"10.1111/biom.12734","usgsCitation":"Barker, R.J., Schofield, M., Link, W.A., and Sauer, J.R., 2018, On the reliability of N‐mixture models for count data: Biometrics, v. 74, no. 1, p. 369-377, https://doi.org/10.1111/biom.12734.","productDescription":"9 p.","startPage":"369","endPage":"377","ipdsId":"IP-075479","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":460879,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/biom.12734","text":"Publisher Index Page"},{"id":355564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-03","publicationStatus":"PW","scienceBaseUri":"5b46e541e4b060350a15d063","contributors":{"authors":[{"text":"Barker, Richard J.","contributorId":206174,"corporation":false,"usgs":false,"family":"Barker","given":"Richard","email":"","middleInitial":"J.","affiliations":[{"id":37272,"text":"University of Otago; Dunedin, New Zealand","active":true,"usgs":false}],"preferred":false,"id":739705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schofield, Matthew J.","contributorId":206175,"corporation":false,"usgs":false,"family":"Schofield","given":"Matthew J.","affiliations":[{"id":37272,"text":"University of Otago; Dunedin, New Zealand","active":true,"usgs":false}],"preferred":false,"id":739706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Link, William A. 0000-0002-9913-0256 wlink@usgs.gov","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":146920,"corporation":false,"usgs":true,"family":"Link","given":"William","email":"wlink@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":739704,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":739707,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198013,"text":"ofr20181106 - 2018 - Juvenile salmonid monitoring following removal of Condit Dam in the White Salmon River Watershed, Washington, 2017","interactions":[],"lastModifiedDate":"2018-07-10T10:08:29","indexId":"ofr20181106","displayToPublicDate":"2018-07-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1106","title":"Juvenile salmonid monitoring following removal of Condit Dam in the White Salmon River Watershed, Washington, 2017","docAbstract":"

Condit Dam, at river kilometer 5.3 on the White Salmon River, Washington, was breached in 2011, and removed completely in 2012, providing anadromous salmonids with the opportunity to recolonize habitat blocked for nearly 100 years. Prior to dam removal, a multi-agency workgroup concluded that the preferred salmonid restoration alternative was to allow natural recolonization. Monitoring would assess fish recolonization efficacy, followed by management evaluation 5 years after dam removal. Limited monitoring of salmon and steelhead recolonization has occurred since 2011. The U.S. Geological Survey began juvenile salmonid monitoring in 2016 and did a second year during 2017, with sampling efforts like those of 2016. River conditions differed between the 2 years, both during (that is, high flows in 2017) and prior to (that is, 2015 summer drought conditions and December 2015 White Salmon River flood event) sampling. We operated a rotary screw trap at river kilometer 2.3 (3 kilometers downstream of the former dam site) from early April through early June to assess species diversity, and production of smolt and other migrant life stages. We also used backpack electrofishing during summer to assess juvenile salmonid distribution and abundance. Both sampling methods provided the opportunity to collect genetic samples (analysis of samples was not covered under funding received from the Mid-Columbia Fisheries Enhancement Group for the 2017 monitoring efforts) and to tag fish with passive integrated transponder (PIT) tags, which will provide life-history data through future recaptures and detections.

The screw trap captured steelhead (anadromous rainbow trout, Oncorhynchus mykiss), fry, parr, and smolts; coho salmon (O. kisutch) fry, parr, and smolts; and Chinook salmon (O. tshwaytscha) fry, parr, and one smolt. Prolonged high water and some missed trapping periods during 2017 prevented us from generating smolt estimates. Despite difficult trapping conditions, the number of coho salmon fry and parr, and steelhead fry and parr captured in 2017 exceeded those captured during 2016. The number of age-0 Chinook salmon captured in the screw trap during 2017 was much higher (n = 222) than in 2016 (n = 4).

Electrofishing in tributaries provided information on distribution and abundance of juvenile coho salmon and O. mykiss. Juvenile coho salmon were again found in Mill and Buck Creeks and, for the first time, in Rattlesnake Creek (all three creeks are upstream of the former dam site). In both Rattlesnake and Buck Creeks, age-0 O. mykiss abundance decreased between 2016 and 2017; however, age-1 and older O. mykiss and age-0 coho salmon abundance increased between years at both sites. Data on O. mykiss abundance at sites in Buck and Rattlesnake Creeks is providing the opportunity to begin to understand trends and variability post-dam removal and to compare to pre-dam removal periods.

Mean age-0 O. mykiss abundance (fish per meter [fish/m]) at the Rattlesnake Creek site has been slightly lower during post-dam removal (mean = 3.0, n = 2, range = 2.4–3.6) than pre-dam removal (mean = 3.4, n = 5, range = 1.5–5.1). However, the presence of juvenile coho salmon in Rattlesnake Creek during 2017 (0.5 fish/m) brought total age-0 salmonid abundance in 2017 to 2.9 fish/m. Mean age-1 or older O. mykiss abundance (fish/m) at the Rattlesnake Creek site has been lower post-dam removal (mean = 0.2, n = 2, range = 0.1–0.3) than pre-dam removal (mean = 0.5, n = 2, range = 0.3–0.8). Mean age-0 O. mykiss abundance (fish/m) at the Buck Creek site has been higher post-dam removal (mean = 2.1, n = 2, range = 1.2–3.0) than pre-dam removal (mean = 1.8, n = 2, range = 1.6–1.9). The addition of age-0 coho salmon to Buck Creek brings mean age-0 salmonid abundance post-dam removal to 2.7 fish/m (range = 1.9–3.4). Mean age-1 or older O. mykiss abundance (fish/m) in Buck Creek has been slightly higher post-dam removal (mean = 0.8, n = 2, range = 0.6–1.1) than pre-dam removal (mean = 0.6, n = 2, both years 0.6).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181106","collaboration":"Prepared in cooperation with the Mid-Columbia Fisheries Enhancement Group","usgsCitation":"Jezorek, I.G., and Hardiman, J.M., 2018, Juvenile salmonid monitoring following removal of Condit Dam in the White Salmon River watershed, Washington, 2017: U.S. Geological Survey Open-File Report 2018-1106, 31 p. https://doi.org/10.3133/ofr20181106.","productDescription":"vi, 31 p.","numberOfPages":"41","onlineOnly":"Y","ipdsId":"IP-094796","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":355554,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1106/ofr20181106.pdf","text":"Report","size":"874 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1106"},{"id":355553,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1106/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Condit Dam, White Salmon River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.21466064453125,\n 45.64668833372338\n ],\n [\n -121.09680175781249,\n 45.64668833372338\n ],\n [\n -121.09680175781249,\n 46.47191632087041\n ],\n [\n -122.21466064453125,\n 46.47191632087041\n ],\n [\n -122.21466064453125,\n 45.64668833372338\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2018-07-09","noUsgsAuthors":false,"publicationDate":"2018-07-09","publicationStatus":"PW","scienceBaseUri":"5b46e541e4b060350a15d065","contributors":{"authors":[{"text":"Jezorek, Ian G. 0000-0002-3842-3485 ijezorek@usgs.gov","orcid":"https://orcid.org/0000-0002-3842-3485","contributorId":3572,"corporation":false,"usgs":true,"family":"Jezorek","given":"Ian","email":"ijezorek@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":739596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hardiman, Jill M. 0000-0002-3661-9695 jhardiman@usgs.gov","orcid":"https://orcid.org/0000-0002-3661-9695","contributorId":2672,"corporation":false,"usgs":true,"family":"Hardiman","given":"Jill","email":"jhardiman@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":739597,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198008,"text":"70198008 - 2018 - “Asian carp” is societally and scientifically problematic. Let's replace it","interactions":[],"lastModifiedDate":"2018-08-03T16:10:27","indexId":"70198008","displayToPublicDate":"2018-07-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"“Asian carp” is societally and scientifically problematic. Let's replace it","docAbstract":"

Bighead Carp Hypophthalmichthys nobilis, Black Carp Mylopharyngodon piceus, Grass Carp Ctenopharyngodon idella, and Silver Carp H. molitrix are considered invasive species in North America and Europe. In North America, they are typically referred to collectively as “Asian carp”, a reference to their native range. The category “Asian carp” fails to acknowledge the cultural value and the ecological differences of these fishes, causes confusion when translated into Chinese, and frequently causes problems of communication with the public and occasionally among professionals when some species are intentionally or inadvertently in‐ or excluded when referred to collectively. Herein we review the long history of aquaculture of these species in China, their human cultural significance, the origin of the category “Asian carp”, and the problems the term “Asian carp” might cause when used in cross‐cultural communication. We recommend discontinuing use of the term Asian carp and replacing it with individual species names. When a group term is required, there are several more favorable alternatives, including existing Chinese terms that have been used for centuries.

","language":"English","publisher":"Wiley","doi":"10.1002/fsh.10087","usgsCitation":"Kocovsky, P., Chapman, D., and Qian, S.S., 2018, “Asian carp” is societally and scientifically problematic. Let's replace it: Fisheries, v. 43, no. 7, p. 311-316, https://doi.org/10.1002/fsh.10087.","productDescription":"6 p.","startPage":"311","endPage":"316","ipdsId":"IP-086982","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":355528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"7","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-27","publicationStatus":"PW","scienceBaseUri":"5b46e542e4b060350a15d06d","contributors":{"authors":[{"text":"Kocovsky, Patrick 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":739577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":739578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Qian, Song S.","contributorId":198934,"corporation":false,"usgs":false,"family":"Qian","given":"Song","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":739579,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198005,"text":"70198005 - 2018 - Variation in inbreeding rates across the range of Northern Spotted Owls (Strix occidentalis caurina): Insights from over 30 years of monitoring data","interactions":[],"lastModifiedDate":"2018-07-06T13:28:28","indexId":"70198005","displayToPublicDate":"2018-07-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3544,"text":"The Auk","onlineIssn":"1938-4254","printIssn":"0004-8038","active":true,"publicationSubtype":{"id":10}},"title":"Variation in inbreeding rates across the range of Northern Spotted Owls (Strix occidentalis caurina): Insights from over 30 years of monitoring data","docAbstract":"

Inbreeding has been difficult to quantify in wild populations because of incomplete parentage information. We applied and extended a recently developed framework for addressing this problem to infer inbreeding rates in Northern Spotted Owls (Strix occidentalis caurina) across the Pacific Northwest, USA. Using pedigrees from 14,187 Northern Spotted Owls, we inferred inbreeding rates for 14 types of matings among relatives that produce pedigree inbreeding coefficients of F = 0.25 or F = 0.125. Inbreeding was most common in the Washington Cascades, where an estimated 15% of individuals are inbred. Inbreeding was lowest in western Oregon (3.5%) and northern California (2.7%), and intermediate for the Olympic Peninsula of Washington (6.1%). Estimates from the Olympic Peninsula were likely underestimates because of small sample sizes and the presence of few pedigrees capable of resolving inbreeding events. Most inbreeding resulted from matings between full siblings or half siblings, although a high rate of inbreeding from mother–son pairs was identified in the Olympic Peninsula. Geographic variation in inbreeding rates may reflect population declines and bottlenecks that have been detected in prior investigations. We show that there is strong selection against inbred birds. Only 3 of 44 inbred birds were later identified as parents (6.8%), whereas 2,823 of 10,380 birds that represented a comparable cross section of the data were later seen as reproducing parents (27.2%). Habitat loss and competition with Barred Owls (S. varia) remain primary threats to Northern Spotted Owls. However, given the negative consequences of inbreeding, Spotted Owl populations in Washington with suitable habitat and manageable numbers of Barred Owls may benefit from translocations of individuals from Oregon and California to introduce new genetic variation and reduce future inbreeding events.

","language":"English","publisher":"American Ornithological Society","doi":"10.1642/AUK-18-1.1","usgsCitation":"Miller, M.P., Haig, S.M., Forsman, E.D., Anthony, R., Diller, L., Dugger, K.M., Franklin, A.B., Fleming, T.L., Gremel, S., Lesmeister, D.B., Higley, M., Herter, D.R., and Sovern, S.G., 2018, Variation in inbreeding rates across the range of Northern Spotted Owls (Strix occidentalis caurina): Insights from over 30 years of monitoring data: The Auk, v. 135, no. 4, p. 821-833, https://doi.org/10.1642/AUK-18-1.1.","productDescription":"13 p.","startPage":"821","endPage":"833","ipdsId":"IP-096546","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":468599,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1642/auk-18-1.1","text":"Publisher Index Page"},{"id":355529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.13427734374999,\n 37.64903402157866\n ],\n [\n -119.5751953125,\n 37.64903402157866\n ],\n [\n -119.5751953125,\n 49.03786794532644\n ],\n [\n -125.13427734374999,\n 49.03786794532644\n ],\n [\n -125.13427734374999,\n 37.64903402157866\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"135","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e543e4b060350a15d06f","contributors":{"authors":[{"text":"Miller, Mark P. 0000-0003-1045-1772 mpmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1045-1772","contributorId":1967,"corporation":false,"usgs":true,"family":"Miller","given":"Mark","email":"mpmiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":739563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":739564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forsman, Eric D.","contributorId":96792,"corporation":false,"usgs":false,"family":"Forsman","given":"Eric","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":739565,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anthony, Robert G.","contributorId":61324,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert G.","affiliations":[],"preferred":false,"id":739566,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diller, Lowell","contributorId":206137,"corporation":false,"usgs":false,"family":"Diller","given":"Lowell","affiliations":[{"id":24606,"text":"Green Diamond Resource Company","active":true,"usgs":false}],"preferred":false,"id":739567,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dugger, Katie M. 0000-0002-4148-246X","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":36037,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"","middleInitial":"M.","affiliations":[{"id":517,"text":"Oregon Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":739568,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Franklin, Alan B.","contributorId":101999,"corporation":false,"usgs":false,"family":"Franklin","given":"Alan","email":"","middleInitial":"B.","affiliations":[{"id":12434,"text":"USDA, Wildlife Services, National Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":739569,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fleming, Tracy L.","contributorId":96199,"corporation":false,"usgs":true,"family":"Fleming","given":"Tracy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":739638,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gremel, Scott","contributorId":206139,"corporation":false,"usgs":false,"family":"Gremel","given":"Scott","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":739570,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lesmeister, Damon B. 0000-0003-1102-0122","orcid":"https://orcid.org/0000-0003-1102-0122","contributorId":205006,"corporation":false,"usgs":false,"family":"Lesmeister","given":"Damon","email":"","middleInitial":"B.","affiliations":[{"id":37019,"text":"USDA Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":739571,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Higley, Mark","contributorId":206140,"corporation":false,"usgs":false,"family":"Higley","given":"Mark","email":"","affiliations":[{"id":37256,"text":"Hoopa Valley Tribal Forestry","active":true,"usgs":false}],"preferred":false,"id":739572,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Herter, Dale R.","contributorId":206141,"corporation":false,"usgs":false,"family":"Herter","given":"Dale","email":"","middleInitial":"R.","affiliations":[{"id":37257,"text":"Raedeke Associates, Inc","active":true,"usgs":false}],"preferred":false,"id":739573,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sovern, Stan G","contributorId":206142,"corporation":false,"usgs":false,"family":"Sovern","given":"Stan","email":"","middleInitial":"G","affiliations":[{"id":27990,"text":"Deceased","active":true,"usgs":false}],"preferred":false,"id":739574,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70197579,"text":"sim3410 - 2018 - Map of recently active traces of the Rodgers Creek Fault, Sonoma County, California","interactions":[],"lastModifiedDate":"2018-07-16T13:25:56","indexId":"sim3410","displayToPublicDate":"2018-07-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3410","title":"Map of recently active traces of the Rodgers Creek Fault, Sonoma County, California","docAbstract":"

The accompanying map and digital data identify recently active strands of the Rodgers Creek Fault in Sonoma County, California, interpreted primarily from the geomorphic expression of recent faulting on aerial photography and hillshade imagery derived from airborne lidar data. A recently active fault strand is defined here as having evidence consistent with slip during the Holocene epoch (approximately the past 11,700 years). The purpose of the map is to update the fundamental fault dataset for characterizing surface-rupture hazard, siting slip-rate and paleoseismic studies, and studying the geometry and evolution of slip. To serve a range of users, the map is presented in several formats: as an image map, as a digital database for use within GIS, and as a KML file for visualizing the fault using virtual globe software.

Important outcomes of this mapping revision include the following: (1) a northward 17-km increase in the known length of Holocene-active faulting to include most of the Healdsburg Fault, a structural continuation of the Rodgers Creek Fault northwest of a bend in the fault at Santa Rosa; (2) first-time identification of fault strands across the Santa Rosa Creek floodplain in central Santa Rosa; (3) increases in the known width and complexity of faulting; and (4) identification of fault splays that project toward the Bennett Valley-Maacama Fault system to the east and toward a recently mapped active extension of the Hayward Fault to the south beneath San Pablo Bay.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3410","usgsCitation":"Hecker, S., and Randolph Loar, C.E., 2018, Map of recently active traces of the Rodgers Creek Fault, Sonoma County, California: U.S. Geological Survey Scientific Investigations Map 3410, 7 p., 1 sheet, https://doi.org/10.3133/sim3410.","productDescription":"Sheet: 39.85 x 40.25 inches; Pamphlet: iii, 7 p.; Metadata; Spatial data; Read Me","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-094680","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":355540,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3410/sim3410_mapsheet.pdf","text":"Map sheet","size":"17.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3410"},{"id":355541,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3410/sim3410_rcf_hfsec.shp.xml","text":"Northern section","size":"40 KB xml","description":"SIM 3410","linkHelpText":" - Healdsburg Fault section of the Rodgers Creek Fault "},{"id":355542,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3410/sim3410_rcf_rcfsec.shp.xml","text":"Southern section","size":"40 KB xml","description":"SIM 3410","linkHelpText":" - Rodgers Creek Fault section of the Rodgers Creek Fault"},{"id":355543,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3410/sim3410_data.zip","text":"Database","size":"1 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3410"},{"id":355544,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3410/sim3410_rodgerscreekfault.kmz","text":"KMZ file","size":"450 KB kmz","description":"SIM 3410"},{"id":355545,"rank":8,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3410/sim3410_readme.txt","text":"Read Me","size":"3 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3410"},{"id":355538,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3410/coverthb.jpg"},{"id":355539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3410/sim3410_pamphlet.pdf","text":"Pamphlet","size":"350 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3410"}],"country":"United States","state":"California","otherGeospatial":"Rodgers Creek Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.4167,\n 38.16667\n ],\n [\n -122.4833,\n 38.16667\n ],\n [\n -122.9833,\n 38.68333\n ],\n [\n -122.8667,\n 38.68333\n ],\n [\n -122.4167,\n 38.16667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Contact Information
Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025

","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2018-07-06","noUsgsAuthors":false,"publicationDate":"2018-07-06","publicationStatus":"PW","scienceBaseUri":"5b46e543e4b060350a15d071","contributors":{"authors":[{"text":"Hecker, Suzanne 0000-0002-5054-372X","orcid":"https://orcid.org/0000-0002-5054-372X","contributorId":205568,"corporation":false,"usgs":true,"family":"Hecker","given":"Suzanne","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":737818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Randolph Loar, Carolyn E.","contributorId":205569,"corporation":false,"usgs":false,"family":"Randolph Loar","given":"Carolyn","email":"","middleInitial":"E.","affiliations":[{"id":37115,"text":"Stantec Consulting Services Inc","active":true,"usgs":false}],"preferred":false,"id":737819,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198015,"text":"70198015 - 2018 - An updated method for estimating landslide‐event magnitude","interactions":[],"lastModifiedDate":"2018-07-13T14:28:34","indexId":"70198015","displayToPublicDate":"2018-07-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"An updated method for estimating landslide‐event magnitude","docAbstract":"

Summary statistics derived from the frequency–area distribution (FAD) of inventories of triggered landslides allows for direct comparison of landslides triggered by one event (e.g. earthquake, rainstorm) with another. Such comparisons are vital to understand links between the landslide‐event and the environmental characteristics of the area affected. This could lead to methods for rapid estimation of landslide‐event magnitude, which in turn could lead to estimates of the total triggered landslide area. Previous studies proposed that the FAD of landslides follows an inverse power‐law, which provides the basis to model the size distribution of landslides and to estimate landslide‐event magnitude (mLS), which quantifies the severity of the event. In this study, we use a much larger collection of earthquake‐induced landslide (EQIL) inventories (n=45) than previous studies to show that size distributions are much more variable than previously assumed. We present an updated model and propose a method for estimating mLS and its uncertainty that better fits the observations and is more reproducible, robust, and consistent than existing methods. We validate our model by computing mLS for all of the inventories in our dataset and comparing that with the total landslide areas of the inventories. We show that our method is able to estimate the total landslide area of the events in this larger inventory dataset more successfully than the existing methods. 

","language":"English","publisher":"Wiley","doi":"10.1002/esp.4359","usgsCitation":"Tanyas, H., Allstadt, K.E., and van Weston, C.J., 2018, An updated method for estimating landslide‐event magnitude: Earth Surface Processes and Landforms, v. 43, no. 9, p. 1836-1847, https://doi.org/10.1002/esp.4359.","productDescription":"12 p.","startPage":"1836","endPage":"1847","ipdsId":"IP-090008","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468601,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.4359","text":"Publisher Index Page"},{"id":437830,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79022QD","text":"USGS data release","linkHelpText":"landslides-mLS"},{"id":355523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","scienceBaseUri":"5b46e541e4b060350a15d067","contributors":{"authors":[{"text":"Tanyas, Hakan","contributorId":198731,"corporation":false,"usgs":false,"family":"Tanyas","given":"Hakan","affiliations":[],"preferred":false,"id":739604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allstadt, Kate E. 0000-0003-4977-5248 kallstadt@usgs.gov","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":167684,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"kallstadt@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":false,"id":739603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Weston, Cees J.","contributorId":206153,"corporation":false,"usgs":false,"family":"van Weston","given":"Cees","email":"","middleInitial":"J.","affiliations":[{"id":37261,"text":"University of Twente, Netherlands","active":true,"usgs":false}],"preferred":false,"id":739605,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198011,"text":"70198011 - 2018 - Using cluster analysis to compartmentalize a large managed wetland based on physical, biological, and climatic geospatial attributes","interactions":[],"lastModifiedDate":"2018-09-10T10:59:41","indexId":"70198011","displayToPublicDate":"2018-07-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Using cluster analysis to compartmentalize a large managed wetland based on physical, biological, and climatic geospatial attributes","docAbstract":"

Hierarchical and partitional cluster analyses were used to compartmentalize Water Conservation Area 1, a managed wetland within the Arthur R. Marshall Loxahatchee National Wildlife Refuge in southeast Florida, USA, based on physical, biological, and climatic geospatial attributes. Single, complete, average, and Ward’s linkages were tested during the hierarchical cluster analyses, with average linkage providing the best results. In general, the partitional method, partitioning around medoids, found clusters that were more evenly sized and more spatially aggregated than those resulting from the hierarchical analyses. However, hierarchical analysis appeared to be better suited to identify outlier regions that were significantly different from other areas. The clusters identified by geospatial attributes were similar to clusters developed for the interior marsh in a separate study using water quality attributes, suggesting that similar factors have influenced variations in both the set of physical, biological, and climatic attributes selected in this study and water quality parameters. However, geospatial data allowed further subdivision of several interior marsh clusters identified from the water quality data, potentially indicating zones with important differences in function. Identification of these zones can be useful to managers and modelers by informing the distribution of monitoring equipment and personnel as well as delineating regions that may respond similarly to future changes in management or climate.

","language":"English","publisher":"Springer","doi":"10.1007/s00267-018-1050-5","usgsCitation":"Hahus, I., Migliaccio, K., Douglas-Mankin, K.R., Klarenberg, G., and Muñoz-Carpena, R., 2018, Using cluster analysis to compartmentalize a large managed wetland based on physical, biological, and climatic geospatial attributes: Environmental Management, v. 62, no. 3, p. 571-583, https://doi.org/10.1007/s00267-018-1050-5.","productDescription":"13 p.","startPage":"571","endPage":"583","ipdsId":"IP-094746","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":355526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.446,\n 26.356\n ],\n [\n -80.222,\n 26.356\n ],\n [\n -80.222,\n 26.683\n ],\n [\n -80.446,\n 26.683\n ],\n [\n -80.446,\n 26.356\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"62","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-27","publicationStatus":"PW","scienceBaseUri":"5b46e542e4b060350a15d06b","contributors":{"authors":[{"text":"Hahus, Ian","contributorId":206143,"corporation":false,"usgs":false,"family":"Hahus","given":"Ian","email":"","affiliations":[{"id":37258,"text":"Department of Agricultural and Biological Engineering, University of Florida","active":true,"usgs":false}],"preferred":false,"id":739586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Migliaccio, Kati","contributorId":111526,"corporation":false,"usgs":true,"family":"Migliaccio","given":"Kati","affiliations":[],"preferred":false,"id":739587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Douglas-Mankin, Kyle R. 0000-0002-3155-3666","orcid":"https://orcid.org/0000-0002-3155-3666","contributorId":203927,"corporation":false,"usgs":true,"family":"Douglas-Mankin","given":"Kyle","email":"","middleInitial":"R.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739585,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klarenberg, Geraldine","contributorId":206145,"corporation":false,"usgs":false,"family":"Klarenberg","given":"Geraldine","email":"","affiliations":[{"id":37258,"text":"Department of Agricultural and Biological Engineering, University of Florida","active":true,"usgs":false}],"preferred":false,"id":739588,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Muñoz-Carpena, Rafael","contributorId":206146,"corporation":false,"usgs":false,"family":"Muñoz-Carpena","given":"Rafael","affiliations":[{"id":37258,"text":"Department of Agricultural and Biological Engineering, University of Florida","active":true,"usgs":false}],"preferred":false,"id":739589,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198012,"text":"70198012 - 2018 - Frictional properties and 3-D stress analysis of the southern Alpine Fault, New Zealand","interactions":[],"lastModifiedDate":"2018-07-06T13:09:35","indexId":"70198012","displayToPublicDate":"2018-07-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2468,"text":"Journal of Structural Geology","active":true,"publicationSubtype":{"id":10}},"title":"Frictional properties and 3-D stress analysis of the southern Alpine Fault, New Zealand","docAbstract":"

New Zealand's Alpine Fault (AF) ruptures quasi-periodically in large-magnitude earthquakes. Paleoseismological evidence suggests that about half of all recognized AF earthquakes terminated at the boundary between the Central and South Westland sections of the fault. There, fault geometry and the polarity of uplift change. The South Westland AF exhibits oblique-normal fault motion on a structure oriented 052°/82°SE that, for at least 35 km along strike, contains saponite-rich principal slip zone gouges. New hydrothermal friction experiments reveal that the saponite fault gouge is frictionally weak, exhibiting friction coefficients between μ = 0.12 and μ = 0.16 for a range of temperatures (T = 25–210 °C) and effective normal stresses (σn' = 31.2–93.6 MPa). The saponite gouge is rate-strengthening in all velocity steps performed at velocities between 0.01 and 3.0 μm/s, behavior conducive to aseismic creep. A three-dimensional stress analysis shows that the South Westland AF is favorably oriented with respect to the regional stress field for slip within the frictionally weak saponite fault gouge. Geometrically, the fault is severely misoriented for slip in any fault-forming materials with friction coefficients exceeding μ∼0.5. The combination of weak gouges prone to aseismic creep, strong asperities, and low resolved shear stress may impede earthquake rupture propagation along the South Westland Alpine Fault.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jsg.2018.06.003","usgsCitation":"Boulton, C., Barth, N.C., Moore, D.E., Lockner, D.A., Townend, J., and Faulkner, D.R., 2018, Frictional properties and 3-D stress analysis of the southern Alpine Fault, New Zealand: Journal of Structural Geology, v. 114, p. 43-54, https://doi.org/10.1016/j.jsg.2018.06.003.","productDescription":"12 p.","startPage":"43","endPage":"54","ipdsId":"IP-094797","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468600,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jsg.2018.06.003","text":"Publisher Index Page"},{"id":355524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 165.8056640625,\n -47.5172006978394\n ],\n [\n 176.77001953125,\n -47.5172006978394\n ],\n [\n 176.77001953125,\n -39.65645604812829\n ],\n [\n 165.8056640625,\n -39.65645604812829\n ],\n [\n 165.8056640625,\n -47.5172006978394\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"114","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e541e4b060350a15d069","contributors":{"authors":[{"text":"Boulton, Carolyn","contributorId":195077,"corporation":false,"usgs":false,"family":"Boulton","given":"Carolyn","email":"","affiliations":[],"preferred":false,"id":739591,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barth, Nicolas C.","contributorId":206132,"corporation":false,"usgs":false,"family":"Barth","given":"Nicolas","email":"","middleInitial":"C.","affiliations":[{"id":37254,"text":"University of California, Riverside, CA","active":true,"usgs":false}],"preferred":false,"id":739592,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Diane E. 0000-0002-8641-1075 dmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-8641-1075","contributorId":2704,"corporation":false,"usgs":true,"family":"Moore","given":"Diane","email":"dmoore@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":739590,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lockner, David A. 0000-0001-8630-6833 dlockner@usgs.gov","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":567,"corporation":false,"usgs":true,"family":"Lockner","given":"David","email":"dlockner@usgs.gov","middleInitial":"A.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":739593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Townend, John","contributorId":206133,"corporation":false,"usgs":false,"family":"Townend","given":"John","email":"","affiliations":[{"id":34132,"text":"Victoria University of Wellington, NZ","active":true,"usgs":false}],"preferred":false,"id":739594,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Faulkner, Daniel R.","contributorId":206134,"corporation":false,"usgs":false,"family":"Faulkner","given":"Daniel","email":"","middleInitial":"R.","affiliations":[{"id":37255,"text":"University of Liverpool, UK","active":true,"usgs":false}],"preferred":false,"id":739595,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197997,"text":"70197997 - 2018 - Transient coastal landscapes: Rising sea level threatens salt marshes","interactions":[],"lastModifiedDate":"2018-07-05T10:20:30","indexId":"70197997","displayToPublicDate":"2018-07-05T00:00:00","publicationYear":"2018","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":"Transient coastal landscapes: Rising sea level threatens salt marshes","docAbstract":"

Salt marshes are important coastal environments that provide key ecological services. As sea level rise has accelerated globally, concerns about the ability of salt marshes to survive submergence are increasing. Previous estimates of likely survival of salt marshes were based on ratios of sea level rise to marsh platform accretion. Here we took advantage of an unusual, long-term (1979–2015), spatially detailed comparison of changes in a representative New England salt marsh to provide an empirical estimate of habitat losses based on actual measurements. We show prominent changes in habitat mosaic within the marsh, consistent and coincident with increased submergence and coastal erosion. Model results suggest that at current rates of sea level rise, marsh platform accretion, habitat loss, and with the limitation of the widespread “coastal squeeze”, the entire ecosystem might disappear by the beginning of the next century, a fate that might be likely for many salt marshes elsewhere. Meta-analysis of available data suggests that 40 to 95% of the world's salt marshes will be submerged, depending on whether sea level rise remains at current or reaches anticipated rates for the end of this century.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.05.235","usgsCitation":"Valiela, I., Lloret, J., Bowyer, T., Miner, S., Remsen, D.P., Elmstrom, E., Cogswell, C., and Thieler, E.R., 2018, Transient coastal landscapes: Rising sea level threatens salt marshes: Science of the Total Environment, v. 640-641, p. 1148-1156, https://doi.org/10.1016/j.scitotenv.2018.05.235.","productDescription":"9 p.","startPage":"1148","endPage":"1156","ipdsId":"IP-081985","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hdl.handle.net/1912/10488","text":"Publisher Index Page"},{"id":355497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"640-641","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e544e4b060350a15d075","contributors":{"authors":[{"text":"Valiela, Ivan","contributorId":189387,"corporation":false,"usgs":false,"family":"Valiela","given":"Ivan","email":"","affiliations":[],"preferred":false,"id":739535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lloret, Javier","contributorId":206128,"corporation":false,"usgs":false,"family":"Lloret","given":"Javier","email":"","affiliations":[{"id":37252,"text":"Ecosystems Center, Marine Biological Laboratory, Woods Hole MA US 02543","active":true,"usgs":false}],"preferred":false,"id":739536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowyer, Tynan","contributorId":206129,"corporation":false,"usgs":false,"family":"Bowyer","given":"Tynan","email":"","affiliations":[{"id":37252,"text":"Ecosystems Center, Marine Biological Laboratory, Woods Hole MA US 02543","active":true,"usgs":false}],"preferred":false,"id":739537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miner, Simon","contributorId":196953,"corporation":false,"usgs":false,"family":"Miner","given":"Simon","affiliations":[],"preferred":false,"id":739538,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Remsen, David P.","contributorId":196868,"corporation":false,"usgs":false,"family":"Remsen","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":739539,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elmstrom, Elizabeth","contributorId":206130,"corporation":false,"usgs":false,"family":"Elmstrom","given":"Elizabeth","email":"","affiliations":[{"id":37252,"text":"Ecosystems Center, Marine Biological Laboratory, Woods Hole MA US 02543","active":true,"usgs":false}],"preferred":false,"id":739540,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cogswell, Charlotte","contributorId":206131,"corporation":false,"usgs":false,"family":"Cogswell","given":"Charlotte","email":"","affiliations":[{"id":37253,"text":"CR Environmental, Inc. 639 Boxberry Hill Road, East Falmouth, MA US 02536","active":true,"usgs":false}],"preferred":false,"id":739541,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thieler, E. Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739534,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70197568,"text":"ofr20181096 - 2018 - Procedures for using the Horiba Scientific Aqualog® fluorometer to measure absorbance and fluorescence from dissolved organic matter","interactions":[],"lastModifiedDate":"2018-07-11T10:42:39","indexId":"ofr20181096","displayToPublicDate":"2018-07-05T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1096","title":"Procedures for using the Horiba Scientific Aqualog® fluorometer to measure absorbance and fluorescence from dissolved organic matter","docAbstract":"

Advances in spectroscopic techniques have led to an increase in the use of optical measurements (absorbance and fluorescence) to assess dissolved organic matter composition and infer sources and processing. Although optical measurements are easy to make, they can be affected by many variables rendering them less comparable, including by inconsistencies in sample collection (for example, filter pore size, preservation), the application of corrections for interferences (for example, inner-filtering corrections), differences in holding times, and instrument drift (for example, lamp intensity). A documented, standardized procedure to address these variables ensures that the optical (absorbance and fluorescence) measurements collected by U.S. Geological Survey researchers are useful and widely comparable.

Rigorous and quantifiable quality assurance and quality control are essential for making these data comparable, particularly because there is no published guideline for the measurement of dissolved organic matter absorbance and fluorescence, and especially because there is no National Institute of Standards and Technology standard for dissolved organic matter. Validation and quality-control samples are analyzed on a monthly basis to determine laboratory and instrument precision and daily (that is, each day samples are run) to ensure repeatability. Data are not considered acceptable unless they meet laboratory criteria: All standards should be within 10 percent of the target value, laboratory replicates should be within 5 percent relative percent difference, and laboratory blanks (that is, laboratory reagent-grade water) should be less than one-tenth of the long-term method detection limit.

Finally, for data to be useful, they must be accessible to users in a format that can be easily analyzed and interpreted. The Organic Matter Research Laboratory staff has developed a processing routine that extracts a subset of the data, which is made available to the public through the USGS National Water Quality Information System (http://nwis.waterdata.usgs.gov/usa/nwis/qwdata), and organizes the full datasets (that is, complete absorbance spectra and fluorescence excitation-emission matrices) in different forms that allow for these data to be analyzed using multi-parameter and multi-way statistical approaches.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181096","usgsCitation":"Hansen, A.M., Fleck, J.A., Kraus, T.E.C., Downing, B.D., von Dessonneck, T., and Bergamaschi, B.A., 2018, Procedures for using the Horiba Scientific Aqualog® fluorometer to measure absorbance and fluorescence from dissolved organic matter: U.S. Geological Survey Open-File Report 2018–1096, 31 p., https://doi.org/10.3133/ofr20181096.","productDescription":"Report: vi, 31 p.; 3 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-082063","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":355505,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1096/coverthb.jpg"},{"id":355506,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1096/ofr2018.1096.pdf","text":"Report","size":"5.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1096"},{"id":355509,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1096/ofr20181096_appendix3.xlsx","text":"Appendix 3","size":"12.8 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2018-1096 Appendix 3"},{"id":355507,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1096/ofr20181096_appendix1.pdf","text":"Appendix 1","size":"450 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1096 Appendix 1"},{"id":355508,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1096/ofr20181096_appendix2.xlsx","text":"Appendix 2","size":"350 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2018-1096 Appendix 2"}],"contact":"
Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2018-07-05","noUsgsAuthors":false,"publicationDate":"2018-07-05","publicationStatus":"PW","scienceBaseUri":"5b46e544e4b060350a15d079","contributors":{"authors":[{"text":"Hansen, Angela M. 0000-0003-0938-7611","orcid":"https://orcid.org/0000-0003-0938-7611","contributorId":204702,"corporation":false,"usgs":true,"family":"Hansen","given":"Angela M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleck, Jacob 0000-0002-3217-3972 jafleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-3972","contributorId":168694,"corporation":false,"usgs":true,"family":"Fleck","given":"Jacob","email":"jafleck@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kraus, Tamara E. C. 0000-0002-5187-8644 tkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":147560,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara","email":"tkraus@usgs.gov","middleInitial":"E. C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737700,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Downing, Bryan D. 0000-0002-2007-5304 bdowning@usgs.gov","orcid":"https://orcid.org/0000-0002-2007-5304","contributorId":1449,"corporation":false,"usgs":true,"family":"Downing","given":"Bryan","email":"bdowning@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737697,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"von Dessonneck, Travis","contributorId":178352,"corporation":false,"usgs":false,"family":"von Dessonneck","given":"Travis","email":"","affiliations":[],"preferred":false,"id":737698,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":737699,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198084,"text":"70198084 - 2018 - Modeling the distributions of tegu lizards in native and potential invasive ranges","interactions":[],"lastModifiedDate":"2018-07-13T10:13:21","indexId":"70198084","displayToPublicDate":"2018-07-05T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the distributions of tegu lizards in native and potential invasive ranges","docAbstract":"

Invasive reptilian predators can have substantial impacts on native species and ecosystems. Tegu lizards are widely distributed in South America east of the Andes, and are popular in the international live animal trade. Two species are established in Florida (U.S.A.) - Salvator merianae (Argentine black and white tegu) and Tupinambis teguixin sensu lato (gold tegu) – and a third has been recorded there— S. rufescens (red tegu). We built species distribution models (SDMs) using 5 approaches (logistic regression, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy) based on data from the native ranges. We then projected these models to North America to develop hypotheses for potential tegu distributions. Our results suggest that much of the southern United States and northern México probably contains suitable habitat for one or more of these tegu species. Salvator rufescens had higher habitat suitability in semi-arid areas, whereas S. merianae and T. teguixin had higher habitat suitability in more mesic areas. We propose that Florida is not the only state where these taxa could become established, and that early detection and rapid response programs targeting tegu lizards in potentially suitable habitat elsewhere in North America could help prevent establishment and abate negative impacts on native ecosystems.

","language":"English","publisher":"Springer","doi":"10.1038/s41598-018-28468-w","usgsCitation":"Jarnevich, C.S., Hayes, M., Fitzgerald, L.A., Yackel, A., Falk, B., Collier, M., Bonewell, L., Klug, P., Naretto, S., and Reed, R., 2018, Modeling the distributions of tegu lizards in native and potential invasive ranges: Scientific Reports, v. 8, e10193; 12 p., https://doi.org/10.1038/s41598-018-28468-w.","productDescription":"e10193; 12 p.","ipdsId":"IP-090713","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468602,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-28468-w","text":"Publisher Index Page"},{"id":437831,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JZZE4W","text":"USGS data release","linkHelpText":"Data for modeling tegu lizard distributions in the Americas"},{"id":355667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-05","publicationStatus":"PW","scienceBaseUri":"5b6fc418e4b0f5d57878e9e1","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Mark","contributorId":206268,"corporation":false,"usgs":false,"family":"Hayes","given":"Mark","affiliations":[],"preferred":false,"id":739938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzgerald, Lee A.","contributorId":141035,"corporation":false,"usgs":false,"family":"Fitzgerald","given":"Lee","email":"","middleInitial":"A.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":739939,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yackel, Amy 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":152310,"corporation":false,"usgs":true,"family":"Yackel","given":"Amy","email":"yackela@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739940,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Falk, Bryan 0000-0002-9690-5626 bfalk@usgs.gov","orcid":"https://orcid.org/0000-0002-9690-5626","contributorId":150075,"corporation":false,"usgs":true,"family":"Falk","given":"Bryan","email":"bfalk@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739941,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Collier, Michelle 0000-0001-5715-448X","orcid":"https://orcid.org/0000-0001-5715-448X","contributorId":206269,"corporation":false,"usgs":true,"family":"Collier","given":"Michelle","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739942,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bonewell, Lea","contributorId":206270,"corporation":false,"usgs":true,"family":"Bonewell","given":"Lea","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739943,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Klug, Page 0000-0002-0836-3901","orcid":"https://orcid.org/0000-0002-0836-3901","contributorId":206271,"corporation":false,"usgs":false,"family":"Klug","given":"Page","affiliations":[{"id":37295,"text":"USDA APHIS","active":true,"usgs":false}],"preferred":false,"id":739944,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Naretto, Sergio","contributorId":206272,"corporation":false,"usgs":false,"family":"Naretto","given":"Sergio","email":"","affiliations":[{"id":37296,"text":"Instituto de Diversidad y Ecología Animal","active":true,"usgs":false}],"preferred":false,"id":739945,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":152301,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739946,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70199208,"text":"70199208 - 2018 - Defining the risk landscape in the context of pathogen pollution: Toxoplasma gondii in sea otters along the Pacific Rim","interactions":[],"lastModifiedDate":"2018-09-10T13:50:22","indexId":"70199208","displayToPublicDate":"2018-07-04T13:50:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3908,"text":"Royal Society Open Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Defining the risk landscape in the context of pathogen pollution: Toxoplasma gondii in sea otters along the Pacific Rim","title":"Defining the risk landscape in the context of pathogen pollution: Toxoplasma gondii in sea otters along the Pacific Rim","docAbstract":"

Pathogens entering the marine environment as pollutants exhibit a spatial signature driven by their transport mechanisms. The sea otter (Enhydra lutris), a marine animal which lives much of its life within sight of land, presents a unique opportunity to understand land–sea pathogen transmission. Using a dataset on Toxoplasma gondii prevalence across sea otter range from Alaska to California, we found that the dominant drivers of infection risk vary depending upon the spatial scale of analysis. At the population level, regions with high T. gondii prevalence had higher human population density and a greater proportion of human-dominated land uses, suggesting a strong role for population density of the felid definitive host of this parasite. This relationship persisted when a subset of data were analysed at the individual level: large-scale patterns in sea otter T. gondii infection prevalence were largely explained by individual exposure to areas of high human housing unit density, and other landscape features associated with anthropogenic land use, such as impervious surfaces and cropping land. These results contrast with the small-scale, within-region analysis, in which age, sex and prey choice accounted for most of the variation in infection risk, and terrestrial environmental features provided little variation to help in explaining observed patterns. These results underscore the importance of spatial scale in study design when quantifying both individual-level risk factors and landscape-scale variation in infection risk.

","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rsos.171178","usgsCitation":"Burgess, T.L., Tinker, M.T., Miller, M.A., Bodkin, J.L., Murray, M.J., Saarinen, J.A., Nichol, L.M., Larson, S.E., Conrad, P.A., and Johnson, C., 2018, Defining the risk landscape in the context of pathogen pollution: Toxoplasma gondii in sea otters along the Pacific Rim: Royal Society Open Science, v. 5, Article 171178; 11 p., https://doi.org/10.1098/rsos.171178.","productDescription":"Article 171178; 11 p.","ipdsId":"IP-091756","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468604,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsos.171178","text":"Publisher Index Page"},{"id":357204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.618408203125,\n 34.15272698011818\n ],\n [\n -119.24560546875001,\n 34.15272698011818\n ],\n [\n -119.24560546875001,\n 37.69251435532741\n ],\n [\n -122.618408203125,\n 37.69251435532741\n ],\n [\n -122.618408203125,\n 34.15272698011818\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-04","publicationStatus":"PW","scienceBaseUri":"5b98a2a2e4b0702d0e842f94","contributors":{"authors":[{"text":"Burgess, Tristan L.","contributorId":207772,"corporation":false,"usgs":false,"family":"Burgess","given":"Tristan","email":"","middleInitial":"L.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":744678,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":744677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Melissa A.","contributorId":57701,"corporation":false,"usgs":false,"family":"Miller","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":39007,"text":"CA Dept of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":744679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bodkin, James L. 0000-0003-1641-4438 jbodkin@usgs.gov","orcid":"https://orcid.org/0000-0003-1641-4438","contributorId":748,"corporation":false,"usgs":true,"family":"Bodkin","given":"James","email":"jbodkin@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":744680,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murray, Michael J.","contributorId":206852,"corporation":false,"usgs":false,"family":"Murray","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":37418,"text":"Monterey Bay Aquarium, Monterey, CA","active":true,"usgs":false}],"preferred":false,"id":744681,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Saarinen, Justin A.","contributorId":207774,"corporation":false,"usgs":false,"family":"Saarinen","given":"Justin","email":"","middleInitial":"A.","affiliations":[{"id":35150,"text":"New College of Florida","active":true,"usgs":false}],"preferred":false,"id":744682,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nichol, Linda M.","contributorId":207775,"corporation":false,"usgs":false,"family":"Nichol","given":"Linda","email":"","middleInitial":"M.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":744683,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Larson, Shawn E.","contributorId":149287,"corporation":false,"usgs":false,"family":"Larson","given":"Shawn","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":744684,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Conrad, Patricia A.","contributorId":181937,"corporation":false,"usgs":false,"family":"Conrad","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":744685,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Johnson, Christine K.","contributorId":23771,"corporation":false,"usgs":false,"family":"Johnson","given":"Christine K.","affiliations":[],"preferred":false,"id":744686,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70213052,"text":"70213052 - 2018 - Discussion of “Shallow water hydro-sediment-morphodynamic equations for fluvial processes” by Zhixian Cao, Chunchen Xia, Gareth Pender, and Qingquan Liu","interactions":[],"lastModifiedDate":"2020-09-08T16:25:27.151806","indexId":"70213052","displayToPublicDate":"2018-07-04T11:21:29","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2338,"text":"Journal of Hydraulic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Discussion of “Shallow water hydro-sediment-morphodynamic equations for fluvial processes” by Zhixian Cao, Chunchen Xia, Gareth Pender, and Qingquan Liu","docAbstract":"

The original paper concerns the formulation and use of depth-integrated equations of motion to model the dynamics of shallow flows that entrain or deposit bed material. A recurring theme of the original paper is the authors’ criticism of related theoretical results published by Iverson and Ouyang (2015). This discussion explains why that criticism is misguided.

","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)HY.1943-7900.0001519","usgsCitation":"Iverson, R.M., 2018, Discussion of “Shallow water hydro-sediment-morphodynamic equations for fluvial processes” by Zhixian Cao, Chunchen Xia, Gareth Pender, and Qingquan Liu: Journal of Hydraulic Engineering, 07018009, 3 p., https://doi.org/10.1061/(ASCE)HY.1943-7900.0001519.","productDescription":"07018009, 3 p.","ipdsId":"IP-084425","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":378199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Iverson, Richard M. 0000-0002-7369-3819 riverson@usgs.gov","orcid":"https://orcid.org/0000-0002-7369-3819","contributorId":536,"corporation":false,"usgs":true,"family":"Iverson","given":"Richard","email":"riverson@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":798081,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70198411,"text":"70198411 - 2018 - Survival and cause-specific mortality of translocated female mule deer in southern New Mexico, USA","interactions":[],"lastModifiedDate":"2018-08-03T13:42:31","indexId":"70198411","displayToPublicDate":"2018-07-03T13:42:20","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"Survival and cause-specific mortality of translocated female mule deer in southern New Mexico, USA","docAbstract":"

Context: Many mule deer (Odocoileus hemionus) populations in New Mexico have failed to recover from previous population declines, while some populations near urban areas have increased, resulting in more frequent human–wildlife conflicts. Translocations were used in an effort to simultaneously reduce an urban mule deer population and augment two low-density populations in south-western New Mexico, USA.

Aims: Because of insufficient monitoring, the efficacy of many ungulate translocations is unknown. Our goal was to monitor cause-specific mortality and 1 year post-release survival of mule deer translocated during 2013 and 2014. We compared survival rates of mule deer released with a hard- versus soft-release during the 2014 translocation.

Methods: . We translocated 218 mule deer in 2013 and 2014 into the Peloncillo Mountains (PM) and San Francisco River Valley (SFRV); 106 adult female mule deer were fitted with telemetry collars to determine cause-specific mortality and estimate survival 1 year post-release. All deer were hard-released in 2013. In 2014, translocated mule deer were either held in a soft-release pen (0.81 ha) for approximately 3 weeks or hard-released into their new environment. We used a Kaplan–Meier approach to estimate survival of translocated mule deer at each release area and to compare survival of mule deer translocated using each release method (i.e. hard- versus soft-release).

Key results: In 2013–14, survival of hard-released deer in the PM was 0.627 (s.e. = 0.09), compared with 0.327 (s.e. = 0.10) in the SFRV. In 2014–15, survival of hard–released deer in the PM was 0.727 (s.e. = 0.13) and survival of soft-released deer was 0.786 (s.e. = 0.11). In the SFRV, survival of hard- and soft-released deer was 0.656 (s.e. = 0.14) and 0.50 (s.e. = 0.16), respectively. Causes of mortality were predation (51%), potential disease (9%; blue tongue or epizootic haemorrhagic disease), accident (5%), poaching (5%) and unknown (20%).

Conclusions: Translocations can be an effective management tool to augment populations of mule deer while reducing overabundant urban populations. Soft-released mule deer did not have higher survival than hard-released mule deer, although the length and conditions of the acclimation period were limited in our study.

Implications: Overabundant mule deer populations in urban areas may serve as sources of animals to bolster declining populations. Soft-release pens of smaller size and short period of acclimation did not influence survival.

","language":"English","publisher":"CSIRO","doi":"10.1071/WR17173","usgsCitation":"Cain, J.W., Ashling, J.B., and Liley, S., 2018, Survival and cause-specific mortality of translocated female mule deer in southern New Mexico, USA: Wildlife Research, v. 45, no. 4, p. 325-335, https://doi.org/10.1071/WR17173.","productDescription":"11 p.","startPage":"325","endPage":"335","ipdsId":"IP-077616","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":356143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","volume":"45","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc418e4b0f5d57878e9e3","contributors":{"authors":[{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":741364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashling, Jana B.","contributorId":206715,"corporation":false,"usgs":false,"family":"Ashling","given":"Jana","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":741542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liley, Stewart","contributorId":171908,"corporation":false,"usgs":false,"family":"Liley","given":"Stewart","affiliations":[],"preferred":false,"id":741543,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210190,"text":"70210190 - 2018 - Distinguishing Southern Africa precipitation response by strength of El Niño events and implications for decision-making","interactions":[],"lastModifiedDate":"2020-05-20T12:53:17.304468","indexId":"70210190","displayToPublicDate":"2018-07-03T07:46:49","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Distinguishing Southern Africa precipitation response by strength of El Niño events and implications for decision-making","docAbstract":"

December–February precipitation in southern Africa during recent El Niño events is studied by distinguishing circulation and precipitation responses during strong and moderate-to-weak events. We find that while both strong and moderate-to-weak El Niño events tend to dry southern Africa, the pattern and magnitude of precipitation anomalies in the region are different, with strong El Niño events resulting in rainfall deficits often less than −0.88 standardized units and deficits of only about half that for the moderate-to-weak case. Additionally, the likelihood of southern Africa receiving less than climatologic precipitation is approximately 80% for strong El Niño events compared to just over 60% for moderate-to-weak El Niño. Strong El Niño events are found to substantially disrupt onshore moisture transports from the Indian Ocean and increase geopotential heights within the Angola Low. Since El Niño is the most predictable component of the climate system that influences southern Africa precipitation, the information provided by this assessment of the likelihood of dry conditions can serve to benefit early warning systems.

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These sensor innovations provide real-time ground shaking observations that could improve emergency response following damaging earthquakes and may advance our understanding of the physics of earthquake ruptures.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41467-018-04790-9","usgsCitation":"Cochran, E.S., 2018, To catch a quake: Nature Communications, v. 9, Article number: 2508; 4 p., https://doi.org/10.1038/s41467-018-04790-9.","productDescription":"Article number: 2508; 4 p.","ipdsId":"IP-097663","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468606,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-018-04790-9","text":"Publisher Index Page"},{"id":356677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-03","publicationStatus":"PW","scienceBaseUri":"5b98a2a2e4b0702d0e842f96","contributors":{"authors":[{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":743105,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70197980,"text":"fs20183037 - 2018 - Coastal National Elevation Database","interactions":[],"lastModifiedDate":"2018-07-03T12:42:37","indexId":"fs20183037","displayToPublicDate":"2018-07-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3037","title":"Coastal National Elevation Database","docAbstract":"

The Coastal National Elevation Database (CoNED) Applications Project develops enhanced topographic (land elevation) and bathymetric (water depth) datasets that serve as valuable resources for coastal hazards research (Danielson and others, 2016; Thatcher and others, 2016). These datasets are used widely for mapping inundation zones from riverine flood events, hurricanes, and sea-level rise and for other Earth science applications, such as sediment transport, erosion, and storm impact models.

CoNED is a U.S. Geological Survey (USGS) Coastal-Marine Hazards and Resources Program (formerly Coastal and Marine Geology Program) activity centered at the USGS Earth Resources Observation and Science Center and distributed at other USGS Science Centers. As part of the vision for a 3D Nation, the CoNED Project is working collaboratively with the USGS National Geospatial Program, the National Oceanic and Atmospheric Administration, and the U.S. Army Corps of Engineers through the Interagency Working Group on Ocean and Coastal Mapping to build integrated elevation models in the coastal zone by assimilating the land surface topography with littoral zone and continental shelf bathymetry. Several nongovernmental organizations and Federal agencies, including the Department of the Interior Pacific Islands Climate Adaptation Science Center, the National Park Service, the Nature Conservancy, the Louisiana Coastal Protection and Restoration Authority, and numerous academic institutions, partner to make CoNED a success.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183037","usgsCitation":"Danielson, J.J., Poppenga, S.K., Tyler, D.J., Palaseanu-Lovejoy, M., and Gesch, D.B., 2018, Coastal National Elevation Database: U.S. Geological Survey Fact Sheet 2018–3037, 2 p., https://doi.org/10.3133/2018.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-093676","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":355477,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3037/coverthb.jpg"},{"id":355478,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3037/fs20183037.pdf","text":"Report","size":"617 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018–3037"}],"contact":"

Director, Earth Resources Observation and Science Center  
U.S. Geological Survey
47914 252nd Street 
Sioux Falls, SD 57198

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2018-07-03","noUsgsAuthors":false,"publicationDate":"2018-07-03","publicationStatus":"PW","scienceBaseUri":"5b46e544e4b060350a15d07b","contributors":{"authors":[{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":739450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poppenga, Sandra K. 0000-0002-2846-6836 spoppenga@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-6836","contributorId":3327,"corporation":false,"usgs":true,"family":"Poppenga","given":"Sandra","email":"spoppenga@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":739451,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tyler, Dean J. 0000-0002-1542-7539 dtyler@usgs.gov","orcid":"https://orcid.org/0000-0002-1542-7539","contributorId":177897,"corporation":false,"usgs":true,"family":"Tyler","given":"Dean","email":"dtyler@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":739452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":739453,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739454,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}