{"pageNumber":"264","pageRowStart":"6575","pageSize":"25","recordCount":41062,"records":[{"id":70225669,"text":"70225669 - 2020 - USGS Telemetry Project","interactions":[],"lastModifiedDate":"2024-03-22T14:39:41.708826","indexId":"70225669","displayToPublicDate":"2020-12-01T09:34:11","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":9543,"text":"Interim Summary Report","active":true,"publicationSubtype":{"id":3}},"title":"USGS Telemetry Project","docAbstract":"Telemetry of acoustically tagged bigheaded carp (i.e., bighead carp Hypophthalmichthys nobilis and silver carp H. molitrix) and surrogate fish species has become an invaluable tool in management for these species in the upper Illinois Waterway Systems (i.e., upper Illinois River, lower Des Plaines River, and Chicago Area Waterway System). For example, movement probabilities between adjacent navigation pools need to be estimated to parameterize the Spatially Explicit Asian Carp Population Model (SEAcarP). SEAcarP is a population model used in scenario planning by the Monitoring and Response Workgroup (MRWG) to evaluate alternative management actions. These movement probabilities are estimated from the telemetry data obtained from a longitudinal network of strategically placed receivers that detect bigheaded carp that have been implanted with acoustic transmitters. In addition, fish removal by contracted fishers has become the primary method of controlling bigheaded carp in the upper Illinois and lower Des Plaines Rivers. Variable patterns in bigheaded carp distribution, habitat, and movement, influenced by seasonal and environmental conditions, make targeting bigheaded carp for removal and containment challenging and costly. Understanding these movement patterns for bigheaded carp through modeling and real-time telemetry applications informs removal efforts and facilitates monitoring and contingency actions based on fish movements.
To develop a better understanding of fish movement dynamics to meet management objectives, an existing network of real-time and data-logging acoustic receivers in the upper Illinois Waterway Systems is collaboratively managed by a multi-agency team (see Participating Agencies section above). A Telemetry Workgroup has been established by the MRWG to ensure that the multi-agency telemetry efforts are coordinated to efficiently and effectively meet the MRWG goals. This workgroup plans and executes the placement of receivers, tagging of bigheaded carp with acoustic tags, and management of the telemetry data. Three primary objectives to meet MRWG goals identified by the Telemetry Workgroup included (1) development of a common standardized telemetry database with visualization and analysis tools, (2) transitioning from Program MARK (http://www.phidot.org/software/mark/) to a custom Bayesian multi-state model for estimating movement probabilities needed for SEAcarP and (3) deploying, maintaining, and serving data from real-time acoustic receivers to inform contingency planning and fish removal.
A telemetry database and visualization tools (FishTracks) will facilitate standardization, archiving, sharing, quality assurance, visualization and analysis of the telemetry data needed for management. Modifications and additions to FishTracks will facilitate more problem-free use of the database and associated applications, as well as useful extraction of information to meet management goals. The transition to a custom Bayesian multi-state model to estimate movement probabilities will support more efficient, effective, and robust population modeling with SEAcarP by overcoming short comings of Program MARK for this purpose. These shortcomings include lack of customizability and extensibility, problems of singularities and poor-convergence, software crashes, parameter exclusion from models, an inability to consistently generate estimates of movement probability, and a lack of uncertainty estimates for movement probabilities. A real-time receiver network that is maintained and tested annually will ensure reliability and accuracy of the real-time alerts to bigheaded carp movements that can be used by management to plan contingency actions.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Interim summary report 2020","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Asian Carp Regional Coordinating Committee","usgsCitation":"Knights, B.C., Brey, M.K., Stanton, J.C., Harrison, T.J., Appel, D., Hlavacek, E., and Duncker, J.J., 2020, USGS Telemetry Project: Interim Summary Report, 6 p.","productDescription":"6 p.","startPage":"41","endPage":"46","ipdsId":"IP-128212","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":391250,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://invasivecarp.us/PlansReports.html"},{"id":426889,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"upper Illinois Waterway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.34655836479192,\n 42.36183831544582\n ],\n [\n -89.74494117447833,\n 42.36183831544582\n ],\n [\n -89.74494117447833,\n 40.51767088873834\n ],\n [\n -87.34655836479192,\n 40.51767088873834\n ],\n [\n -87.34655836479192,\n 42.36183831544582\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":826139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":826140,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":826141,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harrison, Travis J. 0000-0002-9195-738X","orcid":"https://orcid.org/0000-0002-9195-738X","contributorId":213966,"corporation":false,"usgs":true,"family":"Harrison","given":"Travis","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":826142,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Appel, Douglas 0000-0001-8775-1058","orcid":"https://orcid.org/0000-0001-8775-1058","contributorId":268159,"corporation":false,"usgs":true,"family":"Appel","given":"Douglas","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":826143,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hlavacek, Enrika 0000-0002-9872-2305 ehlavacek@usgs.gov","orcid":"https://orcid.org/0000-0002-9872-2305","contributorId":149114,"corporation":false,"usgs":true,"family":"Hlavacek","given":"Enrika","email":"ehlavacek@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":826144,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826145,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70228975,"text":"70228975 - 2020 - A multispecies approach to manage effects of land cover and weather on upland game birds","interactions":[],"lastModifiedDate":"2022-02-25T15:21:38.85868","indexId":"70228975","displayToPublicDate":"2020-12-01T09:11:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A multispecies approach to manage effects of land cover and weather on upland game birds","docAbstract":"Loss and degradation of grasslands in the Great Plains region have resulted in major declines in abundance of grassland bird species. To ensure future viability of grassland bird populations, it is crucial to evaluate specific effects of environmental factors among species to determine drivers of population decline and develop effective conservation strategies. We used threshold models to quantify the effects of land cover and weather changes in \"lesser prairie-chicken\" and \"greater prairie-chicken\" (Tympanuchus pallidicinctus and T. cupido, respectively), northern bobwhites (Colinus virginianus), and ring-necked pheasants (Phasianus colchicus). We demonstrated a novel approach for estimating landscape conditions needed to optimize abundance across multiple species at a variety of spatial scales. Abundance of all four species was highest following wet summers and dry winters. Prairie chicken and ring-necked pheasant abundance was highest following cool winters, while northern bobwhite abundance was highest following warm winters. Greater prairie chicken and northern bobwhite abundance was also highest following cooler summers. Optimal abundance of each species occurred in landscapes that represented a grassland and cropland mosaic, though prairie chicken abundance was optimized in landscapes with more grassland and less edge habitat than northern bobwhites and ring-necked pheasants. Because these effects differed among species, managing for an optimal landscape for multiple species may not be the optimal scenario for any one species.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7034","usgsCitation":"Schindler, A., Haukos, D.A., Hagen, C., and Ross, B., 2020, A multispecies approach to manage effects of land cover and weather on upland game birds: Ecology and Evolution, v. 10, no. 24, p. 14330-14345, https://doi.org/10.1002/ece3.7034.","productDescription":"16 p.","startPage":"14330","endPage":"14345","ipdsId":"IP-119651","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":352,"text":"Kansas Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":454717,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.7034","text":"Publisher Index Page"},{"id":396483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n 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,{"id":70216843,"text":"70216843 - 2020 - Development and application of an empirical dune growth model for evaluating barrier island recovery from storms","interactions":[],"lastModifiedDate":"2020-12-09T14:30:57.032964","indexId":"70216843","displayToPublicDate":"2020-12-01T08:21:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Development and application of an empirical dune growth model for evaluating barrier island recovery from storms","docAbstract":"Coastal zone managers require models that predict barrier island change on decadal time scales to estimate coastal vulnerability, and plan habitat restoration and coastal protection projects. To meet these needs, methods must be available for predicting dune recovery as well as dune erosion. In the present study, an empirical dune growth model (EDGR) was developed to predict the evolution of the primary foredune of a barrier island. Within EDGR, an island is represented as a sum of Gaussian shape functions representing dunes, berms, and the underlying island form. The model evolves the foredune based on estimated terminal dune height and location inputs. EDGR was assessed against observed dune evolution along the western end of Dauphin Island, Alabama over the 10 years following Hurricane Katrina (2005). The root mean square error with EDGR (ranging from 0.18 to 0.74 m over the model domain) was reduced compared to an alternate no-change model (0.69–0.96 m). Hindcasting with EDGR also supports the study of dune evolution processes. At Dauphin Island, results suggest that a low-lying portion of the site was dominated by overwash for ~5 years after Katrina, before approaching their terminal height and becoming growth-limited after 2010. EDGR’s computational efficiency allows dune evolution to be rapidly predicted and enables ensemble predictions to constrain the uncertainty that may result if terminal dune characteristics are unknown. In addition, EDGR can be coupled with an external model for estimating dune erosion and/or the long-term evolution of other subaerial features to allow decadal-scale prediction of barrier island evolution.
","language":"English","publisher":"MDPI","doi":"10.3390/jmse8120977","usgsCitation":"Dalyander, P., Mickey, R.C., Passeri, D., and Plant, N.G., 2020, Development and application of an empirical dune growth model for evaluating barrier island recovery from storms: Journal of Marine Science and Engineering, v. 8, no. 12, 9, 21 p., https://doi.org/10.3390/jmse8120977.","productDescription":"9, 21 p.","ipdsId":"IP-104554","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454720,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse8120977","text":"Publisher Index Page"},{"id":381165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.34930419921875,\n 30.216948502671475\n ],\n [\n -88.06640625,\n 30.216948502671475\n ],\n [\n -88.06640625,\n 30.271521387805628\n ],\n [\n -88.34930419921875,\n 30.271521387805628\n ],\n [\n -88.34930419921875,\n 30.216948502671475\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Dalyander, Patricia (Soupy) 0000-0001-9583-0872 sdalyander@usgs.gov","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":191931,"corporation":false,"usgs":true,"family":"Dalyander","given":"Patricia (Soupy)","email":"sdalyander@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":806595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mickey, Rangley C. 0000-0001-5989-1432 rmickey@usgs.gov","orcid":"https://orcid.org/0000-0001-5989-1432","contributorId":141016,"corporation":false,"usgs":true,"family":"Mickey","given":"Rangley","email":"rmickey@usgs.gov","middleInitial":"C.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":806596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Passeri, Davina L. 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":806597,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":806598,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70213224,"text":"70213224 - 2020 - Quantitative textural measures of the aeromagnetic field: Two examples at regional scale","interactions":[],"lastModifiedDate":"2021-01-26T12:43:53.716355","indexId":"70213224","displayToPublicDate":"2020-11-30T11:34:52","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"6","title":"Quantitative textural measures of the aeromagnetic field: Two examples at regional scale","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"An Introduction to Approaches and Modern Applications with Ensemble Learning","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Nova Science Publishers, Inc.","usgsCitation":"Gettings, M.E., 2020, Quantitative textural measures of the aeromagnetic field: Two examples at regional scale, chap. 6 of An Introduction to Approaches and Modern Applications with Ensemble Learning.","ipdsId":"IP-093118","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":382561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gettings, Mark E. 0000-0002-2910-2321 mgetting@usgs.gov","orcid":"https://orcid.org/0000-0002-2910-2321","contributorId":602,"corporation":false,"usgs":true,"family":"Gettings","given":"Mark","email":"mgetting@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":798643,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70219169,"text":"70219169 - 2020 - Decreases in aluminum toxicity and mortality of caged brook trout in Adirondack Mountain Streams","interactions":[],"lastModifiedDate":"2021-03-29T14:38:42.342371","indexId":"70219169","displayToPublicDate":"2020-11-30T09:33:20","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5792,"text":"Summary Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"20-35","title":"Decreases in aluminum toxicity and mortality of caged brook trout in Adirondack Mountain Streams","docAbstract":"Mortality of juvenile brook trout and water chemistry were characterized in six western Adirondack streams in northern New York State during spring 2015, 2016, and 2017 and compared with results from comparable tests done between 1980 and 2003 in many of the same streams to assess temporal changes in inorganic monomeric aluminum (Ali) concentrations, Ali-toxicity, and the role of Ali-exposure duration on mortality. Ali concentrations of 2 and 4 micromoles per liter (µmol L-1) corresponded to chronic- and acute-mortality thresholds for brook trout, but prolonged exposure to ≥ 1 µmol Ali L-1 also produced low-to-moderate mortality levels. The variability, mean, and highest Ali concentrations in Buck Creek (BUC) year-round, and in several other streams during spring, decreased significantly over the past 30 years. Predictive models indicate that Ali surpassed highly toxic concentrations at BUC for three to four months annually during 2001–2003 but for only two to three weeks annually during 2015–2017. The current lack of extremely high Ali concentrations indicate toxicity has declined markedly between the 1989–1990, 2001–2003, and 2015–2017 test periods, yet acid- Ali episodes can still cause moderate-to-high levels of brook trout mortality during high springtime flows. Assembled models show how mortality of brook trout in several Adirondack streams likely declined in response to the 1990 Clean Air Act Amendments and offer a means to predict how changes in United States regulations that limit the atmospheric emissions of nitrogen (N) and sulfur (S) oxides, and the deposition of N and S, could affect brook trout survival and impaired stream ecosystems in the western Adirondack region.","language":"English","publisher":"New York Energy Research and Development Authority","usgsCitation":"Baldigo, B.P., and George, S.D., 2020, Decreases in aluminum toxicity and mortality of caged brook trout in Adirondack Mountain Streams: Summary Report 20-35, vi, 31 p.","productDescription":"vi, 31 p.","ipdsId":"IP-107974","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":384719,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":384707,"type":{"id":15,"text":"Index Page"},"url":"https://www.nyserda.ny.gov/-/media/Files/Publications/Research/Transportation/20-35-Decreases-in-Aluminium-toxicity-and-mortality-of-caged-brook-trout.pdf"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.0146484375,\n 43.56447158721811\n ],\n [\n -74.44335937499999,\n 43.56447158721811\n ],\n [\n -74.44335937499999,\n 43.830564195198264\n ],\n [\n -75.0146484375,\n 43.830564195198264\n ],\n [\n -75.0146484375,\n 43.56447158721811\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813104,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70216789,"text":"70216789 - 2020 - Comparing methods to estimate the proportion of turbine-induced bird and bat mortality in the search area under a road and pad search protocol","interactions":[],"lastModifiedDate":"2020-12-07T14:56:49.886538","indexId":"70216789","displayToPublicDate":"2020-11-30T08:53:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1573,"text":"Environmental and Ecological Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Comparing methods to estimate the proportion of turbine-induced bird and bat mortality in the search area under a road and pad search protocol","docAbstract":"Estimating bird and bat mortality at wind facilities typically involves searching for carcasses on the ground near turbines. Some fraction of carcasses inevitably lie outside the search plots, and accurate mortality estimation requires accounting for those carcasses using models to extrapolate from searched to unsearched areas. Such models should account for variation in carcass density with distance, and ideally also for variation with direction (anisotropy). We compare five methods of accounting for carcasses that land outside the searched area (ratio, weighted distribution, non-parametric, and two generalized linear models (glm)) by simulating spatial arrival patterns and the detection process to mimic observations which result from surveying only, or primarily, roads and pads (R&P) and applying the five methods. Simulations vary R&P configurations, spatial carcass distributions (isotropic and anisotropic), and per turbine fatality rates. Our results suggest that the ratio method is less accurate with higher variation relative to the other four methods which all perform similarly under isotropy. All methods were biased under anisotropy; however, including direction covariates in the glm method substantially reduced bias. In addition to comparing methods of accounting for unsearched areas, we suggest a semiparametric bootstrap to produce confidence-based bounds for the proportion of carcasses that land in the searched area.
","language":"English","publisher":"Springer","doi":"10.1007/s10651-020-00466-0","usgsCitation":"Maurer, J., Huso, M., Dalthorp, D., Madsen, L., and Fuentes, C., 2020, Comparing methods to estimate the proportion of turbine-induced bird and bat mortality in the search area under a road and pad search protocol: Environmental and Ecological Statistics, v. 27, p. 769-801, https://doi.org/10.1007/s10651-020-00466-0.","productDescription":"33 p.","startPage":"769","endPage":"801","ipdsId":"IP-099193","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":454728,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10651-020-00466-0","text":"Publisher Index Page"},{"id":381025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","noUsgsAuthors":false,"publicationDate":"2020-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Maurer, Joseph","contributorId":245476,"corporation":false,"usgs":false,"family":"Maurer","given":"Joseph","email":"","affiliations":[{"id":49202,"text":"W. L. Gore and Associates, Inc.","active":true,"usgs":false}],"preferred":false,"id":806263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huso, Manuela 0000-0003-4687-6625 mhuso@usgs.gov","orcid":"https://orcid.org/0000-0003-4687-6625","contributorId":223969,"corporation":false,"usgs":true,"family":"Huso","given":"Manuela","email":"mhuso@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":806264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dalthorp, Daniel 0000-0002-4815-6309 ddalthorp@usgs.gov","orcid":"https://orcid.org/0000-0002-4815-6309","contributorId":4902,"corporation":false,"usgs":true,"family":"Dalthorp","given":"Daniel","email":"ddalthorp@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":806265,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Madsen, Lisa","contributorId":210021,"corporation":false,"usgs":false,"family":"Madsen","given":"Lisa","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":806266,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuentes, Claudio","contributorId":245477,"corporation":false,"usgs":false,"family":"Fuentes","given":"Claudio","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":806267,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70216691,"text":"70216691 - 2020 - colorspace: A toolbox for manipulating and assessing colors and palettes","interactions":[],"lastModifiedDate":"2020-12-01T13:30:32.548807","indexId":"70216691","displayToPublicDate":"2020-11-29T07:27:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2465,"text":"Journal of Statistical Software","active":true,"publicationSubtype":{"id":10}},"title":"colorspace: A toolbox for manipulating and assessing colors and palettes","docAbstract":"| The R package colorspace provides a flexible toolbox for selecting individual colors or color palettes, manipulating these colors, and employing them in statistical graphics and data visualizations. In particular, the package provides a broad range of color palettes based on the HCL (hue-chroma-luminance) color space. The three HCL dimensions have been shown to match those of the human visual system very well, thus facilitating intuitive selection of color palettes through trajectories in this space. Using the HCL color model, general strategies for three types of palettes are implemented: (1) Qualitative for coding categorical information, i.e., where no particular ordering of categories is available. (2) Sequential for coding ordered/numeric information, i.e., going from high to low (or vice versa). (3) Diverging for coding ordered/numeric information around a central neutral value, i.e., where colors diverge from neutral to two extremes. To aid selection and application of these palettes, the package also contains scales for use with ggplot2, shiny and tcltk apps for interactive exploration, visualizations of palette properties, accompanying manipulation utilities (like desaturation and lighten/darken), and emulation of color vision deficiencies. The shiny apps are also hosted online at http://hclwizard.org/. |
","language":"English","publisher":"Foundation of Open Access Statistics","doi":"10.18637/jss.v096.i01","usgsCitation":"Zeileis, A., Fisher, J.C., Hornik, K., Ihaka, R., McWhite, C.D., Murrell, P., Stauffer, R., and Wilke, C.O., 2020, colorspace: A toolbox for manipulating and assessing colors and palettes: Journal of Statistical Software, v. 96, no. 1, 49 p., https://doi.org/10.18637/jss.v096.i01.","productDescription":"49 p.","ipdsId":"IP-107096","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":454733,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.18637/jss.v096.i01","text":"Publisher Index Page"},{"id":380906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zeileis, Achim","contributorId":245311,"corporation":false,"usgs":false,"family":"Zeileis","given":"Achim","email":"","affiliations":[{"id":49146,"text":"Universität Innsbruck","active":true,"usgs":false}],"preferred":false,"id":805894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Jason C. 0000-0001-9032-8912 jfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-9032-8912","contributorId":2523,"corporation":false,"usgs":true,"family":"Fisher","given":"Jason","email":"jfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":805895,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hornik, Kurt","contributorId":245312,"corporation":false,"usgs":false,"family":"Hornik","given":"Kurt","email":"","affiliations":[{"id":49147,"text":"WU Wirtschafts- universität Wien","active":true,"usgs":false}],"preferred":false,"id":805896,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ihaka, Ross","contributorId":245313,"corporation":false,"usgs":false,"family":"Ihaka","given":"Ross","email":"","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":805897,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McWhite, Claire D.","contributorId":245314,"corporation":false,"usgs":false,"family":"McWhite","given":"Claire","email":"","middleInitial":"D.","affiliations":[{"id":29861,"text":"The University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":805898,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murrell, Paul","contributorId":245315,"corporation":false,"usgs":false,"family":"Murrell","given":"Paul","email":"","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":805899,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stauffer, Reto","contributorId":245316,"corporation":false,"usgs":false,"family":"Stauffer","given":"Reto","email":"","affiliations":[{"id":49146,"text":"Universität Innsbruck","active":true,"usgs":false}],"preferred":false,"id":805900,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wilke, Claus O.","contributorId":245317,"corporation":false,"usgs":false,"family":"Wilke","given":"Claus","email":"","middleInitial":"O.","affiliations":[{"id":29861,"text":"The University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":805901,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70216777,"text":"70216777 - 2020 - The new Landsat Collection-2 Digital Elevation Model","interactions":[],"lastModifiedDate":"2020-12-07T16:01:13.585843","indexId":"70216777","displayToPublicDate":"2020-11-28T09:57:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"The new Landsat Collection-2 Digital Elevation Model","docAbstract":"The Landsat Collection-2 distribution introduces a new global Digital Elevation Model (DEM) for scene orthorectification. The new global DEM is a composite of the latest and most accurate freely available DEM sources and will include reprocessed Shuttle Radar Topographic Mission (SRTM) data (called NASADEM), high-resolution stereo optical data (ArcticDEM), a new National Elevation Dataset (NED) and various publicly available national datasets including the Canadian Digital Elevation Model (CDEM) and DEMs for Sweden, Norway and Finland (SNF). The new DEM will be available world-wide with few exceptions. It is anticipated that the transition from the Collection-1 DEM at 3 arcsecond to the new DEM will be seamless because processing methods to maintain a seamless transition were employed, void filling techniques were used, where persistent gaps were found, and the pixel spacing is the same between the two collections. Improvements to the vertical accuracy were realized by differencing accuracies of other elevation datasets to the new DEM. The greatest improvement occurred where ArcticDEM data were used, where an improvement of 35 m was measured. By using theses improved vertical values in a line of sight algorithm, horizontal improvements were noted in some of the most mountainous regions over multiple 30-m Landsat pixels. This new DEM will be used to process all of the scenes from Landsat 1-8 in Collection-2 processing and will be made available to the public by the end of 2020.
","language":"English","publisher":"MDPI","doi":"10.3390/rs12233909","usgsCitation":"Franks, S., Storey, J., and Rengarajan, R., 2020, The new Landsat Collection-2 Digital Elevation Model: Remote Sensing, v. 12, no. 23, 3909, 24 p., https://doi.org/10.3390/rs12233909.","productDescription":"3909, 24 p.","ipdsId":"IP-123106","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":454735,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12233909","text":"Publisher Index Page"},{"id":381037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"23","noUsgsAuthors":false,"publicationDate":"2020-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Franks, Shannon 0000-0003-1335-5401","orcid":"https://orcid.org/0000-0003-1335-5401","contributorId":245457,"corporation":false,"usgs":false,"family":"Franks","given":"Shannon","email":"","affiliations":[{"id":49197,"text":"KBR, Contractor to NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":806216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storey, James C. 0000-0002-6664-7232","orcid":"https://orcid.org/0000-0002-6664-7232","contributorId":242015,"corporation":false,"usgs":false,"family":"Storey","given":"James C.","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":806217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rengarajan, Rajagopalan 0000-0003-1860-7110","orcid":"https://orcid.org/0000-0003-1860-7110","contributorId":242014,"corporation":false,"usgs":false,"family":"Rengarajan","given":"Rajagopalan","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":806218,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70240902,"text":"70240902 - 2020 - Evidence of spawning by lake trout Salvelinus namaycush on substrates at the base of large boulders in northern Lake Huron","interactions":[],"lastModifiedDate":"2023-03-01T12:39:03.288748","indexId":"70240902","displayToPublicDate":"2020-11-27T06:36:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of spawning by lake trout Salvelinus namaycush on substrates at the base of large boulders in northern Lake Huron","docAbstract":"Identification of lake trout spawning sites has focused on cobble substrates associated with bathymetric relief (e.g., ‘contour’ or ‘slope’ along reefs), but this ‘model’ may be narrow in scope. Previous telemetry work conducted near Drummond Island, USA, Lake Huron, identified egg presence in substrates at the base of large boulders (>1 m diameter); however, the extent of this phenomenon was unknown. Telemetry data paired with multi-beam bathymetry identified a 0.63 km2 area used by lake trout characterized by low bathymetric relief and numerous (~269) large boulders (>1 m diameter) with small-diameter substrates at their bases. Diver surveys revealed egg presence at all 40 boulders surveyed, exclusively associated with clean gravel-cobble (0.6–42 cm) substrates in undercut areas beneath overhanging edges of boulders and in narrow spaces between adjacent boulders. Egg presence was not associated with boulder or substrate physical characteristics which highlighted the possible importance of interstitial currents. Successful incubation in these habitats was inferred by capture of free embryos and post-embryos the following spring using traps and an electrofishing ROV although at lower densities than at popular spawning habitats nearby (1–3 km away). Free embryos and post-embryos were also caught where eggs were not observed the previous fall including unexpectedly on top of boulders which suggested that post-hatch stages may move more than previously thought. Extensive use of boulder-associated habitats for spawning, egg incubation, and early growth suggested this undescribed habitat type may provide an unanticipated contribution to total available lake trout spawning habitat and recruitment in the Great Lakes.
During explosive volcanic eruptions, large quantities of tephra can be dispersed and deposited over wide areas. Following deposition, subsequent aeolian remobilisation of ash can potentially exacerbate primary impacts on timescales of months to millennia. Recent ash remobilisation events (e.g., following eruptions of Cordón Caulle 2011; Chile, and Eyjafjallajökull 2010, Iceland) have highlighted this to be a recurring phenomenon with consequences for human health, economic sectors, and critical infrastructure. Consequently, scientists from observatories and Volcanic Ash Advisory Centers (VAACs), as well as researchers from fields including volcanology, aeolian processes and soil sciences, convened at the San Carlos de Bariloche headquarters of the Argentinian National Institute of Agricultural Technology to discuss the “state of the art” for field studies of remobilised deposits as well as monitoring, modeling and understanding ash remobilisation. In this article, we identify practices for field characterisation of deposits and active processes, including mapping, particle characterisation and sediment traps. Furthermore, since forecast models currently rely on poorly-constrained dust emission schemes, we call for laboratory and field measurements to better parameterise the flux of volcanic ash as a function of friction velocity. While source area location and extent are currently the primary inputs for dispersion models, once emission schemes become more sophisticated and better constrained, other parameters will also become important (e.g., source material volume and properties, effective precipitation, type and distribution of vegetation cover, friction velocity). Thus, aeolian ash remobilisation hazard and associated impact assessment require systematic monitoring, including the development of a regularly-updated spatial database of resuspension source areas.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2020.575184","usgsCitation":"Jarvis, P.A., Bonadonna, C., Dominguez, L., Forte, P., Frischknecht, C., Bran, D., Aguilar, R., Beckett, F., Elissondo, M., Gillies, J., Kueppers, U., Merrison, J., Varley, N., and Wallace, K.L., 2020, Aeolian remobilisation of volcanic ash: Outcomes of a workshop in the Argentinian Patagonia: Frontiers in Earth Science, v. 8, 575184, 9 p., https://doi.org/10.3389/feart.2020.575184.","productDescription":"575184, 9 p.","ipdsId":"IP-120112","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467270,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2020.575184","text":"Publisher Index Page"},{"id":463343,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2020-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Jarvis, Paul A.","contributorId":345634,"corporation":false,"usgs":false,"family":"Jarvis","given":"Paul","email":"","middleInitial":"A.","affiliations":[{"id":82666,"text":"Department of Earth Sciences, University of Geneva, Geneva, Switzerland","active":true,"usgs":false}],"preferred":false,"id":917147,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonadonna, Costanza","contributorId":345635,"corporation":false,"usgs":false,"family":"Bonadonna","given":"Costanza","affiliations":[{"id":82666,"text":"Department of Earth Sciences, University of Geneva, Geneva, Switzerland","active":true,"usgs":false}],"preferred":false,"id":917148,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dominguez, 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,{"id":70216842,"text":"70216842 - 2020 - Evaluating the impacts of foreshore sand and birds on microbiological contamination at a freshwater beach","interactions":[],"lastModifiedDate":"2020-12-10T12:47:42.117676","indexId":"70216842","displayToPublicDate":"2020-11-26T08:00:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the impacts of foreshore sand and birds on microbiological contamination at a freshwater beach","docAbstract":"Beaches along the Great Lakes shorelines are important recreational and economic resources. However, contamination at the beaches can threaten their usage during the swimming season, potentially resulting in beach closures and/or advisories. Thus, understanding the dynamics that control nearshore water quality is integral to effective beach management. There have been significant improvements in this effort, including incorporating modeling (empirical, mechanistic) in recent years. Mechanistic modeling frameworks can contribute to this understanding of dynamics by determining sources and interactions that substantially impact fecal indicator bacteria concentrations, an index routinely used in water quality monitoring programs. To simulate E. coli concentrations at Jeorse Park beaches in southwest Lake Michigan, a coupled hydrodynamic and wave–current interaction model was developed that progressively added contaminant sources from river inputs, avian presence, bacteria–sediment interactions, and bacteria–sand–sediment interactions. Results indicated that riverine inputs affected E. coli concentrations at Jeorse Park beaches only marginally, while avian, shoreline sand, and sediment sources were much more substantial drivers of E. coli contamination at the beach. By including avian and riverine inputs, as well as bacteria–sand–sediment interactions at the beach, models can reasonably capture the variability in observed E. coli concentrations in nearshore water and bed sediments at Jeorse Park beaches. Consequently, it will be crucial to consider avian contamination sources and water-sand-sediment interactions in effective management of the beach for public health and as a recreational resource and to extend these findings to similar beaches affected by shoreline embayment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2020.116671","usgsCitation":"Saffaie, A., Weiskerger, C.J., Nevers, M., Byappanahalli, M., and Phanikumar, M.S., 2020, Evaluating the impacts of foreshore sand and birds on microbiological contamination at a freshwater beach: Water Research, v. 190, 116671, 13 p., https://doi.org/10.1016/j.watres.2020.116671.","productDescription":"116671, 13 p.","ipdsId":"IP-120391","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":381163,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illlinois","city":"Chicago","otherGeospatial":"Jeorse Park Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.440185546875,\n 41.64803176818231\n ],\n [\n -87.43228912353514,\n 41.64803176818231\n ],\n [\n -87.43228912353514,\n 41.656625449889276\n ],\n [\n -87.440185546875,\n 41.656625449889276\n ],\n [\n -87.440185546875,\n 41.64803176818231\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"190","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Saffaie, Ammar","contributorId":245601,"corporation":false,"usgs":false,"family":"Saffaie","given":"Ammar","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":806590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weiskerger, Chelsea J.","contributorId":150865,"corporation":false,"usgs":false,"family":"Weiskerger","given":"Chelsea","email":"","middleInitial":"J.","affiliations":[{"id":18126,"text":"National Park Service, Indiana Dunes National Lakeshore","active":true,"usgs":false}],"preferred":false,"id":806591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nevers, Meredith B. 0000-0001-6963-6734","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":201531,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":806592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Byappanahalli, Muruleedhara 0000-0001-5376-597X byappan@usgs.gov","orcid":"https://orcid.org/0000-0001-5376-597X","contributorId":147923,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":806593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phanikumar, Mantha S.","contributorId":208872,"corporation":false,"usgs":false,"family":"Phanikumar","given":"Mantha","email":"","middleInitial":"S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":806594,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70224312,"text":"70224312 - 2020 - Post-fire vegetation response in a repeatedly burned low-elevation sagebrush steppe protected area provides insights about resilience and invasion resistance","interactions":[],"lastModifiedDate":"2021-09-21T12:37:06.443373","indexId":"70224312","displayToPublicDate":"2020-11-26T07:33:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Post-fire vegetation response in a repeatedly burned low-elevation sagebrush steppe protected area provides insights about resilience and invasion resistance","docAbstract":"Sagebrush steppe ecosystems are threatened by human land-use legacies, biological invasions, and altered fire and climate dynamics. Steppe protected areas are therefore of heightened conservation importance but are few and vulnerable to the same impacts broadly affecting sagebrush steppe. To address this problem, sagebrush steppe conservation science is increasingly emphasizing a focus on resilience to fire and resistance to non-native annual grass invasion as a decision framework. It is well-established that the positive feedback loop between fire and annual grass invasion is the driving process of most contemporary steppe degradation. We use a newly developed ordinal zero-augmented beta regression model fit to large-sample vegetation monitoring data from John Day Fossil Beds National Monument, USA, spanning 7 years to evaluate fire responses of two native perennial foundation bunchgrasses and two non-native invasive annual grasses in a repeatedly burned, historically grazed, and inherently low-resilient protected area. We structured our model hierarchically to support inferences about variation among ecological site types and over time after also accounting for growing-season water deficit, fine-scale topographic variation, and burn severity. We use a state-and-transition conceptual diagram and abundances of plants listed in ecological site reference conditions to formalize our hypothesis of fire-accelerated transition to ecologically novel annual grassland. Notably, big sagebrush (Artemisia tridentata) and other woody species were entirely removed by fire. The two perennial grasses, bluebunch wheatgrass (Pseudoroegneria spicata) and Thurber's needlegrass (Achnatherum thurberianum) exhibited fire resiliency, with no apparent trend after fire. The two annual grasses, cheatgrass (Bromus tectorum) and medusahead (Taeniatherum caput-medusae), increased in response to burn severity, most notably medusahead. Surprisingly, we found no variation in grass cover among ecological sites, suggesting fire-driven homogenization as shrubs were removed and annual grasses became dominant. We found contrasting responses among all four grass species along gradients of topography and water deficit, informative to protected-area conservation strategies. The fine-grained influence of topography was particularly important to variation in cover among species and provides a foothold for conservation in low-resilient, aridic steppe. Broadly, our study demonstrates how to operationalize resilience and resistance concepts for protected areas by integrating empirical data with conceptual and statistical models.
>In the current era of rapid climate change, accurate characterization of climate-relevant gas dynamics – namely production, consumption, and net emissions – is required for all biomes, especially those ecosystems most susceptible to the impact of change. Marine environments include regions that act as net sources or sinks for numerous climate-active trace gases including methane (CH4) and nitrous oxide (N2O). The temporal and spatial distributions of CH4 and N2O are controlled by the interaction of complex biogeochemical and physical processes. To evaluate and quantify how these mechanisms affect marine CH4 and N2O cycling requires a combination of traditional scientific disciplines including oceanography, microbiology, and numerical modeling. Fundamental to these efforts is ensuring that the datasets produced by independent scientists are comparable and interoperable. Equally critical is transparent communication within the research community about the technical improvements required to increase our collective understanding of marine CH4 and N2O. A workshop sponsored by Ocean Carbon and Biogeochemistry (OCB) was organized to enhance dialogue and collaborations pertaining to marine CH4 and N2O. Here, we summarize the outcomes from the workshop to describe the challenges and opportunities for near-future CH4 and N2O research in the marine environment.
","language":"English","publisher":"Copernicus","doi":"10.5194/bg-17-5809-2020","usgsCitation":"Wilson, S., Al-Haj, A., Bourbonnais, A., Frey, C., Fulweiler, R., Kessler, J.D., Marchant, H., Milucka, J., Ray, N., Suntharalingham, P., Thornton, B., Upstill-Goddard, R., Weber, T., Arévalo-Martínez, D., Bange, H., Benway, H., Bianchi, D., Borges, A., Chang, B., Crill, P., del Valle, D., Farias, L., Joye, S., Kock, A., Labidi, J., Manning, C., Pohlman, J., Rehder, G., Sparrow, K., Tortell, P., Truede, T., Valentine, D., Ward, B., Yang, S., and Yurganov, L., 2020, Ideas and perspectives: A strategic assessment of methane and nitrous oxide measurements in the marine environment: Biogeosciences, v. 17, no. 22, p. 5809-5828, https://doi.org/10.5194/bg-17-5809-2020.","productDescription":"20 p.","startPage":"5809","endPage":"5828","ipdsId":"IP-123280","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454748,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-17-5809-2020","text":"Publisher Index Page"},{"id":382916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"22","noUsgsAuthors":false,"publicationDate":"2020-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, S.T.","contributorId":248724,"corporation":false,"usgs":false,"family":"Wilson","given":"S.T.","email":"","affiliations":[{"id":49988,"text":"University of Hawai’i at Manoa, Daniel K. 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Canada","active":true,"usgs":false}],"preferred":false,"id":809785,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Truede, T.","contributorId":248752,"corporation":false,"usgs":false,"family":"Truede","given":"T.","email":"","affiliations":[{"id":50001,"text":"University of California Los Angeles, Department of Atmospheric and Oceanic Sciences, California","active":true,"usgs":false}],"preferred":false,"id":809786,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Valentine, D.L.","contributorId":184239,"corporation":false,"usgs":false,"family":"Valentine","given":"D.L.","email":"","affiliations":[],"preferred":false,"id":809787,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Ward, B.B.","contributorId":248753,"corporation":false,"usgs":false,"family":"Ward","given":"B.B.","affiliations":[{"id":50012,"text":"Princeton University, Geoscience Department, New Jersey","active":true,"usgs":false}],"preferred":false,"id":809788,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Yang, S.","contributorId":248754,"corporation":false,"usgs":false,"family":"Yang","given":"S.","affiliations":[{"id":50001,"text":"University of California Los Angeles, Department of Atmospheric and Oceanic Sciences, California","active":true,"usgs":false}],"preferred":false,"id":809789,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Yurganov, L.N.","contributorId":248755,"corporation":false,"usgs":false,"family":"Yurganov","given":"L.N.","email":"","affiliations":[{"id":50013,"text":"University of Maryland Baltimore County, Baltimore","active":true,"usgs":false}],"preferred":false,"id":809790,"contributorType":{"id":1,"text":"Authors"},"rank":35}]}}
,{"id":70217298,"text":"70217298 - 2020 - Whitebark pine in the national parks of the Pacific states: An assessment of population vulnerability","interactions":[],"lastModifiedDate":"2021-01-18T13:54:14.320789","indexId":"70217298","displayToPublicDate":"2020-11-25T07:49:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2900,"text":"Northwest Science","onlineIssn":"2161-9859","printIssn":"0029-344X","active":true,"publicationSubtype":{"id":10}},"title":"Whitebark pine in the national parks of the Pacific states: An assessment of population vulnerability","docAbstract":"Whitebark pine (Pinus albicaulis) is a long-lived tree found in high-elevation forests of western North America that is declining due to the non-native white pine blister rust (Cronartium ribicola) and climate-driven outbreaks of mountain pine beetle (Dendroctonus ponderosae; MPB). The National Park Service established a monitoring program for whitebark pine in seven parks, including Sequoia & Kings Canyon, Yosemite, Lassen Volcanic, Crater Lake, Mount Rainier, Olympic, and North Cascades National Parks. Using these data, we summarized stand structure, presence of blister rust, and MPB prevalence to provide a baseline for future monitoring. Next, we used a stochastic, size-structured population model to speculate on future trends in the seven national park populations under conditions of increased MPB activity and ongoing blister rust infection observed in Crater Lake. We found that blister rust infected 29 to 54% of whitebark pine in all the parks except the two southernmost, Sequoia & Kings Canyon and Yosemite, where infections rates were 0.3% and 0.2%, respectively. The proportion of dead trees in Sequoia & Kings Canyon and Yosemite was low (0 to 1%), while they ranged from 10 to 43% in the other parks. Model projections suggested an average population decline of 25% in the parks over the next century using Crater Lake conditions, declines which are possible if blister rust continues to spread and climate change results in a significant increase in the frequency or severity of MPB outbreaks. Overall, our study describes conditions at seven western parks and illustrates potential rates of whitebark pine decline if pest outbreaks and/or blister rust infections worsen.
Thirty water wells were sampled in 2018 to understand the geochemistry and age of groundwater in the Williston Basin and assess potential effects of shale-oil production from the Three Forks-Bakken petroleum system (TBPS) on groundwater quality. Two geochemical groups are identified using hierarchical cluster analysis. Group 1 represents the younger (median 4He = 21.49 × 10−8 cm3 STP/g), less chemically evolved water. Group 2 represents the older (median 4He = 1389 × 10−8 cm3 STP/g), more chemically evolved water. At least two samples from each group contain elevated Cl concentrations (>70 mg/L). Br/Cl, B/Cl, and Li/Cl ratios indicate multiple sources account for the elevated Cl concentrations: septic-system leachate/road deicing salt, lignite beds in the aquifers, Pierre Shale beneath the aquifers, and water associated with the TBPS (one sample). 3H and 14C data indicate that 10.8, 21.6, and 67.6% of the samples are modern (post-1952), mixed age, and premodern (pre-1953), respectively. Lumped-parameter modeling of 3H, SF6, 3He, and 14C concentrations indicates mean ages of the modern and premodern fractions range from ~1 to 30 years and 1300 to >30,000 years, respectively. Group 2 contains the highest CH4 concentrations (0.0018–32 mg/L). δ13C–CH4 and C1/C2+C3 data in groundwater (−91.7 to −70.0‰ and 1280 to 13,600) indicate groundwater CH4 is biogenic in origin and not from thermogenic shale gas. Four volatile organic compounds (VOCs) were detected in two samples. One mixed-age sample contains chloroform (0.25 μg/L) and dichloromethane (0.05 μg/L), which are probably associated with septic leachate. One premodern sample contains butane (0.082 μg/L) and n-pentane (0.032 μg/L), which are probably associated with thermogenic gas from a nearby oil well. The data indicate hydrocarbon production activities do not currently (2018) widely affect Cl, CH4, and VOC concentrations in groundwater. The predominance of premodern recharge in the aquifers indicates the groundwater moves relatively slowly, which could inhibit widespread chemical movement in groundwater overlying the TBPS. Comparison of groundwater-age data from five major unconventional hydrocarbon-production areas indicates aquifer zones used for water supply in the TBPS area have a lower risk of widespread chemical movement in groundwater than similar aquifer zones in the Fayetteville (Arkansas) and Marcellus (Pennsylvania) Shale production areas, but have a higher risk than similar aquifer zones in the Eagle Ford (Texas) and Haynesville (Texas, Louisiana) Shale production areas.
Bathymetric and velocimetric data were collected by the U.S. Geological Survey, in cooperation with the Missouri Department of Transportation, near 7 bridges at 6 highway crossings of the Missouri and Mississippi Rivers on the periphery of the State of Missouri from July 16 to August 13, 2018. A multibeam echosounder mapping system was used to obtain channel-bed elevations for river reaches about 1,640 feet longitudinally and generally extending laterally across the active channel from bank to bank during moderate flood-flow conditions. These surveys indicate the channel conditions at the time of the surveys and provide characteristics of scour holes that may be useful in the development of predictive guidelines or equations for scour holes. These data also may be useful to the Missouri Department of Transportation as a low to moderate flood-flow comparison to help assess the bridges for stability and integrity issues with respect to bridge scour during floods.
Bathymetric data were collected around every pier that was in water, except those at the edge of water, and scour holes were present at most piers for which bathymetry could be obtained, except those on banks, on bedrock, or surrounded by riprap. Occasionally, the scour hole near a pier was difficult to discern from nearby bed features. The observed scour holes at the surveyed bridges were generally examined with respect to shape and depth.
Although partial exposure of substructural support elements was observed at several piers, at most sites the exposure likely can be considered minimal compared to the overall substructure that remains buried in bed material at these piers. The notable exceptions are piers 12 and 13 at structure L0135 on State Highway 51 at Chester, Illinois, at which the bedrock material was fully exposed around the piers.
The presence of riprap blankets, pier size and nose shape, and alignment to flow had a substantial effect on the size of the scour hole observed for a given pier. Piers that were surrounded by riprap blankets had scour holes that were substantially smaller (to nonexistent) compared to piers at which no rock or riprap were present. Narrow piers having round or sharp noses that were aligned with flow often had scour holes that were difficult to discern from nearby bed features, whereas piers having wide or blunt noses resulted in larger, deeper scour holes. Several of the structures had piers that were skewed to primary approach flow, and scour holes near these piers generally displayed deposition on the leeward side of the pier and greater depth on the side of the pier with impinging flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205088","collaboration":"Prepared in cooperation with the Missouri Department of Transportation","usgsCitation":"Huizinga, R.J., 2020, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri and Mississippi Rivers on the periphery of Missouri, July–August 2018: U.S. Geological Survey Scientific Investigations Report 2020–5088, 100 p., https://doi.org/10.3133/sir20205088.","productDescription":"Report: vii, 100 p.; Data Release","numberOfPages":"112","onlineOnly":"Y","ipdsId":"IP-115831","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":380760,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5088/coverthb.jpg"},{"id":380761,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5088/sir20205088.pdf","text":"Report","size":"21.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5088"},{"id":380762,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WDI9YF","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Bathymetry and velocity data from surveys at highway bridges crossing the Missouri and Mississippi Rivers on the periphery of Missouri, December 2008 through August 2018"}],"country":"United States","state":"Missouri","otherGeospatial":"Mississippi River, Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.68017578125,\n 39.257778150283364\n ],\n [\n -94.72412109375,\n 39.07890809706475\n ],\n [\n -94.603271484375,\n 38.993572058209466\n ],\n [\n -94.28466796874999,\n 39.00211029922515\n ],\n [\n -93.88916015625,\n 39.00211029922515\n ],\n [\n -93.526611328125,\n 39.06184913429154\n ],\n [\n -93.09814453125,\n 39.155622393423215\n ],\n [\n -93.05419921875,\n 39.00211029922515\n ],\n [\n -92.92236328125,\n 38.87392853923629\n ],\n [\n -92.65869140625,\n 38.805470223177466\n ],\n [\n -92.59277343749999,\n 38.659777730712534\n ],\n [\n -92.30712890625,\n 38.53097889440024\n ],\n [\n -92.054443359375,\n 38.46219172306828\n ],\n [\n -91.42822265625,\n 38.51378825951165\n ],\n [\n -91.01074218749999,\n 38.436379603\n ],\n [\n -90.802001953125,\n 38.41916639395372\n ],\n [\n -90.3515625,\n 38.66835610151506\n ],\n [\n -90.164794921875,\n 38.77978137804918\n ],\n [\n -90.054931640625,\n 38.950865400919994\n ],\n [\n -90.19775390625,\n 38.95940879245423\n ],\n [\n -90.54931640625,\n 38.84826438869913\n ],\n [\n -90.90087890624999,\n 38.69408504756833\n ],\n [\n -91.16455078125,\n 38.831149809348744\n ],\n [\n -91.593017578125,\n 38.85682013474361\n ],\n [\n -92.10937499999999,\n 38.7283759182398\n ],\n [\n -92.373046875,\n 38.96795115401593\n ],\n [\n -92.7685546875,\n 39.27478966170308\n ],\n [\n -93.09814453125,\n 39.470125122358176\n ],\n [\n -93.955078125,\n 39.317300373271024\n ],\n [\n -94.22973632812499,\n 39.33429742980725\n ],\n [\n -94.68017578125,\n 39.257778150283364\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
","tableOfContents":"- Abstract
- Introduction
- Results of Bathymetric and Velocimetric Surveys
- Summary and Conclusions
- References Cited
- Appendix 1. Shaded Triangulated Irregular Network Images of the Channel and Side of Pier for Each Surveyed Pier
","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-11-24","noUsgsAuthors":false,"publicationDate":"2020-11-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Huizinga, Richard J. 0000-0002-2940-2324 huizinga@usgs.gov","orcid":"https://orcid.org/0000-0002-2940-2324","contributorId":2089,"corporation":false,"usgs":true,"family":"Huizinga","given":"Richard","email":"huizinga@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":805541,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70216484,"text":"sim3465 - 2020 - Predicted pH of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers, south-central United States","interactions":[],"lastModifiedDate":"2020-11-25T12:48:14.764979","indexId":"sim3465","displayToPublicDate":"2020-11-24T14:14:54","publicationYear":"2020","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":"3465","displayTitle":"Predicted pH of Groundwater in the Mississippi River Valley Alluvial and Claiborne Aquifers, South-Central United States","title":"Predicted pH of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers, south-central United States","docAbstract":"Regional aquifers in the Mississippi embayment are the principal sources of water used for public and domestic supply, irrigation, and industrial uses throughout the region. An understanding of how water quality varies spatially, temporally, and with depth are critical aspects to ensuring long-term sustainable use of these resources. A boosted regression tree (BRT) model was used by the U.S. Geological Survey (USGS) to map water quality in the three regional aquifers with the largest groundwater withdrawals in the embayment: the Mississippi River Valley alluvial (MRVA) aquifer, middle Claiborne aquifer (MCAQ), and lower Claiborne aquifer (LCAQ).
The BRT model was used to predict pH to 1-kilometer raster grid cells for seven aquifer layers (one MRVA, four MCAQ, two LCAQ) following the hydrogeologic framework of the Mississippi embayment aquifer system regional MODFLOW model. The methods and approach used for pH predictions are the same as those used recently by the USGS to predict specific conductance and chloride in the aquifers. Explanatory variables for the BRT models included variables describing well location and construction, surficial variables such as soil properties and land use, and variables extracted from the groundwater flow model, such as groundwater levels and ages. The primary source of pH data was the USGS National Water Information System database. Additional data from State ambient groundwater monitoring programs and the Safe Drinking Water Information System also were used. For wells sampled multiple times, the most recent sample was used. Because groundwater residence times are long (greater than 100 years) throughout much of the study area, the possible effects of changes in water quality over time were considered small compared to the improvement in overall model accuracy by using available historical data. Values of pH from 3,362 wells for samples collected between 1960 and 2018 were used as training data for the BRT model. An additional 839 samples were used as holdout data to evaluate model performance. The predictive performance of the pH model is lower than for the training dataset, as indicated by an r-squared value of 0.89 for the training data and an r-squared of 0.71 for the holdout data. The root mean squared errors for the training and holdout data are 0.32 and 0.50 standard pH units, respectively. Data generated during this study and the model output are available from the companion data release.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3465","usgsCitation":"Kingsbury, J.A., Knierim, K.J., and Haugh, C.J., 2020, Predicted pH of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers, South-Central United States: U.S. Geological Survey Scientific Investigations Map 3465, 1 sheet, https://doi.org/10.3133/sim3465.","productDescription":"1 Sheet: 34.60 x 28.70 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-111848","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":380668,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CXX7LN","text":"USGS data release","linkHelpText":"Prediction grids of pH for the Mississippi River Valley alluvial and Claiborne aquifers"},{"id":380666,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3465/coverthb2.jpg"},{"id":380667,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3465/sim3465.pdf","text":"Report","size":"3.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3465"}],"country":"United States","state":"Alabama, Arkansas, Louisiana, Mississippi, Missouri","otherGeospatial":"Mississippi River Valley alluvial, Claiborne aquifers","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.296875,\n 37.020098201368114\n ],\n [\n -90.1318359375,\n 36.66841891894786\n ],\n [\n -91.93359375,\n 35.28150065789119\n ],\n [\n -93.33984375,\n 33.65120829920497\n ],\n [\n -94.04296874999999,\n 33.100745405144245\n ],\n [\n -93.91113281249999,\n 31.952162238024975\n ],\n [\n -93.1640625,\n 31.090574094954192\n ],\n [\n -91.7578125,\n 30.939924331023445\n ],\n [\n -91.0986328125,\n 31.952162238024975\n ],\n [\n -90.703125,\n 32.24997445586331\n ],\n [\n -89.3408203125,\n 32.175612478499325\n ],\n [\n -88.0224609375,\n 31.57853542647338\n ],\n [\n -87.4951171875,\n 31.80289258670676\n ],\n [\n -86.748046875,\n 32.99023555965106\n ],\n [\n -87.4072265625,\n 33.211116472416855\n ],\n [\n -88.9892578125,\n 33.94335994657882\n ],\n [\n -89.7802734375,\n 34.74161249883172\n ],\n [\n -90,\n 35.24561909420681\n ],\n [\n -89.56054687499999,\n 36.13787471840729\n ],\n [\n -89.3408203125,\n 36.421282443649496\n ],\n [\n -89.2529296875,\n 36.84446074079564\n ],\n [\n -89.296875,\n 37.020098201368114\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
","tableOfContents":"- Introduction
- References Cited
","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-11-24","noUsgsAuthors":false,"publicationDate":"2020-11-24","publicationStatus":"PW","contributors":{"authors":[{"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":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":805380,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knierim, Katherine J. 0000-0002-5361-4132 kknierim@usgs.gov","orcid":"https://orcid.org/0000-0002-5361-4132","contributorId":191788,"corporation":false,"usgs":true,"family":"Knierim","given":"Katherine","email":"kknierim@usgs.gov","middleInitial":"J.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":805381,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haugh, Connor J. 0000-0002-5204-8271 cjhaugh@usgs.gov","orcid":"https://orcid.org/0000-0002-5204-8271","contributorId":3932,"corporation":false,"usgs":true,"family":"Haugh","given":"Connor","email":"cjhaugh@usgs.gov","middleInitial":"J.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":805382,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70217198,"text":"70217198 - 2020 - Critical shifts in trace metal transport and remediation performance under future low river flows","interactions":[],"lastModifiedDate":"2021-01-12T13:25:25.078301","indexId":"70217198","displayToPublicDate":"2020-11-24T07:22:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Critical shifts in trace metal transport and remediation performance under future low river flows","docAbstract":"Exceptionally low river flows are predicted to become more frequent and more severe across many global regions as a consequence of climate change. Investigations of trace metal transport dynamics across streamflows reveal stark changes in water chemistry, metal transformation processes, and remediation effectiveness under exceptionally low-flow conditions. High spatial resolution hydrological and water quality datasets indicate that metal-rich groundwater will exert a greater control on stream water chemistry and metal concentrations because of climate change. This is because the proportion of stream water sourced from mined areas and mineralized strata will increase under predicted future low-flow scenarios (from 25% under Q45 flow to 66% under Q99 flow in this study). However, mineral speciation modelling indicates that changes in stream pH and hydraulic conditions at low flow will decrease aqueous metal transport and increase sediment metal concentrations by enhancing metal sorption directly to streambed sediments. Solute transport modelling further demonstrates how increases in the importance of metal-rich diffuse groundwater sources at low flow could minimize the benefits of point source metal contamination treatment. Understanding metal transport dynamics under exceptionally low flows, as well as under high flows, is crucial to evaluate ecosystem service provision and remediation effectiveness in watersheds under future climate change scenarios.
This report presents abundance and occurrence data for three species of ambystomad salamanders (Ambystoma maculatum, A. jeffersonianum, and A. opacum) collected over a 3-year period (2000, 2001, and 2002) at 200 potentional breeding sies within the Delaware Water Gap National Recreation Area (DEWA). In addition, numerous measures of inpond, near-pond, and landscape attributes were measured and used to inform statistical models to determine species-habitat relationships in the DEWA.
The results of a 3-year study of ambystomatid salamander breeding habits and habitats in the (DEWA) that was conducted by the U.S. Geological Survey, in cooperation with the National Park Service, are described in the report. The objectives of the study were to document the population status and critical breeding habitats of the three species of ambystomatid salamanders known to be present in the DEWA—Ambystoma maculatum (spotted salamander), A. opacum (marbled salamander), and A. jeffersonianum (Jefferson salamander). DEWA managers are interested in ecological information on these species for several reasons. First, at the time the study began, there was little known regarding the status of pond-breeding amphibians and their habitats in the DEWA. Second, because they require undegraded habitats in both terrestrial and aquatic habitats to successfully complete their life cycles, the status of ambystomatid salamanders is widely viewed as indicative of overall ecosystem health. Third, because ambystomatid salamanders and other pond-breeding amphibians have been observed in numerous artificial impoundments with the DEWA, park managers would like to assess whether dismantling or discontinuing maintenance of artificial impoundments could affect pond-breeding amphibians and possibly other species that use pond or wetland habitats in the Park.
In 2001, 2002, and 2003, the size and location of 200 wetlands, ponds, and artificial impoundments, and related landscape positions (Ridge versus Valley; Pennsylvania side versus New Jersey side of the Delaware river) were mapped, and site habitat data relating to salamander occurrence and abundance patterns were collected. The data collected during this study provide important new baseline information on ambystomatid salamanders and wetland habitats in the DEWA that will enhance long-term inventory and monitoring efforts. In addition, breeding habitat assessments indicate that ambystomatid salamanders may be sensitive to a wide variety of stresses important in the DEWA and in the region. In particular, recent trends in development (for example, roads) in and near the DEWA, regional increases in the acidity of precipitation, and predicted long-term warming trends for the region could be detrimental to pond-breeding salamander populations because of their effects on breeding site quality and quantity, and on the integrity of migration corridors. In contrast, the results of the study indicate management plans to eliminate small impoundments are not likely to adversely affect salamanders in DEWA, at least in the short-term. However, it is possible that these small impoundments may offer stable habitats that provide a rescure effect during long-term droughts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205081","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Snyder, C.D., Young, J.A., Julian, J.T., King, T.L., and Julian, S.E., 2020, Assessment of Ambystomatid salamander populations and their breeding habitats in the Delaware Water Gap National Recreation Area: U.S. Geological Survey Scientific Investigations Report 2020–5081, 41 p., https://doi.org/10.3133/sir20205081.","productDescription":"Report: viii, 41 p.; Data Release","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-113175","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":380510,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5081/coverthb.jpg"},{"id":380511,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5081/sir20205081.pdf","text":"Report","size":"3.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5081"},{"id":380512,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XCVHY3","text":"USGS data release","linkHelpText":"Ambystomatid salamander population and breeding pond habitat data for the Delaware Water Gap National Recreation Area (2001–2003)"}],"country":"United States","state":"New Jersey, Pennsylvania","otherGeospatial":"Delaware Water Gap National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.7564697265625,\n 41.380930388318\n ],\n [\n -74.8992919921875,\n 41.29844430929419\n ],\n [\n -74.9761962890625,\n 41.18278832811288\n ],\n [\n -75.1080322265625,\n 41.06692773019345\n ],\n [\n -75.179443359375,\n 40.992337919312305\n ],\n [\n -75.1629638671875,\n 40.93011520598305\n ],\n [\n -75.0970458984375,\n 40.93841495689795\n ],\n [\n -74.893798828125,\n 41.075210270566636\n ],\n [\n -74.6630859375,\n 41.253032440653186\n ],\n [\n -74.7564697265625,\n 41.380930388318\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
11649 Leetown Road
Kearneysville, WV 25430
Contact Pubs Warehouse
","tableOfContents":"- Acknowledgments
- Abstract
- Introduction
- Study Area
- Methods
- Findings
- Discussion
- Summary
- References Cited
","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2020-11-23","noUsgsAuthors":false,"publicationDate":"2020-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Snyder, Craig D. 0000-0002-3448-597X csnyder@usgs.gov","orcid":"https://orcid.org/0000-0002-3448-597X","contributorId":2568,"corporation":false,"usgs":true,"family":"Snyder","given":"Craig","email":"csnyder@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":804867,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":804868,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Julian, James T.","contributorId":244030,"corporation":false,"usgs":false,"family":"Julian","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":48803,"text":"Pennsylvania Department of Conservation and Natural Resources, Mira Lloyd Dock Resource Conservation Center","active":true,"usgs":false}],"preferred":false,"id":804869,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"King, Tim L. tlking@usgs.gov","contributorId":3520,"corporation":false,"usgs":true,"family":"King","given":"Tim","email":"tlking@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":804870,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Julian, Shanon E.","contributorId":244894,"corporation":false,"usgs":false,"family":"Julian","given":"Shanon","email":"","middleInitial":"E.","affiliations":[{"id":34554,"text":"U.S. Fish and Wildlife Service Northeast Fishery Center","active":true,"usgs":false}],"preferred":false,"id":804871,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70216751,"text":"70216751 - 2020 - U.S. mineral supply chain security in the age of pandemics and trade wars","interactions":[],"lastModifiedDate":"2020-12-04T15:53:22.134457","indexId":"70216751","displayToPublicDate":"2020-11-23T09:48:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7448,"text":"The Science Breaker","active":true,"publicationSubtype":{"id":10}},"title":"U.S. mineral supply chain security in the age of pandemics and trade wars","docAbstract":"Modern technology makes use of numerous mineral commodities whose production is concentrated in a few countries. New research identifies the commodities whose supply disruption poses the greatest risk to the manufacturing sector. While the analysis is applied to the U.S. manufacturing sector, the principles are equally applicable to other economies heavily reliant on imported mineral materials.","language":"English","publisher":"The Science Breaker","doi":"10.25250/thescbr.brk421","usgsCitation":"Nassar, N., and Fortier, S.M., 2020, U.S. mineral supply chain security in the age of pandemics and trade wars: The Science Breaker, HTML Document, https://doi.org/10.25250/thescbr.brk421.","productDescription":"HTML Document","ipdsId":"IP-118370","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":454764,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.25250/thescbr.brk421","text":"Publisher Index Page"},{"id":380983,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nassar, Nedal 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":196630,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":806065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fortier, Steven M. 0000-0001-8123-5749","orcid":"https://orcid.org/0000-0001-8123-5749","contributorId":202406,"corporation":false,"usgs":true,"family":"Fortier","given":"Steven","email":"","middleInitial":"M.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":806066,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227148,"text":"70227148 - 2020 - Linking mosquito surveillance to dengue fever through Bayesian mechanistic modeling","interactions":[],"lastModifiedDate":"2022-01-03T15:52:27.699945","indexId":"70227148","displayToPublicDate":"2020-11-23T09:25:28","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5023,"text":"PLoS Neglected Tropical Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Linking mosquito surveillance to dengue fever through Bayesian mechanistic modeling","docAbstract":"Our ability to effectively prevent the transmission of the dengue virus through targeted control of its vector, Aedes aegypti, depends critically on our understanding of the link between mosquito abundance and human disease risk. Mosquito and clinical surveillance data are widely collected, but linking them requires a modeling framework that accounts for the complex non-linear mechanisms involved in transmission. Most critical are the bottleneck in transmission imposed by mosquito lifespan relative to the virus’ extrinsic incubation period, and the dynamics of human immunity. We developed a differential equation model of dengue transmission and embedded it in a Bayesian hierarchical framework that allowed us to estimate latent time series of mosquito demographic rates from mosquito trap counts and dengue case reports from the city of Vitória, Brazil. We used the fitted model to explore how the timing of a pulse of adult mosquito control influences its effect on the human disease burden in the following year. We found that control was generally more effective when implemented in periods of relatively low mosquito mortality (when mosquito abundance was also generally low). In particular, control implemented in early September (week 34 of the year) produced the largest reduction in predicted human case reports over the following year. This highlights the potential long-term utility of broad, off-peak-season mosquito control in addition to existing, locally targeted within-season efforts. Further, uncertainty in the effectiveness of control interventions was driven largely by posterior variation in the average mosquito mortality rate (closely tied to total mosquito abundance) with lower mosquito mortality generating systems more vulnerable to control. Broadly, these correlations suggest that mosquito control is most effective in situations in which transmission is already limited by mosquito abundance.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pntd.0008868","usgsCitation":"Leach, C.B., Hoeting, J., Pepin, K.M., Eiras, A.E., Hooten, M., and Colleen T. Webb, C., 2020, Linking mosquito surveillance to dengue fever through Bayesian mechanistic modeling: PLoS Neglected Tropical Diseases, v. 14, no. 11, p. 1-20, https://doi.org/10.1371/journal.pntd.0008868.","productDescription":"e0008868, 20 p.","startPage":"1","endPage":"20","ipdsId":"IP-107662","costCenters":[{"id":189,"text":"Colorado Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":454766,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pntd.0008868","text":"Publisher Index Page"},{"id":393742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","state":"Espírito Santo","city":"Vitória","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -40.42968749999999,\n -20.43473423110048\n ],\n [\n -40.222320556640625,\n -20.43473423110048\n ],\n [\n -40.222320556640625,\n -20.17456745043183\n ],\n [\n -40.42968749999999,\n -20.17456745043183\n ],\n [\n -40.42968749999999,\n -20.43473423110048\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Leach, Clinton B.","contributorId":270703,"corporation":false,"usgs":false,"family":"Leach","given":"Clinton","email":"","middleInitial":"B.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":829794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoeting, Jennifer A.","contributorId":270704,"corporation":false,"usgs":false,"family":"Hoeting","given":"Jennifer A.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":829795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pepin, Kim M.","contributorId":270705,"corporation":false,"usgs":false,"family":"Pepin","given":"Kim","email":"","middleInitial":"M.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":829796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eiras, Alvaro E.","contributorId":270706,"corporation":false,"usgs":false,"family":"Eiras","given":"Alvaro","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":829797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":829793,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Colleen T. Webb, Colleen T.","contributorId":270707,"corporation":false,"usgs":false,"family":"Colleen T. Webb","given":"Colleen T.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":829798,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70226612,"text":"70226612 - 2020 - Evaluation of Arctic warming in mid-Pliocene climate simulations","interactions":[],"lastModifiedDate":"2021-12-01T13:03:35.899178","indexId":"70226612","displayToPublicDate":"2020-11-23T06:57:23","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of Arctic warming in mid-Pliocene climate simulations","docAbstract":"Palaeoclimate simulations improve our understanding of the climate, inform us about the performance of climate models in a different climate scenario, and help to identify robust features of the climate system. Here, we analyse Arctic warming in an ensemble of 16 simulations of the mid-Pliocene Warm Period (mPWP), derived from the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2).
The PlioMIP2 ensemble simulates Arctic (60–90∘ N) annual mean surface air temperature (SAT) increases of 3.7 to 11.6 ∘C compared to the pre-industrial period, with a multi-model mean (MMM) increase of 7.2 ∘C. The Arctic warming amplification ratio relative to global SAT anomalies in the ensemble ranges from 1.8 to 3.1 (MMM is 2.3). Sea ice extent anomalies range from −3.0 to -10.4×106\">−10.4×106 km2, with a MMM anomaly of -5.6×106\">−5.6×106 km2, which constitutes a decrease of 53 % compared to the pre-industrial period. The majority (11 out of 16) of models simulate summer sea-ice-free conditions (≤1×106\">≤1×106 km2) in their mPWP simulation. The ensemble tends to underestimate SAT in the Arctic when compared to available reconstructions, although the degree of underestimation varies strongly between the simulations. The simulations with the highest Arctic SAT anomalies tend to match the proxy dataset in its current form better. The ensemble shows some agreement with reconstructions of sea ice, particularly with regard to seasonal sea ice. Large uncertainties limit the confidence that can be placed in the findings and the compatibility of the different proxy datasets. We show that while reducing uncertainties in the reconstructions could decrease the SAT data–model discord substantially, further improvements are likely to be found in enhanced boundary conditions or model physics. Lastly, we compare the Arctic warming in the mPWP to projections of future Arctic warming and find that the PlioMIP2 ensemble simulates greater Arctic amplification than CMIP5 future climate simulations and an increase instead of a decrease in Atlantic Meridional Overturning Circulation (AMOC) strength compared to pre-industrial period. The results highlight the importance of slow feedbacks in equilibrium climate simulations, and that caution must be taken when using simulations of the mPWP as an analogue for future climate change.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/cp-16-2325-2020","usgsCitation":"de Nooijer, W., Zhang, Q., Li, Q., Zhang, Q., Li, X., Zhang, Z., Guo, C., Nisancioglu, K.H., Haywood, A.M., Tindall, J.C., Dowsett, H.J., Stepanek, C., Lohman, G., Otto-Bliesner, B.L., Feng, R., Sohl, L., Chandler, M., Tan, N., Contoux, C., Ramstein, G., Baatsen, M., von der Heydt, A.S., Chandan, D., Peltier, W.R., Abe-Ouchi, A., Chan, W., Kamae, Y., and Brierley, C.M., 2020, Evaluation of Arctic warming in mid-Pliocene climate simulations: Climate of the Past, v. 16, no. 6, p. 2325-2341, https://doi.org/10.5194/cp-16-2325-2020.","productDescription":"17 p.","startPage":"2325","endPage":"2341","ipdsId":"IP-123682","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":454772,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-16-2325-2020","text":"Publisher Index 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Zhongshi","contributorId":269576,"corporation":false,"usgs":false,"family":"Zhang","given":"Zhongshi","email":"","affiliations":[{"id":55988,"text":"Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":827465,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Guo, Chuncheng","contributorId":269577,"corporation":false,"usgs":false,"family":"Guo","given":"Chuncheng","email":"","affiliations":[{"id":55989,"text":"NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research, Bergen, Norway","active":true,"usgs":false}],"preferred":false,"id":827466,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nisancioglu, Kerim H","contributorId":269578,"corporation":false,"usgs":false,"family":"Nisancioglu","given":"Kerim","email":"","middleInitial":"H","affiliations":[{"id":55989,"text":"NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research, Bergen, 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,{"id":70216491,"text":"70216491 - 2020 - Development of a novel framework for modeling field-scale conservation effects of depressional wetlands in agricultural landscapes","interactions":[],"lastModifiedDate":"2020-11-23T13:47:37.113837","indexId":"70216491","displayToPublicDate":"2020-11-20T07:46:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2456,"text":"Journal of Soil and Water Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Development of a novel framework for modeling field-scale conservation effects of depressional wetlands in agricultural landscapes","docAbstract":"The intermixed cropland, grassland, and wetland ecosystems of the upper mid-western United States combine to provide a suite of valuable ecological services. Grassland and wetland losses in the upper midwestern United States have been extensive, but government-funded conservation programs have protected and restored hundreds of thousands of acres of wetland and grassland habitat in the region. The value of restored wetlands in agricultural fields is complex, and the USDA Natural Resource Conservation Service, Conservation Effects Assessment Project (CEAP) has been lacking the methodology to include these conservation practices in their analyses. Our aim is to develop a reproducible methodology for simulating wetlands within the CEAP cropland modeling framework used to evaluate other agricultural conservation practices. Furthermore, we evaluate the effect of using upland conservation practices on the functioning of restored wetlands. By simulating the addition of a depressional wetland that effectively removes 6% of the field from crop production, we obtained a 15% reduction in annual runoff and a 29% and 28% reduction in mean annual nitrogen (N) and phosphorus (P) losses, respectively. The presence of the depressional wetland in the field is estimated to also reduce edge-of-field losses of sediments by 20% and sediment-bound N and P by 19% and 23%, respectively. Additionally, adding a grass filter strip around the wetland greatly decreased sediment inputs to the wetland, increasing the effective life of the wetland, in terms of its ability to perform valued services, by decades to centuries. Our method for modeling depressional wetlands embedded in cropped fields provides a means to quantify the effects of wetland conservation practices on field-level losses for regional assessments, such as the CEAP.
Geysers are rare geologic features that intermittently discharge liquid water and steam driven by heating and decompression boiling. The cause of variability in eruptive styles and the associated seismic signals are not well understood. Data collected from five broadband seismometers at Lone Star Geyser, Yellowstone National Park are used to determine the properties, location, and temporal patterns of hydrothermal tremor. The tremor is harmonic at some stages of the eruption cycle and is caused by near‐periodic repetition of discrete seismic events. Using the polarization of ground motion, we identify the location of tremor sources throughout several eruption cycles. During preplay episodes (smaller eruptions preceding the more vigorous major eruption), tremor occurs at depths of 7–10 m and is laterally offset from the geyser's cone by ~5 m. At the onset of the main eruption, tremor sources migrate laterally and become shallower. As the eruption progresses, tremor sources migrate along the same path but in the opposite direction, ending where preplay tremor originates. The upward and then downward migration of tremor sources during eruptions are consistent with warming of the conduit followed by evacuation of water during the main eruption. We identify systematic relations among the two types of preplays, discharge, and the main eruption. A point‐source moment tensor fit to low‐frequency waveforms of an individual tremor event using half‐space velocity models indicates average VS ≳ 0.8 km/s, source depths ~4–20 m, and moment tensors with primarily positive isotropic and compensated linear vector dipole moments.
We show that seismic attenuation ( ![\"urn:x-wiley:00948276:media:grl61586:grl61586-math-0001\"](\"https://agupubs.onlinelibrary.wiley.com/cms/asset/fe6e1bba-0f11-4326-9d90-0344d44a07b8/grl61586-math-0001.png\")
) along the San Andreas fault (SAF) at Parkfield correlates with the occurrence of moderate‐to‐large earthquakes at local and regional distances. Earthquake‐related ![\"urn:x-wiley:00948276:media:grl61586:grl61586-math-0002\"](\"https://agupubs.onlinelibrary.wiley.com/cms/asset/a89f08da-3eff-4c9e-95a4-b39accaeac3b/grl61586-math-0002.png\")
anomalies are likely caused by changes in permeability from dilatant static stress changes, damage by strong shaking from local sources, and pore unclogging/clogging from mobilization of colloids by dynamic strains. We find that, prior to the 2004 M6 Parkfield earthquake, prefailure conditions for some local events of moderate magnitude correspond to positive anomalies of ![\"urn:x-wiley:00948276:media:grl61586:grl61586-math-0003\"](\"https://agupubs.onlinelibrary.wiley.com/cms/asset/999ff49d-0c63-413d-a3d3-7163e4f59927/grl61586-math-0003.png\")
on the Pacific side, with local and regional earthquakes producing sharp attenuation reversals. After the 2004 Parkfield earthquake, we see higher ![\"urn:x-wiley:00948276:media:grl61586:grl61586-math-0004\"](\"https://agupubs.onlinelibrary.wiley.com/cms/asset/4d674cda-5354-4c8d-a1a4-54b743103370/grl61586-math-0004.png\")
anomalies along the SAF, but low sensitivity to local and regional earthquakes, probably because the mainshock significantly altered the permeability state of the rocks adjacent to the SAF, and its sensitivity to earthquake‐induced stress perturbations.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL089201","usgsCitation":"Malagnini, L., and Parsons, T.E., 2020, Seismic attenuation monitoring of a critically stressed San Andreas fault: Geophysical Research Letters, v. 47, no. 23, 11 p., https://doi.org/10.1029/2020GL089201.","productDescription":"11 p.","ipdsId":"IP-117715","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":380869,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Andreas Fault-Parkfield Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.72302246093749,\n 35.646137228802424\n ],\n [\n -120.64361572265624,\n 35.646137228802424\n ],\n [\n -120.64361572265624,\n 36.61332303966068\n ],\n [\n -121.72302246093749,\n 36.61332303966068\n ],\n [\n -121.72302246093749,\n 35.646137228802424\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"23","noUsgsAuthors":false,"publicationDate":"2020-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Malagnini, Luca 0000-0001-5809-9945","orcid":"https://orcid.org/0000-0001-5809-9945","contributorId":245308,"corporation":false,"usgs":false,"family":"Malagnini","given":"Luca","email":"","affiliations":[{"id":5113,"text":"INGV","active":true,"usgs":false}],"preferred":false,"id":805881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805882,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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