Aims
Understanding the conditions associated with dryland vegetation recovery after restoration treatments is challenging due to a lack of monitoring data and high environmental variability over time and space. Tracking recovery trajectories with satellite‐based vegetation indices can strengthen predictions of restoration outcomes across broad areas with varying environmental conditions.
Location
Southwestern United States.
Methods
We quantified the recovery trajectories of spring and summer soil‐adjusted total vegetation index (SATVI) for 5 to 10 year periods following post‐wildfire seeding or prescribed burns for 241 treatment sites, and related SATVI to ground‐based vegetation cover. We modeled SATVI based on time since treatment, yearly temperature and precipitation, weather extremes following treatment, soil available water capacity, invasive species presence, and treatment type. We also tested for the effects of environmental variables on trajectories, by examining interactions with years post‐treatment.
Results
Ground‐based vegetation cover and SATVI were highly correlated. Most treatment sites had positive recovery rates for spring (82%) and summer (85%) SATVI. Several environmental variables affected vegetation recovery trajectories as indicated by interactions with time since treatment. Yearly warm season precipitation had a positive effect on SATVI recovery that increased over time, whereas the positive effect of extreme high warm season precipitation following treatment decreased over time for both seasons of vegetation measurements. For spring SATVI, the positive effect of cool season yearly precipitation increased over time while the negative effect of extreme high temperatures following treatment became more negative over time. Invasive species presence led to higher spring, but not summer, SATVI.
Conclusions
Satellite‐based remote sensing is a promising tool to assess vegetation recovery following restoration treatments, particularly when it is combined with ground‐based monitoring. Our results suggest that weather extremes following restoration treatments can affect vegetation recovery trajectories and should be considered in decisions such as the timing of restoration treatments.
Early ocean survival of Chinook salmon, Oncorhynchus tshawytscha, varies greatly inter-annually and may be the period during which later spawning abundance and fishery recruitment are set. Therefore, identifying environmental drivers related to early survival may inform better models for management and sustainability of salmon in a variable environment. With this in mind, our main objectives were to (a) identify regions of high temporal variability in growth potential over a 23-year time series, (b) determine whether the spatial distribution of growth potential was correlated with observed oceanographic conditions, and (c) determine whether these spatial patterns in growth potential could be used to estimate juvenile salmon survival. We applied this method to the fall run of the Central Valley Chinook salmon population, focusing on the spring and summer period after emigration into central California coastal waters. For the period from 1988 to 2010, juvenile salmon growth potential on the central California continental shelf was described by three spatial patterns. These three patterns were most correlated with upwelling, detrended sea level anomalies, and the strength of onshore/offshore currents, respectively. Using the annual strength of these three patterns, as well as the overall growth potential throughout central California coastal waters, in a generalized linear model we explained 82% of the variation in juvenile salmon survival estimates. We attributed the relationship between growth potential and survival to variability in environmental conditions experienced by juvenile salmon during their first year at sea, as well as potential shifts in predation pressure following out-migration into coastal waters.
Jupiter's Moon Europa has one of the youngest geological surfaces in our solar system with an age of 40–90 Ma, implying an intense history of resurfacing. The surface of Europa indeed shows abundant evidence of tectonic deformation related to extension, strike-slip, and shortening. However, observed features related to shortening are scarce compared with pervasive extensive extensional features such as dilational bands, and do not suffice as the sole mechanism for recycling aging terranes. Recently, evidence for potential plate tectonics, associated with subduction zones, has been discovered on Europa; this could be responsible for recycling most of Europa's surface. However, basic physical parameters needed to initiate subduction on Europa, such as thickness of the brittle layer, deformation rates, and orientation of pre-existing zones of weakness at which subduction could start, are not well understood. Here, we aim to better understand the process and the conditions that could lead to initiation of subduction on Europa through physical experiments, using wax to simulate Europa's two-layered (i.e. convective) icy crust. By deforming the wax, strain on Europa's surface—possibly caused by diurnal tides or its nonsynchronous rotation—is simulated. Our results indicate that subduction could initiate over a broad range of surface thicknesses and deformation rates above a minimum conductive layer thickness, but is strongly dependent on the orientation of the pre-existing zones of weakness. Very thin conductive layer experiments, however, result in a previously undescribed process that we term ductile rolldown, which creates surface features similar to double ridges observed on Europa. Thus, subduction and ductile rolldown represent physically plausible mechanisms that could play a critical role in resurfacing Europa throughout its geologic history. These results could yield significant implications for Europa's thermal history and evolution, habitability, and future spacecraft missions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2018.11.005","usgsCitation":"Klasner, M.W., Gross, J., Tindall, S., Schlishe, R.W., and Potter, C.J., 2019, Europa’s ice tectonics: New insights from physical wax experiments with implications for subduction initiation and global resurfacing processes: Icarus, v. 321, p. 593-607, https://doi.org/10.1016/j.icarus.2018.11.005.","productDescription":"15 p.","startPage":"593","endPage":"607","ipdsId":"IP-098567","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":420904,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Europa, Jupiter","volume":"321","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Klasner, Michael W","contributorId":329765,"corporation":false,"usgs":false,"family":"Klasner","given":"Michael","email":"","middleInitial":"W","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":883238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gross, Juliane 0000-0002-5288-0981","orcid":"https://orcid.org/0000-0002-5288-0981","contributorId":223401,"corporation":false,"usgs":false,"family":"Gross","given":"Juliane","email":"","affiliations":[{"id":40711,"text":"Rutgers State University of New Jersey","active":true,"usgs":false}],"preferred":false,"id":883239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tindall, Sarah","contributorId":329766,"corporation":false,"usgs":false,"family":"Tindall","given":"Sarah","email":"","affiliations":[{"id":78714,"text":"Kutztown University","active":true,"usgs":false}],"preferred":false,"id":883240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schlishe, Roy W.","contributorId":329767,"corporation":false,"usgs":false,"family":"Schlishe","given":"Roy","email":"","middleInitial":"W.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":883241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Potter, Christopher J. 0000-0002-2300-6670 cpotter@usgs.gov","orcid":"https://orcid.org/0000-0002-2300-6670","contributorId":1026,"corporation":false,"usgs":true,"family":"Potter","given":"Christopher","email":"cpotter@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":883242,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70207166,"text":"70207166 - 2019 - Interannual snow accumulation variability on glaciers derived from repeat spatially extensive ground-penetrating radar surveys","interactions":[],"lastModifiedDate":"2019-12-11T08:06:31","indexId":"70207166","displayToPublicDate":"2018-11-22T07:51:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3554,"text":"The Cryosphere","active":true,"publicationSubtype":{"id":10}},"title":"Interannual snow accumulation variability on glaciers derived from repeat spatially extensive ground-penetrating radar surveys","docAbstract":"There is significant uncertainty regarding the spatiotemporal distribution of seasonal snow on glaciers, despite being a fundamental component of glacier mass balance. To address this knowledge gap, we collected repeat, spatially extensive high-frequency ground-penetrating radar (GPR) observations on two glaciers in Alaska for five consecutive years. GPR measurements showed steep snow water equivalent (SWE) elevation gradients at both sites; continental Gulkana Glacier’s SWE gradient averaged 115 mm 100 m–1 and maritime Wolverine Glacier’s gradient averaged 440 mm 100 m–1 (over >1000 m). We extrapolated GPR point observations across the glacier surface using terrain parameters derived from digital elevation models as predictor variables in two statistical models (stepwise multivariable linear regression and regression trees). Elevation and proxies for wind redistribution had the greatest explanatory power, and exhibited relatively time-constant coefficients over the study period. Both statistical models yielded comparable estimates of glacier-wide average SWE (1 % average difference at Gulkana, 4 % average difference at Wolverine), although the spatial distributions produced by the models diverged in unsampled regions of the glacier, particularly at Wolverine. In total, six different methods for estimating the glacier-wide average agreed within ± 11 %. We assessed interannual variability in the spatial pattern of snow accumulation predicted by the statistical models using two quantitative metrics. Both glaciers exhibited a high degree of temporal stability, with ~85 % of the glacier area experiencing less than 25 % normalized absolute variability over this five-year interval. We found SWE at a sparse network (3 stakes per glacier) of long-term glaciological stake sites to be highly correlated with the GPR-derived glacier-wide average. We estimate that interannual variability in the spatial pattern of SWE is only a small component (4–10 % of glacier-wide average) of the total mass balance uncertainty and thus, our findings support the concept that sparse stake networks effectively measure interannual variability in winter balance on glaciers, rather than some spatially varying pattern of snow accumulation.","language":"English","publisher":"Copernicus Publications","doi":"10.5194/tc-12-3617-2018","usgsCitation":"McGrath, D.J., Sass, L., O’Neel, S., McNeil, C., Candela, S.G., Baker, E., and Marshall, H.P., 2019, Interannual snow accumulation variability on glaciers derived from repeat spatially extensive ground-penetrating radar surveys: The Cryosphere, v. 12, p. 3617-3633, https://doi.org/10.5194/tc-12-3617-2018.","productDescription":"17 p.","startPage":"3617","endPage":"3633","ipdsId":"IP-098923","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":468053,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/tc-12-3617-2018","text":"Publisher Index Page"},{"id":370143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.80859375,\n 58.21702494960191\n ],\n [\n -140.888671875,\n 58.21702494960191\n ],\n [\n -140.888671875,\n 64.28275952823394\n ],\n [\n -153.80859375,\n 64.28275952823394\n ],\n [\n -153.80859375,\n 58.21702494960191\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"McGrath, Daniel J 0000-0002-9462-6842","orcid":"https://orcid.org/0000-0002-9462-6842","contributorId":221142,"corporation":false,"usgs":false,"family":"McGrath","given":"Daniel","email":"","middleInitial":"J","affiliations":[{"id":40333,"text":"Department of Geosciences, Colorado State University, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":777116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sass, Louis 0000-0003-4677-029X lsass@usgs.gov","orcid":"https://orcid.org/0000-0003-4677-029X","contributorId":221141,"corporation":false,"usgs":true,"family":"Sass","given":"Louis","email":"lsass@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":777115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Neel, Shad 0000-0002-9185-0144 soneel@usgs.gov","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":166740,"corporation":false,"usgs":true,"family":"O’Neel","given":"Shad","email":"soneel@usgs.gov","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":777117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNeil, Christopher J. 0000-0003-4170-0428 cmcneil@usgs.gov","orcid":"https://orcid.org/0000-0003-4170-0428","contributorId":5803,"corporation":false,"usgs":true,"family":"McNeil","given":"Christopher J.","email":"cmcneil@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":777118,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Candela, Salvatore G 0000-0002-1605-4463","orcid":"https://orcid.org/0000-0002-1605-4463","contributorId":221143,"corporation":false,"usgs":false,"family":"Candela","given":"Salvatore","email":"","middleInitial":"G","affiliations":[{"id":40334,"text":"School of Earth Sciences and Byrd Polar Research Center, Ohio State University, Columbus, OH","active":true,"usgs":false}],"preferred":false,"id":777119,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baker, Emily 0000-0002-0938-3496 ehbaker@usgs.gov","orcid":"https://orcid.org/0000-0002-0938-3496","contributorId":200570,"corporation":false,"usgs":true,"family":"Baker","given":"Emily","email":"ehbaker@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":777120,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Marshall, Hans P.","contributorId":172745,"corporation":false,"usgs":false,"family":"Marshall","given":"Hans","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":777121,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202166,"text":"70202166 - 2019 - Uncertainty in quantitative analyses of topographic change: Error propagation and the role of thresholding","interactions":[],"lastModifiedDate":"2019-06-18T08:59:22","indexId":"70202166","displayToPublicDate":"2018-11-21T13:07:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainty in quantitative analyses of topographic change: Error propagation and the role of thresholding","docAbstract":"Topographic surveys inevitably contain error, introducing uncertainty into estimates of volumetric or mean change based on the differencing of repeated surveys. In the geomorphic community, uncertainty has often been framed as a problem of separating out real change from apparent change due purely to error, and addressed by removing measured change considered indistinguishable from random noise from analyses (thresholding). Thresholding is important when quantifying gross changes (i.e. total erosion or total deposition), which are systematically biased by random errors in stable parts of a landscape. However, net change estimates are not substantially influenced by those same random errors, and the use of thresholds results in inherently biased, and potentially misleading, estimates of net change and uncertainty. More generally, thresholding is unrelated to the important process of propagating uncertainty in order to place uncertainty bounds around final estimates. Error propagation methods for uncorrelated, correlated, and systematic errors are presented. Those equations demonstrate that uncertainties in modern net change analyses, as well as in gross change analyses using reasonable thresholds, are likely to be dominated by low‐magnitude but highly correlated or systematic errors, even after careful attempts to reduce those errors. In contrast, random errors with little to no correlation largely cancel to negligible levels when averaged or summed. Propagated uncertainty is then typically insensitive to the precision of individual measurements, and is instead defined by the relative mean error (accuracy) over the area of interest. Given that real‐world mean elevation changes in many landscape settings are often similar in magnitude to potential mean errors in repeat topographic analyses, reducing highly correlated or systematic errors will be central to obtaining accurate change estimates, while placing uncertainty bounds around those results provides essential context for their interpretation.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.4551","usgsCitation":"Anderson, S.W., 2019, Uncertainty in quantitative analyses of topographic change: Error propagation and the role of thresholding: Earth Surface Processes and Landforms, v. 44, no. 5, p. 1015-1033, https://doi.org/10.1002/esp.4551.","productDescription":"19 p.","startPage":"1015","endPage":"1033","ipdsId":"IP-097288","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":361175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":196687,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757062,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70200978,"text":"70200978 - 2019 - Distance models as a tool for modelling detection probability and density of native bumblebees","interactions":[],"lastModifiedDate":"2019-03-15T12:42:58","indexId":"70200978","displayToPublicDate":"2018-11-20T10:58:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5782,"text":"Journal of Applied Entomology","active":true,"publicationSubtype":{"id":10}},"title":"Distance models as a tool for modelling detection probability and density of native bumblebees","docAbstract":"Effective monitoring of native bee populations requires accurate estimates of population size and relative abundance among habitats. Current bee survey methods, such as netting or pan trapping, may be adequate for a variety of study objectives but are limited by a failure to account for imperfect detection. Biases due to imperfect detection could result in inaccurate abundance estimates or erroneous insights about the response of bees to different environments. To gauge the potential biases of currently employed survey methods, we compared abundance estimates of bumblebees (Bombus spp.) derived from hierarchical distance sampling models (HDS) to bumblebee counts collected from fixed‐area net surveys (“net counts”) and fixed‐width transect counts (“transect counts”) at 47 early‐successional forest patches in Pennsylvania. Our HDS models indicated that detection probabilities of Bombus spp. were imperfect and varied with survey‐ and site‐covariates. Despite being conspicuous, Bombus spp. were not reliably detected beyond 5 m. Habitat associations of Bombus spp. density were similar across methods, but the strength of association with shrub cover differed between HDS and net counts. Additionally, net counts suggested sites with more grass hosted higher Bombusspp. densities whereas HDS suggested that grass cover was associated with higher detection probability but not Bombus spp. density. Density estimates generated from net counts and transect counts were 80%–89% lower than estimates generated from distance sampling. Our findings suggest that distance modelling provides a reliable method to assess Bombus spp. density and habitat associations, while accounting for imperfect detection caused by distance from observer, vegetation structure, and survey covariates. However, detection/non‐detection data collected via point‐counts, line‐transects and distance sampling for Bombus spp. are unlikely to yield species‐specific density estimates unless individuals can be identified by sight, without capture. Our results will be useful for informing the design of monitoring programs for Bombus spp.and other pollinators.
","language":"English","publisher":"Wiley","doi":"10.1111/jen.12583","usgsCitation":"McNeil, D.J., Otto, C., Moser, E.L., Urban-Mead, K.R., King, D.E., Rodewald, A.D., and Larkin, J.L., 2019, Distance models as a tool for modelling detection probability and density of native bumblebees: Journal of Applied Entomology, v. 143, no. 3, p. 225-235, https://doi.org/10.1111/jen.12583.","productDescription":"11 p.","startPage":"225","endPage":"235","ipdsId":"IP-096861","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":359602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Centre County, Clinton County","otherGeospatial":"Pennsylvania 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Jr.","contributorId":37620,"corporation":false,"usgs":false,"family":"McNeil","given":"Darin","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":751537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":751536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moser, Erin L.","contributorId":210723,"corporation":false,"usgs":false,"family":"Moser","given":"Erin","email":"","middleInitial":"L.","affiliations":[{"id":38138,"text":"Indiana University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":751538,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Urban-Mead, Katherine R.","contributorId":210724,"corporation":false,"usgs":false,"family":"Urban-Mead","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":38139,"text":"Department of Entomology, Cornell University, Ithaca, NY 14850, US","active":true,"usgs":false}],"preferred":false,"id":751539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"King, David E.","contributorId":210754,"corporation":false,"usgs":false,"family":"King","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":751540,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rodewald, Amanda D.","contributorId":169748,"corporation":false,"usgs":false,"family":"Rodewald","given":"Amanda","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":751541,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Larkin, Jeffrey L.","contributorId":169747,"corporation":false,"usgs":false,"family":"Larkin","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[{"id":34542,"text":"Department of Biology. Indiana University of Pennsylvania","active":true,"usgs":false},{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false}],"preferred":false,"id":751542,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202862,"text":"70202862 - 2019 - Keeping the crown of the continent connected: An interagency US2 connectivity workshop report","interactions":[],"lastModifiedDate":"2019-04-17T10:20:15","indexId":"70202862","displayToPublicDate":"2018-11-20T10:19:53","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Keeping the crown of the continent connected: An interagency US2 connectivity workshop report","docAbstract":"At over 2.5 million acres, Glacier National Park and the Bob Marshall Wilderness complex form one of the largest protected areas in the continental United States. Straddling the Continental Divide, these two areas form a vital linkage between vast areas of public land to the south towards Yellowstone, and contiguous protected areas north of the US-Canada border. However, US Highway 2 (US2) and the Burlington Northern-Santa Fe (BNSF) railroad separate Glacier National Park to the north from the Bob Marshall Wilderness complex to the south. While this narrow ribbon of development passes through primarily public land, it is bordered in some areas by narrow strips of private land. Many of these private parcels are developed as ranches, campgrounds, or seasonal and permanent home sites and businesses.
Currently, two of the defining characteristics of this portion of the US2 corridor are relatively low highway traffic volume, but relatively high railroad traffic volume. The highway had a 2017 annual average daily traffic volume (AADT) of 1859 vehicles, far less than other interstate highways around the region which often have AADTs well over 10,000. Conversely, the BNSF railroad line currently carries about 33 trains per day, making it one of the busier railroad lines in the northwestern US.
While wildlife movement patterns across this corridor have not been well studied, the existing data suggests that wildlife can still make frequent and successful crossings at current railroad and highway traffic levels. However, as the region’s human population grows, we expect that connectivity to diminish. Over the past decade (2000-2017), based on census data, Flathead County has grown by 10% and Glacier County has grown by 1.5%. A study on loss of open space found that Flathead County alone accounts for 15% of the new homes built in Montana since 2000 (https://headwaterseconomics.org/economicdevelopment/local-studies/montana-home construction/). Outdoor recreation and tourism have also been breaking participation records (source: GPI record passengers https://flatheadbeacon.com/2018/01/24/glacier-park-international-airport-sees-record-passengers-2017/, GNP record visitation https://www.usnews.com/news/best-states/montana/articles/2018-01 15/glaciernational-park-breaks-visitation-record-in-2017). This growth has been accompanied by a ~50% increase in highway traffic volume in the corridor over the past decade (Waller and Miller 2015). This increased traffic is decreasing the time available for wildlife to cross the highway and appears to be increasing the frequency of wildlife killed by vehicles (Fig. 1 and 2).
In addition, the Middle Fork of the Flathead River is a favored river for recreation, and this also appears to be growing. In the summer of 2017, researchers recorded 136 boats per day in July and 93 boats per day in August. Although the river does not extend along the entire highway, it extends along 31 miles of the highway corridor.
Accurate and precise analyses of oil and gas (O&G) wastewaters and solids (e.g., sediments and sludge) are important for the regulatory monitoring of O&G development and tracing potential O&G contamination in the environment. In this study, 15 laboratories participated in an inter-laboratory comparison on the chemical characterization of three O&G wastewaters from the Appalachian Basin and four solids impacted by O&G development, with the goal of evaluating the quality of data and the accuracy of measurements for various analytes of concern. Using a variety of different methods, analytes in the wastewaters with high concentrations (i.e., >5 mg L−1) were easily detectable with relatively high accuracy, often within ±10% of the most probable value (MPV). In contrast, often less than 7 of the 15 labs were able to report detectable trace metal(loid) concentrations (i.e., Cr, Ni, Cu, Zn, As, and Pb) with accuracies of approximately ±40%. Despite most labs using inductively coupled plasma mass spectrometry (ICP-MS) with low instrument detection capabilities for trace metal analyses, large dilution factors during sample preparation and low trace metal concentrations in the wastewaters limited the number of quantifiable determinations and likely influenced analytical accuracy. In contrast, all the labs measuring Ra in the wastewaters were able to report detectable concentrations using a variety of methods including gamma spectroscopy and wet chemical approaches following Environmental Protection Agency (EPA) standard methods. However, the reported radium activities were often greater than ±30% different to the MPV possibly due to calibration inconsistencies among labs, radon leakage, or failing to correct for self-attenuation. Reported radium activities in solid materials had less variability (±20% from MPV) but accuracy could likely be improved by using certified radium standards and accounting for self-attenuation that results from matrix interferences or a density difference between the calibration standard and the unknown sample. This inter-laboratory comparison illustrates that numerous methods can be used to measure major cation, minor cation, and anion concentrations in O&G wastewaters with relatively high accuracy while trace metal(loid) and radioactivity analyses in liquids may often be over ±20% different from the MPV.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/c8em00359a","usgsCitation":"Tasker, T.L., Burgos, W.D., Ajemigbitse, M.A., Lauer, N.E., Gusa, A.V., Kuatbek, M., May, D., Landis, J.D., Alessi, D.S., Johnsen, A.M., Kaste, J.M., Headrick, K., Wilke, F.D., McNeal, M., Engle, M.A., Jubb, A., Vidic, R., Vengosh, A., and Warner, N.R., 2019, Accuracy of methods for reporting inorganic element concentrations and radioactivity in oil and gas wastewaters from the Appalachian Basin, U.S. based on an inter-laboratory comparison.: Environmental Science: Processes and Impacts, v. 21, no. 2, p. 224-241, https://doi.org/10.1039/c8em00359a.","productDescription":"18 p.","startPage":"224","endPage":"241","ipdsId":"IP-100644","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":365078,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Pittsburg","active":true,"usgs":false}],"preferred":false,"id":765150,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Vengosh, Avner","contributorId":208460,"corporation":false,"usgs":false,"family":"Vengosh","given":"Avner","email":"","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":765151,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Warner, Nathaniel R.","contributorId":211458,"corporation":false,"usgs":false,"family":"Warner","given":"Nathaniel","email":"","middleInitial":"R.","affiliations":[{"id":38248,"text":"Civil and Environmental Engineering Department, The Pennsylvania State University,","active":true,"usgs":false}],"preferred":false,"id":765152,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70216090,"text":"70216090 - 2019 - New approach to assessing age uncertainties – The 2300-year varve chronology from Eklutna Lake, Alaska (USA)","interactions":[],"lastModifiedDate":"2023-11-08T14:28:34.652988","indexId":"70216090","displayToPublicDate":"2018-11-19T10:49:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"New approach to assessing age uncertainties – The 2300-year varve chronology from Eklutna Lake, Alaska (USA)","docAbstract":"Developing robust chronological frameworks of lacustrine sediment is central to reconstructing past environmental changes. We present varve chronologies from five sites extending back 2300 years from Eklutna Lake, in the Chugach Mountains of south-central Alaska. The chronologies are built from image analysis of high-resolution photographs and CT scans of sediment cores. The age uncertainty of each record is tested by three methods. We first present varve chronologies from individual sites and reconcile the difference in varve delimitation from two observers. The varve chronologies from each site are then compared to each other using a series of marker beds that can be traced across the lake basin. Finally, using a new Bayesian probabilistic model, we develop age models that incorporate information regarding age uncertainty from the multiple-observer method and the age distribution of marker layers from multiple cores. To evaluate the accuracy of the Bayesian model output, we used seven radiocarbon ages from terrestrial macrofossils and four tephra layers traceable across the core sites. The major-element geochemistry of the tephra layers and their ages are presented here for the first time. The Bayesian age model offers a new approach to quantifying age uncertainty in inter-correlated cores of varved sediment.
In this chapter we present a hypothesis, and data supporting it, that vascular plants in diverse families possess symbiotic/endophytic bacteria that frequently vector on or within their seeds; seedlings degrade symbiotic bacteria within roots. Evidence of widespread microbivory was found in a survey for intracellular bacteria that we conducted including seedlings in 36 species of vascular plants distributed in 20 plant families. Experiments indicate that when seeds germinate, bacteria colonize seedlings and internalize into root cells where they are oxidatively-degraded in the periplasmic spaces of cells. The process of degradation of microbes in roots has been termed “rhizophagy”, and “rhizophagy cycle” or “rhizophagy symbiosis” in the case of symbiotic bacteria that alternate between a free-living soil phase and intracellular/endophytic phase. We hypothesize that microbivory could account for a significant portion of nutrients acquired by plants from soils—with one estimate suggesting that as much as 30% of the nutrients acquired by seedlings may stem from rhizophagy symbiosis. Developing a better understanding of rhizophagy symbiosis could lead to new ways to cultivate crops without reliance on excessive agrochemical applications. Learning how to manipulate rhizophagy symbiosis could result in new technologies for reducing growth of weedy or invasive plant species by inhibiting rhizophagy symbiosis.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"PGPR amelioration in sustainable agriculture food security and environmental management","language":"English","publisher":"Woodhead Publishing","doi":"10.1016/B978-0-12-815879-1.00009-4","usgsCitation":"White, J., Torres, M.S., Verma, S.K., Elmore, M.T., Kowalski, K., and Kingsley, K.L., 2019, Evidence for widespread microbivory of endophytic bacteria in roots of vascularplants through oxidative degradation in root cell periplasmic spaces, chap. of PGPR amelioration in sustainable agriculture food security and environmental management, p. 167-193, https://doi.org/10.1016/B978-0-12-815879-1.00009-4.","productDescription":"27 p.","startPage":"167","endPage":"193","ipdsId":"IP-094340","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":359517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5befe5b6e4b045bfcadf7f1e","contributors":{"authors":[{"text":"White, James F.","contributorId":152046,"corporation":false,"usgs":false,"family":"White","given":"James F.","affiliations":[],"preferred":false,"id":741861,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torres, Monica S.","contributorId":152047,"corporation":false,"usgs":false,"family":"Torres","given":"Monica","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":741862,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Verma, Satish Kumar","contributorId":203175,"corporation":false,"usgs":false,"family":"Verma","given":"Satish","email":"","middleInitial":"Kumar","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":741863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elmore, Matthew T.","contributorId":206820,"corporation":false,"usgs":false,"family":"Elmore","given":"Matthew","email":"","middleInitial":"T.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":741864,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":741860,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kingsley, Kathryn L.","contributorId":203176,"corporation":false,"usgs":false,"family":"Kingsley","given":"Kathryn","email":"","middleInitial":"L.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":741865,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70200930,"text":"70200930 - 2019 - Identification of conservation and restoration priority areas in the Danube River based on the multi-functionality of river-floodplain systems","interactions":[],"lastModifiedDate":"2018-11-16T10:54:17","indexId":"70200930","displayToPublicDate":"2018-11-16T10:54:13","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Identification of conservation and restoration priority areas in the Danube River based on the multi-functionality of river-floodplain systems","docAbstract":"Large river-floodplain systems are hotspots of biodiversity and ecosystem services but are also used for multiple human activities, making them one of the most threatened ecosystems worldwide. There is wide evidence that reconnecting river channels with their floodplains is an effective measure to increase their multi-functionality, i.e., ecological integrity, habitats for multiple species and the multiple functions and services of river-floodplain systems, although, the selection of promising sites for restoration projects can be a demanding task. In the case of the Danube River in Europe, planning and implementation of restoration projects is substantially hampered by the complexity and heterogeneity of the environmental problems, lack of data and strong differences in socio-economic conditions as well as inconsistencies in legislation related to river management. We take a quantitative approach based on best-available data to assess biodiversity using selected species and three ecosystem services (flood regulation, crop pollination, and recreation), focused on the navigable main stem of the Danube River and its floodplains. We spatially prioritize river-floodplain segments for conservation and restoration based on (1) multi-functionality related to biodiversity and ecosystem services, (2) availability of remaining semi-natural areas and (3) reversibility as it relates to multiple human activities (e.g. flood protection, hydropowerand navigation). Our approach can thus serve as a strategic planning tool for the Danube and provide a method for similar analyses in other large river-floodplain systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.10.322","usgsCitation":"Funk, A., Martinez-Lopez, J., Borgwardt, F., Traunder, D., Bagstad, K.J., Balbi, S., Magrach, A., Villa, F., and Hein, T., 2019, Identification of conservation and restoration priority areas in the Danube River based on the multi-functionality of river-floodplain systems: Science of the Total Environment, v. 654, p. 763-777, https://doi.org/10.1016/j.scitotenv.2018.10.322.","productDescription":"15 p.","startPage":"763","endPage":"777","ipdsId":"IP-099325","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468055,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.10.322","text":"Publisher Index Page"},{"id":359509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Austria, Bulgaria, Croatia, Germany, Hungary, Romania, Slovakia, Serbia, Ukraine","otherGeospatial":"Danube River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 10,\n 43\n ],\n [\n 32,\n 43\n ],\n [\n 32,\n 50\n ],\n [\n 10,\n 50\n ],\n [\n 10,\n 43\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"654","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5befe5b7e4b045bfcadf7f20","contributors":{"authors":[{"text":"Funk, Andrea","contributorId":210646,"corporation":false,"usgs":false,"family":"Funk","given":"Andrea","email":"","affiliations":[{"id":38121,"text":"University of Natural Resources and Life Sciences, Vienna","active":true,"usgs":false}],"preferred":false,"id":751358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martinez-Lopez, Javier 0000-0003-4857-3396","orcid":"https://orcid.org/0000-0003-4857-3396","contributorId":208480,"corporation":false,"usgs":false,"family":"Martinez-Lopez","given":"Javier","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":751359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borgwardt, Florian","contributorId":210647,"corporation":false,"usgs":false,"family":"Borgwardt","given":"Florian","email":"","affiliations":[{"id":38121,"text":"University of Natural Resources and Life Sciences, Vienna","active":true,"usgs":false}],"preferred":false,"id":751360,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Traunder, Daniel","contributorId":210648,"corporation":false,"usgs":false,"family":"Traunder","given":"Daniel","email":"","affiliations":[{"id":38121,"text":"University of Natural Resources and Life Sciences, Vienna","active":true,"usgs":false}],"preferred":false,"id":751361,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":751357,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Balbi, Stefano 0000-0001-8190-5968","orcid":"https://orcid.org/0000-0001-8190-5968","contributorId":208481,"corporation":false,"usgs":false,"family":"Balbi","given":"Stefano","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":751362,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Magrach, Ainhoa 0000-0003-2155-7556","orcid":"https://orcid.org/0000-0003-2155-7556","contributorId":208482,"corporation":false,"usgs":false,"family":"Magrach","given":"Ainhoa","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":751363,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Villa, Ferdinando 0000-0002-5114-3007","orcid":"https://orcid.org/0000-0002-5114-3007","contributorId":208486,"corporation":false,"usgs":false,"family":"Villa","given":"Ferdinando","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":751364,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hein, Thomas 0000-0002-7767-4607","orcid":"https://orcid.org/0000-0002-7767-4607","contributorId":210649,"corporation":false,"usgs":false,"family":"Hein","given":"Thomas","email":"","affiliations":[{"id":38121,"text":"University of Natural Resources and Life Sciences, Vienna","active":true,"usgs":false}],"preferred":false,"id":751365,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70228044,"text":"70228044 - 2019 - Estimating spatial–temporal differences in Chinook salmon outmigration survival with habitat- and predation-related covariates","interactions":[],"lastModifiedDate":"2022-02-03T16:07:10.658187","indexId":"70228044","displayToPublicDate":"2018-11-15T10:00:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Estimating spatial–temporal differences in Chinook salmon outmigration survival with habitat- and predation-related covariates","docAbstract":"Low survival rates of Chinook salmon (Oncorhynchus tshawytscha) smolts in California’s Central Valley have been attributed to multiple biological and physical factors, but it is not clear which factors have the largest impact. We used 5 years of acoustic telemetry data for 1709 late-fall Chinook salmon smolts to evaluate the effect of habitat- and predation-related covariates on outmigration survival through the Sacramento River. Using a Cormack–Jolly–Seber mark–recapture model, we estimated survival rates both as a function of covariates (covariate model) and as a function of river location and release year (spatial–temporal model). Our covariate model was overwhelmingly supported as the preferred model based on model selection criteria, suggesting the covariates adequately replicated spatial and temporal patterns in smolt survival. The covariates in the selected model included individual fish covariates, habitat-specific covariates, and temporally variable physical conditions. The most important covariate affecting salmon survival was flow. We describe the importance of these parameters in the context of juvenile salmon predation risk and suggest that additional research on predator distribution and density could improve model estimates.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0212","usgsCitation":"Henderson, M., Iglesias, I.S., Michel, C.J., Ammann, A.J., and Huff, D.D., 2019, Estimating spatial–temporal differences in Chinook salmon outmigration survival with habitat- and predation-related covariates: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 9, p. 1549-1561, https://doi.org/10.1139/cjfas-2018-0212.","productDescription":"13 p.","startPage":"1549","endPage":"1561","ipdsId":"IP-097049","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":501022,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/94927","text":"External Repository"},{"id":395356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.3,\n 38.70265930723801\n ],\n [\n -120.9375,\n 38.70265930723801\n ],\n [\n -120.9375,\n 40.44694705960048\n ],\n [\n -122.3,\n 40.44694705960048\n ],\n [\n -122.3,\n 38.70265930723801\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"76","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Henderson, Mark J. 0000-0002-2861-8668 mhenderson@usgs.gov","orcid":"https://orcid.org/0000-0002-2861-8668","contributorId":198609,"corporation":false,"usgs":true,"family":"Henderson","given":"Mark J.","email":"mhenderson@usgs.gov","affiliations":[],"preferred":false,"id":832954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iglesias, Ilysa S.","contributorId":274387,"corporation":false,"usgs":false,"family":"Iglesias","given":"Ilysa","email":"","middleInitial":"S.","affiliations":[{"id":56613,"text":"uc sc","active":true,"usgs":false}],"preferred":false,"id":832955,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Michel, Cyril J.","contributorId":207096,"corporation":false,"usgs":false,"family":"Michel","given":"Cyril","email":"","middleInitial":"J.","affiliations":[{"id":37452,"text":"National Marine Fisheries Service, Southwest Fisheries Science Center, 110 Shaffer Rd., Santa Cruz, CA 95060","active":true,"usgs":false}],"preferred":false,"id":832956,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ammann, Arnold J.","contributorId":207095,"corporation":false,"usgs":false,"family":"Ammann","given":"Arnold","email":"","middleInitial":"J.","affiliations":[{"id":37452,"text":"National Marine Fisheries Service, Southwest Fisheries Science Center, 110 Shaffer Rd., Santa Cruz, CA 95060","active":true,"usgs":false}],"preferred":false,"id":832957,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huff, David D.","contributorId":171694,"corporation":false,"usgs":false,"family":"Huff","given":"David","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":832958,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203350,"text":"70203350 - 2019 - Do low-cost seismographs perform well enough for your network? An overview of laboratory tests and field observations of the OSOP Raspberry Shake 4D","interactions":[],"lastModifiedDate":"2019-05-07T13:06:04","indexId":"70203350","displayToPublicDate":"2018-11-14T13:04:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Do low-cost seismographs perform well enough for your network? An overview of laboratory tests and field observations of the OSOP Raspberry Shake 4D","docAbstract":"Seismologists have recently begun utilizing low-cost nodal sensors in dense deployments to sample the seismic wavefield at unprecedented spatial resolution. Earthquake Early Warning Systems (EEWS) and other monitoring networks (e.g. wastewater injection) would additionally benefit from network densification; however, current nodal systems lack power systems and/or real-time data transmission required for these applications. A candidate sensor for these networks may instead be a low-cost, all-in-one package such as the OSOP Raspberry Shake 4D (RS-4D). The RS-4D includes a vertical component geophone, 3-component accelerometer, digitizer, and near real-time miniSEED data transmission, and costs only a few hundred dollars per unit. Here, we step through instrument testing of three RS-4Ds at the Albuquerque Seismological Laboratory. We find the geophones have sensitivities constrained to within 4% of nominal, but that they have relatively high self-noise levels compared to the broadband sensors typically used in seismic networks. To demonstrate the impact this would have on characterizing nearby events, we estimate local magnitudes of earthquakes in Oklahoma using Trillium Compact broadband sensor data from U.S. Geological Survey (USGS) aftershock deployments as well as 23 Raspberry Shakes operated by hobbyists and private owners within Oklahoma. We find that for ML 2.0-4.0 earthquakes at distances of 20-100 km from seismic stations, the Raspberry Shakes require events of magnitude ~0.3 larger than the broadband sensors in order to reliably estimate ML at a given distance from the epicenter. We conclude that RS-4Ds are suitable for densifying backbone networks designed for studies of local and regional events.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220180251","usgsCitation":"Anthony, R.E., Ringler, A.T., Wilson, D.C., and Wolin, E., 2019, Do low-cost seismographs perform well enough for your network? An overview of laboratory tests and field observations of the OSOP Raspberry Shake 4D: Seismological Research Letters, v. 90, no. 1, p. 219-228, https://doi.org/10.1785/0220180251.","productDescription":"10 p.","startPage":"219","endPage":"228","ipdsId":"IP-102210","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":363559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":762269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":762270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":762271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolin, Emily 0000-0003-1610-1191 ewolin@usgs.gov","orcid":"https://orcid.org/0000-0003-1610-1191","contributorId":198778,"corporation":false,"usgs":true,"family":"Wolin","given":"Emily","email":"ewolin@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":762272,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215783,"text":"70215783 - 2019 - A reinterpretation of “Homing pigeons’ flight over and under low stratus” based on atmospheric propagation modeling of infrasonic navigational cues","interactions":[],"lastModifiedDate":"2020-10-29T14:05:55.372525","indexId":"70215783","displayToPublicDate":"2018-11-14T09:03:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2225,"text":"Journal of Comparative Physiology A","active":true,"publicationSubtype":{"id":10}},"title":"A reinterpretation of “Homing pigeons’ flight over and under low stratus” based on atmospheric propagation modeling of infrasonic navigational cues","docAbstract":"Pigeons flying above temperature inversion and related low-stratus layers appear to lack important navigational cues, and a reinterpretation of Wagner’s 1978 study suggests that these cues are low-frequency acoustic signals (infrasound). Wagner released homing pigeons above opaque stratus over the Swiss Plateau to determine whether they could locate their loft beneath it. Birds above the clouds appeared lost, while those that descended beneath them returned home directly. Atmospheric propagation modeling of infrasonic waves virtually transmitted from the loft area shows that these signals would have been ducted beneath the inversion layer, and would not have reached the release sites above it. The absence of homeward infrasonic cues above temperature inversions could explain the disorientation of Wagner’s birds, especially if such signals are the predominant cues used by pigeons to home. The possible generation of infrasonic navigational signals in the loft area and recent queries concerning the infrasound navigational “map” hypothesis are also discussed.
We present multitechnique U-Pb geochronology and Hf isotopic data from zircon separated from rapakivi biotite granite within the Eocene Golden Horn batholith in Washington, USA. A weighted mean of twenty-five Th-corrected 206Pb/238U zircon dates produced at two independent laboratories using chemical abrasion-isotope dilution-thermal ionisation mass spectrometry (CA-ID-TIMS) is 48.106 ± 0.023 Ma (2s analytical including tracer uncertainties, MSWD = 1.53) and is our recommended date for GHR1 zircon. Microbeam 206Pb/238U dates from laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) and secondary ion mass spectrometry (SIMS) laboratories are reproducible and in agreement with the CA-ID-TIMS date to within < 1.5%. Solution multi-collector ICP-MS (MC-ICP-MS) measurements of Hf isotopes from chemically purified aliquots of GHR1 yield a mean 176Hf/177Hf of 0.283050 ± 17 (2s, n = 10), corresponding to a εHf0 of +9.3. Hafnium isotopic measurements from two LA-ICP-MS laboratories are in agreement with the solution MC-ICP-MS value. The reproducibility of 206Pb/238U and 176Hf/177Hf ratios from GHR1 zircon across a variety of measurement techniques demonstrates their homogeneity in most grains. Additionally, the effectively limitless reserves of GHR1 material from an accessible exposure suggest that GHR1 can provide a useful reference material for U-Pb geochronology of Cenozoic zircon and Hf isotopic measurements of zircon with radiogenic 176Hf/177Hf.
The New England Fishery Management Council used management strategy evaluation (MSE) to evaluate possible harvest control rules for Atlantic herring (Clupea harengus), the first MSE in the US and perhaps globally to use open-invitation, public workshops for input. Stakeholder inclusion can increase both realism and likelihood of use by managers, but inclusivity is not achieved easily. Here, self-selected participants had diverse backgrounds and differing levels of interest and preparedness. We describe some challenges with directly engaging the public in MSE and offer broader insights for obtaining effective public participation during a decision-making process. Conducting an open MSE aligns well with publicly driven management but requires clear goals and communication. Investment in effective organizers, impartial facilitators, and knowledgeable analysts can improve communication and understanding of MSE to the betterment of fisheries management. We aim to further MSE best practices on integrating stakeholders and hope that our lessons learned on communication, engagement, and integration of MSE into an existing management arena will be useful to other practitioners.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0125","usgsCitation":"Feeney, R.G., Boelke, D.V., Deroba, J.J., Gaichas, S., Irwin, B.J., and Lee, M., 2019, Integrating management strategy evaluation into fisheries management: Advancing best practices for stakeholder inclusion based on an MSE for Northeast US Atlantic herring: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 7, p. 1103-1111, https://doi.org/10.1139/cjfas-2018-0125.","productDescription":"9 p.","startPage":"1103","endPage":"1111","ipdsId":"IP-096830","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":501374,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/93688","text":"External Repository"},{"id":395359,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Feeney, Rachael G.","contributorId":274373,"corporation":false,"usgs":false,"family":"Feeney","given":"Rachael","email":"","middleInitial":"G.","affiliations":[{"id":40788,"text":"New England Fishery Management Council","active":true,"usgs":false}],"preferred":false,"id":832944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boelke, Deirdre V.","contributorId":274374,"corporation":false,"usgs":false,"family":"Boelke","given":"Deirdre","email":"","middleInitial":"V.","affiliations":[{"id":40788,"text":"New England Fishery Management Council","active":true,"usgs":false}],"preferred":false,"id":832945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deroba, Jonathan J","contributorId":274375,"corporation":false,"usgs":false,"family":"Deroba","given":"Jonathan","email":"","middleInitial":"J","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":832946,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gaichas, Sarah","contributorId":212185,"corporation":false,"usgs":false,"family":"Gaichas","given":"Sarah","email":"","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":832947,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Irwin, Brian J. 0000-0002-0666-2641 bjirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":4037,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian","email":"bjirwin@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832948,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lee, Min-Yang","contributorId":274376,"corporation":false,"usgs":false,"family":"Lee","given":"Min-Yang","email":"","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":832949,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203339,"text":"70203339 - 2019 - Spatiotemporal analysis of the Foreshock-Mainshock-Aftershock sequence of the 6 July 2017 M5.8 Lincoln, Montana, earthquake","interactions":[],"lastModifiedDate":"2019-05-07T09:44:21","indexId":"70203339","displayToPublicDate":"2018-11-07T09:40:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal analysis of the Foreshock-Mainshock-Aftershock sequence of the 6 July 2017 M5.8 Lincoln, Montana, earthquake","docAbstract":"A MW 5.8 earthquake occurred on 6 July 2017 at 12.2 km depth, 11 km southeast of Lincoln in west central Montana. No major damage or injuries were reported; however, the widely felt mainshock generated a prolific aftershock sequence with more than 1200 located events through the end of 2017. The Lincoln event is the latest in a series of moderate-to-large earthquakes that have affected western Montana. We characterize the spatiotemporal evolution of the sequence using matched filter detection and multiple-event relocation techniques. Moment tensor solutions and aftershock locations indicate faulting occurred on a 9-km-long NNE-striking, near-vertical, strike-slip fault antithetic to the Lewis and Clark Line, the main through-going fault system. Seismicity primarily occurs between 6 and 16 km depth, consistent with seismicity in the Intermountain Seismic Belt. We estimate a fault rupture area of ~64 km2 and ~30 cm of average fault displacement. We identified four foreshocks in the three days prior to, and 3005 aftershocks in the three weeks following the mainshock. The supplemented catalog frequency-magnitude distribution has a b-value of 0.79 and a minimum magnitude of completeness of 0.7. The overall decay rate is consistent with a modified Omori decay law p-value of 0.76 and c-value of 0.32. This event demonstrates that unmapped faults antithetic to major geologic structures play a role in accommodating regional strain in Western Montana and can host significant earthquakes","language":"English","publisher":"GSW","doi":"10.1785/0220180180","usgsCitation":"McMahon, N., Yeck, W.L., Stickney, M.C., Aster, R.C., Martens, H.R., and Benz, H.M., 2019, Spatiotemporal analysis of the Foreshock-Mainshock-Aftershock sequence of the 6 July 2017 M5.8 Lincoln, Montana, earthquake: Seismological Research Letters, v. 9, no. 1, p. 131-139, https://doi.org/10.1785/0220180180.","productDescription":"9 p.","startPage":"131","endPage":"139","ipdsId":"IP-101033","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":363551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":363531,"type":{"id":15,"text":"Index 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Geographic object-based image analysis (GEOBIA) was determined to be a promising method to approach both goals. An existing GEOBIA workflow was modified and the resulting segmented objects and terrain categories tested for a strategically chosen physiographic province in the mid-western US, the Ozark Plateaus. The chi-squared test of independence confirmed that there is significant overall spatial association between terrain categories of the GEOBIA and GNIS feature classes. Contingency table analysis also suggests strong category-specific associations between select GNIS and GEOBIA classes. However, 3D visual analysis revealed that GEOBIA objects resembled segmented regions more than they did individual landform objects, with their boundaries often failing to correspond to match what people would likely perceive as landforms. Still, objects derived through GEOBIA can provide initial baseline landscape divisions that can improve the efficiency of more specialized feature extraction methods.","language":"English","publisher":"Taylor and Francis","doi":"10.1080/15230406.2018.1526652","usgsCitation":"Arundel, S., and Sinha, G., 2019, Validating the use of object-based image analysis to map commonly-recognized landform features in the United States: Cartography and Geographic Information Science, v. 46, no. 5, p. 441-455, https://doi.org/10.1080/15230406.2018.1526652.","productDescription":"15 p.","startPage":"441","endPage":"455","ipdsId":"IP-091147","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":368695,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"5","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":773989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sinha, Gaurav","contributorId":220051,"corporation":false,"usgs":false,"family":"Sinha","given":"Gaurav","email":"","affiliations":[{"id":12807,"text":"Ohio University","active":true,"usgs":false}],"preferred":false,"id":773990,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70200835,"text":"70200835 - 2019 - Modeling landowner interactions and development patterns at the urban fringe","interactions":[],"lastModifiedDate":"2018-11-13T13:16:26","indexId":"70200835","displayToPublicDate":"2018-11-06T14:51:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2603,"text":"Landscape and Urban Planning","active":true,"publicationSubtype":{"id":10}},"title":"Modeling landowner interactions and development patterns at the urban fringe","docAbstract":"Population growth and unrestricted development policies are driving low-density urbanization and fragmentation of peri-urban landscapes across North America. While private individuals own most undeveloped land, little is known about how their decision-making processes shape landscape-scale patterns of urbanization over time. We introduce a hybrid agent-based modeling (ABM) – cellular automata (CA) modeling approach, developed for analyzing dynamic feedbacks between landowners’ decisions to sell their land for development, and resulting patterns of landscape fragmentation. Our modeling approach builds on existing conceptual frameworks in land systems modeling by integrating an ABM into an established grid-based land-change model – FUTURES. The decision-making process within the ABM involves landowner agents whose decision to sell their land to developers is a function of heterogeneous preferences and peer-influences (i.e., spatial neighborhood relationships). Simulating landowners’ decision to sell allows an operational link between the ABM and the CA module. To test our hybrid ABM-CA approach, we used empirical data for a rapidly growing region in North Carolina for parameterization. We conducted a sensitivity analysis focusing on the two most relevant parameters—spatial actor distribution and peer-influence intensity—and evaluated the dynamic behavior of the model simulations. The simulation results indicate different peer-influence intensities lead to variable landscape fragmentation patterns, suggesting patterns of spatial interaction among landowners indirectly affect landscape-scale patterns of urbanization and the fragmentation of undeveloped forest and farmland.","language":"English","publisher":"Elsevier","doi":"10.1016/j.landurbplan.2018.09.023","usgsCitation":"Koch, J., Dorning, M., Van Berkel, D.B., Beck, S.M., Sanchez, G., Shashidharan, A., Smart, L.S., Zhang, Q., Smith, J.W., and Meentemeyer, R.K., 2019, Modeling landowner interactions and development patterns at the urban fringe: Landscape and Urban Planning, v. 182, p. 101-113, https://doi.org/10.1016/j.landurbplan.2018.09.023.","productDescription":"13 p.","startPage":"101","endPage":"113","ipdsId":"IP-091393","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468057,"rank":0,"type":{"id":40,"text":"Open Access 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