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The method of obtaining zircon samples affects estimation of the global U-Pb age distribution.Researchers typically collect zircons via convenience sampling and cluster sampling.When using these techniques,weight adjustments proportional to the areas of the sampled regions improve upon unweighted estimates.Here,grid-area and modern sediment methods are used to weight the samples from a new database of 418,967 U-Pb ages.Preliminary tests involve two age models.Model-1 uses the most precise U-Pb ages as the best ages.Model-2 uses the~(206)Pb/~(238)U age as the best age if it is less than a1000 Ma cutoff,otherwise it uses the~(207)Pb/~(206)Pb age as the best age.A correlation analysis between the Model-1 and Model-2 ages indicates nearly identical distributions for both models.However,after applying acceptance criteria to include only the most precise analyses with minimal discordance,a histogram of the rejected samples shows excessive rejection of the Model-2 analyses around the1000 Ma cutoff point.Because of the excessive rejection rate for Model-2,we select Model-1 as the preferred model.After eliminating all rejected samples,the remaining analyses use only Model-1 ages for five rock-type subsets of the database:igneous,meta-igneous,sedimentary,meta-sedimentary,and modern sediments.Next,time-series plots,cross-correlation analyses,and spectral analyses determine the degree of alignment among the time-series and their periodicity.For all rock types,the U-Pb age distributions are similar for ages older than 500 Ma,but align poorly for ages younger than 500 Ma.The similarities(500 Ma)and differences(500 Ma)highlight how reductionism from a detailed database enhances understanding of time-dependent sequences,such as erosion,detrital transport mechanisms,lithification,and metamorphism.Time-series analyses and spectral analyses of the age distributions predominantly indicate a synchronous period-tripling sequence of~91-Myr,~273-Myr,and~819-Myr among the various rock types.  相似文献   
64.
International Journal of Earth Sciences - The geometry and emplacement of the ~ 96 km2, Late Cretaceous Sintra Igneous complex (SIC, ca. 80 Ma) into the West Iberian passive...  相似文献   
65.
International Journal of Earth Sciences - The Western Sierras Pampeanas (WSP) of Argentina record a protracted geological history from the Mesoproterozoic assembly of the Rodinia supercontinent to...  相似文献   
66.
Mount Bulusan, the Philippines’ fourth most active volcano, erupted in February 21, 2011, sending volcanic ash and pyroclastic materials to its surrounding rivers. The waters drained into the estuary of harmful algal blooms plagued Sorsogon Bay. We aim to determine the impact of the 2011 volcanic eruption and the preceding volcanic ash emissions to the dissolved silica concentration of rivers draining the flanks of Mt. Bulusan and its possible implications to the phytoplankton assemblage of the bay. Six river water sampling periods from August 2010 to October 2012 overlapped with Mt. Bulusan’s active phase of volcanism. Our data shows that mean river silica from pre-eruption levels of ~?500 μM increased by more than 200% during and post-eruption. Highest Si concentration of 2270 μM was measured from Cadacan River in August 2011. Here, we argue that the sustained general increase of dissolved silica is due to the silica-containing materials from Mt. Bulusan’s eruption and that their concentration in river waters is also a function of watershed lithology and precipitation. Increase in dissolved silica and other nutrients caused a shift to diatom domination and, possibly, termination of Pyrodinium bahamense var. compressum blooms. Silica load increase in embayments is a natural process that controls the dominance of algae. Our study also highlights the importance of Philippine rivers to the global ocean silica budget as a function of high precipitation, tectonics in general, and volcanism in particular.  相似文献   
67.
Estuaries are productive and ecologically important ecosystems, incorporating environmental drivers from watersheds, rivers, and the coastal ocean. Climate change has potential to modify the physical properties of estuaries, with impacts on resident organisms. However, projections from general circulation models (GCMs) are generally too coarse to resolve important estuarine processes. Here, we statistically downscaled near-surface air temperature and precipitation projections to the scale of the Chesapeake Bay watershed and estuary. These variables were linked to Susquehanna River streamflow using a water balance model and finally to spatially resolved Chesapeake Bay surface temperature and salinity using statistical model trees. The low computational cost of this approach allowed rapid assessment of projected changes from four GCMs spanning a range of potential futures under a high CO2 emission scenario, for four different downscaling methods. Choice of GCM contributed strongly to the spread in projections, but choice of downscaling method was also influential in the warmest models. Models projected a ~2–5.5 °C increase in surface water temperatures in the Chesapeake Bay by the end of the century. Projections of salinity were more uncertain and spatially complex. Models showing increases in winter-spring streamflow generated freshening in the Upper Bay and tributaries, while models with decreased streamflow produced salinity increases. Changes to the Chesapeake Bay environment have implications for fish and invertebrate habitats, as well as migration, spawning phenology, recruitment, and occurrence of pathogens. Our results underline a potentially expanded role of statistical downscaling to complement dynamical approaches in assessing climate change impacts in dynamically challenging estuaries.  相似文献   
68.
While many studies of non-native species have examined either soft-bottom or hard-bottom marine communities, including artificial structures at docks and marinas, formal comparisons across these habitat types are rare. The number of non-indigenous species (NIS) may differ among habitats, due to differences in species delivery (trade history) and susceptibility to invasions. In this study, we quantitatively compared NIS to native species richness and distribution and examined community similarity across hard-bottom and soft-sediment habitats in San Francisco Bay, California (USA). Benthic invertebrates were sampled using settlement panels (hard-bottom habitats) and sediment grabs (soft-bottom habitats) in 13 paired sites, including eight in higher salinity areas and five in lower salinity areas during 2 years. Mean NIS richness was greatest in hard-bottom habitat at high salinity, being significantly higher than each (a) native species at high salinity and (b) NIS richness at low salinity. In contrast, mean NIS richness in soft-bottom communities was not significantly different from native species richness in either high- or low-salinity waters, nor was there a difference in NIS richness between salinities. For hard-bottom communities, NIS represented an average of 79% of total species richness per sample at high salinity and 78% at low salinity, whereas the comparable values for soft bottom were 46 and 60%, respectively. On average, NIS occurred at a significantly higher frequency (percent of samples) than native species for hard-bottom habitats at both salinities, but this was not the case for soft-bottom habitats. Finally, NIS contributed significantly to the existing community structure (dissimilarity) across habitat types and salinities. Our results show that NIS richness and occurrence frequency is highest in hard-bottom and high-salinity habitat for this Bay but also that NIS contribute strongly to species richness and community structure across each habitat evaluated.  相似文献   
69.
An unsupervised machine-learning workflow is proposed for estimating fractional landscape soils and vegetation components from remotely sensed hyperspectral imagery. The workflow is applied to EO-1 Hyperion satellite imagery collected near Ibirací, Minas Gerais, Brazil. The proposed workflow includes subset feature selection, learning, and estimation algorithms. Network training with landscape feature class realizations provide a hypersurface from which to estimate mixtures of soil (e.g. 0.5 exceedance for pixels: 75% clay-rich Nitisols, 15% iron-rich Latosols, and 1% quartz-rich Arenosols) and vegetation (e.g. 0.5 exceedance for pixels: 4% Aspen-like trees, 7% Blackberry-like trees, 0% live grass, and 2% dead grass). The process correctly maps forests and iron-rich Latosols as being coincident with existing drainages, and correctly classifies the clay-rich Nitisols and grasses on the intervening hills. These classifications are independently corroborated visually (Google Earth) and quantitatively (random soil samples and crossplots of field spectra). Some mapping challenges are the underestimation of forest fractions and overestimation of soil fractions where steep valley shadows exist, and the under representation of classified grass in some dry areas of the Hyperion image. These preliminary results provide impetus for future hyperspectral studies involving airborne and satellite sensors with higher signal-to-noise and smaller footprints.  相似文献   
70.
Geotechnical and Geological Engineering - Dispersive soils are susceptible to phenomena of internal and external erosion when in contact with relatively pure water due to its particle’s...  相似文献   
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