Using Foraminifera to estimate trends in ancient sea-levels

Sea‐level curves are powerful tools for correlation: rocks deposited at the peaks of global transgressions, otherwise known as maximum flooding surfaces, can be correlated theoretically from one region to another. This begs the question: given that geologists can estimate the change in sea‐level between one rock formation and the next, can they discern trends at a smaller scale, within formations? Here I outline how foraminifera can be used to draw time/sea‐level graphs.     

Further considerations on combining earth rotation observations from different space geodetic systems

Additional results are presented concerning a study that consider improvements over present Earth Rotation Parameter (ERP) determination methods by directly combining observations from various space geodetic systems in one adjustment. Earlier results are extended, showing that in addition to slight improvements in accuracy substantial (a factor of three or more) improvements in precision and significant reductions in correlations between various parameters can be obtained (by combining Lunar Laser Ranging (LLR), Satellite Laser Ranging (SLR) to Lageos, and Very Long Baseline Interferometry (VLBI) data in one adjustment) as compared to results from individual systems. Smaller improvements are also seen over the weighted means of the individual system results. Although data transmission would not be significantly reduced, negligible additional computer time would be required if (standardized) normal equations were available from individual solutions. Suggestions for future work and implications for the new International Earth Rotation Service (IERS) are also presented.     

Time-based correlation of biogenic,lithogenic and authigenic sediment components with anthropogenic inputs in the Gulf of Mexico NECOP study area

Hypotheses related to variability in seasonal hypoxic conditions, coastal nutrient enhancement, and off-shelf transport of carbon on the Louisiana continental shelf were tested by characterization of biogenic, lithogenic, and authigenic components from two shelf and one Mississippi Canyon sediment cores. The authigenic-phase glauconite occurs above detection limits only in the core from the hypoxic area. A major increase in glauconite concentration was coincident with the onset (≈1940) of the increased use of commercial fertilizers in the United States. In the same hypoxic-area core, benthic foraminifera species diversity decreases upcore from approximately the turn of the century to the present in a manner concurrent with glauconite and fertilizer increases. A subset of opportunistic benthic foraminifera species, known to become more prominent in stressed environments (i.e., hypoxic), increased upcore from ～52% of the total population at core bottom to ≈90% at core top. These benthic foraminifera population and diversity changes were not apparent in a “control” core outside the area of documented hypoxia. Seaward of the shelf, in the Mississippi Canyon, coincident increases in sediment accumulation rate, percentages of coarse fraction and of organic carbon at core top indicate increased offshelf transport of carbon and other components. Quartz percentages indicate that episodic down-canyon transport has been active to core bottom (prior to the mid 1800s).     

Dating of raised marine and lacustrine deposits in east Greenland using beryllium‐10 depth profiles and implications for estimates of subglacial erosion

Here we combine ¹⁰Be depth profile techniques applied to late glacial ice‐contact marine and lacustrine deltas, as well as boulder exposure dating of associated features in the Scoresby Sound region, east Greenland, to determine both the surface age and the magnitude of cosmogenic nuclide inheritance. Boulder ages from an ice‐contact delta in northern Scoresby Sund show scatter typical of polar regions and yield an average age of 12.8 ± 0.5 ka – about 2 ka older than both our average profile surface age of 10.9 ± 0.7 ka from three depth profiles and a radiocarbon‐based estimate. On the other hand, boulder exposure ages from a set of moraines in southern Scoresby Sund show excellent internal consistency for polar regions and yield an average age of 11.6 ± 0.2 ka. The profile surface age from a corresponding ice‐contact delta is 8.1 ± 0.9 ka, while a second delta yields an age of 10.0 ± 0.4 ka. Measured ¹⁰Be inheritance concentrations from all depth profiles are internally consistent and are between 10% and 20% of the surface concentrations, suggesting a regional cosmogenic inheritance signal for the Scoresby Sound landscape. Based on the profile inheritance concentrations, we explore the first‐order catchment‐averaged bedrock erosion under the Greenland ice sheet, yielding estimates of total erosion during the last glacial cycle of the order of 2–30 m. Copyright © 2010 John Wiley & Sons, Ltd.     

Generous statistical tests

A common statistical problem is deciding which of two possible sources, A and B, of a contaminant is most likely the actual source. The situation considered here, based on an actual problem of polychlorinated biphenyl contamination discussed below, is one in which the data strongly supports the hypothesis that source A is responsible. The problem approach here is twofold: One, accurately estimating this extreme probability. Two, since the statistics involved will be used in a legal setting, estimating the extreme probability in such a way as to be as generous as is possible toward the defendant’s claim that the other site B could be responsible; thereby leaving little room for argument when this assertion is shown to be highly unlikely. The statistical testing for this problem is modeled by random variables {X _i } and the corresponding sample mean the problem considered is providing a bound ɛ for which for a given number a ₀. Under the hypothesis that the random variables {X _i } satisfy E(X _i ) ≤ μ, for some 0  < μ < 1, statistical tests are given, described as “generous”, because ɛ is maximized. The intent is to be able to reject the hypothesis that a ₀ is a value of the sample mean while eliminating any possible objections to the model distributions chosen for the {X _i } by choosing those distributions which maximize the value of ɛ for the test used.