Investigating the effect of ballasting by CaCO3 in Emiliania huxleyi, II: Decomposition of particulate organic matter

The quantitative relationship between organic carbon and mineral contents of particles sinking below 1800 m in the ocean indicates that organisms with mineral shells such as coccolithophores are of special importance for transporting carbon into the deep sea. Several hypotheses about the mechanism behind this relationship between minerals and organic matter have been raised, such as mineral protection of organic matter or enhanced sinking rates through ballast addition. We examined organic matter decomposition of calcifying and non-calcifying Emiliania huxleyi cultures in an experiment that allowed aggregation and settling in rotating tanks. Biogenic components such as particulate carbon, particulate nitrogen, particulate volume, pigments, transparent exopolymer particles (TEP), and particulate amino acids in suspended particles and aggregates were followed over a period of 30 d. The overall pattern of decrease in organic matter, the amount of recalcitrant organic matter left after 30 d, and the compositional changes within particulate organic matter indicated that cells without a shell are more subject to loss than calcified cells. It is suggested that biogenic calcite helps in the preservation of particulate organic matter (POM) by offering structural support for organic molecules. Over the course of the experiment, half the particulate organic carbon in both calcifying and non-calcifying cultures was partitioned into aggregates and remained so until the end of the experiment. The partial protection of particulate organic matter from solubilization by biominerals and by aggregation that was observed in our experiment may help explain the robustness of the relationship between organic and mineral matter fluxes in the deep ocean.     

Triangulated spherical splines for geopotential reconstruction

We present an alternate mathematical technique than contemporary spherical harmonics to approximate the geopotential based on triangulated spherical spline functions, which are smooth piecewise spherical harmonic polynomials over spherical triangulations. The new method is capable of multi-spatial resolution modeling and could thus enhance spatial resolutions for regional gravity field inversion using data from space gravimetry missions such as CHAMP, GRACE or GOCE. First, we propose to use the minimal energy spherical spline interpolation to find a good approximation of the geopotential at the orbital altitude of the satellite. Then we explain how to solve Laplace’s equation on the Earth’s exterior to compute a spherical spline to approximate the geopotential at the Earth’s surface. We propose a domain decomposition technique, which can compute an approximation of the minimal energy spherical spline interpolation on the orbital altitude and a multiple star technique to compute the spherical spline approximation by the collocation method. We prove that the spherical spline constructed by means of the domain decomposition technique converges to the minimal energy spline interpolation. We also prove that the modeled spline geopotential is continuous from the satellite altitude down to the Earth’s surface. We have implemented the two computational algorithms and applied them in a numerical experiment using simulated CHAMP geopotential observations computed at satellite altitude (450 km) assuming EGM96 (n _max = 90) is the truth model. We then validate our approach by comparing the computed geopotential values using the resulting spherical spline model down to the Earth’s surface, with the truth EGM96 values over several study regions. Our numerical evidence demonstrates that the algorithms produce a viable alternative of regional gravity field solution potentially exploiting the full accuracy of data from space gravimetry missions. The major advantage of our method is that it allows us to compute the geopotential over the regions of interest as well as enhancing the spatial resolution commensurable with the characteristics of satellite coverage, which could not be done using a global spherical harmonic representation. The results in this paper are based on the research supported by the National Science Foundation under the grant no. 0327577.     

Comparing spatially varying coefficient models: a case study examining violent crime rates and their relationships to alcohol outlets and illegal drug arrests

In this paper, we compare and contrast a Bayesian spatially varying coefficient process (SVCP) model with a geographically weighted regression (GWR) model for the estimation of the potentially spatially varying regression effects of alcohol outlets and illegal drug activity on violent crime in Houston, Texas. In addition, we focus on the inherent coefficient shrinkage properties of the Bayesian SVCP model as a way to address increased coefficient variance that follows from collinearity in GWR models. We outline the advantages of the Bayesian model in terms of reducing inflated coefficient variance, enhanced model flexibility, and more formal measuring of model uncertainty for prediction. We find spatially varying effects for alcohol outlets and drug violations, but the amount of variation depends on the type of model used. For the Bayesian model, this variation is controllable through the amount of prior influence placed on the variance of the coefficients. For example, the spatial pattern of coefficients is similar for the GWR and Bayesian models when a relatively large prior variance is used in the Bayesian model.      

The Use of LiDAR in Digital Surface Modelling: Issues and Errors

Modelling and extracting 3D geographical data presents numerous challenges that require continual research to attempt to evolve an efficient, reliable and accurate solution. LiDAR data capture and analysis has become a preferred acquisition choice for elevation data because the resulting quality and level of detail far exceeds traditional methods for large survey areas. As with any data collection system, LiDAR is prone to errors. Analysing these errors, ascertaining causes and producing error correction strategies is vital if accurate and confident results are to be obtained. Eight years of LiDAR datasets (from 1998 to 2005) have been closely analysed for a large coastal area of South Wales. This article provides a detailed and accurate summary of the identified LiDAR data issues and subsequent errors which affect the accuracy of end products such as Digital Surface Models (DSMs).     

Large sand waves on the Atlantic Outer Continental Shelf around Wilmington Canyon,off Eastern United States

New seismic-reflection data show that large sand waves near the head of Wilmington Canyon on the Atlantic Outer Continental Shelf have a spacing of 100–650 m and a relief of 2–9 m. The bedforms trend northwest and are asymmetrical, the steeper slopes being toward the south or west. Vibracore sediments indicate that the waves apparently have formed on a substrate of relict nearshore sediments. Although the age of the original bedforms is unknown, the asymmetry is consistent with the dominant westerly to southerly drift in this area which has been determined by other methods; the asymmetry, therefore, is probably modern. Observations in the sand-wave area from a submersible during August 1975, revealed weak bottom currents, sediment bioturbation, unrippled microtopography, and lack of scour. Thus, the asymmetry may be maintained by periodic water motion, possibly associated with storms or perhaps with flow in the canyon head.