Geostatistical interpretation of paleoceanographic data over large ocean basins - Reality and fiction

A promising approach to reconstruct oceanographic scenarios of past time slices is to drive numerical ocean circulation models with sea surface temperatures, salinities, and ice distributions derived from sediment core data. Set up properly, this combination of boundary conditions provided by the data and physical constraints represented by the model can yield physically consistent sets of three-dimensional water mass distribution and circulation patterns. This idea is not only promising but dangerous, too. Numerical models cannot be fed directly with data from single core locations distributed unevenly and, as it is the common case, scarcely in space. Conversely, most models require forcing data sets on a regular grid with no missing points, and some method of interpolation between punctual source data and model grid has to be employed. An ideal gridding scheme must retain as much of the information present in the sediment core data while generating as few artifacts in the interpolated field as possible. Based on a set of oxygen isotope ratios, we discuss several standard interpolation strategies, namely nearest neighbour schemes, bicubic splines, Delaunay triangulation, and ordinary and indicator kriging. We assess the gridded fields with regard to their physical consistence and their implications for the oceanic circulation

Evaluation of metals that are potentially toxic to agricultural surface soils, using statistical analysis, in northwestern Saudi Arabia

© 2015, Springer-Verlag Berlin Heidelberg. Heavy metals in agricultural soils enter the food chain when taken up by plants. The main purpose of this work is to determine metal contamination in agricultural farms in northwestern Saudi Arabia. Fifty surface soil samples were collected from agricultural areas. The study focuses on the geochemical behavior of As, Cd, Co, Cr, Cu, Hg, Pb and Zn, and determines the enrichment factor and geoaccumulation index. Multivariate statistical analysis, including principle component analysis and cluster analysis, is also applied to the acquired data. The study shows considerable variation in the concentrations of the analyzed metals in the studied soil samples. This variation in concentration is attributed to the intensity of agricultural activities and, possibly, to nearby fossil fuel combustion activities, as well as to traffic flows from highways and local roads. Multivariate analysis suggests that As, Cd, Hg and Pb are associated with anthropogenic activities, whereas Co, Cr, Cu and Zn are mainly controlled by geogenic activities. Hg and Pb show the maximum concentration in the analyzed samples as compared to the background concentration