Grain-size distribution from different surface sediment samples of Lake Towuti, Indonesia

A digital elevation model (DEM) of Lake Towuti and its surrounding was calculated using ArcGIS (Esri, Inc., Redlands, CA, USA). The model is based on open source satellite data for Sulawesi provided by the United States Geological Survey (Aster Global DEM based on the Shuttle Radar Topography Mission carried out by the National Aeronautics and Space Administration at 1 arc-second 30 m spatial resolution). Spatial interpolation of the analytical surface sediment data was carried out with the software Surfer 9 (Golden Software Inc., Golden, CO, USA) using the kriging method. Statistical analyses employed on the surface sediment data sets comprise end-member (EM) unmixing, principal component analysis (PCA) and a redundancy analysis (RDA). EM analyses were carried out on normalized and standardized grain-size (EMGS), chemical (EMChem) and mineralogical (EMMin) data sets. Assuming a sedimentary mixture from different sources the mixing model in all cases can be written as: X = AS + E (1) where X represents the n-by-m matrix of n samples (one per row) and m variables (relative abundance of individual data). Matrix A (n-by-l) denotes the mixing proportion of l end-members for the n samples, S represents the m properties of the l EMs and E is the error matrix of residuals. The uncertainties of the EM analyses are controlled by the errors of the data sets used. The EM algorithm developed by Heslop and Dillon (2007) adopting the approach of Weltje (1997) was applied. The decision criterion of how many EMs are included in the three models is based partly on the coefficients of determination derived from the PCA. Nevertheless, the number of the respective EMs should also be reasonable in the geological context of the data set (Weltje, 1997; Weltje and Prins, 2007). Residuals of the EM models include analytical errors and non-identified additional sources of variability. All other multivariate statistical analyses were carried out with the Excel-based software Addinsoft XLSTAT (STATCON GmbH, Witzenhausen, Germany) The PCA was conducted with the sand content and the concentrations of selected elements determined by ICP-MS and XRF analyses (Fe, Mg, Al, Si, K, Ca, Cr and Ni). In the RDA, the results derived from the PCA are expanded by the concentrations of major minerals, the MS and TOC values and the C/N ratio. The correlation matrix includes all data except 13COM and the concentrations of diatom frustules, sponge spicules and tephra particles, which all were determined on a subset of the surface samples only.