Scientists from the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a time-series collection of shallow sediment cores from the back-barrier environments along the Chandeleur Islands, Louisiana from March 2012 through July 2013. The sampling efforts were part of a larger USGS study to evaluate the effects on the geomorphology of the Chandeleur Islands following the construction of an artificial sand berm in response to the Deep Water Horizon oil spill. The objective of this study was to evaluate the response of the back-barrier tidal and wetland environments to the berm.
This report serves as an archive for sedimentological, radiochemical, and microbiological data derived from the sediment cores. Data is available for a time-series of four sampling periods: March 2012; July 2013; September 2012; and July 2013. Data is available in downloadable spreadsheet, Joint Photographic Experts Group and Portable Document File formats. Additional files included: ArcGIS shape files of the study sites, detailed results of sediment grain size analyses, and formal Federal Geographic Data Committee (FDGC) metadata.
The Grain_Size_Data.zip file includes Excel spreadsheets summarizing particle size analysis results from back-barrier wetlands collected on or around the Chandeleur Islands, Louisiana from March 2012 to July 2013 by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center.
Grain-size analyses were performed using a Coulter LS 200 (
https://www.beckmancoulter.com/) particle-size analyzer, which uses laser diffraction to measure the size distribution of sediments ranging in size from 0.4 microns to 2 millimeters (mm) (clay to very coarse-grained sand). A total of 284 samples from 49 cores were analyzed. Prior to particle size analysis, organic material was chemically removed for the marsh core samples using 30% hydrogen peroxide (H2O2). The organic matter content in the back-barrier core samples were estimated from the LOI values to be ‹3% and therefore would not interfere with the LS200 measurements. Wet sediment from the marsh samples were dissolved in H2O2 overnight. The H2O2 was then evaporated and the sediment washed and centrifuged twice with deionized water. In order to prevent shell fragments from damaging the LS 200, particles greater than 1 mm in diameter were separated from all samples prior to analysis using a number 18 (1000 microns or 1 mm) U.S. standard sieve, which meets the American Society for Testing and Materials (ASTM) E11 standard specifications for determining particle size using woven-wire test sieves. Two subsamples from each sample were processed through the LS 200 a minimum of three runs each. The LS 200 measures the particle-size distribution of each sample by passing sediment suspended in solution between two narrow panes of glass in front of a laser. Light is scattered by the particles into characteristic refraction patterns measured by an array of photodetectors as intensity per unit area and recorded as relative volume for 92 size-related channels (bins). The size-classification boundaries for each bin were specified based on the ASTM E11 standard.
The raw grain size data were then run through the free software program GRADISTAT (Blott and Pye, 2001;
http://www.kpal.co.uk/gradistat), which calculates the mean, sorting, skewness, and kurtosis of each sample geometrically in metric units and logarithmically in phi units (Krumbein, 1934) using the Folk and Ward (1957) method. GRADISTAT also calculates the fraction of sediment from each sample by size category (for example, clay, coarse silt, fine sand) based on a modified Wentworth (1922) size scale. A macro function in Microsoft Excel, developed by the USGS SPCMSC, was applied to the data tocalculate average and standard deviation for each sample set (6 runs per sample), and highlight runs that varied from the set average by more than ±1.5 standard deviations. Excessive deviations from the mean are likely the result of equipment error or extraneous organic material in the sample and are not considered representative of the sample. The highlighted runs were removed from the results and the sample average was recalculated using the remaining runs.
The grain size data can be viewed or downloaded from
https://doi.org/10.3133/ofr20141079/ofr1079_data.html. Each data file includes averaged statistics for each sample and the sand-silt-clay ternary diagram generated by GRADISTAT. The unedited output files with statistics for each sample run along with averaged statistics for each sample generated by the USGS Average and Check Standard Deviation macro can be downloaded from
https://doi.org/10.3133/ofr20141079/ofr1079_data.html/Grain_Size_Run_Statistics.zip. GRADISTAT calculates statistics for several parameters that do not apply to our dataset or future analyses and therefore are not included in the summarized data files. For example, GRADISTAT also calculates the arithmetic mean grain size of each sample; however, an arithmetic grain-size scale is generally not used in sedimentology because the standard grain-size classifications (Wentworth, 1922) are not based on a normal (Gaussian) distribution, which tends to overemphasize coarse sediment, whereas geometric and their derivative log-normal scales place equal emphasis on the small size differences between fine particles (for example, clay and silt) and the larger size differences between coarse particles (for example, pebbles and cobbles). Other parameters, such as percent gravel, do not apply to this dataset because particles coarser than 1 mm were removed from the samples prior to processing. The averaged results for the subset of statistical parameters that apply to these data are summarized in three spreadsheets, which can be downloaded from
https://doi.org/10.3133/ofr20141079/images/Tables/Grain_Size_Data.zip. These metadata are not complete with out the data dictionary (Grain_Size_Data_Dictionary.pdf) also included in this archive, which applies specifically to the summary statistics spreadsheets.
