As part of the Barrier Island Evolution Research (BIER) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected sediment samples from the northern Chandeleur Islands in July 2013. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to understand better the depositional and erosional processes that drive the morphologic evolution of barrier islands over annual to interannual timescales (1 to 5 years). Between June 2010 and April 2011, in response to the Deepwater Horizon oil spill, the State of Louisiana constructed a sand berm extending more than 14 kilometers (km) along the northern Chandeleur Islands platform. The construction of the berm provided a unique opportunity for scientists to investigate how this new sediment source interacts with and affects the morphologic evolution of the barrier-island system. Data collected from this study can be used to describe differences in the physical characteristics and spatial distribution of sediments both along the axis of the berm and also along transects across the berm and onto the adjacent barrier island. Comparison of these data with data from prior sampling efforts can provide information about sediment interactions and movement between the berm and the natural island platform, improving insight into short-term morphologic change and processes in this barrier-island system.
This data series serves as an archive of sediment data collected in July 2013 from the Chandeleur Islands sand berm and adjacent barrier-island environments. Data products, including descriptive core logs, core photographs and x-radiographs, results of sediment grain-size analyses, sample location maps, and Geographic Information System (GIS) data files with accompanying formal Federal Geographic Data Committee (FDGC) metadata, can be downloaded from
https://pubs.usgs.gov/ds/894/ds894_data.html.
This zip archive includes a Microsoft Excel workbook with three spreadsheets summarizing the results of grain-size analyses from sediment samples collected in July 2013 from the northern Chandeleur Islands, Louisiana (U.S. Geological Survey Field Activity Number 13BIM05).
Grain-size analyses were performed with 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 194 sediment samples were analyzed. To prevent shell fragments from damaging the LS 200, particles greater than 1 mm in diameter were separated from all samples prior to analysis with a number 18 (1000 microns, 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 run through the free, widely available program GRADISTAT (Blott and Pye, 2001;
http://www.kpal.co.uk/gradistat.html), which calculates the geometric (in metric units) and logarithmic (in phi units; Krumbein, 1934) mean, sorting, skewness, and kurtosis of each sample using the Folk and Ward (1957) method and the cumulative particle-size distribution. 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 ("Average and Check Standard Deviation") developed by the USGS was applied to calculate the average and standard deviation of each sample set (six 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 material in the sample and are not considered representative of the sample. Runs that deviated excessively were removed from the results, and the sample average was recalculated using the remaining runs.
The grain-size data can be downloaded from
https://pubs.usgs.gov/ds/894/ds894_data.html. The unedited output files, which are sorted by core number or sample type (for example, surface or submerged grab sample), can be downloaded from
https://pubs.usgs.gov/ds/894/downloads/13BIM05_grainsize_GRADISTAT-Statistics.zip. Each file includes the output spreadsheets with statistics for each sample run and the sand-silt-clay ternary diagram generated by GRADISTAT along with averaged statistics for each sample generated by the USGS Average and Check Standard Deviation macro application. GRADISTAT calculates statistics for several parameters that do not apply to this dataset or future analyses. For example, GRADISTAT 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 scales 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://pubs.usgs.gov/ds/0894/downloads/13BIM05_Grain_Size.zip. These metadata are not complete without the data dictionary (
https://pubs.usgs.gov/ds/894/downloads/metadata/grainsize_data-dictionary.pdf) included in this archive, which applies specifically to the summary statistics spreadsheets.
