As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic sampling program has been undertaken to monitor the production of algal mats in glacial meltwater streams of the region. This table contains data showing the chlorophyll, carbon, nitrogen, and hydrogen concentrations of algal communities and some mosses from selected streams from each of three Taylor Valley basins. The data set constitutes the LTER algal and moss biomass data, along with measurements of the amount of carbon and nitrogen associated with algal mats for construction of nutrient budgets.
Within each transect, algal mats were visually identified as either orange, red, black, or green. Algal and moss samples were collected using a cork borer or a known area of substrate was scraped. Samples were stored in bottles until taken back to the lab for processing. Samples were filtered onto GF/C glass fiber filters. They were then extracted in buffered acetone and analyzed spectrophotometrically using the trichromatic method. Concentrations are reported in units of microg/cm2 for each pigment quantified (chlorophylls a, b, c, carotenoids, and phaeophyton). Carbon, hydrogen and nitrogen samples were air-dried (approximately 60 degrees C), then a weighed amount of algae was taken from the filter and analyzed on a Carlo Erba NA1500NCS element analyzer.
Data from this table was initially included in the raw data files specified under the variable for 'file name'. These are Microsoft Excel version 5.0 files and can be found on the McMurdo LTER data manager's personal computer at INSTAAR. Once submitted to INSTAAR, the data manager combined all of the stream biology files that included information for chlorophyll/biomass and removed any variables that had no direct influence. The resulting files are represented in the "strmbims.dat" and "strmbims.txt" files used on the web page. In July, 2000, dataset code and location code (strmtrnsid) fields were added. This would simplify generating links between different data and metadata fields and assist in making the data more relational / useful in Oracle and ArcInfo.