Low temperatures, limited precipitation, and high salinity in the McMurdo Dry Valleys (MCM) of Antarctica constrain life to simple communities that are more easily interpreted in ecological studies. For these reasons, the MCM Long Term Ecological Research (LTER) site provides an ideal opportunity to address complex ecological questions. Understanding how soil abiotic resources vary across space is essential to predicting patterns in species diversity, abundance, and ecosystem functions in general. Thus, we used a spatially-explicit experimental design to examine fine scale heterogeneity of snowpack, soil biogeochemistry, and soil respiration in the Taylor Valley of Antarctica. This observational field study focused on three main research questions. (1) What is the spatial heterogeneity of soil chemistry and respiration in subnivian compared to adjacent exposed soils? (2) How does small-scale variation in snow depth influence chemistry and respiration of soils? (3) Which factors of soil chemistry best correlate with soil respiration? The study site involved sampling from an 8 year old snowfence manipulation experiment utilizing both the exposed and subnivian areas. We used a spatially explicit sampling scheme that maximized the number of pairwise comparisons with different distances. A total of 89 sample points were completed.
Some data (such as nitrate and C:N ratio) and statistical analyses are still pending, but initial examination of patterns in field data show results of higher pH in subnivian compared to exposed sites, and no differences in variability of soil pH, salinity, or soil moisture between subnivian and exposed sites. Ongoing analyses, using geostatistics in program R 2.7.2, focus on spatially explicit examination of autocorrelation using variograms. We predict the following: (1) There will be greater fine scale spatial heterogeneity of soil chemistry and respiration under subnivian conditions. (2) Presence of small-scale variation in snow depth will increase fine scale heterogeneity of chemistry and mean CO2 respiration of soils. (3) Soil moisture will correlate best with soil respiration. Information gained from this study will not only help us better understand how future alteration in snowpack from climate change will impact soil biogeochemistry and respiration, it will also provide a much improved framework for the design of future studies, ensuring the most efficient sampling possible to maximize independent comparisons between points.