OOS 34-7 - A global scale analysis of grassland soil stoichiometry using the Nutrient Network Global Research Cooperative

Wednesday, August 8, 2012: 3:40 PM
B116, Oregon Convention Center
Ryan J. Williams, Agricultural and Biosystems Engineering, Iowa State University, Ames, IA, Kirsten S. Hofmockel, Pacific Northwest National Laboratory, Richland, WA, W. Stanley Harpole, Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA and Nutrient Network, Multiple Institutions

Terrestrial ecosystem functioning is predominantly driven by biogeochemical processes localized to the soil and is often constrained by the stoichiometric relationships between elements necessary for life.  The rates and stability of these material pools are largely driven by microbial communities, which transform inorganic material to alternate forms while breaking large organic molecules down to inorganic forms. The metabolic activity of soil microbial communities is constrained by the availability of resources in concert; these resource ratios thereby drive the microbial machines that generate biogeochemical cycling and the availability of nutrients for surrounding organisms.  The objective of our study was to explore stoichiometric ratios of soil nutrients at the global and grassland ecosystem scale.  The establishment of the Nutrient Network (NutNet) experiment, a factorial design of N, P, and K addition, has generated a large database of soil nutrient variables from a variety of grassland ecosystems across the globe.  Using the NutNet database and soils from 43 sites across 5 continents, we explored the effect of climatic and vegetation variables on soil nutrient stoichiometry. 


Soil organic matter (SOM) content varied among continents (2.5-4.6%) and grassland ecosystems (0.8-5.3%) despite soil C:N ratios remaining between 11:1 and 18:1. N:P ratios varied an order of magnitude between continents, creating extremely wide C:N:P ratios globally (5782:326:1-903:169:1) and even wider ratios than previously reported at the ecosystem scale (5335:350:1-96:9:1).  All bivariate nutrient ratios except C:N and P:K showed strong positive correlations with SOM (R2 ≥ 0.45, P < 0.0001). Total soil C and N had a strong, positive correlation (R2 = 0.91, P < 0.001), while both C and N were positively correlated to mean annual precipitation (R2 ≥ 0.36, P < 0.0001) and negatively correlated with maximum annual temperature (R2 ≥ 0.44, P < 0.0001).  Precipitation and temperature appear as important predictors of soil C and N possibly through climatic effects on decomposition rate, while P and K are likely controlled through proximate and historical site characteristics. There were weak, but significant correlations between nutrient ratios and vegetation measurements including productivity and diversity metrics, suggesting that soil stoichiometry may be more dependent on abiotic processes than aboveground vegetation alone.