Differences in soil biological activity by terrain types at the sub-field scale in central Iowa US

Authors

Amy L. Kaleita, Iowa State UniversityFollow
Linda R. Schott, University of Nebraska - LincolnFollow
Sarah K. Hargreaves, Ecological Farmers Association of Ontario
Kirsten S. Hofmockel, Environmental Molecular Sciences Laboratory

Document Type

Article

Date of this Version

2017

Citation

Kaleita AL, Schott LR, Hargreaves SK, Hofmockel KS (2017)

Comments

PLoS ONE 12(7): e0180596.

https://doi.org/10.1371/journal.pone.0180596

Abstract

Soil microbial communities are structured by biogeochemical processes that occur at many different spatial scales, which makes soil sampling difficult. Because soil microbial communities are important in nutrient cycling and soil fertility, it is important to understand how microbial communities function within the heterogeneous soil landscape. In this study, a self-organizing map was used to determine whether landscape data can be used to characterize the distribution of microbial biomass and activity in order to provide an improved understanding of soil microbial community function. Points within a row crop field in southcentral Iowa were clustered via a self-organizing map using six landscape properties into three separate landscape clusters. Twelve sampling locations per cluster were chosen for a total of 36 locations. After the soil samples were collected, the samples were then analysed for various metabolic indicators, such as nitrogen and carbon mineralization, extractable organic carbon, microbial biomass, etc. It was found that sampling locations located in the potholes and toe slope positions had significantly greater microbial biomass nitrogen and carbon, total carbon, total nitrogen and extractable organic carbon than the other two landscape position clusters, while locations located on the upslope did not differ significantly from the other landscape clusters. However, factors such as nitrate, ammonia, and nitrogen and carbon mineralization did not differ significantly across the landscape. Overall, this research demonstrates the effectiveness of a terrain-based clustering method for guiding soil sampling of microbial communities.