Microbial carbon dynamics in nitrogen amended Arctic tundra soil: Measurement and model testing

• Published in: Soil Biology and Biochemistry
• Main Authors: Stapleton, L M, Crout, N M J, Säwström, Christin, Marshall, W A, Poulton, P R, Tye, A M, Laybourn-Parry, J
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2005
• Subjects: Environmental Sciences; Ecology; Arctic; Svalbard; Kongsfjord*; Kongsfjorden; Tundra
• Online Access: https://lup.lub.lu.se/record/150691; https://doi.org/10.1016/j.soilbio.2005.03.016

We examined the responses of grazers (protozoa and nematodes) and their main food sources to low levels of nitrogen (N) fertilisation and applied carbon (C) flux models to our data. Replicate plots of tundra soil adjacent to the Kongsfjorden (Svalbard 78°N) were amended with ammonium and nitrate at concentrations of 1 and 5 kg N ha−1 to assess the impact of anthropogenic N deposition over three summers. Bacterial abundance as determined using the fluorochrome SYBR Green and epifluorescence microscopy ranged between 9.73×108 and 102.49×108 cells/g dry wt of soil, with a significant response to N addition occurring only during the second sampling in 2001. Despite little change in bacterial biomass, bacterial production (measured by the incorporation of 3H thymidine into DNA) during the second sampling in 2002, increased in NH4 enriched plots compared to control and NO3 amended plots, indicating that NH4 was the preferred source of inorganic N. The main bacterial predators were heterotrophic flagellates (HNAN) and naked amoebae, which showed no significant response to the N addition. HNAN showed a correlation with bacterial abundance suggesting a dependence on bacteria as a food source. The inability of a microbial C flux model to fit our data (RWSS/data=18.6, r2=0.088) was at least partly due to insufficient bacterial production to meet the C demands of predator taxa, and high variability in the data over time. This is reflected in the performance statistics for model variants where select microbial taxa and data were removed. The optimal model in terms of predictive utility was a model with data from 2002 only, minus naked amoebae (RWSS/data=2.45, r2=0.806).