Microbial limitation in a changing world: A stoichiometric approach for predicting microbial resource limitation and fluxes

Microbes mediate fluxes of carbon (C), nitrogen (N), and phosphorus (P) in soils depending on ratios of available C, N, and P relative to microbial demand. Hence, characterizing microbial C and nutrient limitation in soils is critical for predicting how ecosystems will respond to human alterations of climate and nutrient availability. Here, we take a stoichiometric approach to assessing microbial C, N, and P limitation by using threshold element ratios (TERs). TERs enable shifting resource limitation to be assessed by matching C, N and P ratios from microbial biomass, extracellular enzyme activities, and soil nutrient concentrations. We assessed microbial nutrient limitation in temperate forests dominated by trees that associate with one of two mycorrhizal symbionts: arbsucular mycorrhizal (AM) or ectomycorrhizal (ECM) fungi. We found that both ECM and AM microbial communities were co-limited by C and N, supporting conventional wisdom that microbes are C-limited and temperate forests are N-limited. However, AM microbial communities were relatively more C-limited than ECM communities (P=0.001). In response to chronic field N fertilization, both AM and ECM communities became relatively more P-limited (P=0.011), but they remained N- and C-limited overall. Thus, realistic levels of N deposition may not dampen microbial N limitation. Reflecting differences in relative limitation, N mineralization rates were higher in AM soils than in ECM soils (P=0.004) while C mineralization rates were higher in ECM soils than in AM soils (P=0.023). There were no significant differences in P flux between AM and ECM soils or detectable mineralization responses to N addition, indicating that mineralization rates are closely tied to C and nutrient limitation. Overall, we found that 1) microbial resource limitation can be detected without resource addition; and 2) TERs and ratios of labile resources are viable tools for predicting mineralization responses to resource additions.