Soil microbial responses to rewetting depend on rewetting intensity and soil properties

Soil drying and rewetting (DRW) events are perceived differently by the soil microbes depending on their adaptation to the previous soil moisture history. Microbes adapted to intense cycles of DRW can experience an experimental DRW event as less harsh than microbes adapted to stable and moist conditions. The perceived harshness in turn can affect the carbon balance after DRW because it can determine the responses of microbial growth (eventually leading to SOC gains) and respiration (SOC loss) after rewetting. These responses have been categorized as “type 1” with immediate fast recovery, or “type 2” with a time lag before fast recovery, due to low and high levels of perceived harshness, respectively. However, we lack a quantitative definition of perceived harshness and how it varies depending on pedoclimatic conditions. Moreover, microbial response types could vary continuously along a continuum from prototypical type 1 to type 2. Therefore, if the shapes of the response curves could be synthesized by using a single function, then the fitted parameters could be used to reflect the harshness levels perceived by the microbes. In turn, these parameters might be combined into an index of harshness with biological interpretation. Relating this index to climatic and edaphic factors would then help to understand the drivers of harshness and microbial recovery after rewetting. To these aims, we described microbial growth with a single logistic function G(t)=G_max/(1+e^b(t-τ)) and respiration with a rescaled gamma distribution R(t)=Ckⁿt^n-1e^-kt/Γ[n] using data from 15 papers (in total 97 datasets). These functions described well the rates of fungal and bacterial growth, and whole community respiration after rewetting, resulting in a range of shapes consistent with the idea that soil microbial responses form a continuum between types 1 and 2. The product of growth parameters τ (delay time) and b (growth rate at time τ) allowed separating type 1 and 2 responses better than τ or b alone or than any other parameter describing the growth or respiration response. Thus, the product τ×b could be regarded as an effective index to quantify harshness. This index varied depending on soil and experimental conditions: τ×b increased with rewetting intensity (the difference in soil moisture between dry and wet conditions) and declined with higher pH; moreover, bacteria in carbon-rich soils had lower τ×b and thus perceived lower harshness. These results suggest that both fungi and bacteria facing the challenges of acidic soils are also worse adapted to respond to DRW compared to microbes from near-neutral soils. Carbon-rich soils might instead promote bacterial resilience thanks to the more available resources compared to carbon-poor soils. In conclusion, this study places soil microbial responses to DRW along a continuous gradient from fast to slow recovery as quantified by perceived harshness (which in turn is quantifiable by fitting growth and respiration curves to data). Our results help to predict the microbial carbon allocation to growth and respiration at rewetting across ecosystems and environmental conditions.

Keywords: soil drying and rewetting, microbial resilience, microbial resistance, growth, respiration