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Drought legacy affects microbial community trait distributions related to moisture along a savannah grassland precipitation gradient

Cite this dataset

Leizeaga, Ainara et al. (2020). Drought legacy affects microbial community trait distributions related to moisture along a savannah grassland precipitation gradient [Dataset]. Dryad. https://doi.org/10.5061/dryad.r2280gbbn

Abstract

  1. Ecosystem models commonly use stable-state assumptions to predict responses of soil microbial functions to environmental change. However, past climatic conditions can shape microbial functional responses resulting in a “legacy effect”. For instance, exposure to drier conditions in the field may shape how soil microbial communities respond to subsequent drought and drying and rewetting events. 
  2. We investigated microbial tolerance to low moisture levels (“resistance”) and ability to recover after a drying and rewetting (DRW) perturbation (“resilience”) across a steep precipitation gradient in Texas, USA.
  3. Although differences in precipitation regime did not result in differences in resistance and resilience of soil microbes, microbial communities appeared to be generally resilient and resistant across the gradient, suggesting that frequent exposure to drought had characterized the trait distributions of microbial communities. Moreover, microbial communities from historically drier sites used carbon more efficiently during a DRW perturbation suggesting that long-term drought history leaves a legacy effect on microbial functions. This may have been due to an indirect effect of drought caused via precipitation-induced differences in primary productivity, influencing the availability of soil organic matter to microbes. Alternatively, different exposures to drought might have shaped the microbial “readiness” to cope with the DRW disturbance. Microbial community composition was also linked to drought history, but was unrelated to variation in function. 
  4. Synthesis: exposure to drought can have both direct and indirect effects on soil microbial communities, which can result in lasting legacy effects on the functions they control. 

Methods

There are 3 types of data that can be found in this file: 

  1. Soil characterization data such as: C/N ratios, soil organic matter (SOM), soil inorganic carbon (SIC), water holding capacity (WHC), pH, EC, soil texture (% Sand, Clay and Silt), PLFA concentrations and NDVI. 
  2. Primary growth and respiration rate data, for the drying and rewetting (DRW) and the moisture dependence (MD) experiments. The data that is shown is normalized. For the DRW data in the first column the time after rewetting (in hours) is shown, and in the following columns the process rates after rewetting in each one of the soils from the gradiend (indicated by the MAP of the site in the heading of the column). In the MD data sheets in the first columns the moisture level (shown as % of WHC) is shown, and in the following columns the process rates at each one of this soil moistures in each one of the soils from the gradiend (indicated by the MAP of the site in the heading of the column). In the MD data, for each one of the measured processes there are 2 data sheets (rep1 and rep2) since the experiment was repeated twice and the data was then combined. 
  3. Calculations done based in the primary data. For the DRW experiment calculations of cumulative processes and recovery times can be found, as well as the cumulative processes for the continuously moist control soils. For the MD data, the IC 10 and IC 50 (moisture levels at whcih the processes are inhibited by 10% and 50% respectively) values for each one of the processes can be found.