Precipitation changes altered soil heterotrophic respiration, but the underlying microbial mechanisms remain
rarely studied. This study conducted three-year switchgrass (Panicum virgatum L.) mesocosm experiment to
investigate soil heterotrophic respiratory responses to altered precipitation. Five treatments were considered,
including ambient precipitation (P0), two wet treatments (P+33 and P+50: 33% and 50% enhancement relative to P0), and two drought treatments (P-33 and P-50: 33% and 50% reduction relative to P0). The plant’s aboveground biomass (AGB), soil organic carbon (SOC), total nitrogen (TN), microbial biomass carbon (MBC), heterotrophic respiration (Rs), biomass-specific respiration (Rss: respiration per unit of microbial biomass as a reciprocal index of microbial growth efficiency), and extracellular enzymes activities (EEAs) were quantified in soil samples (0–15 cm). Despite significantly different soil moisture contents among treatments, results showed no impact of precipitation treatments on SOC and TN. Increasing precipitation had no effect, but decreasing precipitation significantly reduced plant AGB. Relative to P0, P+33 significantly increased Rs by more than 3-fold and caused no changes in MBC, leading to significantly higher Rss (P < 0.05). P+33 also significantly increased hydrolytic enzyme activities associated with labile carbon acquisition (Cacq) by 115%. The only significant effect of drought treatments was the decreased β-D-cellobiosidase (CBH) and peroxidase (PEO) under P-33. Nonparametric analyses corroborated the strong influences of moisture and CBH on the enhanced precipitation, which stimulated soil respiratory carbon loss, likely driven by both elevated hydrolase activities and reduced microbial growth efficiency. However, the less sensitive drought effects suggested potential microbial tolerance to water deficiency despite depressed plant growth. This study informs the likely decoupled impacts of microbes and plants on soil heterotrophic respiration under changing precipitation in the switchgrass mesocosm experiment.
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This content will become publicly available on May 1, 2025
Photosynthetic responses of switchgrass to light and CO₂ under different precipitation treatments
Switchgrass (Panicum virgatum L.) is a prominent bioenergy crop with robust resilience to environmental stresses. However, our knowledge regarding how precipitation changes affect switchgrass photosynthesis and its responses to light and CO2 remains limited. To address this knowledge gap, we conducted a field precipitation experiment with five different treatments, including -50%, -33%, 0%, +33%, and +50% of ambient precipitation. To determine the responses of leaf photosynthesis to CO2 concentration and light, we measured leaf net photosynthesis of switchgrass under different CO2 concentrations and light levels in 2020 and 2021 for each of the five precipitation treatments. We first evaluated four light and CO2 response models (i.e., rectangular hyperbola model, nonrectangular hyperbola model, exponential model, and the modified rectangular hyperbola model) using the measurements in the ambient precipitation treatment. Based on the fitting criteria, we selected the nonrectangular hyperbola model as the optimal model and applied it to all precipitation treatments, and estimated model parameters. Overall, the model fit field measurements well for the light and CO2 response curves. Precipitation change did not influence the maximum net photosynthetic rate (Pmax) but influenced other model parameters including quantum yield (α), convexity (θ), dark respiration (Rd), light compensation point (LCP), and saturated light point (LSP). Specifically, the mean Pmax of five precipitation treatments was 17.6 μmol CO2 m-2s-1, and the ambient treatment tended to have a higher Pmax. The +33% treatment had the highest α, and the ambient treatment had lower θ and LCP, higher Rd, and relatively lower LSP. Furthermore, precipitation significantly influenced all model parameters of CO2 response. The ambient treatment had the highest Pmax, largest α, and lowest θ, Rd, and CO2 compensation point LCP. Overall, this study improved our understanding of how switchgrass leaf photosynthesis responds to diverse environmental factors, providing valuable insights for accurately modeling switchgrass ecophysiology and productivity.
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- Award ID(s):
- 1900885
- PAR ID:
- 10507247
- Editor(s):
- Long, Steve.
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- GCB bioenergy
- ISSN:
- 1757-1707
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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