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Abstract Switchgrass (Panicum virgatumL.) 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 CO2remains 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 CO2concentration and light, we measured leaf net photosynthesis of switchgrass under different CO2concentrations and light levels in 2020 and 2021 for each of the five precipitation treatments. We first evaluated four light and CO2response 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 CO2response 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 meanPmaxof five precipitation treatments was 17.6 μmol CO2m−2 s−1, and the ambient treatment tended to have a higherPmax. The +33% treatment had the highestα, and the ambient treatment had lowerθandLCP, higherRd, and relatively lowerLSP. Furthermore, precipitation significantly influenced all model parameters of CO2response. The ambient treatment had the highestPmax, largestα, and lowestθ,Rd, and CO2compensation pointLCP. 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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This content will become publicly available on July 1, 2026
Elevated light and CO2 levels increase photosynthetic rates of diverse snow algal communities from the North Cascades
Summary Microalgae adapted to near‐zero temperatures and high light levels live on snowfields and glaciers worldwide. Snow algae have red‐colored pigments that darken snow surfaces, lowering its albedo and accelerating snowmelt. Despite their importance to the cryosphere, we know little about controls on snow algal productivity and biomass.Here, we characterize photophysiology from diverse natural field‐collected populations of alpine snow algae from the North Cascades of Washington, USA, where the major red‐bloom producing generaChlainomonas,Sanguina, andRosettawere present. We tested short‐term physiological responses of snow algae to light (0–3000 μmol m−2 s−1) and CO2levels (0–1600 ppm), allowing us to determine the saturating light and CO2levels for snow algal community net photosynthesis.All snow algal communities surveyed were adapted to extremely high light levels (3000 μmol m−2 s−1). In addition, photosynthesis rates of all the snow algal communities responded strongly to increasing CO2levels. At current atmospheric CO2levels (420 ppm), snow algal net photosynthesis rates were onlyc.50% saturated.Together, these results suggest the primary productivity of important bloom‐forming snow algal communities in alpine ecosystems will likely rise as atmospheric CO2concentrations increase, regardless of potential changes in available light levels.
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- Award ID(s):
- 2208949
- PAR ID:
- 10612250
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- New Phytologist
- ISSN:
- 0028-646X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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