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Updated: Mar 1, 2026

Simulating Temperature in a Soil Incubation Experiment
Published on: October 28, 2022
Acclimation of light and dark respiration to experimental and seasonal warming are mediated by changes in leaf
K Y Crous1, G Wallin2, O K Atkin3
1Hawkesbury Institute for Environment, Western Sydney University, Hawkesbury Campus, Locked Bag 1797, Penrith, NSW 2751, Australia.
Abstract:
Quantifying the adjustments of leaf respiration in response to seasonal temperature variation and climate warming is crucial because carbon loss from vegetation is a large but uncertain part of the global carbon cycle. We grew fast-growing Eucalyptus globulus Labill. trees exposed to +3 °C warming and elevated CO2 in 10-m tall whole-tree chambers and measured the temperature responses of leaf mitochondrial respiration, both in light (RLight) and in darkness (RDark), over a 20-40 °C temperature range and during two different seasons. RLight was assessed using the Laisk method. Respiration rates measured at a standard temperature (25 °C - R25) were higher in warm-grown trees and in the warm season, related to higher total leaf nitrogen (N) investment with higher temperatures (both experimental and seasonal), indicating that leaf N concentrations modulated the respiratory capacity to changes in temperature. Once differences in leaf N were accounted for, there were no differences in R25 but the Q10 (i.e., short-term temperature sensitivity) was higher in late summer compared with early spring. The variation in RLight between experimental treatments and seasons was positively correlated with carboxylation capacity and photorespiration. RLight was less responsive to short-term changes in temperature than RDark, as shown by a lower Q10 in RLight compared with RDark. The overall light inhibition of R was ∼40%. Our results highlight the dynamic nature of leaf respiration to temperature variation and that the responses of RLight do not simply mirror those of RDark. Therefore, it is important not to assume that RLight is the same as RDark in ecosystem models, as doing so may lead to large errors in predicting plant CO2 release and productivity.
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