Environmental controls on light inhibition of respiration and leaf and canopy daytime carbon exchange in a temperate...

Uncertainty in the estimation of daytime ecosystem carbon cycling due to the light inhibition of leaf respiration and photorespiration, and how these small fluxes vary through the growing season in the field, remains a confounding element in calculations of gross primary productivity and ecosystem respiration. Our study focuses on how phenology, short-term temperature changes and canopy position influence leaf-level carbon exchange in Quercus rubra L. (red oak) at Harvard Forest in central Massachusetts, USA. Using leaf measurements and eddy covariance, we also quantify the effect of light inhibition on estimates of daytime respiration at leaf and ecosystem scales. Measured rates of leaf respiration in the light and dark were highest in the early growing season and declined in response to 10-day prior air temperatures (P < 0.01), evidence of within-season thermal acclimation. Leaf respiration was significantly inhibited by light (27.1 ± 2.82% inhibited across all measurements), and this inhibition varied with the month of measurement; greater inhibition was observed in mid-summer leaves compared with early- and late-season leaves. Increases in measurement temperature led to higher rates of respiration and photorespiration, though with a less pronounced positive effect on photosynthesis; as a result, carbon-use efficiency declined with increasing leaf temperature. Over the growing season when we account for seasonally variable light inhibition and basal respiration rates, our modeling approaches found a cumulative 12.9% reduction of leaf-level respiration and a 12.8% reduction of canopy leaf respiration, resulting in a 3.7% decrease in total ecosystem respiration compared with estimates that do not account for light inhibition in leaves. Our study sheds light on the environmental controls of the light inhibition of daytime leaf respiration and how integrating this phenomenon and other small fluxes can reduce uncertainty in current and future projections of terrestrial carbon cycling.