Ozone (O3 ) damage to leaves can reduce plant photosynthesis, which suggests that declines in ambient O3 concentrations ([O3 ]) in the United States may have helped increase gross primary production (GPP) in recent decades. Here, we assess the effect of long-term changes in ambient [O3 ] using 20 years of observations at Harvard forest. Using artificial neural networks, we found that the effect of the inclusion of [O3 ] as a predictor was slight, and independent of O3 concentrations, which suggests limited high-frequency O3 inhibition of GPP at this site. Simulations with a terrestrial biosphere model, however, suggest an average long-term O3 inhibition of 10.4% for 1992-2011. A decline of [O3 ] over the measurement period resulted in moderate predicted GPP trends of 0.02-0.04 μmol C m-2 s-1 yr-1 , which is negligible relative to the total observed GPP trend of 0.41 μmol C m-2 s-1 yr-1 . A similar conclusion is achieved with the widely used AOT40 metric. Combined, our results suggest that ozone reductions at Harvard forest are unlikely to have had a large impact on the photosynthesis trend over the past 20 years. Such limited effects are mainly related to the slow responses of photosynthesis to changes in [O3 ]. Furthermore, we estimate that 40% of photosynthesis happens in the shade, where stomatal conductance and thus [O3 ] deposition is lower than for sunlit leaves. This portion of GPP remains unaffected by [O3 ], thus helping to buffer the changes of total photosynthesis due to varied [O3 ]. Our analyses suggest that current ozone reductions, although significant, cannot substantially alleviate the damages to forest ecosystems.
Keywords: artificial neural networks; decadal trend; deciduous forest; gross primary production; ozone inhibition; photosynthesis; stomatal conductance; terrestrial biosphere model.
© 2016 John Wiley & Sons Ltd.