期刊
GLOBAL CHANGE BIOLOGY
卷 22, 期 11, 页码 3750-3759出版社
WILEY
DOI: 10.1111/gcb.13300
关键词
artificial neural networks; decadal trend; deciduous forest; gross primary production; ozone inhibition; photosynthesis; stomatal conductance; terrestrial biosphere model
资金
- Yale University
- Macquarie University
Ozone (O-3) damage to leaves can reduce plant photosynthesis, which suggests that declines in ambient O-3 concentrations ([O-3]) 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 [O-3] using 20 years of observations at Harvard forest. Using artificial neural networks, we found that the effect of the inclusion of [O-3] as a predictor was slight, and independent of O-3 concentrations, which suggests limited high-frequency O-3 inhibition of GPP at this site. Simulations with a terrestrial biosphere model, however, suggest an average long-term O-3 inhibition of 10.4% for 1992-2011. A decline of [O-3] over the measurement period resulted in moderate predicted GPP trends of 0.02-0.04 mu mol C m(-2) s(-1) yr(-1), which is negligible relative to the total observed GPP trend of 0.41 mu mol 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 [O-3]. Furthermore, we estimate that 40% of photosynthesis happens in the shade, where stomatal conductance and thus [O-3] deposition is lower than for sunlit leaves. This portion of GPP remains unaffected by [O-3], thus helping to buffer the changes of total photosynthesis due to varied [O-3]. Our analyses suggest that current ozone reductions, although significant, cannot substantially alleviate the damages to forest ecosystems.
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