title: Limited effect of ozone reductions on the 20-year photosynthesis trend at Harvard forest.
abstract: Ozone (O3) damage to leaves can reduce plant photosynthesis, which suggests that declines in ambient O3concentrations ([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 O3concentrations, which suggests limited high-frequency O3inhibition of GPP at this site. Simulations with a terrestrial biosphere model, however, suggest an average long-term O3inhibition 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-2s-1yr-1, which is negligible relative to the total observed GPP trend of 0.41 μmol C m-2s-1yr-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.
authors.affiliation: School of Forestry and Environmental Studies, Yale University, 195 Prospect Street, New Haven, CT, 06511, USA. xu.yue@yale.edu.|Climate Change Research Center, Chinese Academy of Sciences, Beijing, 100029, China. xu.yue@yale.edu.
authors.forename: Xu
authors.initials: X
authors.lastname: Yue
authors.affiliation: Lawrence Berkeley National Lab, Berkeley, CA, 94720, USA.|Department of Biological Sciences, Macquarie University, Sydney, NSW, 2109, Australia.
authors.forename: Trevor F
authors.identifier: 0000-0002-7579-7494
authors.initials: TF
authors.lastname: Keenan
authors.affiliation: Department of Earth and Planetary Sciences, School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA.
authors.forename: William
authors.identifier: 0000-0002-1042-8452
authors.initials: W
authors.lastname: Munger
authors.affiliation: School of Forestry and Environmental Studies, Yale University, 195 Prospect Street, New Haven, CT, 06511, USA.
authors.forename: Nadine
authors.initials: N
authors.lastname: Unger
mesh_terms: D005544:Forecasting; D065928:Forests; D016571:Neural Networks, Computer; D010126:Ozone; D010788:Photosynthesis; D018515:Plant Leaves; D014481:United States
chemical_list: D010126:Ozone
keywords: artificial neural networks; decadal trend; deciduous forest; gross primary production; ozone inhibition; photosynthesis; stomatal conductance; terrestrial biosphere model