An evaluation of ozone exposure metrics for a seasonally drought-stressed ponderosa pine ecosystem

  • Sites: US-Blo
  • Panek, J. A., Kurpius, M. R., Goldstein, A. H. (2002) An evaluation of ozone exposure metrics for a seasonally drought-stressed ponderosa pine ecosystem, Environmental Pollution, 117(1), 93-100. https://doi.org/10.1016/S0269-7491(01)00155-5
  • Funding Agency: Environmental Protection Agency STAR Ecosystem Indicators Program (Award No. R826601), the University of California President's Postdoctoral Fellowship Program, and the Hellman Foundation

  • Ozone stress has become an increasingly significant factor in cases of forest decline reported throughout the world. Current metrics to estimate ozone exposure for forest trees are derived from atmospheric concentrations and assume that the forest is physiologically active at all times of the growing season. This may be inaccurate in regions with a Mediterranean climate, such as California and the Pacific Northwest, where peak physiological activity occurs early in the season to take advantage of high soil moisture and does not correspond to peak ozone concentrations. It may also misrepresent ecosystems experiencing non-average climate conditions such as drought years. We compared direct measurements of ozone flux into a ponderosa pine canopy with a suite of the most common ozone exposure metrics to determine which best correlated with actual ozone uptake by the forest. Of the metrics we assessed, SUM0 (the sum of all daytime ozone concentrations>0) best corresponded to ozone uptake by ponderosa pine, however the correlation was only strong at times when the stomata were unconstrained by site moisture conditions. In the early growing season (May and June), SUM0 was an adequate metric for forest ozone exposure. Later in the season, when stomatal conductance was limited by drought, SUM0 overestimated ozone uptake. A better metric for seasonally drought-stressed forests would be one that incorporates forest physiological activity, either through mechanistic modeling, by weighting ozone concentrations by stomatal conductance, or by weighting concentrations by site moisture conditions.


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