Rising tropospheric ozone (O3) concentrations pose a critical threat to forest ecosystems. A stomatal flux-based risk evaluation methodology at leaf level was established recently in the context of the Convention on Long-Range Transboundary Air Pollution. This study demonstrates improvement and validation of the stomatal flux–effect approach for European beech and Norway spruce with results from the 8-year free-air O3 enrichment experiment at Kranzberg Forest (Germany). Based on the recommended O3/water vapour diffusivity ratio of 0.663, provisional corrected flux–effect functions for beech and spruce were deduced. Comparison of observed and modelled loss in annual growth under twice-ambient O3 exposure relative to whole-stem productivity under ambient O3 seems to confirm the Convention’s leaf-level stomatal flux approach and the associated response function for Norway spruce up to twice-ambient O3 exposure. For European beech, it must be emphasized that the Convention’s methodology may underestimate the risk for loss in whole-stem productivity.

Meteorological variables affect composition, structure, growth, health, and dynamics of forest ecosystems. The measurement of meteorological data at forest monitoring plots is essential for the interpretation of climate change effects. Within an ecological monitoring network, standard meteorological variables such as precipitation, air temperature, relative humidity, solar radiation, wind velocity, and direction should be measured. These variables are essential for the calculation of total deposition of air pollutants, for the interpretation of biological processes or for the derivation of water budgets and percolation from the rooting zone. Additional variables of interest are soil temperature, stand precipitation, and soil moisture. The magnitude and changes in time of the meteorological variables can be assessed as explanatory factors for other observations made in forest ecological monitoring. A detailed description of different methods is given. As an example for an integrated analysis, the application of meteorological data in water budget modeling is described and results of a pilot study are shown.