Influence of Soil Type on the Effects of Elevated Atmospheric CO2 and N Deposition on the Water Balance and Growth of a Young Spruce and Beech Forest

Sixteen open-top chambers, each equipped with two non-weighablegravity-drained lysimeter compartments, were used to investigate the impacts of elevated atmospheric carbon dioxide (CO2) concentration and nitrogen (N) deposition on the water relations and growth of young model forest ecosystems on two different types of soils. The same vegetation of a mixed spruce and beech overstorey and various herbs in the understorey was planted in all treatments on both soils. The soils were repacked on top of a drainage layer. Four combinations of treatments were applied in four replicates each: ambient (370 cm3 m-3) CO2 + low (7 kg N ha-1 a-1) N deposition, ambient CO2 + high(70 kg N ha-1 a-1) N deposition, elevated (590 cm3 m-3) CO2 + low N deposition, and elevated CO2 + high N deposition. After canopy closure, treatment effects on evapotranspiration and growth during the third year of study were very different for the two soils.On the acidic sandy loam, elevated CO2 enhanced growth(leaf biomass +21%, roots +27%) at reduced evapotranspiration (–9%). High N deposition increased aboveground growth even more strongly (+50%), but also increased evapotranspiration (+16%). Together, elevated CO2 and high N had a more than additive fertilizer effect on growth, while their effects on evapotranspirationcompensated. On the calcareous loamy sand, elevated CO2not only tended to enhance growth (leaf biomass +17%, roots +20%), but also increased evapotranspiration (+5%).On this soil, aboveground growth was stimulated by N only incombination with elevated CO2, but less than on the acidic soil, while evapotranspiration (–6.5%) and root growth into the subsoil (–54%) were decreased by increased N deposition at both CO2 concentrations, in contrast to the N treatments on the acidic sandy loam. The influence of the soil on the observed ecosystem responses canbe interpreted in terms of the concept of optimal resource allocation.