Marika Haupt

Spatial variability and temporal trends in water‐use efficiency of European forests

The increasing carbon dioxide (CO2 ) concentration in the atmosphere in combination with climatic changes throughout the last century are likely to have had a profound effect on the physiology of trees: altering the carbon and water fluxes passing through the stomatal pores. However, the magnitude and spatial patterns of such changes in natural forests remain highly uncertain. Here, stable carbon isotope ratios from a network of 35 tree-ring sites located across Europe are investigated to determine the intrinsic water-use efficiency (iWUE), the ratio of photosynthesis to stomatal conductance from 1901 to 2000. The results were compared with simulations of a dynamic vegetation model (LPX-Bern 1.0) that integrates numerous ecosystem and land-atmosphere exchange processes in a theoretical framework. The spatial pattern of tree-ring derived iWUE of the investigated coniferous and deciduous species and the model results agreed significantly with a clear south-to-north gradient, as well as a general increase in iWUE over the 20th century. The magnitude of the iWUE increase was not spatially uniform, with the strongest increase observed and modelled for temperate forests in Central Europe, a region where summer soil-water availability decreased over the last century. We were able to demonstrate that the combined effects of increasing CO2 and climate change leading to soil drying have resulted in an accelerated increase in iWUE. These findings will help to reduce uncertainties in the land surface schemes of global climate models, where vegetation-climate feedbacks are currently still poorly constrained by observational data.

Reduced climate sensitivity of carbon, oxygen and hydrogen stable isotope ratios in tree-ring cellulose of silver fir (Abies alba Mill.) influenced by background SO2 in Franconia (Germany, Central Europe)

The climate sensitivity of carbon (δ(13)C), oxygen (δ(18)O) and hydrogen (δ(2)H) isotope signatures in tree-ring cellulose of Abies alba Mill. from a marginally industrialized area of Franconia (Germany) was analysed for the last 130 years. All isotopes preserve climatic signals up to c. 1950 AD. After 1950 we observe a clear reduction in climate sensitivity of δ(13)C and δ(2)H while δ(18)O - climate relations remain well pronounced. Nevertheless statistical tests implied that SO2 background emissions of West Germany had influenced isotope signatures long before 1950. The relationships between isotope values and concentrations of SO2, dust, O3 and NO2 at the regional level during the period 1979-2006 indicate that δ(13)C and δ(18)O were influenced primarily by SO2. The impact of SO2 on δ(2)H was negligible, but the observed reduction of climate sensitivity may be caused by synergic influences. The results have significant implications if isotope signatures from tree-rings from anthropogenic influenced regions are used to reconstruct past climate.

The construction of oxygen isotope chronologies from tree-ring series sampled at different temporal resolution and its use as climate proxies: statistical aspects

Tree-ring oxygen stable isotope data series from conifers growing on the Dachstein Plateau (Austrian Alps) were selected to demonstrate the applicability of the serial pooling method using shifted 5-year tree-ring blocks for summer temperature reconstruction. The addressed method allows the construction of long isotope chronologies with significant climate correlation and well preserved climate sensitivity applying the irreducible sample replication of five trees. The linear regression model for temperature reconstruction is verifiable and the predicted data are well correlated with instrumental data, especially reproducing the long-term temperature trend. However, the reduced mean variance leads to loss of extreme years, which can be regulated by the combination of one data series in annual resolution with five shifted 5-year block data series. This significantly improves the variance of the mean chronology, sufficiently to identify extremes. Therefore, we recommend the use of mixed data sets as a compromise between essential sample replication and economic considerations.