Modeling the biogeochemistry of sulfur in beech (Fagus sylvatica L.) stands of the Vienna Woods.

In this article, we describe the setup and the application of a novel Sulfur Dynamics Model (SDM), with the aim to identify and quantify processes, which are crucial for the understanding of the biogeochemical sulfur (S) cycle of forest ecosystems. The simulator takes into account abiotic processes as well as biotic interactions between atmosphere, plant and soil. We applied the model to two Austrian beech stands where deposition of S and soil solution chemistry were monitored intensively over a two-year period. Under consideration of high historic loads and the more recent recession of atmospheric S deposition, we found a suitable model configuration where it was possible to assign both intra-annual fluctuations of the SO4-S in soil solution and long-time trends in the stream discharge to specific S transformation processes. We identified the interplay of microbial immobilization (the microbial conversion of solute sulfate to organic soil S) and mineralization as key driver of short-term fluctuations in the soil solution. In the long term, the delayed release of historically accumulated S is driven mainly by the slow mineralization of S rich plant biomass, recalcitrant to decomposition. Adsorption and desorption processes seem to play only a negligible role on our investigated stands. We conclude that our proposed model which is based on the current understanding of S biogeochemistry is sufficient to describe S dynamics on the investigated forest stands. The code file (SAS) for all model functions will be provided by the authors after request.

The impact of rising temperatures on water balance and phenology of European beech (Fagus sylvatica L.) stands.

In this article, we outline the set-up and the application of an eco-hydrological box model, with the aim to describe the water balance of deciduous (Fagus Sylvatica L.) forest stands. The water balance model (WBM) uses standard meteorological parameters as input variables and runs on a daily time step. It consists of two modules. The aboveground module (1) comprises routines for fog precipitation generation, precipitation interception and snowfall/snowmelt dynamics. Covered belowground processes (2) are bypass flow, percolation, soil evaporation and transpiration, where the latter two processes are considered separately. Preceding to the WBM, a routine is introduced, specifying the intra-annual foliage dynamics of beech. Emphasis is also laid on the inter-annual variation of beech phenology. Leaf sprouting and leaf senescence are calculated as functions of day-length and air temperature. The WBM was applied to four European beech dominated forest stands in the northeastern part of Austria. They are located on a gradient of declining annual precipitation (from west to east). The two easterly sites are located close to the (dry) limit of the natural distribution of beech. Records of soil moisture were used for the adjustment of 26 parameters. On all sites the calibration process (simulated annealing) delivered good predictions of soil moisture (Nash-Sutcliffe efficiency≥ 0.925). Then, the obtained parameterization was used to apply different scenarios of global warming. The temperature was increased step-wisely up to 4 °C. All scenarios were run (1) with present phenological conditions and (2) with phenology responding to higher temperatures. This way, we wanted to assign the effect of higher temperatures and longer growing seasons on the water dynamics of the forest stands. A warming of 1 °C corresponded roughly to an elongation of the growing season of 4.5 days, where the start of the growing season was affected more strongly than the end. Apparently, higher temperatures led to drier soils. The strongest change was observed in early summer, also amplified by an earlier start of the growing season. Rising temperatures led to lower export fluxes of liquid water, simultaneously increasing evapotranspiration (ET). The gain in ET was almost entirely assignable to increased soil evaporation. Drier soils led to a sharp depression of transpiration during summer months. This decline was compensated by the effect of elongated growing seasons. The risk of severe drought was increased by higher temperatures, but here the contribution of growing season length was negligible. Drier soils seem to hamper the stands' productivity. For all warming scenarios, the estimated increase of the gross primary production, caused by longer periods of assimilation, is nullified by the effect of soil water deficit in mid-summer.

A new approach to predict soil temperature under vegetated surfaces.

In this article, the setup and the application of an empirical model, based on Newton's law of cooling, capable to predict daily mean soil temperature (Tsoil) under vegetated surfaces, is described. The only input variable, necessary to run the model, is a time series of daily mean air temperature. The simulator employs 9 empirical parameters, which were estimated by inverse modeling. The model, which primarily addresses forested sites, incorporates the effect of snow cover and soil freezing on soil temperature. The model was applied to several temperate forest sites, managing the split between Central Europe (Austria) and the United States (Harvard Forest, Massachusetts; Hubbard Brook, New Hampshire), aiming to cover a broad range of site characteristics. Investigated stands differ fundamentally in stand composition, elevation, exposition, annual mean temperature, precipitation regime, as well as in the duration of winter snow cover. At last, to explore the limits of the formulation, the simulator was applied to non-forest sites (Illinois), where soil temperature was recorded under short cut grass. The model was parameterized, specifically to site and measurement depth. After calibration of the model, an evaluation was performed, using ~50 % of the available data. In each case, the simulator was capable to deliver a feasible prediction of soil temperature in the validation time interval. To evaluate the practical suitability of the simulator, the minimum amount of soil temperature point measurements, necessary to yield expedient model performance was determined. In the investigated case 13-20 point observations, uniformly distributed within an 11-year timeframe, have been proven sufficient to yield sound model performance (root mean square error <0.9 °C, Nash-Sutcliffe efficiency >0.97). This makes the model suitable for the application on sites, where the information on soil temperature is discontinuous or scarce.