On the Ecology of Mountainous Forests in a Changing Climate: A ...

The forest model FORCLIM 55
the establishment and growth of trees and the decomposition of soil organic matter (cf.
Prentice & Helmisaari 1991, Prentice et al. 1993).
GENERATION OF WEATHER DATA
The monthly means of temperature (T m,y,l ) and precipitation (P m,y,l ) are sampled
stochastically from their respective long-term statistics (Fig. 3.4). It is assumed that both
variables are distributed normally around their long-term means. This assumption is met
better for temperature than for precipitation (Fliri 1974). In principle, a different statistical
distribution (such as the γ distribution, Bonan et al. 1990) could be fitted on a site-by-site
basis to the precipitation data, and sampling from such a distribution would provide more
realistic precipitation data for the current climate. However, there is no evidence that the
assumption of normality of monthly precipitation sums falls short relative to the sensitivity
of forest gap models; moreover, all the parameters of more complicated distributions
probably change with a changing climate, and it is more difficult to generate consistent
scenarios for the parameters of complicated distributions than for those of the simple
normal distribution. Thus, the assumption of normality is used for sampling both temperature
and precipitation data in FORCLIM-E.
Warm, sunny summer months tend to be dry, whereas cool, cloudy ones often are wet.
In other words, the temperature and precipitation data are cross-correlated. It may be important
to take this phenomenon into account when modelling the water balance of the
soil: For example, if the evaporative demand in a given month is large due to high temperatures,
then the soil water content will be reduced to a larger extent if there is little
rainfall at the same time; this effect is not negligible even if the correlation is moderate
(|r| < 0.64, cf. Appendix III), which was used as an argument against modelling the
cross-correlation (Kräuchi & Kienast 1993). Thus the cross-correlation between monthly
temperature and precipitation data is modelled explicitly in FORCLIM (Fig. 3.4).
BIOCLIMATIC VARIABLES
Winter minimum temperature (uWiT)
Based on the global data set by Müller (1982), Prentice et al. (1992) showed that there is
a good correlation between the absolute minimum temperature and the average temper-