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

Behaviour of FORCLIM along a transect in the European Alps 119
both on the number of species participating in the succession as well as the specific role
of those species (Shugart 1984).
The forest simulated by FORCLIM-E/P at the site Bern is among those with the highest
species diversity (Fig. 4.12). Since the average value of the PS coefficients tends to increase
with decreasing diversity, this site may be considered as a “worst case” of the statistical
properties of the PS coefficients. Hence, two steady states of low-elevation,
species-rich forests that are estimated using n = 200 and ∆t = 150 years are significantly
(95%) different from each other if PS < 0.85 (Tab. 4.6). The less species are present,
the more the lower confidence limit increases; for species-poor forests (typically at higher
elevations such as Davos), the lower end of the confidence interval (95%) increases to
≈0.92 (Tab. 4.6). Thus, also with respect to the size of this confidence limit the design
of simulation experiments with n = 200 points and ∆t = 150 years appears to be appropriate.
The simulation time required on a Macintosh Quadra 700 computer for simulating 200
patches of 1200 years each with the FORCLIM-E/P model is 133 minutes. On the other
hand, estimating the steady state with n = 200 and ∆t = 150 years and discarding the first
1000 years of the simulation requires to simulate one patch during 31'000 years, which
corresponds to 17 minutes of simulation time, or 12.8% of the time necessary for the
transient experiment. Thus, the method presented above is quite efficient if one desires to
estimate the steady-state species composition of forest gap models.
Tab. 4.8: Averages (µ) and coefficients of variation (CV) of 400 species-specific steady-state biomass
estimates at the site Bern (n = 200, ∆t = 150).
Variable µ [t/ha] CV
total biomass 392.6 2.4%
Fagus silvatica 151.1 8.8%
Abies alba 128.9 9.5%
Acer pseudoplatanus 17.8 26.3%
Ulmus scabra 17.3 24.1%
Quercus petraea 17.3 59.8%
Picea excelsa 11.3 35.1%
Acer platanoides 10.4 20.0%
Populus nigra 9.6 26.4%
Fraxinus excelsior 6.5 30.3%
Quercus robur 5.6 122.7%