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

24 Chapter 2
of the samples and the median (med), which characterizes their location. The quotient
given in Eq. 2.2 was used for this characterization. Theoretically, q should converge toward
a non-zero value as the sample size approaches infinity.
q = p 90 – p 10
med
(2.2)
To perform the analysis, the site Bern on the Swiss plateau (cf. Appendix III) was
chosen because it is representative of a large area of the Swiss Plateau. The site-specific
parameters were taken from Kienast (1987). The q value was calculated for three species
each playing a key role at this site, i.e. Abies alba with a low abundance at the beginning
and intermediate abundance during later stages; Fagus silvatica with high abundance at
the beginning and intermediate abundance after about 600 years; and Ulmus scabra, a
species with low abundance throughout the succession (Kienast 1987). Three points in
time were selected for the analysis, i.e. the simulation years 400, 800 and 1200. By doing
so, temporal autocorrelation becomes negligible (cf. section 2.2.1).
25
Year 100
70
Year 500
Frequency
20
15
10
5
60
50
40
30
20
10
0
0 50 100 150 200 250 300
Biomass (t/ha)
0
0 50 100 150 200 250 300
Biomass (t/ha)
Fig. 2.8: Distribution of the biomass of Fagus silvatica from 200 simulation runs of the
FORECE model V1.0 at the site Bern in the years 100 (left) and 500 (right).
Since the original FORECE model (Kienast 1987) does not allow for performing more
than 50 simulation runs at a time, the FORECE model version 1.0 as translated to the
programming language Modula-2 (see section 2.1) was used to perform 4'000 simulation
runs on an Apple Macintosh II computer. From this data base n random samples were
taken to calculate the quotient from Eq. 2.2. The procedure was repeated 10 times for
each sample size (n = 5, 10, 25, 50, 75, 100, 125, 150, 200, 250, 300, 350, 400). Ad-