On the Ecology of Mountainous Forests in a Changing Climate: A ...
On the Ecology of Mountainous Forests in a Changing Climate: A ...
On the Ecology of Mountainous Forests in a Changing Climate: A ...
You also want an ePaper? Increase the reach of your titles
YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.
202 Appendix<br />
80% <strong>of</strong> <strong>the</strong> foliage weight obta<strong>in</strong>ed for group 2 (Tab. A-3). The relationships between<br />
foliage weight and diameter as well as a comparison <strong>of</strong> <strong>the</strong> new parametrization with <strong>the</strong><br />
one used by Kienast (1987) are plotted <strong>in</strong> Fig. A-1.<br />
Tab. A-3: Regressions <strong>of</strong> foliage wet weight (L) vs. diameter at breast height (D) for several species<br />
groups as derived from <strong>the</strong> data <strong>in</strong> Burger (1945-53), where L = kA 1·D kA 2. L<strong>in</strong>ear regressions were calculated<br />
based on <strong>the</strong> transformation Ln(L) = Ln(kA 1 ) + kA 2·Ln(D). n denotes sample size.<br />
Species kA 1 kA 2 r 2 group no. n<br />
Abies alba, Picea excelsa, P<strong>in</strong>us cembra, P. montana 0.23 1.56 0.93 5 130<br />
P. silvestris 0.17 1.40 0.76 4 210<br />
Fagus silvatica, Quercus spp. 0.06 1.70 0.93 3 144<br />
Larix decidua 0.10 1.43 0.87 2 99<br />
Betula sp., Salix sp. (no data) 0.08 1.43 – 1 –<br />
L (kg)<br />
Picea: foliage data<br />
gFolW (kg)<br />
40.00<br />
300<br />
35.00<br />
30.00<br />
25.00<br />
1<br />
2<br />
200<br />
20.00<br />
3<br />
15.00<br />
10.00<br />
5.00<br />
0.00<br />
0 20 40 60 80<br />
D (cm)<br />
4<br />
5<br />
100<br />
0<br />
0<br />
20<br />
40<br />
60<br />
80<br />
Kienast’s formula<br />
regression, group 5<br />
measurement<br />
100 120 D (cm)<br />
Fig. A-1: Left: Relationship between foliage dry weight (gFolW) and diameter at breast<br />
height (D) <strong>of</strong> <strong>the</strong> species groups def<strong>in</strong>ed <strong>in</strong> Tab. A-3. Right: Measured foliage fresh weight<br />
<strong>of</strong> Picea excelsa (dots), <strong>the</strong> FORECE parametrization (Kienast 1987) and <strong>the</strong> parametrization<br />
for group 5 derived from <strong>the</strong> orig<strong>in</strong>al Burger data (Tab. A-3).<br />
Group<strong>in</strong>g <strong>of</strong> <strong>the</strong> species<br />
To assign every species to one <strong>of</strong> <strong>the</strong> five groups def<strong>in</strong>ed above (Tab. A-3), <strong>the</strong> rank<strong>in</strong>g<br />
<strong>of</strong> <strong>the</strong> species with respect to <strong>the</strong>ir capability <strong>of</strong> cast<strong>in</strong>g shade from Ellenberg (1986) and<br />
<strong>the</strong> values <strong>of</strong> <strong>the</strong> parameters A1 and A2 used by Kienast (1987) were consulted (Tab. A-<br />
4). These data sources allowed to rank <strong>the</strong> 30 tree species with respect to <strong>the</strong> sType parameter.<br />
kDm, kHm & kAm parameters<br />
Probably <strong>the</strong> best way to determ<strong>in</strong>e <strong>the</strong>se three parameters would be based on diameter,<br />
height, and age distributions <strong>of</strong> trees <strong>in</strong> old-growth forests that are not subject to strong<br />
environmental stress. A <strong>the</strong>oretical distribution could be fitted to such data, e.g. an exponential<br />
distribution <strong>in</strong> <strong>the</strong> case <strong>of</strong> maximum age (cf. Eq. 3.29f. <strong>in</strong> section 3.3.1), and <strong>the</strong><br />
parameters could be estimated from <strong>the</strong>se distributions. However, data from old-growth<br />
European forests is scarce (e.g. Leibundgut 1993). Moreover, it would be difficult to obta<strong>in</strong><br />
<strong>the</strong>se data for many tree species, let alone for all <strong>the</strong> 30 species used under European<br />
conditions <strong>in</strong> FORCLIM. Therefore, a simpler and necessarily less accurate approach had<br />
to be adopted to derive an estimate <strong>of</strong> <strong>the</strong>se parameters.