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