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 ...
Create successful ePaper yourself
Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.
Discussion 171<br />
F<strong>in</strong>ally, <strong>the</strong> analysis <strong>of</strong> <strong>the</strong> formulation <strong>of</strong> climate-dependent factors <strong>in</strong> forest gap models<br />
revealed that many conventional models implicitly assume a constant climate, and that<br />
model behaviour is sensitive to relax<strong>in</strong>g <strong>the</strong>se assumptions (cf. Bugmann & Fischl<strong>in</strong><br />
1994, Fischl<strong>in</strong> et al. 1994). O<strong>the</strong>r researchers came to similar f<strong>in</strong>d<strong>in</strong>gs us<strong>in</strong>g a different<br />
approach, i.e. by comb<strong>in</strong><strong>in</strong>g conventional forest gap models with detailed biophysical or<br />
physiological submodels for calculat<strong>in</strong>g <strong>the</strong> <strong>in</strong>fluence <strong>of</strong> climatic parameters (Mart<strong>in</strong><br />
1990, 1992, Bonan & van Cleve 1992, Friend et al. 1993). However, <strong>the</strong> fact that a<br />
model is sensitive to <strong>the</strong> formulation <strong>of</strong> a factor is a necessary, but not a sufficient condition<br />
to show that a detailed submodel is required to calculate that factor. The present<br />
study suggests that at least <strong>in</strong> some <strong>in</strong>stances simple yet realistic parametrizations <strong>of</strong><br />
abiotic factors can be developed, and that <strong>the</strong>y improve <strong>the</strong> reliability <strong>of</strong> a model considerably.<br />
Thus, <strong>the</strong> call for detailed biophysical or physiological submodels form<strong>in</strong>g part <strong>of</strong><br />
forest gap models appears not conclusive yet (cf. Bonan 1993).<br />
7.2 Structure and behaviour <strong>of</strong> FORCLIM<br />
The construction <strong>of</strong> FORCLIM as a forest gap model composed <strong>of</strong> three submodels (E –<br />
abiotic environment, P – plant population dynamics, and S – soil organic matter turnover)<br />
provided <strong>the</strong> flexibility to evaluate <strong>the</strong> behaviour <strong>of</strong> each submodel and any desirable<br />
comb<strong>in</strong>ation <strong>of</strong> <strong>the</strong> submodels. This constitutes a dist<strong>in</strong>ct advantage over conventional<br />
forest gap models, where <strong>the</strong> complete model is <strong>the</strong> s<strong>in</strong>gle scope <strong>of</strong> simulation studies.<br />
These analyses revealed that FORCLIM-P on its own does not provide realistic species<br />
compositions under conditions <strong>of</strong> strong environmental stress, e.g. when approach<strong>in</strong>g<br />
<strong>the</strong> alp<strong>in</strong>e and <strong>the</strong> dry timberl<strong>in</strong>e, suggest<strong>in</strong>g that FORCLIM-E is <strong>of</strong> paramount importance<br />
for simulat<strong>in</strong>g forest dynamics under <strong>the</strong>se conditions. The forest gap model FORSKA-2<br />
(Prentice et al. 1993) does not <strong>in</strong>corporate <strong>the</strong> effects <strong>of</strong> a stochastic environment, although<br />
<strong>the</strong> model was designed for boreal and broadleaf forests <strong>of</strong> Scand<strong>in</strong>avia, where<br />
precipitation sums <strong>of</strong>ten are small and drought stress is large. Thus it would be <strong>in</strong>terest<strong>in</strong>g<br />
to <strong>in</strong>vestigate if <strong>the</strong> above f<strong>in</strong>d<strong>in</strong>gs are restricted to forests <strong>in</strong> <strong>the</strong> European Alps, or<br />
whe<strong>the</strong>r <strong>the</strong>y apply also to o<strong>the</strong>r areas.<br />
The <strong>in</strong>fluence <strong>of</strong> FORCLIM-P on <strong>the</strong> amount <strong>of</strong> litter and humus simulated by FORCLIM-<br />
S is small. This may partly be due to <strong>the</strong> fact that <strong>the</strong> quality <strong>of</strong> a large fraction <strong>of</strong> <strong>the</strong> litter<br />
produced by FORCLIM-P does not vary with <strong>the</strong> species produc<strong>in</strong>g it, i.e. twig, wood,<br />
and root litter, which constitute up to 90% <strong>of</strong> <strong>the</strong> total litter production. Thus, a more detailed<br />
modell<strong>in</strong>g <strong>of</strong> litter production would be desirable; unfortunately, <strong>the</strong> data base for