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

158 Chapter 6
Finally, most climate scenarios give us an indication about what the change in a given
weather variable will be by a certain point in the future. However, in most scenarios it is
not known how this change will be realized. Most impact studies so far have assumed
that climate changes linearly (Solomon 1986, Pastor & Post 1988, Kienast 1991); other
authors have studied the response of forest models to an instantaneous climatic change,
i.e. its step response (Fischlin et al. 1994, Bugmann & Fischlin 1994). Thus, there arises
the question how sensitive the behaviour of forest gap models is to the assumptions on
the nature of transient climatic change.
6.2.1 Material & methods
Forest models
Five forest gap models are used in this study: The first model, FORECE (Kienast 1987),
is a conventional gap model that was analyzed in detail in chapter 2. The second model,
FORCLIM 1.1 (Bugmann & Fischlin 1994), is a simplified descendant of FORECE and
comprises only the most fundamental ecological processes (cf. section 2.3.1); the formulation
of climatic factors in FORCLIM 1.1 is done in the same way as in FORECE. The
third model, FORCLIM 1.3 (Bugmann & Fischlin 1994), was developed from FORCLIM
1.1 by altering the mathematical formulations of the climatic factors (cf. section 2.3.2 and
Fischlin et al. 1994). The fourth model, FORCLIM-E/P, is one variant of the model developed
in chapter 3; it differs from FORCLIM 1.3 concerning the formulation of ecological
factors and of climatic influences. The last model is FORCLIM-E/P/S, which incorporates
also belowground carbon and nitrogen turnover (chapter 3).
Study sites and steady state climate scenarios
Six sites were selected along a climatological and at the same time altitudinal gradient,
ranging from above the current alpine timberline to central alpine valleys close to the dry
timberline. In a previous study of possible impacts of climatic change on forests, Kienast
(1991) presented simulation results from the sites St. Gotthard, Airolo, and Sion along
with results from 15 other sites. To allow for a comparison of the results from the
Kienast (1991) study with the ones obtained here, these three sites will be used as well.
Gyalistras et al. (1994) developed a methodology to relate large-scale temperature and
pressure anomalies to local weather anomalies by means of principal component analysis
and canonical correlation analysis (“Downscaling”). Based on the results obtained by this
technique for the sites Bever, Davos, and Bern, Bugmann & Fischlin (1994) performed