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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Parameter sensitivity & model validation 127<br />
availability. O<strong>the</strong>r important parameters are those shap<strong>in</strong>g <strong>the</strong> maximum growth equation<br />
(kG), followed by those describ<strong>in</strong>g <strong>the</strong> response <strong>of</strong> <strong>the</strong> species to drought (kDrT), w<strong>in</strong>ter<br />
temperature (kWiT), and light availability (kL y , kL a , sType).<br />
Even though it was possible to perform a sensitivity analysis that <strong>in</strong>cluded all speciesspecific<br />
parameters <strong>in</strong> FORCLIM, this does not mean that a generalized statement about<br />
<strong>the</strong> sensitivity <strong>of</strong> <strong>the</strong> model to <strong>the</strong> values <strong>of</strong> <strong>the</strong>se parameters can be derived: First, <strong>the</strong><br />
sensitivity <strong>of</strong> <strong>the</strong> model to <strong>the</strong> value <strong>of</strong> a certa<strong>in</strong> parameter is a function <strong>of</strong> <strong>the</strong> abiotic environment<br />
and can not be stated generally from <strong>the</strong> analysis at one s<strong>in</strong>gle site (Airolo).<br />
Second, only <strong>the</strong> effects on <strong>the</strong> steady-state species composition were evaluated. Kercher<br />
& Axelrod (1984) showed that <strong>the</strong> relative sensitivity <strong>of</strong> <strong>the</strong> SILVA model varies along <strong>the</strong><br />
time axis; ecologically speak<strong>in</strong>g, <strong>the</strong> sensitivity <strong>of</strong> a model dur<strong>in</strong>g <strong>the</strong> transient phase may<br />
be just as important as <strong>in</strong> its steady state. Moreover, <strong>the</strong> percentage similarity coefficient<br />
used to compare <strong>the</strong> species compositions is an aggregated <strong>in</strong>dex which is little sensitive<br />
to <strong>the</strong> biomass <strong>of</strong> species with low abundance, thus conceal<strong>in</strong>g part <strong>of</strong> <strong>the</strong> effects <strong>of</strong> <strong>the</strong><br />
changed parameters. It may be concluded that fur<strong>the</strong>r studies on <strong>the</strong> parameter sensitivity<br />
<strong>of</strong> forest gap models would be desirable.<br />
The results from <strong>the</strong> present study agree to a large extent with those from earlier, partial<br />
sensitivity analyses (Kercher & Axelrod 1984, Dale et al. 1988, Leemans 1991), suggest<strong>in</strong>g<br />
that <strong>the</strong> same ecological factors govern <strong>the</strong> dynamics <strong>in</strong> <strong>the</strong> various forest gap<br />
models. Moreover, <strong>the</strong> robustness <strong>of</strong> <strong>the</strong> species composition simulated by <strong>the</strong> FORCLIM<br />
model <strong>in</strong>creases our confidence that <strong>the</strong>se results are not arbitrary and that <strong>the</strong> model produces<br />
reliable hypo<strong>the</strong>ses about <strong>the</strong> near-natural forest vegetation.<br />
5.2 Choice <strong>of</strong> data and experiments for model validation<br />
The term “model validation” is used with various mean<strong>in</strong>gs <strong>in</strong> ecology. Swartzman &<br />
Kaluzny (1987) note that “validation” <strong>in</strong> <strong>the</strong> strict sense is a misnomer: It is impossible to<br />
assess <strong>the</strong> truth <strong>of</strong> a model. We can simply design experiments to <strong>in</strong>crease our confidence<br />
that a model meets its objectives; Swartzman & Kaluzny (1987) term this “model<br />
corroboration”. However, because it is widespread, <strong>the</strong> term “validation” will be used <strong>in</strong><br />
<strong>the</strong> present study as well with <strong>the</strong> follow<strong>in</strong>g def<strong>in</strong>ition: In a validation procedure, <strong>the</strong><br />
performance <strong>of</strong> a model is tested on its agreement with a set <strong>of</strong> observations that are