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

8 Chapter 1
1916, 1928, 1936, Margalef 1968, Odum 1969). According to this concept, ecosystems
possess “emergent” properties that can not be predicted from the structure and behaviour
of lower organizational levels such as populations. The notion of a stable, homeostatic
climax community is central to the Clementsian view of vegetation dynamics (Shugart
1984).
A fundamentally different view of forest succession was proposed by Gleason (1917,
1927, 1939), Jones (1945), and in the classic paper by Watt (1947). Their individualistic
(reductionist) theory stresses the importance of population dynamics and competition
between organisms, and it acknowledges the nonequilibrium nature of vegetation at small
scales (Drury & Nisbet 1973, Connell & Slatyer 1977, Bormann & Likens 1979, Pickett
& White 1985, Remmert 1991). The essential concept is that a forest can be abstracted as
a mosaic of patches, a patch being the area dominated by a canopy tree. With its death,
the environment is radically altered, leading to a wave of seedling establishment and the
release of suppressed trees. In the simplest case, one of the competing trees comes to
dominate the canopy, and the cycle repeats (Shugart 1984). The notion of cyclical change
in plant communities, the explicit consideration of spatial patterns and the importance of
the life history characteristics of the species involved can be considered as the cornerstones
of the “Gleasonian” view of forest dynamics.
Forest gap models like JABOWA (Botkin et al. 1972a,b) adopt an individualistic view of
the forest ecosystem and simulate the establishment, growth, and death of individual trees
on small forest patches (typically 0.01-0.1 ha) as a mixture of deterministic and stochastic
processes. However, these models also take into account processes that operate at the
scale of the “Clementsian” ecosystem, such as the effects of canopy closure and soil resources
on tree growth. To obtain forest development on the ecosystem level, the successional
patterns of many independent patches are averaged. In these models, tree establishment
is a stochastic function of climatic (abiotic) as well as biotic factors, such as temperature,
shading, and the amount of leaf litter present. The growth of each tree is simulated
in a deterministic manner by decreasing the maximum potential growth rate at its respective
age by factors that are less than optimum. Examples of growth factors considered are
the growing-season temperature, soil moisture, and light availability. The equation for
maximum growth has a sigmoid shape and is based on the assumption that annual gross
productivity is proportional to the amount of sunlight the leaves receive. Tree death is determined
stochastically with a function based on the assumption of a constant mortality
rate throughout tree life. Moreover, most gap models include a stress-induced mortality
function that kills trees if they attain less than a certain minimum growth rate. Shugart