Ecological Succession and Community Dynamics - Ecological Systems - page 49

commercial forests) in the mid-1960s. Their computational innovation was being
independently paralleled in other fields, notably astronomy, physics, and several
engineering sciences [ 55 , 56 ]. The early individual-tree-based forest models were
quite complex. For example, the competition among individual trees was typically
simulated by crown interactions involving the 3-dimensional geometry of each
individual tree crown for all the trees in a stand; [ 57 ] the growth of the tree trunks of
each tree were often simulated at multiple heights; [ 58 , 59 ] a tree's mortality was
related to 2- or 3-dimensional crown pruning among trees [ 60 ].
For vegetation dynamics, the earliest individual-based model of forests [ 57 ] was
developed for Douglas-fir ( Pseudotsuga menziesii ) applications and there were
soon several similar models developed as doctoral dissertations at several Schools
of Forestry [ 37 ]. These early individual-based models of forests were inordinately
complex, perhaps because they were applied to tree-spacing problems in even-aged
and single-species forests or forest plantations. However, a most detailed early
model [ 61 ] with multiple tree species, tree interactions based on interacting three-
dimensional crown geometry, mapping exact locations of trees, calculating the
dispersion of seed-fall based on seed morphology, etc., exceeds the complexity of
almost all of the individual-based models of today.
As noted above, Watt noted that to understand succession one must account for
the results of individual plants interacting with one another, but that it is “imprac-
tical at the individual level.” Twenty years later, the explosive expansion of
computational power that still continues to date has made such computations
more and more feasible. Early versions of these models in ecology were developed
by population ecologists interested in including animal behavior in population
models [ 62 - 64 ] and lead to a diverse array of applications for fish, insects, and
birds [ 55 ]. An advantage of such models is that two implicit assumptions
associated with traditional ecological modeling populations are not necessary,
namely that:
1. The unique features of individuals (including their size and relative location) are
sufficiently unimportant to the degree that individuals are assumed to be identi-
cal and
2. The population is “perfectly mixed” so that there are no local spatial interactions
of any important magnitude [ 55 ].
As Watt noted, most ecologists are interested in variation between individuals (a
basis for the theory of evolution and a frequently measured aspect of plants and
animals) and appreciate spatial variation as being quite important. Assumption that
this variation somehow is uniform seems particularly inappropriate for trees which
are sessile and which vary greatly in size over their life span. This may be one of the
reasons why tree-based forest models are among the earliest and most widely
elaborated of this genre of models in ecology.
In 1972, Botkin and colleagues [ 65 ] produced an important simplification of the
early forestry work (called the JABOWA model for the initials of its developers)
and introduced this modeling approach to ecologists. They did not cite any of the
antecedent forestry models and likely were not aware of them. The earlier forestry