25. Ecosystem Modeling
namics and plant production in grazed grasslands
and agroecosystems. The CENTURY model simulates the dynamics of carbon (C), nitrogen (N),
and phosphorus (P) in soil-plant systems using
monthly time steps. The input data required for the
model include soil texture, monthly precipitation,
maximum and minimum air temperatures, and
plant lignin content. By the late 1980s, the
CENTURY model had been used to simulate regional patterns of soil C, N, and P and plant production for the U.s. central grasslands region and
the impact of management practices on agroecosystems (Parton et al. 1987, 1988).
Combined Models of Change in Structure
and Material Flow
Recently, models that combine the biophysical understanding found in canopy process models with
the transport of matter associated with material
transport models have come to the fore in studies
of large-scale environmental change. For example,
the Forest-BGC model (Running and Coghlan
1988; Running and Nemani 1988; Running et al.
1989) for hydrology and plant canopy function has
been melded to an individual-tree-based forest
model to provide a capability to simulate the
change in forest structure over time (Friend et al.
1993). The resultant model, HYBRID, also uses a
more detailed photosynthesis model, PGEN (Friend
1991), to improve the representation of mechanisms for photosynthesis production and allocation.
As another example, the DOLY model (Woodward
et al. 1995) is a global scale terrestrial model that
combines predicting primary productivity and the
phytogeographical problem of predicting leaf area
across continents. The model has features associated with canopy process models, such as a model
representation of the bulk biochemical features of
photosynthesis, the dependence of CO2 exchange,
temperature and moisture changes on the stomatal
conductance, and the role of canopy conductance
on evapotranspiration and soil water losses. The involvement of N with the photosynthesis process
and the dynamics of the uptake and allocation of N
is also simulated. The model can be used to simulate the global distributions of leaf areas and net
primary productivity under present and altered
climates.
385
Individual-Based Models
In the past two decades or so, a broad range of
ecologists (animal behaviorists, population biologists, community and ecosystems ecologists) has
independently created a diverse array of individualbased models (Huston et al. 1988). The catalyst for
this development was undoubtedly the increased
availability and power of digital computers-the
necessary tools to solve most of these models. The
earliest such models were developed by population
ecologists (Holling 1961, 1964; Rohlf and Davenport 1969) interested in incorporating animal behavior into population models and foresters interested relating tree growth to forest yield. The
dynamics of populations when represented by
individual-based models can differ significantly
from an equivalent state-variable representation of
the same system (Lomnicki 1988; Huston et al.
1988; DeAngelis and Gross 1992).
Increasingly, models that simulate the dynamics
of ecological systems by accounting for changes in
each of a large number of individuals in the system
have been developed and applied in population and
ecosystems ecology (Huston et al. 1988; DeAngelis
and Gross 1992). Huston et al. (1988) point out that
one advantage of such models is that two implicit
assumptions associated with the more traditional
state-variable approach used in ecological modeling populations are not necessary. These are the
assumptions that (1) the unique features of individuals are sufficiently unimportant to the degree that
individuals are assumed to be identical, and (2) the
population is "perfectly mixed" so that there are no
local spatial interactions of any important magnitude. Most ecologists are interested in variation in
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.
These assumptions seem particularly inappropriate for trees, which are sessile and which vary
greatly in size over their life span. This may be one
of the reasons that tree-based forest models are
among the earliest and most widely elaborated of
this genre of models. The effects of spatial pattern
have been well known from practical experience in
agronomy and forestry for some time. In many agricultural (and forestry) experiments, the determination of spacing of plants has a profound effect on
namics and plant production in grazed grasslands
and agroecosystems. The CENTURY model simulates the dynamics of carbon (C), nitrogen (N),
and phosphorus (P) in soil-plant systems using
monthly time steps. The input data required for the
model include soil texture, monthly precipitation,
maximum and minimum air temperatures, and
plant lignin content. By the late 1980s, the
CENTURY model had been used to simulate regional patterns of soil C, N, and P and plant production for the U.s. central grasslands region and
the impact of management practices on agroecosystems (Parton et al. 1987, 1988).
Combined Models of Change in Structure
and Material Flow
Recently, models that combine the biophysical understanding found in canopy process models with
the transport of matter associated with material
transport models have come to the fore in studies
of large-scale environmental change. For example,
the Forest-BGC model (Running and Coghlan
1988; Running and Nemani 1988; Running et al.
1989) for hydrology and plant canopy function has
been melded to an individual-tree-based forest
model to provide a capability to simulate the
change in forest structure over time (Friend et al.
1993). The resultant model, HYBRID, also uses a
more detailed photosynthesis model, PGEN (Friend
1991), to improve the representation of mechanisms for photosynthesis production and allocation.
As another example, the DOLY model (Woodward
et al. 1995) is a global scale terrestrial model that
combines predicting primary productivity and the
phytogeographical problem of predicting leaf area
across continents. The model has features associated with canopy process models, such as a model
representation of the bulk biochemical features of
photosynthesis, the dependence of CO2 exchange,
temperature and moisture changes on the stomatal
conductance, and the role of canopy conductance
on evapotranspiration and soil water losses. The involvement of N with the photosynthesis process
and the dynamics of the uptake and allocation of N
is also simulated. The model can be used to simulate the global distributions of leaf areas and net
primary productivity under present and altered
climates.
385
Individual-Based Models
In the past two decades or so, a broad range of
ecologists (animal behaviorists, population biologists, community and ecosystems ecologists) has
independently created a diverse array of individualbased models (Huston et al. 1988). The catalyst for
this development was undoubtedly the increased
availability and power of digital computers-the
necessary tools to solve most of these models. The
earliest such models were developed by population
ecologists (Holling 1961, 1964; Rohlf and Davenport 1969) interested in incorporating animal behavior into population models and foresters interested relating tree growth to forest yield. The
dynamics of populations when represented by
individual-based models can differ significantly
from an equivalent state-variable representation of
the same system (Lomnicki 1988; Huston et al.
1988; DeAngelis and Gross 1992).
Increasingly, models that simulate the dynamics
of ecological systems by accounting for changes in
each of a large number of individuals in the system
have been developed and applied in population and
ecosystems ecology (Huston et al. 1988; DeAngelis
and Gross 1992). Huston et al. (1988) point out that
one advantage of such models is that two implicit
assumptions associated with the more traditional
state-variable approach used in ecological modeling populations are not necessary. These are the
assumptions that (1) the unique features of individuals are sufficiently unimportant to the degree that
individuals are assumed to be identical, and (2) the
population is "perfectly mixed" so that there are no
local spatial interactions of any important magnitude. Most ecologists are interested in variation in
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.
These assumptions seem particularly inappropriate for trees, which are sessile and which vary
greatly in size over their life span. This may be one
of the reasons that tree-based forest models are
among the earliest and most widely elaborated of
this genre of models. The effects of spatial pattern
have been well known from practical experience in
agronomy and forestry for some time. In many agricultural (and forestry) experiments, the determination of spacing of plants has a profound effect on