Miguel F.Acevedo
ABSTRACTS
ESTIMATING PARAMETERS OF
FOREST PATCH TRANSITION MODELS FROM GAP MODELS
Environmental
Modelling
and Software 16: 649-658. 2001
Miguel F. Acevedo1, Magdiel
Ablan2,
Dean L. Urban3 and Siva Pamarti4
1Institute
of Applied Sciences and Department of Geography, University of North
Texas,
Denton, Texas 76203, USA.
2Centro
de Simulación y Modelos (CESIMO), Facultad de Ingeniería,
Universidad de Los
Andes, Mérida 5101, Venezuela.
3Nicholas
School of the Environment, Duke University, Durham, North Carolina,
27708, USA.
4Computer
Sciences Department, University of North Texas, Denton, Texas, 76203,
USA.
Abstract
An algorithm to estimate the parameter values of a transition
forest landscape model (MOSAIC) from a gap model (FACET) is presented
here.
MOSAIC is semi-Markov; it includes random distributed holding times and
fixed
or deterministic delays in addition to transition probabilities. FACET
is a
terrain-sensitive version of ZELIG, a spatially explicit gap model. For
each
topographic class, the input to the algorithm consists of gap model
tracer
files identifying the cover type of each plot through time. These cover
types
or states are defined a priori. The
method, based on individual plots of the FACET model, requires one
FACET run
initialized from the “gap” cover type and follows the time history of
each
plot. The algorithm estimates the transition probability by counting
the number
of transitions between each pair of states and estimates the fixed lags
and the
parameters of the probability density functions of the distributed
delays by
recording the times at which these transitions are made. These density
functions
are assumed to be Erlang; its two parameters, order and rate, are
estimated
using a nonlinear least squares procedure. Thus, as output, the
algorithm
produces four matrices at each terrain class: transition probabilities,
fixed
delays, and the two parameters for the Erlang distributions. The
algorithm is
illustrated by its application to two sites, high and low elevation,
from the
H.J. Andrews Forest in the Oregon Cascades. This scaling-up method
helps to
bridge the conceptual breach between landscape- and stand-scale models.
To
reflect landscape heterogeneity, the algorithm can be executed
repetitively for
many different terrain classes. While the method developed here focuses
on
FACET and MOSAIC, this general approach could be extended to use other
fine-scale models or other forms of metamodels.
Keywords: transition, forest dynamics,
semi-Markov, parameterization, scaling-up, simulation, landscape,
FACET, MOSAIC, gap, H.J. Andrews.
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