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Advisor(s)
Abstract(s)
Cellular automata (CA) are discrete models
frequently used in ecological and epidemiological studies due to
the capacity to simulate dynamics systems and analyze their
behavior. One of the applications of CA in ecology is in the
analysis of the spatial distribution of species, where models are
created and simulated in order to study the response of ecological
systems to different kinds of exogenous or endogenous
perturbations. In this study we describe an implementation of a
cellular automaton model able to incorporate environmental data
collected from different heterogeneous sources. To the user is
given the power to produce and analyze different scenarios by
combining the available variables at will. Different hypothesis
regarding the individual contribution of each environmental
variable can be promptly tested. As an illustrative example of the
flexibility of our implementation we present a case study where,
departing from a general additive model (GAM), validated in the
literature, a possible explanation is given for the spatio-temporal
distribution of two haplotypes of honeybees along Iberian
Peninsula. Environmental data were used to describe every 30x30
second unit grid of the study area (World Geodetic System 1984
WGS84, geographical coordinates). The results of our model are
compared and discussed at the light of the real data collected on
the terrain. Curiously enough, both in the synthesized model and
in the real data, one can observe that the frequency of African
haplotypes decreases in a SW-NE trend, while that of west
European lineage increases.
Description
Keywords
Environmental modeling Cellular automata Modeling tools Species distribution models