Stochastic models in seed dispersals: random walks and birth-death processes
Authored by A Abdullahi, S Shohaimi, A Kilicman, M H Ibrahim
Date Published: 2019
DOI: 10.1080/17513758.2019.1605003
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Abstract
Seed dispersals deal with complex systems through which the data
collected using advanced seed tracking facilities pose challenges to
conventional approaches, such as empirical and deterministic models. The
use of stochastic models in current seed dispersal studies is
encouraged. This review describes three existing stochastic models: the
birth-death process (BDP), a 2 dimensional () symmetric random walks and
a intermittent walks. The three models possess Markovian property, which
make them flexible for studying natural phenomena. Only a few of
applications in ecology are found in seed dispersals. The review
illustrates how the models are to be used in seed dispersals context.
Using the nonlinear BDP, we formulate the individual-based models for
two competing plant species while the cover time model is formulated by
the symmetric and intermittent random walks. We also show that these
three stochastic models can be formulated using the Gillespie algorithm.
The full cover time obtained by the symmetric random walks can
approximate the Gumbel distribution pattern as the other searching
strategies do. We suggest that the applications of these models in seed
dispersals may lead to understanding of many complex systems, such as
the seed removal experiments and behaviour of foraging agents, among
others.
Tags
Individual-based model
Simulation
movement
Seed dispersal
Random walk
patterns
Search
Density
Monkeys
Birth-death process
Cover time
Cover times