Abstract

ABSTRACTSeed 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.

Highlights

  • The seedling survival, growth and development of many plant species depend on seed dispersals through which agents, such as rodents, move seeds away from the seed producing trees

  • Seed dispersal is dealing with many complex systems, some of which are difficult to be analysed with empirical or deterministic models alone

  • In an attempt to confront the challenges pose by large amount of data generated from advanced seed tracking facilities, the models and illustrations related to seed dispersals are described in this review

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Summary

Introduction

The seedling survival, growth and development of many plant species depend on seed dispersals through which agents, such as rodents, move seeds away from the seed producing trees. Even if the data are available, it is not always guaranteed to obtain a model that is suitable for the analyses This compels the application of variety of methods such as individual-based models (IBMs), which their basis entities are individual plants and animals species among others, to seed dispersals. Even though tools [62], such as the birth–death processes (BDPs), symmetric and intermittent random walks, were separately applied in many studies, obtaining a single work that include these three models and relate them to seed dispersals remains elusive. These three models share common Markovian property, through which the future event does not depend on the fast given the present [40]. We show that interaction of plant species that require some dispersal agents, time taken by the agent to remove a seed and agents’ foraging pattern can all be studied with the three models

Birth–death processes
Two species IBM
Random walk models
Symmetric random walks
Intermittent random walks
Cover time models of animal movements
Conclusion
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