Model Comparison for Abiotic versus Biotic Pollen Dispersal.

Area of Science:

• Ecology
• Computational Biology
• Population Genetics

Background:

• Pollination is crucial for forest ecosystems.
• Understanding gene dispersal is key to forest resilience.
• Agent-based models offer insights into complex ecological processes.

Purpose of the Study:

• To investigate the impact of different dispersal mechanisms on gene flow within a forest ecosystem.
• To compare the effects of purely random (abiotic) versus correlated (biotic) walks on pollination patterns.
• To analyze how plant density influences gene dispersal under various pollination scenarios.

Main Methods:

• Development of an agent-based model incorporating correlated random walks.
• Simulation of abiotic (wind) dispersal using a purely random walk.
• Simulation of biotic (insect) dispersal using moderately and highly correlated random walks.
• Analysis of biological measurements related to gene dispersal across low and high plant densities.

Main Results:

• Correlated random walks, simulating biotic dispersal, result in distinct gene dispersal patterns compared to purely random walks (abiotic dispersal).
• Differences in gene dispersal are observed between purely random and correlated walks, particularly influenced by plant density.
• The degree of correlation in biotic dispersal significantly alters the spatial distribution of genes.

Conclusions:

• Biotic dispersal via correlated random walks promotes more localized gene flow compared to abiotic dispersal.
• Plant density is a critical factor modulating the effectiveness of different pollination strategies on gene dispersal.
• Agent-based modeling with correlated random walks provides a valuable framework for understanding forest pollination dynamics and genetic diversity.