A random planting model
Julian Talbot, Pascal Viot, David Colliaux

TL;DR
This paper introduces a one-dimensional random planting model inspired by adsorption processes, analyzing plant growth patterns, yields, and species interactions under stochastic planting conditions.
Contribution
It presents a novel stochastic model for plant planting and growth, providing insights into spatial patterns, yields, and species competition in agroecological practices.
Findings
Steady state yield approaches 4/3 plants per unit length per time.
Slower-growing species are enriched in harvest compared to seed mix.
Smaller species tend to be enriched in harvest, larger species may be absent at high planting rates.
Abstract
The adoption of agroecological practices will be crucial to address the challenges of climate change and biodiversity loss. Such practices favor the cultivation of plants in complex mixtures with layouts differing from the monoculture approach of conventional agriculture. Inspired by random sequential adsorption processes, we propose a one-dimensional model in which the plants are represented as line segments that start as points and grow at a constant rate until they reach length after a time interval . The planting positions and times are randomly chosen with the constraint that plant overlap is forbidden. We apply an exact, event-driven simulation to investigate the resulting spatiotemporal patterns and yields in both mono- and duocultures. After a transient period, with oscillations in the density and coverage, the field reaches a steady state in which the mean age of…
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Taxonomy
TopicsGreenhouse Technology and Climate Control
