Optimal Control of Lantana camara: An Entropy-Based Sustainable Strategy

TL;DR

This paper develops a control strategy for invasive Lantana camara using ecological modeling, control theory, and entropy measures to promote sustainable biodiversity management within the SDG framework.

Contribution

It introduces a novel entropy-based approach combined with control theory to design sustainable policies for invasive species management.

Findings

Control strategy depends critically on growth rate ratios.

Entropy effectively assesses policy sustainability.

Modular decision support algorithm developed.

Abstract

Framing control policies to mitigate the impact of invasive plants on indigenous biodiversity within the Sustainable Development Goals (SDG) framework is the primary objective of this work. Using reported ecological dynamics of the invasive species \textit{Lantana camara}, we develop a minimal three-species network model, where each node follows generalized Lotka-Volterra (GLV) dynamical equations. Employing Lie algebra and network control theory, we establish the model's controllability and accessibility criteria. Through nonlinear optimization programming, we derive sustainable policies for controlling abundances of \textit{Lantana camara}. We also have used Shannon entropy as an indicator to assess the sustainability of these optimal policies. The analysis of the sensitivity measured using this technique reveals that the control strategy is critically dependent on the ratio of the intrinsic growth rates of the \textit{Lantana camara} and the control plant. Thus, we get a modular algorithmic decision support mechanism for designing control policies to manage \textit{Lantana camara} abundances.