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Optimizing strategies for slowing the spread of invasive species

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  • Adam Lampert

Abstract

Invasive species are spreading worldwide, causing damage to ecosystems, biodiversity, agriculture, and human health. A major question is, therefore, how to distribute treatment efforts cost-effectively across space and time to prevent or slow the spread of invasive species. However, finding optimal control strategies for the complex spatial-temporal dynamics of populations is complicated and requires novel methodologies. Here, we develop a novel algorithm that can be applied to various population models. The algorithm finds the optimal spatial distribution of treatment efforts and the optimal propagation speed of the target species. We apply the algorithm to examine how the results depend on the species’ demography and response to the treatment method. In particular, we analyze (1) a generic model and (2) a detailed model for the management of the spongy moth in North America to slow its spread via mating disruption. We show that, when utilizing optimization approaches to contain invasive species, significant improvements can be made in terms of cost-efficiency. The methodology developed here offers a much-needed tool for further examination of optimal strategies for additional cases of interest.Author summary: In light of the global spread of invasive species that threaten ecosystems, biodiversity, agriculture, and human health, we developed an advanced computer algorithm to identify the optimal strategy to slow the spread of established invaders. In particular, the algorithm finds the most cost-effective way to allocate resources for treatment across different locations. The algorithm is generic and is suitable for a wide variety of population dynamical models and treatment methods. We tested the algorithm using both a broad-based model and a specific model focused on the spongy moth in North America. Our findings revealed significantly improved strategies for slowing the spread of invasive species. The algorithm thus offers a promising tool for improving environmental conservation and assisting policymakers in facing the challenges posed by invasive species.

Suggested Citation

  • Adam Lampert, 2024. "Optimizing strategies for slowing the spread of invasive species," PLOS Computational Biology, Public Library of Science, vol. 20(4), pages 1-20, April.
    • Handle: RePEc:plo:pcbi00:1011996
    DOI: 10.1371/journal.pcbi.1011996
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