Lampert Adam
Institute of Environmental Sciences, The Robert H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot, Israel.
PLoS Comput Biol. 2024 Apr 3;20(4):e1011996. doi: 10.1371/journal.pcbi.1011996. eCollection 2024 Apr.
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.
入侵物种正在全球范围内扩散，对生态系统、生物多样性、农业和人类健康造成损害。因此，一个主要问题是如何在空间和时间上以具有成本效益的方式分配防治工作，以防止或减缓入侵物种的扩散。然而，为种群复杂的时空动态寻找最优控制策略是复杂的，需要新颖的方法。在此，我们开发了一种可应用于各种种群模型的新颖算法。该算法能找到防治工作的最优空间分布以及目标物种的最优传播速度。我们应用该算法来研究结果如何依赖于物种的种群统计学特征以及对防治方法的反应。特别地，我们分析了（1）一个通用模型和（2）一个针对北美舞毒蛾管理的详细模型，以通过交配干扰减缓其扩散。我们表明，在利用优化方法控制入侵物种时，在成本效益方面可以取得显著改进。这里开发的方法为进一步研究其他感兴趣案例的最优策略提供了急需的工具。
