Butler C D, Lloyd A L
Biomathematics Graduate Program and Department of Mathematics, North Carolina State University, Raleigh, NC 27606.
bioRxiv. 2024 Nov 11:2024.11.08.622719. doi: 10.1101/2024.11.08.622719.
Managing pest species relies critically on mechanisms that regulate population dynamics, particularly those factors that change with population size. These density-dependent factors can help or hinder control efforts and are especially relevant considering recent advances in genetic techniques that allow for precise manipulation of the timing and sex-specificity of a control. Despite this importance, density dependence is often poorly characterized owing to limited data and an incomplete understanding of developmental ecology. To address this issue, we construct and analyze a mathematical model of a pest population with a general control under a wide range of density dependence scenarios. Using this model, we investigate how control performance is affected by the strength of density dependence. By modifying the timing and sex-specificity of the control, we tailor our analysis to simulate different pest control strategies, including conventional and genetic biocontrol methods. We pay particular attention to the latter as case studies by extending the baseline model to include genetic dynamics. Finally, we clarify past work on the dynamics of mechanistic models with density dependence. As expected, we find substantial differences in control performance for differing strengths of density dependence, with populations exhibiting strong density dependence being most resilient to suppression. However, these results change with the size and timing of the control load, as well as the target sex. Interestingly, we also find that population invasion by certain genetic biocontrol strategies is affected by the strength of density dependence. While the model is parameterized using the life history traits of the yellow fever mosquito, , the principles developed here apply to many pest species. We conclude by discussing what this means for pest population suppression moving forward.
控制害虫种群严重依赖于调节种群动态的机制，特别是那些随种群大小而变化的因素。这些密度依赖性因素可能有助于或阻碍控制工作，考虑到基因技术的最新进展，这些因素尤其重要，因为基因技术能够精确控制控制措施的时间和性别特异性。尽管其重要性，但由于数据有限以及对发育生态学的理解不完整，密度依赖性往往难以得到准确描述。为了解决这个问题，我们构建并分析了一个在广泛的密度依赖性情景下具有一般控制措施的害虫种群数学模型。利用这个模型，我们研究了密度依赖性强度如何影响控制效果。通过改变控制措施的时间和性别特异性，我们调整分析以模拟不同的害虫控制策略，包括传统和基因生物防治方法。我们特别关注后者，通过扩展基线模型以纳入基因动态来进行案例研究。最后，我们澄清了过去关于具有密度依赖性的机制模型动态的研究工作。正如预期的那样，我们发现不同强度的密度依赖性在控制效果上存在显著差异，表现出强密度依赖性的种群对抑制最具弹性。然而，这些结果会随着控制负荷的大小和时间以及目标性别而变化。有趣的是，我们还发现某些基因生物防治策略对种群入侵的影响受到密度依赖性强度的影响。虽然该模型是根据黄热病蚊子的生活史特征进行参数化的，但这里所阐述的原理适用于许多害虫物种。我们通过讨论这对未来害虫种群抑制意味着什么来得出结论。
