PesTwin：一种用于害虫和病媒种群控制的基于模块化代理的框架
PesTwin: A modular agent-based framework for pest and vector population control
AI总结：
针对基因控制技术建模工具滞后问题，提出PesTwin框架，可跨物种等模拟基因控制技术，捕捉多种因素。经与实验室数据验证后可扩展到田间场景，能在基因控制系统实际应用前进行模拟测试，助力相关决策，缩短研发到应用路径。
AI中文摘要：
物种特异性的害虫和病媒控制策略，如不育昆虫技术、基于沃尔巴克氏体的干预措施和基因控制技术，为广谱化学控制提供了有力替代方案。其中基因控制技术发展迅速，但预测结果、指导技术设计与实施等所需的建模工具发展滞后。本文提出PesTwin，一个基于代理的建模框架，可在通用计算环境中跨物种、生态环境和部署策略模拟基因控制技术。它能捕捉随机人口统计学效应等多种因素。通过与四项基因控制系统的实验室笼养数据验证，显示预测与观察的种群轨迹高度吻合。还展示了该模型可扩展到空间明确的田间尺度场景。PesTwin能在基因控制系统构建或释放前进行计算机模拟测试，缩短从实验室构建到田间干预的路径，为相关决策提供信息。
英文摘要：
Species-specific pest and vector control strategies, including the sterile insect technique, Wolbachia-based interventions, and genetic control technologies, offer powerful alternatives to broad-spectrum chemical control, with applications ranging from targeted crop protection to large-scale disease control. Among these, genetic control technologies are advancing rapidly, but the pace of technological development is outstripping the modelling tools needed to predict outcomes, guide technology design and its implementation, compare alternative strategies across different use settings, and support regulatory and operational decision-making. Here we present PesTwin, an agent-based modelling framework for simulating genetic control technologies across species, ecological settings, and deployment strategies within a common computational environment. PesTwin captures stochastic demographic effects, species-specific life-history traits, heterogeneous dispersal, and temporal variation in resource availability and infestation pressure. We validate PesTwin against published laboratory cage data from four genetic control systems, drawn from three studies, in two insect species, showing close agreement between predicted and observed population trajectories, including their replicate-to-replicate variability. We then illustrate how the same validated models extend beyond the cage to spatially explicit, field-scale scenarios, using PesTwin to explore how the timing, density and spatial placement of releases shape suppression and spread across heterogeneous landscapes. By making genetic control systems testable in silico before they are built or released, PesTwin can shorten the path from laboratory construct to field intervention: informing which constructs to prioritise, how to design the experiments that test them, where and when to release, and what evidence is needed to evaluate them.
