基于风险的入侵性白纹伊蚊综合监测系统

M. Antonovic, M. Cannata, A. Danani, Lukas Engeler, E. Flacio, F. Mangili, D. Ravasi, D. Strigaro, M. Tonolla
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引用次数: 1

摘要

根据基于气候驱动的大尺度模型的预测,在某种程度上,lsamman湖周围地区和瑞士高原适合Ae的传播。阿尔卑斯山脉以北的白纹伊蚊,而瑞士的其他地区(如z里奇市)目前的冬季似乎过于寒冷,不利于卵的存活。然而,该模型没有考虑到该物种繁殖的城市地区的特定小气候条件。城市微栖息地(尤其是捕集池)的气候条件增加了冬季滞育卵存活的可能性,有利于在被认为太冷而无法存活的新城市殖民。因此,迫切需要适当的监测工具和基于风险的监测。蚊的种群数量。2018年,瑞士南部应用科学与艺术大学(SUPSI)的一个多学科研究小组加入启动了白纹伊蚊综合系统(ALBIS)项目。所设计的系统侧重于监测城市集水区,主要是微气候环境感知、数据传输、数据获取和数据传播。收集到的数据作为经验机器学习模型的输入,用于预测Ae的时空分布。蚊。第一批实时监测测试正在提契诺州卢加诺市的试点地区进行。地球科学研究所与当地一家电子产品制造商(TECinvent)合作,结合开源istSOS OGC传感器观测服务软件,设计了功能齐全的原型,用于数据采集和传播,在第一批测试案例中,在能源效率、数据质量和数据传输可靠性方面表现出良好的质量。第一个结果表明,集水区的温度可能与传统地形测量检测到的外部温度不同:2018年2月,在提契诺州的冷空气温度低至-8°C期间,监测集水区壁面的原型传感器显示温度最高可达6°C。考虑到Ae。白纹伊蚊的孳生阈值是1月平均温度>0°C,以使卵能够越冬,考虑到这种小气候环境可能会导致更现实的预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ALBIS: integrated system for risk-based surveillance of invasive mosquito Aedes albopictus
According to predictions bases on a climate-driven large-scale model the areas surrounding Lake Léman and, to some extent, the Swiss Plateau are suitable for the spread of Ae. albopictus North of the Alps, while other areas in Switzerland (e.g., the city of Zürich) seem currently too cold in winter for the survival of eggs. However, this model does not take into account particular micro-climate conditions in urban areas where the specie thrives. Climate conditions in urban micro-habitats (in particular catch basins) increase the probability of the survival of diapausing eggs in the winter season favoring the colonization of new cities that were thought to be too cold for the survival of the eggs. Therefore, there is an urgent need for appropriate monitoring tools and risk-based surveillance of Ae. albopictus populations. In 2018 a multidisciplinary group of researchers from the University of Applied Sciences and Arts of Southern Switzerland (SUPSI) has joined launching the project ALBIS (Albopictus Integrated System). The designed system focuses on the monitoring of urban catch basins, primarily on micro-climate environmental sensing, data transmission, data acquisition and data dissemination. The gathered data are the input for an empirical machine learning model for the prediction of spatial and temporal distribution of the Ae. albopictus. The first real time monitoring tests are in progress in the pilot area in the city of Lugano in the Canton Ticino. Fully functional prototypes have been engineered by the Institute of Earth Science in collaboration with a local electronics manufacturer (TECinvent) combined with the Open Source istSOS OGC Sensor Observation Service software for data acquisition and dissemination, and in the first tests cases have demonstrated good quality in terms of energy efficiency, data quality and data transmission reliability. The first results demonstrated that temperature in catch basins can be different from outside temperature that is detected by traditional terrain measures: in February 2018 during a period of cold air temperature in Canton Ticino of down to -8°C, the prototype sensor monitoring the catch basins' wall surface shows temperatures up to 6°C higher. Considering that one of the Ae. albopictus establishment thresholds is to have a mean January temperature of >0°C to allow egg overwintering, taking into account this micro-climate environments could lead to more realistic predictions.
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