Faculty of Natural Sciences, Institute of Biology, Biotechnology and Environmental Protection, Animal Physiology and Ecotoxicology Team, University of Silesia in Katowice, PL 40-007, Katowice, Bankowa 9, Poland.
Główny Instytut Górnictwa (GIG), 40-166, Katowice, plac Gwarków 1, Poland.
Int J Biometeorol. 2021 Oct;65(10):1647-1658. doi: 10.1007/s00484-021-02119-8. Epub 2021 Apr 21.
Dwelling intensity of horse-chestnut miner (Cameraria ohridella) larvae in various leaves insolation and temperature was measured to determine whether this pest's development follows a predictable pattern or depends more on local microenvironment conditions. Mines growing on leaves of mature host plants (Aesculus hippocastanum L.) in their natural conditions were photographed for two consecutive generations of the pest and in two separated vegetation periods. Apart from meteorological data obtained from the nearest station, the temperature of intact and mined parts of sun-exposed and shaded leaf blades was measured at various daytimes throughout the experiment. Obtained sets of digital data were analysed and combined to model mine area growth as a function of degree-days sum by adopting of Verhulst logistic equation. We showed the predictive potential of our model based on experimental data, and it may be useful in the scheduling of pest control measures in natural conditions. Our analyses also revealed that despite significant differences in microenvironment conditions depending on mines' insolation, the horse-chestnut miner larvae could partially compensate for them and complete their development at similar endpoints expressed as the cumulative sum of degree-days. We conclude that computer-aided analysis of photographic documentation of leaf-miner larval growth followed by mathematical modelling offers a noninvasive, reliable, and inexpensive alternative for monitoring local leaf-miners populations.
测定了马栗潜叶虫幼虫在不同光照和温度条件下的叶内密度,以确定这种害虫的发育是否遵循可预测的模式,还是更多地取决于当地的微观环境条件。在害虫的两个连续世代和两个不同的植被期,对生长在成熟寄主植物(欧洲七叶树)叶片上的潜叶虫虫瘿进行了拍照。除了从最近的气象站获得的气象数据外,还在整个实验过程中的不同白天测量了暴露在阳光下和遮荫的叶片完整和有虫瘿部分的温度。对获得的数字数据集进行了分析和组合,通过采用 Verhulst 逻辑方程将虫瘿面积的生长建模为度日和的函数。我们展示了基于实验数据的模型的预测潜力,它可能有助于在自然条件下安排害虫防治措施。我们的分析还表明,尽管微环境条件因虫瘿的光照而异存在显著差异,但栗马潜叶虫幼虫可以部分补偿这些差异,并以相似的累计度日和为终点完成其发育。我们的结论是,对叶片潜叶虫幼虫生长的摄影记录进行计算机辅助分析,然后进行数学建模,提供了一种非侵入性、可靠且廉价的监测当地潜叶虫种群的替代方法。