Abstract
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.