Linear and non-linear models to explain influence of temperature on life history traits of Oryzaephilus surinamensis (L.)

Abstract

This study deals with the effect of five constant temperatures (20, 25, 30, 32.5 and 35°C) on development, longevity, fecundity and survival of Oryzaephilus surinamensis (L.) (Coleoptera: Silvanidae) infesting white soft wheat flour. Temperature showed profound effects on immature development, and adult longevity. Egg hatching at 20°C took 13.58 d that is decreased to 3.26 d at 35°C. Larval developmental time decreased by 40.47 d from 20 to 32.5°C with no significant difference between 32.5 and 35°C. Pupal developmental time was shortened from 17.18 d at 20°C to 4.48 d at 35°C, while no significant differences were observed in pupal development between 32.5 and 35°C. Female and male longevity increased by 164.12 and 156.42 d, respectively when temperature was increased from 20 to 25°C followed by a decrease in longevity for both sexes at 35°C. Female fecundity was lowest at 20°C (1.09 eggs/female) and highest at 25°C (64.82 eggs/female). Using the non-linear Briere model, the lower developmental threshold of O. surinamensis was estimated as 16.9°C, the upper threshold as 40.7°C, and the temperature for maximum developmental rate close to 31.3°C. Ikemoto & Takai linear model indicated that 313.3 degree-d above a threshold of 16.3°C were needed for the completion of immature development. Temperature-dependent egg to adult survival of O. surinamensis was described by an extreme value equation, indicating that survival decreased at both ends of the temperature range, but higher temperatures had more detrimental impact on immature survival than lower temperatures. According to the estimated parameters, the highest immature survival (93.6%) was estimated to occur at 28.3°C. The highest value of the net reproductive rate (20.10 females/female), was observed at 25°C. We expect these results to be useful for the prediction of the phenology and potential expansion of O. surinamensis, through the implementation of temperature-driven models, leading to accurate management strategies.