Thermal Biology and Developmental Parameters of Aphis spiraecola (Hemiptera: Aphididae) on Apple at Different Temperatures
Keywords:
Aphis Spiraecola, Thermal Biology, Degree-Days, Life Table Parameters, Apple Orchards, Temperature-Dependent DevelopmentAbstract
Developmental performance, survival and population growth of Aphis spiraecola (Hemiptera: Aphididae) were assessed on apple under a range of constant temperatures to elucidate thermal requirements and phenology-related risk potential. Immature development, adult longevity, fecundity, and life table parameters were recorded across temperature gradients under laboratory conditions. Development rate increased progressively with temperature up to an optimal range, beyond which survival and reproductive output declined sharply. Minimum developmental thresholds were estimated using linear regression of inverse development rates, and thermal constants were derived in degree-days to complete immature stages. Highest intrinsic rate of increase (r), net reproductive rate (R0), and finite rate of increase (λ) were observed at intermediate temperatures, indicating optimal population performance under moderate thermal conditions. Extreme low and high temperatures significantly prolonged development time, reduced fecundity, and increased mortality across nymphal instars. Age-specific survivorship curves demonstrated temperature-dependent shifts in mortality distribution, with early instars exhibiting higher sensitivity to thermal stress. The findings highlight strong temperature-mediated regulation of population dynamics in A. spiraecola, with implications for seasonal outbreak prediction in apple orchards. Integration of thermal biology parameters into forecasting models can improve timing of management interventions and enhance pest suppression efficiency under variable climatic conditions. Such insights are critical for developing climate-resilient integrated pest management strategies in temperate fruit production systems. These results provide a quantitative framework for degree-day based forecasting and support adaptive management under climate warming scenarios.