Simulating Honeybee ( Apis mellifera) Winter Mortality Rate under Climate Change Scenarios: Development and Application of Meteorological Index-Based Predictive Models

This study investigates the role of winter meteorological indices in predicting Apis mellifera colony losses under various climate change scenarios. This predictive model focuses on environmental temperature variability, emphasizing extreme fluctuations and persistent cold spells, which significantly contribute to overwintering mortality. The findings indicate that rising average temperatures and an increase in high-temperature days have the most profound impact on A. mellifera overwintering mortality. Additionally, an expanded daily temperature range, especially in southern and inland regions, further complicates the bees' ability to regulate their temperature, leading to additional energy expenditures that weaken colony resilience. Furthermore, the projected decrease in low-temperature days by 2100, particularly in southern coastal and central inland areas, presents a challenge for bees, as reduced exposure to cold disrupts their ability to transition into the overwintering phase, leaving colonies unprepared for winter. Moreover, the increase in autumn rainfall days threatens bees by limiting their foraging days and hindering their ability to stockpile resources for winter. This study developed meteorological index-based predictive models to simulate A. mellifera winter mortality rate across the country and applied these models to evaluate the potential impacts of future climate change scenarios on A. mellifera overwintering mortality. The findings emphasize the need for region-specific weather-based forecasting models, as climate impacts on A. mellifera survival vary across different geographic areas. The development of such predictive tools can inform strategic management decisions to mitigate the effects of climate change on pollinator populations and maintain the critical ecosystem services.