No abstract

The bee Apis mellifera plays an important role in the balance of the ecosystem. New technologies are used for the evaluation of hives, and to determine the quality of the honey and the productivity of the hive. Climatic factors, management, flowering, and other factors affect the weight of a hive. The objective of this research was to explain the interrelationship between climatic variables and the weight of an Apis mellifera beehive using a vector autoregressive (VAR) model. The adjustment of a VAR model was carried out with seven climatic variables, and hive weight and its lags, by adjusting an equation that represents the studied hive considering all interrelationships. It was proven that the VAR (1) model can effectively capture the interrelationship among variables. The impulse response function and the variance decomposition show that the variable that most influences the hive weight, during the initial period, is the minimum dew point, which represents 5.33% of the variance. Among the variables analyzed, the one that most impacted the hive weight, after 20 days, was the maximum temperature, representing 7.50% of the variance. This study proves that it is possible to apply econometric statistical models to bee data and to relate them to climatic data, contributing significantly to the area of applied and bee statistics.