Time-series dataset: fondant feeding in overwintering Apis mellifera colonies

OBJECTIVES: Winter mortality of honey bee colonies remains high and reduces early-spring pollination. Fondant feeding is a common emergency intervention, yet quantitative descriptions of colony and microclimate responses-especially homogeneous time-series-are scarce. Milder winters and unstable springs further elevate starvation risk and complicate overwintering. We present a homogeneous time-series dataset that captures the thermal response of overwintering Apis mellifera colonies to fondant feeding under these conditions. The dataset fills this gap and supports reproducible protocols for winter and early-spring fondant feeding. DATA DESCRIPTION: The dataset covers Ukraine (mild winter, unstable spring; one colony) and Canada (record-warm winter; three colonies; four feeding events). Data were collected non-invasively from identical Internet of Things (IoT) hives equipped with internal/external temperature (°C) and relative humidity (%) sensors, a load-cell scale, and a solar-powered acquisition and transmission unit. Measurements were recorded at fixed intervals to ensure homogeneous time series. The repository provides raw and cleaned data, a variable dictionary, cleaning/imputation rules, an event log, and a validation script, enabling quantitative assessment for forecasting colony development and for designing scheduled fondant feeding to help reduce winter losses and prepare colonies for early-spring pollination.