Time-series models to quantify short-term effects of meteorological conditions on bumblebee forager activity in agricultural landscapes

Abstract

The decline of bumblebees in Europe has been linked primarily to agricultural inten- sification, although climate change also has the potential to disrupt plant-pollinator interactions, partly through an increased frequency of extreme short-term weather events. There have been few attempts to use time-series models to determine meteoro- logical variables affecting forager activity at hourly time periods over several months. 2 Time-series models require large datasets to be reliable. We describe the use of infrared detectors at nest entrances to record forager exits/returns from 36 captive colonies of Bombus terrestris audax on a mixed farm in northern England, recording over a 78-day period. 3 Over 1.73 million individual records of forager activity were obtained. These were aggregated into 1872 hourly blocks and analyzed with autoregressive time-series models that used nine meteorological factors as explanatory variables. 4 Forager activity was positively linked to air temperature and solar elevation, and negatively associated with rainfall, humidity and wind-speed. The effects of increased variability in meteorological conditions are considered in the context of these results. The time-series models that we describe will be useful in future analyses of the large datasets of foraging behaviour that are becoming available through new technologies such as radio-frequency identification and video tracking.