Monitoring colony phenology using within-day variability in continuous weight and temperature of honey bee hives

W G Meikle,A R Stilwell,M Weiss

doi:10.1007/s13592-015-0370-1

Abstract

Continuous weight and temperature data were collected for honey bee hives in two locations in Arizona, and those data were evaluated with respect to separate measurements of hive phenology to develop methods for noninvasive hive monitoring. Weight and temperature data were divided into the 25-h running average and the daily within-day changes, or “detrended” data. Data on adult bee and brood masses from hive evaluations were regressed on the amplitudes of sine curves fit to the detrended data. Weight data amplitudes were significantly correlated with adult bee populations during nectar flows, and temperature amplitudes were found inversely correlated with the log of colony brood weight. The relationships were validated using independent datasets. In addition, the effects of an adult bee kill on hive weight data were contrasted with published data on weight changes during swarming. Continuous data were found to be rich sources of information about colony health and activity.

Highlights

Data gathered from bee colonies on a continuous basis, in this case defined as hourly or more often for periods exceeding 2 days, are rich in information about bee colony growth and activity (Buchmann and Thoenes 1990; Meikle and Holst 2014)
Foraging activity, as shown by weight changes due to forager traffic, and foraging success, as shown by increases in hive food stores, can be measured, provided the scales are of sufficient precision (Meikle et al 2008)
Buchmann and Thoenes (1990) advanced the field by using electronic scales linked to a computer and proposed using hive weight to examine the impact of pesticides on bee colonies, changes in nectar and pollen availability, and differences among honey bee races

Summary

Introduction

Data gathered from bee colonies on a continuous basis, in this case defined as hourly or more often for periods exceeding 2 days, are rich in information about bee colony growth and activity (Buchmann and Thoenes 1990; Meikle and Holst 2014). Buchmann and Thoenes (1990) advanced the field by using electronic scales linked to a computer and proposed using hive weight to examine the impact of pesticides on bee colonies, changes in nectar and pollen availability, and differences among honey bee races. Meikle et al (2008) correlated parameters of curves fit to running average and detrended data with adult bee mass, brood mass, and food stores gathered from hive inspections, demonstrating that the two types of data reveal different aspects of colony dynamics Detrending to remove longer term trends in data is used in many disciplines in ecology and elsewhere; Garibaldi et al (2011), for example, detrended leaf data in order to remove latitude effects. Meikle et al (2008) correlated parameters of curves fit to running average and detrended data with adult bee mass, brood mass, and food stores gathered from hive inspections, demonstrating that the two types of data reveal different aspects of colony dynamics

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Conclusion