Herein, we cover measures of honey bee field colony strength, by which we primarily mean population measures of adult bees and brood. We will also talk about secondary measures such as: quantity of stored honey and pollen; “brood pattern” by which is meant the degree of worker brood solidity or contiguity; and the expression of visible disease or parasite symptoms. Strictly speaking these measures are not so much indicators of a colony’s immediate state as they are legacy effects or predictors of future condition.
For our purposes there are two contexts in which an investigator wishes to measure colony strength: 1. at the beginning of a study as part of manipulations to produce uniform colonies and reduce experimental error and; 2. as response variables during or at the end of an experiment. Moreover, there are two general modes of measuring colony strength: 1. an objective mode which uses empirical measures such as weight (mg, g, or kg) or area (cm2), covered in sections 3 and 4.1. and; 2. a subjective mode that relies on visual estimates by one or more observers, covered in sections 4.2. and 5.1. The objective mode is the more accurate of the two, but it is also invasive and disruptive to the bees, constituting in some cases the complete deconstruction and reassembly of colonies with disruption to any social cohesion formerly intact. For this reason we consider the objective mode best suited to the beginning and end of experiments. In contrast, the subjective mode is less accurate, but far less disruptive to the bees and therefore appropriate for collecting response variables during the experiment when the investigator has an interest in preserving the social cohesion and health of experimental colonies. One exception to this would be if the sampling intervals are sufficiently distanced (2-3 times per year) to justify the objective mode throughout. Nevertheless, with safeguards in place such as we describe below, the subjective mode is an acceptably robust technique.
There is a third emerging mode for measuring colony strength; 3. computer-assisted digital image analysis, covered in sections 5.2. – 5.5. This method is minimally invasive, automatically generates archival images for data traceability and verification, provides objective empirical data, and can be done moderately quickly. Its chief disadvantages are cost and dependence on technology. Moreover, it is the opinion of some that the speed and ease of visual estimates surpass the advantages of objectivity and archival properties of digital methods. Nevertheless, we will probably see technical improvements and increasing use of this mode in the near future. Computer-assisted digital image analysis is useful for experiments that call for measures of bee health or development but fall short of field-scale colony strength assessment, chief examples being laboratory studies in environmental toxicology or nutrition.
The sections 5.6. – 5.9. cover methods that do not fit neatly into the other sections. These include: measuring flight activity at the entrance; comb construction; and two proxy measures of colony fitness: production of queen cells; and drone brood.
A note is warranted here on a couple omissions from this chapter; gross colony weight and X-ray tomography. Gross colony weight is a useful metric in the context of seasonal changes in forage availability. Hive-scale data have long interested beekeepers for their usefulness in tracking local nectar flows, and more recently these kinds of data have been used to monitor flowering phenology in the context of climate change (Nightingale et al., 2008). As a measure of colony strength per se, however, gross colony weight is ambiguous and unreliable, owing to the fact that workers from health-compromised colonies may express precocious foraging with the result that weights of colonies may increase, not decrease, in response to disease or other disorders (Mayack and Naug, 2009). X-ray tomography offers what is probably the most empirically quantifiable, thorough, and non-invasive means of monitoring colony strength of colonies of honey bees or other social insects (Greco, 2010). Although it sets a gold standard, its formidable technical requirements keep this method out of reach of most honey bee researchers.