Aging and demographic plasticity in response to experimental age structures in honeybees (<Emphasis Type="Italic">Apis mellifera</Emphasis> L)

Honeybee colonies are highly integrated functional units characterized by a pronounced division of labor. Division of labor among workers is mainly age-based, with younger individuals focusing on in-hive tasks and older workers performing the more hazardous foraging activities. Thus, experimental disruption of the age composition of the worker hive population is expected to have profound consequences for colony function. Adaptive demography theory predicts that the natural hive age composition represents a colony-level adaptation and thus results in optimal hive performance. Alternatively, the hive age composition may be an epiphenomenon, resulting from individual life history optimization. We addressed these predictions by comparing individual worker longevity and brood production in hives that were composed of a single-age cohort, two distinct age cohorts, and hives that had a continuous, natural age distribution. Four experimental replicates showed that colonies with a natural age composition did not consistently have a higher life expectancy and/or brood production than the single-cohort or double-cohort hives. Instead, a complex interplay of age structure, environmental conditions, colony size, brood production, and individual mortality emerged. A general tradeoff between worker life expectancy and colony productivity was apparent, and the transition from in-hive tasks to foraging was the most significant predictor of worker lifespan irrespective of the colony age structure. We conclude that the natural age structure of honeybee hives is not a colony-level adaptation. Furthermore, our results show that honeybees exhibit pronounced demographic plasticity in addition to behavioral plasticity to react to demographic disturbances of their societies.     

Seatbelt non-use and car crash injury: an interview study

OBJECTIVES: To examine the relationship between seatbelt non-use at the time of a crash, habitual non-use of seatbelts, and car crash injury; and to calculate the population attributable risk for car crash injury due to seatbelt non-use. METHODS: A population-based case control, interview study in Auckland, New Zealand, with 571 injured or killed drivers as cases and 588 population-based controls randomly selected from the driving population. RESULTS: Unbelted drivers had 10 times the risk of involvement in an injury crash compared to belted drivers after adjustment for multiple confounders. Habitual non-users were likely to be unbelted when involved in a crash. The population attributable risk for seatbelt non-use was 13%. CONCLUSIONS: Non-use of seatbelts is very strongly associated with increased injury crash involvement. Even where seatbelt use rates are higher than 90%, there remains a small group of habitual non-users who are at high risk; these drivers may benefit from targeted interventions.     

The influence of water vapour on the determination of glutaraldehyde vapour concentrations using an electrochemical fuel cell sensor

The effects of relative humidity (40-90% RH) and varying glutaraldehyde vapour concentrations (< 0.1 ppm) on the response of an electrochemical fuel cell sensor have been investigated over time (0-400 s). These studies have identified changes in the response of the fuel cell with time after sampling. In particular, it has been found that the maximum cell output for water vapour occurs ca. 10 s after sampling whilst the response to glutaraldehyde occurs much later (> 100 s). For mixtures containing different ratios of water and glutaraldehyde vapours, the time taken to reach maximum fuel cell response varies between 10 and 100 s, depending on the ratio of the two vapours. For instance, glutaraldehyde vapour containing higher % RH has been found to result in shorter times to reach maximum fuel cell response. A comparison was made between measuring glutaraldehyde vapour concentrations in the presence of water vapour at the maximum fuel cell response and also at a fixed interval (240 s) after sampling. Such a comparison resulted in a reduction in the standard error from 36% to 5% for a glutaraldehyde vapour sample (0.023 ppm) measured at different values of relative humidity (40 to 80%). Examination of the effect of the sample volume (30-60 ml) on the response of the fuel cell shows, as expected, an approximate doubling of the fuel cell response. Optimisation of the fuel cell measurement parameters to measure a 60 ml sample leads to a lowering of the limit of detection from 0.083 ppm (for data taken at the maximum cell response) to 0.017 ppm for data measured 240 s after sampling. In the light of recent reductions in the legal limits for exposure to glutaraldehyde, this has important implications for the measurement of glutaraldehyde vapour in the workplace.