Colony-level non-associative plasticity of alarm responses in the stingless honey bee, Tetragonisca angustula

  • Christopher M. JerniganEmail author
  • Justas Birgiolas
  • Cora McHugh
  • David W. Roubik
  • William T. Wcislo
  • Brian H. Smith
Original Article


In ants, bees, and other social Hymenoptera, alarm pheromones are widely employed to coordinate colony nest defense. In that context, alarm pheromones elicit innate species-specific defensive behaviors. Therefore, in terms of classical conditioning, an alarm pheromone could act as an unconditioned stimulus (US). Here, we test this hypothesis by establishing whether repeated exposure to alarm pheromone in different testing contexts modifies the alarm response. We evaluate colony-level alarm responses in the stingless bee, Tetragonisca angustula, which has a morphologically distinct guard caste. First, we describe the overall topology of defense behaviors in the presence of an alarm pheromone. Second, we show that repeated, regular exposure to synthetic alarm pheromone reduces different components of the alarm response, and memory of that exposure decays over time. This observed decrease followed by recovery occurs over different time frames and is consistent with behavioral habituation. We further tested whether the alarm pheromone can act as a US to classically condition guards to modify their defense behaviors in the presence of a novel (conditioned) stimulus (CS). We found no consistent changes in the response to the CS. Our study demonstrates the possibility that colony-level alarm responses can be adaptively modified by experience in response to changing environmental threats. Further studies are now needed to reveal the extent of these habituation-like responses in regard to other pheromones, the potential mechanisms that underlie this phenomenon, and the range of adaptive contexts in which they function at the colony level.

Significance statement

Pheromones are classically thought to elicit stereotyped action patterns. Here, we test the idea that responses to pheromones are plastic and show characteristics of an unconditioned stimulus. This study demonstrates clear non-associative plasticity in the colony-level response to alarm pheromone, in the stingless honey bee, Tetragonisca angustula. Colonies of T. angustula show habituation-like responses across multiple measures to repeated stimulation of their alarm pheromone. We therefore demonstrate that colony-level responses to pheromones are adaptively plastic. Finally, we failed to demonstrate colony-level conditioning using alarm pheromone as the unconditioned stimulus; however, these findings and others warrant further investigation.


Stingless honey bee Tetragonisca angustula Colony-level plasticity Colony defense Alarm pheromone 



We would like to thank Sonia Villa and Erik Rohner for their support helping to analyze video recordings. We would also like to thank Richard C. Gerkin for input on the analyses, and the anonymous reviewers for their comments on the manuscript.

Funding information

C. M. Jernigan was supported by joint grants from Arizona State University and the Smithsonian Tropical Research Institute during data collection, and teaching assistantships from Arizona State University, School of Life Sciences. J. Birgiolas was supported by an Arizona State University Interdisciplinary Graduate Program in Neuroscience fellowship and NIH grants F31DC016811 to JB and R01MH1006674 to Sharon M. Crook. This work was also supported by an award from NIH-NIGMS (GM113967) to BHS.

Supplementary material

265_2018_2471_MOESM1_ESM.pdf (10.5 mb)
Figure S1 A. Diagram of attack by Tetragonisca angustula (left) on potential robber bee presented to hovering guards (right). B. A photograph of T. anglustula (upper-right), which performed a “death grip” on the wing of a stingless bee raider (left, Trigona sp.). The potential raider was observed near the T. angustula nest and was likely scouting to recruit a raid on the T. angustula nest. (PDF 10789 kb)
265_2018_2471_MOESM2_ESM.pdf (598 kb)
Figure S2 The mean change in guard number from just before (pre-AP) to during synthetic alarm pheromone presentation (AP). There is also an unaccounted change in total guard number from before to after AP presentation, represented by the unaccounted change column. Error bars represent standard error from the mean. (two-tailed, one sample Student’s t test ***p < 0.001) Standing: two-tailed t test, t-value = − 6.81, df = 32, p<<<0.001; hovering: t test, t-value = 6.69, df = 32, p<<<0.001, unaccounted difference: t test, t-value = 3.648, df = 32, p < 0.001). Analysis of a total of 34 observation periods during AP stimulation of 6 colonies. (PDF 597 kb)
265_2018_2471_MOESM3_ESM.pdf (1.3 mb)
Figure S3 A. The mean net inflow of bees before (PR), during (AP) and after (PO) synthetic alarm pheromone presentation pooled by time of day. All morning presentations are denoted in light gray and all afternoon presentations are denoted in dark gray (PR: ANOVA, F-value = 0.103, df = 1, p = 0.05, AP: ANOVA, F-value = 1.01, df = 1, p = 0.32, PO: ANOVA, F-value = 0.004, df = 5, p = 0.948). Error bars represent standard error of the mean. Analysis of a total of 212 observations of 6 colonies, and 3 periods of stimulation before during and after AP. B. The mean percent change in flight activity (measured by frame-to-frame changes in video pixels) from mineral oil (MO) to synthetic alarm pheromone presentation (AP) presentation pooled by time of day presented (ANOVA, F-value = 0.483, df = 1, p = 0.495). Error bars represent standard error of the mean. Analysis of 55 observations of 6 colonies. C. The mean number of guards during mineral oil (MO) presentation pooled by time of day. Column shading as in “A.” No effect of time of day on the number of standing guards (F-value = 1.47, df = 1, p = 0.2330) but a significant effect of time as reported by Grüter et al. (2011) (ANOVA, F-value = 5.84, df = 1, p = 0.02). Error bars represent standard error of the mean (Tukey HSD *p < 0.05). Analysis of 37 observations of 6 colonies during MO stimulation. D. The mean number of guards during synthetic alarm pheromone (AP) presentation pooled by time of day. Column shading as in “A.” During AP there was a significant effect of time of day on both the number of standing (ANOVA, F-value = 6.158, df = 1, p = 0.0180) and hovering guards (ANOVA, F-value = 5.494, df = 1, p = 0.015). Error bars represent standard error of the mean (Tukey HSD *p < 0.05). Analysis of 37 observations of 6 colonies during AP stimulation. (PDF 1353 kb)
265_2018_2471_MOESM4_ESM.pdf (703 kb)
Figure S4 The mean net influx rate of bees entering the nest (bees/min) during various stimulus presentations and pairings: sponge only present (SO), sponge with mineral oil stimulus (MO), sponge with synthetic alarm pheromone and Octane pairing (AP/Oct), sponge with octane only (Oct), sponge with synthetic alarm pheromone and 3-Heptanal pairing (AP/3-Hept), and sponge with 3-Heptanal only (3-Hept). First exposure to stimulus is denoted in dark gray and the pooled following stimulus presentations are denoted in light gray. Error bars represent standard error of the mean. We are only presenting the net influx rates as those seemed to be the some of the most robust measures we tested to determine significant impacts on colony behavior. Summary of 163 observations of 5 colonies. Supplemental Analyses: GLM: We performed a model fit of the data that describes a decay and recovery phase defined by the following equation: y = c*(1 + (-TauFast*t)-(TauSlow*t)) (c, TauFast, and TauSlow are fit constants, t is time since previous exposure (hrs), and y is one of the colony measures discussed). This gave us a saddle or inflection point for each measure y. We then performed a GLM analysis separately on the decay phase and recovery phase of the model using R (R core team, 2016) looking at the interacting factors of time since previous exposure (t) and total number of alarm pheromone exposures on the measure y. We used a Gaussian distribution or Poisson distribution during these analyses when appropriate based upon the observed data structure of y. We also performed a chi squared model fit test comparing the above model with a null model in which just number of alarm pheromone (AP) exposures was predicting the measure y. (PDF 703 kb)
265_2018_2471_MOESM5_ESM.pdf (1.6 mb)
Figure S5 Plots of measures during alarm pheromone (AP) exposure minus the measure during mineral oil exposure vs. the time (t) since previous AP exposure (hrs). The points in each plot are the data and the solid line is a model fit of the data, described in supplemental analyses. The vertical dashed line indicates the saddle or inflection point as defined by the model fit, and separates the decay phase and the recovery phases observed in the data. A. The number of attacks during AP stimulation, this is also the difference between this measure and mineral oil, as there were never any attacks observed during mineral oil stimulation. The model fits the saddle point to be 4.5 h. The decay phase shows a non-significant effect of t (GLM, estimate = 0.535, z-value = 1.704, p = 0.089), a significant effect of the number of AP exposures (GLM, estimate = − 1.539, z-value = − 3.766, p < 0.001), and a non-significant interaction (GLM, estimate = − 0.032, z-value = − 0.201, p = 0.841). The decay model still has a better fit of the data than the null (χ2, p = 0.02). The recovery phase shows a non-significant effect of t (GLM, estimate = − 0.01, z-value = − 0.835, p = 0.404), a significant effect of number of AP exposures (GLM, estimate = − 0.662, z-value = − 4.483, p < 0.001), and a significant interaction (GLM, estimate = 0.009, z-value = 2.527, p = 0.011). The recovery model fits significantly better than the null (χ2, p < 0.001). B. The number of bees attacking during AP stimulation, this is also the difference between this measure and mineral oil, as there were never any attacks observed during mineral oil stimulation. The model fits the saddle to be 1.2 h. The decay phase shows a significant effect of t (GLM, estimate = − 1.162, z-value = − 2.853, p = 0.004). There were not enough measures in the 1.2 h to test the number of exposures or the interaction. The recovery phase shows a significant effect of t (GLM, estimate = 0.028, z-value = 2.245, p = 0.025), a non-significant effect of number of AP exposures (GLM, estimate = − 0.242, z-value = − 1.609, p = 0.12), and a non-significant interaction (GLM, estimate = − 0.001, z-value = − 0.533, p = 0.594). The recovery model is significantly better fit than the null (χ2, p < 0.001). C. The net forager influx rate (bees/min) difference between AP and mineral oil stimulation plotted against the time since previous alarm pheromone exposure. The model fits the saddle to be at 3.7 h. The decay phase shows non-significant effect of both t (GLM, estimate = 5.27, t-value = 0.399, p = 0.701) and number of AP exposures on observed measures (GLM, estimate = − 0.466, t-value = − 0.03, p = 0.977), and no difference from null model (χ2, p = 0.9). However, the recovery phase shows a significant effect of t (GLM, estimate = 1.159, t-value = 3.426, p = 0.003), number of exposures (GLM, estimate = 7.935, t-value = 2.198, p = 0.04), and an interaction (GLM, estimate = − 0.283, t-value = − 3.204, p = 0.005). The recovery has a significantly better fit than the null model (χ2, p = 0.003). D. The colony activity change during AP simulation and mineral oil stimulation vs. the time since previous AP exposure (hrs). The model fits the saddle point to be 30.6 h. Both the recovery and the decay showed non-significant differences from the null models (χ2, p > 0.6) and no significant effect of either t or number of AP exposures on activity (GLM, p > 0.5). There was also no significant interaction between the two (GLM, p > 0.6) (PDF 1641 kb)
265_2018_2471_MOESM6_ESM.pdf (1.1 mb)
Table S1 The test statistics for ANOVA and paired t test outputs of the novel odor-alarm pheromone paring tests. Presenting for number of bees attacking, number of attacks, and average percent flight activity change between mineral oil and alarm stimulation. All tests are non-significant. (MP4 356,640 kb) (PDF 1089 kb)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Christopher M. Jernigan
    • 1
    • 2
    Email author
  • Justas Birgiolas
    • 1
  • Cora McHugh
    • 1
  • David W. Roubik
    • 2
  • William T. Wcislo
    • 2
  • Brian H. Smith
    • 1
  1. 1.School of Life Sciences, Arizona State UniversityTempeUSA
  2. 2.Smithsonian Tropical Research InstituteBalboaRepublic of Panama

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