Skip to main content

Advertisement

Log in

Adaptive tuning of the exploitation-exploration trade-off in four honey bee species

  • Original Article
  • Published:
Behavioral Ecology and Sociobiology Aims and scope Submit manuscript

Abstract

Foraging animals continually face the decision of whether to exploit known resources or explore for new ones, a decision with large implications for their fitness. Though animal foraging decisions have been extensively studied, we currently lack a deep understanding of how the exploitation-exploration trade-off has evolved, including how it is shaped by divergent selection pressures between species. As a first step towards examining how the exploitation-exploration trade-off has been adaptively tuned by natural selection, we compared the exploratory behavior of four honey bee species that differ in traits such as nest architecture, body size, and colony size. In a common behavioral context—exploratory behavior triggered by a decrease in quality of a known food resource—we found species differences in exploratory behavior that are consistent with selection arising from evolved differences in nest architecture, though the behavioral differences were also strongly influenced by the magnitude of the reward decrease. We had expected that species that build their nests in the open, and hence face a higher fitness cost of worker attrition compared with species that inhabit protective cavities, would be less likely to prolong unrewarded search when food declines in quality. The behavioral data were partially consistent with this expectation. However, at times, the environmental context strongly modulated species differences in behavior that would be expected based on nest architecture. Overall, our results suggest that the resolution of the exploitation-exploration trade-off has been adaptively tuned between species by a number of interacting selection pressures.

Significance statement

Foraging animals must constantly decide whether to exploit known resources or explore for new, potentially better, ones. How animals resolve this trade-off is likely to have a cumulative effect on their fitness, so natural selection should shape it according to species-specific differences in life history. Using an experimental approach comparing four honey bee species, our results suggest that the tendency to engage in costly search is shaped by multiple interactions among selection pressures differing between honey bee species. We found a correlation between search and how species build their nests, with species nesting in the open generally searching less than those nesting in cavities. However, past experience with a reward can sometimes interact with or overshadow the patterns expected based on nesting behavior. These patterns highlight the complicated effects of life history and ecology on the evolution of behavior.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data availability

The datasets generated during and/or analyzed during the current study are available in this published article and/or its supplementary information files.

References

  • Al Toufailia H, Grüter C, Ratnieks FL (2013) Persistence to unrewarding feeding locations by honeybee foragers (Apis mellifera): the effects of experience, resource profitability and season. Ethology 119:1096–1106

    Article  Google Scholar 

  • Berger-Tal O, Avgar T (2012) The glass is half-full: overestimating the quality of a novel environment is advantageous. PLoS One 7:e34578

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Bhagavan H, Muthmann O, Brockmann A (2016) Structural and temporal dynamics of the bee curtain in the open-nesting honey bee species, Apis florea. Apidologie 47:749–758

    Article  CAS  Google Scholar 

  • Chole H, Woodard SH, Bloch G (2019) Body size variation in bees: regulation, mechanisms, and relationship to social organization. Curr Opin Insect Sci 35:77–87

    Article  PubMed  Google Scholar 

  • Cook Z, Franks DW, Robinson EJ (2013) Exploration versus exploitation in polydomous ant colonies. J Theor Biol 323:49–56

    Article  PubMed  Google Scholar 

  • Corbet SA, Unwin DM, Prŷs-Jones OE (1979) Humidity, nectar and insect visits to flowers, with special reference to Crataegus, Tilia and Echium. Ecol Entomol 4:9–22

    Article  Google Scholar 

  • Danner N, Molitor AM, Schiele S, Härtel S, Steffan-Dewenter I (2016) Season and landscape composition affect pollen foraging distances and habitat use of honey bees. Ecol Appl 26:1920–1929

    Article  PubMed  Google Scholar 

  • Delaney JT, Jokela KJ, Debinski DM (2015) Seasonal succession of pollinator floral resources in four types of grasslands. Ecosphere 6:1–14

    Article  Google Scholar 

  • Dyer FC (1985) Nocturnal orientation by the Asian honey bee, Apis dorsata. Anim Behav 33:769–774

    Article  Google Scholar 

  • Dyer FC, Seeley TD (1987) Interspecific comparisons of endothermy in honey-bees (Apis): deviations from the expected size-related patterns. J Exp Biol 127:1–26

    Article  Google Scholar 

  • Dyer FC, Seeley TD (1991) Nesting behavior and the evolution of worker tempo in four honey bee species. Ecology 72:156–170

    Article  Google Scholar 

  • Eliassen S, Jørgensen C, Mangel M, Giske J (2007) Exploration or exploitation: life expectancy changes the value of learning in foraging strategies. Oikos 116:513–523

    Article  Google Scholar 

  • Flaherty CF (1982) Incentive contrast: a review of behavioral changes following shifts in reward. Anim Learn Behav 10:409–440

    Article  Google Scholar 

  • Fry CH (1983) Honeybee predation by bee-eaters, with economic considerations. Bee World 64:65–78

    Article  Google Scholar 

  • Harrison JF, Fewell JH (2002) Environmental and genetic influences on flight metabolic rate in the honey bee, Apis mellifera. Comp Biochem Phys A Mol Integr Physiol 133:323–333

    Article  Google Scholar 

  • Kapil RP (1959) Variation in the developmental period of the Indian bee. Indian BeeJ 21:3–6

    Google Scholar 

  • Kastberger G, Sharma DK (2000) The predator-prey interaction between blue-bearded bee eaters (Nyctyornis athertoni Jardine and Selby 1830) and giant honeybees (Apis dorsata Fabricius 1798). Apidologie 31:727–736

    Article  Google Scholar 

  • Katz K, Naug D (2015) Energetic state regulates the exploration–exploitation trade-off in honeybees. Behav Ecol 26:1045–1050

    Article  Google Scholar 

  • Katz K, Naug D (2016) Dancers and followers in a honeybee colony differently prioritize individual and colony nutritional needs. Anim Behav 119:69–74

    Article  Google Scholar 

  • Kerr NZ, Crone EE, Williams NM (2019) Integrating vital rates explains optimal worker size for resource return by bumblebee workers. Funct Ecol 33:467–478

    Article  Google Scholar 

  • Kotler BP, Brown JS, Bouskila A (2004) Apprehension and time allocation in gerbils: the effects of predatory risk and energetic state. Ecology 85:917–922

    Article  Google Scholar 

  • Kramer DL, Weary DM (1991) Exploration versus exploitation: a field study of time allocation to environmental tracking by foraging chipmunks. Anim Behav 41:443–449

    Article  Google Scholar 

  • Lichtenberg EM, Heiling JM, Bronstein JL, Barker JL (2020) Noisy communities and signal detection: why do foragers visit rewardless flowers? Philos Trans R Soc B 375:20190486

    Article  Google Scholar 

  • Lima SL, Dill LM (1990) Behavioral decisions made under the risk of predation: a review and prospectus. Can J Zool 68:619–640

    Article  Google Scholar 

  • Lindauer M, Watkin B (1953) Division of labour in the honeybee colony. Bee World 34:63–73

    Article  Google Scholar 

  • Mardan M, Kevan PG (1989) Honeybees and ‘yellow rain’. Nature 341:191–191

    Article  Google Scholar 

  • McNamara J (1982) Optimal patch use in a stochastic environment. Theor Popul Biol 21:269–288

    Article  Google Scholar 

  • McNamara JM, Fawcett TW, Houston AI (2013) An adaptive response to uncertainty generates positive and negative contrast effects. Science 340:1084–1086

    Article  CAS  PubMed  Google Scholar 

  • Mehlhorn K, Newell BR, Todd PM, Lee MD, Morgan K, Braithwaite VA, Hausmann D, Fiedler K, Gonzalez C (2015) Unpacking the exploration–exploitation tradeoff: a synthesis of human and animal literatures. Decision 2:191–215

    Article  Google Scholar 

  • Müller CB, Blackburn TM, Schmid-Hempel P (1996) Field evidence that host selection by conopid parasitoids is related to host body size. Insect Soc 43:227–233

    Article  Google Scholar 

  • Oldroyd BP, Wongsiri S (2009) Asian honey bees: biology, conservation, and human interactions. Harvard University Press, Cambridge

  • Page RE, Fondrk MK (1995) The effects of colony-level selection on the social organization of honey bee (Apis mellifera L.) colonies: colony-level components of pollen hoarding. Behav Ecol Sociobiol 36:135–144

    Article  Google Scholar 

  • Page RE, Robinson GE, Fondrk MK, Nasr ME (1995) Effects of worker genotypic diversity on honey bee colony development and behavior (Apis mellifera L.). Behav Ecol Sociobiol 36:387–396

    Article  Google Scholar 

  • Pankiw T (2003) Directional change in a suite of foraging behaviors in tropical and temperate evolved honey bees (Apis mellifera L.). Behav Ecol Sociobiol 54:458–464

    Article  Google Scholar 

  • Patrick SC, Pinaud D, Weimerskirch H (2017) Boldness predicts an individual’s position along an exploration–exploitation foraging trade-off. J Anim Ecol 86:1257–1268

    Article  PubMed  PubMed Central  Google Scholar 

  • Pecoraro NC, Timberlake WD, Tinsley M (1999) Incentive downshifts evoke search repertoires in rats. J Exp Psychol Anim Behav Process 25:153–167

    Article  CAS  PubMed  Google Scholar 

  • Pyke GH (1984) Optimal foraging theory: a critical review. Annu Rev Ecol Evol Syst 15:523–575

    Article  Google Scholar 

  • Pyke G (2019) Optimal foraging theory: an introduction. In: Breed MD, Moore J (eds) Encyclopedia of animal behavior. Elsevier Academic Press, London, pp 111–117

    Chapter  Google Scholar 

  • Raffiudin R, Crozier RH (2007) Phylogenetic analysis of honey bee behavioral evolution. Mol Phylogenet Evol 43:543–552

    Article  CAS  PubMed  Google Scholar 

  • Rana RS, Verma LR (1994) Hoarding behaviour and lifespan of workers of Apis mellifera and Apis cerana. J. Apic Res 33:205–208

    Article  Google Scholar 

  • Robinson GE (1992) Regulation of division of labor in insect societies. Annu Rev Entomol 37:637–665

    Article  CAS  PubMed  Google Scholar 

  • Ruttner F (1988) Biogeography and taxonomy of honeybees. Springer, Berlin, Germany

    Book  Google Scholar 

  • Sandhu AS, Singh S (1960) The biology and brood rearing activities of the little honeybee (Apis florea Fabricius). Indian Bee J 22:27–35

    Google Scholar 

  • Santhosh S, Basavarajappa S (2016) Study on nectar plants of few butterfly species at agriculture ecosystems of Chamarajanagar District, Karnataka, India. Inter J Entomol Res 1:40–48

    Google Scholar 

  • Seeley TD (1983) Division of labor between scouts and recruits in honeybee foraging. Behav Ecol Sociobiol 12:253–259

    Article  Google Scholar 

  • Seeley TD (1985) Honeybee ecology: a study of adaptation in social life. Princeton University Press, Princeton

    Book  Google Scholar 

  • Seeley TD (1995) The wisdom of the hive. Harvard University Press, Cambridge

    Book  Google Scholar 

  • Seeley TD, Seeley RH, Akratanakul P (1982) Colony defense strategies of the honeybees in Thailand. Ecol Monogr 52:43–63

    Article  Google Scholar 

  • Singh KP, Kushwaha CP (2006) Diversity of flowering and fruiting phenology of trees in a tropical deciduous forest in India. Ann Bot 97:265–276

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Stephens DW (1987) On economically tracking a variable environment. Theor Popul Biol 32:15–25

    Article  Google Scholar 

  • Stephens DW, Krebs JR (1986) Foraging theory. Princeton University Press, Princeton

    Google Scholar 

  • Szabo TI, Heikel DT (1987) Patterns of honeybee colony gain in Alberta, Canada. Journal Apic Res 26:47–45

    Article  Google Scholar 

  • Tan NQ (2007) Biology of Apis dorsata in Vietnam. Apidologie 38:221–229

    Article  Google Scholar 

  • Townsend-Mehler JM, Dyer FC (2012) An integrated look at decision-making in bees as they abandon a depleted food source. Behav Ecol Sociobiol 66:275–286

    Article  Google Scholar 

  • Townsend-Mehler JM, Dyer FC, Maida K (2011) Deciding when to explore and when to persist: a comparison of honeybees and bumble bees in their response to downshifts in reward. Behav Ecol Sociobiol 65:305–312

    Article  Google Scholar 

  • Underwood BA (1991) Thermoregulation and energetic decision-making by the honeybees Apis cerana, Apis dorsata and Apis laboriosa. J Exp Biol 157:19–34

    Article  Google Scholar 

  • Visscher PK, Crailsheim K, Sherman G (1996) How do honey bees (Apis mellifera) fuel their water foraging flights? J Insect Physiol 42:1089–1094

    Article  CAS  Google Scholar 

  • Wajnberg E, Fauvergue X, Pons O (2000) Patch leaving decision rules and the marginal value theorem: an experimental analysis and a simulation model. Behav Ecol 11:577–586

    Article  Google Scholar 

  • Waldron FA, Wiegmann DD, Wiegmann DA (2005) Negative incentive contrast induces economic choice behavior by bumble bees. Int J Comp Psychol 18:4

    Article  Google Scholar 

  • Wei CA, Dyer FC (2009) Investing in learning: why do honeybees, Apis mellifera, vary the durations of learning flights? Anim Behav 77:1165–1177

    Article  Google Scholar 

  • Wiegmann DD, Smith BH (2009) Incentive relativity and the specificity of reward expectations in honey bees. Int J Comp Psychol 22:3

    Article  Google Scholar 

  • Winston ML (1991) The biology of the honey bee. Harvard University Press, Cambridge

    Google Scholar 

  • Yogeswaran M, Ponnambalam SG (2012) Reinforcement learning: exploration–exploitation dilemma in multi-agent foraging task. Opsearch 49:223–236

    Article  Google Scholar 

Download references

Acknowledgments

We would like to thank Emily Mall and Julia Fudala for their help with data collection and the Michigan State University Center for Statistical Training and Consulting for assistance with statistical analyses. We would also like to thank two anonymous reviewers for constructive feedback on this manuscript.

Funding

This work was supported by a National Science Foundation Graduate Research Fellowship (DGE-1848739 to AY), a National Science Foundation Graduate Research Opportunities Worldwide Fellowship jointly funded by the National Science Foundation and the Science and Engineering Research Board, administered by the Indo-US Science and Technology Forum (DGE-1848739 to AY), and a Fulbright-Nehru Fellowship jointly funded by the US Department of State and the Republic of India (2018/ST/89 to AY). This work was also supported by the Michigan State University Department of Integrative Biology. Research in AB’s lab is supporteds by institutional funding from the National Centre for Biological Sciences (NCBS-TIFR; 12P4167) and the Department of Atomic Energy, Government of India, under 472 project no. 12-R&D-TFR-5.04-0800.

Author information

Authors and Affiliations

Authors

Contributions

Not applicable.

Corresponding author

Correspondence to Allison M. Young.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Code availability

The R code used to analyze data during the current study is available in this published article and/or its supplementary information files.

Additional information

Communicated by O. Rueppell

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

ESM 1

(DOCX 97 kb)

ESM 2

(R 23 kb)

ESM 3

(CSV 28 kb)

ESM 4

(CSV 28 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Young, A.M., Brockmann, A. & Dyer, F.C. Adaptive tuning of the exploitation-exploration trade-off in four honey bee species. Behav Ecol Sociobiol 75, 20 (2021). https://doi.org/10.1007/s00265-020-02938-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00265-020-02938-6

Keywords

Navigation