Abstract

Learning facilitates behavioral plasticity, leading to higher success rates when foraging. However, memory is of decreasing value with changes brought about by moving to novel resource locations or activity at different times of the day. These premises suggest a foraging model with location- and time-linked memory. Thus, each problem is novel, and selection should favor a maximum likelihood approach to achieve energy maximization results. Alternatively, information is potentially always applicable. This premise suggests a different foraging model, one where initial decisions should be based on previous learning regardless of the foraging site or time. Under this second model, no problem is considered novel, and selection should favor a Bayesian or pseudo-Bayesian approach to achieve energy maximization results. We tested these two models by offering honey bees a learning situation at one location in the morning, where nectar rewards differed between flower colors, and examined their behavior at a second location in the afternoon where rewards did not differ between flower colors. Both blue-yellow and blue-white dimorphic flower patches were used. Information learned in the morning was clearly used in the afternoon at a new foraging site. Memory was not location-time restricted in terms of use when visiting either flower color dimorphism.

Highlights

  • Many insect nectivores experience changing floral composition in resource patches over their foraging life [1]

  • In all four experiments flower color choice in the afternoon foraging location was highly predictable from the behavior observed at the morning foraging site

  • Flower color was remembered from the earlier foraging experience and used in the afternoon at the new location

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Summary

Introduction

Many insect nectivores experience changing floral composition in resource patches over their foraging life [1]. Even relatively short-lived foragers like honey bees face changes in nectar and pollen sources that have different reward potentials and associated costs This situation creates a fundamental problem for foragers. The forager approximates the initial distribution of possible results associated with alternative flower choices based on prior learned information from completely different foraging situations, and continually updates estimates as it forages [48,49]. This seems cognitively possible for honey bees based on the work of. We report on whether foragers restrict use of reward information linked to a specific time and location in the environment (space-time linked memory), and use a maximum likelihood “new problem approach”, or whether they apply information learned earlier in different contexts (different location and time) to new situations in a Bayesian type of strategy

Experimental Section
Blue and Yellow Flowers
Blue and White Flowers
Data Analysis
Results and Discussion
Blue-Yellow Dimorphic Flower Patches
Blue-White Dimorphic Flower Patches
Conclusions
Angiosperm Evolution
Agricultural Settings
Full Text
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