Different solutions by bees to a foraging problem

Çakmak, İbrahim; Sanderson, Charlotte; Blocker, Tomica D.; Pham, L. Lisa; Checotah, Sky; Norman, Ashley A.; Harader-Pate, Brice K.; Reidenbaugh, R. Tyler; Nenchev, P.; Barthell, John F.; Wells, Harrington

doi:10.1016/j.anbehav.2009.01.032

Cited by 34 publications

(34 citation statements)

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“…Keasar, Motro, Shur, & Shmida, 1996;Worden et al, 2005), as well as in a study of their foraging behaviour on wild complex flowers (Laverty, 1994). Similar findings have also been reported for honeybees tested under similar conditions, where individuals varied in what flower type they specialized on when choosing between artificial flowers with high rewards but high handling times and low rewards and low handling times (Cakmak et al, 2009). Flower preferences were also heavily influenced by unlearned colour preferences in that species, as bees would restrict their visits to either blue or white flowers regardless of reward or cost of accessing the reward.…”

Section: Discussionsupporting

confidence: 71%

“…A greater number of cues could mean less variation between individuals as they can more readily identify a particular highly rewarding flower (Gegear & Laverty, 2005;. Alternatively, it could lead to more variation as differences in individuals' perceptual abilities are emphasized (Cakmak et al, 2009). Discerning this would help us better understand how individual differences in this context arise.…”

Section: Discussionmentioning

confidence: 95%

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Trading off short-term costs for long-term gains: how do bumblebees decide to learn morphologically complex flowers?

Muth

Keasar

2015

Animal Behaviour

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Section: Discussionsupporting

confidence: 71%

Section: Discussionmentioning

confidence: 95%

Trading off short-term costs for long-term gains: how do bumblebees decide to learn morphologically complex flowers?

Muth

Keasar

2015

Animal Behaviour

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“…By trial 6 in each treatment, bees chose the rewarding disk over 90% of the time (Fig.2). These results are comparable to success rates of bees visiting artificial flower patches where the choice is between blue flowers and white flowers; they choose the rewarding flower color 80 to 90% of the time (Wells and Wells, 1986;Hill et al, 1997;Cakmak et al, 2009). Similar success rates have been observed using harnessed bees discriminating between odors such as cinnamon and lavender oils as conditioning stimuli (Bitterman et al, 1983;Abramson and Boyd, 2001; Abramson et al, 2010).…”

Section: Discussionsupporting

confidence: 69%

Feature-positive and feature-negative learning in honey bees

Abramson

Çakmak

Duell

et al. 2012

Journal of Experimental Biology

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SUMMARYHoney bees (Apis mellifera anatolica) were subjected to sequential trials where they were given the choice between a featurepositive and a feature-negative feeding plate. The ʻfeatureʼ being manipulated is the presence of a single blue circle among three circles marking the location of a small sucrose reward. That is, a ʻfeature-negativeʼ target had three white circles, while a ʻfeature-positiveʼ target had two white circles and one blue one. Two experiments were performed. In both experiments, each bee was tested under two different reward scenarios (treatments). In the first experiment, during the feature-positive treatment bees received 4μl of 2moll -1 sucrose when choosing the feature-positive plate, but received 4μl of saturated NaCl solution (saltwater) when choosing the feature-negative plate. During the feature-negative treatment, bees were rewarded when visiting the featurenegative plate, while visitation to the feature-positive plate only offered bees the saltwater. The second experiment was a repeat of the first except that pure water was offered instead of saltwater in the non-rewarding feeding plate. As an experimental control, a set of bees was offered sequential trials where both the feature-positive and feature-negative plates offered the sucrose reward. Bee feeding plate choice differed between the feature-positive and feature-negative treatments in both experiments. Bees favored the feeding plate type with the sucrose reward in each treatment, and never consumed the saltwater or pure water when encountered in either treatment. Further, behavior of bees during both the feature-positive and feature-negative treatments differed from that of control bees. However, neither feature-positive nor feature-negative learning reached high levels of success. Further, a feature-positive effect was seen when pure water was offered; bees learned to solve the feature-positive problem more rapidly. When we tested bees using simply the choice of blue versus white targets, where one color held the sucrose reward and the other the saltwater, a beeʼs fidelity to the color offering the sucrose reward quickly reached very high levels.

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“…However, given that all locations had contained rewards some of the time, depending on the reinforcement contingency in force in a particular phase, squirrels that preferred to use the sequential search behaviour might not be making 'errors' but instead using an alternative strategy in foraging (Evans & Raine, 2014), involving a different speed/accuracy trade-off (Chittka, Dyer, Bock, & Dornhaus, 2003) in the face of a complex design (Cakmak et al, 2009), even if the time cost of sequential tactics is higher Being flexible to achieve efficiency 20 than that of integrative tactics. A quick but inaccurate foraging style has been shown to be adaptive in some foraging situations (Burns, 2005).…”

Section: Discussionmentioning

confidence: 99%

Serial reversal learning in gray squirrels: Learning efficiency as a function of learning and change of tactics.

Chow¹,

Leaver²,

Wang³

et al. 2015

Journal of Experimental Psychology: Animal Learning and Cogniti

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Learning allows individuals to adapt their behaviours flexibly to changing environment. When the same change recurs repeatedly, acquiring relevant tactics may increase learning efficiency under recurring change. We examined this relationship, along with the effects of proactive interference and other interference information, in a serial spatial reversal task with five grey squirrels (Sciurus carolinensis). Squirrels completed an acquisition and 11 reversal phases with a poke box in which two out of four possible reward locations were baited diagonally in a square array. In this situation, an efficient tactic is to locate the diagonally related locations consecutively (integrative search tactic) instead of searching rewards in a clockwise or anti-clockwise direction (sequential search tactic). All the squirrels formed a learning set acquiring successive reversals in fewer trials. Although four individuals gradually employed more integrative tactics in locating the rewards both within and between phases, sequential tactics were used in the first trial of each phase. This suggests the integrative tactic did not depend on an association between the rewarded locations but was learned as a spatial pattern and/or by use of extra-apparatus cues to locate individual reward. Generalized Estimating Equation (GEE) models showed that learning efficiency increased with experience and tactic change. Although tactic change partially mediated the effect of learning on learning efficiency, learning retained an independent contribution to improved efficiency. Squirrels that used integrative tactics more made less total errors than squirrels that used less; suggesting learning a task relevant tactic using spatial cues can provide direct benefits in maximising rewards and minimising time costs.

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Different solutions by bees to a foraging problem

Cited by 34 publications

References 50 publications

Trading off short-term costs for long-term gains: how do bumblebees decide to learn morphologically complex flowers?

Trading off short-term costs for long-term gains: how do bumblebees decide to learn morphologically complex flowers?

Feature-positive and feature-negative learning in honey bees

Serial reversal learning in gray squirrels: Learning efficiency as a function of learning and change of tactics.

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