String pulling is one of the most extensively used approaches in comparative psychology to evaluate the understanding of causal relationships (Jacobs and Osvath, 2015), with most research focused on mammals and birds, where a food item is visible to the animal but accessible only by pulling on a string attached to the reward (Taylor et al., 2010; Range et al., 2012; Jacobs and Osvath, 2015; Wakonig et al., 2021). A fundamental challenge in animal cognition research revolves around unraveling the strategies that animals employ when confronted with specific tasks (de Waal and Ferrari, 2010; Shettleworth, 2010; Chittka et al., 2012). The complexity of the string-pulling paradigm can be altered by manipulating the number and mutual positions of the strings and reward, allowing the investigation of different aspects of cognition (Jacobs and Osvath, 2015; Wang et al., 2019). Multiple mechanisms can be involved in the string-pulling task, including the proximity principle, perceptual feedback and means-end understanding (Taylor et al., 2012; Wasserman et al., 2013; Jacobs and Osvath, 2015; Wang et al., 2021). The principle of proximity refers to animals preferring to pull the reward that is closest to them (Jacobs and Osvath, 2015). Taylor et al., 2012 proposed that the success of New Caledonian crows in string-pulling tasks is based on a perceptual-motor feedback loop, where the reward gradually moves closer to the animal as they pull the strings. If the visual signal of the reward approaching is restricted, crows with no prior string-pulling experience are unable to solve the broken string task (Taylor et al., 2012).

Means-end understanding is expressed as goal-directed behavior, which involves the deliberate and planned execution of a sequence of steps to achieve a goal (Jacobs and Osvath, 2015; Torres Ortiz et al., 2019). String-pulling studies have directly tested means-end comprehension in various species (Riemer et al., 2014; Jacobs and Osvath, 2015). In these studies, organisms are presented with two or more strings, where one is connected to a reward and the other one is interrupted; pulling the connected string indicates that animals comprehend that a continuous string is a means to the end of obtaining the reward (Piaget, 1953; Wasserman et al., 2013; Jacobs and Osvath, 2015; Hofmann et al., 2016; Wang et al., 2019). Most animals fail in such string-pulling tasks when they have to spontaneously solve them, but they can be trained to recognize that an interrupted string is useless through trial-and-error learning (Mayer et al., 2014; Torres Ortiz et al., 2019; Wang et al., 2019).

To our knowledge, bumblebees are the only invertebrates that have been trained to learn to pull a string to obtain a reward (Alem et al., 2016; Wen et al., 2024; Zhou et al., 2024). However, the performance of bumblebees in these studies could be explained by associative learning (Alem et al., 2016). It remains unknown whether the bumblebees understand the connectivity of the string. We aim to explore the question of means-end comprehension in bumblebees when tackling string-pulling tasks. We conducted nine horizontal string-pulling experiments. These experiments were designed to manipulate factors such as string color and spatial arrangement during both the training and testing phases. Firstly, bumblebees without string-pulling experience were tested to discriminate between strings connected to a target containing the reward and disconnected strings. In another set of experiments, we examined whether bumblebees with string-pulling experience would discriminate between connected and disconnected strings. Furthermore, we changed the color of strings in training to determine whether bees generalize features learned to solve tasks with different colored strings. In two other experiments, black tape was used to cover the strings, preventing the bees from seeing the string connected to the flower from above the table during the training phase. In one of these experiments, a green table was placed behind where the bee pulled to prevent the bee from seeing the string connected to the flower even after having reached the reward during the training phase. Finally, to further verify whether bumblebees choose strings through image learning, the straight strings were changed to coiled so that the image of the string was distinct from that in training.

In Experiment 1, we evaluated whether uninformed bumblebees with no string-pulling experience could discriminate between connected and disconnected strings. Bees were trained to retrieve a yellow flower (without a string) containing sugar water from under a transparent table (Figure 1; Video 1). In the test, bees had two different flowers to choose from, one with a connected string and the other with a disconnected string (Figure 2). The strings and flowers used were discarded after each test to prevent the use of chemosensory cues. We found that 10 of 21 bees (48%, χ²=0.05, p=0.83) chose the connected string as their first choice in the test (Table 1). Over the entire duration of the test, bees showed no preference for either string during the test [n=21, generalized linear mixed model (GLMM): 95% CI=−0.09 (-0.48–0.29), Z = –0.48, p=0.63; Figure 3], suggesting that there is no spontaneous comprehension of the significance of the gap, and that any preference for connected strings would have to be acquired through training.

Figure 1

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Figure 2

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Table 1

Training
Task
Experiment	1	2	3	4	5	6	7	8	9
Number of choices (mean ±SE)	5.10±0.54	15.00±1.53	15.56±2.16	12.10±2.19	11.63±1.66	15.87±2.05	5.60±1.55	20.60±1.80	14.37±2.82
Number of bees choosing connected strings at first choice/N	10/21 (N.S.)	13/18 (N.S.)	17/18 (***)	7/10 (N.S.)	14/16 (*)	10/15 (N.S.)	5/10 (N.S.)	11/20 (N.S.)	10/19 (N.S.)
Chi-square result	χ2=0.05 P=0.83	χ2=3.56 P=0.06	χ2=14.22 P<0.001	χ2=1.60 P=0.21	χ2=9.00 P<0.05	χ2=1.67 P=0.20	χ2=0.00 P=1.00	χ2=0.20 P=0.65	χ2=0.05 P=0.82

1. The numbers before the slash are the numbers of bumblebees pulling connected strings on the first choice, and the numbers after the slash are the total number of tested bumblebees. N is the total number of the bees. *** p＜0.001; * p＜0.05; N.S. p＞0.05.

Figure 3

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Video 1

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We next examined whether bumblebees with string-pulling experience would discriminate between connected and disconnected strings. In Experiment 2, bees were first trained to retrieve yellow flowers from under a transparent table by pulling an attached white string (Video 2). After training, bees were presented with two different flowers: one was connected to a string and the other had a disconnected string. We found that 13 of 18 bumblebees (72%, χ²=3.56, p=0.06) chose the connected string as their first choice in the test (Table 1). Over the entire duration of the test, bees selected the connected strings (76 ± 4%) significantly more than the disconnected strings [n=18, GLMM: 95% CI=1.06 (0.78–1.33), Z=7.56, p<0.001; Figure 3, Video 3]. In addition, bees spent much more time attempting to pull the connected strings (94.67±13.19 s) than the disconnected strings (13.61±4.59 s) [n=18, GLMM: 95% CI=0.07 (0.02–0.11), t=2.90, p<0.01; Figure 4].

Figure 4

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Video 2

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Video 3

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In Experiment 3, we trained another group of bees with the same procedure as in Experiment 2, but the disconnected string pointed to the flower in the test (there was no lateral displacement between the disconnected string and flower in the test; Figure 2). Again, we found that most bees (17/18, 94%, χ²=14.22, p<0.001) chose the connected string as their first choice (Table 1). Over the course of the entire test, the percentage of bees pulling connected strings (79 ± 4%) was significantly above chance level [n=18, GLMM: 95% CI=1.56 (0.72–2.40), Z=5.90, p<0.001; Figure 3; Video 4], and bees spent longer times manipulating connected strings (79.59±10.15 s) [GLMM: 95% CI=0.09 (0.03–0.14), t=3.23, p<0.01; Figure 4].

Video 4

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To explore whether bees simply memorized the visual display of the ‘lollipop shape’ of a string connected to a flower during training with a given color combination, we then asked whether bees generalize from the string color used during training. Bumblebees were trained with green strings (Video 5) or blue strings (Video 6) connected to flowers. If the bees had the ability to generalize the function of strings, this color change should not affect their ability to discriminate connected and disconnected strings. Overall, changing the color of the string in training reduced the accuracy of the choice, 7/10 bees (70%, χ²=1.60, p=0.21) selected the connected string in the first choice (Table 1). But over the entire test, the bees still maintained the basic discrimination at well above chance level when trained with green strings (61 ± 5%) [n=10, generalized linear model (GLM): 95% CI=1.13 (0.71–1.54), Z=5.27, p<0.001; Figure 3]. In addition, the duration of pulling connected strings (47.79±9.91 s) was significantly longer than disconnected ones (24.78±6.05 s) [n=10, GLMM: 95% CI=0.10 (0.01–0.19), t=2.26, p<0.05; Figure 4]. In this sense, bees might possess the ability to generalize string color from the originally learned stimulus. A similar result was found in bees trained with blue strings. We found that 14 of 16 bees (87%, χ²=9.00, p<0.05) selected the connected string in the first choice (Table 1). The percentage of bees pulling connected strings was significantly higher than chance level [n=16, GLMM: 95% CI=0.60 (0.30–0.90), Z=3.90, p<0.001; Figure 3], and the duration data also indicate that the bees prefer pulling connected strings [n=16, linear mixed model (LMM): 95% CI=−66.91 (-80.86 to -52.96), t = –9.68, p<0.001; Figure 4].

Video 5

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Video 6

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The question of whether animals rely on perceptual feedback during string pulling has been tested with occluders between the string and the reward in a variety of other species (Taylor et al., 2010; Gaycken et al., 2019; Chaves Molina et al., 2019; Wakonig et al., 2021). Bumblebees were trained to feed on yellow artificial flowers, and then trained with transparent tables covered by black tape through a four-step process (Video 7). The aim was to prevent the bees from seeing the string connected to the flower during training. Note, however, the bees were able to see this ‘lollipop shape’ (string connected to the flower) after they pulled the strings out from the table or during the initial step of the training (Figure 1). Ten out of fifteen bees (67%, χ²=1.67, p=0.20) pulled the connected string in their first choice (Table 1). However, over the full duration of the test, the percentage of the bees pulling connected strings (82 ± 3%) was significantly higher than chance level [n=15, GLMM: 95% CI=1.31 (1.00–1.62), Z=8.23, p<0.001; Figure 3], and the duration data also indicate that the bees preferred pulling connected strings [n=15, GLMM: 95% CI=0.10 (0.02–0.17), t=2.61, p<0.01; Figure 4]. To help ensure that the bees could not see the ‘lollipop shape’ during the training phase, we placed a green table behind the bee (Figure 2). In this way, the ‘lollipop shape’ was not directly presented during the initial step of training, nor was it visible after the bee had reached the reward because the string was then covered by the back green table (Video 8). We found that the initial choices of bees in this test were at chance level (5 out of 10 bees chose the connected string). Over the full test, the percentage of pulling connected strings was significantly lower than chance level [n=10, GLMM: 95% CI=−0.77 (-1.33 to -0.20), Z = –2.61, p<0.01; Figure 3]. But duration data indicated that the bees showed no preference for pulling the connected strings or disconnected strings [n=10, GLMM: 95% CI=−0.09 (-0.38–0.19), t = –0.64, p=0.53; Figure 4].

Video 7

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Video 8

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So far, our results show that bumblebees could have been using image matching to discriminate connected from disconnected strings in the test. We therefore designed further experiments based on Taylor et al., 2012 to test this hypothesis. Bumblebees were first trained to feed on yellow artificial flowers, and then trained with the same procedure as Experiment 2, but the connected strings were coiled in the test. Bees failed to choose the connected strings when strings were coiled. We observed that 11/20 bees (55%, χ²=0.20, p=0.65) pulled the connected string in their first choice (Table 1). Over the full duration of the test, no difference in the percentage of pulling connected strings compared with chance level [n=20, GLMM: 95% CI=0.17 (-0.26–0.59), Z=0.70, p=0.48; Figure 3]. There was also no significant difference between the duration of bees pulling the connected strings and disconnected strings [n=20, LMM: 95% CI=−5.77 (-24.04–12.50), t = –0.63, p=0.53; Figure 4], suggesting that bumblebees did not recognize the continuity of coiled strings. Another group of bees was trained with straight strings, while both connected and disconnected strings were coiled in the test. Ten of 19 bees (53%, χ²=0.05, p=0.82) chose the connected string as their first choice in the test (Table 1). Similarly, no differences were found in percentage [n=19, GLMM: 95% CI=−0.03 (-0.54–0.48), Z = –0.29, p=0.77; Figure 3] and duration [n=19, GLMM: 95% CI=0.005 (-0.02–0.03), t=0.22, p=0.83; Figure 4] of pulling each string.

Latency to the first choice was defined as the latency to initiate pulling the string after the bee entered the set-up. The latency to the first choice was measured to assess if the bumblebees were familiarizing themselves with the testing pattern. A shorter latency might indicate that the bumblebees were more familiar with the patterns. The latency of the bees that were trained with blue strings (684.33±105.45 s) was substantially longer than that of bees which were trained with white strings and tested with straight strings (Figure 5). A long latency time was observed in Experiment 7 (557.26±104.09 s), in which the bees were trained with black tape covering the table, and a green table placed behind the bees (Figure 5).

Figure 5

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Our results show that: (i) bumblebees require experience with string pulling to distinguish between connected and disconnected strings; (ii) bumblebees are able to generalize features learned during string-pulling training to solve a task with different colored strings; (iii) bumblebees solve string-pulling tasks through image matching.

The results suggest that bumblebees require experience to recognize interrupted strings and acquire a preference for connected ones. This corroborates previous findings that most bees failed to solve single string-pulling tasks without previous training (Alem et al., 2016). Some animals, including dogs (Osthaus et al., 2005), cats (Whitt et al., 2009), western scrub-jays (Hofmann et al., 2016) and azure-winged magpies (Wang et al., 2019) fail in such spontaneous tasks. It is worth noting that some crows and parrots known for complex cognition perform poorly on the broken string task without perceptual feedback or learning. For example, New Caledonian crows use perceptual feedback strategies to solve the broken string-pulling task, and no individual showed a significant preference for the connected string when perceptual feedback was restricted (Taylor et al., 2012). Some Australian magpies and African grey parrots can solve the broken string task, but they require a high number of trials, indicating that learning plays a crucial role in solving this task (Chaves Molina et al., 2019; Johnsson et al., 2023).

Our findings suggest that bumblebees with experience of string pulling prefer the connected strings, but they failed to identify the interrupted strings when the string was coiled in the test. Bees acquire their preferences for flowers with connected strings at least in part by learning the visual appearance of the ‘lollipop shape’ present during training. Trained bees may have memorized this image as a predictor of reward and applied it to solve novel string-pulling tasks. This makes sense because the bees could see the ‘lollipop shape’ once they pulled it out from the table in Experiment 6. Another possibility is that bumblebees might remember the image of the ‘lollipop shape’ from the initial training step, because the shape was directly presented to the bees. However, when a green table was placed behind the string to obscure the ‘lollipop’ structure during the training, the bees could not see the ‘lollipop’ during the initial training stage or after pulling the string from under the table. In this situation, the bees were unable to identify the connected string, further supporting the notion that bumblebees chose the connected string based on image matching. Bumblebees exhibited longer delay times to the first choice in Experiments 5 and 7 (Figure 5). The reason might be attributable to bees’ search time for the familiar image or neophobic response (Muller et al., 2010), because the strings during training were changed in the test, which the bees had not encountered before.

Bees often need to match memorized images of flowers to currently visible flowers while foraging in the wild (Chittka et al., 1999; Giurfa, 2003). Different flower species offer varying profitability in terms of nectar and pollen to bumblebees; they need to make careful choices and learn to use floral cues to predict rewards (Chittka, 2017). Bumblebees can easily learn visual patterns and shapes of flowers (Meyer-Rochow, 2019) they can detect stimuli and discriminate between differently coloured stimuli when presented as briefly as 25ms (Nityananda et al., 2014). In contrast, causal reasoning involves understanding and responding to causal relationships. Bumblebees might favor, or be limited to, a visual approach, likely due to the efficiency and simplicity of processing visual cues to solve the string-pulling task.

Rather than relying on means-end comprehension, most animals likely use simpler associative strategies to solve string-pulling tasks, as observed in the bumblebees in the present study (Jacobs and Osvath, 2015; Wakonig et al., 2021). Empirical evidence from several vertebrates has shown that success in object use does not necessarily imply causal understanding; rather, it involves abstracting simple rules based on observable features of the physical task at hand (Seed et al., 2006; Schuck-Paim et al., 2009; Herrmann et al., 2008; Gagne et al., 2012). In several vertebrate string-pulling studies, animals relied on a ‘proximity rule’ in most cases, choosing to pull the strings closest to the reward, regardless of their connectivity (Whitt et al., 2009; Wang et al., 2021).

In conclusion, even though bumblebees may not understand the causality of string-pulling, they can match the image of the strings connected to flowers, and rely on associative mechanisms to remember the previously visited stimuli. Bumblebees, whether with or without string-pulling experience, do not appear to understand the value of strings to target objects. This negative result does not necessarily mean that bumblebees are entirely unable to comprehend the link between a means and an end, but our results suggest that for the paradigms tested here, such comprehension is not required.

All data generated or analysed during this study are included in the manuscript and supporting files.

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Author details

1. Chao Wen

   1. School of Grassland Science, Beijing Forestry University, Beijing, China
   2. Biological and Experimental Psychology, School of Biological and Behavioural Sciences, Queen Mary University of London, London, United Kingdom

   Contribution

   Conceptualization, Resources, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Validation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

   Contributed equally with

   Yuyi Lu

   For correspondence

   wenchao@bjfu.edu.cn

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5650-3454

2. Yuyi Lu

   1. Biological and Experimental Psychology, School of Biological and Behavioural Sciences, Queen Mary University of London, London, United Kingdom
   2. Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China

   Contribution

   Conceptualization, Resources, Data curation, Software, Formal analysis, Validation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   Contributed equally with

   Chao Wen

   Competing interests

   No competing interests declared

3. Cwyn Solvi

   Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2517-6179

4. Shunping Dong

   Beijing Key Laboratory for Forest Pest Control, Beijing Forestry University, Beijing, China

   Contribution

   Data curation, Software, Formal analysis, Visualization, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

5. Cai Wang

   College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, China

   Contribution

   Conceptualization, Resources, Supervision, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

6. Xiujun Wen

   College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, China

   Contribution

   Conceptualization, Resources, Supervision, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

7. Haijun Xiao

   School of Grassland Science, Beijing Forestry University, Beijing, China

   Contribution

   Conceptualization, Resources, Supervision, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0832-0493

8. Shikui Dong

   School of Grassland Science, Beijing Forestry University, Beijing, China

   Contribution

   Conceptualization, Resources, Supervision, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

9. Junbao Wen

   Beijing Key Laboratory for Forest Pest Control, Beijing Forestry University, Beijing, China

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

10. Fei Peng

    1. Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
    2. Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China

    Contribution

    Conceptualization, Resources, Formal analysis, Supervision, Methodology, Writing – original draft, Writing – review and editing

    For correspondence

    fpeng@smu.edu.cn

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-1637-5611

11. Lars Chittka

    Biological and Experimental Psychology, School of Biological and Behavioural Sciences, Queen Mary University of London, London, United Kingdom

    Contribution

    Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Methodology, Writing – original draft, Project administration, Writing – review and editing

    For correspondence

    l.chittka@qmul.ac.uk

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-8153-1732

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