Tool use is a widespread phenomenon within the animal kingdom (Shumaker et al., 2011; Sanz et al., 2013) and new examples of animal tool use are regularly discovered, such as recently in pigs (Root-Bernstein et al., 2019) and seabirds (Fayet et al., 2020). Tool use is defined as "the external employment of an unattached or manipulable attached environmental object to alter more efficiently the form, position, or condition of another object, another organism, or the user itself, when the user holds and directly manipulates the tool during or prior to use and is responsible for the proper and effective orientation of the tool" (Shumaker et al., 2011, p. 5). Most of the reports concern vertebrates, particularly primates and birds, which can manufacture tools to solve specific tasks (Hunt and Gray, 2002; Sanz et al., 2013; Auersperg et al., 2014), use multiple tools sequentially (Martin-Ordas et al., 2012), and choose effective tools based on their functional properties (Visalberghi et al., 2009). We know that capuchin monkeys have been using stone tools to process food for at least 3000 years (Falótico et al., 2019) but presumably the use of tools appeared even earlier in invertebrates. Smith and Bentley-Condit, 2010 reported about 50 cases of tool use in insects, encompassing 30 different genera. Among the best described examples is the use of debris to transport liquid food by some species of ants (Morrill, 1972; Barber et al., 1989), in particular, several species of the genus Aphaenogaster (Fellers and Fellers, 1976; Tanaka and Ono, 1978; McDonald, 1984; Agbogba, 1985). Workers of these species are characterised by the lack of a distensible crop and by a chitinous gaster, preventing the transportation of large amounts of liquid food inside their bodies, a feature common in many other ant species (Hölldobler and Wilson, 1990; Davidson et al., 2004). Moreover, unlike most ant species, Aphaenogaster workers do not perform mouth-to-mouth exchange of liquid food (i.e. trophallaxis, Delage and Jaisson, 1969); therefore, foragers cannot use this form of food transmission among colony members. Workers forage individually mostly on the ground level and can cover large areas in habitats with scarce food sources (Cerdá et al., 1998). When Aphaenogaster foragers discover a source of liquid food, such as fruit pulp or body fluids of dead insects, they collect debris (pieces of leaves, soil, sand grains), drop them into the liquid food, and then transport these soaked debris to their nest. This behaviour qualifies as tool use, namely tool-assisted food transport. Indeed, these ants do not drop debris in non-food substances (Banschbach et al., 2006).

In a previous study (Maák et al., 2017), we have investigated whether Aphaenogaster ants are selective in the choice of material to be used as tools and we demonstrated that ant workers prefer materials that are easy to handle and with good soaking capacity. Furthermore, ants can learn to use artificial material that is novel to them and select the material with optimal soaking properties, thus showing that tool use is not behaviourally fixed in ants (Maák et al., 2017). Tool selection also depends on the foraging environment and varies with food type (viscosity), distance, and availability of tools (Lőrinczi et al., 2018).

The process of tool use in ants has not been studied at the individual level. In particular, we do not know whether any forager with sufficient information about the location of the food and the availability of the tools would perform tool use or whether there are specialised workers which perform tool use repeatedly. In A. rudis, it was observed that the tool use behaviour is carried out by a small subset of individuals within the group of foragers and only a small number of workers perform the debris dropping task (Banschbach et al., 2006). In A. subterranea as well, the proportion of workers observed to use tools was only a small fraction of the total number of foragers. The number of tool users did not increase with colony size, while the number of total foragers did. Moreover, there was no significant relationship between the number of ants working at the debris dropping task and the number of debris pieces dropped, indicating that a small number of workers can perform this task very efficiently (Lőrinczi, 2014).

We asked the question of what makes a good tool user in A. senilis ants. It is indeed unknown whether some individual characteristics of workers, such as personality traits, would predict tool use behaviour. When inter-individual differences in behavioural traits are consistent across time and/or context they are considered personality traits (Réale and Dingemanse, 2012). In ants, both workers and colonies can show personalities (Pinter-Wollman, 2012) and there is a link between individual and collective behaviour (Carere et al., 2018). There is some evidence that the allocation of workers to a certain task may be influenced by individual personality, for instance in the ant Leptothorax acervorum (Kühbandner et al., 2014), where more exploratory and aggressive workers were also more active in the nest (rested less). This inter-individual difference could enhance division of labour (Jeanson and Weidenmüller, 2014), the phenomenon in which different individuals perform different tasks. Division of labour is beneficial for colony organisation and it is believed to be one of the principal factors explaining the extraordinary ecological success of social insects (Hölldobler and Wilson, 1990). A broadly acknowledged model explaining the emergence of division of labour within a colony is the ‘response threshold model’, which posits that individual workers differ in their sensory perception and/or in their behavioural responses to stimuli associated with specific tasks (Robinson, 1992; Beshers and Fewell, 2001). However, the possible interplay between consistent individual differences and division of labour has not been explored (Jeanson and Weidenmüller, 2014).

We also know that there is an association between personality traits and cognitive traits in ants. Consistent individual differences in exploratory activity predicted learning performance of individual carpenter ants, with ‘active-explorers’ being slower in learning than ‘inactive-explorers’ (Udino et al., 2017) and individual differences in exploratory activity were linked to cognitive judgement bias, the propensity to anticipate either positive or negative consequences in response to ambiguous information (d'Ettorre et al., 2017). Therefore, we expected a link between individual personality traits and tool use.

We performed three different experiments to study the tool use behaviour at the individual level in the ant A. senilis. In Experiment 1, we observed the tool use process in whole colonies to characterise the behaviour of ants during the two parts of the process: the transport of tools to the bait and the transport of tools from the bait to the nest. In social insects, task partitioning -a phenomenon in which a piece of work is divided among two or more workers- has been reported in a wide variety of foraging tasks in several species of ants, bees, wasps and termites (Ratnieks and Anderson, 1999). However, partitioning may reduce task efficiency and reliability unless the number of workers involved in the task is high or a given subtask is carried out by morphologically specialised workers (Ratnieks and Anderson, 1999). In Aphaenogaster, workers are morphologically similar, therefore we predicted that we would not observe task partitioning and that the same worker could perform both parts of the task.

In Experiment 2, we created sub-colonies to investigate whether there is an individual specialisation in tool use. Are the same ants using tools repeatedly? Are ants that use tools to collect liquid food also transporting solid food items? We predicted that ants would specialise in tool use only, under the general assumption that specialised individuals work more efficiently than less specialised ones (Robinson, 1992). In this experiment, we also asked whether the simple fact of observing nestmates using tools during one trial would facilitate the task performance of naive workers by social learning. The involvement of social learning in solving complex tasks has been shown in social insects, for instance, bumblebees (Loukola et al., 2017).

In Experiment 3, we studied the possible link between individual personality traits and tool use. Previous studies demonstrated the existence of colony-level personality in A. senilis (Blight et al., 2016a; Blight et al., 2016b), we thus predicted that consistent behavioural differences will be found also at the individual level in this species (worker personality). Using workers that were individually characterised for personality traits, namely exploratory activity and reaction to prey, we created sub-colonies that were tested in tool use trials. After each trial, the ants that used tools were removed from the sub-colony. Thus, we could test whether personality would predict which ants will become tool users in the next trial.

Workers of some ant species use debris as tools to collect and transport liquid food to the nest. We studied tool use behaviour at the individual level in Aphaenogaster senilis to determine whether any forager that knows the location of the food and the tools puts the two together, or if it is an attribute of a subset of workers. Three experiments explored this question. Experiments 1 and 3 showed that several workers contacted the food and the tools before the first tool user started transporting tools to the bait. Therefore, tool users were not simply the first workers that learned about the location of the food and the tools. Experiment 2 showed that only a small subset of foragers (about 8%) used tools and that the observed individual distribution of tool use events was not random. Moreover, tool use was a significantly repeatable behaviour across trials at the individual level. Finally, in experiment 3, we found that workers show consistent inter-individual behavioural variation in exploratory activity and reaction to prey. These highly repeatable behavioural traits were used to calculate a personality score that significantly predicted the probability of using tools. Based solely on these behavioural traits we could distinguish two groups of workers: the tool users and the non-tool users. In sum, our data indicate that tool use is not a stochastic phenomenon but it is performed by a subset of workers with specific behavioural traits.

In both experiments 1 and 2, we observed tool users performing repeated tool transport within the same trial and also between trials. In experiment 2, more than 60% of the tool users performed repeated tool transport to the bait and their efficiency increased during the process: for a given ant, the time to transport one tool decreased with the number of tools transported and was not affected by the presence of another worker transporting tools. This improved efficiency is likely explained by the fact that ants learned the location of the tools with respect to the bait and could return quickly to pick up the next tool. In several ant species, foraging speed is enhanced by route learning (Czaczkes et al., 2011; Pasquier and Grüter, 2016), which appears to be a general phenomenon. More than 30% of the tool users participated in more than one trial, nevertheless, the performance of these workers did not improve along with the trials as the average time to transport a tool did not change significantly across trials. In other social insect species, however, an improvement over consecutive trials has been observed. For instance, bees become more efficient in foraging with experience (Dukas and Visscher, 1994; Klein et al., 2019) and, in the context of nest emigration, Temnothorax albipennis ant workers improve their performance over successive emigrations (Langridge et al., 2008). This suggests that in A. senilis the limiting factor to speed up the process is memorising the location of the tools, which is different in every trial.

In experiment 1, we observed that the same ant could perform both parts of the tool use task, that is transport of tools to the bait and from the bait to the nest. Therefore, as we predicted, there was no clear evidence of task partitioning. Nevertheless, our results regarding the lack of task partitioning are not conclusive due to the relatively small total number of ants that were observed participating in both parts of tool use process. To the best of our knowledge, the observations reported in the literature also lack conclusive evidence. In A. rudis, similarly to A. senilis, no evidence of task partitioning was found (Banschbach et al., 2006), although task partitioning was suggested in earlier observations of A. famelica (Tanaka and Ono, 1978). This suggests that this behavioural aspect might be species-specific but ideally requires further research.

The results of experiment one also showed that the dynamics of tool transport to the bait does not influence the transport of food-imbibed tools to the nest, which starts on average 2 hrs after completion of the first part. In natural conditions, covering the food quickly with debris gives an advantage to Aphaenogaster ants in the competition with more dominant ant species, which cannot exploit the food once it is covered (Fellers and Fellers, 1976), thus leaving plenty of time for Aphaenogaster to bring the food-imbibed tools to the nest. Therefore, it appears to be advantageous to first completely cover the food with debris and then to start transporting them to the nest. During the first part of the process, the results of experiment one showed that the higher the number of workers present in the foraging area the shorter was the latency to start the tool use process. A shorter latency resulted in a shorter total time to complete the task, but interestingly, this did not depend on the number of workers involved in tool use. Enhanced efficiency related to shorter latency was also found in the ant Temnothorax albipennis, where shorter recruitment latencies to high quality nest sites, compared to low-quality ones, improved the nest emigration process (Mallon et al., 2001; but see Robinson et al., 2009). Similarly, in the ant Formica fusca, shorter latencies to return to the nest after exploration of a novel arena characterised larger colonies and indicated efficient exploration of the surroundings (Somogyi et al., 2020).

Tool use events were not randomly distributed among workers, however, the results of experiment two also indicate that tool users were not necessarily specialised only in this task. About half of the workers that transported solid food (cricket legs) were also tool users. This may not hinder efficiency since it has been shown that task specialisation does not translate into higher performance in ant species without morphologically differentiated workers (Dornhaus, 2008). Some workers exhibited very high activity by participating in several tool use trials and transporting more than one cricket leg. These resemble ‘elite’ workers that show high performance in several tasks, as observed in some ant species (Robson and Traniello, 1999; Pinter-Wollman et al., 2012). It would be interesting to test whether these very active workers act as key individuals that increase the activity level of group members (Robson and Traniello, 1999).

In experiment 2, we also tested whether the simple fact of observing nestmates transporting tools during one trial would facilitate the task performance of naïve workers via social learning. We did not find a difference in the performance of workers that were given the possibility to observe nestmates performing tool use and workers that did not have this possibility, suggesting that social learning might not be involved in the ontogeny of the tool use behaviour in A. senilis. Our finding is in agreement with the observation by Tanaka and Ono, 1978 that naïve foragers can carry out tool use in A. famelica. Spontaneous tool use and manufacture has been also shown in vertebrates, such as naive juvenile New Caledonian crows (Kenward et al., 2005), while social learning appears to be essential when the task is complex and non-natural, as observed in bumblebees (Alem et al., 2016; Loukola et al., 2017). Nevertheless, we should acknowledge that in the present study we used only one type of tool. We know that Aphaenogaster ants are able to select among different types of tools according to their soaking capacity and the environmental context (Maák et al., 2017; Lőrinczi et al., 2018) and that they learn to choose the optimal tools over successive trials (Maák et al., 2017), therefore we cannot exclude that social learning could play a role in the process of tool selection, a possibility that awaits formal testing.

Experiment 3 clearly showed that workers of A. senilis are characterised by consistent behavioural variation at the individual level concerning exploratory activity and reaction to prey. Consistent inter-individual behavioural variation has also been shown in other ant species (e.g. Kühbandner et al., 2014; Udino et al., 2017) and it might be a general characteristic of workers. What is new in our work is the discovery that individual behavioural variability is directly linked to the probability to perform a certain task, in this case tool use. Workers with a positive personality score, characterised by high explorative behaviour and prey-attraction, were more likely to be involved in tool use than workers with a less positive or negative personality score. Despite finding relatively small effect sizes in the analysis of the personality data, our results reveal the importance of even slight individual differences in behavioural traits, if they are consistent, in the organisation of social life. Inter-individual variability is the basis for division of labour, the phenomenon in which different individuals perform different tasks. According to the ‘response threshold model’ (Robinson, 1992; Beshers and Fewell, 2001), workers characterised by a low threshold will respond to low stimulus intensity (high responsiveness), while workers with high threshold will respond to high stimulus intensity (low responsiveness) (Bonabeau et al., 1996). Several proximate mechanisms underlying inter-individual behavioural variability have been described, including genetic diversity, ontogeny, nutrition, experience and learning (reviewed in Jeanson and Weidenmüller, 2014). Experience may act as ‘self-reinforcement’ and directly modulate the individual response threshold. It was hypothesised that the simple fact of performing a task would lower the corresponding stimulus threshold, while not performing a task would further increase the individual threshold (Theraulaz et al., 1998). Indeed, a study using clonal ants showed that, all else being equal, foragers that were successful had a higher probability to perform the foraging task again, compared to unsuccessful foragers, which specialised in brood care (Ravary et al., 2007).

Individual personality differences within a given behavioural group (foragers, nurses) may contribute to a fine-tuned division of labour but this possibility is relatively unexplored. A study in honeybees found evidence for life-long personality differences in workers and suggested that the response thresholds to some stimuli could be related to personality type, thus contributing to more robust inter-individual behavioural differences leading to division of labour even when individuals age together or share similar experiences (Walton and Toth, 2016). In carpenter ants, there is evidence for inter-individual variability in sucrose responsiveness and learning success in different behavioural groups of workers performing different tasks (Perez et al., 2013). In the ant Myrmica rubra, individual personality differences are connected to spatial fidelity (the position in the nest) and ants located in a given position show low thresholds to perform tasks associated with that position, thus generating division of labour (Pamminger et al., 2014). However, examples of interplay between personality and task performance in social insects are generally scarce.

Individual behavioural flexibility is another important aspect guaranteeing division of labour in social insects, particularly following changes in the social environment, such as changes in colony demography (Jeanson, 2019). We found that A. senilis colonies could cope well with the removal of active tool users, which were immediately replaced by individuals that were previously less active. Similarly, in the red harvester ant, Pogonomyrmex barbatus, when the most active foragers were experimentally removed they were replaced by other individuals (Beverly et al., 2009). In the ant Temnothorax rugatulus as well, when the most active nurses and foragers were removed they were quickly replaced by workers from the reserve pool of inactive individuals (Charbonneau et al., 2017). In T. albipennis, in the context of nest emigration, 20% of ants were more active and performed transports repeatedly in successive experimental emigration trials (Pinter-Wollman et al., 2012). Pinter-Wollman et al., 2012 performed an experiment in which they removed these active ants during some emigration trials and then they put them back. Removed active ants were replaced by previously less active individuals, but when they were returned to the colony they did not resume their active role, they were thus permanently replaced. The authors suggest that modifications in the social context and experience can cause a long-lasting change in the response threshold of workers (Pinter-Wollman et al., 2012; Jeanson, 2019). This is not what we observed in A. senilis, in which many of the removed active workers resumed tool use when they were returned to their sub-colony in the last trial with 20 tools, including workers that were removed 10 days earlier (after the very first trial). This is not surprising if we consider that the probability to perform tool use in A. senilis is linked to personality, which, by definition, is consistent over time.

In conclusion, our work shows that instead of extreme task specialisation, the involvement of workers with appropriate personality ensures high efficiency in tool use. Given the scarcity of examples linking individual personality and task performance in social insects, our study provides new insight into the interplay between personality and division of labour and should encourage further theoretical and empirical studies in this direction.

All data generated during this study are included in the manuscript and supporting files. Source data files have been provided for all Figures.

1. 1. Agbogba C

   (1985)

   Observations on foraging of liquid sugar and insect body fluids by two species of Aphaenogaster: A. senilis and A. subterranea (Hym Formicidae)

   Insect Soc 32:427–434.

   • Google Scholar
2. 1. Alem S
   2. Perry CJ
   3. Zhu X
   4. Loukola OJ
   5. Ingraham T
   6. Søvik E
   7. Chittka L

   (2016) Associative mechanisms allow for social learning and cultural transmission of string pulling in an insect

   PLOS Biology 14:e1002564.

   https://doi.org/10.1371/journal.pbio.1002564

   • PubMed
   • Google Scholar
3. 1. Auersperg AMI
   2. von Bayern AMI
   3. Weber S
   4. Szabadvari A
   5. Bugnyar T
   6. Kacelnik A

   (2014) Social transmission of tool use and tool manufacture in Goffin cockatoos ( Cacatua goffini )

   Proceedings of the Royal Society B: Biological Sciences 281:20140972.

   https://doi.org/10.1098/rspb.2014.0972

   • Google Scholar
4. 1. Banschbach VS
   2. Brunelle A
   3. Bartlett KM
   4. Grivetti JY
   5. Yeamans RL

   (2006) Tool use by the forest ant Aphaenogaster rudis: ecology and task allocation

   Insectes Sociaux 53:463–471.

   https://doi.org/10.1007/s00040-006-0897-2

   • Google Scholar
5. 1. Barber JT
   2. Ellgaard EG
   3. Thien LB
   4. Stack AE

   (1989) The use of tools for food transportation by the imported fire ant, Solenopsis invicta

   Animal Behaviour 38:550–552.

   https://doi.org/10.1016/S0003-3472(89)80052-1

   • Google Scholar
6. Software

   1. Bates D
   2. Maechler M

   (2013) Lme4: Linear Mixed-Effects Models Using Eigen and S4, version 1.0-5

   R package.

   http://CRAN.R-project.org/package=lme4
7. 1. Beshers SN
   2. Fewell JH

   (2001) Models of division of labor in social insects

   Annual Review of Entomology 46:413–440.

   https://doi.org/10.1146/annurev.ento.46.1.413

   • PubMed
   • Google Scholar
8. 1. Beverly BD
   2. McLendon H
   3. Nacu S
   4. Holmes S
   5. Gordon DM

   (2009) How site fidelity leads to individual differences in the foraging activity of harvester ants

   Behavioral Ecology 20:633–638.

   https://doi.org/10.1093/beheco/arp041

   • Google Scholar
9. 1. Blight O
   2. Albet Díaz-Mariblanca G
   3. Cerdá X
   4. Boulay R

   (2016a) A proactive–reactive syndrome affects group success in an ant species

   Behavioral Ecology 27:118–125.

   https://doi.org/10.1093/beheco/arv127

   • Google Scholar
10. 1. Blight O
    2. Villalta I
    3. Cerdá X
    4. Boulay R

    (2016b) Personality traits are associated with colony productivity in the gypsy ant Aphaenogaster senilis

    Behavioral Ecology and Sociobiology 70:2203–2209.

    https://doi.org/10.1007/s00265-016-2224-x

    • Google Scholar
11. 1. Bonabeau E
    2. Theraulaz G
    3. Deneubourg JL

    (1996) Quantitative study of the fixed threshold model for the regulation of division of labour in insect societies

    Proc R Soc Lond B 263:1565–1569.

    https://doi.org/10.1098/rspb.1996.0229

    • Google Scholar
12. 1. Boulay R
    2. Hefetz A
    3. Cerdá X
    4. Devers S
    5. Francke W
    6. Twele R
    7. Lenoir A

    (2007) Production of sexuals in a fission-performing ant: dual effects of queen pheromones and colony size

    Behavioral Ecology and Sociobiology 61:1531–1541.

    https://doi.org/10.1007/s00265-007-0385-3

    • Google Scholar
13. 1. Carere C
    2. Audebrand C
    3. Rödel HG
    4. d'Ettorre P

    (2018) Individual behavioural type and group performance in Formica fusca ants

    Behavioural Processes 157:402–407.

    https://doi.org/10.1016/j.beproc.2018.07.009

    • PubMed
    • Google Scholar
14. 1. Cerdá X
    2. Retana J
    3. Cros S

    (1998) Critical thermal limits in Mediterranean ant species: trade-off between mortality risk and foraging performance

    Functional Ecology 12:45–55.

    https://doi.org/10.1046/j.1365-2435.1998.00160.x

    • Google Scholar
15. 1. Charbonneau D
    2. Sasaki T
    3. Dornhaus A

    (2017) Who needs 'lazy' workers? Inactive workers act as a 'reserve' labor force replacing active workers, but inactive workers are not replaced when they are removed

    PLOS ONE 12:e0184074.

    https://doi.org/10.1371/journal.pone.0184074

    • PubMed
    • Google Scholar
16. 1. Czaczkes TJ
    2. Grüter C
    3. Jones SM
    4. Ratnieks FL

    (2011) Synergy between social and private information increases foraging efficiency in ants

    Biology Letters 7:521–524.

    https://doi.org/10.1098/rsbl.2011.0067

    • PubMed
    • Google Scholar
17. 1. d'Ettorre P
    2. Carere C
    3. Demora L
    4. Le Quinquis P
    5. Signorotti L
    6. Bovet D

    (2017) Individual differences in exploratory activity relate to cognitive judgement Bias in carpenter ants

    Behavioural Processes 134:63–69.

    https://doi.org/10.1016/j.beproc.2016.09.008

    • PubMed
    • Google Scholar
18. 1. Davidson DW
    2. Cook SC
    3. Snelling RR

    (2004) Liquid-feeding performances of ants (Formicidae): ecological and evolutionary implications

    Oecologia 139:255–266.

    https://doi.org/10.1007/s00442-004-1508-4

    • PubMed
    • Google Scholar
19. 1. Delage B
    2. Jaisson P

    (1969)

    Social relations among ants of the genus Aphaenogaster

    Sciences Naturelles 268:701–703.

    • Google Scholar
20. 1. Dornhaus A

    (2008) Specialization does not predict individual efficiency in an ant

    PLOS Biology 6:e285.

    https://doi.org/10.1371/journal.pbio.0060285

    • PubMed
    • Google Scholar
21. 1. Dukas R
    2. Visscher PK

    (1994) Lifetime learning by foraging honey bees

    Animal Behaviour 48:1007–1012.

    https://doi.org/10.1006/anbe.1994.1333

    • Google Scholar
22. 1. Falótico T
    2. Proffitt T
    3. Ottoni EB
    4. Staff RA
    5. Haslam M

    (2019) Three thousand years of wild capuchin stone tool use

    Nature Ecology & Evolution 3:1034–1038.

    https://doi.org/10.1038/s41559-019-0904-4

    • PubMed
    • Google Scholar
23. 1. Fayet AL
    2. Hansen ES
    3. Biro D

    (2020) Evidence of tool use in a seabird

    PNAS 117:1277–1279.

    https://doi.org/10.1073/pnas.1918060117

    • PubMed
    • Google Scholar
24. 1. Fellers JH
    2. Fellers GM

    (1976) Tool use in a social insect and its implications for competitive interactions

    Science 192:70–72.

    https://doi.org/10.1126/science.192.4234.70

    • PubMed
    • Google Scholar
25. Book

    1. Hölldobler B
    2. Wilson EO

    (1990)

    The Ants

     Cambridge, USA: Belknap Press of Harvard University.

    • Google Scholar
26. 1. Hunt GR
    2. Gray RD

    (2002) Species-wide manufacture of stick-type tools by new caledonian crows

    Emu - Austral Ornithology 102:349–353.

    https://doi.org/10.1071/MU01056

    • Google Scholar
27. 1. Jeanson R

    (2019) Within-individual behavioural variability and division of labour in social insects

    The Journal of Experimental Biology 222:jeb190868.

    https://doi.org/10.1242/jeb.190868

    • PubMed
    • Google Scholar
28. 1. Jeanson R
    2. Weidenmüller A

    (2014) Interindividual variability in social insects - proximate causes and ultimate consequences

    Biological Reviews 89:671–687.

    https://doi.org/10.1111/brv.12074

    • PubMed
    • Google Scholar
29. 1. Kenward B
    2. Weir AAS
    3. Ch R
    4. Kacelnik A

    (2005) Tool manufacture by naive juvenile crows

    Nature 433:121.

    https://doi.org/10.1038/433121a

    • Google Scholar
30. 1. Klein S
    2. Pasquaretta C
    3. He XJ
    4. Perry C
    5. Søvik E
    6. Devaud JM
    7. Barron AB
    8. Lihoreau M

    (2019) Honey bees increase their foraging performance and frequency of pollen trips through experience

    Scientific Reports 9:6778.

    https://doi.org/10.1038/s41598-019-42677-x

    • PubMed
    • Google Scholar
31. 1. Kühbandner S
    2. Modlmeier AP
    3. Foitzik S

    (2014) Age and ovarian development are related to worker personality and task allocation in the ant Leptothorax acervorum

    Current Zoology 60:392–400.

    https://doi.org/10.1093/czoolo/60.3.392

    • Google Scholar
32. 1. Langridge EA
    2. Sendova-Franks AB
    3. Franks NR

    (2008) How experienced individuals contribute to an improvement in collective performance in ants

    Behavioral Ecology and Sociobiology 62:447–456.

    https://doi.org/10.1007/s00265-007-0472-5

    • Google Scholar
33. 1. Le S
    2. Josse J
    3. Husson F

    (2008) FactoMineR : An R Package for Multivariate Analysis

    Journal of Statistical Software 25:1–18.

    https://doi.org/10.18637/jss.v025.i01

    • Google Scholar
34. 1. Lessells CM
    2. Boag PT

    (1987) Unrepeatable repeatabilities: a common mistake

    The Auk 104:116–121.

    https://doi.org/10.2307/4087240

    • Google Scholar
35. 1. Lőrinczi G

    (2014)

    Some notes on the tool-using behaviour of the ant, Aphaenogaster subterranea (Hymenoptera: formicidae)

    Tiscia 40:17–24.

    • Google Scholar
36. 1. Lőrinczi G
    2. Módra G
    3. Juhász O
    4. Maák IE

    (2018) Which tools to use? choice optimization in the tool-using ant, Aphaenogaster subterranea

    Behavioral Ecology 29:1444–1452.

    https://doi.org/10.1093/beheco/ary110

    • Google Scholar
37. 1. Loukola OJ
    2. Perry CJ
    3. Coscos L
    4. Chittka L

    (2017) Bumblebees show cognitive flexibility by improving on an observed complex behavior

    Science 355:833–836.

    https://doi.org/10.1126/science.aag2360

    • PubMed
    • Google Scholar
38. 1. Maák I
    2. Lőrinczi G
    3. Le Quinquis P
    4. Módra G
    5. Bovet D
    6. Call J
    7. d'Ettorre P

    (2017) Tool selection during foraging in two species of funnel ants

    Animal Behaviour 123:207–216.

    https://doi.org/10.1016/j.anbehav.2016.11.005

    • Google Scholar
39. 1. Mallon E
    2. Pratt S
    3. Franks N

    (2001) Individual and collective decision-making during nest site selection by the ant Leptothorax albipennis

    Behavioral Ecology and Sociobiology 50:352–359.

    https://doi.org/10.1007/s002650100377

    • Google Scholar
40. 1. Martin-Ordas G
    2. Schumacher L
    3. Call J

    (2012) Sequential tool use in great apes

    PLOS ONE 7:e52074.

    https://doi.org/10.1371/journal.pone.0052074

    • PubMed
    • Google Scholar
41. 1. McDonald P

    (1984)

    Tool use by the ant, Novomessor albisetosus (Mayr)

    J New York Entomol S 92:156–161.

    • Google Scholar
42. 1. Morrill WL

    (1972) Tool using behavior of Pogonomyrmex badius (Hymenoptera: formicidae)

    The Florida Entomologist 55:59–60.

    https://doi.org/10.2307/3493647

    • Google Scholar
43. 1. Nakagawa S
    2. Schielzeth H

    (2010) Repeatability for gaussian and non-Gaussian data: a practical guide for biologists

    Biological Reviews of the Cambridge Philosophical Society 85:935–956.

    https://doi.org/10.1111/j.1469-185X.2010.00141.x

    • PubMed
    • Google Scholar
44. 1. Pamminger T
    2. Foitzik S
    3. Kaufmann KC
    4. Schützler N
    5. Menzel F

    (2014) Worker personality and its association with spatially structured division of labor

    PLOS ONE 9:e79616.

    https://doi.org/10.1371/journal.pone.0079616

    • PubMed
    • Google Scholar
45. 1. Pasquier G
    2. Grüter C

    (2016) Individual learning performance and exploratory activity are linked to colony foraging success in a mass-recruiting ant

    Behavioral Ecology 58:arw079–1709.

    https://doi.org/10.1093/beheco/arw079

    • Google Scholar
46. 1. Perez M
    2. Rolland U
    3. Giurfa M
    4. d'Ettorre P

    (2013) Sucrose responsiveness, learning success, and task specialization in ants

    Learning & Memory 20:417–420.

    https://doi.org/10.1101/lm.031427.113

    • PubMed
    • Google Scholar
47. 1. Pinter-Wollman N

    (2012) Personality in social insects: how does worker personality determine colony personality?

    Current Zoology 58:580–588.

    https://doi.org/10.1093/czoolo/58.4.580

    • Google Scholar
48. 1. Pinter-Wollman N
    2. Hubler J
    3. Holley J-A
    4. Franks NR
    5. Dornhaus A

    (2012) How is activity distributed among and within tasks in Temnothorax ants?

    Behavioral Ecology and Sociobiology 66:1407–1420.

    https://doi.org/10.1007/s00265-012-1396-2

    • Google Scholar
49. 1. Prut L
    2. Belzung C

    (2003) The open field as a paradigm to measure the effects of drugs on anxiety-like behaviors: a review

    European Journal of Pharmacology 463:3–33.

    https://doi.org/10.1016/S0014-2999(03)01272-X

    • PubMed
    • Google Scholar
50. Software

    1. R Development Core Team

    (2019) R: A language and environment for statistical computing, version 2.6.2

    R Foundation for Statistical Computing, Vienna, Austria.

    https://www.R-project.org/
51. 1. Ratnieks FLW
    2. Anderson C

    (1999) Task partitioning in insect societies

    Insectes Sociaux 46:95–108.

    https://doi.org/10.1007/s000400050119

    • Google Scholar
52. 1. Ravary F
    2. Lecoutey E
    3. Kaminski G
    4. Châline N
    5. Jaisson P

    (2007) Individual experience alone can generate lasting division of labor in ants

    Current Biology 17:1308–1312.

    https://doi.org/10.1016/j.cub.2007.06.047

    • PubMed
    • Google Scholar
53. Book

    1. Réale D
    2. Dingemanse NJ

    (2012) Animal Personality

    Chichester: John Wiley & Sons, LTD.

    https://doi.org/10.1002/9780470015902.a0023570

    • Google Scholar
54. 1. Robinson GE

    (1992) Regulation of division of labor in insect societies

    Annual Review of Entomology 37:637–665.

    https://doi.org/10.1146/annurev.en.37.010192.003225

    • PubMed
    • Google Scholar
55. 1. Robinson EJH
    2. Smith FD
    3. Sullivan KME
    4. Franks NR

    (2009) Do ants make direct comparisons?

    Proceedings of the Royal Society B: Biological Sciences 276:2635–2641.

    https://doi.org/10.1098/rspb.2009.0350

    • Google Scholar
56. Book

    1. Robson SK
    2. Traniello JFA

    (1999)

    Key individuals and the organization of labor in ants

    In: Detrain C, Deneubourg J. L, Pasteels J. M, editors. Information Processing in Social Insects. Basel: Birkhauser. pp. 239–260.

    • Google Scholar
57. 1. Root-Bernstein M
    2. Narayan T
    3. Cornier L
    4. Bourgeois A

    (2019) Context-specific tool use by Sus cebifrons

    Mammalian Biology 98:102–110.

    https://doi.org/10.1016/j.mambio.2019.08.003

    • Google Scholar
58. Book

    1. Sanz C
    2. Call J
    3. Boesch C

    (2013)

    Tool Use in Animals: Cognition and Ecology

    New York, USA: Cambridge University Press.

    • Google Scholar
59. Book

    1. Shumaker RW
    2. Walkup KR
    3. Beck BB

    (2011)

    Animal Tool Behavior: The Use and Manufacture of Tool by Animals

    Baltimore, USA: Johns Hopkins University Press.

    • Google Scholar
60. 1. Smith
    2. Bentley-Condit V

    (2010) Animal tool use: current definitions and an updated comprehensive catalog

    Behaviour 147:185.

    https://doi.org/10.1163/000579509X12512865686555

    • Google Scholar
61. 1. Somogyi AÁ
    2. Tartally A
    3. Maák IE
    4. Barta Z

    (2020) Colony size, nestmate density and social history shape behavioural variation in Formica fusca colonies

    Ethology 126:727–734.

    https://doi.org/10.1111/eth.13022

    • Google Scholar
62. 1. Stoffel MA
    2. Nakagawa S
    3. Schielzeth H

    (2017) rptR: repeatability estimation and variance decomposition by generalized linear mixed‐effects models

    Methods in Ecology and Evolution 8:1639–1644.

    https://doi.org/10.1111/2041-210X.12797

    • Google Scholar
63. 1. Tanaka T
    2. Ono Y

    (1978) The tool use by foragers of Aphaenogaster famelica

    Japanese Journal of Ecology 28:49–58.

    https://doi.org/10.18960/seitai.28.1_49

    • Google Scholar
64. 1. Theraulaz G
    2. Bonabeau E
    3. Denuebourg J-N

    (1998) Response threshold reinforcements and division of labour in insect societies

    Proceedings of the Royal Society of London. Series B: Biological Sciences 265:327–332.

    https://doi.org/10.1098/rspb.1998.0299

    • Google Scholar
65. 1. Udino E
    2. Perez M
    3. Carere C
    4. d'Ettorre P

    (2017) Active explorer show low learning performance in a social insect

    Current Zoology 63:555–560.

    https://doi.org/10.1093/cz/zow101

    • PubMed
    • Google Scholar
66. 1. Visalberghi E
    2. Addessi E
    3. Truppa V
    4. Spagnoletti N
    5. Ottoni E
    6. Izar P
    7. Fragaszy D

    (2009) Selection of Effective Stone Tools by Wild Bearded Capuchin Monkeys

    Current Biology 19:213–217.

    https://doi.org/10.1016/j.cub.2008.11.064

    • Google Scholar
67. 1. Walton A
    2. Toth AL

    (2016) Variation in individual worker honey bee behavior shows hallmarks of personality

    Behavioral Ecology and Sociobiology 70:999–1010.

    https://doi.org/10.1007/s00265-016-2084-4

    • Google Scholar

Author details

1. István Maák

   1. Department of Ecology, University of Szeged, Szeged, Hungary
   2. Museum and Institute of Zoology, Polish Academy of Science, Warsaw, Poland

   Contribution

   Conceptualization, Formal analysis, Supervision, Investigation, Methodology, Writing - original draft

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0999-4916

2. Garyk Roelandt

   Laboratory of Experimental and Comparative Ethology UR 4443, University Sorbonne Paris Nord, Villetaneuse, France

   Contribution

   Formal analysis, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

3. Patrizia d'Ettorre

   1. Laboratory of Experimental and Comparative Ethology UR 4443, University Sorbonne Paris Nord, Villetaneuse, France
   2. Institut Universitaire de France (IUF), Paris, France

   Contribution

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

   For correspondence

   d-ettorre@univ-paris13.fr

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8712-5719

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