cooperative problem solving in a social carnivore

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Cooperative problem solving in a social carnivore

2009, Animal Behaviour

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Andrea Migliano

Human hypercooperativity and the emergence of division of labor enables us to solve problems not only effectively within a group but also collectively. Collective problem-solving occurs when groups perform better than the additive performance of separate individuals. Currently, it is unknown whether this is unique to humans. To investigate the evolutionary origin of collective problem-solving and potential precursors, we propose a continuum of group effects on problem-solving, from simple to complex ones, eventually culminating in collective problem-solving. We tested captive common marmosets with a series of problem-solving tasks, either alone or in a group. To test whether the performance of a group was more than the sum of its parts, we compared real groups to virtual groups (pooled scores of animals tested alone). Marmosets in real groups were both more likely to solve problems than marmosets within the virtual groups and to do so faster. Although individuals within real groups ...

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Introduction to the special column: communication, cooperation, and cognition in predators

Arik kershenbaum.

a Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK

Daniel T. Blumstein

b Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095-1606, USA

Communication is the glue that holds societies together and we might expect that highly social species with more to communicate about will have more complex communication systems and more complex cognitive abilities. Social species gain benefits from living in groups, and many of these benefits rely on intra-group communication. For example, predator-specific alarm calls can lead to different evasion responses ( Suzuki 2014 ), or difficult to obtain food resources can be acquired using aggregation calls ( King and Janik 2015 ).

Thinking about the logical relationships between social complexity and communicative complexity date back to Larmark and Darwin but only more recently has been formalized into the Social Complexity Hypothesis (SCH) that states “… groups with more complex social systems require more complex communicative systems to regulate interactions and relations among group members ( Freeberg et al. 2012 ). Freeberg et al. (2012) special issue of the Philosophical Transactions of the Royal Society B provides a comprehensive, and timely evaluation of the SCH. It is logically related to the social or Machiavellian Intelligence Hypothesis, MIH ( Byrne and Whiten 1989 ) and the Social Brain Hypothesis, SBH ( Brothers 2002 ; Dunbar 2003 ) both of which emphasize the increased cognitive capabilities required for complex social living. Thus, communication, sociality, and cognition are logically intertwined with each other. And, as Freeberg and Krams (2015) point out, highly vocal species cooperate via calling behavior, so we can hypothesize that highly cooperative species may mediate their cooperation via vocalizations.

The existence of at least a correlative relationship between cooperation and cognition has been noted by multiple researchers, and forms the basis of the SBH ( Brothers 2002 ; Dunbar 2003 ) and the MIH ( Byrne and Whiten 1989 ). Recently, a link between social complexity and communicative complexity has also been observed ( Freeberg and Krams 2015 ), indicating the existence of a tripartite behavioral complex, in which communication, cooperation, and cognition (CCC) appear to be positively correlated with each other. However, the causal relationships between these three behaviors remain unclear.

Proponents of the SBH suggest that increased cognition (and with it, increased neocortical volume) evolved as a mechanism to track complex inter-individual relationships in social groups ( Dunbar 1993 , 2003 ; Sewall 2015 ). Others suggest that ecological factors may have driven increased cognitive ability, enhancing the potential of animals to benefit from social aggregations ( Barrett et al. 2007 ; Barrett and Würsig 2014 ).

The evolution of complex communication is even less clear, with some suggestions that communicative signals evolved as a result of living in large groups ( McComb and Semple 2005 ), whereas evidence from birds suggest that existing communicative abilities could have been exapated to support coexistence in larger aggregations ( Krams et al. 2012 ). However, complexity in sociality and communication has not received the attention it deserves outside sciurid rodents, birds, and primates ( Sewall 2015 ).

Much of the debate on these topics centers on the few study systems that have been extensively investigated for support of the SBH/MIH, in particular, non-human primates. While some criticism may be justified that a focus on primate behavior may lead to anthropomorphism of ecological context ( Barrett and Würsig 2014 ), a stronger argument in favor of widening the taxonomic base of CCC studies is that general evolutionary mechanisms are more likely to become apparent when examining a wider range of niches and adaptations. The generalizability of the SBH and MIH have been called into question ( Barrett et al. 2007 ; Bergman and Beehner 2015 ), and additional taxa must be studied that meet the criteria of cooperative behavior and well-developed cognition. Model systems such as social carnivores appear to be a fruitful direction of study, and interestingly these species often also show highly sophisticated communication ( Drea and Carter 2009 ). What were the evolutionary processes leading to this tripartite behavioral complex? And what can it tell us about the evolution of human CCC?

From an evolutionary perspective, it may be constructive to begin by thinking about what explains variation in acoustic structure and repertoire size. The SBH proposes that complex cognition is an adaptation to social living, and the SCH extends this to an explanation of complex communication ( Freeberg and Krams 2015 ). However, the emphasis on non-human primates, and the emphasis on explaining brain size in terms of social complexity may neglect the importance of other social and ecological factors driving cognition, such as cooperative foraging in dolphins ( Barrett and Würsig 2014 ), or limitations on physical brain size in otherwise highly social and cooperative species such as hyenas ( Holekamp et al. 2013 ).

This also leaves open the question of how cognitive and communicative complexity arose in the first place. It is constructive to address the precise drivers of acoustic structure and repertoire size in non-primate species. For instance, group size drives the evolution of individualistic alarm calls in sciurid rodents ( Pollard and Blumstein 2011 , 2012 ) while social complexity drives the evolution of repertoire size ( Blumstein and Armitage 1997 ; McComb and Semple 2005 ; Blumstein 2013 ).

The application of formal social network analyses across a wide range of species has permitted us to identify a suite of specific social attributes, but which attributes are relevant to models of cognition remains unclear ( Bergman and Beehner 2015 ). In addition, there remains a challenge to identify how these attributes map onto specific acoustic features and communicative abilities. More generally, however, these social attributes may be uniquely associated with specific types of cooperative behavior. For instance, Flack et al. (2006) showed that third-party policing maintains cooperative interactions in pigtailed macaques Macaca nemestrina and permits more complex social interactions to emerge. Without policing, macaque aggression fragments the social group into smaller and less stable social niches.

Meaning, arguably the most complex aspect of communication emerges both directly from signal structure when noisy, nonlinear vocalizations elicit enhanced responses (e.g., Slaughter et al. 2013 ; Blesdoe and Blumstein 2014 ), and from increased cognitive abilities (e.g., cooperative foraging in dolphins King and Janik 2015 ). These cognitive abilities may then influence the nature of cooperation, or cognitive abilities that evolved for social interactions may be exapted to permit more information and hence meaning from contextually variable vocalizations.

Although these proposed evolutionary pathways to communicative complexity are appealing, to understand them more precisely we need to identify model systems with sufficient complexity to allow us to identify common themes and variations.

We are not the first to propose that social carnivores are such a system to investigate the links between CCC ( Drea and Carter 2009 ). Social carnivores engage in a number of complex cooperative social behaviors ( Smith et al. 2012 ; Bailey et al. 2013 ). Some species coordinate movement through space, while others maintain social cohesion. Some cooperatively hunt and by doing so are able to take down larger prey than they could alone ( Escobedo et al. 2015 ), while others cooperatively defend their food from both conspecifics and heterospecifics ( Holekamp et al. 2007 ). Some engage in communal rearing, which may require complex “contracts” ( Clutton-Brock and Parker 1995 ; Silk 2007 ). The nature and complexity of cooperation varies widely, and whereas passive cooperation appears to require little or no coordination ( Brosnan et al. 2010 ), many predator species exhibit a high level of synchrony, coordination, and collaboration ( Bailey et al. 2013 ) that does indicate the ability of one animal to attend to the behavior and state of partner animals ( Tomasello et al. 1998 ; Emery et al. 2007 ; Drea and Carter 2009 ). All of these tasks are underpinned by effective communication, and communication efficiency has also been suggested as a driver of cognitive abilities ( Dunbar 1993 ).

Cooperative hunting also introduces challenges not present in other collaborative activities, most notably attention to the dynamic behavior of other individuals, whether hunter or prey. In fact, it appears to be attention to conspecifics that characterizes the most sophisticated cooperation. In examining the behavior of cooperative hunters in the order Carnivora, Bailey et al. (2013) point out that the highest level of cooperation is characterized by behavior that is more influenced by the position and behavior of conspecifics, rather than the position and behavior of the prey item. This in itself would suggest a beneficial role for intraspecific communication. Hunting also requires a (temporary) suppression of within-group aggression, and exercising restraint under highly aroused conditions; both of which are features of social groups with sophisticated communicative systems ( Bailey et al. 2013 ). Although few examples exist of vocal communication actually directing the course of a cooperative hunt, there are some indications that killer whales Orcinus orca use their vocal abilities coordinate seal hunting by “wave-washing” ( Pitman and Durban 2012 ).

The connection between cooperation and cognition however remains largely opaque to us. Despite intuitive ideas that sophisticated cooperative tasks, such as wolf pack hunting, must imply human-like abilities of foresight, planning, and even sense of self/other, many mathematical simulations have shown remarkably sophisticated patterns of cooperative or goal-directed behavior can be explained by simple rules ( Muro et al. 2011 ; Strombom et al. 2014 ). Furthermore, detailed examination of multiple taxa has not provided convincing evidence that cooperation is underpinned by sophisticated cognitive abilities ( Smith et al. 2012 ). It therefore remains an open question whether human mental abilities such as Theory of Mind arose from positive selection for problem solving such as cooperative hunting, or whether cognitive abilities arose first to contend with complex social relationships, and later were put to use to solve ecological problems ( Barrett et al. 2007 ; Seed et al. 2008 ). However, even if as has been proposed ( Gavrilets 2015 ), complex cognition arose from inter-group conflict, rather than intra-group cooperation, many social carnivore species show a range of inter- as well as intra-group behaviors similar to those exhibited by humans—such as that seen in the cooperative territorial defence in wolves ( Harrington and Mech 1983 ).

We have special relationships with several carnivores forged by a history of domestication. While we know that domestication selects for a series of behavioral and morphological traits, we have yet to understand how it has selected for specific cognitive abilities and how it may have simplified communication. However, some research suggests that domestication of dogs has preserved a communicative system that may at least in part support inter-specific collaborative hunting ( Hare and Tomasello 2005 ).

Others ( Smith et al. 2012 ) have noted how and why social carnivores are an important out-group for studies of cooperation in mammals and humans, principally because cooperation and sociality has independently evolved in carnivores. Thus, a number of questions about the mechanisms underpinning these independent evolutions permit us to search for general rules.

If the goal is to understand differences in species and to study the evolution of mechanistic diversity, we suggest that a concrete model linking CCC is required ( Figure 1 ). A tripartite behavioral complex such as CCC necessarily involves multiple interactions between the three elements of behavior (cooperation, cognition, and communication), and also the external environment, both physical and social. An integrative framework similar to that shown in Figure 1 can aid in formalizing and specifying these relationships, with a view to developing experimental and observational assessments of the relative role of each in the evolution of the complex as a whole.

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An integrative model linking cooperation, acoustic communication, and cognition that recognizes the important role that the physical environment plays in structuring signals, as well as the factors that influence the evolution of meaning and how increased cognitive abilities can facilitate the evolution of more complex cooperation.

Our model recognizes that the acoustic structure of vocalizations is influenced by both the physical environment, which both creates a context and may also influence the emotional valence of a signal and the social environment. We know that more socially complex species produce more complex repertoires and that social stress might modify the acoustic structure of vocalizations in ways that would be predicted by then nonlinearity and fear hypothesis ( Blumstein and Récapet 2009 ; Blumstein et al. 2010 ). The physical and social environment also places constraints on the communicative and cognitive abilities of species, as well as driving them to particular solutions to fitness challenges, that together define the animal’s niche ( Holekamp et al. 2013 ; Barrett and Würsig 2014 ).

We also suggest that the relationships between CCC should continue to embrace their Tinbergen diversity. For instance, there are classical studies of the development of both sociality and communication. New techniques, such as the animal model ( Kruuk 2004 ), permit us to study development in a variance decomposition way that reveals different factors may explain variation in signal structure at different age classes. For instance, the maternal environment explains significant variation in the structure of juvenile yellow-bellied marmot alarm calls, while variation in the structure of older animals is heritable ( Blumstein 2013 ). Adopting a trait-decomposition approach to study the evolution of complex abilities—both social and cognitive—might be possible for properly defined traits. Further, the sociogenomic revolution creates the opportunity to dive even deeper to identify both homology and homeoplasy in communicative, social, and cognitive traits ( Robinson et al. 2005 ).

Field studies of carnivores are often, by their very nature, long term. We believe this provides yet another call for the value of long-term research because the data required to understand the CCC nexus require long-term data and thus long-term financial support. In an age of budget cuts for scientific research, funding for long-term field studies is extremely difficult to obtain. Carnivore research is not inexpensive and thus articulating the need and value of a deeper understanding of the nexus is essential.

This special issue emerged from a symposium at a scientific meeting—Behaviour 2015 in Cairns, Australia—where five speakers shared insights into the relationship between CCC from studies of meerkats Suricata suricatta , feral cats Felis silvestris catus , spotted hyenas Crocuta crocuta , dogs Canis familiaris and wolves Canis lupus , and lions Panthera leo . We are pleased to have solicited additional articles from other contributors for this special issue.

Dunston et al. (2016) address the crucial question of the interplay between sociality (as measured by social network analysis), and varying conditions of the physical environment. African lions are highly social and highly cooperative hunters that are subject to intense conservation challenges. By comparing the social structure of both wild and captive-bred prides, Dunston et al. not only provide answers to important conservation questions of how and whether to reintroduce captive-bred animals into the wild, but also open a window into the fundamental nature of the social network in cooperative species. Captive-bred lions show very similar social structure to wild prides, indicating that specific aspects of how they interact with others are highly canalized are innate and likely adapted to their particular niche.

Staying in Africa, Lehmann et al. (2016) examine the highly sophisticated cooperative defence mechanisms of spotted hyenas. These social breeders use complex vocal communication to mediate their defensive responses to challenges from other species, particularly lions. Hyena mobbing calls represent one of the most sophisticated examples of vocal-mediated cooperative behavior, and Lehmann et al. show how the recruitment of additional hyenas greatly impacts the likely outcome of a potential conflict with lions. This study system represents one of the most promising avenues for investigating the interplay between sociality and communication, and Lehmann et al. lay the basis for future research in this direction.

Complex social cooperation is also found in wolves C. lupus and their close relatives, domestic dogs C. familiaris . Dale et al. (2017) examine one of the more perplexing aspects of social cooperation: food sharing between unrelated individuals. Despite the close relationship between these two species, the physical and social environments are very different, with wolves living in small, stable, mostly kin-groups, whereas free-ranging dogs live in large, multi-male/multi-female, mostly non-kin aggregations. The findings of Dale et al. that reciprocal provisioning non-kin is more common in more complex, less kin-related groups, provide an interesting hypothesis for the potential evolutionary pathways to the formation of more complex social groups.

Feral cats, as well as feral dogs, provide a surprising addition to our knowledge of the interplay between social cooperation and vocal communication. Once considered to be essentially solitary animals, Owens et al. (2017) show that feral cats have an unexpectedly complex vocal repertoire, which seems consistent with our current understanding of the social structure of feral cat colonies that often consist of large numbers of animals, displaying cooperative behavior such as alloparental care. However, studies of complex communicative behavior in feral cats have been frustrated by a lack of a consistent methodology for describing these vocalizations. Owens et al. bring the study of cat vocal behavior into line with the work done on other species, by providing an acoustic hierarchical classification system, which allows investigation of the nature and role of vocal signals in this well-known but under-studied animal.

One important question when examining the interplay between environment and behavior is the role of phylogeny and genetic drift. The many subspecies of gray wolf have become genetically isolated relatively recently, and provide an interesting study system for investigating the adaptive role of vocal communication in cooperative species. Hennelly et al. (2017) compare the vocal behavior of three smaller-bodied, more basal wolf lineages, to that of the larger Holoarctic subspecies. Howling is a long-range communication modality, vital to maintaining the cooperative social structure of wolf packs, and one could speculate that adaptive forces may shape the acoustic nature of howling to suit the different niches of each subspecies. However, Hennelly et al. show that the Himalayan wolf C. l. chanco uses vocalizations that are acoustically distinct from those of similarly sized North African wolves C. l. lupaster and Indian wolves C. l. pallipes . Phylogenetic constraints as well as habitat differences may underlie different vocal behaviors, adding yet another dimension to the raft of factors both driving and constraining the evolution of complex social, cognitive, and communicative behavior.

Finally, Wyman et al. (2017) examine the role of social effects in modifying the communicative behavior of cooperative group-living meerkats. Information reliability, and the role of dominance and signaler identity (shown on the lower axis of Figure 1 ) play a major role in shaping the acoustic structure of a group’s communication signals. Meerkats cooperatively provision pups while foraging, but the loud and persistent begging calls of the young cause a marked alteration in adult cohesion calling. Individuals must trade off the various constraints driving a particular communicative behavior, in the light of changing social group composition (e.g., the presence of pups). Such changes in acoustic structure with changing social context may provide a pathway to more context-specific communication, and thence to communicative meaning, and the cognitive skills necessary to interpret that meaning.

We are thrilled by the opportunities that knowledge of cognitive abilities has for both welfare and conservation. All the studies in this issue raise questions that are relevant for understanding the nature and evolution of complex cognition and cooperation, but also address real-world questions of conservation and management. By understanding better the nature of the social behavior of some of the world’s most charismatic animals, we can make better decisions to mitigate conflict with humans, and preserve their presence in the wild.

We thank the organizers of Behaviour-2015 for supporting our symposium and Dr Zhi-Yun Jia for making this special column possible.

DTB is currently supported by NSF DEB-1557130, and AK by a Herchel Smith fellowship from the University of Cambridge. We thank the general public who supported participation in the symposium at Behaviour 2015 through the crowdfunding website https://experiment.com/projects/canid-howls-a-window-to-cognition-and-cooperation .

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Hyenas Cooperate, Problem-solve Better Than Primates

Spotted hyenas may not be smarter than chimpanzees, but a new study shows that they outperform the primates on cooperative problem-solving tests.

Captive pairs of spotted hyenas (Crocuta crocuta) that needed to tug two ropes in unison to earn a food reward cooperated successfully and learned the maneuvers quickly with no training. Experienced hyenas even helped inexperienced partners do the trick.

When confronted with a similar task, chimpanzees and other primates often require extensive training and cooperation between individuals may not be easy, said Christine Drea, an evolutionary anthropologist at Duke University.

Drea's research, published online in the October issue of Animal Behavior , shows that social carnivores like spotted hyenas that hunt in packs may be good models for investigating cooperative problem solving and the evolution of social intelligence. She performed these experiments in the mid-1990s but struggled to find a journal that was interested in non-primate social cognition.

"No one wanted anything but primate cognition studies back then," Drea said. "But what this study shows is that spotted hyenas are more adept at these sorts of cooperation and problem-solving studies in the lab than chimps are. There is a natural parallel of working together for food in the laboratory and group hunting in the wild."

Drea and co-author Allisa N. Carter of the Univ. of California at Berkeley, designed a series of food-reward tasks that modeled group hunting strategies in order to single out the cognitive aspects of cooperative problem solving. They selected spotted hyenas to see whether a species' performance in the tests might be linked to their feeding ecology in the wild.

Spotted hyena pairs at the Field Station for the Study of Behavior, Ecology and Reproduction in Berkeley, Calif. were brought into a large pen where they were confronted with a choice between two identical platforms 10 feet above the ground. Two ropes dangled from each platform. When both ropes on a platform were pulled down hard in unison -- a similar action to bringing down large prey -- a trap door opened and spilled bone chips and a sticky meatball. The double-rope design prevented a hyena from solving the task alone, and the choice between two platforms ensured that a pair would not solve either task by chance.

The first experiment sought to determine if three pairs of captive hyenas could solve the task without training. "The first pair walked in to the pen and figured it out in less than two minutes," Drea said. "My jaw literally dropped."

Drea and Carter studied the actions of 13 combinations of hyena pairs and found that they synchronized their timing on the ropes, revealing that the animals understood the ropes must be tugged in unison. They also showed that they understood both ropes had to be on the same platform. After an animal was experienced, the number of times it pulled on a rope without its partner present dropped sharply, indicating the animal understood its partner's role.

"One thing that was different about the captive hyena's behavior was that these problems were solved largely in silence," Drea said. Their non-verbal communication included matching gazes and following one another. "In the wild, they use a vocalization called a whoop when they are hunting together."

In the second and third experiments, Drea found that social factors affected the hyenas' performance in both positive and negative ways. When an audience of extra hyenas was present, experienced animals solved the task faster. But when dominant animals were paired, they performed poorly, even if they had been successful in previous trials with a subordinate partner.

"When the dominant females were paired, they didn't play nicely together," Drea said. "Their aggression toward each other led to a failure to cooperate."

When a naïve animal unfamiliar with the feeding platforms was paired with a dominant, experienced animal, the dominant animals switched social roles and submissively followed the lower-ranking, naïve animal. Once the naïve animal became experienced, they switched back.

Both the audience and the role-switching trials revealed that spotted hyenas self-adjust their behavior based upon social context.

It was not a big surprise that the animals were strongly inclined to help each other obtain food, said Kay Holekamp, a professor of zoology at Michigan State University who studies the behavioral ecology of spotted hyenas.

"But I did find it somewhat surprising that the hyenas' performance was socially modulated by both party size and pair membership," Holekamp said. "And I found it particularly intriguing that the animals were sensitive to the naïveté of their potential collaborators."

Researchers have focused on primates for decades with an assumption that higher cognitive functioning in large-brained animals should enable organized teamwork. But Drea's study demonstrates that social carnivores, including dogs, may be very good at cooperative problem solving, even though their brains are comparatively smaller.

"I'm not saying that spotted hyenas are smarter than chimps," Drea said. "I'm saying that these experiments show that they are more hard-wired for social cooperation than chimpanzees."

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Christine M. Drea, Allisa N. Carter. Cooperative problem solving in a social carnivore . Animal Behaviour , 2009; 78 (4): 967 DOI: 10.1016/j.anbehav.2009.06.030

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Cooperative problem solving in giant otters ( Pteronura brasiliensis ) and Asian small-clawed otters ( Aonyx cinerea )

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Published: 24 August 2017
Volume 20 , pages 1107–1114, ( 2017 )

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Martin Schmelz 1 , 2 , 3 ,
Shona Duguid ORCID: orcid.org/0000-0003-4844-0673 1 , 3 ,
Manuel Bohn 1 , 3 &
Christoph J. Völter 1 , 3 , 4

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Cooperative problem solving has gained a lot of attention over the past two decades, but the range of species studied is still small. This limits the possibility of understanding the evolution of the socio-cognitive underpinnings of cooperation. Lutrinae show significant variations in socio-ecology, but their cognitive abilities are not well studied. In the first experimental study of otter social cognition, we presented two species—giant otters and Asian small-clawed otters—with a cooperative problem-solving task. The loose string task requires two individuals to simultaneously pull on either end of a rope in order to access food. This task has been used with a larger number of species (for the most part primates and birds) and thus allows for wider cross-species comparison. We found no differences in performance between species. Both giant otters and Asian small-clawed otters were able to solve the task successfully when the coordination requirements were minimal. However, when the temporal coordination demands were increased, performance decreased either due to a lack of understanding of the role of a partner or due to difficulty inhibiting action. In conclusion, two species of otters show some ability to cooperate, quite similar to most other species presented with the same task. However, to draw further conclusions and more nuanced comparisons between the two otter species, further studies with varied methodologies will be necessary.

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Introduction

Cooperation can take many forms in social carnivores, from cooperative hunting, to territory defense, intragroup alliances and cooperative breeding. The cognitive processes resulting in these various forms of cooperation are likely to be equally varied and have thus been the subject of much experimental research with captive populations. These studies investigate not only the conditions under which cooperation is successful but also what individuals understand about cooperation, for example, what they understand about the need for cooperative partners and how they use this understanding to solve problems cooperatively. The comparison of these cooperative abilities between species has important implications for understanding the evolution of cooperation and cognition (Brosnan et al. 2010 ; Burkart and van Schaik 2010 ; Byrne and Whiten 1988 ; Dunbar 2009 ).

A simple experimental paradigm, the “loose string task,” has been used to investigate cooperation in a variety of species, including primates (e.g., Hirata and Fuwa 2007 ; Melis et al. 2006a ; Molesti and Majolo 2016 ), birds (e.g., Massen et al. 2015 ; Seed et al. 2008 ), and elephants (Plotnik et al. 2011 ), but no carnivores have been studied, except for domestic dogs (Ostojić and Clayton 2014 ), which are a special case because of the effects of human selection. This task focuses on mutualistic cooperation in which individuals need to coordinate their actions with others to gain rewards they would not be able to access individually. Originally designed for chimpanzees, the task requires two individuals to pull simultaneously on either end of a rope to pull in a food reward. The rope is set up so that if only one pulls, the other end of rope moves out of reach and the food remains inaccessible (Hirata and Fuwa 2007 ). Success in this task suggests an ability to coordinate actions with conspecifics. However, a stronger test of what individuals understand about the role of a partner for successful cooperation is the delayed version of the task (also part of the original design in Hirata and Fuwa 2007 ). In this case, initially only one subject is given access to the rope and they have to wait until a partner arrives before pulling. Importantly, this version rules out the possibility that success is achieved by individuals accidently pulling at the same time. In order to pass the delay task, subjects need to understand that a partner is necessary for success. Chimpanzees not only wait for a partner, but are able to recruit a partner when necessary (Melis et al. 2006a ) and can also choose a competent partner over an incompetent one (Melis et al. 2006b ). Few other species have been presented with this version of the task: rooks (Seed et al. 2008 ); ravens (Massen et al. 2015 ); African grey parrots (Péron et al. 2011 ); kea (Heaney et al. 2017 ); domestic dogs with human partners (Ostojić and Clayton 2014 ); and Asian elephants (Plotnik et al. 2011 ). Of these, only Asian elephants and kea were able to wait for a partner for an extended period of time (up to 45 s for elephants and 65 s for kea) and domestic dogs for a shorter period (2.2 s on average).

In the current study, we compare two species of otter on the loose string task: giant otters ( Pteronura brasiliensis ) and Asian small-clawed otters ( Aonyx cinerea ; Fig. 1 ).

The two study species. a Asian small-clawed otters (photograph by Isabelle Grubert) and b giant otters (photograph by Shona Duguid) in Zoo Leipzig

To date, very little is known about the cognitive abilities of otters (Lutrinae) and the experimental work that has been conducted is spread across species, particularly with regard to social cognition. Most notably, call-back experiments suggest that both giant and Asian small-clawed otters can recognize individual callers (Lemasson et al. 2013 ; Mumm et al. 2014 ) and small-clawed otters show evidence of spatial memory for food locations (Perdue et al. 2013 ).

Although the experimental research is sparse, more is known about the behavior of wild populations, at least for giant otters. Giant otters are the largest species of otter and are found mainly in Brazilian river systems (Kruuk 2006 ). They are cooperative breeders that live in groups of up to 20 (though usually around 3–9 individuals; Duplaix 1980 ; Groenendijk et al. 2014 ) consisting of a breeding pair, their young, and older helpers that babysit (Rosas et al. 2009 ) and provision the young (Kruuk 2006 ). As well as being cooperative breeders, groups will jointly defend their territory from predators such as caiman and forage together (Duplaix 1980 ), with some indication they hunt fish cooperatively (Staib 2002 ).

Asian small-clawed otters are the smallest otter species; they are found in wetland habitats across India, South East Asia and southern China (Hussain et al. 2011 ). They also live in social groups; however, much less is known about their socio-ecology as most observations of their social structure were made in captive populations (Hussain et al. 2011 ). They live in extended family groups of up to 15 individuals (Kruuk 2006 ), with both parents involved in upbringing of the young (Hussain et al. 2011 ). In contrast to giant otters, small-clawed otters generally forage individually (Kruuk et al. 1994 ).

Overall, both species are social but the evidence suggests that coordinated cooperative activities, particularly in foraging contexts, play a more important role in the lives of giant otters. Thus, when presented with a new cooperative problem-solving task that involves coordination, we expect giant otters to outperform Asian small-clawed otters. We presented captive otters, one group of giant otters ( N = 5) and one group of Asian small-clawed otters ( N = 4) with the simultaneous and delay versions of the loose string task to investigate their abilities to cooperate with each other. Following Massen et al. ( 2015 ) and Molesti and Majolo ( 2016 ), we tested both species in a group setting, with all group members present. This reflects the setting in which cooperative problems would be solved in the wild.

Two family groups of otters—five giant otters ( Pteronura brasiliensis ) and four Asian small-clawed otters ( Aonyx cinerea )—participated in this study. None of the subjects had previous experience with experimental studies. The animals were housed at Leipzig zoo. The giant otter group consisted of an adult female (9.5 years) with her four subadult offspring (2 females, all 1.5 years of age). The small-clawed otter group consisted of four males (siblings) aged between 5.0 and 6.6 years (see Supplementary Material 1 for details concerning husbandry and enclosures). One juvenile giant (Erna) otter stopped participating during the training and was therefore not included in any analysis.

The individual training apparatus consisted of small, square PVC platforms (giant otters: 30 × 30 cm, small-clawed otters: 15 × 15 cm) with a rope attached to it (see Fig. 2 a). The cooperation apparatus was modeled on the original design by Hirata and Fuwa ( 2007 ). Our “Hirotter” board consisted of a long, flat, U-shaped platform (giant otters: 200 × 60 cm, small-clawed otter: 100 × 30 cm, see Fig. 2 b). The training and test boards were located on the floor outside the enclosure. During the test, we baited both ends of the board with food rewards with preferred food types as indicated by the caretakers (pieces of fresh fish for the giant otters and cat food for the small-clawed otters, after trying grapes in the first sessions). A rope ran around three vertical screws (for the giant otters) or through two eyebolts (for the small-clawed otters) that were protruding from the platform at both ends (and in the middle for the giant otters). At both sides of the platform, the ends of the rope extended into the otter enclosure underneath the mesh. The otters could access the food on the platform if two individuals were cooperating either by pulling at each end of the rope simultaneously or by holding one end of the rope, while the partner was pulling the other end of the rope. One individual pulling the rope alone resulted in removal of the rope from the apparatus without moving the baited platform. Thus, pulling only one end of the rope resulted in loss of access to the food as the second individual could no longer reach the rope.

Illustrations of the two types of apparatus used in the current study. a Individual training, b cooperation test

The entire study was conducted in a group setting per species, i.e., no individuals were separated from the group at any point. Subjects were first trained in an individual string pulling task before they entered the cooperation test phase (see Supplementary Material 1 for details). The cooperation test phase encompassed five conditions that were administered in this order: Simultaneous I (6 sessions/103 trials), Simultaneous II (6 sessions/93 trials), Delay I (3 sessions/28 trials), Long-rope-delay (3 sessions/29 trials) and Delay II (1 session/14 trials) (see Supplementary Material 2 for examples of simultaneous and delay trials in both species). For the giant otters, the number of trials per session varied (between 5 and 30 trials) depending on the food availability as the amount and size of fish provided to us by the zoo varied. For the small-clawed otters, we matched the number of trials to the giant otters. In all conditions, both sides of the platform were baited at the same time. In the simultaneous conditions, the experimenters slid both ends of the rope underneath the mesh of the enclosure at the same time when at least one subject was present on each side of the apparatus. Subjects could therefore access the two ends of the rope simultaneously; no waiting was necessary. When one individual pulled harder than the other one, the platform sometimes tilted so that one side of the platform became accessible before the other one. When this happened, the former individual typically released the rope to eat the food. For this reason, the other individual could not retrieve its food reward. In the Simultaneous I condition, this resulted in an uneven food distribution in some trials (proportion of trials with uneven food distribution in Simultaneous 1: giant otters: 0.40; small-clawed otters: 0.20). In Simultaneous II, the experimenters pushed the other side of the platform forward when the platform tilted to maintain a consistent reward contingency.

In the delay conditions, all individuals in the group were lured to another compartment of the enclosure as far from the apparatus as possible where every individual would receive a piece of food. While the test compartment was empty, the platform was baited and the two ends of the rope were pushed into the test compartment (see Fig. 3 ). The delayed access to the rope ends was achieved by the delayed entry of the otters because one rope was closer to the door to the adjacent compartment, so that when the otters returned to the testing compartment, the first individual could access this end first and they would have to wait before another individual could move around to the other end of the rope. In Delay I and II, the rope was the same length as in the simultaneous conditions (giant otters: 4.0 m total length, approx. 0.3 m inside the cage at either end; small-clawed otters: 2.0 m, approx. 0.15 m inside). In the Long-rope-delay condition, we extended the length of the rope, thereby relaxing the need for temporal synchronization of pulling (giant otters: 5.4 m, approx. 1 m inside; small-clawed otters: 2.7 m, approx. 0.5 m inside) and providing the otters with further opportunity to learn the affordances of the delay conditions.

Illustration of the setup in the delay conditions. Subjects were lured to the adjacent compartment, while the Hirotter board was baited. One end of the rope was closer to the door to the adjacent compartment than the other one so that the returning subjects could access this end of the rope before the other one

Coding and analysis

For each trial, we coded whether or not the participating otters were successful. Trials in which the board was pulled in only on one side were also coded as success (proportion of all trials: giant otters: 0.45; small-clawed otters: 0.27). A second coder, blind to the purpose of the study, coded a random selection of 20% of test trials from video. There was a very high agreement of 96.36% between the two coders (Cohen’s Kappa; Κ = 0.92). Furthermore, we coded live which subject pulled on which end of the rope (left or right). In most unsuccessful trials, one subject started pulling on the rope, while the other end was unoccupied. For these trials, we coded the subject who pulled on the rope. For the delay conditions, a third coder coded the time between the arrival of the first otter and the arrival of the second otter at the board from video.

The dependent variable was the binary success code. To analyze the data, we used a generalized linear mixed model (GLMM) with a binomial error structure. All models were fitted in R (R Core Team 2012 ) using the function glmer of the R-package lme4 (Bates et al. 2015 ). We used likelihood ratio tests (LRT) to assess whether the inclusion of predictors and their interactions improved the general fit of a model to the data by comparing models with and without the respective effects (Dobson and Barnett 2008 ).

The full model comprised of species, condition and their interaction as fixed effects and trial and session number as covariates. We compared this model to a reduced model comprising of only the covariates (trial number and session number). To test the significance of the interaction, we compared the full model to a reduced model without the interaction. Given the interaction turned out to be nonsignificant, we tested the significance of each fixed effect (species and condition) by comparing a model comprising them to a model lacking them. We accounted for the identity of the first individual pulling one end of the rope (left and right) and the specific dyad by including them as random intercept terms (see Supplementary Material 1 for details).

The full model of coordination success comprising of species, condition and their interaction fit the data better compared to models lacking them [LRT: χ 2 (9) = 39.05, p < .001]. The interaction term between species and condition did not improve the model fit [LRT: χ 2 (9) = 2.13, p = .713]. In the final models without the interaction, we found a significant effect of condition [LRT: χ 2 (4) = 34.61, p > .001] but no significant differences between species [LRT: χ 2 (1) = 1.20, p = .283]. Figure 4 shows the proportion of successful trials for each condition in the two species; Table 1 shows the average estimates, p values and confidence intervals for the final model.

Proportion of successful trials per condition and otter species

Performance in all conditions was compared to the Simultaneous I condition (see Table 1 ). There was a tendency for higher success in the Simultaneous II condition. This could be due to learning or higher motivation because the experimenters compensated for the tilting of the board. In the crucial comparison between the Simultaneous I condition and the Delay I condition, we found that success was significantly lower in the Delay I condition. Figure 4 depicts the substantial reduction in coordination success between the conditions in both species. A direct comparison between Delay I and Delay II found no significant increase [average GLMM estimate: β = 0.38, p = .496, 95% CI (−8.38: 2.99)] suggesting the experience with the longer rope in the Long-rope-delay condition did not improve performance.

Interestingly, there was no significant difference in success between the Simultaneous I and Long-rope-delay condition, suggesting the increase in rope length did reduce the coordination demands, though there was no significant improvement in comparison with Delay I [average GLMM estimate: β = 1.74, p = .159, 95% CI (−0.90: 4.84)].

In successful trials, giant otters had to wait on average 3.25 s (range: 1–5 s) for a partner to arrive at the board, while small-clawed otters had to wait on average 1.6 s (range: 1–3 s). In unsuccessful trials, the second partner arrived on average after 8.22 s (range: 1–28 s) for giant otters and after 1.83 s (range: 0–13 s) for small-clawed otters. More details about qualitative differences between species can be found in Supplementary Material 1.

In the first comparative experimental study of otter social cognition, individuals of the two otter species spontaneously passed the individual training and solved the cooperative problem-solving task in a well-established paradigm, the loose string task (Hirata and Fuwa 2007 ). When the two ends of the rope were within reach simultaneously, both giant otter and Asian small-clawed otter pairs were able access the food at high rates. There were no differences in success rates between species, but there were differences across conditions. Otters performed substantially worse as soon as there was a delay between individuals accessing the ropes, requiring the first subject to wait for another one to act together. When we increased the length of the rope to provide an opportunity for subjects to learn the arrival of a partner would lead to success, we found evidence the longer rope did relax synchronization requirements; however, this did not lead to subsequent improvement in performance with the original rope length. Our results do not support the hypothesis that the more socially dependent lifestyle of giant otters would cause higher cooperative problem-solving skills in this experiment. There are several factors that should be taken into consideration; these will be discussed below.

Otters (and other species that do not succeed in the delay task) could either not inhibit pulling the rope or did not understand the task contingencies sufficiently and therefore pulled the rope as soon as they could reach it. This resulted in low success rates in the delay condition. They were, however, successful in the simultaneous conditions. With this result, they are in good company with various species known for their high cognitive skills such as rooks (Seed et al. 2008 ), African grey parrots (Péron et al. 2011 ) and ravens (Massen et al. 2015 ) that were all tested in the loose string task with similar methods and all showed similar results. Importantly, all these species also failed a delay condition. This leads to the question of what the simultaneous condition can tell us about cooperation, when success can be achieved as a by-product of individual actions. This is particularly important considering there are several studies using the loose string task that did not include a delay condition at all (e.g., Hare et al. 2007 ; Drea and Carter 2009 ; Scheid and Noë 2010 ). Succeeding in the simultaneous condition clearly does not suffice to claim complex social cognitive abilities, but it is a successful behavior nonetheless. It could also be argued that successful cooperation in the wild, such as cooperative hunting, may also depend more on situational coordination and by-product mutualism than on cognitive skills and an understanding of a partner’s role (Gilby and Connor 2010 ). Success in the delay task, however, appears necessary to draw any conclusions about the ability of a species to coordinate their actions for cooperation (according to the definition of Boesch and Boesch 1989 ).

In the current version of the loose string task, the otters were tested in their social group, increasing the ecological validity of the situation. Given the feeding ecology of giant otters (foraging in groups) versus Asian small-clawed otters (foraging individually), we expected this setup to advantage giant otters. Our results suggest this was not the case. It is possible that the group setting, instead of fostering more natural cooperative behaviors, increased competition which might in turn have promoted faster, less inhibited decision making and thus poor performance in the delay task. Tolerance has previously been found to play an important role in task success (Hare et al. 2007 ; Schwing et al. 2016 ), and neither of the two previous species presented with the loose string task in a group passed the delay task (Massen et al. 2015 ; Molesti and Majolo 2016 ). We noted a species difference in the composition of pulling pairs: A single pair was responsible for the vast majority of all successful trials in giant otters (Madija and Otto), whereas successful pairs in small-clawed otters were more balanced across individuals, suggesting the level of tolerance in small-clawed otters is higher. However, the group composition differed between groups: Both groups were made up of family members, as is typical for both species, but in the giant otters the adult male had died the previous year, and in the small-clawed otters, there was no breeding pair, only siblings. It is difficult to predict how these differences may have affected the behavior in the test. Future research might aim at testing otters in a more controlled setting to look at success rates of dyads and to investigate the effect of the group setting. Unfortunately, to avoid major disruption of group cohesion it was not possible for us to separate the giant otters.

The current study is the first comparative social cognitive study conducted with otters. It is therefore a first step to explore the socio-cognitive capacities of these species known for traits suggested to be an indication of complex cognitive skills in other taxa, e.g., cooperative breeding and hunting, large relative neocortex size (compared to other carnivores; Dunbar and Bever 1998 ), neophilia and social complexity (Byrne and Whiten 1988 ; Humphrey 1976 ). We have a clear-cut result: Both giant otters and Asian small-clawed otters succeeded in solving the social problem of our version of the loose string task when pairs could reach the ends of the rope simultaneously. In both species, this success broke down as soon as a delay was introduced. Otters’ failure to wait for a partner suggests that they either did not understand the task contingencies or could not inhibit pulling a rope as soon as it was available. This initial finding should be explored in more detail in the future.

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Acknowledgements

Open access funding provided by Max Planck Society. We thank the Zoo Leipzig, particularly Kerstin Tischmeyer, Christian Patzer, Michael Ernst and Fabian Schmidt, for the access to the otters, and we are very grateful for the pleasant collaborative experience. We thank Sebastian Schütte and Johannes Grossmann for their help with the apparatus, Mathias Harrer and Tjadina Klein for coding assistance and especially Roger Mundry for the statistical analysis.

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Department of Developmental and Comparative Psychology, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

Martin Schmelz, Shona Duguid, Manuel Bohn & Christoph J. Völter

Department of Cognitive Biology, University of Vienna, Vienna, Austria

Martin Schmelz

The Otter Project, Leipzig, Germany

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MS, SD, MB and CV designed the experiment, collected the data and wrote the manuscript. MB analyzed the data.

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Correspondence to Shona Duguid .

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All applicable international, national and/or institutional guidelines for the care and use of animals were followed. All procedures performed in studies involving animals were in accordance with the ethical standards of the institution or practice at which the studies were conducted. Research was noninvasive and strictly adhered to the legal requirements of Germany. The study was ethically approved by an Internal Committee at the Zoo Leipzig. Animal husbandry and research comply with the “EAZA Minimum Standards for the Accommodation and Care of Animals in Zoos and Aquaria,” the “WAZA Ethical Guidelines for the Conduct of Research on Animals by Zoos and Aquariums” and the “Guidelines for the Treatment of Animals in Behavioural Research and Teaching” of the Association for the Study of Animal Behaviour (ASAB). IRB approval was not necessary because no special permission for the use of animals in purely behavioral or observational studies is required in Germany (TierSchGes §7 and §8).

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Schmelz, M., Duguid, S., Bohn, M. et al. Cooperative problem solving in giant otters ( Pteronura brasiliensis ) and Asian small-clawed otters ( Aonyx cinerea ). Anim Cogn 20 , 1107–1114 (2017). https://doi.org/10.1007/s10071-017-1126-2

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Received : 23 January 2017

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Accepted : 18 August 2017

Published : 24 August 2017

Issue Date : November 2017

DOI : https://doi.org/10.1007/s10071-017-1126-2

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Hyenas cooperate, problem-solve better than primates

Duke University

DURHAM, N.C. -- Spotted hyenas may not be smarter than chimpanzees, but a new study shows that they outperform the primates on cooperative problem-solving tests.

"When the dominant females were paired, they didn't play nicely together," Drea said. "Their aggression toward each other led to a failure to cooperate."

Both the audience and the role-switching trials revealed that spotted hyenas self-adjust their behavior based upon social context.

"I'm not saying that spotted hyenas are smarter than chimps," Drea said. "I'm saying that these experiments show that they are more hard-wired for social cooperation than chimpanzees."

Animal Behaviour

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Hyenas Cooperate, Problem-Solve Better Than Primates

Non-verbal communication, social awareness guide pack behavior

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A pair of captive hyenas cooperatively solving a task to get some food.

Spotted hyenas may not be smarter than chimpanzees, but a new study shows that they outperform the primates on cooperative problem-solving tests.

Drea's research, published online in the October issue of Animal Behavior, shows that social carnivores like spotted hyenas that hunt in packs may be good models for investigating cooperative problem solving and the evolution of social intelligence. She performed these experiments in the mid-1990s but struggled to find a journal that was interested in non-primate social cognition.

"When the dominant females were paired, they didn't play nicely together," Drea said. "Their aggression toward each other led to a failure to cooperate."

Both the audience and the role-switching trials revealed that spotted hyenas self-adjust their behavior based upon social context.

"I'm not saying that spotted hyenas are smarter than chimps," Drea said. "I'm saying that these experiments show that they are more hard-wired for social cooperation than chimpanzees."

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Cooperative problem solving in a social carnivore
Numerous field researchers have described cooperative hunting in social carnivores, but experimental evidence of cooperative problem solving typically derives from laboratory studies of nonhuman primates. We present the first experimental evidence of cooperation in a social carnivore, the spotted hyaena, Crocuta crocuta.
PDF Cooperative problem solving in a social carnivore
We suggest that social carnivores should be considered relevant models for the study of cooperative problem solving, as their abilities provide a comparative framework for testing theories about the mechanisms of social learning and the evolution of intelligence. 2009 The Association for the Study of Animal Behaviour.
Cooperative problem solving in a social carnivore
More cooperative behaviors are associated with, among other factors, larger brains in the Carnivora [66] and cooperative problem-solving has been tested in several species of social carnivores ...
Cooperative problem solving in a social carnivore
Semantic Scholar extracted view of "Cooperative problem solving in a social carnivore" by C. Drea et al. Skip to search form Skip to main content Skip to ... @article{Drea2009CooperativePS, title={Cooperative problem solving in a social carnivore}, author={Christine M. Drea and Allisa Neves Carter}, journal={Animal Behaviour}, year={2009 ...
Cooperative problem solving in a social carnivore.
Numerous field researchers have described cooperative hunting in social carnivores, but experimental evidence of cooperative problem solving typically derives from laboratory studies of nonhuman primates. We present the first experimental evidence of cooperation in a social carnivore, the spotted hyaena, Crocuta crocuta. Eight captive hyaenas, paired in 13 combinations, coordinated their ...
Cooperation in Social Carnivores
Although the social carnivores evolved from noncooperative ancestors, individuals within these extant species cooperate with group-mates to hunt large game, defend resources, guard against predators, attack others, and/or rear young (Smith et al. 2012, In press ). Moreover, older and socially dominant individuals often emerge as leaders in the ...
Natural conditions and adaptive functions of problem-solving in the
More cooperative behaviors are associated with, among other factors, larger brains in the Carnivora [66] and cooperative problem-solving has been tested in several species of social carnivores including lions [40], spotted hyenas [38], wolves [67], dogs [67], giant otters (Pteronura brasiliensis) [41], and small-clawed otters (Aonyx cinerea ...
The current state of carnivore cognition
Social and asocial carnivores present opportunities to test whether inhibitory control is necessary for cooperative hunting. Social carnivores may have enhanced inhibitory control due to the need to delay gratification during ... Drea CM, Carter AN (2009) Cooperative problem solving in a social carnivore. Anim Behav 78(4):967-977. ...
Cooperative problem solving in a social carnivore
Cooperative problem solving in a social carnivore
Cooperative problem solving in giant otters (Pteronura brasiliensis
Cooperation can take many forms in social carnivores, from cooperative hunting, to territory defense, intragroup alliances and cooperative breeding. ... Cooperative problem solving in a social carnivore. Anim Behav. 2009; 78 (4):967-977. doi: 10.1016/j.anbehav.2009.06.030. [Google Scholar] Dunbar RIM. The social brain hypothesis and its ...
Socially tolerant lions ( Panthera leo ) solve a novel cooperative problem
I used a food-sharing task and cooperative problem-solving task to investigate tolerance and cooperation in lions. The majority of pairs (N = 5/7 dyads) solved the cooperative task, repeated success in consecutive trials, and demonstrated cooperative complexity at the levels of similarity and synchrony. ... Social carnivores outperform asocial ...
Introduction to the special column: communication, cooperation, and
Cooperative problem solving in a social carnivore. Anim Behav 78:967-977. [Google Scholar] Dunbar RI, 1993. Coevolution of neocortical size, group size and language in humans. Behav Brain Sci 16:681-694. [Google Scholar] Dunbar RI, 2003. The social brain: mind, language, and society in evolutionary perspective. Annu Rev Anthropol 32:163-181.
Cooperative problem solving in a social carnivore
Numerous field researchers have described cooperative hunting in social carnivores, but experimental evidence of cooperative problem solving typically derives from laboratory studies of nonhuman primates. We present the first experimental evidence of cooperation in a social carnivore, the spotted hyaena, Crocuta crocuta.
PDF Hyenas cooperate, problem-solve better than primates
But Drea's study demonstrates that social carnivores, including dogs, may be very good at cooperative problem ... More information: Cooperative problem solving in a social carnivore, doi:10.1016/j ...
Natural conditions and adaptive functions of problem-solving in the
Physical problem-solving paradigms are popular for testing a variety of cognitive abilities linked with intelligence including behavioral flexibility, innovation, and learning. Members of the mammalian order Carnivora are excellent candidates for studying problem-solving because they occupy a diverse array of socio-ecological niches, allowing researchers to test competing hypotheses on the ...
Hyenas Cooperate, Problem-solve Better Than Primates
But Drea's study demonstrates that social carnivores, including dogs, may be very good at cooperative problem solving, even though their brains are comparatively smaller. ... Cooperative problem ...
16
Cooperative problem solving in a social carnivore. ... Cooperative behavior and social organization of the swallowed-tailed manakin (Chiroxiphia caudate). Behavioral Ecology and Sociobiology, 9, 167 ... Cooperative problem solving in African grey parrots (Psittacus erithacus).
Cooperative problem solving in giant otters
Cooperative problem solving has gained a lot of attention over the past two decades, but the range of species studied is still small. ... Drea CM, Carter AN (2009) Cooperative problem solving in a social carnivore. Anim Behav 78(4):967-977. Article Google Scholar Dunbar RIM (2009) The social brain hypothesis and its implications for social ...
Hyenas cooperate, problem-solve better than p
Drea's research, published online in the October issue of Animal Behavior, shows that social carnivores like spotted hyenas that hunt in packs may be good models for investigating cooperative ...
Social carnivores outperform asocial carnivores on an innovative problem
Figure 2. Innovative problem-solving performance of social species (hyaenas, lions) and asocial species (leopards, tigers). Dark grey bars show the proportion of individuals that successfully opened the puzzle-box on at least one of three trials. Light grey bars show the proportion of individuals that failed to open the puzzle-box within three ...
Hyenas Cooperate, Problem-Solve Better Than Primates
Researchers have focused on primates for decades with an assumption that higher cognitive functioning in large-brained animals should enable organized teamwork. But Drea's study demonstrates that social carnivores, including dogs, may be very good at cooperative problem solving, even though their brains are comparatively smaller.
Cooperative problem solving in rooks
We tested cooperative problem-solving in rooks to compare their performance and cognition with primates. Without training, eight rooks quickly solved a problem in which two individuals had to pull both ends of a string simultaneously in order to pull in a food platform. ... Drea C and Carter A (2009) Cooperative problem solving in a social ...
Social carnivores outperform asocial carnivores on an innovative problem
Semantic Scholar extracted view of "Social carnivores outperform asocial carnivores on an innovative problem" by Natalia Borrego et al. ... this is the first experimental test of and support for cooperative problem solving in lions and lions displayed high tolerance and cooperative success was positively correlated with tolerance. Expand. 10.

Cooperative problem solving in a social carnivore

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Hyenas cooperate, problem-solve better than primates

Hyenas Cooperate, Problem-Solve Better Than Primates

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