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School of Arts & Sciences Theses Hunter College

Summer 8-9-2019

Exploring Innovation and Behavioral Flexibility in African lions (Panthera leo) and snow leopards (Panthera uncia)

Victoria L. O'Connor CUNY Hunter College

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Exploring Innovation and Behavioral Flexibility

in African lions (Panthera leo) and snow leopards (Panthera uncia)

by

Victoria L. O’Connor

Submitted in partial fulfillment of the requirements for the degree of Master of Arts in Animal Behavior and Conservation, Hunter College, The City University of New York

2019

Thesis Sponsors:

August 1 2019 Natalia Borrego, Ph.D. ______Date Signature of First Reader

August 1 2019 Martin Chodorow, Ph.D. ______Date Signature of Second Reader

CARNIVORE BEHAVIORAL FLEXIBILITY 2

Dedication

Mom and Dad- Thank you for encouraging my unwavering passion from an early age and giving

me the best education and opportunities.

Cassie- Thank you for being my best friend and for all of your support and TV appearance

advice.

Derek- Thank you for coming into my life and providing me with all of the love and

encouragement when my path forward didn’t seem so clear.

CARNIVORE BEHAVIORAL FLEXIBILITY 3

Acknowledgments

This thesis became a reality with the kind support and help of many individuals. I would like to extend my sincere thanks to all of them. It truly was a team effort and they were integral to its completion and success.

Firstly, I would like to thank my mentor, Dr. Natalia Borrego for her invaluable guidance, patience and support. Natalia played an incredible role in directing this research from multiple locations and time zones all days of the week, and an even bigger role in advocating for, and uplifting me. Secondly, I would like to thank Dr. Martin Chodorow for his expertise, positivity and care. I count myself extremely lucky to have had their mentorship.

I would also like to thank Dr. Sheila Chase, Dr. Patrick Thomas and Erin Mowatt for their counsel and support. My sincerest gratitude is also extended to the many zookeepers that took time out of their busy schedules to not only run trials, but fill out surveys, prepare food, shift animals and clean the puzzle box.

I would like to thank my friends and colleagues in the Hunter College Animal Behavior and Conservation program, particularly Jenna Pantophlet and Shannon Keeley.

Many thanks and appreciation to all others that encouraged and helped. Without all of your encouragement and support, this dream project would not have been a reality.

CARNIVORE BEHAVIORAL FLEXIBILITY 4

Abstract

Intelligence may have evolved to help animals problem-solve in their physical and/or social environments, which enables them to cope with changes in their environments. Humans can reduce wildlife conflict by understanding how species that face harsh environments assess a situation and alter their behavior. Tests for cognitive behavior aim to formulate clear behavioral criteria for inferring an animal’s mental processes. We designed a custom multi-access puzzle box (MAB) to present a simple and effective behavioral test for exploring innovation in two species, African lions (Panthera leo) and snow leopards (Panthera uncia). Despite being vastly underrepresented in cognitive studies, the order Carnivora, and felids in particular, make an excellent group for studying, species’ abilities to problem solve and innovate. We measured innovation, repeated innovation, persistence, success, contact latency, learning and the exploration diversity of individuals interacting with the MAB. Of the 6 African lions, 5 were able to solve at least one door to the box and of the 9 snow leopards, only 4 were able to solve at least one door. To date, this is the first examination of multi-task problem solving in African lions and the first experimental test of cognition in snow leopards. As expected, persistence significantly predicted success on trials in both species, but significant between subject effects were only found in snow leopards. Our results suggest that species and individuals vary in their problem-solving approaches. Carnivores are particularly susceptible to environmental challenges of human-wildlife conflict, and by understanding their abilities to problem-solve and innovate, we can understand and mitigate conservation issues.

Keywords: Panthera, innovation, problem-solving, multi-access puzzle box, persistence, carnivores, behavioral flexibility

CARNIVORE BEHAVIORAL FLEXIBILITY 5

Exploring Innovation and Behavioral Flexibility in African lions (Panthera leo) and Snow

leopards (Panthera uncia)

Studies of animal cognition, or cognitive ethology, seek to understand animals’ mental experiences. Cognition is multifaceted and can be defined as “all the ways in which animals take in information through the senses, process, retain and decide to act on it”(Shettleworth 2001).

Animal behavior across species suggests that there is a functional awareness of states, processes and actions (Griffin 1976). Behaviors are deemed cognitive when they cannot be explained by simple reflexes or associations (Shettleworth 2001). Cognition encompasses language, social insight, cognitive-mapping, learning, memory, decision-making, problem-solving, and innovation (Breed & Moore 2016) and plays a role in mate choice, foraging, territoriality and many other behaviors (Shettleworth 2001; Rubenstein & Wrangham 2014). Innovation can be defined as “producing a solution to a novel problem or presenting a novel solution to an old problem” (Kummer & Goodall 1985). Innovation is an aspect of an individual’s cognitive abilities that enables them to use resources and their habitat more efficiently. Repeated innovation is the ability of individuals to produce multiple new solutions to a task after those solutions became obsolete (Johnson-Ulrich et al., 2018). It tests whether individuals can adjust their behavior when the physicality of an innovative task changes, which is behavioral flexibility.

Behavioral flexibility is the ability to change one’s behavior in response to a change or novelty in one’s environment.

Cognition has been linked to a species ability to exploit novel resources and adapt to changing environment. By understanding how a species behaves, researchers can mitigate their behavior in their captive environments and in their changing wild environments. Exotic animals have lived in captivity for hundreds of years, with the first zoo emerging in 1828 in London CARNIVORE BEHAVIORAL FLEXIBILITY 6

(Hancocks 1996). The intent of a zoo was to bring exotic species into a foreign area to satisfy human curiosity. However, challenges have persisted in how we care for the animals’ physical and mental health. Stereotypic behaviors (McPhee 2002), lack of enrichment and space (Lyons,

Young & Deag 1997), inability to perform natural behaviors (Dawkins 1988), fecundity (Mason et al., 2009), and poor health and nutrition (Kenny 1998) are just some of the issues plaguing carnivores in captivity. Within zoos, nine carnivores were provided with intact carcasses which significantly decreased their off-exhibit stereotypical behavior (McPhee 2002), and similar studies showed that cats pace more on days when they are not fed (Lyons, Young, & Deag

1997). In another study, providing a natural diet over commercial food in tigers showed significant improvement in their oral health problems (Haberstroh et al., 1984). Many carnivores do not adapt well to captivity and show signs of poor welfare, but there is a lack of research in trying to understand the sources and solutions of these issues. More recently, studies have explored the use of animal cognition in conservation (Berger- Tal et al., 2011; Healy & Rowe

2014), specifically in linking how research on human tolerance (Bostwick et al., 2014), aversion

(Nielsen et al., 2014), fear learning (Griffin, Blumstein & Evans 2000), social learning (Griffin

2004), and adaptability (Hockings et al., 2015) can inform conservation action. A study in 2008 found that mammal species with larger brains tend to be more successful at establishing themselves in novel environments (Sol et al., 2008). Similar results were found in birds. Using more than 600 events, researchers were able to establish that birds with larger brains were better able to establish themselves in novel environments (Sol et al., 2005) and experience lower mortality rates than their smaller brained counterparts (Sol et al., 2007). This is important evidence as it shows that individuals of different species can rapidly develop responses to new challenges. CARNIVORE BEHAVIORAL FLEXIBILITY 7

Cognitive Evolutionary Theories in an Applied Context

Intelligence may have evolved to help animals problem-solve in their physical and/or social environments, which can allow them to cope with changes in their environments. Habitats are shrinking and in order to survive, species can adapt to environmental change via changes in their behavior. Cognition underlies behavior and can assist in understanding behavioral modification as a tool for conservation. Central to behavioral modification is learning, individually and socially. Here, individuals may be more successful at having a healthy adjustment to a new zoo if they are introduced with a known conspecific. Tigers’ and lions’ pacing significantly increases when they are not allowed access to social partners (Bashaw et al.,

2007). This study shows that in both social and asocial species, the presence of a conspecific can alleviate stress in captivity. In addition, social learning, or learning from the behavior of others, encourages adaptation through greater understanding in how factors, such as environmental barriers, can negatively harm animals (Greggor et al., 2014). Individuals that face harsh environments are accustomed to individually assessing a situation and altering their behavior accordingly. A learned association between an area and a prey’s carcass can increase that individual’s behavior in that area, whereas, if the carcass is a conspecific, individuals display learned avoidance and decrease their presence in the area (Swift & Marzluff 2015; Marzluff &

Swift 2017).

By leveraging a species’ response to human presence, human-wildlife conflicts can be reduced (Marzluff & Swift 2017). Already we have seen evidence that some species are able to live in human-altered habitats (Barrett, Stanton & Benson- Amram 2018). Human-altered habitats require species to find new shelter and food resources, deal with new predators and food competitors, develop new navigation strategies, and deal with noises, lights and humans (Barrett, CARNIVORE BEHAVIORAL FLEXIBILITY 8

Stanton & Benson- Amram 2018). In order to adapt to these changing habitats, species have to exhibit cognitive abilities and be flexible in their behavior to meet the demands associated with urban environments. Recent studies on bobcats, coyotes (Tigas, Van Vuren, & Sauvajot 2002), red foxes (Baker et al., 2007) and black bears (Beckman & Berger 2003) provide evidence of species changing their behavior in response to humans. Bobcats and coyotes decreased their activity during daylight hours and moved between land fragments using corridors and culverts indicating that they are avoiding human presence with behavioral adjustments (Tigas, Van

Vuren, & Sauvajot 2002). Similarly, black bears and red foxes were active for fewer daylight hours, significantly increasing their nocturnal hours (Baker et al., 2007; Beckman & Berger

2003). These findings confirm that carnivores are exhibiting behavior flexibility, which is underpinned by cognitive processes, to aid in their survival in disturbed habitats.

By understanding animals’ behavioral flexibility, animal behavior researchers can positively influence conservation management. Managers will more effectively be able to understand human activity, predict disturbances, and make informed management decisions.

However, the specific challenges that favor cognitive abilities, such as abilities associated with behavioral flexibility and innovation, are debated and the evolutionary processes acting on cognition remain unclear. Several hypotheses seek to explain cognitive evolution (see Table 1).

Physical Intelligence Hypothesis

The physical intelligence hypothesis states that advanced cognitive abilities are favored by selective forces in animals’ physical environments, forcing species to learn and adapt (Dunbar

1998). A larger brain, which is more energetically costly (Isler & van Shaik 2009; Striedter

2005) is a sensible solution to species’ ecological problems. A larger brain contains more neurons, which supports the development or modification of new behavioral patterns through the CARNIVORE BEHAVIORAL FLEXIBILITY 9 processing, storage and integration of information (Sol 2008; Herculano- Houzel et al., 2006).

The link between brain size and cognitive abilities has been observed in a number of species including crows and other birds (Garamszegi et al., 2014; Sol et al., 2005; Weir, Chappell &

Kacelnik 2002), fish (Kotrschal et al., 2013), primates (Aiello & Wheeler 1995) and some carnivores (MacLean et al., 2014; Swanson et al., 2012; Vonk & Beran 2012). Ecological demands and challenges posed on all species, including memory issues, navigational challenges, foraging, and shelter, are hypothesized to encourage the evolution of large brains to cope.

MacLean and co-authors (2014) tested 567 individuals of 36 species on cognitive tasks with results indicating that differences in absolute brain volume best predicted performance on these tasks. They suspect that regardless of species, absolute brain size predicts the evolution of cognitive abilities. In a similar experiment on 39 mammalian carnivore species, Benson- Amram,

Dantzer, Stricker, Swanson and Holekamp (2016) found that brain size reflected an animal’s cognitive abilities on a puzzle box task. They found that enhanced problem solving is related to a disproportionally large brain size ratio to body mass. Enlarged brains are adaptive to novel environments as they enable the individual to exhibit flexible behavior in unpredictable environments (Benson-Amram et al., 2016). Evidence of the physical intelligence hypothesis shows higher wild survival rates and flexible behavior patterns as a result of a larger brain.

However, a study in 2009 found that captive-bred big cats generally have reduced brain sizes in comparison to their wild conspecifics, which suggests that an animal’s living condition affects their brain size (Yamaguchi et al., 2009). This finding is crucial in understanding that the past and current zoo environments are not conducive to the successful longevity of large felids, and even more important in the context of potential reintroduction of captive individuals to a wild environment. CARNIVORE BEHAVIORAL FLEXIBILITY 10

Social Intelligence Hypothesis

The social intelligence hypothesis, or the social brain hypothesis, states that the pressures of living in large social networks shaped the evolution of complex cognition. This hypothesis, which developed in the late 1980’s, offered an alternative to the physical intelligence hypothesis.

A large brain is adaptive but can be costly to evolve and maintain. The social intelligence hypothesis predicts that intelligence has sustained due to the demands of navigating the difficulties of a social life (Byrne & Bates 2007; Whiten & Byrne 1988). The more advanced cognitive abilities of conspecific group members can include, but are not limited to, group hunting, cooperative territory defense, and raising young. Social cognition has been defined as

“an individual’s knowledge of their own and other animals’ social interactions and relationships”

(Seyfarth & Cheney 2015, p. 192; Cheney & Seyfarth 1990). Therefore, it can be hypothesized that social relationships are only possible with advanced cognitive abilities.

Sociality has strongly influenced the evolution of intelligence in a number of species but can be specifically seen in primates. In a review of the evidence of intelligence in primates,

Dunbar correlated physical and behavioral evidence (2003). Dunbar found significant correlations using Jerison’s study (1973), which states that primates have a disproportionately large brain for their body size, and behavioral studies which looked at group size and social skills

(Dunbar 1992; Bryne 1995; Lewis 2001). In a more recent study, MacLean and colleagues tested six species of primates and found that their performance on cognitive measures was predicted by their social group size (2013).

More recent studies have sought to generalize this hypothesis about social cognition in other species than primates. Researchers have examined cognition in a number of social species, including elephants (Plotnik et al., 2010), dolphins (McCowan et al., 2000), domestic dogs CARNIVORE BEHAVIORAL FLEXIBILITY 11

(Cooper et al., 2003), ants, bees and fish (Miller 2010). In a study comparing social and asocial carnivores, authors Borrego and Gaines (2016) tested captive lions, leopards, hyenas and tigers on a puzzle box. Lions and hyenas were examined together as the social species, while leopards and tigers were classified as the asocial species. Their results found that the two social species performed significantly better on the task than their asocial counterparts (Borrego & Gaines

2016). If larger brains and greater intelligence in primates evolved due to sociality, then in theory, it could have convergently evolved in social, non-primate mammals.

Understanding how large a role sociality plays in cognitive abilities is important for both captive and wild welfare. In particular, reintroduction of species can be more successful with conspecifics. Between 1995-1997, 41 wolves were released into Yellowstone National Park as part of a reintroduction program (NPS 2019). Wolves, which are social pack animals, were released with conspecifics which presumably eased their reintroduction by having assistance in establishing a territory, finding prey, and rearing young. Their numbers increased from 41 wolves to over 500 wolves today residing in at least 8 different packs (NPS 2019). The cognitive abilities associated with maintaining social relationships and hierarchies encouraged the wolves to quickly establish territories and packs in the vast park. Within captivity, individuals do not have options in choosing mates or packs. Within captive wild dogs, an investigation into their stressors found that the most severe stressor as observed in their adrenocortical response was that of unresolved relationships in groups of individuals held in adjacent cages (De Villiers et al.,

1997). In a study on captive brown bears, 66 bears exhibited varying stereotypic behavior when kept with related and unrelated conspecifics (Montaudouin & Le Pape 2005). The extent to which sociality affected cognitive abilities has yet to be fully investigated. By understanding the CARNIVORE BEHAVIORAL FLEXIBILITY 12 social requirements, and the intelligence of social and asocial species, we can improve housing and management for carnivores in captivity.

Emotional Reactivity Hypothesis

The emotional reactivity hypothesis states that social constraints associated with social interactions and temperament can affect cognitive evolution (Borrego & Dowling 2016; Hare &

Tomasello 2005a). Specifically, individuals in hierarchical living, who suffer from rank-related aggression as submissive members of a social society, may suffer and have limited cognitive development. Evidence is seen for this hypothesis in chimpanzee society. As social animals, chimpanzees are forced to cooperate with conspecifics. However, they require social criteria and inter-individual tolerance; in studies, submissive chimpanzees will only cooperate on a task if dominants are out of reach, and they can share food (Melis, Hare & Tomasello 2006). Similar evidence comes from the exploration of wolves and dogs. Comparative studies on these closely related species suggest that social skills evolved because of selection by emotional systems (Hare

& Tomasello 2005a). In a study looking at domestic dogs, researchers found that they have unusually high social skills that evolved as a result of systems mediating fear and aggression towards humans (Hare & Tomasello 2005b). While still a newer theory, the emotional reactivity hypothesis provides more insight into the possibilities of the evolution of cognition; hopefully, further studies in a variety of species can see the effect temperament has on development.

As previously stated, captive settings control putting conspecifics together. Within large carnivores, pairing individuals for mating can be based solely on genetic diversity and zoo location without taking into account temperament and hierarchy. In male tree shrews, the submissive animals exhibit high levels of stress, changing their behavior to avoid conspecifics, food and water (von Holst 1986). They also decrease their allogrooming and increase their CARNIVORE BEHAVIORAL FLEXIBILITY 13 locomotion, avoiding the dominant (von Holst 1986). Within the wild, individuals in packs or prides may have the opportunity to leave the group, or more room to avoid conflict. The close proximity and sharing of resources in captivity can cause unnecessary stress on individuals lower in the hierarchy. Additionally, many females, naïve to the experiences of mating and young- rearing they would see in the wild, reject or harm their young. Hand-rearing is a way that zoological institutions combat female inexperience by raising the offspring with humans for as long as necessary. However, hand-reared tigers, snow leopards and male cheetahs and female clouded leopards produce fewer offspring than parent-reared individuals (Hampson & Schwitzer

2016). The same study found that hand-reared snow leopard females reproduce later in life, hand-reared female tigers lived shorter lives and infant mortality was lower in tigers and male snow leopard cubs (Hampson & Schwitzer 2016). This study is important for conservation as it provides evidence against captive raising for reintroduction, and it provides information against hand-rearing in captivity. The loss of an emotional bond has direct physical consequences for an individual including behavioral problems, reduced copulation and lower breeding success

(Hampson & Schwitzer 2016). Presumably, these young are not raised with the necessary social interactions to form their role in the group, and they are not managed by the adults for unruly temperaments.

Cultural Intelligence Hypothesis

Another hypothesis in its infancy, the cultural intelligence hypothesis states that social learning favored the evolution of cognition abilities more than individual learning (Reader,

Hager & Laland 2011). It is important to note that social learning is not only more efficient by this theory, but that it is necessary for individuals in practice to acquire skills. These social interactions have special properties that select for this intelligence, not general intelligence (Frith CARNIVORE BEHAVIORAL FLEXIBILITY 14

& Frith 2003). By this theory, individuals would test well on social tests, but not asocial tests as this theory only encourages greater ability in relation to tasks that focus on social learning mechanisms, culture and social living. Humans are an example of this theory at its core; human cognition has evolved to specifically adapt to the acquisition of cultural knowledge (Boyd &

Richerson 2005; Reader, Hager & Laland 2011). There is a surplus of early-rearing studies that show how important a caretaker-young bond is. Menzel and colleagues (1970) found that wild- born chimpanzees were better at tool-use than their captive-born and abnormally reared conspecifics. In a comprehensive study, researchers gave several cognitive battery tests to humans, chimpanzees and orangutans. Supporting this hypothesis, human children and young chimpanzees have similar cognitive physical skills, like spatial memory, but humans had better cognitive skills, like social learning, than their ape counterparts (Herrmann et al., 2007). This acquisition of behavior at a young age encourages expression in adult life.

This notion is common in zoo, or other captive facilities. Captivity, and in particular raising young in captivity can affect an animal’s ability to function in the wild (O’Regan &

Kitchener 2005). Issues include inability to locate resources, inability to recognize or flee from predators, inability to find suitable shelter and other necessary resources. For example, once released into the wild, the golden lion tamarin lost the ability to successfully maneuver the environment (Menzel & Beck 2000). In a review on carnivores, researchers found that on average only 30% of released carnivores survive (Jule, Leaver & Lee 2008). Animals in captivity usually do not have the natural cognitive behaviors needed to survive in the wild. The “culture”, which includes social interaction and learning of specialized skills at a young age, especially from a close mother- young bond is necessary for individuals to survive in challenging environments (Holekamp & Benson- Amram 2017). CARNIVORE BEHAVIORAL FLEXIBILITY 15

Table 1. Evolutionary theories for the evolution of cognitive abilities Evolutionary Description Species Source Study Expectation Theory Examples Physical Environments Apes, monkeys, Dunbar 1998 Snow leopards intelligence make species lemurs, rodents, would do just as more cognitively carnivores, well as, or better advanced elephants and than African lions birds Social Sociality makes African lions Byron & African lions would intelligence species more Bates 2007 do better than snow cognitively leopards advanced Emotional Temperament Chimpanzees Hare & African lions will reactivity and ranking and dogs Tomasello show variability affects cognition (compared to 2005 because of wolves) dominance hierarchy while snow leopards will be relatively similar Cultural Social learning Humans and Whiten & van Individuals raised intelligence makes species dogs Schaik 2007 in the wild, or by more cognitively their own mothers advanced in captivity would do better

Puzzle Boxes

Puzzle boxes present a simple and efficient behavioral test for exploring behavioral flexibility, problem-solving, innovation, motor diversity and learning in a variety of species

(Chance 1999; Bloomstrand et al., 1986). Puzzle boxes allow researchers to present animals with a novel problem and measure the variation in approaching to and solving that problem.

Multi-access puzzle boxes (MABs) present a simple and effective behavioral test for exploring innovation and problem-solving (Borrego & Gaines 2016; Borrego 2017; Chance

1999). MABs test innovation by requiring subjects to solve a novel problem and then use new solutions after past solutions become inaccessible. MAB studies assess whether species can produce new solutions to a task after old ones become obsolete, assessing the subjects’ inhibition to refrain from using responses that no longer function. Currently, studies using multi-access are CARNIVORE BEHAVIORAL FLEXIBILITY 16 heavily based on birds (Auersperg et al., 2011; Biondi, Bo, & Vassallo 2012; Bokony et al.,

2013; Boogert et al., 2008; Griffin & Diquelou 2015; Morand- Ferron & Quinn 2011), with few studies on mammals [monkeys (Day et al., 2003; Kendal et al., 2005), great apes (Manrique,

Volter & Call 2013), meerkats (Thornton & Samson 2012) and hyenas (Johnson-Ulrich,

Johnson- Ulrich & Holekamp 2018)].

One study exploring behavior with a multi-access puzzle box in great apes indicated significant flexibility in problem-solving (Manrique, Volter & Call 2013). The apparatus was accessible using three different solutions: (1) inserting a finger in the front hole, (2) lifting the bottom of the apparatus up to insert the finger in the middle hole, and (3) shooting the bottom of the apparatus up to launch the grape out of the hole at the top. Three of the four species were able to solve all of the apparatus problems; more importantly, they invented new solutions when necessary and abandoned responses that no longer worked (Manrique, Volter & Call 2013).

Another study used an apparatus to successfully test problem-solving in raptors (Biondi, Bo, &

Vassallo 2012). Using a clear plexiglass box, researchers tested four solutions: (1) lifting, (2) pushing, (3) pulling the lid and (4) sliding the lid. Subjects varied in their performance but showed some success in solving a novel problem (Biondi, Bo, & Vassallo 2012). Recently, researchers tested 10 captive hyenas on a MAB paradigm, and they found that they were highly innovative (Johnson-Ulrich, Johnson- Ulrich & Holekamp 2018). When examining individuals, researchers found that a behavioral syndrome, which consisted of persistence, motor diversity, activity and neophobia, predicted repeated innovation. These results are extremely important in examining successful innovation as a means to better understand the cognitive abilities of carnivores. CARNIVORE BEHAVIORAL FLEXIBILITY 17

In a more relevant study, researchers presented puzzle boxes to 140 individuals, of 39 species from the order Carnivora to understand whether brain size is associated with puzzle box success (Benson- Amram et al., 2016). No significant differences between social and asocial species were detected, but both snow leopards and African lions were successful in opening the puzzle box. A subsequent study sought to narrow in on the differences of cognition in differing sociality levels. A positive connection between sociality, persistence and innovation was determined when lions, tigers, hyenas and leopards were tested on a puzzle box task (Borrego &

Gaines 2016). Most significantly, the social carnivores, particularly the lions, outperformed their asocial counterparts.

Cognition in Carnivores

Despite being underrepresented in cognitive studies, the order Carnivora makes an excellent group for studies of social and physical intelligence hypotheses. Carnivores offer a socially, ecologically and morphologically diverse model (Ewer 1973; Bekoff et al., 1984).

Within in the order, felids are highly specialized carnivores whose behavior is influenced by a number of ecological constraints including hunting cover, climate, potential competitors and prey behavior (WCS 2019). Predation is affected by prey abundance, distribution, size, defenses and anti-predator tactics (Sunquist & Sunquist 1989). Members of the order Carnivora, family

Felidae, and genus Panthera, Snow leopards (Panthera uncia) and African lions (Panthera leo) provide excellent models to evaluate cognitive abilities of felids. Within the Carnivora phylogenetic tree, they share a pattern of lineage divergence and share the closest living relative estimated between1.5- 3.5 million years ago (Flynn 1996). Both species face ecological challenges and, presumably, benefit from cognitive abilities facilitating the successful navigation CARNIVORE BEHAVIORAL FLEXIBILITY 18 of these challenges. In the current study, they serve as the best species to examine cognition in two species that face increasingly changing and complex environments.

Snow leopards (Panthera uncia)

Snow leopards are typically found in dry, rocky, alpine terrain in Central Asia within twelve countries: Afghanistan, Bhutan, China, India, Kazakhstan, Kyrgyzstan, Mongolia, Nepal,

Pakistan, Russia, Tajikistan and Uzbekistan (McCarthy et al., 2017). They are solitary carnivores with a diurnal, arrhythmic activity pattern (Gittleman 1989; Jackson & Ahlborn 1984). They are highly endangered in every region they inhabit with a rapidly decreasing population estimated between 3,920-6,390 (McCarthy et al., 2017; IUCN 2019). Population numbers are difficult to measure due to their secretive nature and the remote terrain they inhabit. Snow leopards maintain small, exclusive home ranges that overlap with conspecifics (Eisenberg & Lockhart 1972;

Jackson & Hillard 1986). Snow leopards only associate for mating, young-rearing and territory disputes (Jackson 1996). Females own home ranges that grow and shrink in relation to reproductive status and cub-rearing, with males overlapping on multiple female territories; the general size of territories is dependent on abundance of prey in the area (Jackson 1996;

Seidensticker et al., 1973; Seidensticker 1977). A significant amount of pressure is placed on this solitary mammal as daily life activities, such as travel, young-rearing, territory-guarding and hunting, are extremely difficult. A higher level of cognitive ability may facilitate problem- solving within their harsh environment on a daily basis.

African lions (Panthera leo)

African lions live, forage, and rear young as familial prides in open grasslands and woodlands in sub-Saharan Africa (Gittleman 1989). Lion populations are declining with an estimated population of 7,500 in a total of 24 countries: Angola, Benin, Botswana, Burkina Faso, CARNIVORE BEHAVIORAL FLEXIBILITY 19

Cameroon, Central African Republic, Chad, The Democratic Republic of the Congo, Ethiopia,

Kenya, Malawi, Mozambique, Namibia, Niger, Nigeria, Senegal, Somalia, South Africa, South

Sudan, Sudan, Swaziland, United Republic of Tanzania, Uganda, Zambia and Zimbabwe (Bauer et al., 2016). High, female- centric densities of lions reside in large territories guarded by male coalitions (Packer, Scheel & Pusey 1990; Grinnell, Packer & Pusey 1995); these groups, or prides, consist or four to six adults (Bauer et al., 2016). Their cooperative hunting allows them to take down prey larger than themselves (O’Brien et. al. 1987; Stander 1992). Social activities such as group hunting and territory guarding require higher level cognitive abilities including communication and navigating social ranks. In a long term 38-year study on wild African lions, it was determined that sociality confers a numerical advantage in territory defense and defense of young, which the authors argued as the prime benefit of group living in lions (Mosser & Packer

2009). As the only social Felidae species that occupies a territory containing two other large cat species, African lions represent a unique case to understand how social and ecological challenges select for problem solving flexibility and innovation.

Testing for Cognition

Advanced cognitive abilities have been documented throughout taxa in the animal kingdom. Researchers have examined cognition in mammals (Jolly 1966; McCowan et al.,

2000), birds (Taylor et al., 2014; Pepperberg 1983), reptiles (Burghardt 1991), fish (Schuster et al., 2006) and invertebrates (Mather 1995). Tests for cognitive behavior try to formulate clear behavioral criteria for inferring an animal’s mental processes. Different testing approaches provide insight into the mental lives and abilities of animals.

In this study, we focus on two aspects of cognition: problem-solving and innovation.

Problem-solving is simply finding solutions for difficult issues. Innovation can be defined as the CARNIVORE BEHAVIORAL FLEXIBILITY 20 ability to invent new behaviors to solve old problems or use pre-existing behaviors to solve new problems (Reader & Laland 2003; Griffin & Guez 2014). In an ever-changing world, the ability for species to problem-solve and innovate allows them to succeed and adapt.

Cognition associated with problem solving and innovation has been linked to species richness (Nicolakakis, Sol, & Lefebvre 2003) and a species’ ability to exploit novel resources and adapt to changing environment (Reader & Laland 2001).Carnivores are particularly susceptible to habitat loss, parasites and diseases, hunted for sport, and the victims of human- wildlife conflict (MacDonald 2016; MacDonald, Loveridge & Rabinowitz 2010). By understanding how a species behaves, we can understand and mitigate the conservation issue.

For example, in order to remain effective hunters, African lions must rotate between watering holes where their prey will be located. However, with habitat fragmentation, the number of watering holes within a home range varies, making it dangerous to leave a territory (Macdonald

2016; Loveridge et al., 2009; Valeix, Loveridge, Macdonald 2012). Similarly, observed intraspecific differences in the behavior of leopards affect their vulnerability to trophy hunters.

Adult leopards are equally likely to encounter hunters, but subadults rarely encounter hunters

(Macdonald 2016; Braczkowski et al., 2015). Human behavior has affected leopard behavior enough to have generational behavioral consequences.

Hypothesis, Objectives and Predictions

This study examined behavioral flexibility and the innovative abilities of African lions

(Panthera leo) and snow leopards (Panthera uncia) on a custom multi-access puzzle box.

Cognition testing is important for both captive welfare and conservation practices. For African lions and snow leopards, their changing environments and vulnerable statuses are important factors for behavioral flexibility research. In addition, their captive welfare needs are largely CARNIVORE BEHAVIORAL FLEXIBILITY 21 unknown as very little research has been conducted on their mental needs. The aim of this study is to examine behavioral flexibility within one genus to better understand these species’ behavioral responses to changing environments, particularly in the face of increasing anthropogenic pressures. An exploration of cognition within species can help determine which challenges affect their conservation and zoo welfare.

Based on the problem-solving performance of African lions in previous studies, we predict that lions will demonstrate problem-solving by successfully opening at least one solution of the task. Based on the performance of other closely-related species (i.e. African leopards), we also expect snow leopards to solve at least one solution to the multi-access box.

We will examine potential links between a variety of behavioral traits linked to problem- solving success. There has been evidence that motor flexibility is involved in innovation (Griffin

& Guez 2014). Behavioral diversity positively correlates with successful problem solving

(Johnson-Ulrich, Johnson-Ulrich, & Holekamp ,2018; Daniels et al., 2019), tool use (Lefebvre et al., 2002) and physical manipulation while foraging (Boinski et al., 2000). Persistent individuals are more likely to solve given tasks (Benson-Amram et al., 2016), and less neophobic individuals can be more successful than their high neophobic counterparts (Griffin & Guez 2014). Inhibitory control, the ability to resist a previously used behavior that will no longer produce a reward, is strongly correlated with innovative success in some species (Manrique et al., 2013; Johnson-

Ulrich, Johnson- Ulrich, & Holekamp 2018).

We predict that greater exploratory diversity will be associated with more successful problem-solving and solutions attained; the perseverance of an animal, and a greater score of exploration diversity, will increase the animal’s success rate. Additionally, we expect latency to success to be related to success and repeated innovation. To date, this will be the first CARNIVORE BEHAVIORAL FLEXIBILITY 22 examination of multi-task problem solving in African lions and the first experimental test of cognition in snow leopards.

Methods

Subjects

This study includes African lions (n= 6) and snow leopards (n = 9) from The Bronx Zoo and The Turtleback Zoo (see Table 1). All subjects were born in captivity, with the exception of one snow leopard (Leo), who was rescued from the Naltar Valley of northern Pakistan. Four of the lions (Thulani, Ime, Bahati, and Amara) were the offspring of a female test subject (Sukari).

One of the male snow leopards (Willie) was the offspring of a male test subject (Leo), and one of the female snow leopards (Khyber) was the offspring of two of the other subjects (K2 and

Willie). At the time of the study, the Bronx Zoo subjects were housed individually, or in social groups off- exhibit and the Turtleback Zoo subjects were housed with conspecifics off-exhibit

(see Figures 1-4).

CARNIVORE BEHAVIORAL FLEXIBILITY 23

Table 1. Descriptive information for the subjects in the study

Name Sex Age Location Years at the (years) Zoo African lions Thulani M 5 Bronx Zoo 5 Ime M 5 Bronx Zoo 5 Bahati M 5 Bronx Zoo 5 Demarcus M 4 Turtleback Zoo 2 Sukari F 15 Turtleback Zoo 2 Amara F 5 Turtleback Zoo 2 Snow leopards Tanja F 18 Bronx Zoo 5 MJ M 2 Bronx Zoo 1 Willie M 5 Bronx Zoo 5 Leo M 13 Bronx Zoo 12 Mike M 4 Bronx Zoo 4 K2 F 8 Bronx Zoo 4 Khyber F 1 Bronx Zoo 1.5 Chameli F 6 Turtleback Zoo 2 Gala M 4 Turtleback Zoo 2

Housing and Husbandry

The Bronx Zoo African lions were tested individually in their normal indoor holding enclosures, each measuring 8’ x 10’ (see Figure 1). The multi-access puzzle box was attached to the back wall (see Figure 1). The indoor testing enclosures included a raised platform attached to the back wall, a water dispenser on the front right, and enrichment objects, including tree stumps and boomer balls. The ground surfaces and walls of the enclosures were concrete. The Bronx

Zoo snow leopards were tested in their normal outdoor holding enclosures, measuring 17’ x 22’ CARNIVORE BEHAVIORAL FLEXIBILITY 24 x 8’ and 16’ x 17’ x 8’ (see Figure 2). Within the enclosures was a 1.22 x 2.44-meter den and a raised platform. The ground surfaces of the enclosures were dirt and screening, and the walls were welded metal box wire fencing with Guillotine doors, which were used for all Bronx Zoo animal entry and exit. The Bronx Zoo African lions and snow leopards were fed six days a week, with one fasting day. Water was available at all times.

Guillotine Door (behind metal box feeder in picture)

Figure 1. The Bronx Zoo African lion indoor, off-exhibit enclosure and testing area CARNIVORE BEHAVIORAL FLEXIBILITY 25

Guillotine Door (out of picture range)

Figure 2. The Bronx Zoo snow leopard outdoor, off exhibit enclosure and testing area

The Turtleback Zoo African lions were tested in one indoor holding enclosure, measuring

12’ x 12’ (see Figure 3). The puzzle box was attached to the back wall. Within the enclosure were a raised platform attached to the side wall, a water dispenser on the front right, and enrichment objects. The ground surface and walls of the enclosure were concrete, and the enclosure door was metal mesh. The Turtleback Zoo snow leopards were tested in their normal indoor holding enclosures, each measuring 7’6” x 11’8” (see Figure 4). The ground surface and walls of the enclosure were concrete, and the enclosure door was metal mesh. Guillotine doors were used for all animal entry and exit. Turtleback Zoo African lions and snow leopards were CARNIVORE BEHAVIORAL FLEXIBILITY 26 fed six days a week, with one fasting day. Water was available at all times. Turtleback Zoo

African lions and snow leopards were housed with conspecifics at all times.

Guillotine Door

Figure 3. The Turtleback Zoo African lion indoor, off- exhibit enclosure and testing area

CARNIVORE BEHAVIORAL FLEXIBILITY 27

Guillotine Door

Figure 4. The Turtleback Zoo snow leopard indoor, off-exhibit enclosure and testing area

Apparatus

The custom multi-access puzzle box was a molded Starboard box with a stainless-steel frame measuring 2’ x 2’ x 2’ (see Figures 5-7). The box was accessible via three separate solutions:

Solution 1 (Push Door Technique) The box could be opened by pushing on a spring- loaded door with hinges inside of the box. When pressure was applied to the door, the door swung down flat into the box (see Figure 5). CARNIVORE BEHAVIORAL FLEXIBILITY 28

Solution 2 (Pull Rope Technique) A spring-loaded latch held a hinged door closed. A detachable rope was attached to the latch. In order to open the door, the subject could grasp the rope and pull away from the box at a 180o angle. Pulling the latch in the correct direction by rope triggered the door to open (see Figure 6).

Solution 3 (Pull Door Technique) The box could be opened by pulling down a door on the side of the box. A lip at the top of the door was pulled down to open the entire side of the box. Hinges were attached along the base of the door to create resistance to open the door. The door was also held to the box frame with waterproof magnets. This encouraged the cats to apply a substantial amount of pressure to open the door (see Figure 7).

Figure 5. The multi-access puzzle box showing the open push door technique, or solution 1 which was opened by pushing the door allowing for access to the food reward.

CARNIVORE BEHAVIORAL FLEXIBILITY 29

Figure 6. The multi-access puzzle box showing the pull rope technique, or solution 2 which swung open by pulling the rope exposing the inside of the box.

Figure 7. The multi-access puzzle box showing the open pull door technique, or solution 3 which pulls down flush to the ground, exposing the entire inside of the box.

CARNIVORE BEHAVIORAL FLEXIBILITY 30

Experimental Design

Data were collected from October 2018 through February 2019 at The Bronx Zoo in

Bronx, New York and from March 2019 through April 2019 at The Turtleback Zoo in West

Orange, New Jersey. The custom puzzle box was given to each of the subjects in the morning between 830-1200hours and the behavior of each subject was recorded for a maximum of 15 minutes. The box was baited with a food reward and placed in the subject’s testing enclosure against the back wall while the focal subject was physically and visually away from the testing area in a separate indoor enclosure. The food rewards were part of the everyday diet and were chosen by the zookeepers and staff. The reward items included shank bones, chicken breasts, and

Nebraska feline diet. The focal subject was then released into the testing enclosure via the

Guillotine doors (Figures 1-4).

The number of videos per subject was dependent upon the subject’s number of trials, one video per trial. Trials were videotaped with a Sony Handycam by either Victoria O’Connor or

Dr. Patrick Thomas. Cameras were set on the outside of the enclosure capturing a view of the testing enclosure. Dr. Thomas and staff were present but out of visual sight for all Bronx Zoo trials. Erin Mowatt, Director of Animal Operations at The Turtleback Zoo, staff and Victoria

O’Connor were present but out of visual sight for all Turtleback Zoo trials.

The puzzle box was left unbolted in the snow leopards’ enclosures, but due to safety concerns, zoo staff required that the box be bolted to the middle of the enclosure’s back wall for the lion trials. A food reward was placed inside the box and was accessible via three solutions, as described above. The puzzle box was cleaned and disinfected between different species’ trials.

Subjects were given a series of three conditions that were dependent on their performance in the preceding condition(s). Conditions followed the standard protocol of similar studies CARNIVORE BEHAVIORAL FLEXIBILITY 31

(Biondi, Bo & Vassallo 2010; Johnson-Ulrich, Johnson-Ulrich & Holekamp 2018); each condition was defined by a set of trials in which subjects were allotted five trials and 15 minutes per trial to successfully open the puzzle box. A subject either failed a condition, which was defined as failing to open the box in three out of five trials, or succeeded in a condition, which was defined as opening the box in three out of five trials. Subjects that succeeded moved on to the next condition. Subjects that failed did not advance to the next condition and testing was discontinued.

Subjects underwent one trial per day. The trial began when the subject made physical contact with the puzzle box. Trials ended when the subject opened the puzzle box (a successful trial) or after 15 minutes elapsed without the subject opening the puzzle box (a failed trial). At the end of each trial, the subject was shifted to an adjacent enclosure according to the zoos’ procedures.

Condition 1 (5 trials): The meat reward inside was retrievable via any of the solutions; all three doors were unlocked at the start of the first trial. Once a subject achieved their first successful trial, the door that they opened remained unlocked and the other two doors were locked for the remainder of the first condition. Three successful trials out of a possible five advanced the subject to the next condition. Condition 2 (5 trials): The remaining two unsolved doors were unlocked at the start of the first trial. Once a subject succeeded in opening an unlocked door, that door remained unlocked and the other two doors were locked for the remainder of the second condition. Three successful trials out of a possible five advanced the subject to the final condition. Condition 3 (5 trials): Only the remaining unsolved door was unlocked, and the subject was given five trials in which to open it three times.

CARNIVORE BEHAVIORAL FLEXIBILITY 32

Behavioral assays

We used the following measures to examine problem solving and innovation (see Table

2): (1) Persistence, (2) Success, (3) Contact Latency, 4) Success latency, (5) Repeated

Innovation, (6) Number of trials to repeated success, (6) Innovative Behavior-2, (7) Innovative

Behavior-3, (8) Inhibitory Behavior-1, (9) Inhibitory Behavior-2, (10) Inhibitory Behavior-3,

(11) Exploration Diversity. Contact latency was determined when the animal was making contact with the box through the video analysis. In order to account for the possibility that the subject was not making direct contact, though debatable in the video, an approach distance of 2 inches was also used to account for this possibility due to the location and clarity of the video camera.

CARNIVORE BEHAVIORAL FLEXIBILITY 33

Table 2. Summary of behavioral assays used in analysis.

Measure (level) Definition

Persistence (trial) Ratio of time spent actively working on the box to total trial time (Borrego & Gaines ,2016); actively working on the box is spending time making physical contact with the box, or within two inches of the box Trial: success (opening the box) or failure on a given trial. Success (trial) Subject: ratio of successful trials to total trials Success (subject) Contact Latency (trial) Time from entering testing enclosure until the subject makes contact with or approaches within 2 inches of the box (Griffin & Guez 2014; Johnson-Ulrich et al., 2018) Success Latency (trial) If successful, time taken to open the box from the contact latency start (Johnson-Ulrich et al., 2018) Repeated Innovation Score of 0-3 indicating the number of solutions learned (Johnson-Ulrich et al., 2018) (subject) Number of Trials to Number of trials before at least two successful trials in a row (0= success on first trial; 1= Repeated Success success on second trial; 2= success on third trial; 3= success on fourth trial; 4= no success) (condition) Innovative Behavior-2 Time spent working on previously unsolved, unlocked doors in Condition 2, up to and (condition) including first successful trial in condition 2 Innovative Behavior-3 Time spent working on previously unsolved, unlocked door in Condition 3, up to and including (condition) first successful trial in condition 3 Inhibitory Behavior-1 Time spent working on locked doors in Condition 1, after the first successful trial in condition (condition) 1 (Johnson-Ulrich et al., 2018) Inhibitory Behavior-2 Time spent working on locked, solved door(s) in Condition 2 (condition) Inhibitory Behavior-3 Time spent working on locked, solved door(s) in Condition 3 (condition) Exploration Diversity Score of 0-6 representing the level of exploration of a subject; the more behaviors present, the (trial) higher the score (Benson-Amram et al., 2013; Borrego & Gaines 2016). Behaviors included: circling’, ‘pawing on top’, ‘pawing at sides’, ‘biting/licking’, ‘stalking’, and ‘standing on top’

Reliability

Victoria O’Connor analyzed all videos, and a 20% random sample of the videos were re-

analyzed by another observer trained to test for reliability. One behavioral measure, “contact

latency”, was analyzed by a third observer for accuracy.

Statistical Analyses

This study examines carnivore cognition using a multi-access puzzle box to test

innovation. Multi-access puzzle boxes assess species’ ability to produce solutions to a task, to

examine their behavioral flexibility. Behavioral flexibility, including the important ability to alter CARNIVORE BEHAVIORAL FLEXIBILITY 34 behavior in changing environments, determines the likelihood that new behaviors will arise in natural or testing situations (Manrique et al., 2013). In study sites, we tested six African lions

(Panthera leo) and nine snow leopards (Panthera uncia). Of those individuals, five African lions and four snow leopards were successful at meeting the criterion of Condition 1.

The presence and duration of all behaviors were extracted from video collection. Data were analyzed using SPSS v. 25 software for Macintosh. Results were considered significant when p < 0.05. African lions and snow leopards were treated as separate based on species.

Wilcoxon Rank Sum tests were performed on African lions and snow leopards to determine whether sex, or zoo location (Turtleback Zoo or Bronx Zoo) predicted success.

A paired samples t-test was used to examine whether working time and success latency significantly differed across trials. Success latency was compared between the first and second successful trials, the second and third successful trials and the first and third successful trials. We predicted that success latency would decrease between trials within a condition, indicating that subjects were learning how to open the box faster.

To mitigate the effects of non-normal distributions and small sample sizes, we also used non-parametric tests. To assess behavioral assays, we examined bivariate correlations using

Kendall’s tau. We used several measures in analyzing by-trial and by-subject differences. Snow leopards were the only species to exhibit all six of the exploratory behaviors; no African lion was observed ‘stalking’ the MAB. Interestingly, Borrego & Gaines (2016) observed African lions exhibiting more exploratory behaviors than their African leopard counterparts, but stalking behavior was not a behavior used in that study.

As a way to measure response reliability on the behavioral assays, one-way analyses of variance, or ANOVAs, using subjects as a fixed effect were conducted to compare variance CARNIVORE BEHAVIORAL FLEXIBILITY 35 between subjects to variance within subjects. Three specific behavioral assays were used for further analysis based on their significance in other studies (Borrego & Gaines 2016; Johnson-

Ulrich, Johnson-Ulrich & Holekamp 2018): ‘Persistence’, ‘Contact Latency’ and ‘Exploration

Diversity’. For each of these assays, we built a logistic generalized estimating equation (GEE) model to predict trial success. Each model included subjects as a random effect and one of three behavioral assays (‘Persistence’, ‘Contact Latency’ and ‘Exploration Diversity’) as a fixed effect.

Results

African lions

Of the six African lions that were tested on the multi-access puzzle box, one did not reach criterion (3 successful trials out of 5) on condition 1 (16%), three reached criterion for condition

1 (50%), one reached criterion for condition 2 (16%), and one reached criterion for condition 3

(16%).

Door 1, the push in door, was opened in 4 out of the 8 successful conditions (50%) and was opened first by two subjects. Door 3, the pull-down door, was opened in 3 out of the 8 successful conditions (37.5%) and was opened first by three subjects. Door 2, the pull rope door, was opened by only one subject (12.5%).

Success did not depend on sex (Wilcoxon Rank Sum test: Z= -0.577, p= 0.564), or zoo location (i.e. Turtleback Zoo or Bronx Zoo; Wilcoxon Rank Sum test: Z= -1.00, p= 0.317).

In conditions that African lion subjects reached criterion, time to success was significantly lower between the second successful trial and the third successful trial (t(7)=

3.034, p= 0.019; M= 77.75, SD= 72.484; Figure 8), but there was no significant difference between the first successful trial and the second successful trial (t(7)= -0.537, p= 0.608; M=- CARNIVORE BEHAVIORAL FLEXIBILITY 36

60.00, SD= 316.049) or the first successful trial and third successful trial (t(7)= 1.355 p= 0.218;

M= 137.75, SD= 287.555).

Figure 8. Learning curves for individual African lions across trials. Success latency was the time to open the MAB from the trial start. The number on the graph represents the door opened. A condition is solved once an individual opens a door in 3/5 trials. ‘Thulani’ was the only African lion not successful in meeting criterion for Condition 1. ‘Ime’, ‘Bahati’, and ‘Demarcus’ met criterion for Condition 1, but failed to meet criterion for Condition 2. ‘Sukari’ met criterion for

Conditions 1 and 2, but failed to meet criterion for Condition 3. ‘Amara’ met criterion for all three Conditions. CARNIVORE BEHAVIORAL FLEXIBILITY 37

Behavioral assays were measured at both the trial and subject levels for successful and unsuccessful individuals, where successful individuals were those that met criterion for

Condition 1, and unsuccessful individuals were those subjects that did not meet criterion on

Condition 1. Five out of six African lions were successful at meeting criterion for Condition 1

(Table 3). ‘Thulani’ was the only unsuccessful subject.

Table 3. Means and standard deviations for the behavioral measures of both successful and unsuccessful African lions. As there was only one unsuccessful individual, that individual’s SDs were not included in the table.

Successful (n=5) Unsuccessful (n=1) Mean SD Mean SD Persistence 0.387 0.274 0.340 NA Contact Latency 9.561 21.624 21.000 NA Success Latency 115.192 169.024 39.875 NA Exploration Diversity 2.781 0.245 2.25 NA Success 0.622 0.488 .630 NA Number of Trials to Repeated Success 2.400 0.962 2.500 NA Number of Solutions 0.634 0.488 1.00 NA

To assess the behavioral assays and their degree of independence, we examined the bivariate correlations between the trial-level measures persistence, contact latency, success latency, and exploration diversity using Kendall’s tau (see Table 4). The only significant correlation was between success latency and exploration diversity (rТ = 0.313, p < 0.05; see

Figure 9).

CARNIVORE BEHAVIORAL FLEXIBILITY 38

Table 4: Correlations based on trial measures

Persistence Contact Success Exploration Latency Latency Diversity Persistence 1.00 -.011 -.166 .075 Contact Latency 1.00 -.089 -.115 Success Latency 1.00 .313* Exploration Diversity 1.00 Rank Correlation Matrix of four trial-level behavioral measures; * p < 0.05, ** p< 0.01

Figure 9. Trial-level success latency as a function of exploration diversity in African lions (p <

0.05)

We also examined the bivariate correlations between the subject-level measures persistence, contact latency, success latency, exploration diversity, number of trials to repeated success and number of solutions (see Table 5). Contact latency was negatively correlated with exploration diversity (rТ = -1.00, p < 0.01; see Figure 10). Number of trials to repeated success was negatively correlated with number of solutions (rТ = -.775, p < 0.05; see Figure 11) and positively correlated with success latency (rТ = .867, p < 0.05; see Figure 12) CARNIVORE BEHAVIORAL FLEXIBILITY 39

Table 5: Correlations based on subject means

Persistence Contact Success Exploration Number Number Latency Latency Diversity of Trials of to Solutions Repeated Success Persistence 1.00 -.200 -.333 .200 -.467 .602 Contact 1.00 -.467 -1.00** -.333 .086 Latency Success 1.00 .467 .867* -.602 Latency Exploration 1.00 .333 -.034 Diversity Number of 1.00 -.775* Trials to Repeated Success Number of 1.00 Solutions Rank Correlation Matrix of six subject-level behavioral measures; * p<0.05, ** p<0.01,

Kendall’s tau rank correlation

CARNIVORE BEHAVIORAL FLEXIBILITY 40

Figure 10. Negative correlation of the subject-level measures contact latency and exploration diversity (p < 0.01)

Figure 11. Subject-level number of solutions as a function of trials to repeated success (p < 0.05) CARNIVORE BEHAVIORAL FLEXIBILITY 41

Figure 12. Subject-level Success Latency as a function of number of trials to repeated success (p

< 0.05)

A one-way independent groups analysis of variance (ANOVA) using subjects as a fixed effect (i.e., a grouping variable) showed significant differences between subjects for the persistence measure (p<0.01; see Figure 13), but similar ANOVAs for contact latency and exploration diversity were not statistically significant (p=.158 and p=.963, respectively).

CARNIVORE BEHAVIORAL FLEXIBILITY 42

Figure 13. Variation among African lion individuals on the behavioral measure ‘persistence’.

As expected, persistence was a highly significant predictor of trial success using a GEE

(ß=12.141, X2(1)=15.226, p<.001). However, GEEs using either exploration diversity (ß=-.305,

X2(1)=1.991, p=.158) as the predictor or contact latency (ß=.000, X2(1)=.002, p=.963) as the predictor were not significant.

Snow leopards

Of the nine snow leopards that were tested on the multi-access puzzle box, four reached criteria on condition 1 (44%), and three reached criteria for condition 2 (33%).

Door 2, the pull rope door, was opened in 4 out of the 7 successful conditions (57%) and was opened first by two successful subjects. Door 1, the push in door, was opened in 3 out of the

7 successful trials (43%) and was opened first by two successful subjects. Door 3, the pull-down door, was not opened on any trials.

Success did not depend on sex (Wilcoxon Rank Sum test: Z= 0.00, p= 1.00), or zoo location (i.e. Turtleback Zoo or Bronx Zoo; Wilcoxon Rank Sum test: Z= -1.00, p= 0.317). CARNIVORE BEHAVIORAL FLEXIBILITY 43

In conditions where subjects reached criterion, success latency was significantly lower between the first successful trial and the second successful trial (t(6)= 2.566, p= 0.04,

M=265.143, SD=273.355; see Figure 14), but there was no significant difference between the first successful trial and the third successful trial (t(6)= .847, p= 0.429, M=94.857, SD=296.286) or the second successful trial and the third successful trial (t(6)= -1.460, p= 0.195, M=-170.286,

SD=308.660). CARNIVORE BEHAVIORAL FLEXIBILITY 44

Figure 14. Learning curves for individual snow leopards across trials. Success latency was the time to open the MAB from the trial start. The number on the graph represents the door opened. CARNIVORE BEHAVIORAL FLEXIBILITY 45

A condition is solved once an individual opens a door in 3/5 trials. ‘Gala’, ‘Tanja’, ‘Leo’, ‘Mike’ and ‘Khyber’ were not successful in meeting criterion for Condition 1. ‘Willie’, and ‘MJ’ met criterion for Condition 1, but failed to meet criterion for Condition 2. ‘Chameli’ and ‘K2’ met criterion for Conditions 1 and 2, but failed to meet criterion for Condition 3. No snow leopard met criterion for all three Conditions. In snow leopard contact latency analyses, the subject,

‘Willie’, was removed as an outlier for the behavioral measure ‘contact latency’ in by-subject, by-trial measures, the ANOVAs, and the GEE model. There were three trials in which he never made contact with the box, which did not affect the presence of significance in behavioral measures, but it did affect the skew of the data.

Behavioral assays were measured at both the trial and subject levels for both successful and unsuccessful individuals where successful individuals were those that met criterion for

Condition 1. Four out of nine snow leopards were successful at meeting criterion for Condition

1, and five were unsuccessful at meeting criterion for Condition 1 (see Table 6).

Table 6. Means and standard deviations for the behavioral measure of both successful and unsuccessful snow leopards

Successful (n=4) Unsuccesful (n=5) Mean SD Mean SD Persistence 0.425 0.257 0.206 0.266 Contact Latency 4.320 3.639 13.160 13.567 Success Latency 545.601 80.772 750.900 55.013 Exploration Diversity 3.033 0.782 2.406 1.732 Number of Trials to Repeated Success 2.333 0.471 3.400 1.342 Number of Solutions 1.750 0.500 0.000 0.000

To further assess behavioral assays and their degree of independence, we examined the bivariate correlations between the trial-level measures persistence, contact latency, success CARNIVORE BEHAVIORAL FLEXIBILITY 46 latency, and exploration diversity using Kendall’s tau (see Table 7). Persistence was negatively correlated with contact latency (rТ = -.359 p < 0.01; see Figure 15). In addition, exploration diversity was positively correlated with persistence (rТ = .403, p < 0.01; see Figure 16) and success latency (rТ = .636, p < 0.01; see Figure 17), and negatively correlated with contact latency (rТ = -.355, p < 0.01; see Figure 18).

Table 7: Correlations based on trial measures

Persistence Contact Success Exploration Latency Latency Diversity Persistence 1.00 -.359** .010 .403** Contact Latency 1.00 -.239 -.355** Success Latency 1.00 .636** Exploration Diversity 1.00 Rank Correlation Matrix of four trial-level behavioral measures; * p < 0.05, ** p< 0.01

Figure 15. Trial-level persistence as a function of contact latency (p < 0.01)

CARNIVORE BEHAVIORAL FLEXIBILITY 47

Figure 16. Trial-level persistence as a function of exploration diversity (p < 0.01)

Figure 17. Trial-level success latency as a function of exploration diversity (p < 0.01) CARNIVORE BEHAVIORAL FLEXIBILITY 48

Figure 18. Trial-level contact latency as a function of exploration diversity (p < 0.01)

We also examined the bivariate correlations between the subject-level measures persistence, contact latency, success latency, exploration diversity, number of trials to repeated success and number of solutions (see Table 8). Persistence was negatively correlated with contact latency (rТ = -.643, p < 0.05; see Figure 19) and number of trials to repeated success (rТ

= -.588, p < 0.05; see Figure 20), and positively correlated with exploration diversity (rТ = .722, p < 0.01; see Figure 21). Exploration diversity was positively correlated with contact latency (rТ

= .643, p < 0.05; see Figure 22) and negatively correlated with number of trials to repeated success (rТ = -.588, p < 0.05; see Figure 23).

CARNIVORE BEHAVIORAL FLEXIBILITY 49

Table 8: Correlations based on subject means

1 2 3 4 5 6 1. Persistence 1.00 -.643* -.333 .722** -.588* .452 2. Contact Latency 1.00 .000 .643* .536 -.342 3. Success Latency 1.00 .067 -.138 -.701 4. Exploration Diversity 1.00 -.588* .243 5. Number of Trials to Repeated Success 1.00 -.581 6. Number of Solutions 1.00 Rank Correlation Matrix of six subject-level behavioral measures; * p<0.05, ** p<0.01,

Kendall’s tau rank correlation

Figure 19. Subject-level measures of persistence as a function of contact latency (p < 0.05) CARNIVORE BEHAVIORAL FLEXIBILITY 50

Figure 20. Subject-level persistence as a function of number of trials to repeated success (p <

0.05)

Figure 21. Subject-level persistence as a function of exploration diversity (p < 0.01) CARNIVORE BEHAVIORAL FLEXIBILITY 51

Figure 22. Subject-level contact latency as a function of exploration diversity (p < 0.05)

Figure 23. Subject-level number of trials to repeated success as a function of exploration

diversity (p < 0.05) CARNIVORE BEHAVIORAL FLEXIBILITY 52

One-way independent groups ANOVAs using subjects as a fixed effect (i.e., a grouping variable) showed significant differences between subjects for persistence (p<0.01; see Figure

24), contact latency (p<0.01; see Figure 25), and exploration diversity (p<0.01; see Figure 26).

‘Gala’, ‘Tanja’, ‘Leo’, ‘Mike’ and ‘Khyber’ were not successful in meeting criterion for

Condition 1. ‘Willie’, and ‘MJ’ met criterion for Condition 1, but failed to meet criterion for

Condition 2. ‘Chameli’ and ‘K2’ met criterion for Conditions 1 and 2, but failed to meet criterion for Condition 3. No snow leopard met criterion for all three Conditions.

Figure 24. Variation among snow leopards on the behavioral measure ‘persistence’.

CARNIVORE BEHAVIORAL FLEXIBILITY 53

Figure 26. Variation among snow leopards on the behavioral measure ‘exploration diversity’.

One subject, ‘Willie’, was removed from the analyses as an outlier.

Figure 26. Variation among snow leopards on the behavioral measure ‘exploration diversity’.

To further assess the relation between the behavioral measures and success in opening the puzzle box, we built GEE models to predict trial success using subjects as a random effect and, CARNIVORE BEHAVIORAL FLEXIBILITY 54 as a single fixed effect, persistence, exploration diversity, or contact latency. Persistence (ß=-

3.343, X2(1)=5.619, p<.05), and exploration diversity were significant predictors of trial success in snow leopards (ß=.004, X2(1)=6.537, p<.05). Contact latency did not significantly predict trial success (ß=.025, X2(1)=.012, p=.914).

Examining the Differences Between African lions & snow leopards

Snow leopards, though having less successful individuals, showed more significant correlations and individual variation than the African lions. In addition, snow leopard success is predicted by persistence and exploration diversity, whereas African lion success is only predicted by persistence.

Numerically, successful African lions exhibited a mean success latency of 115.192 while successful snow leopards exhibited a mean success latency of 545.601s. Not only did African lions solve the MAB almost 5 times faster on average, but 83.33% of the individuals tested met the criterion for Condition 1. In comparison, only 55.56% of tested snow leopards met the criterion for Condition 1. Snow leopard exhibited all six exploratory behaviors, while no African lion exhibited the ‘stalking’ behavior during testing.

For African lions, the push in door was most preferential and it was opened 4 out of 8 conditions (50%). Door 3 was opened in 3 out of 8 conditions (37.5%) and Door 2 was only opened once (12.5%). Successful Turtleback Zoo lions both opened the push in door, whereas the successful Bronx Zoo lions all opened the pull-down door. Only one lion opened Door 2, the pull rope door. In comparison, Door 2 was most preferential by snow leopards and was opened in

4 out of the 7 successful conditions (57%) Door 1, the push in door, was opened in 3 out of the 7 successful trials (43%) and Door 3, the pull-down door, was not opened on any trials.

CARNIVORE BEHAVIORAL FLEXIBILITY 55

Discussion

This is the first formal study on repeated innovation in African lions and snow leopards and provides crucial and overdue evidence on their cognitive abilities. We found that both species were able to successfully repeatedly innovate by opening more than one solution to the puzzle box. African lions were able to open all three solutions, with their success predicted by persistence. Snow leopards were able to open doors 1 (the push in door) and 2 (the pull rope door), but no individual opened door 3 during the trial. Success in snow leopards was predicted by persistence and exploration diversity. Previous research on mammalian carnivores found that on a one-solution puzzle box, only 1 out of 5 African lions, and 2 out of 4 snow leopards could innovate and open the door (Benson- Amram et al., 2016). In a larger sample size, Borrego and

Gaines found that 16 of 21 African lions, and 6 of 11 African leopards (Panthera pardus) could innovate by opening a puzzle box (Borrego & Gaines 2016). We know from these studies that

African lions and snow leopards can innovate, and with the current study we are able to establish that both species can repeatedly innovate and exhibit behavioral flexibility.

In addition to persistence as a positive predictor of success, which is also supported by other research (Benson-Amram et al., 2016; Griffin & Guez 2014), we also found that a higher number of exploratory behaviors and a lower time to make contact with the puzzle had a significant effect on problem-solving. High exploration diversity positively correlated with success and contact latency negatively correlated with success in African lions and snow leopards. Success related to higher number of diverse behaviors and low contact latency is supported by other studies on behavioral variety and innovation (Borrego & Gaines 2016;

Benson-Amram et al., 2013; Griffin & Guez 2014). When testing cognitive abilities in captivity, it is important to note that only a handful of studies have gathered evidence on wild populations, CARNIVORE BEHAVIORAL FLEXIBILITY 56 and no studies have yet been gathered on snow leopard nor African lion wild populations.

However, one study on wild spotted hyenas (Crocuta crocuta) found that both captive and wild individuals were able to open a one-solution puzzle box (Benson-Amram, Weldele & Holekamp

2012). Captive hyenas did significantly better, and were more persistent than their wild counterparts, which is due to neophobia, and not actually innovation differences in wild hyenas.

It is suggested that wild hyenas avoided the puzzle box as it was a manmade object, and thus could present a danger. In contrast to the results, this would suggest more successful wild behavior and cognitive abilities. From our study, we know that both African lions and snow leopards can innovate, but expect similar avoidance, particularly in snow leopards, in the wild.

Therefore, innovative studies in zoo are increasingly important for carnivore species in both for their important implications in captivity and the wild.

The analysis of the carnivores’ behavioral responses indicates that both species can be successful in repeatedly innovating when asked to come up with new solutions to a problem. We saw a decrease in time to success in both snow leopards and African lions. However, African lions showed a decreased between second and third successful trials in a condition, whereas snow leopards showed a decrease between first and second successful trials in a condition. In the first examination of learning in snow leopards, this confirms that snow leopards can learn and suggests that they may learn faster than African lions. This result is in line with previous studies that provide evidence for the physical intelligence hypothesis, which suggests that ecological demands encourage the evolution of intelligence. Snow leopards live in extremely harsh environments due to the terrain, prey scarcity, and frigid weather. Their specialized skills for navigating their intense environments encourages their cognitive abilities to exhibit rapid behavioral flexibility. CARNIVORE BEHAVIORAL FLEXIBILITY 57

From an overview, our results suggest that with further testing, African lions may be better innovators than their asocial counterparts, as seen in lions, hyenas, tigers, and leopards

(Borrego & Gaines 2016), in agreement with the social intelligence hypothesis. As the only social cat in Panthera, African lions, under the social intelligence hypothesis, exhibit more advanced cognitive abilities due to their social relationships.

Even with a small sample size of carnivores, our approach in this study was successful in revealing ‘persistence’ as a highly significant predictor of trial success in African lions and identifying ‘persistence’ and ‘exploration diversity’ as significant predictors of trial success in snow leopards. Although not significant due to the removal of Willie, this nearing significance suggests with more subjects contact latency may be significant, which would further support neophobia’s negative relationship with problem-solving success. Neophobia is one individual factor likely to inhibit behavioral flexibility and to prevent individuals from using devices in the wild (Benson-Amram, Weldele & Holekamp 2012; Morand-Ferron, Cole & Quinn 2016). It is hypothesized that neophobic individuals adopt an accuracy over speed strategy, in comparison to bold, impulsive and routine-forming individuals (Sih & del Giudice 2012). Neophobic tendencies have been found in multiple species, including wild raccoons, where it impeded their problem-solving success on a multi-access puzzle box (Daniels et al., 2019).

The relationship between sex and success approached significance, with females tending to be more successful than males. We suspect the lack of significance to be affected by the sample size, with an uneven number of males compared to females, a larger range in ages of females compared to males, or the genetic relatedness of the individuals of both species. We would therefore expect to see differences between females and males in future studies. As females and males in the African lion sample size showed more differences, this may be support CARNIVORE BEHAVIORAL FLEXIBILITY 58 for the emotional reactivity hypothesis. Female lions run the hierarchy as the primary hunters, and by synchronizing their births and young-rearing (Bertram 1975; Stander 1992). This inter- individual balance between females and males may show differences in their innovation on a problem-solving task.

These results are in contrast to those in the previous paragraphs, which are in line with physical intelligence hypothesis and the social intelligence hypothesis. We found no results for the cultural intelligence hypothesis as it was not a social test and the only wild member, ‘Leo’, did not meet criterion for Condition 1. Further results on these two species, and more species within this genus would provide sufficient evidence for one theory over the others.

Snow leopards’ exploration diversity scores correlated with two other behaviors on trial- level measures. In addition to success latency, exploration diversity was negatively correlated with contact latency and positively correlated with persistence at both the trial-level and the subject-level. It has been demonstrated that a higher range of motor behaviors in multiple species is a significant predictor of greater problem-solving abilities (Benson-Amram & Holekamp

2012; Manrique et al., 2013; Griffin et al., 2014). A longer time to approach the box suggests neophobic behavior, which is supported by the correlation with less exploratory behaviors. This is supported by a previous study, which found that neophobic captive hyenas were significantly less likely to problem solve (Benson-Amram et al., 2013). This correlation suggests that snow leopards exhibited more neophobic behavior in trials than African lions. It is also expected that a higher level of persistent working behavior will strongly positively correlate to a larger number of behaviors exhibited. However, this was not exhibited in a previous study; Johnson-Ulrich and colleagues (2018) found no significant relationship between persistence and exploration diversity

(in their paper exploration diversity was referred to as ‘motor diversity’. This may be due to the CARNIVORE BEHAVIORAL FLEXIBILITY 59 different behaviors and number of behaviors used in either study (Johnson-Ulrich and colleagues used only 5 behaviors), or it may be due to the different species (Johnson-Ulrich and colleagues tested hyenas). These comparative results may support the physical intelligence hypothesis, as asocial snow leopards are exhibiting a positive correlation between persistent behavior and exploratory behavior.

In the one-way ANOVAs for between subjects effects, there were significant differences between African lions for persistence and between snow leopards for persistence, contact latency and exploration diversity. There have been studies that show dominance (Thornton & Samson

2012), rank (Boogert et al., 2008), motivation (Sol et al., 2012), age (Kendal et al., 2005) and sex

(Reader & Laland 2001) can affect problem-solving and innovative abilities. Further studies increasing the sample size offer the opportunity to test the potential links between factors that may influence behavioral flexibility. It is important to note here that genetic relatedness and physical location may play a role in the lack of differences between individuals. Four of the lions, ‘Thulani’, ‘Ime’, ‘Bahati’, and ‘Amara’ are littermates and direct offspring of ‘Sukari’.

Additionally, ‘Thulani’, ‘Ime’ and ‘Bahati’ have been born and raised in the Bronx Zoo with the same zookeepers. ‘Sukari’ and ‘Amara’ moved from the Bronx Zoo to the Turtleback Zoo together about two years ago. These five lions spent a significant amount of time together, with three of them never having left their original enclosures and are biologically related. In contrast, only four of the nine snow leopards share relatedness. ‘Khyber’ is the offspring of ‘K2’ and

‘Willie’, and ‘Willie’ is the offspring of ‘Leo’. The snow leopards show more diversity in age, length of time at the current zoo, and genetic relatedness than the African lions.

Studying the innovation and problem-solving ability of large carnivores will help us understand the evolution of their cognitive abilities and help us predict how they may adjust to CARNIVORE BEHAVIORAL FLEXIBILITY 60 the changing environment. Almost all of the 40 wild cat species are shrinking and sixteen species, including the two being tested are considered vulnerable, or endangered (IUCN 2019).

Innovation and problem-solving are currently being used for species survival (Griffin 2004;

Hockings et al., 2015; Griffin, Blumstein & Evans 2000). Studies using innovation and problem- solving are currently being used to predict survival in wild reintroduction programs, and to match breeding pairs in captivity. The widespread approach of this study can integrate species, sex, sociality, welfare and cognition, which can provide a multitude of findings to test a hypothesis with implications for captive welfare and wildlife conservation.

The results of this study will help in the development of better captive environments for large mammals. Zoos contribute to the conservation and enrichment of the lives of the animals in their care. However, housing large solitary animals and the enrichment of large carnivores are growing concerns in captive management (McPhee 2004; Mason 1991). Social housing can serve as a significant form of enrichment for social species, but research on housing specifications for asocial species is not well documented (Macri & Patterson-Kane 2011;

Szokalski, Litchfield & Foster 2012; Price & Stoinski 2007). We know that knowledge is required to understand if and how species can adapt to their changing environments. There is potential and a need to reintroduce carnivores to specific areas in order to control a prey population, or provide a separate population. However, in previous release programs, Asiatic lions (Panthera leo persica) were unable to survive in the 1950s when released to a second location in India, and no successful release of snow leopards has been recorded (Sale 1986). A reintroduction program of African lions in 1991 was successful in that the populations have lived, however the lack of members in the original population, the fragmentation of the translocated populations, and the uninformed decisions of management provide little CARNIVORE BEHAVIORAL FLEXIBILITY 61 contribution to the overall need (Slotow & Hunter 2009). With this study and future studies, there is the hope that crucial information will be attained to assist in immediate action for captive and wild welfare of all carnivore species; it is with this knowledge that more informed decisions can be made on how to conserve this unique species who have between-species and between- individuals differences.

Future studies should examine the relationship of sex, age, individual differences, species differences, and group dynamics with cognitive abilities. Further studies exploring different cognitive tasks are of utmost importance to better accommodate for interspecies differences.

Within captivity, cognitive differences within sex and species can better accommodate for priorities such as introduction of new individuals, mate pairing, and enrichment. With the wild, behavioral observations, tracking, and grouping are just some of the factors that could be evaluated differently. Findings of this proposed project are increasingly important in today’s climate to put forward new information and new questions. By observing carnivores’ reactions to a problem-solving task within captivity, with environmental pressures removed, we can better identify the factors in the evolution of cognition to hopefully better understand differences between species.

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