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Seyfarth, R. M., Cheney, D. L., & Marler, P. (1980). Monkey responses to three different alarm calls: evidence of predator classification and semantic communication. Science, 210(4471), 801–803.
Abstract: Vervet monkeys give different alarm calls to different predators. Recordings of the alarms played back when predators were absent caused the monkeys to run into trees for leopard alarms, look up for eagle alarms, and look down for snake alarms. Adults call primarily to leopards, martial eagles, and pythons, but infants give leopard alarms to various mammals, eagle alarms to many birds, and snake alarms to various snakelike objects. Predator classification improves with age and experience.
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Fenton, B., & Ratcliffe, J. (2004). Animal behaviour: eavesdropping on bats. Nature, 429(6992), 612–613. |
Palleroni, A., Hauser, M., & Marler, P. (2005). Do responses of galliform birds vary adaptively with predator size? Anim. Cogn., 8(3), 200–210.
Abstract: Past studies of galliform anti-predator behavior show that they discriminate between aerial and ground predators, producing distinctive, functionally referential vocalizations to each class. Within the category of aerial predators, however, studies using overhead models, video images and observations of natural encounters with birds of prey report little evidence that galliforms discriminate between different raptor species. This pattern suggests that the aerial alarm response may be triggered by general features of objects moving in the air. To test whether these birds are also sensitive to more detailed differences between raptor species, adult chickens with young were presented with variously sized trained raptors (small, intermediate, large) under controlled conditions. In response to the small hawk, there was a decline in anti-predator aggression and in aerial alarm calling as the young grew older and less vulnerable to attack by a hawk of this size. During the same developmental period, responses to the largest hawk, which posed the smallest threat to the young at all stages, did not change; there were intermediate changes at this time in response to the middle-sized hawk. Thus the anti-predator behavior of the adult birds varied in an adaptive fashion, changing as a function of both chick age and risk. We discuss these results in light of current issues concerning the cognitive mechanisms underlying alarm calling behavior in animals.
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Ratcliffe, J. M., Fenton, M. B., & Shettleworth, S. J. (2006). Behavioral flexibility positively correlated with relative brain volume in predatory bats. Brain Behav Evol, 67(3), 165–176.
Abstract: We investigated the potential relationships between foraging strategies and relative brain and brain region volumes in predatory (animal-eating) echolocating bats. The species we considered represent the ancestral state for the order and approximately 70% of living bat species. The two dominant foraging strategies used by echolocating predatory bats are substrate-gleaning (taking prey from surfaces) and aerial hawking (taking airborne prey). We used species-specific behavioral, morphological, and ecological data to classify each of 59 predatory species as one of the following: (1) ground gleaning, (2) behaviorally flexible (i.e., known to both glean and hawk prey), (3) clutter tolerant aerial hawking, or (4) open-space aerial hawking. In analyses using both species level data and phylogenetically independent contrasts, relative brain size was larger in behaviorally flexible species. Further, relative neocortex volume was significantly reduced in bats that aerially hawk prey primarily in open spaces. Conversely, our foraging behavior index did not account for variability in hippocampus and inferior colliculus volume and we discuss these results in the context of past research.
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Wolf, M., van Doorn, G. S., Leimar, O., & Weissing, F. J. (2007). Life-history trade-offs favour the evolution of animal personalities. Nature, 447(7144), 581–584.
Abstract: In recent years evidence has been accumulating that personalities are not only found in humans but also in a wide range of other animal species. Individuals differ consistently in their behavioural tendencies and the behaviour in one context is correlated with the behaviour in multiple other contexts. From an adaptive perspective, the evolution of animal personalities is still a mystery, because a more flexible structure of behaviour should provide a selective advantage. Accordingly, many researchers view personalities as resulting from constraints imposed by the architecture of behaviour (but see ref. 12). In contrast, we show here that animal personalities can be given an adaptive explanation. Our argument is based on the insight that the trade-off between current and future reproduction often results in polymorphic populations in which some individuals put more emphasis on future fitness returns than others. Life-history theory predicts that such differences in fitness expectations should result in systematic differences in risk-taking behaviour. Individuals with high future expectations (who have much to lose) should be more risk-averse than individuals with low expectations. This applies to all kinds of risky situations, so individuals should consistently differ in their behaviour. By means of an evolutionary model we demonstrate that this basic principle results in the evolution of animal personalities. It simultaneously explains the coexistence of behavioural types, the consistency of behaviour through time and the structure of behavioural correlations across contexts. Moreover, it explains the common finding that explorative behaviour and risk-related traits like boldness and aggressiveness are common characteristics of animal personalities.
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Shettleworth, S. J., & Plowright, C. M. (1992). How pigeons estimate rates of prey encounter. J Exp Psychol Anim Behav Process, 18(3), 219–235.
Abstract: Pigeons were trained on operant schedules simulating successive encounters with prey items. When items were encountered on variable-interval schedules, birds were more likely to accept a poor item (long delay to food) the longer they had just searched, as if they were averaging prey density over a short memory window (Experiment 1). Responding as if the immediate future would be like the immediate past was reversed when a short search predicted a long search next time (Experiment 2). Experience with different degrees of environmental predictability appeared to change the length of the memory window (Experiment 3). The results may reflect linear waiting (Higa, Wynne, & Staddon, 1991), but they differ in some respects. The findings have implications for possible mechanisms of adjusting behavior to current reinforcement conditions.
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Isenbugel, E. (2002). [From wild horse to riding horse]. Schweiz Arch Tierheilkd, 144(7), 323–329.
Abstract: Over 45 million years of evolution the horse developed to a highly specialized animal in anatomy, physiology and behavior. No other animal had influenced the economic and cultural history of men to such extent. Hunting prey since the ice age, domesticated 4000 B.C. and used for thousands of years as unique animal all over the world has attained a new role today as partner in sport, as companion animal and even as cotherapeutic. The well known behavioral demands in use and keeping are still often not fulfilled.
Keywords: Animal Husbandry/*history; Animals; Animals, Domestic; Animals, Wild; *Bonding, Human-Pet; Breeding/history; Evolution; Female; History, 15th Century; History, 16th Century; History, 17th Century; History, 18th Century; History, 19th Century; History, 20th Century; History, Ancient; History, Medieval; *Horses/physiology/psychology; Humans; Male; Paintings; Predatory Behavior; Sculpture; Sports/history
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Arnold, K., & Zuberbuhler, K. (2006). Language evolution: semantic combinations in primate calls. Nature, 441(7091), 303.
Abstract: Syntax sets human language apart from other natural communication systems, although its evolutionary origins are obscure. Here we show that free-ranging putty-nosed monkeys combine two vocalizations into different call sequences that are linked to specific external events, such as the presence of a predator and the imminent movement of the group. Our findings indicate that non-human primates can combine calls into higher-order sequences that have a particular meaning.
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Thornton, A., & McAuliffe, K. (2006). Teaching in wild meerkats. Science, 313(5784), 227–229.
Abstract: Despite the obvious benefits of directed mechanisms that facilitate the efficient transfer of skills, there is little critical evidence for teaching in nonhuman animals. Using observational and experimental data, we show that wild meerkats (Suricata suricatta) teach pups prey-handling skills by providing them with opportunities to interact with live prey. In response to changing pup begging calls, helpers alter their prey-provisioning methods as pups grow older, thus accelerating learning without the use of complex cognition. The lack of evidence for teaching in species other than humans may reflect problems in producing unequivocal support for the occurrence of teaching, rather than the absence of teaching.
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Cole, P. D., & Adamo, S. A. (2005). Cuttlefish (Sepia officinalis: Cephalopoda) hunting behavior and associative learning. Anim. Cogn., 8(1), 27–30.
Abstract: Because most learning studies in cephalopods have been performed on octopods, it remains unclear whether such abilities are specific to octopus, or whether they correlate with having a larger and more centrally organized brain. To investigate associative learning in a different cephalopod, six sexually mature cuttlefish (Sepia officinalis) participated in a counterbalanced, within-subjects, appetitive, classical conditioning procedure. Two plastic spheres (conditioned stimuli, CSs), differing in brightness, were presented sequentially. Presentation of the CS+ was followed 5 s later by a live feeder fish (unconditioned stimulus, US). Cuttlefish began to attack the CS+ with the same type of food-acquisition seizures used to capture the feeder fish. After seven blocks of training (42 presentations of each CS) the difference in seizure probability between CS+ and CS- trials more than doubled; and was found to be significantly higher in late versus early blocks. These results indicate that cuttlefish exhibit autoshaping under some conditions. The possible ecological significance of this type of learning is briefly discussed.
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