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Krueger, K., Trager, L., Farmer, K., & Byrne, R. (2022). Tool Use in Horses. Animals, 12(15), 1876.
Abstract: Tool use has not yet been confirmed in horses, mules or donkeys. As this subject is difficult to research with conventional methods, we used a crowdsourcing approach to gather data. We contacted equid owners and carers and asked them to report and video examples of �unusual� behaviour via a dedicated website. We also searched YouTube and Facebook for videos of equids showing tool use. From 635 reports, including 1014 behaviours, we found 20 cases of tool use, 13 of which were unambiguous in that it was clear that the behaviour was not trained, caused by reduced welfare, incidental or accidental. We then assessed (a) the effect of management conditions on tool use and (b) whether the animals used tools alone, or socially, involving other equids or humans. We found that management restrictions were associated with corresponding tool use in 12 of the 13 cases (p = 0.01), e.g., equids using sticks to scrape hay within reach when feed was restricted. Furthermore, 8 of the 13 cases involved other equids or humans, such as horses using brushes to groom others. The most frequent tool use was for foraging, with seven examples, tool use for social purposes was seen in four cases, and there was just one case of tool use for escape. There was just one case of tool use for comfort, and in this instance, there were no management restrictions. Equids therefore can develop tool use, especially when management conditions are restricted, but it is a rare occurrence.
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Mann Janet, & Patterson Eric M. (2013). Tool use by aquatic animals. Phil. Trans. Biol. Sci., 368(1630), 20120424.
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Kräußlich, H., & Brem, G. (1997). Tierzucht und allgemeine Landwirtschaftslehre für Tiermediziner. Stuttgart: Enke.
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Mech, L. D. (1970). The Wolf: The Ecology and Behaviour of an Endangered Species. New York: The Natural History Press, Garden City.
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Nelson, X. J., & Fijn, N. (2013). The use of visual media as a tool for investigating animal behaviour. Animal Behaviour, 85(3), 525–536.
Abstract: In this essay we outline how video-related technology can be used as a tool for studying animal behaviour. We review particular aspects of novel, innovative animal behaviour uploaded by the general public via video-based media on the internet (using YouTube as a specific example). The behaviour of animals, particularly the play behaviour focused on here, is viewed by huge audiences. In this essay we focused on three different kinds of media clips: (1) interspecies play between dogs and a range of other species; (2) object play in horses; and (3) animal responses to stimuli presented on iPads, iPods and iPhones. We argue that the use of video is a good means of capturing uncommon or previously unknown behaviour, providing evidence that these behaviours occur. Furthermore, some of the behaviours featured on YouTube provide valuable insights for future directions in animal behaviour research. If we also take this opportunity to convey our knowledge to a public that seems to be fundamentally interested in animal behaviour, this is a good means of bridging the gap between knowledge among an academic few and the general public.
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Pimlott, D. H. (1960). The use of tape-recorded wolf howls to locate timber wolves. Toronto: Twenty-second Midwest Wildlife Congress.
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Kaczensky, P., & Huber, K. (2010). The Use of High Frequency GPS Data to Classify Main Behavioural Categories in a Przewalski’s Horse in the Mongolian Gobi. DigitalCommons@University of Nebraska – Lincoln, .
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Dunbar, R. I. M. (2009). The social brain hypothesis and its implications for social evolution. Annals of Human Biology, 36(5), 562–572.
Abstract: The social brain hypothesis was proposed as an explanation for the fact that primates have unusually large brains for body size compared to all other vertebrates: Primates evolved large brains to manage their unusually complex social systems. Although this proposal has been generalized to all vertebrate taxa as an explanation for brain evolution, recent analyses suggest that the social brain hypothesis takes a very different form in other mammals and birds than it does in anthropoid primates. In primates, there is a quantitative relationship between brain size and social group size (group size is a monotonic function of brain size), presumably because the cognitive demands of sociality place a constraint on the number of individuals that can be maintained in a coherent group. In other mammals and birds, the relationship is a qualitative one: Large brains are associated with categorical differences in mating system, with species that have pairbonded mating systems having the largest brains. It seems that anthropoid primates may have generalized the bonding processes that characterize monogamous pairbonds to other non-reproductive relationships (?friendships?), thereby giving rise to the quantitative relationship between group size and brain size that we find in this taxon. This raises issues about why bonded relationships are cognitively so demanding (and, indeed, raises questions about what a bonded relationship actually is), and when and why primates undertook this change in social style.
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Zohary, D., Tchernov, E., & Horwitz, L. K. (1998). The role of unconscious selection in the domestication of sheep and goats. J Zool, 245.
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Lanata, A., Guidi, A., Valenza, G., Baragli, P., & Scilingo, E. P. (2017). The Role of Nonlinear Coupling in Human-Horse Interaction: a Preliminary Study. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
Abstract: This study focuses on the analysis of humanhorse
dynamic interaction using cardiovascular information
exclusively. Specifically, the Information Theoretic Learning
(ITL) approach has been applied to a Human-Horse Interaction
paradigm, therefore accounting for the nonlinear information
of the heart-heart interplay between humans and horses.
Heartbeat dynamics was gathered from humans and horses
during three experimental conditions: absence of interaction,
visual-olfactory interaction, and brooming. Cross Information
Potential, Cross Correntropy, and Correntropy Coefficient were
computed to quantitatively estimate nonlinear coupling in a
group of eleven subjects and one horse. Results showed a
statistical significant difference on all of the three interaction
phases. Furthermore, a Support Vector Machine classifier
recognized the three conditions with an accuracy of 90:9%.
These preliminary and encouraging results suggest that ITL
analysis provides viable metrics for the quantitative evaluation
of human-horse interaction.
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