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Goetsch, A. L., Gipson, T. A., Askar, A. R., & Puchala, R. (2010). Feeding behavior of goats. J Anim Sci, 88.
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Riede, T., Herzel, H., Mehwald, D., Seidner, W., Trumler, E., & Böhme, G. (2000). Nonlinear phenomena in the natural howling of a dog-wolf mix. J Acoust Soc Am, 108.
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Gazzola, A., Avanzinelli, E., Mauri, L., Scandura, M., & Apollonio, M. (2002). Temporal changes of howling in south European wolf packs. Ital J Zool, 69.
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Blanco, J. C., & Yolanda, C. (2012). Surveying wolves without snow: a critical review of the methods used in Spain. Hystrix. Ital J Mammal, 23.
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Burke, C., Rashman, M., Wich, S., Symons, A., Theron, C., & Longmore, S. (2019). Optimizing observing strategies for monitoring animals using drone-mounted thermal infrared cameras. International Journal of Remote Sensing, 40(2), 439–467.
Abstract: ABSTRACTThe proliferation of relatively affordable off-the-shelf drones offers great opportunities for wildlife monitoring and conservation. Similarly the recent reduction in the cost of thermal infrared cameras also offers new promise in this field, as they have the advantage over conventional RGB cameras of being able to distinguish animals based on their body heat and being able to detect animals at night. However, the use of drone-mounted thermal infrared cameras comes with several technical challenges. In this article, we address some of these issues, namely thermal contrast problems due to heat from the ground, absorption and emission of thermal infrared radiation by the atmosphere, obscuration by vegetation, and optimizing the flying height of drones for a best balance between covering a large area and being able to accurately image and identify animals of interest. We demonstrate the application of these methods with a case study using field data and make the first ever detection of the critically endangered riverine rabbit (Bunolagus monticularis) in thermal infrared data. We provide a web-tool so that the community can easily apply these techniques to other studies (http://www.astro.ljmu.ac.uk/aricburk/uav_calc/).
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Kuczaj, S. A., Makecha, R., Trone, M., Paulos, R. D., & Ramos, J. A. (2006). Role of Peers in Cultural Innovation and Cultural Transmission: Evidence from the Play of Dolphin Calves. Int. J. Comp. Psychol, 19(2), 223–240.
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Kruska, D. (1988). Mammalian domestication and its effect on brain structure and behavior. In H. J. Jerison, & I. Jerison (Eds.), Intelligence and Evolutionary Biology. New York: Springer-Verlag.
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Houpt, K. A. (1981). Equine behavior problems in relation to humane management. Int. J. Stud. Anim. Prob., 2(6), 329–337.
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Krueger, K. (Ed.). (2008). Proceedings of the International Equine Science Meeting 2008. Wald: Xenophon Verlag.
Abstract: Target group: Biologists, Psychologists, Veterinarians and Professionals
Meeting target: Because the last international meeting on Equine Science took place a couple years ago, there is an urgent need for equine scientists to exchange scientific knowledge, coordinate research provide knowledge for practical application, and discus research results among themselves and with professionals who work with horses. Additionally, dialog concerning the coordination of the study “Equitation Science” in Europe is urgently needed. Coordination and cooperation shall arise from the meeting, enrich the research, and advance the application of scientific knowledge for the horses` welfare.
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Passilongo, D., Marchetto, M., & Apollonio, M. (2017). Singing in a wolf chorus: structure and complexity of a multicomponent acoustic behaviour. Hysterix, 28(2), 180–185.
Abstract: Wolf choruses ( Canis lupus ) are complex, multicomponent signals, composed by a series of different vocalizations emitted by a pack. Although howls, the main component, have been highly studied, poor attention has been drawn upon the other vocalizations of the chorus. In this study, we investigate the structure of the chorus by means of the analysis and the quantification of the different components, taking advantage both of the digital sound recording and analysis, and of the modern statistical methodologies. We provide for the first time a detailed, objective description of the types of call emitted during the wolf howlings, combining spectrographic examinations, spectral analyses and automated classifications, with the aim to identify different types of call. Our results show that wolf choruses have a rich, complex structure, that reveals six other types of call, to be added to those howls already described in literature. Wolf choruses are typically composed by other three different types of calls: the bark, i.e. relatively long calls characterized by low frequencies and the presence of harsh components (deterministic chaos); the whimper, characterized by a harmonic structure and a very short duration; and the growl, a call with a noisy structure, low frequencies but relative long duration. Although further investigations are necessary to understand the meaning of the different calls, this research provides a basis for those studies that aim to compare wolves and other canids vocal behaviour.
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