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Henry, S., Fureix, C., Rowberry, R., Bateson, M., & Hausberger, M. (2017). Do horses with poor welfare show 'pessimistic' cognitive biases? Sci. Nat., 104(1), 8.
Abstract: This field study tested the hypothesis that domestic horses living under putatively challenging-to-welfare conditions (for example involving social, spatial, feeding constraints) would present signs of poor welfare and co-occurring pessimistic judgement biases. Our subjects were 34 horses who had been housed for over 3 years in either restricted riding school situations (e.g. kept in single boxes, with limited roughage, ridden by inexperienced riders; N = 25) or under more naturalistic conditions (e.g. access to free-range, kept in stable social groups, leisure riding; N = 9). The horses' welfare was assessed by recording health-related, behavioural and postural indicators. Additionally, after learning a location task to discriminate a bucket containing either edible food ('positive' location) or unpalatable food ('negative' location), the horses were presented with a bucket located near the positive position, near the negative position and halfway between the positive and negative positions to assess their judgement biases. The riding school horses displayed the highest levels of behavioural and health-related problems and a pessimistic judgment bias, whereas the horses living under more naturalistic conditions displayed indications of good welfare and an optimistic bias. Moreover, pessimistic bias data strongly correlated with poor welfare data. This suggests that a lowered mood impacts a non-human species' perception of its environment and highlights cognitive biases as an appropriate tool to assess the impact of chronic living conditions on horse welfare.
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Herbst, C. T., Herzel, H., Svec, J. G., Wyman, M. T., & Fitch, W. T. (2013). Visualization of system dynamics using phasegrams. J R Soc Interface, 10.
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Heydebreck, K. von. (1928). Reitlehrer und Reiter in Uniform und Zivil eine Anleitung nach den Grundsätzen der deutschen Reitvorschrift (2., neubearb. Aufl ed.). Berlin: Mittler.
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Heyes, C. (2012). What's social about social learning? J Comp Psychol, 120.
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Hiby, E. F., Rooney, N. J., & Bradshaw, J. W. S. (2004). Dog training methods: their use, effectiveness and interaction with behaviour and welfare. Anim. Welf., 13(1), 63–69.
Abstract: Historically, pet dogs were trained using mainly negative reinforcement or punishment, but positive reinforcement using rewards has recently become more popular. The methods used may have different impacts on the dogs� welfare. We distributed a questionnaire to 364 dog owners in order to examine the relative effectiveness of different training methods and their effects upon a pet dog�s behaviour. When asked how they trained their dog on seven basic tasks, 66% reported using vocal punishment, 12% used physical punishment, 60% praise (social reward), 51% food rewards and 11% play. The owner�s ratings for their dog�s obedience during eight tasks correlated positively with the number of tasks which they trained using rewards (P<0.01), but not using punishment (P=0.5). When asked whether their dog exhibited any of 16 common problematic behaviours, the number of problems reported by the owners correlated with the number of tasks for which their dog was trained using punishment (P<0.001), but not using rewards (P=0.17). Exhibition of problematic behaviours may be indicative of compromised welfare, because such behaviours can be caused byor result ina state of anxiety and may lead to a dog being relinquished or abandoned. Because punishment was associated with an increased incidence of problematic behaviours, we conclude that it may represent a welfare concern without concurrent benefits in obedience. We suggest that positive training methods may be more useful to the pet-owning community.
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Hoelker, S. (2016). Typologie der deutschen Pferdehaltung – Eine empirische Studie mittels Two-Step-Clusteranalyse. Berichte über Landwirtschaft Zeitschrift für Agrarpolitik und Landwirtschaft, 94(3).
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Hofmeester, T. R., Cromsigt, J. P. G. M., Odden, J., Andrén, H., Kindberg, J., & Linnell, J. D. C. (2019). Framing pictures: A conceptual framework to identify and correct for biases in detection probability of camera traps enabling multi-species comparison. Ecol Evol, .
Abstract: Abstract Obtaining reliable species observations is of great importance in animal ecology and wildlife conservation. An increasing number of studies use camera traps (CTs) to study wildlife communities, and an increasing effort is made to make better use and reuse of the large amounts of data that are produced. It is in these circumstances that it becomes paramount to correct for the species- and study-specific variation in imperfect detection within CTs. We reviewed the literature and used our own experience to compile a list of factors that affect CT detection of animals. We did this within a conceptual framework of six distinct scales separating out the influences of (a) animal characteristics, (b) CT specifications, (c) CT set-up protocols, and (d) environmental variables. We identified 40 factors that can potentially influence the detection of animals by CTs at these six scales. Many of these factors were related to only a few overarching parameters. Most of the animal characteristics scale with body mass and diet type, and most environmental characteristics differ with season or latitude such that remote sensing products like NDVI could be used as a proxy index to capture this variation. Factors that influence detection at the microsite and camera scales are probably the most important in determining CT detection of animals. The type of study and specific research question will determine which factors should be corrected. Corrections can be done by directly adjusting the CT metric of interest or by using covariates in a statistical framework. Our conceptual framework can be used to design better CT studies and help when analyzing CT data. Furthermore, it provides an overview of which factors should be reported in CT studies to make them repeatable, comparable, and their data reusable. This should greatly improve the possibilities for global scale analyses of (reused) CT data.
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Holzapfel, M., Wagner, C., & Kluth, G. et al. (2011). Zur Nahrungsökologie der Wölfe (Canis lupus) in Deutschland. Beiträge zur Jagd- und Wildforschung, 36, 117–128.
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Hoppitt, W., & Laland, K. N. (2008). Social processes influencing learning in animals: a review of the evidence. Adv Study Behav, 38, 105–165.
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Houpt, K., Marrow, M., & Seeliger, M. (2000). A preliminary study of the effect of music on equine behavior. Journal of Equine Veterinary Science, 20(11), 691–737.
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