Abstract

In addition to domestication, interactions with humans or task-specific training during ontogeny have been proposed to play a key role in explaining differences in human–animal communication across species. In livestock, even short-term positive interactions with caretakers or other reference persons can influence human–animal interaction at different levels and over different periods of time. In this study, we investigated human-directed behaviour in the ‘unsolvable task’ paradigm in two groups of domestic goats (Capra aegagrus hircus). One group was positively handled and habituated to a plastic box by the experimenter to retrieve a food reward, while the other group only received standard husbandry care and was habituated to the box without human assistance. In the unsolvable task, the lid was fixed to the box, with the reward inaccessible to the subjects. The goats were confronted with the unsolvable task three times. We observed no difference between the two groups regarding gaze and contact alternations with the experimenter when confronted with the task they cannot solve by themselves. The goats did not differ in their expression rates of both gaze and contact alternations over three repetitions of the unsolvable task; however, they showed earlier gaze and contact alternations in later trials. The results do not support the hypothesis that short-term positive handling or task-specific training by humans facilitates human-directed behaviour in goats. In contrast, standard husbandry care might be sufficient to establish humans as reference persons for farm animals in challenging situations.

Highlights

  • It has been argued that domestication has turned animals, such as the dog (Canis lupus familiaris), the cat (Felis silvestris catus), the horse (Equus ferus caballus), the pig (Sus scrofa domesticus) and the goat (Capra aegagrus hircus), at different levels, into specialists in the field of heterospecific communication with humans (Pfungst 1907; McKinley and Sambrook 2000; Hare et al 2002; Miklósi et al 2003, 2005; Kaminski et al 2005; Maros et al 2008)

  • Groups did not differ in the latency to their first gaze alternation (F1,14.5 = 1.430, p = 0.251; Fig. 3d) or to their first contact alternation (F1,10.3 = 0.190, p = 0.672; Fig. 3e); latency times decreased across trials for both measures (F2,15.4 = 42.057, p < 0.001; F2,10.1 = 32.925, p < 0.001, respectively)

  • We compared the level of human-directed behaviour between goats that only experienced standard handling during husbandry care and goats that received short-term positive handling for 3 weeks prior to testing in the ‘unsolvable task’ paradigm

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Summary

Introduction

It has been argued that domestication has turned animals, such as the dog (Canis lupus familiaris), the cat (Felis silvestris catus), the horse (Equus ferus caballus), the pig (Sus scrofa domesticus) and the goat (Capra aegagrus hircus), at different levels, into specialists in the field of heterospecific communication with humans (Pfungst 1907; McKinley and Sambrook 2000; Hare et al 2002; Miklósi et al 2003, 2005; Kaminski et al 2005; Maros et al 2008). Before Training and Test (see below), one group (‘handled’) was handled by a human experimenter, who interacted with the animals in their home pen through friendly talking, gentle touching, stroking and hand feeding This procedure was repeated for 30 min twice daily over 2 weeks. In SAS (version 9.3, 2009, SAS Institute Inc., Cary, NC, USA), we analysed latency to retrieve the reward in the training trials, gaze and contact alternations, and gaze and contact latency and time in physical contact with the box in the test trials using generalized linear mixed models (GLIMMIX procedure) with group (handled, non-handled), repetition (training trials: 16–20; unsolvable trials: 1–3; solvable motivation trials: 1–6) and their interactions as fixed effects, with the appropriate distributions (Poisson or normal) and link functions (log or identity). Least-square means (LSMs) and their standard errors (SEs) were computed for each fixed effect in the model

Results
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