Abstract: We examined if time spent in turnout influenced behaviour during turnout for horses maintained in stalls and given either 2 h/week (n = 7) or 12 h/week (n = 7) of turnout. Horses turned out for 2 h/week were more likely than those turned out for 12 h/week to trot, canter, and buck. Frequency of trotting and cantering was also higher and frequency of grazing lower in horses turned out for 2 h/week. These results have welfare implications and support previous studies showing that horses react to confinement with increased activity when not confined.

Abstract: Temperament is an important factor when working with horses. Behavioural tests have already been developed to measure certain dimensions of a horse's temperament (fearfulness, gregariousness, etc.). In order to measure the temperament more precisely, our work aimed to identify a dimension which has already been described in several species but not yet in horses, namely sensory sensitivity. Our study was based on the definition of a temperament dimension as “a behavioural characteristic stable across situations and over time”. We designed several tests for each sense and then determined whether the responses observed were correlated between situations and in time. The principle of the tests was to generate two stimuli of different intensities for each sense (e.g. two different sounds) and to measure the intensity of the horse's response (N = 26). Using Spearman rank correlations, we tested whether the responses to these different stimuli were inter-correlated. We repeated the same tests 5 months later to determine whether the responses were correlated over time. Within each sense, results show that the greater the horses' response to one stimulus, the greater their response to the other. For example, the reaction to the odour of cinnamon (time spent near the source of the odour) was significantly correlated to the reaction to lavender (R = 0.53, p = 0.004). The reactions to two different sounds or to two different tactile stimuli (von Frey filaments, or contact of a brush on the body), were also significantly correlated (R = 0.59, p < 0.0001; R = 0.38, p = 0.029). Finally, the reactions to two different tastes or to two visual stimuli tended to be correlated (R = 0.27, p = 0.09; R = 0.27, p = 0.09). However, there was no significant correlation between the responses to stimuli relating to different senses. Finally, except for the responses to odour, the responses to other sensory stimuli showed stability over a 5-month period (e.g. tactile stimulation: R = 0.71, p < 0.0001). In conclusion, our study revealed characteristics which were stable across situations and over time. The absence of links between the characteristics measured for the different senses suggests that a dimension for each sense exists (e.g. tactile sensitivity) rather than a general sensory sensitivity dimension covering all the senses.

Abstract: The responsiveness of 10 horses and 10 ponies to environmental challenge (represented by an open field test) was assessed using a qualitative approach based on free choice profiling methodology (FCP), which gives observers complete freedom to choose their own descriptive terms. Data were analysed with generalised Procrustes analysis (GPA), a multivariate statistical technique associated with FCP. A cross-validation of the outcomes of this approach to data recorded through quantitative behaviour analysis, and through a questionnaire given to the animals' owner/riding instructor, was also performed using principal component analysis (PCA). Twelve undergraduate students generated their own descriptive vocabularies, by watching 20 horse/pony video clips lasting 2.5 min each. GPA showed that the consensus profile explained a high percentage of variation among the 12 observers, and differed significantly from the mean randomised profile (p < 0.001). Two main dimensions of the consensus profile were identified, explaining 60% and 5.2% of the variation between animals, respectively. The 12 observer word charts interpreting these dimensions were semantically consistent, as they all converged towards the same meaning, albeit using different terms. The most used term to describe the positive end of axis 1 was “quiet”, whereas “attentive” was the best positive descriptor of axis 2. The most frequently used descriptors for the negative ends of axes 1 and 2 were “nervous” and “bored”, respectively. Thus, axis 1 was labelled as “quiet/nervous” and axis 2 was named as “attentive/bored”. A marked effect of animal category was observed on the scores of the animals on the first dimension (p < 0.001). Horses received significantly higher scores, and were thus assessed as more quiet and calm, than ponies. Conversely, ponies tended to receive lower scores on the second dimension (p < 0.12), therefore they appeared less curious and attentive. The results of the PCA showed that the variables from different types of measurement clearly had meaningful relationships. For instance, the variables with the highest loading on the positive end of axis 1 were all indicative of tractable and docile animals, whereas axis 2 showed high loadings on the positive end for variables indicating attentive animals. Qualitative behaviour assessment proved to be an appropriate methodology for the study of horse behavioural responsiveness, in that it provided a multifaceted characterisation of horse behavioural expression that was in agreement with other quantitative and subjective assessments of the animals' behaviour.

Abstract: The aim of this study was to test the existence of a “reactivity-to-humans” trait which is stable over time and across situations. For this purpose, four test situations were repeated on the same animals at 8 months, 1.5 years (N = 110 horses) and 2.5 years of age (N = 54 horses). These situations involved a “familiar passive human test” during which a familiar person stayed motionless in the test pen, a “familiar active human test” and an “unfamiliar active human test” during which a familiar or unfamiliar person attempted to touch the horse, and a “halter-fitting and heart-rate measurement test”, during which the horse was haltered and equipped with a surcingle and then had its heart-rate measured. Many behavioural variables were recorded during the tests, and correlations between ages and variables measured during other situations were investigated. When correlations were found, we concluded that the variables corresponded to temperament traits which are stable over time and across situations. The horses tested were divided into four groups according to breed (Anglo-Arab and Welsh) and year of birth (2001 and 2002). Data for each group were analysed separately with Spearman rank correlations. Regarding stability over time, there was a strong correlation between ages in the frequency of licking/nibbling the passive human, the time taken by a familiar or unfamiliar person to touch the horse, and the time taken to fit a halter (e.g. the time taken to touch the horse's muzzle was significantly correlated between ages in 7 out of the 8 possible cases: 0.40 <= R <= 0.67). Regarding stability across situations, results indicate that the more frequently a horse sniffed, licked or nibbled a passive human, the easier it was for either a familiar or unfamiliar active human to touch and halter it. Moreover, a horse which could be touched easily by a familiar human could also be touched and haltered easily by an unfamiliar human. These behaviours, which are linked directly to humans, therefore indicate good stability over time and across situations. In conclusion, this stability suggests the existence of a “reactivity-to-humans” temperament trait, whether the human is passive or active, familiar or unfamiliar. When the animals do not have frequent contact with humans, this reactivity is stable over time and can be measured as early as 8 months of age using the behavioural variables cited above.

Abstract: Social animals live and interact together, forming complex relationships and social structure. These relationships can have important fitness consequences, but most studies do not explicitly measure those relationships. An approach that explicitly measures relationships will further our understanding of social complexity and the consequences of both direct and indirect interactions. Social network analysis is the study of social groups as networks of nodes connected by social ties. This approach examines individuals and groups in the context of relationships between group members. Application of social network analysis to animal behaviour can advance the field by identifying and quantifying specific attributes of social relationships, many of which are not captured by more common measures of sociality, such as group size. Sophisticated methods for network construction and analysis exist in other fields, but until recently, have seen relatively little application to animal systems. We present a brief history of social network analysis, a description of basic concepts and previous applications to animal behaviour. We then highlight relevance and constraints of some network measures, including results from an original study of the effect of sampling on network parameter estimates, and we end with promising directions for research. By doing so, we provide a prospective overview of social network analysis' general utility for the study of animal social behaviour.