Abstract: The innovation process is currently undergoing significant change in many industries. The World Wide Web has created a virtual world of collective intelligence and helped large groups of people connect and collaborate in the innovation process [1]. Von Hippel [2], for instance, states that a large number of users of a given technology will come up with innovative ideas. This process, originating in business, is now also being observed in science. Discussions around “Citizen Science” [3] and “Science 2.0” [4] suggest the same effects are relevant for fundamental research practices. “Crowdsourcing” [5] and “Open Innovation” [6] as well as other names for those paradigms, like Peer Production, Wikinomics, Swarm Intelligence etc., have become buzzwords in recent years. However, serious academic research efforts have also been started in many disciplines. In essence, these buzzwords all describe a form of collective intelligence that is enabled by new technologies, particularly internet connectivity. The focus of most current research on this topic is in the for-profit domain, i.e. organizations willing (and able) to pay large sums to source innovation externally, for instance through innovation contests. Our research is testing the applicability of Crowdsourcing and some techniques from Open Innovation to the scientific method and basic science in a non-profit environment (e.g., a traditional research university). If the tools are found to be useful, this may significantly change how some research tasks are conducted: While large, apriori unknown crowds of “irrational agents” (i.e. humans) are used to support scientists (and teams thereof) in several research tasks through the internet, the usefulness and robustness of these interactions as well as scientifically important factors like quality and validity of research results are tested in a systematic manner. The research is highly interdisciplinary and is done in collaboration with scientists from sociology, psychology, management science, economics, computer science, and artificial intelligence. After a pre-study, extensive data collection has been conducted and the data is currently being analyzed. The paper presents ideas and hypotheses and opens the discussion for further input.

Abstract: This study investigated the horse’s contribution to tension in the reins. The experimental hypotheses were that tension in side reins (1) increases biphasically in each trot stride, (2) changes inversely with rein length, and (3) changes with elasticity of the reins. Eight riding horses trotted in hand at consistent speed in a straight line wearing a bit and bridle and three types of side reins (inelastic, stiff elastic, compliant elastic) were evaluated in random order at long, neutral, and short lengths. Strain gauge transducers (240 Hz) measured minimal, maximal and mean rein tension, rate of loading and impulse. The effects of rein type and length were evaluated using ANOVA with Bonferroni post hoc tests. Rein tension oscillated in a regular pattern with a peak during each diagonal stance phase. Within each rein type, minimal, maximal and mean tensions were higher with shorter reins. At neutral or short lengths, minimal tension increased and maximal tension decreased with elasticity of the reins. Short, inelastic reins had the highest maximal tension and rate of loading. Since the tension variables respond differently to rein elasticity at different lengths, it is recommended that a set of variables representing different aspects of rein tension should be reported.

Abstract: Current definitions of horse personality traits are rather vague, lacking clear, universally accepted guidelines for evaluation in performance tests. Therefore, the aim of the present study was to screen behavioural and physiological measurements taken during riding for potential links with scores the same horses received in the official stallion performance test for rideability and personality traits. Behaviour, heart rate (HR) and HR variability from thirty-six stallions participating in a performance test were recorded repeatedly during their performance test training. Using the coefficient of determination, regression analysis revealed that about 1/3 of variation (ranging between r = 0.26 (“constitution” (i.e. fitness, health)) and r = 0.46 (rideability)) in the personality trait scores could be explained by selecting the three most influential behaviour patterns per trait. These behaviour patterns included stumbling (with all traits except character), head-tossing (temperament, rideability), tail-swishing (willingness to work), involuntary change in gait (character) and the rider's use of her/his hands (constitution, rideability), voice (temperament) or whip (constitution). Subsequent mixed model analysis revealed a significant (P < 0.05) influence of the behaviour pattern “horse-induced change in gait” on character (-0.98 ± 0.31 scores per additional occurrence of change in gaits), of head-tossing (-0.25 ± 0.08 scores) and rider's use of voice (-0.51 ± 0.25; P = 0.0594) on temperament, and of stumbling on each of the following: willingness to work (-2.5 ± 1.2), constitution (-2.5 ± 1.2 scores; P = 0.0516) and rideability scores (-3.3 ± 1.4). In addition, constitution scores tended (P = 0.0889) to increase with higher low frequency/high frequency heart rate variation ratios (LF/HF), indicating a shift towards sympathetic dominance and thus a higher stress load in horses with higher scores for constitution. Rideability scores from the training phase were also significantly influenced by head-tossing (-0.5 ± 0.1), and in addition rideability scores from the final test were influenced by the training rider, ranging between average estimated rideability scores of 6.8 ± 0.4 for one training rider and 8.36 ± 0.3 scores for another training rider. Horses ridden with their nose-line predominantly behind the vertical received higher scores for rideability (8.3 ± 0.3) than horses ridden with their nose-line at the vertical (7.7 ± 0.2). These findings indicate that either judges perceive horses to have a better rideability when they readily offer a more extreme poll flexion, or that riders make use of horses’ better rideability by imposing a more extreme poll flexion. Several of the above described associations, but also of the non-existing links (e.g. no association between shying or heart rate and temperament) between behaviour patterns and scores for personality traits are rather surprising, warranting further investigation regarding the underlying causes of these relationships. Some of these behaviour patterns should be considered when redesigning the current guidelines for evaluation of personality traits during breeding horse performance tests, ultimately leading to improved genetic selection for equine personality traits. However, ethical implication of defining aversive behaviour such as head-tossing as an indicator of, for example, poor temperament, should not be neglected when devising new guidelines: such aversive behaviour may in fact be an indication of inadequate training techniques rather than poor horse personality.

Abstract: The traditional way to train horses is by the application of negative reinforcement (NR). In the past few years, however, the use of positive reinforcement (PR) has become more common. To evaluate the effectiveness and the possible stressor effect of the 2 training methods, 12 horses showing severe trailer-loading problems were selected and exposed to trailer-loading. They were randomly assigned to one of the 2 methods. NR consisted of various degrees of pressure (lead rope pulling, whip tapping). Pressure was removed as soon as the horse complied. PR horses were exposed to clicker training and taught to follow a target into the trailer. Heart rate (HR) was recorded every 5 seconds and behavior denoting discomfort was observed using one-zero sampling with 10 seconds sampling intervals. Training was completed when the horse could enter the trailer upon a signal, or was terminated after a maximum of 15 sessions. Of the 12 horses, 10 reached the criterion within the 15 sessions. One horse was eliminated from the study because of illness and 1 PR horse failed to enter the trailer. A Mann-Whitney U-test indicated that the horses trained with NR displayed significantly more discomfort behavior per training session than horses trained with PR (NR: 13.26 ± 3.25; PR: 3.17 ± 8.93, P < 0.0001) and that horses in the PR group spent less time (second) per session to complete the training criterion (NR: 672.9 ± 247.12; PR: 539.81 ± 166.37, P < 0.01). A Mann-Whitney U-test showed that no difference existed in mean HR (bpm) between the 2 groups (NR: 53.06 ± 11.73 bpm; PR: 55.54 ± 6.7 bpm, P > 0.05), but a Wilcoxon test showed a difference in the PR group between the baseline of HR and mean HR obtained during training sessions (baseline PR: 43 ± 8.83 bpm; PR: 55.54 ± 6.7 bpm, P < 0.05). In conclusion, the PR group provided the fastest training solution and expressed less stress response. Thus, the PR procedure could provide a preferable training solution when training horses in potentially stressing situations.

Abstract: Living in complex social systems requires perceptual and cognitive capacities for the recognition of group membership and individual competitors. Olfaction is one means by which this can be achieved. Many animals can identify individual proteins in urine, skin secretions, or saliva by scent. Additionally, marking behaviour in several mammals and especially in horses indicates the importance of sniffing conspecifics’ faeces for olfactory recognition. To test this hypothesis, we conducted two separate experiments: Experiment 1 addressed the question of whether horses can recognise the group membership of other horses by sniffing their faeces. The horses were presented with four faecal samples: (1) their own, (2) those of other members of their own group, (3) those of unfamiliar mares, and (4) those of unfamiliar geldings. Experiment two was designed to assess whether horses can identify the group member from whom a faecal sample came. Here, we presented two groups of horses with faecal samples from their group mates in random distribution. As controls, soil heaps and sheep faecal samples were used. In experiment one, horses distinguished their own from their conspecifics’ faeces, but did not differentiate between familiarity and sex. In experiment two, the horses from both groups paid most attention to the faeces of the horses from which they received the highest amount of aggressive behaviours. We therefore suggest that horses of both sexes can distinguish individual competitors among their group mates by the smell of their faeces.