Abstract: This paper describes a method in which horses learn to communicate by touching different neutral visual symbols, in order to tell the handler whether they want to have a blanket on or not. Horses were trained for 10-15min per day, following a training program comprising ten steps in a strategic order. Reward based operant conditioning was used to teach horses to approach and touch a board, and to understand the meaning of three different symbols. Heat and cold challenges were performed to help learning and to check level of understanding. At certain stages, a learning criterion of correct responses for 8-14 successive trials had to be achieved before proceeding. After introducing the free choice situation, on average at training day 11, the horse could choose between a “no change” symbol and the symbol for either “blanket on” or “blanket off” depending on whether the horse already wore a blanket or not. A cut off point for performance or non-performance was set to day 14, and 23/23 horses successfully learned the task within this limit. Horses of warm-blood type needed fewer training days to reach criterion than cold-bloods (P<0.05). Horses were then tested under differing weather conditions. Results show that choices made, i.e. the symbol touched, was not random but dependent on weather. Horses chose to stay without a blanket in nice weather, and they chose to have a blanket on when the weather was wet, windy and cold (χ2=36.67, P<0.005). This indicates that horses both had an understanding of the consequence of their choice on own thermal comfort, and that they successfully had learned to communicate their preference by using the symbols. The method represents a novel tool for studying preferences in horses.

Abstract: Generalist predators are expected to shape their diets according to the local availability of prey species. In turn, the extent of consumption of a prey would be influenced by the number of alternative prey species. We have tested this prediction by considering the wild boar and the grey wolf: two widespread species whose distribution ranges overlap largely in Southern Europe, e.g. in Italy. We have reviewed 16 studies from a total of 21 study areas, to assess whether the absolute frequency of occurrence of wild boar in the wolf diet was influenced by (i) occurrence of the other ungulate species in diet and (ii) the number of available ungulate species. Wild boar turned out to be the main prey of the wolf (49% occurrence, on average), followed by roe deer (24%) and livestock (18%). Occurrence of wild boar in the wolf diet decreased with increasing usage of roe deer, livestock, and to a lower extent, chamois and red deer. The number of prey species did not influence the occurrence of wild boar in the wolf diet. The wild boar is a gregarious, noisy and often locally abundant ungulate, thus easily detectable, to a predator. In turn, the extent of predation on this ungulate may not be influenced so much by the availability of other potential prey. Heavy artificial reductions of wild boar numbers, e.g. through numerical control, may concentrate predation by wolves on alternative prey (e.g. roe deer) and/or livestock, thus increasing conflicts with human activities.

Abstract: Abstract— We present a study focused on a quantitative estimation of a human-horse dynamic interaction. A set of measures based on magnitude and phase coupling between heartbeat dynamics of both humans and horses in three different conditions is reported: no interaction, visual/olfactory interaction and grooming. Specifically, Magnitude Squared Coherence (MSC), Mean Phase Coherence (MPC) and Dynamic Time Warping (DTW) have been used as estimators of the amount of coupling between human and horse through the analysis of their heart rate variability (HRV) time series in a group of eleven human subjects, and one horse. The rationale behind this study is that the interaction of two complex biological systems go towards a coupling process whose dynamical evolution is modulated by the kind and time duration of the interaction itself. We achieved a congruent and consistent
statistical significant difference for all of the three indices. Moreover, a Nearest Mean Classifier was able to recognize the three classes of interaction with an accuracy greater than 70%. Although preliminary, these encouraging results allow a discrimination of three distinct phases in a real human-animal interaction opening to the characterization of the empirically proven relationship between human and horse.