Abstract: Learning through the observation of others allows the transfer of information without the costs incurred during individual trial and error learning. Horses (Equus caballus) are a highly social species, which might be expected to be capable of learning from others, but experimental findings are inconsistent, and potentially confounded by social facilitation effects not related directly to the learning of the task. We refined the methods used in previous equine social learning studies, to examine and distinguish specific social influences on learning of a task: we used predefined group leaders rather than agonistically dominant individuals to demonstrate a detour task to familiar conspecific observers; in addition we had two control groups: a non-observer (true control) and a group with the demonstrator simply present at the goal (social facilitation control). 44 socially kept horses were allocated to one of the three test conditions and took part in five trials each. Success rate, latency and detour direction were recorded. There was no significant difference between the three groups in the likelihood of them succeeding in the task nor latency to succeed; however there was a significant difference in the route chosen by the groups, with the true control choosing the side with the entrance gate significantly more than either the observer group or social facilitation group. Both of the latter two groups chose to go in the same direction relative to themselves, regardless of which side the gate was. Seven out of nine horses in the observer group chose the same direction as their demonstrator every time. Our results show a significant role of social facilitation on detour behaviour and highlight the importance of including adequate controls for simpler cognitive influences on behaviour before claims can be made about the specific learning of motor actions or goal directed behaviour. Social cues may be important to horses if the task is sufficiently challenging and motivationally important, so future work should consider more demanding, but ecologically relevant situations, in order to maximise the potential revelation of social learning effects which do not depend on simple local or stimulus enhancement effects.

Abstract: Since the first sporadic occurrences of grey wolves (Canis lupus) west of the Polish border in 1996, wolves have shown a rapid population recovery in Germany. Wolves are known to avoid people and wolf attacks on humans are very rare worldwide. However, the subjectively perceived threat is considerable, especially as food-conditioned habituation to humans occurs sporadically. Lower Saxony (Germany) has an exceedingly higher human population density than most other regions with territorial wolves; thus, the potential for human-wolf conflicts is higher. Using hunters' wildlife survey data from 455 municipalities and two years (2014-2015) and data from the official wolf monitoring (557 confirmed wolf presences and 500 background points) collected between 2012-2015, grey wolf habitat selection was modelled using generalized additive models with respect to human population density, road density, forest cover and roe deer density. Moreover, we tested whether habitat use changed in response to human population and road density between 2012/2013 and 2014/2015. Wolves showed a preference for areas of low road density. Human population density was less important as a covariate in the model of the survey data. Areas with higher prey abundance (5-10 roe deer/km2) and areas with >20% forest cover were preferred wolf habitats. Wolves were mostly restricted to areas with the lowest road and human population densities. However, between the two time periods, avoidance of human density decreased significantly. Recolonization of Germany is still in its early stages and it is unclear where this process will halt. To-date authorities mainly concentrate on monitoring measures. However, to avoid conflict, recolonization will require more stringent management of wolf populations and an improved information strategy for rural populations.

Abstract: Understanding the factors that influence horse learning is critical to ensure horse welfare and rider safety. In this study, data were obtained from horses (n=96) training to step backwards through a corridor in response to bit pressure. Following training, learning ability was determined by the latency to step backwards through the corridor when handled on the left and right reins. Additionally, horse owners were questioned about each horse's management, training, behavior and signalment (such as horse breed, age and sex). Factors from these four broad domains were examined using a multiple logistic regression (MLR) model, following an Information Theoretic approach, for associations between horses' behavioral attributes and their ability to learn the task. The MLR also included estimates of the rider's ability and experience as well as owner's perceptions of their horse's trainability and temperament. Results revealed several variables including explanatory variables that correlated significantly with rate of learning. Horses were faster at backing, a behavioral trait, when handled on the right (t = 3.65, df = 94, P < 0.001) than the left side. Thoroughbred horses were slower at completing the tests than other breeds of horses when handled on the left side (LM, F1,48=4.5, P=0.04) and right side (LM, F1,45=6.0, P=0.02). Those in regular work, a training factor, did not learn faster than their unworked counterparts on the right rein but completed the task faster on the left rein (F1,44=5.47, P=0.02). This may reflect differences in laterality and habituation effects. In contrast, more anxious horses were faster at completing the test when handled from the right (Spearman, r=-0.22, P=0.04). It is possible that these horses have an increased arousal level when interacting with handlers, resulting in more engagement with the lesson, accounting for the improved performance results. The findings of this study will help clarify how horse behavior, training and management may influence learning and how their application may optimize learning outcomes. Future equine behavior assessment and research questionnaires should include items that assess these qualities.

Abstract: In this essay we outline how video-related technology can be used as a tool for studying animal behaviour. We review particular aspects of novel, innovative animal behaviour uploaded by the general public via video-based media on the internet (using YouTube as a specific example). The behaviour of animals, particularly the play behaviour focused on here, is viewed by huge audiences. In this essay we focused on three different kinds of media clips: (1) interspecies play between dogs and a range of other species; (2) object play in horses; and (3) animal responses to stimuli presented on iPads, iPods and iPhones. We argue that the use of video is a good means of capturing uncommon or previously unknown behaviour, providing evidence that these behaviours occur. Furthermore, some of the behaviours featured on YouTube provide valuable insights for future directions in animal behaviour research. If we also take this opportunity to convey our knowledge to a public that seems to be fundamentally interested in animal behaviour, this is a good means of bridging the gap between knowledge among an academic few and the general public.

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.