Abstract: Monitoring wolves (Canis lupus) is a difficult and often expensive task due to high mobility,pack dynamic, shyness and nocturnal activity of this species. Wolves communicate acoustically trough howling, within pack and with packs of the neighbourhood. A wolf howl is a low frequency vocalization that can be transmitted over long distances and thus be used
for monitoring tasks. Animated howling survey is a current method to monitor wolves indifferent areas all over the world. Animated howling, however, may be invasive to residential wolf packs and could create possible negative reactions from local human population. Here we show that it is possible to detect wolves by recording spontaneous howling events. We measured the sound pressure level of wolf howls on captive individuals and we further found that simulated howling may be recorded and clearly identified up to a distance of 3 km. We finally conducted non-invasive acoustic detection of wolves in a free ranging population. The use of passive sound recorders may provide a powerful non-invasive tool for future wolf monitoring and thus help to established sustainable management plans for this species.

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.