The field of Audiovisual Biodiversity Research deals with the description, research, and observation of biodiversity using autonomous devices such as bioacoustic methods and camera traps.
Due to the global biodiversity crisis and climatic changes, constant biomonitoring at selected locations is more important than ever for nature conservation e.g., for monitoring of protected or invasive species, control of stocks, or to identify human-nature conflicts. Identifying how wildlife utilizes different habitat types available to them provides key information that can be used to direct management interventions and to determine sustainable land-use practices.
At our research stations in Bolivia and South Africa, we test and develop new methods for long-term monitoring of biodiversity. The first step is simply collecting, documenting, and archiving the data with autonomous devices such as long-term audio recorders and camera traps. The second step is analysis methods, for example with citizen science and artificial intelligence, in order to make this big data usable at all. In the last step, we work on various biological and ecological questions, for example about local biodiversity and biodiversity loss.
Our goal for our WildLIVE! project is to develop a project that acts on the three levels of science, society, and nature conservation. Science documents biodiversity and provides facts about species, and populations, and investigates their threats. Citizen scientists help us by processing data and thus come into contact with science, biodiversity, nature, and sadly in some cases biodiversity loss. However, this research can lead to real-life benefits for nature conservation, for example, the jointly developed results of our long-term observations make the extent of loss clear and provide important information for decision-makers. In addition, the citizen scientists’ newly acquired knowledge of species and their “digital nature experience” can help to initiate social change.
Large volumes of data generated by autonomous devices can be difficult to manage and process timeously. There is also a lack of research data infrastructure available for archiving and cataloguing such “Big Data.” We are working towards developing a collaborative approach that will bring together practitioners, students, citizen scientists, and academics to merge data collection, analysis, archiving, and artificial intelligence.
Autonomous devices today offer a wide range of options for non-invasive nature observation. Using a combination of biomonitoring techniques compensates for detection biases and increases the number of species that can be monitored. For example, camera traps typically target terrestrial animals e.g., carnivores, ungulates, and ground birds, and can assess habitat conditions, whereas acoustic recorders capture vocal species e.g., anurans, bats, birds, and invertebrates. Combining methods allows for multi-scaled assessments of community structures and interactions amongst taxa. Data can then can be used to simultaneously evaluate the abundance, distribution, and behavior of various guilds and trophic levels.
We have already been using this integrative approach to describe new species (alpha taxonomy) by combining different methods, such as morphology, bioacoustics, and molecular data in the taxonomy of the neotropical anurans (frogs).
