Opportunities and limitations: A comparative analysis of citizen science and expert recordings for bioacoustic research

Abstract

Citizen science is an approach that has become increasingly popular in recent years. Despite this growing popularity, there still is widespread scepticism in the academic world about the validity and quality of data from citizen science projects. And although there might be great potential, citizen science is a rarely used approach in the field of bioacoustics. To better understand the possibilities, but also the limitations, we here evaluated data generated in a citizen science project on nightingale song as a case study. We analysed the quantity and quality of song recordings made in a non-standardized way with a smartphone app by citizen scientists and the standardized recordings made with professional equipment by academic researchers. We made comparisons between the recordings of the two approaches and among the user types of the app to gain insights into the temporal recording patterns, the quantity and quality of the data. To compare the deviation of the acoustic parameters in the recordings with smartphones and professional devices from the original song recordings, we conducted a playback test. Our results showed that depending on the user group, citizen scientists produced many to a lot of recordings of valid quality for further bioacoustic research. Differences between the recordings provided by the citizen and the expert group were mainly caused by the technical quality of the devices used—and to a lesser extent by the citizen scientists themselves. Especially when differences in spectral parameters are to be investigated, our results demonstrate that the use of the same high-quality recording devices and calibrated external microphones would most likely improve data quality. We conclude that many bioacoustic research questions may be carried out with the recordings of citizen scientists. We want to encourage academic researchers to get more involved in participatory projects to harness the potential of citizen science—and to share scientific curiosity and discoveries more directly with society.

Improving sightings-derived residency estimation for whale shark aggregations: A novel metric applied to a global data set

“…It is important to understand the limitations of citizen science and ensure any assumptions are met before employing this method (e.g. Bauder et al, 2021;Jäckel et al, 2021).…”

Community engagement and data quality: best practices and lessons learned from a citizen science project on birdsong

“…Our opportunistic approach indeed led to a large collection of geo-referenced nightingale song recordings. We previously showed that the majority of our CS data were valid enough (Jäckel et al 2021 ) and of high value for dialect studies (Jäckel et al 2022 ). The development of the project over three nightingale breeding seasons has not yet been studied.…”

“…Using diverse dissemination activities such as events both inside and outside the MfN, midnight excursions and press coverage, the public was invited to download the 'Naturblick' app on their smartphones and record nightingale songs (for details see Jäckel et al 2021 ). Public events were free of charge, included two to 180 participants and by large took place in Berlin.…”

“…To identify temporal factors for underlying patterns (calendar week and time of day), we descriptively compared the number of nightingale songs and other bird species recorded across all study years. The peak singing time of nightingales (23:00–1:00 h) as reported in the literature (see Jäckel et al 2021 ) and other species of birds (5:00–7:00 h and 19:00–21:00 h) were accounted for to see if they have an influence on the rate of species misidentifications. To understand if and when certain species are most often misidentified as nightingales, we compared recordings from day (04:00–22:00 h) and night (22:00–04:00 h).…”

Key Issues for Realizing Open Ecoacoustic Monitoring in Australia

“…Scaling up ecoacoustics research will require a considerable effort to address the lack of standardization for acoustic data and metadata collection (Roch et al, 2016;Gibb et al, 2019), as well as the development of communities and platforms that enable the sharing of annotated datasets and tested species detection techniques. Enabling acoustic data categorization by citizen scientists also holds great promise (Jäckel et al, 2021). For example, citizen scientists engaging with Hoot Detective [a collaboration between the Australian Acoustic Observatory (A2O), the Australian Broadcasting Commission, Queensland University of Technology, and the University of New England, for National Science Week] have at the time of writing identified 2,624 native owl calls (Noonan, 2021).…”