Decision-making of citizen scientists when recording species observations

Abstract

Citizen scientists play an increasingly important role in biodiversity monitoring. Most of the data, however, are unstructured—collected by diverse methods that are not documented with the data. Insufficient understanding of the data collection processes presents a major barrier to the use of citizen science data in biodiversity research. We developed a questionnaire to ask citizen scientists about their decision-making before, during and after collecting and reporting species observations, using Germany as a case study. We quantified the greatest sources of variability among respondents and assessed whether motivations and experience related to any aspect of data collection. Our questionnaire was answered by almost 900 people, with varying taxonomic foci and expertise. Respondents were most often motivated by improving species knowledge and supporting conservation, but there were no linkages between motivations and data collection methods. By contrast, variables related to experience and knowledge, such as membership of a natural history society, were linked with a greater propensity to conduct planned searches, during which typically all species were reported. Our findings have implications for how citizen science data are analysed in statistical models; highlight the importance of natural history societies and provide pointers to where citizen science projects might be further developed.

Data Gap or Biodiversity Gap? Evaluating apparent spatial biases in community science observations of Odonata in the east-central United States

“…Our findings agreed with numerous studies supporting the viability of community science in conservation (Lauret et al, 2021;McKinley et al, 2017;Walker et al, 2016) and Odonata biodiversity research (Patten et al, 2019;Rapacciuolo et al, 2017b). However, while inconclusive and of limited spatiotemporal scale, our observations of the data gap region mirror concerns about sampling biases and decision-making in community science that have also been the focus of many other studies (Archer et al, 2014;Bowler et al, 2022;Johnston et al, 2020;Millar et al, 2019;Ruete, 2015).…”

Scope and Challenges of Incorporating Citizen Science into Indian Higher Education Institutions: A Case Study

“…5). Bowler et al (2022) argues that in CS, an insufficient understanding of the processes of data/sample gathering presents a significant barrier in utilizing CS data and suggest harnessing the full potential of CS data, citizen scientists need to be trained to understand better how the data collected through CS approach. Here, the HEIs can play a pivotal role in taking the lead by introducing training modules or short-to full-term courses on CS for on-campus students and off-campus volunteers.…”

Spatial distribution of biodiversity citizen science in a natural area depends on area accessibility and differs from other recreational area use

“…Our results demonstrate that trends in citizen science participants’ behaviour can manifest in spatial patterns, and also suggest new directions that could be followed up with social science research: for instance, it would be useful to survey citizen science participants about their selection of trail routes or their on‐ and off‐trail activity. Importantly, our goal of understanding the distribution of citizen science activity at a local scale responds to a commonly documented motivation for citizen science participation: participants regularly indicate that they want their data to be used for the conservation and management of places that they value (Bowler et al., 2022; Ganzevoort et al., 2017; Larson et al., 2020; Maund et al., 2020). Through facilitation of improved data analysis and citizen science program implementation, a stronger understanding of citizen science activity can be a step toward increasing the local conservation impact of participants’ contributions.…”