Analysis of limiting factors to biodiversity data collection on the citizen science platform iNaturalist

Biodiversity and ecosystem services are in a state of global decline. This is alarming not only for species and ecosystems facing extinction, but also for human populations that are dependent on the services and resources that they provide. Impacts on biodiversity and ecosystems are driven in part from land-use change due to urbanization. Nevertheless, cities provide diverse habitats and are just as important as rural areas in protecting biodiversity. To restore these resources, well-informed policies and actions that safeguard global biodiversity must be implemented. To do so, stakeholders need to understand current baselines and changes to biodiversity over time. This is most effectively done by using primary species occurrence data, such as that collected by citizen science platforms. iNaturalist, a citizen science platform specializing in biodiversity, provides species population and distribution information by enabling users to record species occurrence data. This helps professional scientists by providing data that would be difficult, time consuming, or expensive to attain. Citizen scientists around the globe represent a huge advantage to biodiversity monitoring by providing the human capital needed for such tasks, yet the data collected exhibit taxonomic, spatial, and temporal gaps. These gaps pose a threat to comprehensive and effective biodiversity management and conservation. One main objective of this study is to explore various socio-economic, socio-cultural, and platform characteristic barriers to global biodiversity data collection on iNaturalist, that may contribute to spatial, temporal, and taxonomic data gaps. To do this, a survey questionnaire was distributed on the iNaturalist forum. 149 survey responses from 24 different countries around the world were collected and analysed using descriptive and inferential statistics to summarize and interpret the data. Results of a factor analysis found that income, access to technology, experience, accessibility to transport, and education were significant socio-economic factors related to data collection. Motivation and free time were found to be socio-cultural factors that influence data collection. Platform characteristics were not found to have significance in the context of the survey distributed. The study also found that respondents claim to have little bias towards aesthetically pleasing species. This supports that societal preference, and not species charisma, may be a prominent cause of taxonomic bias and data gaps.