Long-term monitoring of citizen science: driving factors and pandemic impacts

Abstract

ABSTRACT In recent years, the importance of citizen science in biodiversity monitoring has become increasingly evident. Citizen science provides valuable data to understand the dynamic changes in biodiversity across different cities. Although long-term monitoring is crucial for understanding these dynamic changes, previous research has primarily focused on short-term data analysis. Therefore, this study analysed data from the iNaturalist platform for 11 Japanese cities from 2016 to 2023, focusing on the driving factors of observation changes and the impact of the COVID-19 pandemic using the Logarithmic Mean Divisia Index (LMDI) method. The results revealed that the population (total number of active users) metric had the greatest impact, followed by intensity (the number of observations per active day), frequency (active days per active user), and structure (proportion of regular users). To ensure data continuity and reliability, optimizing user structure by increasing the proportion of regular users is essential. Although observation volumes fluctuated during the pandemic, they rebounded significantly post-pandemic, demonstrating the resilience, and adaptability of citizen science projects. The iNaturalist platform provides a stable foundation for long-term data collection, aiding in the comprehensive understanding of biodiversity dynamics. Our study also highlighted differences in citizen science participation and biodiversity monitoring across cities, indicating the need for tailored biodiversity conservation policies. To effectively address similar crises in the future, developing contingency plans is recommended to provide continuous support for biodiversity conservation and public engagement in environmental management.