Social media records can reduce tropical biodiversity data gaps and inform conservation

The growing use of community science platforms has led to an exponential increase in biodiversity data stored in global repositories. However, our understanding of species distributions remains patchy. This is primarily due to the fact that biodiversity monitoring programs and citizen science activities remain heavily biased, both taxonomically and geographically, with most data for birds coming from Europe and North America. With the widespread use of smartphones, many people share their biodiversity observations on social media platforms, yet such data remains underutilised in conservation efforts. Incorporating social media data can help fill existing gaps, especially in megadiverse countries with limited records, but whether such data can substantially enhance our understanding of species range shifts is still uncertain. In my presentation, I will discuss how integrating Facebook data can reduce biodiversity data gaps, improve understanding of invasive species distributions, clarify the range dynamics of a highly range-shifting butterfly, and support conservation assessments. We collected species distribution records from Facebook and the Global Biodiversity Information Facility (GBIF), grouping them into GBIF-only and combined (GBIF and Facebook) datasets. We scraped nearly 45,000 unique georeferenced records covering 967 species, with a median of 27 records per species. About 12% of the distribution data related to threatened species, representing 27% of all species. We also gathered data for 56 Data Deficient species in Bangladesh. These findings highlight the importance of using social media data to fill knowledge gaps, track species redistributions, and inform spatial planning under the Kunming–Montreal Global Biodiversity Framework. While most assessments focus on Bangladesh, our method can be adapted for other countries, particularly those lacking detailed biodiversity databases. A key research priority now is to develop methods for extracting and analysing biodiversity data from social media. Community efforts are crucial to achieving the goals of the Kunming–Montreal Global Biodiversity Framework, especially in megadiverse tropical countries that lack current, reliable species distribution data.