A1 Refereed original research article in a scientific journal
Using social media records to inform conservation planning
Authors: Chowdhury Shawan, Fuller A. Richard, Ahmed Sultan, Alam Shofiul, Callaghan T. Corey, Das Priyanka, Correia Ricardo A., Marco Di Moreno, Minin Di Enrico, Jarić Ivan, Labi Muzahid Mahzabin, Ladle J. Richard, Rokonuzzaman Md., Roll Uri, Sbragaglia Valerio, Siddika Asma, Bonn Aletta
Publisher: Wiley-Blackwell Publishing, Inc.
Publication year: 2024
Journal: Conservation Biology
Article number: e14161
Volume: 38
Issue: 1
eISSN: 1523-1739
DOI: https://doi.org/10.1111/cobi.14161
Web address : https://doi.org/10.1111/cobi.14161
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/180405502
Citizen science plays a crucial role in helping monitor biodiversity and inform conservation. With the widespread use of smartphones, many people share biodiversity information on social media, but this information is still not widely used in conservation. Focusing on Bangladesh, a tropical megadiverse and mega-populated country, we examined the importance of social media records in conservation decision-making. We collated species distribution records for birds and butterflies from Facebook and Global Biodiversity Information Facility (GBIF), grouped them into GBIF-only and combined GBIF and Facebook data, and investigated the differences in identifying critical conservation areas. Adding Facebook data to GBIF data improved the accuracy of systematic conservation planning assessments by identifying additional important conservation areas in the northwest, southeast, and central parts of Bangladesh, extending priority conservation areas by 4,000–10,000 km2. Community efforts are needed to drive the implementation of the ambitious Kunming–Montreal Global Biodiversity Framework targets, especially in megadiverse tropical countries with a lack of reliable and up-to-date species distribution data. We highlight that conservation planning can be enhanced by including available data gathered from social media platforms.
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