Publication Details |
| Category | Text Publication |
| Reference Category | Journals |
| DOI | 10.1111/cobi.70234 |
Licence  |
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| Title (Primary) | Harnessing social media data to track species range shifts |
| Author | Chowdhury, S.; Hawladar, N.; Roy, R.C.; Capinha, C.; Cassey, P.; Correia, R.A.; Deme, G.G.; Di Marco, M.; Di Minin, E.; Jarić, I.; Ladle, R.J.; Lenoir, J.; Momeny, M.; Rinne, J.J.; Roll, U.; Bonn, A.
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| Source Titel | Conservation Biology |
| Year | 2026 |
| Department | iDiv; BioP |
| Page From | e70234 |
| Language | englisch |
| Topic | T5 Future Landscapes |
| Data and Software links | https://doi.org/10.15468/dl.wq7282 |
| Supplements | Supplement 1 Supplement 2 Supplement 3 |
| Keywords | biodiversity shortfall; citizen science; Facebook; Flickr; iEcology; invasive species; range shift; social media |
| Abstract | Biodiversity monitoring programs and citizen science data
remain heavily biased toward the Global North. Especially in
megadiverse countries with limited biodiversity records, incorporating
social media data can help address existing data gaps. However, whether
such data can significantly improve our understanding of range-shifting
species is still unknown. We tested whether social media data improved
our knowledge of the range dynamics of a rapid range-shifting butterfly,
the tawny coster (Acraea terpsicore). We collated locality data
from Flickr and Facebook and compared these with occurrence data from
the Global Biodiversity Information Facility (GBIF). We used species
distribution models (SDMs) and niche assessments, which we calibrated
with data from GBIF alone and both sources combined (GBIF and social
media data) to analyze range shift dynamics. Social media data increased
occurrence records by 35%, and the proportion of social media data was
higher in countries poorly represented in GBIF. In addition, we obtained
new distributional information from well-represented countries (e.g.,
Australia and Malaysia). Over time, the SDMs calibrated with GBIF and
social media data showed greater expansion rates than SDMs based solely
on GBIF data. The niche assessments revealed that GBIF-only data failed
to capture regions with relatively low maximum temperature, relatively
low precipitation and high elevation. Our results highlight the
potential of harnessing social media data to track rapid biodiversity
redistribution in response to climate change. |
| Chowdhury, S., Hawladar, N., Roy, R.C., Capinha, C., Cassey, P., Correia, R.A., Deme, G.G., Di Marco, M., Di Minin, E., Jarić, I., Ladle, R.J., Lenoir, J., Momeny, M., Rinne, J.J., Roll, U., Bonn, A. (2026): Harnessing social media data to track species range shifts Conserv. Biol. , e70234 10.1111/cobi.70234 |
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