No abstract

Citizen science programs are becoming increasingly popular among naturalists but remain heavily biased taxonomically and geographically. However, with the explosive popularity of social media and the near-ubiquitous availability of smartphones, many post wildlife photographs on social media. Here, we illustrate the potential of harvesting these data to enhance our biodiversity understanding using Bangladesh, a tropical biodiverse country, as a case study. We compared biodiversity records extracted from Facebook with those from the Global Biodiversity Information Facility (GBIF), collating geospatial records for 1013 unique species, including 970 species from Facebook and 712 species from GBIF. Although most observation records were biased toward major cities, the Facebook records were more evenly spatially distributed. About 86% of the Threatened species records were from Facebook, whereas the GBIF records were almost entirely Of Least Concern species. To reduce the global biodiversity data shortfall, a key research priority now is the development of mechanisms for extracting and interpreting social media biodiversity data.

Citizen science programmes are becoming increasingly sophisticated and popular among those with an interest in natural history, but remain the domain of a relatively small portion of the public and heavily biased toward certain areas. Although systematic recording of biodiversity data has been practiced for centuries in the Global North, many tropical nations are still vastly under-surveyed. Yet with the explosive popularity of social media, and the near-ubiquitous availability of smartphone cameras, millions of people are posting photographs on social media daily. Here, we illustrate the potential of harvesting these data to enhance our biodiversity understanding using Bangladesh, a megadiverse South Asian nation, as a case study. We compared biodiversity records extracted from Facebook with those from the Global Biodiversity Information Facility (GBIF) collating geospatial records for 1,013 unique species, including 970 species from Facebook (representing 25% of observation records) and 712 species in GBIF (representing 75% of observation records). While a vast proportion of the combined spatial data were biased towards major cities, Facebook records were more evenly spatially distributed compared to those from GBIF. About 86% of the available distribution records on threatened species were from Facebook, whereas GBIF records were almost entirely of Least Concern species. Our results reveal that social media archives can contain biodiversity data that far eclipses that available from formal databases in terms of volume, and also complements formal data both taxonomically and spatially. A key research priority now is the development of mechanisms for extracting and interpreting social media biodiversity data.

Citizen science plays a crucial role in helping monitor biodiversity and inform conservation. With the widespread use of smartphones, many people share posts that contain biodiversity information on social media, but this information is still not widely used in conservation. Focusing on Bangladesh, a tropical mega‐diverse and mega‐populated country, we examine the importance of social media records in conservation decision‐making. We show that adding Facebook data to the Global Biodiversity Information Facility (GBIF) data improved the accuracy of 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 mega‐diverse 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.This article is protected by copyright. All rights reserved

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. Here, focussing on Bangladesh - a tropical mega-diverse and mega-populated country, we examine the potential importance of social media records in conservation decision-making. We show that adding Facebook data to the Global Biodiversity Information Facility (GBIF) data improved the accuracy of conservation planning assessments by identifying additional important conservation areas in the northwest, southeast and centre parts of Bangladesh, extending priority conservation areas by 2000-5000 km2. Community efforts are needed to drive the implementation of the ambitious Post-2020 protected area targets, especially in mega-diverse 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.