School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom.
School of Biosciences, Cardiff University, Cardiff, United Kingdom.
PLoS One. 2021 Aug 18;16(8):e0255416. doi: 10.1371/journal.pone.0255416. eCollection 2021.
Citizen science plays an important role in observing the natural environment. While conventional citizen science consists of organized campaigns to observe a particular phenomenon or species there are also many ad hoc observations of the environment in social media. These data constitute a valuable resource for 'passive citizen science'-the use of social media that are unconnected to any particular citizen science program, but represent an untapped dataset of ecological value. We explore the value of passive citizen science, by evaluating species distributions using the photo sharing site Flickr. The data are evaluated relative to those submitted to the National Biodiversity Network (NBN) Atlas, the largest collection of species distribution data in the UK. Our study focuses on the 1500 best represented species on NBN, and common invasive species within UK, and compares the spatial and temporal distribution with NBN data. We also introduce an innovative image verification technique that uses the Google Cloud Vision API in combination with species taxonomic data to determine the likelihood that a mention of a species on Flickr represents a given species. The spatial and temporal analyses for our case studies suggest that the Flickr dataset best reflects the NBN dataset when considering a purely spatial distribution with no time constraints. The best represented species on Flickr in comparison to NBN are diurnal garden birds as around 70% of the Flickr posts for them are valid observations relative to the NBN. Passive citizen science could offer a rich source of observation data for certain taxonomic groups, and/or as a repository for dedicated projects. Our novel method of validating Flickr records is suited to verifying more extensive collections, including less well-known species, and when used in combination with citizen science projects could offer a platform for accurate identification of species and their location.
公民科学在观察自然环境方面发挥着重要作用。虽然传统的公民科学包括有组织的活动来观察特定的现象或物种,但社交媒体中也有许多对环境的临时观察。这些数据构成了“被动公民科学”的宝贵资源——利用与任何特定公民科学项目都没有联系的社交媒体,但代表了具有生态价值的未开发数据集。我们通过评估照片分享网站 Flickr 上的物种分布来探索被动公民科学的价值。我们将数据与英国最大的物种分布数据集国家生物多样性网络(NBN)图集进行了比较。我们的研究集中在 NBN 上 1500 种代表性最强的物种和英国常见的入侵物种上,并与 NBN 数据的时空分布进行了比较。我们还引入了一种创新的图像验证技术,该技术使用 Google Cloud Vision API 结合物种分类数据来确定 Flickr 上提到的物种代表给定物种的可能性。我们的案例研究的时空分析表明,当只考虑没有时间限制的纯空间分布时,Flickr 数据集最能反映 NBN 数据集。与 NBN 相比,Flickr 上最具代表性的物种是日间花园鸟类,因为它们约有 70%的 Flickr 帖子是相对于 NBN 的有效观察结果。对于某些分类群,被动公民科学可能提供丰富的观测数据来源,或者作为专门项目的存储库。我们验证 Flickr 记录的新方法非常适合验证更广泛的收藏,包括不太知名的物种,并且当与公民科学项目结合使用时,可以为准确识别物种及其位置提供一个平台。