MacPhail Victoria J, Gibson Shelby D, Hatfield Richard, Colla Sheila R
Faculty of Environmental Studies, York University, Toronto, ON, Canada.
Department of Biology, York University, Toronto, ON, Canada.
PeerJ. 2020 Jun 29;8:e9412. doi: 10.7717/peerj.9412. eCollection 2020.
Community science programs provide an opportunity to gather scientific data to inform conservation policy and management. This study examines the accuracy of community science identifications submitted to the North American Bumble Bee Watch program on a per species level and as compared to each species' conservation status, as well as users (members of the public) and experts (those with expertise in the field of bumble bee biology) perceived ease of species identification. Photos of bumble bees (Hymenoptera: Apidae: ) are submitted to the program by users and verified (species name corrected or assigned as necessary) by an expert. Over 22,000 records from over 4,900 users were used in the analyses. Accuracy was measured in two ways: percent agreement (percent of all records submitted correctly by users) and veracity (percent of all verified records submitted correctly by the users). Users generally perceived it harder to identify species than experts. User perceptions were not significantly different from the observed percent agreement or veracity, while expert perceptions were significantly different (overly optimistic) from the observed percent agreement but not the veracity. We compared user submitted names to final expert verified names and found that, for all species combined, the average percent agreement was 53.20% while the average veracity was 55.86%. There was a wide range in percent agreement values per species, although sample size and the role of chance did affect some species agreements. As the conservation status of species increased to higher levels of extinction risk, species were increasingly more likely to have a lower percent agreement but higher levels of veracity than species of least concern. For each species name submitted, the number of different species verified by experts varied from 1 to 32. Future research may investigate which factors relate to success in user identification through community science. These findings could play a role in informing the design of community science programs in the future, including for use in long-term and national-level monitoring of wild pollinators.
社区科学项目提供了一个收集科学数据的机会，以便为保护政策和管理提供信息。本研究在物种层面上，以及与每个物种的保护状况进行比较的情况下，考察了提交给北美大黄蜂观察项目的社区科学鉴定的准确性，同时也研究了用户（公众成员）和专家（在大黄蜂生物学领域具有专业知识的人员）对物种鉴定的感知难易程度。用户将大黄蜂（膜翅目：蜜蜂科：）的照片提交给该项目，由专家进行核实（必要时纠正或指定物种名称）。分析中使用了来自4900多名用户的超过22000条记录。准确性通过两种方式衡量：一致率（用户正确提交的所有记录的百分比）和准确性（用户正确提交的所有核实记录的百分比）。用户通常认为识别物种比专家更难。用户的感知与观察到的一致率或准确性没有显著差异，而专家的感知与观察到的一致率有显著差异（过于乐观），但与准确性没有显著差异。我们将用户提交的名称与专家最终核实的名称进行了比较，发现所有物种综合起来，平均一致率为53.20%，而平均准确性为55.86%。每个物种的一致率值范围很广，尽管样本量和偶然性确实影响了一些物种的一致性。随着物种的保护状况增加到更高的灭绝风险水平，与最不受到关注的物种相比，这些物种的一致率越来越低，但准确性水平越来越高。对于提交的每个物种名称，专家核实的不同物种数量从1到32不等。未来的研究可以调查哪些因素与通过社区科学进行用户识别的成功相关。这些发现可能会在未来为社区科学项目的设计提供参考，包括用于野生传粉者的长期和国家级监测。
