Centre for Biodiversity &Environment Research, Department of Genetics, Evolution &Environment, University College London, Gower Street, London WC1E 6BT, UK.
Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK.
Sci Rep. 2016 Sep 13;6:33051. doi: 10.1038/srep33051.
The often opportunistic nature of biological recording via citizen science leads to taxonomic, spatial and temporal biases which add uncertainty to biodiversity estimates. However, such biases may also give valuable insight into volunteers' recording behaviour. Using Greater London as a case-study we examined the composition of three citizen science datasets - from Greenspace Information for Greater London CIC, iSpot and iRecord - with respect to recorder contribution and spatial and taxonomic biases, i.e. when, where and what volunteers record. We found most volunteers contributed few records and were active for just one day. Each dataset had its own taxonomic and spatial signature suggesting that volunteers' personal recording preferences may attract them towards particular schemes. There were also patterns across datasets: species' abundance and ease of identification were positively associated with number of records, as was plant height. We found clear hotspots of recording activity, the 10 most popular sites containing open water. We note that biases are accrued as part of the recording process (e.g. species' detectability) as well as from volunteer preferences. An increased understanding of volunteer behaviour gained from analysing the composition of records could thus enhance the fit between volunteers' interests and the needs of scientific projects.
通过公民科学进行生物记录往往具有机会主义性质，这导致了分类学、空间和时间上的偏差，从而增加了对生物多样性估计的不确定性。然而，这些偏差也可能为志愿者的记录行为提供有价值的见解。我们以大伦敦为例，研究了三个公民科学数据集——来自 Greenspace Information for Greater London CIC、iSpot 和 iRecord——的组成情况，包括记录者的贡献以及空间和分类学偏差，即志愿者何时、何地以及记录了什么。我们发现大多数志愿者只贡献了很少的记录，而且只活跃了一天。每个数据集都有自己的分类学和空间特征，这表明志愿者的个人记录偏好可能会吸引他们参与特定的计划。在不同的数据集之间也存在着模式：物种的丰富度和易于识别性与记录的数量呈正相关，植物的高度也是如此。我们发现了明显的记录活动热点，10 个最受欢迎的地点都含有开阔水域。我们注意到，偏差是在记录过程中积累的（例如物种的可检测性），也是由于志愿者的偏好。通过分析记录的组成来更好地了解志愿者的行为，可以增强志愿者的兴趣与科学项目需求之间的契合度。
