Spatial distribution of citizen science casuistic observations for different taxonomic groups
Spatial distribution of citizen science casuistic observations for different taxonomic groups
复制标题
不同分类群的公民科学因果观察的空间分布
作者：
P. Tiago;Ana Ceia;T. Marques;César Capinha;H. Pereira
机会主义公民科学数据库正在成为收集物种分布信息的重要方式。这些数据在时间和空间上是分散的，并且可能在空间和/或时间上的观测分布偏差方面存在局限性。在这项工作中，我们测试了景观变量对八个分类群的公民科学观测分布的影响。我们使用通过葡萄牙公民科学数据库 (biodiversity4all.org) 收集的数据。我们使用零膨胀负二项式回归将观测分布建模为一组变量的函数，这些变量代表可能影响记录空间分布的景观特征。结果表明，路径密度是最重要的变量，与所考虑的八个分类单元中的七个的观察数量具有统计显着的正相关关系。湿地覆盖率也被确定为与鸟类、两栖动物和爬行动物以及哺乳动物具有显着的正相关关系。我们的结果强调，公民科学项目中物种观察的分布存在空间偏差。更高频率的观测主要是由可及性和水体的存在驱动的。我们的结论是，需要努力提高志愿者采样工作的空间均匀性。
Opportunistic citizen science databases are becoming an important way of gathering information on species distributions. These data are temporally and spatially dispersed and could have limitations regarding biases in the distribution of the observations in space and/or time. In this work, we test the influence of landscape variables in the distribution of citizen science observations for eight taxonomic groups. We use data collected through a Portuguese citizen science database (biodiversity4all.org). We use a zero-inflated negative binomial regression to model the distribution of observations as a function of a set of variables representing the landscape features plausibly influencing the spatial distribution of the records. Results suggest that the density of paths is the most important variable, having a statistically significant positive relationship with number of observations for seven of the eight taxa considered. Wetland coverage was also identified as having a significant, positive relationship, for birds, amphibians and reptiles, and mammals. Our results highlight that the distribution of species observations, in citizen science projects, is spatially biased. Higher frequency of observations is driven largely by accessibility and by the presence of water bodies. We conclude that efforts are required to increase the spatial evenness of sampling effort from volunteers.