Department of Avian Biology & Ecology, Faculty of Biology, Adam Mickiewicz University, Poznań, ul. Uniwersytetu Poznańskiego 6, 61 - 614 Poznań, Poland.
Sci Total Environ. 2021 Aug 1;780:146434. doi: 10.1016/j.scitotenv.2021.146434. Epub 2021 Mar 17.
Artificial light at night (ALAN) is currently recognised as an important environmental disturbance that influences habitats, fitness and behaviour of numerous organisms. However, its effect on bird community distribution on a large spatial scale still remains unclear. Therefore, I decided to use a predictive approach to test an assumption that artificial nightlight, as one of 73 predictors, determines taxonomic, functional and phylogenetic levels of an avian community. In order to safeguard inference from any inconsistency, I used not one but four indices describing functional diversity, two measures showing phylogenetic species richness, and one reflecting taxonomic diversity. For all these measures of species communities I developed two sets of Random Forest models: one set included ALAN as an additional predictor, while the other did not. Following cross validation tests as well as an independent evaluation of models, I demonstrated that artificial night light improved the performance of predictive models. Taxonomic species richness decreased linearly along with increasing artificial luminescence. Moreover, functional diversity showed a unimodal relation to ALAN, which meant that most niches were occupied on a moderate level of artificial lighting. Finally, phylogenetic diversity was under the highest pressure of ALAN, because even a minimal amount of artificial night lighting radically reduced this measure of biodiversity. On the basis of predictive maps, I also found that models which did not include urbanisation processes showed high values of avian biodiversity in regions where in fact they were low. Thus, I conclude that ALAN as a human footprint can play a key role when analysing the distribution of bird communities on large spatial scales.
人工夜间灯光（ALAN）目前被认为是一种重要的环境干扰因素，它会影响到许多生物的栖息地、适应性和行为。然而，它对鸟类群落在大空间尺度上的分布的影响仍不清楚。因此，我决定采用预测方法来检验一个假设，即人工夜间灯光作为 73 个预测因子之一，决定了鸟类群落的分类学、功能和系统发育水平。为了确保推断不受任何不一致性的影响，我使用了四个描述功能多样性的指数、两个表示系统发育物种丰富度的度量以及一个反映分类多样性的度量。对于所有这些物种群落的度量，我开发了两组随机森林模型：一组包括 ALAN 作为附加预测因子，另一组则不包括。经过交叉验证测试和模型的独立评估，我证明了人工夜间灯光提高了预测模型的性能。分类学物种丰富度随人工光照的增加呈线性下降。此外，功能多样性与 ALAN 呈单峰关系，这意味着大多数生态位在中等水平的人工光照下被占据。最后，系统发育多样性受到 ALAN 的最大压力，因为即使是少量的人工夜间照明也会极大地降低这一生物多样性的度量。基于预测地图，我还发现，不包括城市化进程的模型在实际上生物多样性较低的地区显示出了较高的鸟类生物多样性值。因此，我得出结论，ALAN 作为人类足迹在分析大空间尺度上鸟类群落的分布时可以发挥关键作用。
