Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Prague, Czech Republic.
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
Ecol Appl. 2023 Apr;33(3):e2808. doi: 10.1002/eap.2808. Epub 2023 Feb 9.
Most ecological studies use remote sensing to analyze broad-scale biodiversity patterns, focusing mainly on taxonomic diversity in natural landscapes. One of the most important effects of high levels of urbanization is species loss (i.e., biotic homogenization). Therefore, cost-effective and more efficient methods to monitor biological communities' distribution are essential. This study explores whether the Enhanced Vegetation Index (EVI) and the Normalized Difference Vegetation Index (NDVI) can predict multifaceted avian diversity, urban tolerance, and specialization in urban landscapes. We sampled bird communities among 15 European cities and extracted Landsat 30-meter resolution EVI and NDVI values of the pixels within a 50-m buffer of bird sample points using Google Earth Engine (32-day Landsat 8 Collection Tier 1). Mixed models were used to find the best associations of EVI and NDVI, predicting multiple avian diversity facets: Taxonomic diversity, functional diversity, phylogenetic diversity, specialization levels, and urban tolerance. A total of 113 bird species across 15 cities from 10 different European countries were detected. EVI mean was the best predictor for foraging substrate specialization. NDVI mean was the best predictor for most avian diversity facets: taxonomic diversity, functional richness and evenness, phylogenetic diversity, phylogenetic species variability, community evolutionary distinctiveness, urban tolerance, diet foraging behavior, and habitat richness specialists. Finally, EVI and NDVI standard deviation were not the best predictors for any avian diversity facets studied. Our findings expand previous knowledge about EVI and NDVI as surrogates of avian diversity at a continental scale. Considering the European Commission's proposal for a Nature Restoration Law calling for expanding green urban space areas by 2050, we propose NDVI as a proxy of multiple facets of avian diversity to efficiently monitor bird community responses to land use changes in the cities.
大多数生态研究使用遥感技术来分析大范围的生物多样性模式，主要集中在自然景观中的分类多样性上。城市化水平高的一个最重要影响是物种丧失（即生物均质化）。因此，需要经济高效且更有效的方法来监测生物群落的分布。本研究探讨了增强型植被指数（EVI）和归一化差异植被指数（NDVI）是否可以预测多方面的鸟类多样性、城市耐受性和城市景观中的专业化。我们在 15 个欧洲城市中采样鸟类群落，并使用 Google Earth Engine（32 天的 Landsat 8 一级数据集）提取鸟类样本点 50 米缓冲区像素的 30 米分辨率 EVI 和 NDVI 值。混合模型用于寻找 EVI 和 NDVI 的最佳关联，预测多个鸟类多样性方面：分类多样性、功能多样性、系统发育多样性、专业化水平和城市耐受性。在 10 个不同的欧洲国家的 15 个城市中，共检测到 113 种鸟类。EVI 均值是觅食基质专业化的最佳预测因子。NDVI 均值是大多数鸟类多样性方面的最佳预测因子：分类多样性、功能丰富度和均匀度、系统发育多样性、系统发育物种变异性、群落进化独特性、城市耐受性、饮食觅食行为和栖息地丰富度专家。最后，EVI 和 NDVI 标准差不是任何研究的鸟类多样性方面的最佳预测因子。我们的研究结果扩展了以前关于 EVI 和 NDVI 作为大陆尺度鸟类多样性替代物的知识。考虑到欧盟委员会提出的自然恢复法提案，要求到 2050 年扩大绿色城市空间面积，我们建议使用 NDVI 作为鸟类多样性的多个方面的代理，以有效地监测城市土地利用变化对鸟类群落的响应。
