EVI and NDVI as proxies for multifaceted avian diversity in urban areas
Type
Journal article
Language
English
Date issued
2023
Author
Benedetti, Yanina
Callaghan, Corey T.
Ulbrichová, Iva
Galanaki, Antonia
Kominos, Theodoros
Abou Zeid, Farah
Ibáñez‐Álamo, Juan Diego
Suhonen, Jukka
Díaz, Mario
Markó, Gábor
Bussière, Raphaël
Bukas, Nikos
Mägi, Marko
Leveau, Lucas
Pruscini, Fabio
Jerzak, Leszek
Ciebiera, Olaf
Jokimäki, Jukka
Kaisanlahti‐Jokimäki, Marja‐Liisa
Møller, Anders Pape
Morelli, Federico
Faculty
Wydział Medycyny Weterynaryjnej i Nauk o Zwierzętach
Journal
Ecological Applications
ISSN
1051-0761
Volume
33
Number
3
Pages from-to
e2808
Abstract (EN)
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.
License
Closed Access