TY - JOUR
T1 - EVI and NDVI as proxies for multifaceted avian diversity in urban areas
AU - Benedetti, Yanina
AU - Callaghan, Corey T.
AU - Ulbrichová, Iva
AU - Galanaki, Antonia
AU - Kominos, Theodoros
AU - Abou Zeid, Farah
AU - Ibáñez-Álamo, Juan Diego
AU - Suhonen, Jukka
AU - Díaz, Mario
AU - Markó, Gábor
AU - Bussière, Raphaël
AU - Tryjanowski, Piotr
AU - Bukas, Nikos
AU - Mägi, Marko
AU - Leveau, Lucas
AU - Pruscini, Fabio
AU - Jerzak, Leszek
AU - Ciebiera, Olaf
AU - Jokimäki, Jukka
AU - Kaisanlahti-Jokimäki, Marja-Liisa
AU - Møller, Anders Pape
AU - Morelli, Federico
N1 - Publisher Copyright:
© 2023 The Ecological Society of America.
PY - 2023/4
Y1 - 2023/4
N2 - 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.
AB - 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.
KW - avian specialization
KW - biodiversity
KW - bird
KW - enhanced vegetation index
KW - normalized difference vegetation index
KW - remote sensing
KW - urban tolerance
KW - VIIRS night-time lights
UR - http://www.scopus.com/inward/record.url?scp=85147698864&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85147698864&partnerID=8YFLogxK
U2 - 10.1002/eap.2808
DO - 10.1002/eap.2808
M3 - Article
AN - SCOPUS:85147698864
SN - 1051-0761
VL - 33
JO - Ecological Applications
JF - Ecological Applications
IS - 3
M1 - e2808
ER -