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From Concrete to Canopy: Illuminating Moth Biodiversity in New York City's Urban Jungle

Linsk, S.; Thonis, A.; Winchell, K.

2025-08-28 ecology
10.1101/2025.07.11.663976 bioRxiv
Show abstract

Moths (Lepidoptera) are sensitive to anthropogenic threats and serve as valuable bioindicators. Despite the remarkable diversity and abundance of Lepidoptera globally, there is a lack of information on how moth species are impacted by urbanization. Notably, very little is known about moths in the largest city of the United States, New York City, where pervasive urban pollutants, artificial light at night, land cover change, and habitat fragmentation are severe. We examined the effects of urbanization on moth biodiversity in New York City, with a focus on green spaces. We used citizen science records from iNaturalist and complemented these data with ground sampling at twelve locations across six parks at night. While the iNaturalist dataset is comprehensive both spatially and temporally, it failed to detect rarer species we observed on the ground. However, the scope of the field survey dataset is limited in geographical breadth and seasonal coverage. Overall, we found a negative relationship between greater urbanization and moth diversity, with community similarity correlated with environmental similarity. Our results found greater biodiversity with less light at night and urban development, and more deciduous tree cover and open land. Our structural equation model reveals additional insight: although we detected a strong direct negative effect of developed land on moth diversity, urbanization also negatively impacts diversity via indirect effects of reducing open space and deciduous tree cover. Developed open space alone does not directly affect diversity but may positively impact diversity through its covariance with vegetation cover. These findings support the importance of mitigating artificial light at night in urban green spaces and maintaining urban vegetation to ensure nocturnal Lepidoptera can persist in rapidly urbanizing landscapes.

Published in PLOS ONE (predicted rank #8) · training set

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