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Mapping behaviorally relevant light pollution levels to improve urban habitat planning.


ABSTRACT: Artificial nighttime lights have important behavioral and ecological effects on wildlife. Combining laboratory and field techniques, we identified behaviorally relevant levels of nighttime light and mapped the extent of these light levels across the city of Chicago. We began by applying a Gaussian finite mixture model to 998 sampled illumination levels around Chicago to identify clusters of light levels. A simplified sample of these levels was replicated in the laboratory to identify light levels at which C57BL/6J mice exhibited altered circadian activity patterns. We then used camera trap and high-altitude photographic data to compare our field and laboratory observations, finding activity pattern changes in the field consistent with laboratory observations. Using these results, we mapped areas across Chicago exposed to estimated illumination levels above the value associated with statistically significant behavioral changes. Based on this measure, we found that as much as 36% of the greenspace in the city is in areas illuminated at levels greater than or equal to those at which we observe behavioral differences in the field and in the laboratory. Our findings provide evidence that artificial lighting patterns may influence wildlife behavior at a broad scale throughout urban areas, and should be considered in urban habitat planning.

SUBMITTER: Schirmer AE 

PROVIDER: S-EPMC6695421 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Mapping behaviorally relevant light pollution levels to improve urban habitat planning.

Schirmer Aaron E AE   Gallemore Caleb C   Liu Ting T   Magle Seth S   DiNello Elisabeth E   Ahmed Humerah H   Gilday Thomas T  

Scientific reports 20190815 1


Artificial nighttime lights have important behavioral and ecological effects on wildlife. Combining laboratory and field techniques, we identified behaviorally relevant levels of nighttime light and mapped the extent of these light levels across the city of Chicago. We began by applying a Gaussian finite mixture model to 998 sampled illumination levels around Chicago to identify clusters of light levels. A simplified sample of these levels was replicated in the laboratory to identify light level  ...[more]

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