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The use of autonomous terrestrial rovers for high resolution light pollution sampling in beach environments

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Date
2018-04-27
Author
Windle, Anna
Advisor
Johnston, David
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Abstract
Nesting sea turtles have been known to actively avoid brightly lit beaches and often turn back to sea prematurely when exposed to artificial light. Observations and experiments have noted that nesting turtles prefer darker areas where structures such as buildings and high dunes act as light barriers. As a result, sea turtles nest primarily on darker beaches, creating spatial concentrations of nests. Artificial nighttime light, or light pollution, has been quantified using a variety of methods. However, it has proven challenging to make accurate assessments of light impact on smaller nesting beaches. Additionally, light has traditionally been measured from stationary tripods perpendicular to beach vegetation, disregarding the view a nesting female experiences. In the present study, nighttime ambient light conditions were assessed on three different nesting beaches in central North Carolina. Using an autonomous terrestrial rover, high resolution light measurements were collected every minute (Sky Quality Meter-LU-DL, Unihedron). Spatial comparisons between ambient light conditions and nesting density at and between these locations revealed the highest densities of nests occurring in regions with lowest light levels, supporting hypotheses that light pollution from coastal development may impact turtle nesting distribution. These results can support ongoing management strategies to mitigate this pressing conservation issue.
Type
Master's project
Department
Nicholas School of the Environment and Earth Sciences
Subject
light pollution; sea turtles; nesting; drones; rover; North Carolina;
Permalink
https://hdl.handle.net/10161/16565
Citation
Windle, Anna (2018). The use of autonomous terrestrial rovers for high resolution light pollution sampling in beach environments. Master's project, Duke University. Retrieved from https://hdl.handle.net/10161/16565.
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.

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