Literature DB >> 29649758

Association between nighttime artificial light pollution and sea turtle nest density along Florida coast: A geospatial study using VIIRS remote sensing data.

Zhiyong Hu1, Hongda Hu2, Yuxia Huang3.   

Abstract

Artificial lighting at night has becoming a new type of pollution posing an important anthropogenic environmental pressure on organisms. The objective of this research was to examine the potential association between nighttime artificial light pollution and nest densities of the three main sea turtle species along Florida beaches, including green turtles, loggerheads, and leatherbacks. Sea turtle survey data was obtained from the "Florida Statewide Nesting Beach Survey program". We used the new generation of satellite sensor "Visible Infrared Imaging Radiometer Suite (VIIRS)" (version 1 D/N Band) nighttime annual average radiance composite image data. We defined light pollution as artificial light brightness greater than 10% of the natural sky brightness above 45° of elevation (>1.14 × 10-11 Wm-2sr-1). We fitted a generalized linear model (GLM), a GLM with eigenvectors spatial filtering (GLM-ESF), and a generalized estimating equations (GEE) approach for each species to examine the potential correlation of nest density with light pollution. Our models are robust and reliable in terms of the ability to deal with data distribution and spatial autocorrelation (SA) issues violating model assumptions. All three models found that nest density is significantly negatively correlated with light pollution for each sea turtle species: the higher light pollution, the lower nest density. The two spatially extended models (GLM-ESF and GEE) show that light pollution influences nest density in a descending order from green turtles, to loggerheads, and then to leatherbacks. The research findings have an implication for sea turtle conservation policy and ordinance making. Near-coastal lights-out ordinances and other approaches to shield lights can protect sea turtles and their nests. The VIIRS DNB light data, having significant improvements over comparable data by its predecessor, the DMSP-OLS, shows promise for continued and improved research about ecological effects of artificial light pollution.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Eigenvectors spatial filtering; GIS; Generalized estimating equations; Generalized linear model; Light pollution; Remote sensing; Sea turtle; Spatial statistics; VIIRS

Mesh:

Year:  2018        PMID: 29649758     DOI: 10.1016/j.envpol.2018.04.021

Source DB:  PubMed          Journal:  Environ Pollut        ISSN: 0269-7491            Impact factor:   8.071


  3 in total

1.  Investigating the Spatiotemporal Variability and Driving Factors of Artificial Lighting in the Beijing-Tianjin-Hebei Region Using Remote Sensing Imagery and Socioeconomic Data.

Authors:  Wanchun Leng; Guojin He; Wei Jiang
Journal:  Int J Environ Res Public Health       Date:  2019-06-01       Impact factor: 3.390

2.  Assessing the indoor air quality and their predictor variable in 21 home offices during the Covid-19 pandemic in Norway.

Authors:  M Justo Alonso; T N Moazami; P Liu; R B Jørgensen; H M Mathisen
Journal:  Build Environ       Date:  2022-09-08       Impact factor: 7.093

Review 3.  Artificial Light at Night (ALAN): A Potential Anthropogenic Component for the COVID-19 and HCoVs Outbreak.

Authors:  Zeeshan Ahmad Khan; Thangal Yumnamcha; Gopinath Mondal; Sijagurumayum Dharmajyoti Devi; Chongtham Rajiv; Rajendra Kumar Labala; Haobijam Sanjita Devi; Asamanja Chattoraj
Journal:  Front Endocrinol (Lausanne)       Date:  2020-09-10       Impact factor: 5.555

  3 in total

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