Author:
Zeng Haihang,Jia Mingming,Zhang Rong,Wang Zongming,Mao Dehua,Ren Chunying,Zhao Chuanpeng
Abstract
Mangrove forests are one of the most biologically diverse and productive ecosystems on Earth. They are important breeding and nursing grounds for amphibians, invertebrates, birds, fish, etc. Light pollution may cause serious degradation of biodiversity in the ecosystem. A report of the long-term holistic views of light pollution changes is essential for sustainable management of mangrove ecosystems. However, to date, such studies have rarely been carried out. This study aimed to monitor the long-term light pollution changes of China’s mangrove forests. To achieve this goal, we used time-series nighttime light (NTL) data to build continuous light pollution data. NTL maps made with DMSP-OLS (DNL) or NPP-VIIRS (VNL) are widely utilized in research on human activity. However, DMSP and VIIRS images are different in spatial resolution, radiation resolution, and data saturation. Thus, this study innovatively set an optimal threshold for generating consistent light pollution data in mangrove areas from 1992-2020. The results showed that: (1) the proportion of light-polluted mangrove forests in China increased from 12% in 1992 to 52% in 2020; (2) the largest net increase occurred in Guangxi with an area of 4,086 ha, followed by Guangdong (3,365 ha) and Hainan (2,944 ha); (3) Zhejiang had the largest proportion of net growth (from 0% in 1992 to 99% in 2020), followed by Hainan (66%) and Fujian (59%). Mangrove forests have been protected and restored for decades in China; this study indicates that the establishment of nature reserves is effective in preventing the light pollution of mangroves and provides the first long-term multi-temporal dataset of light pollution in China’s mangrove forests. This comprehensive information could support related studies and facilitate the development of applicable coastal management strategies in China.
Funder
National Natural Science Foundation of China
Youth Innovation Promotion Association of the Chinese Academy of Sciences
Subject
Ocean Engineering,Water Science and Technology,Aquatic Science,Global and Planetary Change,Oceanography
Cited by
6 articles.
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