Ecosystems in protected areas (PAs) are facing new challenges from light pollution. Timely assessment of light pollution in protected areas and exploration of its characteristics are positively valuable for biodiversity conservation and sustainable development. As the province with the largest number of nature reserves and the richest biodiversity in China, Guangdong’s protected areas have faced more severe light pollution threats in recent years along with rapid urbanization. Hence, in this study, the temporal trends and spatial distribution of light pollution changes, the correlation between light pollution and human activities, and the sensitive distance induced by light pollution in PAs of Guangdong Province from 2000 to 2018 were analyzed based on nighttime light (NTL) remote sensing data, land-use data, and POI data. The results show that: (1) Overall, the light pollution within the PAs increased significantly in these years, with the mean value of NTL (MNTL) increasing from 8.04 to 15.21 nanoWatt/cm²/sr. The number of PAs affected by light pollution was 900 in 2018, accounting for 83% of the total. (2) From the perspective of spatial distribution, the PAs in the Pearl River Delta suffered from the highest intensity of light pollution. Specifically, the MNTL of PAs within the Pearl River Delta was 5.8 times and 2.8 times higher than that in northern Guangdong in 2000 and 2018, respectively. (3) There is a significant correlation between human activities and NTL in PAs within 100 km, and the most sensitive distance is within 40 km, especially the sensitivity within 20 km is much higher than that between 30–40 km. The findings of this study will provide a reference for the implementation of external lighting control and guidance measures to mitigate light pollution in protected areas in Guangdong Province.

The relationship between export variety and economic growth has been paid much attention in academia. This paper discusses more deeply the relationship between export related and unrelated variety and economic growth, rather than mere export variety. This paper uses the entropy measurement method to measure the level of export variety of Chinese cities and use the concept of “proximity” proposed by Hidalgo to divide the related variety and unrelated variety. Using the panel data of 252 prefecture-level cities in China from 2000 to 2011, we attempt to explore the relationship between export variety, related and unrelated variety and urban economic growth. The empirical results show that it is not export variety as such, but related and unrelated variety that has effects on economic growth. Export related variety has a positive effect on economic growth, while unrelated variety has a negative effect. And there are obvious regional and size differences. The impact of export related and unrelated variety on eastern and coastal cities is greater than that on central and inland cities, and the impact on large-size cities is also greater than that on medium-size cities.