The Ecological Protection Redline (EPR) is an innovative measure implemented in China to maintain the structural stability and functional security of the ecosystem. By prohibiting large-scale urban and industrial construction activities, EPR is regarded as the “lifeline” to ensure national ecological security. It is of great practical significance to scientifically evaluate the protection effect of EPR and identify the protection vacancies. However, current research has focused only on the protection effects of the EPR on ecosystem services (ESs), and the protection effect of the EPR on ecological connectivity remains poorly understood. Based on an evaluation of ES importance, the circuit model, and hotspot analysis, this paper identified the ecological security pattern in Guangdong–Hong Kong–Macao Greater Bay Area (GBA), analyzed the role of EPR in maintaining ES and ecological connectivity, and identified protection gaps. The results were as follows: (1) The ecological sources were mainly distributed in mountainous areas of the GBA. The ecological sources and ecological corridors constitute a circular ecological shelter surrounding the urban agglomeration of the GBA. (2) The EPR effectively protected water conservation, soil conservation, and biodiversity maintenance services, but the protection efficiency of carbon sequestration service and ecological connectivity were low. In particularly, EPR failed to continuously protect regional large-scale ecological corridors and some important stepping stones. (3) The protection gaps of carbon sequestration service and ecological connectivity in the study area reached 1099.80 km² and 2175.77 km², respectively, mainly distributed in Qingyuan, Yunfu, and Huizhou. In future EPR adjustments, important areas for carbon sequestration service and ecological connectivity maintenance should be included. This study provides a comprehensive understanding of the protection effects of EPR on ecological structure and function, and it has produced significant insights into improvements of the EPR policy. In addition, this paper proposes that the scope of resistance surface should be extended, which would improve the rationality of the ecological corridor simulation.

Based on the data obtained in the coastal waters of Shenzhen from the Guangdong Environmental Monitoring Center,the distribution of DIN, DIP were analyzed, and the temporal spatial variations of nutrient level and organic pollution situation were evaluated using methods such as single factor index, eutrophication index,and water organic pollution evaluation index. The results show that the nutrient level of the eastern waters was lower than that of the western. The Dapeng Bay and Daya Bay comply with the first-class seawater standard, the Zhujiang Estuary and Shenzhen Bay exceed the fourth-class seawater standard. And there were some similarities between the eutrophication and organic pollution spatial distribution, and the eutrophication and organic pollution were observed in the western waters. The correlation analysis suggested there was a negatively correlation between salinity and major pollutants (P<0.01), implying the relationship between terrigenous pollution and the content of environmental elements.

Based on the land use data of the study area in 1990, 2000 and 2010, the paper tries to analyse the characteristic of land use and cover change (LUCC) in Pearl River Delta and its driving forces as well as the differences of driving forces among Shenzhen, Dongguan and Foshan by adopting the approaches of land use dynamic degree, the land use transition matrix and case studies. The results show that a large amount of farmland and forests have been converted to construction land in the study area, and the synthesize land use dynamic degrees of the study area are 2.3% and 6.2% during 1990-2000 and 2000-2010, respectively. The results also indicate that Zhuhai and Shenzhen have the highest land use dynamic degree among the nine cities of Pearl River Delta during 1990-2000, and Dongguan has the highest land use dynamic degree during 2000-2010. It can be inferred that the transitions from farmland and forest to construction land have been propelled by the local economic development and population growth, and the land use changes in forest and grassland have been driven by natural factors such as slope and elevation.