Mangrove forests are significant blue carbon pools on the Earth with strong carbon sequestration capacity and play an important role in combating climate change. To improve the capacity of regional carbon sinks, China has implemented a Special Action Plan for Mangrove Protection and Restoration (2020–2025). In this context, based on the MaxEnt model, this study analyzed the important environmental factors affecting the distribution of mangrove forests, combined with the planning objectives and carbon density parameters of different regions; assessed the habitat suitability areas of China’s mangrove forests; and predicted their future carbon stock potential. The results showed the following: (1) Elevation was the most important factor affecting the overall distribution of mangrove forests in China, and the optimal elevation of mangrove distribution was 0.52 m. (2) The most suitable areas of mangrove forests in China were mainly distributed in Hainan, Guangxi, and Guangdong, which had great potential for carbon stock. Danzhou Bay and Hongpai Harbor in Hainan, Lianzhou Bay in Guangxi, and the Huangmao Sea in Guangdong are potential areas for habitat suitability but are not yet under high levels of protection. (3) Achieving the goals of this action plan was expected to increase carbon stocks by 4.13 Tg C. Other suitable areas not included in this plan could still increase carbon stocks by 7.99 Tg C in the long term. The study could provide a scientific basis for siting mangrove restoration areas and developing efficient management policies.

This paper evaluated the latest version 6.0 Global Satellite Mapping of Precipitation (GSMaP) and version 6.0 Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) products during 2018 Typhoon Mangkhut in China. The reference data is the rain gauge datasets from Gauge-Calibrated Climate Prediction Centre (CPC) Morphing Technique (CMORPHGC). The products for comparison include the GSMaP near-real-time, Microwave-IR merged, and gauge-calibrated (GSMaP_NRT, GSMaP_MVK, and GSMaP_Gauge) and the IMERG Early, Final, and Final gauge-calibrated (IMERG_ERUncal, IMERG_FRUncal, and IMERG_FRCal) products. The results show that (1) both GSMaP_Gauge and IMERG_FRCal considerably reduced the bias of their satellite-only products. GSMaP_Gauge outperforms IMERG_FRCal with higher Correlation Coefficient (CC) values of about 0.85, 0.78, and 0.50; lower Fractional Standard Error (FSE) values of about 18.00, 18.85, and 29.30; and Root-Mean-Squared Error (RMSE) values of about 12.12, 33.35, and 32.99 mm in the rainfall centers over mainland China, southern China, and eastern China, respectively. (2) GSMaP products perform better than IMERG products, with higher Probability of Detection (POD) and Critical Success Index (CSI) and lower False Alarm Ratio (FAR) in detecting rainfall occurrence, especially for high rainfall rates. (3) For area-mean rainfall, IMERG performs worse than GSMaP in the rainfall centers over mainland China and southern China but shows better performance in the rainfall center over eastern China. GSMaP_Gauge and IMERG_FRCal perform well in the three regions with a high CC (0.79 vs. 0.94, 0.81 vs. 0.96, and 0.95 vs. 0.97) and a low RMSE (0.04 vs. 0.06, 0.40 vs. 0.59, and 0.19 vs. 0.34 mm). These useful findings will help algorithm developers and data users to better understand the performance of GSMaP and IMERG products during typhoon precipitation events.

The “Two Mountains” concept of “green water and green mountains are gold and silver mountains” plays an important value-oriented role in the ecological transformation of land consolidation. In this study, Guangxi was divided into five consolidation zones in combination with relevant policies, and the evolution characteristics and change intensity of ecological-economic values before and after the three phases of land consolidation in Guangxi and each consolidation zone in 2010, 2015 and 2020 were explored by bivariate spatial autocorrelation, standard deviation ellipse, and linear regression equation. Finally, the ecological-economic values of each consolidation area, which were obtained separately, were standardized by z-score, and the standardized results were matched by dividing quadrants for analysis. The ecological-economic value matching states of each consolidation area are ecological-economic value coordinated development type (central karst basin area of Guangxi), ecological value imbalance type (southeast plain area and coastal hilly plain area of Guangxi), economic value imbalance type (northwest mountain area of Guangxi) and ecological-economic value low imbalance type (northeast hilly mountain area of Guangxi). The study aims to provide a theoretical basis for the planning and differentiated management of land consolidation in Guangxi and promote the ecological-economic value transformation of the region.

The strategic delineation of ecological corridors and establishment of robust ecological security frameworks constitute fundamental prerequisites for advancing ecologically balanced growth and premium development within the Pinglu Canal Economic Belt. In this study, a comprehensive framework integrating ecological sources, resistance surfaces, and ecological corridors was developed using the InVEST model combined with circuit theory. The framework was then applied to assess the spatial and temporal dynamics of four major ecosystem services over the period from 2000 to 2020. The main findings are as follows: (1) From 2000 to 2020, the values of the four ecosystem services showed an overall declining trend. Spatially, areas with high ecosystem service importance were mainly concentrated in woodland and grassland areas in the southwest and northwest of the region. (2) The resistance values of the study area’s resistance surface ranged from 1 to 4.83. High-resistance areas were primarily located in the central region, corresponding to areas of intense human activity, while low-resistance areas were distributed around the periphery and largely overlapped with ecological source areas, presenting a spatial pattern of “high in the center, low at the edges”. (3) In total, 119 ecological barriers, 28 corridors, 8 critical pinch points, and 16 habitat source areas were identified. Building on these results, an enhanced ecological security layout—defined by the ‘three belts and three zones’ strategy—was formulated to guide restoration efforts and inform ecological management across the Pinglu Canal Economic Region.