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As the world's largest reactive carbon reservoir, the ocean plays a critical role in global climate change. Among coastal plant ecosystems, mangroves have the highest carbon storage efficiency and are prone to the impact of anthropogenic activities. In this study, taking the mangrove wetland of Qinglan Bay as an example, we extracted information on mangrove coastal surface change from 1988 to 2020 based on multi-temporal Landsat remote sensing data through field ground surveys and laboratory analysis and used the InVEST model to calculate the spatial and temporal structure of blue carbon in the mangrove area to investigate the effects of mangrove change in an ecological restoration context. The result shows that the overall area of mangrove forests exhibited a decreasing trend from 1988 to 2020, and the area of mangroves decreased from 1559.34 ha to 737.37 ha of which 52.71% was transformed into aquiculture, construction, and farm land. Accordingly, the mangrove carbon sinks from 1988 to 2020 were significantly reduced and the carbon stock decreased at an annual tendency from 1,025,901.71 tons to 712,118.69 tons. With the implementation of mangrove restoration, the decline of mangrove forests has decreased since 2003, promoting the stabilization and enhancement of carbon sinks in the mangrove wetlands of Qinglan Bay. The results of this study provide a technical method to evaluate the carbon sink contribution of mangrove wetland restoration in Hainan Province, a scientific basis and methodological innovation to monitor the carbon sink of mangrove cover change in larger regions of China, a theoretical basis to select criteria for mangrove restoration, and a scientific and systematic management strategy for ecological and mangrove restoration on Hainan Island. [ABSTRACT FROM AUTHOR]

Aim: Mangrove forests are important coastal wetlands for the blue carbon budget and play a significant role in mitigating global climate change. However, spatial patterns of carbon stocks in mangrove forests on an island scale have not been quantified owing to methodological limitations and lack of understanding of controlling factors. We took the entire Hainan Island as a case study and aimed to carry out a comprehensive investigation of the spatial patterns and driving factors of carbon stocks in mangrove forests. Location: Southern China. Time period: 2017–2020. Major taxa studied: Mangrove forest. Methods: The upscaling method combined with field surveys and Sentinel‐2 imagery analysis were used to compare different models for optimization of mangrove ecosystem carbon stock estimations. We also used structural equation modelling (SEM) to evaluate the factors driving the distributional patterns of mangrove carbon stocks on an island scale. Results: The current total mangrove carbon stock of the entire Hainan Island was estimated to be 703,181 Mg C (with a mean density of 192 Mg C/ha), with the above‐ and below‐ground carbon stocks averaging at 44.7 and 147.3 Mg C/ha, respectively. The mangrove carbon storage in the north‐eastern region of the island was the highest and in the west region the lowest. Sediment nitrogen content and plant species diversity had the most positive driving effects on the distribution of total carbon stock for Hainan Island mangroves. Main conclusions: The combination of field surveys and Sentinel‐2 imagery analysis can be applied to regional‐scale estimations of carbon stocks for mangrove forests. Spatial pattens of mangrove carbon stocks vary among locations on Hainan Island, and soil nutrient (especially nitrogen) availability is the dominant factor regulating carbon stock variations along the land‐to‐sea gradient. Our findings have significant implications for better understanding the distribution of mangrove carbon stocks and quantification of the global blue carbon budget. [ABSTRACT FROM AUTHOR]

Hainan Island is endowed with unique climatic and geographical conditions in China. Green orange is a characteristic fruit and plays an important role in local agricultural production of the island. However, few studies have been available regarding the climatic suitability index of green orange planting suitable regions in the island. Based on 30 years (1980 to 2019) of climatic data from 19 meteorological stations in the island, this study established spatial analysis models with topographical data, land use and GIS spatial analysis. Based on climate suitability function, this study established the climate suitability models of temperature, sunshine, precipitation, accumulated temperature and comprehensive suitability model for green orange planting. The Climate suitability index model for green orange planting suitable zoning areas was developed using a natural point segmentation method, and future climate change scenarios were adopted for evaluating the trends of climate suitable areas. The results revealed that the most suitable areas for planting green orange are mainly located at the eastern central region in the island. The climate suitability index ranged from 0.9 to 1.0 in the most suitable regions. The suitable area is mainly distributed in the eastern part, most of the central and western parts of the island, with the climate suitability index ranging from 0.7–0.9. However, the population density in the area is large, and the planting land is limited. The sub-suitable area is mainly located in the coastal areas of the western island, and the high-altitude areas in the central and western regions of the island, with the climate suitability index varying from 0.4 to 0.7. The unsuitable area is mainly distributed in the central mountainous area, with the climate suitability index being 0.0–0.4. The suitability of temperature showed decreasing trend, and the suitability of precipitation gradually moved from the east to the central region under future climate change scenarios. This study is helpful in promoting the development and utilization of agricultural resources and the fine zoning of green orange planting climate suitability in the island. [ABSTRACT FROM AUTHOR]