Mangrove plantation is a fundamental approach for the sustainable management of tropical and subtropical coasts to capture and store atmospheric carbon. However, it is unknown whether the carbon accumulation potential of planted mangroves is as much as that of natural mangroves. Moreover, the effects of tree species, forest age, and hydrodynamic conditions on carbon storage are still unclear. This study investigated the carbon storage potential and influencing factors for planted mangroves in Kaozhouyang, Huidong County, Guangdong Province. The Vegetation carbon stock was calculated by community parameters collected from field investigation, and ecosystem carbon stock was calculated by the sum of vegetation and sediment. The results showed that mangrove plantation significantly increased the carbon stock of the vegetation and soil (vegetation carbon stock = 9.9645.06 t C/ha; soil carbon stock = 70.37-110.64 t C/ha) compared with the nonvegetation mudflat (63.73 t C/ha). However, the ecosystem carbon stock of the planting sites was still lower than that of natural Avicennia marina (282.86 t C/ha), with the significant difference mainly reflected on the soil carbon stock (p < 0.05). Further results revealed that carbon accumulation was affected by forest age, tree species, and tidal level. The vegetation biomass/carbon stock gradually increased with forest age (p < 0.05), but the difference was not significant for soil carbon stock, which indicated that the carbon accumulation was mainly concentrated on the vegetation at the early stage of mangrove restoration. In addition, suitable habitat conditions (landward) and fast-growing species (Sonneratia apetala) are more beneficial to carbon accumulation. Our results suggest that mangrove plantations can achieve carbon storage and sequestration in vegetation and soil for increasing carbon sinks with suitable species selection and management.

The invasion of Spartina alterniflora (S. alterniflora) has posed serious threats to the sustainability, quality and biodiversity of coastal wetlands. To safeguard coastal ecosystems, China has enacted large-scale S. alterniflora removal projects, which set the goal of effectively controlling S. alterniflora throughout China by 2025. The accurate monitoring of S. alterniflora with remote sensing is urgent and requisite for the scientific eradication, control and management of this invasive plant. In this study, we combined multi-temporal WorldView-2/3 (WV-2/3) and Sentinel-1/2 imagery to monitor the S. alterniflora dynamics before and after the S. alterniflora removal projects in Zhangjiang Estuary. We put forward a new method for S. alterniflora detection with eight-band WV-2/3 imagery. The proposed method first used NDVI to discriminate S. alterniflora from water, mud flats and mangroves based on Ostu thresholding and then used the red-edge, NIR1 and NIR2 bands and support vector machine (SVM) classifier to distinguish S. alterniflora from algae. Due to the contamination of frequent cloud cover and tidal inundation, the long revisit time of high-resolution satellite sensors and the short-term S. alterniflora removal projects, we combined Sentinel-1 SAR time series and Sentinel-2 optical imagery to monitor the S. alterniflora removal project status in 2023. The overall accuracies of the S. alterniflora detection results here are above 90%. Compared with the traditional SVM method, the proposed method achieved significantly higher identification accuracy. The S. alterniflora area was 115.19 hm² in 2015, 152.40 hm² in 2017 and 15.29 hm² in 2023, respectively. The generated S. alterniflora maps clearly show the clonal growth of S. alterniflora in Zhangjiang Estuary from 2015 to 2017, and the large-scale S. alterniflora eradication project has achieved remarkable results with a removal rate of about 90% in the study area. With the continuous implementation of the “Special Action Plan for the Prevention and Control of Spartina alterniflora (2022–2025)” which aims to eliminate more than 90% of S. alterniflora in all provinces in China by 2025, the continual high-spatial resolution monitoring of S. alterniflora is crucial to control secondary invasion and restore coastal wetlands.

Although mangrove forests occupy only 0.5% of the global coastal area, they account for 10–15% of coastal organic carbon (OC) storage, and 49–98% of OC is stored in sediments. The biogeochemistry of iron minerals and OC in marine sediments is closely related. To better reveal the role of iron minerals in OC preservation in mangrove sediments, an established dithionite–citrate–bicarbonate (DCB) extraction method was used to extract iron-bound OC (Fe-OC), and then the parameters of OC, Fe-OC, iron content, carbon isotopes, infrared spectroscopy, and XRD diffractions of sediments at a 1 m depth in four typical mangrove communities in the Gaoqiao Mangrove Reserve, Guangdong, China, were systematically measured. XRD diffractograms showed that the iron minerals in mangrove sediments may mainly exist in the form of goethite, which is consistent with the predominant types of iron minerals in marine sediments. About 10% of OC is directly bound to iron, and it is further estimated that about 2.4 × 10¹²–3.8 × 10¹² g OC is preserved in global mangrove forests each year based on the high burial rate of OC in mangrove sediments. Lower Fe-OC/OC molar ratios indicated that iron mainly binds to OC via adsorption mechanisms. More depleted δ¹³C_Fe-OC relative to δ13C_bulk indicated that iron minerals are mainly associated with terrigenous OM, and the infrared spectra also revealed that iron minerals preferentially bind to terrigenous aromatic carbon. This work supports the “giant rusty sponge” view, elucidating that iron plays an important role in the preservation of OC in mangrove sediments.

The rapid and disordered expansion of artificial marine aquaculture areas has caused severe ecological and environmental problems. Accurate monitoring of offshore aquaculture areas is urgent and significant in order to support the scientific and sustainable management and protection of coastal marine resources. Artificial intelligence provides a valuable tool to improve marine resource monitoring. Deep learning methods have been widely used for marine object detection, but You Only Look Once (YOLO) models have not been employed for offshore aquaculture area monitoring. This study therefore evaluated the capacity of two well-known YOLO models, YOLOv5 and YOLOv7, to detect offshore aquaculture areas based on different high-resolution optical remote sensing imagery. Compared with YOLOv7 based on a satellite dataset, YOLOv5 increased the Precision value by approximately 3.29% (to 95.33%), Recall value by 3.02% (to 93.02%), mAP_0.5 by 2.03% (to 96.22%), and F1 score by 2.65% (to 94.16%). Based on the Google Earth dataset, YOLOv5 and YOLOv7 showed similar results. We found that the spatial resolution could affect the deep learning models’ performances. We used the Real-ESRGAN method to enhance the spatial resolution of satellite dataset and investigated whether super-resolution (SR) methods improved the detection accuracy of the YOLO models. The results indicated that despite improving the image clarity and resolution, the SR methods negatively affected the performance of the YOLO models for offshore aquaculture object detection. This suggests that attention should be paid to the use of SR methods before the application of deep learning models for object detection using remote sensing imagery.

Mangroves are one of the world’s most productive and ecologically important ecosystems, and they are threatened by the widespread invasion of Spartina alterniflora Loisel in China. As few studies have examined the spatial pattern differences of S. alterniflora invasion and the nearby mangroves in different latitudes, we chose the Zhangjiang Estuary and the Dandou Sea, two representative mangrove–salt marsh ecotones in the north and south of the Tropic of Cancer, as the study areas for comparison. The object-based image analysis and visual interpretation methods were combined to construct fine-scale mangrove and S. alterniflora maps using high-resolution satellite imagery from 2005 to 2019. We applied spatial analysis, centroid migration, and landscape indexes to analyze the spatio–temporal distribution changes of mangroves and S. alterniflora in these two ecotones over time. We used the landscape expansion index to investigate the S. alterniflora invasion process and expansion patterns. The annual change rates of mangrove and S. alterniflora areas in the Zhangjiang Estuary showed a continuous growth trend. However, the mangrove areas in the Dandou Sea showed a fluctuating trend of increasing, decreasing, and then increasing again, while S. alterniflora areas kept rising from 2005 to 2019. Spartina alterniflora showed larger annual change rates compared with mangroves, indicating rapid S. alterniflora invasion in the intertidal zones. The opposite centroid migration directions of mangroves and S. alterniflora and the decreasing distances between the mangrove and S. alterniflora centroids indirectly revealed the fierce competition between mangroves and S. alterniflora for habitat resources. Both regions saw a decrease in mangrove patch integrality and connectivity. The integrality of mangrove patches in the Zhangjiang Estuary was always higher than those in the Dandou Sea. We observed the growth stage (2011–2014) and outbreak stage (2014–2019) of S. alterniflora expansion in the Zhangjiang Estuary and the outbreak stage (2005–2009) and plateau stage (2009–2019) of S. alterniflora expansion in the Dandou Sea. The expansion pattern of S. alterniflora varies in time and place. Since the expansion of S. alterniflora in the outbreak stage is rapid, with a large annual change rate, early warning of S. alterniflora invasion is quite important for the efficient and economical removal of the invasive plant. Continuous and accurate monitoring of S. alterniflora is highly necessary and beneficial for the scientific management and sustainable development of coastal wetlands.

In traditional kerogen pyrolysis experiments, the effects of minerals and rock fabric on the pyrolysis products were ignored. To further clarify the role of the mineral matrix and rock fabric on hydrocarbon generation and retention, a closed anhydrous pyrolysis experiment was conducted on core plugs, powdered rock and kerogen from a clay-rich sample of Maoming oil shale within a temperature range of 312 °C to 600 °C, at a fixed pressure of 30 Mpa. The experiment’s results showed that the yields of heavy hydrocarbons (C₁₄₊) generated from the core plugs and powdered rock were obviously lower than that of kerogen, which may be caused by the retention effect of clay minerals in raw shale. The yields of gaseous hydrocarbons generated from core plugs were lower compared with powdered rock due to the retention of C₂₊ hydrocarbons by the intact rock fabric and the preferential generation of methane. Light hydrocarbon (C_6-14) yields generated from the core plugs and powdered rock were higher than kerogen, which may be the consequence of the cleavage of extraction bitumen and the interactions with kerogen. Moreover, the ratios of iso to normal paraffin (iC₄/nC₄, iC₅/nC₅) of the core plugs and powdered rock were higher than kerogen. Our experimental results show that kerogen pyrolysis in a confined system may overestimate the hydrocarbon generation potential due to the negligence of the retention effect of minerals and the rock fabric, especially in the source rocks rich in clay minerals.