Tidal dynamics and mangrove carbon sequestration during the Oligo-Miocene in the South China Sea

The spatial patterns and driving mechanisms of blue carbon 'loss' and 'gain' in a typical mangrove ecosystem: A case study of Beihai, Guangxi Province of China

The role of mangroves in carbon sequestration is critical in mitigating climate change. For better identifying the carbon conservation hotspots of mangroves influenced by environmental factors, the spatial distribution and driving mechanisms of mangrove vegetation and soil carbon sequestration, as well as the future carbon dynamics of mangroves, required clarification. Firstly, we assessed the spatial pattern of vegetation biomass and soil depth-varied soil total organic carbon (TOC) in Xiaoguansha, Guangxi Province of China, and its relationships with duration of inundation (DTI) were explored. Additionally, the carbon storage capacity of adjacent mangrove tidal flats as potential carbon reservoirs was quantified. Thirdly, freshwater, and nutrient inputs, biotic factors of mangrove, and soil composition were selected as impact factors, and their mechanisms in carbon sequestration were elucidated by using Partial least squares path modeling (PLS-PM). Finally, medium values of environmental factors on mangrove carbon sequestration were revealed, based on which future loss and gain patterns of carbon sequestration under the combined effects were fully discussed. The results showed that: (1) The Above-ground biomass (AGB) and TOC densities were 32.89 Mg C/ha and 185.10 Mg C/ha in the study area, and both were enriched in the Interior areas. The carbon sequestration in the tidal flats was equivalented to >1/5 of total carbon sequestration of mangroves. (2) DTI was the most critical factor affecting the carbon sequestration pattern and was found to be positive correlated with AGB and TOC via changing soil contents (SC), whereas it exhibits a negative correlation with AGB and TOC through influencing canopy density (CD). CD and TP were identified as significant predictors. (3) Median analysis indicated that future carbon 'gain' area will move nearshore, whereas the carbon-rich intertidal area may undergo carbon loss. This study provided new insights and scientific understanding for management of mangrove blue carbon function.

An Improved Submerged Mangrove Recognition Index-Based Method for Mapping Mangrove Forests by Removing the Disturbance of Tidal Dynamics and S. alterniflora

Currently, it is a great challenge for remote sensing technology to accurately map mangrove forests owing to periodic inundation. A submerged mangrove recognition index (SMRI) using two high- and low-tide images was recently proposed to remove the influence of tides and identify mangrove forests. However, when the tidal height of the selected low-tide image is not at the lowest tidal level, the corresponding SMRI does not function well, which results in mangrove forests below the low tidal height being undetected. Furthermore, Spartina alterniflora Loisel (S. alterniflora) was introduced to China in 1979 and rapidly spread to become the most serious invasive plant along the Chinese coastline. The current SMRI has failed to distinguish S. alterniflora from submerged mangrove forests because of their similar spectral signatures. In this study, an SMRI-based mangrove forest mapping method was developed using the time series of Sentinel-2 images to mitigate the two aforementioned issues. In the proposed method, quantile synthesis was applied to the time series of Sentinel-2 images to generate a lowest-tide synthetic image for creating SMRI to identify submerged mangrove forests. Unsubmerged mangrove forests were classified using a support vector machine, and a preliminary mangrove forest map was created by merging them. In addition, S. alterniflora was distinguished from the mangrove forests by analyzing their phenological differences. Finally, mangrove forest mapping was performed by masking S. alterniflora. The proposed method was applied to the entire coastline of the Guangxi Province, China. The results showed that it can reliably and accurately identify submerged mangrove forests derived from SMRI by synthesizing low- and high-tide images using quantile synthesis, and the differentiation of S. alterniflora using phenological differences results in more accurate mangrove mapping. This work helps to improve the accuracy of mangrove forest mapping using SMRI and its feasibility for coastal wetland monitoring. It also provides data for sustainable management, ecological protection, and restoration of vegetation in coastal zones.

Cloud-Based Monitoring and Evaluation of the Spatial-Temporal Distribution of Southeast Asia’s Mangroves Using Deep Learning

This paper proposes a cloud-based mangrove monitoring framework that uses Google Collaboratory and Google Earth Engine to classify mangroves in Southeast Asia (SEA) using satellite remote sensing imagery (SRSI). Three multi-class classification convolutional neural network (CNN) models were generated, showing F1-score values as high as 0.9 in only six epochs of training. Mangrove forests are tropical and subtropical environments that provide essential ecosystem services to local biota and coastal communities and are considered the most efficient vegetative carbon stock globally. Despite their importance, mangrove forest cover continues to decline worldwide, especially in SEA. Scientists have produced monitoring tools based on SRSI and CNNs to identify deforestation hotspots and drive targeted interventions. Nevertheless, although CNNs excel in distinguishing between different landcover types, their greatest limitation remains the need for significant computing power to operate. This may not always be feasible, especially in developing countries. The proposed framework is believed to provide a robust, low-cost, cloud-based, near-real-time monitoring tool that could serve governments, environmental agencies, and researchers, to help map mangroves in SEA.

The first national scale evaluation of organic carbon stocks and sequestration rates of coastal sediments along the West Sea, South Sea, and East Sea of South Korea

Blue carbon science requires the estimates of organic carbon stock and sequestration rate; however, holistic data analysis remains limited in South Korea. The present study reports current organic carbon stocks and sequestration rates in the coastal areas of West Sea, South Sea, and East Sea of South Korea, encompassing entire intertidal areas using long-term field survey combined with remote sensing technology. Twenty-one intertidal flats were targeted across seven provinces (Gyeonggi, Chungnam, Jeonbuk, Jeonnam, Gyeongnam, Gyeongbuk, Gangwon). Out of the evaluated environmental parameters, mud content represented a significant factor controlling sedimentary organic carbon stocks across target areas, and was significantly positively correlated to the total organic carbon (p < 0.05). Organic carbon stocks measured in salt marshes (i.e., upper intertidal zone) reflected the high carbon fixation capacity of halophytes through primary production. Sediment textural type was classified using analysis of remotely sensed imagery, and was closely correlated to field-based classification data (p < 0.05). Using field and remote sensing results, we estimated total organic carbon stocks (13,142,149 Mg C) and sequestration rates (71,383 Mg C yr^-1) in the tidal flats of South Korea. This study presents the first report on blue carbon potential in the Korean tidal flats, providing baseline information on the carbon dynamics of intertidal sediments in this region and, potentially, elsewhere.

Depth-dependent variability of biological nitrogen fixation and diazotrophic communities in mangrove sediments

BACKGROUND

Nitrogen-fixing prokaryotes (diazotrophs) contribute substantially to nitrogen input in mangrove sediments, and their structure and nitrogen fixation rate (NFR) are significantly controlled by environmental conditions. Despite the well-known studies on diazotrophs in surficial sediments, the diversity, structure, and ecological functions of diazotrophic communities along environmental gradients of mangrove sediment across different depths are largely unknown. Here, we investigated how biological nitrogen fixation varied with the depth of mangrove sediments from the perspectives of both NFR and diazotrophic communities.

RESULTS

Through acetylene reduction assay, nifH gene amplicon and metagenomic sequencing, we found that the NFR increased but the diversity of diazotrophic communities decreased with the depth of mangrove sediments. The structure of diazotrophic communities at different depths was largely driven by salinity and exhibited a clear divergence at the partitioning depth of 50 cm. Among diazotrophic genera correlated with NFR, Agrobacterium and Azotobacter were specifically enriched at 50-100 cm sediments, while Anaeromyxobacter, Rubrivivax, Methylocystis, Dickeya, and Methylomonas were more abundant at 0-50 cm. Consistent with the higher NFR, metagenomic analysis demonstrated the elevated abundance of nitrogen fixation genes (nifH/D/K) in deep sediments, where nitrification genes (amoA/B/C) and denitrification genes (nirK and norB) became less abundant. Three metagenome-assembled genomes (MAGs) of diazotrophs from deep mangrove sediments indicated their facultatively anaerobic and mixotrophic lifestyles as they contained genes for low-oxygen-dependent metabolism, hydrogenotrophic respiration, carbon fixation, and pyruvate fermentation.

CONCLUSIONS

This study demonstrates the depth-dependent variability of biological nitrogen fixation in terms of NFR and diazotrophic communities, which to a certain extent relieves the degree of nitrogen limitation in deep mangrove sediments. Video Abstract.

Abandonment and rapid infilling of a tide-dominated distributary channel at 0.7 ka in the Mekong River Delta

The Ba Lai distributary channel of the Mekong River Delta was abandoned and infilled with sediment during the Late Holocene, providing a unique opportunity to investigate the sediment fill, timing and mechanisms of channel abandonment in tide-dominated deltaic systems. Based on analysis and age dating of four sediment cores, we show that the channel was active since 2.6 ka and was abandoned at 0.7 ka as marked by the abrupt disappearance of the sand fraction and increase in organic matter and sediment accumulation rate. We estimate that the channel might have been filled in a time range of 45–263 years after detachment from the deltaic network, with sediment accumulation rates of centimetres to decimetres per year, rapidly storing approximately 600 Mt of organic-rich mud. We suggest that the channel was abandoned due to a sediment buildup favoured by an increase in regional sediment supply to the delta. This study highlights that mechanisms for abandonment and infilling of tide-dominated deltaic channels do not entirely fit widely used models developed for fluvial-dominated environments. Their abandonment might be driven by autogenic factors related to the river-tidal and deltaic dynamics and favoured by allogenic factors (e.g., human impact and/or climate change).

Spatial variation of soil properties impacted by aquaculture effluent in a small-scale mangrove

Small-scale mangroves serve ecological functions similar to large-scale mangroves regarding biological conservation, environmental purification, and supporting biogeochemical processes. The rising aquaculture neighboring mangroves results in their serving as an important sink for massive nutrients and pollutants from aquaculture effluent. We assessed how long-term aquaculture effluent discharge influenced the soil properties of a mangrove-tidal flat continuum using field survey and geostatistics. Common soil physical-chemical properties presented significant spatial variability. Continued aquaculture effluent discharge caused a significant cumulation of soil total organic carbon (SOC) (64.13 g·kg^-1), total nitrogen (TN) (2.44 g·kg^-1) and total phosphorus (TP) (1.12 g·kg^-1) in the mangrove soil, which were as 2-3 times as those on the mudflat. Most of the soil properties changed significantly with increasing distance from the effluent outlet along a tidal channel, and the maximum concentrations of SOC, TN and TP all occurred at 50 m away from the outlet. The results of principal component analysis indicated that aquaculture effluent significantly affected the spatial pattern of soil properties along the mangrove-tidal flat continuum. Continued aquaculture effluent input rendered extensive accumulation of SOC, TN and TP in the mangroves. The spatial heterogeneity of mangrove is the key driver to process the nutrient input spatially differently.

Patterns and environmental drivers of greenhouse gas fluxes in the coastal wetlands of China: A systematic review and synthesis

Coastal wetlands play an increasingly important role in regulating greenhouse gas (GHG) fluxes and thus affecting climate change. However, the overall magnitude, trend, and environmental drivers of GHG fluxes in these wetlands of China remain uncertain. Herein, we synthesized data from 70 publications involving 187 field observations to identify patterns and drivers of GHG fluxes across coastal wetlands in China. Average methane (CH₄), nitrous oxide (N₂O) fluxes, and carbon dioxide (CO₂) emissions (ecosystem respiration) across coastal wetlands were estimated as 2.20±0.31 mg·m^-2·h^-1, 16.44±2.96 μg·m^-2·h^-1, and 388.76±42.28 mg·m^-2·h^-1, respectively. GHG emissions varied with tidal inundation, where CH₄ and CO₂ emissions during tidal inundation were lower than during ebbing. CH₄ and CO₂ emissions from wetlands decreased linearly with increasing latitude, while N₂O did not. CH₄ fluxes were positively related to air temperature and aboveground biomass, and CO₂ emissions were positively related to soil organic carbon. N₂O fluxes were lower with increasing soil pH, and CH₄ and CO₂ emissions were greater with increasing soil moisture. Based on the results of sustained-flux global warming potential and sustained-flux global cooling potential models, our paper indicate that the fluxes of CH₄ and N₂O in coastal wetlands have a positive feedback to global warming, which is mainly driven by the CH₄ emission. Our synthesis improved understanding of the roles of coastal wetlands in the ecosystem C cycle under global change. We suggest that long-term field observations of GHG fluxes across a wider range of spatiotemporal scales are urgently required to improve the prediction accuracy in GHG fluxes and the assessment of net GHG balance and its contribution to the GWP of coastal wetlands.

A New Vegetation Index to Detect Periodically Submerged Mangrove Forest Using Single-Tide Sentinel-2 Imagery

Mangrove forests are tropical trees and shrubs that grow in sheltered intertidal zones. Accurate mapping of mangrove forests is a great challenge for remote sensing because mangroves are periodically submerged by tidal floods. Traditionally, multi-tides images were needed to remove the influence of water; however, such images are often unavailable due to rainy climates and uncertain local tidal conditions. Therefore, extracting mangrove forests from a single-tide imagery is of great importance. In this study, reflectance of red-edge bands in Sentinel-2 imagery were utilized to establish a new vegetation index that is sensitive to submerged mangrove forests. Specifically, red and short-wave near infrared bands were used to build a linear baseline; the average reflectance value of four red-edge bands above the baseline is defined as the Mangrove Forest Index (MFI). To evaluate MFI, capabilities of detecting mangrove forests were quantitatively assessed between MFI and four widely used vegetation indices (VIs). Additionally, the practical roles of MFI were validated by applying it to three mangrove forest sites globally. Results showed that: (1) theoretically, Jensen–Shannon divergence demonstrated that a submerged mangrove forest and water pixels have the largest distance in MFI compared to other VIs. In addition, the boxplot showed that all submerged mangrove forests could be separated from the water background in the MFI image. Furthermore, in the MFI image, to separate mangrove forests and water, the threshold is a constant that is equal to zero. (2) Practically, after applying the MFI to three global sites, 99–102% of submerged mangrove forests were successfully extracted by MFI. Although there are still some uncertainties and limitations, the MFI offers great benefits in accurately mapping mangrove forests as well as other coastal and aquatic vegetation worldwide.

Broadband Waveguide Cloak for Water Waves

Inspired by electromagnetic waveguide cloaks with gradient index metamaterials, we fabricated a broadband cloak with simply a gradient depth profile on the bottom and without any other structures on the top to confine water waves in a certain area for cloaking regions. The new physics of mode conversion for water waves is first found. The experimental and numerical simulation results are in good agreement and show that the presented device has a nice performance for various situations and is feasible over a broadband of working frequencies. Being easy to construct, this design is potentially of significance for port applications.

Relative sea-level change regulates organic carbon accumulation in coastal habitats

Because coastal habitats store large amounts of organic carbon (C_org ), the conservation and restoration of these habitats are considered to be important measures for mitigating global climate change. Although future sea-level rise is predicted to change the characteristics of these habitats, its impact on their rate of C_org sequestration is highly uncertain. Here we used historical depositional records to show that relative sea-level (RSL) changes regulated C_org accumulation rates in boreal contiguous seagrass-saltmarsh habitats. Age-depth modeling and geological and biogeochemical approaches indicated that C_org accumulation rates varied as a function of changes in depositional environments and habitat relocations. In particular, C_org accumulation rates were enhanced in subtidal seagrass meadows during times of RSL rise, which were caused by postseismic land subsidence and climate change. Our findings identify historical analogs for the future impact of RSL rise driven by global climate change on rates of C_org sequestration in coastal habitats.

Mapping Mangrove Forests Based on Multi-Tidal High-Resolution Satellite Imagery

Mangrove forests, which are essential for stabilizing coastal ecosystems, have been suffering from a dramatic decline over the past several decades. Mapping mangrove forests using satellite imagery is an efficient way to provide key data for mangrove forest conservation. Since mangrove forests are periodically submerged by tides, current methods of mapping mangrove forests, which are normally based on single-date, remote-sensing imagery, often underestimate the spatial distribution of mangrove forests, especially when the images used were recorded during high-tide periods. In this paper, we propose a new method of mapping mangrove forests based on multi-tide, high-resolution satellite imagery. In the proposed method, a submerged mangrove recognition index (SMRI), which is based on the differential spectral signature of mangroves under high and low tides from multi-tide, high-resolution satellite imagery, is designed to identify submerged mangrove forests. The proposed method applies the SMRI values, together with textural features extracted from high-resolution imagery and geographical features of mangrove forests, to an object-based support vector machine (SVM) to map mangrove forests. The proposed method was evaluated via a case study with GF-1 images (high-resolution satellites launched by China) in Yulin City, Guangxi Zhuang Autonomous Region of China. The results show that our proposed method achieves satisfactory performance, with a kappa coefficient of 0.86 and an overall accuracy of 94%, which is better than results obtained from object-based SVMs that use only single-date, remote sensing imagery.

Characterization, sources, and ecological hazards of polycyclic aromatic hydrocarbons in the intertidal sediments of Zhelin Bay, the biggest mariculture area on the eastern Guangdong coast of China

Distribution characteristics, potential sources, and possible biological hazards of polycyclic aromatic hydrocarbons (PAHs) were examined in intertidal surface sediments of Zhelin Bay, the biggest mariculture base of eastern Guangdong Province, Southern China. The total PAH concentrations ranged from 8.05-51.32 ng/g (dry weight) with an average of 29.23 ng/g, which is beneath the documented concentrations in intertidal sediments gathered from various bays across the globe. The composition of PAHs was distinguished by high molecular weight (HMW, 4-6 rings) PAHs, with phenanthrene (PHE), fluoranthene (FA), and benzo(b)fluoranthene (BbFA) established as predominant components. Principle component analysis along with multivariate linear regression discovered that liquid fossil fuel combustion and coal/wood combustion contribute to 60.23% and 39.77% of PAHs in Zhelin Bay's intertidal sediments, respectively. Overall, surface sediments of Zhelin Bay have an 8% increased incidence of adverse biological effects due to PAH contamination, based on the mean probable effect level quotient.

PCR-DGGE Analysis on Microbial Community Structure of Rural Household Biogas Digesters in Qinghai Plateau

To investigate contribution of environmental factor(s) to microbial community structure(s) involved in rural household biogas fermentation at Qinghai Plateau, we collected slurry samples from 15 digesters, with low-temperature working conditions (11.1-15.7 °C) and evenly distributed at three counties (Datong, Huangyuan, and Ledu) with cold plateau climate, to perform polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and further sequencing. The bacterial communities in the total 15 digesters were classified into 38 genera with Mangroviflexus (12.1%) as the first dominant, and the archaeal communities into ten genera with Methanogenium (38.5%) as the most dominant. For each county, the digesters with higher biogas production, designated as HP digesters, exclusively had 1.6-3.1 °C higher fermentation temperature and the unique bacterial structure composition related, i.e., unclassified Clostridiales for all the HP digesters and unclassified Marinilabiliaceae and Proteiniclasticum for Ledu HP digesters. Regarding archaeal structure composition, Methanogenium exhibited significantly higher abundances at all the HP digesters and Thermogymnomonas was the unique species only identified at Ledu HP digesters with higher-temperature conditions. Redundancy analysis also confirmed the most important contribution of temperature to the microbial community structures investigated. This report emphasized the correlation between temperature and specific microbial community structure(s) that would benefit biogas production of rural household digesters at Qinghai Plateau.