Search Results (562)

Although significant progress has been made in the remote sensing extraction of mangroves, research at the species level remains relatively limited. Kandelia obovata is a dominant mangrove species and is frequently used in ecological restoration projects in China. However, owing to the fragmented distribution of K. obovata within mixed mangrove communities and the significant spectral and textural similarities among mangrove species, accurately extracting large-scale K. obovata-based remote sensing data remains a challenging task. In this study, we conducted extensive field surveys and developed a comprehensive sampling database covering K. obovata and other mangrove species across mangrove-distributing areas in China. We identified the optimal bands for extracting K. obovata by utilizing time-series remote sensing data from Sentinel-1 and Sentinel-2, along with the Google Earth Engine (GEE), and proposed a method for extracting K. obovata communities. The main conclusions are as follows: (1) The spectral-temporal variability characteristics of the blue and red-edge bands play a crucial role in the identification of K. obovata communities. The 90th percentile metric of the blue wavelength band ranks first in importance, while the 75th percentile metric of the blue wavelength band ranks second; (2) This method of remote sensing extraction using spectral-temporal variability metrics with time-series optical and radar remote sensing data offers significant advantages in identifying the K. obovata species, achieving a producer’s accuracy of up to 94.6%; (3) In 2018, the total area of pure K. obovata communities in China was 4825.97 ha; (4) In the southern provinces of China, Guangdong Province has the largest K. obovata community area, while Macau has the smallest. This research contributes to the understanding of mangrove ecosystems and provides a methodological framework for monitoring K. obovata and other coastal vegetation using advanced remote sensing technologies. Full article

Mangroves grow in high-salinity environments with low soil water potential (Ψ_s), where high light intensity and strong winds increase the vapor pressure deficit (VPD), causing physiological drought and high transpiration demand (Δw), which limits carbon dioxide (carbon gain) for photosynthesis. This study explored how mangroves optimize their carbon-gain-to-water-loss ratio (water-use strategies) to maximize carbon gain during both dry and rainy seasons. We also calculated the relative costs of key leaf traits and compared them with those of terrestrial forests under the carbon gain optimization model. The results revealed that (1) with increasing Δw, terrestrial forests primarily adjusted leaf hydraulic conductance (K_leaf), while mangroves altered the difference in water potential (ΔΨ); (2) as Ψ_s decreased, π_tlp of both terrestrial forests and mangroves increased; (3) terrestrial forests developed a more balanced distribution of leaf trait costs between osmotic pressure (46.7 ± 0.2%) and stomata (43.3 ± 1.2%), whereas mangroves had the highest cost in osmotic pressure (49.04 ± 0.03%) and the lowest cost in stomata (11.08 ± 3.00%) during the rainy season; and (4) although mangroves showed differences in trait values between dry and rainy seasons, their responses to drought stress remained consistent. These findings provided new theoretical insights into how mangroves maintain high carbon gain and water-use efficiency under extreme environmental conditions, which is important to improve mangrove conservation efforts and contribute to climate mitigation policies. Full article

Historically known for its tin mining industry, Phuket Island has undergone significant transformation into a global tourism hub. This study aims at analyzing the evolutionary dynamics of Phuket Island from the years 1987 to 2024. We integrate Landsat satellite images and sophisticated analytical methods to assess the effects of tourism and economic policies on changes in land use and land cover using Google Earth Engine (GEE) for cloud-based data processing and Random Forest (RF) models for classification, and the Urban Expansion Intensity Index (UEII) and Shannon Entropy metrics for measuring the intensity of urban expansion and diversity, respectively. The results show that there has been a dynamic change in the patterns of land use which was brought about by the economic and environmental forces. Some of the major events that have had a great effect on Phuket’s landscape include the 1997 Asian Financial Crisis, the 2004 Indian Ocean Tsunami, and the COVID-19 pandemic; this highlights how the island is fragile and can be affected easily by events happening around the world. This work reveals a dramatic reduction in forest and mangrove cover, which calls for increased conservation measures to prevent the loss of biodiversity and to preserve the natural balance. Full article

Coastal erosion is a critical environmental challenge in the Upper Gulf of Thailand, driven by both natural processes and human activities. This study analyzes 35 years (1988–2023) of shoreline changes using geoinformatics, machine learning algorithms (Random Forest, Support Vector Machine, Maximum Likelihood, Minimum Distance), and the Digital Shoreline Analysis System (DSAS). The results show that the Random Forest algorithm, utilizing spectral bands and indices (NDVI, NDWI, MNDWI, SAVI), achieved the highest classification accuracy (98.17%) and a Kappa coefficient of 0.9432, enabling reliable delineation of land and water boundaries. The extracted annual shorelines were validated with high accuracy, yielding RMSE values of 13.59 m (2018) and 8.90 m (2023). The DSAS analysis identified significant spatial and temporal variations in shoreline erosion and accretion. Between 1988 and 2006, the most intense erosion occurred in regions 4 and 5, influenced by sea-level rise, strong monsoonal currents, and human activities. However, from 2006 to 2018, erosion rates declined significantly, attributed to coastal protection structures and mangrove restoration. The period 2018–2023 exhibited a combination of erosion and accretion, reflecting dynamic sediment transport processes and the impact of coastal management measures. Over time, erosion rates declined due to the implementation of protective structures (e.g., bamboo fences, rock revetments) and the natural expansion of mangrove forests. However, localized erosion remains persistent in low-lying, vulnerable areas, exacerbated by tidal forces, rising sea levels, and seasonal monsoons. Anthropogenic activities, including urban development, mangrove deforestation, and aquaculture expansion, continue to destabilize shorelines. The findings underscore the importance of sustainable coastal management strategies, such as mangrove restoration, soft engineering coastal protection, and integrated land-use planning. This study demonstrates the effectiveness of combining machine learning and geoinformatics for shoreline monitoring and provides valuable insights for coastal erosion mitigation and enhancing coastal resilience in the Upper Gulf of Thailand. Full article

Wave attenuation by natural coastal features is recognised as a soft engineering approach to shoreline protection from storm surges and destructive waves. The effectiveness of wave energy dissipation is determined, in part, by vegetation structure, extent, and distribution. Mangroves line ca. 15% of the world’s coastlines, primarily in tropical and subtropical regions but also extending into temperate climates, where mangroves are shorter and multi-stemmed. Using wave loggers deployed across mangrove and non-mangrove shorelines, we studied the wave attenuating capacity and the drag coefficient (C_D) of temperate Avicennia marina mangrove forests of varying structure in Western Port, Australia. The structure of the vegetation obstructing the flow path was represented along each transect in a three-dimensional point cloud derived from overlapping uncrewed aerial vehicle (UAV) images and structure-from-motion (SfM) algorithms. The wave attenuation coefficient (b) calculated from a fitted exponential decay model at the vegetated sites was on average 0.011 m⁻¹ relative to only 0.009 m⁻¹ at the unvegetated site. We calculated a C_D for this forest type that ranged between 2.7 and 4.9, which is within the range of other pencil-rooted species such as Sonneratia sp. but significantly lower than prop-rooted species such as Rhizophora spp. Wave attenuation efficiency significantly decreased with increasing water depth, highlighting the dominance of near-bed friction on attenuation in this forest type. The UAV-derived point cloud did not describe the vegetation (especially near-bed) in sufficient detail to accurately depict the obstacles. We found that a temperate mangrove greenbelt of just 100 m can decrease incoming wave heights by close to 70%, indicating that, similarly to tropical and subtropical forests, temperate mangroves significantly attenuate incoming wave energy under normal sea conditions. Full article

Scrub mangrove forests, dominated by Rhizophora mangle L., are characterized by high porewater salinity, which might compromise individual sap flow rates (SF) due to seasonal and diurnal microenvironmental variations. We tested the functional, anatomical, and SF responses of 12 individuals to microenvironmental variables such as solar radiation, photosynthetic photon flux, wind speed, evaporative demand, and porewater salinity, measured using an in situ weather station. Measurements were made in the dry and rainy seasons in the Yucatan Peninsula, using Granier heat dissipation sensors, installed on tree branches. During the rainy season, SF was twice as high as that during the dry season (0.22 ± 0.00 L h⁻¹ and 0.11 ± 0.00 L h⁻¹, respectively), despite lower evaporative demand. In both seasons, negative relationships between SF with vapor pressure deficit (VPD; dry τ = −0.54; rainy τ = −0.56) and with photosynthetic photon flux (PPF; dry τ = −0.97; rainy τ = −0.98) were found, indicating a strong hydraulic coupling to atmospheric conditions. Sap flow and transpiration rates of this R. mangle scrub mangrove forest exceeded those of some tropical dry deciduous forests, suggesting adaptations that support water transport in saline environments. The clustered xylem vessels of R. mangle ensure safe sap flow year-round. As an evergreen species, it contributes water to the atmosphere all year-round, underscoring its critical role in the tropical ecohydrological environment. Full article

Mangrove ecosystems are valuable coastal ecosystems; however, studies on the diversity and functional features of their soil fungal communities during restoration are limited. In this study, we examined fungal diversity and trophic modes across mudflat, young mangrove, and mature mangrove stages. We found that Ascomycota and Basidiomycota were the dominant phyla, with saprotrophs as the most abundant trophic mode. The abundance of the major phyla and trophic modes significantly varied across restoration stages. Although fungal alpha (α)-diversity remained stable among the stages, beta (β)-diversity showed significant differentiation. Spearman’s analysis and partial Mantel tests revealed that total nitrogen and inorganic phosphorus significantly influenced the fungal α-diversity, whereas temperature and pH primarily shaped the fungal β-diversity. Total nitrogen and carbon were key factors affecting the trophic mode α-diversity, whereas total phosphorus and inorganic phosphorus were the main drivers of the trophic mode β-diversity. Variation partitioning analysis confirmed that nutrients, rather than soil properties, were the primary factors shaping fungal communities and trophic modes. Random forest analysis identified key bioindicators, including species such as Paraphyton cookei, and trophic modes such as saprotrophs, both of which were strongly influenced by soil carbon. These findings advance our understanding of fungal ecology in mangrove restoration. Full article

Mangroves have been used for coastal protection in Bangladesh since the 1960s, but their integration with embankment designs has not been fully explored. This paper investigates the effect of existing mangroves on required embankment performance, with a focus on the wave-damping effect of mangroves. Existing mangroves reduce the required thickness of embankment revetment by up to 16–30% in the west, 47–82% in the central region, and 53–77% in the east. Notable mangrove sites include the belt south of polder 45 (Amtali), with an average width of 1.77 km, and the Kukri-Mukri polder, with an average width of 1.82 km. These mangroves reduce the need for thick slope protection, allowing the replacement of concrete revetments with softer materials, such as clay or grass, combined with mangrove foreshore. Additional large mangrove belts are found in Sandwip and Mirersarai. By replacing or reducing revetment requirements, mangrove forests can minimize carbon emissions from construction while providing carbon sequestration and other ecosystem services. This study can inform future sustainable investments in coastal protection systems by identifying areas where mangroves offer the greatest wave-damping benefits, which could be focus of follow-up feasibility studies. Full article

Monitoring mangrove phenology requires frequent, high-resolution remote sensing data, yet satellite imagery often suffers from coarse resolution and cloud interference. Traditional methods, such as denoising and spatiotemporal fusion, faced limitations: denoising algorithms usually enhance temporal resolution without improving spatial quality, while spatiotemporal fusion models struggle with prolonged data gaps and heavy noise. This study proposes an optimized mangrove phenology extraction approach (OMPEA), which integrates Landsat and MODIS data with a denoising algorithm (e.g., Gap Filling and Savitzky–Golay filtering, GF–SG) and a spatiotemporal fusion model (e.g., Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model, ESTARFM). The key of OMPEA is that GF–SG algorithm filled data gaps from cloud cover and satellite transit gaps, providing high-quality input to ESTARFM and improving its accuracy of NDVI imagery reconstruction in mangrove phenology extraction. By conducting experiments on the GEE platform, OMPEA generates 1-day, 30 m NDVI imagery, from which phenological parameters (i.e., the start (SoS), end (EoS), length (LoS), and peak (PoS) of the growing season) are derived using the maximum separation (MS) method. Validation in four mangrove areas along the coastal China shows that OMPEA significantly improves the potential to capture mangrove phenology in the presence of incomplete data. The OMPEA significantly increased usable data, adding 7–33 Landsat images and 318–415 MODIS images per region. The generated NDVI series exhibits strong spatiotemporal consistency with original data (R²: 0.788–0.998, RMSE: 0.007–0.253) and revealed earlier SoS and longer LoS at lower latitudes. Cross-correlation analysis showed a 2–3 month lagged effects of temperature on mangroves’ growth, with precipitation having minimal impact. The proposed OMPEA improves the possibility of capturing mangrove phenology under non-continuous and low-resolution data, providing valuable insights for large-scale and long-term mangrove conservation and management. Full article

The golden apple snail (GAS, Pomacea canaliculata) has invaded mangrove forests. The effect of water contaminated by metabolic activity of GAS feeding on Acanthus ilicifolius (T1), Sonneratia apetala (T2), and without food (CK) on the native mangrove black helmet snail (BHS, Neritina pulligera) was investigated under salinity conditions. The GAS deteriorated saline water quality (2.5‰). DO contents in T1 and T2 approached zero at 9 d. Compared to CK, the contents of COD, total N, NH₄⁺, NO₃⁻, and total P of the contaminated water in T1 increased by 297%, 205%, 262%, 210%, and 518% after 9 d, while these indicators in T2 increased by 74%, 31%, 57%, 326%, and 154%, respectively. The LC₅₀ of the contaminated water in T1 against the BHS reached 22.72%. The weight of the BHS exposed to the 100% contaminated water in T1 and T2 significantly decreased after exposure. The content of GPT of the BHS exposed to the 100%-contaminated water in T1 and T2 increased by 55% and 26%, while the MDA content increased by 38% and 34%. The 100%-contaminated water in T1 led to cell degeneration and incomplete structure in the hepatopancreas tissue of the BHS. The GAS feeding on holly mangroves can compete against native mangrove snails through water deterioration. Full article

Shrimp farming has expanded over coastal areas in Mexico, particularly in the protected regions of Sonora and Sinaloa. Over the past 30 years, the economic activity associated with these farms has grown so much that the amount of shrimp produced in these ponds now exceeds that harvested from traditional shrimp fisheries. Establishing shrimp ponds has led to significant land changes. The construction of these ponds has fragmented local ecosystems, resulting in permanent alterations to areas such as floodplains, mangrove forests, and dunes, many of which are protected zones. This study aimed to investigate the long-term growth of shrimp farms from 1993 to 2022 and their impact on land-use changes in surrounding ecosystems, focusing on protected areas in the Sinaloa and Sonora coastal regions. We analyzed Landsat images using the Google Earth Engine platform. Our findings indicate that shrimp farm development over the past three decades has been extensive, with protected areas experiencing fragmentation and changes. Remote sensing and platforms like Google Earth Engine enable the effective monitoring of these spatiotemporal changes and their impacts, helping to identify the most affected areas. Full article

Mangrove wetlands are naturally divided into habitat patches by tidal creeks, with patch edges highly vulnerable to human activities and biological invasions, making them critical areas for mangrove degradation. Understanding the geometrical characteristics of these patches is essential for mangrove management in the Anthropocene, yet their exploration remains limited. Using a high-resolution (2 m) mangrove distribution dataset from 2018, we analyzed the patch structure of mangroves in southern China. This study revealed predominantly small and elongated patches, with an average area of 0.044 km² and a median of 0.011 km² across 5857 patches. About 65% of patches had a major-axis length over twice their minor-axis length. The patch number and area peaked between 19° N and 22° N. The patch number and area peaked between 19° N and 22° N. In the 0.1° × 0.1° latitudinal-longitudinal grid, the maximum mangrove area was 9.03 km², consisting of 192 patches. Additionally, the patch composition and geometric characteristics differed significantly among the existing reserves. These findings highlight the need to prioritize the patch geometry in management strategies, especially in regions with numerous small patches prone to degradation and invasion. Additionally, this study underscores a critical research gap: the ecological impacts of mangrove fragmentation on biodiversity and ecosystem services remain poorly understood. Future research should focus on how the patch structure and landscape configuration influence ecological processes in mangrove wetlands. Full article

Mangrove forests play a crucial role in coastal ecosystem protection and carbon sequestration processes. However, monitoring remains challenging due to the forests’ complex spatial distribution characteristics. This study addresses three key challenges in mangrove monitoring: limited high-quality datasets, the complex spatial characteristics of mangrove distribution, and technical difficulties in high-resolution image processing. To address these challenges, we present two main contributions. (1) Using multi-source high-resolution satellite imagery from China’s new generation of Earth observation satellites, we constructed the Mangrove Semantic Segmentation Dataset of Beihai, Guangxi (MSSDBG); (2) We propose a novel Multi-scale Fusion Attention Unified Perceptual Network (MFA-UperNet) for precise mangrove segmentation. This network integrates Cascade Pyramid Fusion Modules, a Multi-scale Selective Kernel Attention Module, and an Auxiliary Edge Neck to process the unique characteristics of mangrove remote sensing images, particularly addressing issues of scale variation, complex backgrounds, and boundary accuracy. The experimental results demonstrate that our approach achieved a mean Intersection over Union (mIoU) of 94.54% and a mean Pixel Accuracy (mPA) of 97.14% on the MSSDBG dataset, significantly outperforming existing methods. This study provides valuable tools and methods for monitoring and protecting mangrove ecosystems, contributing to the preservation of these critical coastal environments. Full article

Based on field observation at the north coast of the Zhanjiang Bay in southern China, the characteristics of wave attenuation due to the drag force of one mangrove species, Avicennia marina (Forsk.) Viern., were quantitatively analyzed. The results demonstrated that the mean significant wave height decreased by ~62% within a forest belt up to 80 m due to various bio-physical interactions. Affected by the unique vertical configuration of vegetation, the wave attenuation rate is positively correlated with water depth. The drag force within the forest can be approximated by the function $C_d=0.7344e^{0.1409A_m}$, where A_m is the projected area of the submerged obstacle at a certain water depth. The wave attenuation rate and the vegetation density (ρ_veg) in volume (‰) satisfy the fitting relationship of $r=5\times {10}^{-4}·{\rho }_{veg}-3.6\times {10}^{-3}$. These findings can accumulate quantitative information for studying the influence of mangrove vegetation on wave attenuation characteristics and provide necessary basic data for modeling studies to investigate the processes contributing to the attenuation capacity of mangroves. Full article

Constructed wetlands, as an emerging wastewater treatment system, have been widely used worldwide due to their high purification efficiency and low investment and operating costs. Wetland plants, on the other hand, together with their inter-root microbes, significantly affect the ecological functions of constructed wetlands. The mangrove constructed wetland within Futian District, Shenzhen, China, is a typical wastewater treatment area, but the structure and function of its soil microbial community remain largely unexplored. In this study, the assembly and processes of the soil microbial communities in this constructed wetland were intensively investigated using high-throughput sequencing technology. Our results showed that the three mangrove plants had significant effects on the soil bacterial microbial community α-diversity, insignificant effects on β-diversity, and significant effects on fungal α-diversity and β-diversity. The abundance of genera changed significantly between the treatment groups, such as the genus Candidatus_Udaeobacter for bacteria versus Russula for fungi, and the random forest model showed that rare genera (e.g., Acidibacter, Dyella, Sebacina, and Lachnellula) also play an important role in microbial community construction. Community assembly revealed the deterministic process of soil bacterial and fungal communities under different mangrove species. Overall, this study enhanced our understanding of soil microbial community composition and diversity in constructed wetlands ecosystems, providing insights into their manageability. Full article