Mangrove Distribution Research Articles

Priority areas to protect mangroves and maximise ecosystem services

Anthropogenic activities threaten global biodiversity and ecosystem services. Yet, area-based conservation efforts typically target biodiversity protection whilst minimising conflict with economic activities, failing to consider ecosystem services. Here we identify priority areas that maximise both the protection of mangrove biodiversity and their ecosystem services. We reveal that despite 13.5% of the mangrove distribution being currently strictly protected, all mangrove species are not adequately represented and many areas that provide disproportionally large ecosystem services are missed. Optimising the placement of future conservation efforts to protect 30% of global mangroves potentially safeguards an additional 16.3 billion USD of coastal property value, 6.1 million people, 1173.1 Tg C, and 50.7 million fisher days yr−1. Our findings suggest that there is a pressing need for including ecosystem services in protected area design and that strategic prioritisation and coordination of mangrove conservation could provide substantial benefits to human wellbeing.

Impacts of climate change and variability on the growth potential of global mangrove distribution

ABSTRACT .Mangrove ecosystems are vulnerable to climate change impacts, which depend on species sensitivity and location. We studied the effects of climate change on three dominant mangrove species globally: red, black, and white mangroves. Using simulation, GIS, and statistical modeling, we evaluated spatially explicit changes in growth suitability resulting from climatic change. Our analysis shows that climate change has significant impacts on mangrove wetlands, with red and black mangroves being the most affected. Low precipitation can impact all species, with red, black, and white mangroves showing a 0.008%, 0.004%, and 0.008% decrease in growth suitability, respectively, for each one mm reduction in precipitation. Variability in climatic variables, such as a unit increase in CV, also significantly impacts mangroves. These results highlight the need to protect mangrove ecosystems for the sustainability of coastal ecosystems.

Optimizing the spatial distribution of Southeast Asia mangrove restoration based on zonation, species and carbon projection schemes

Mangroves contain large amounts of carbon that can reduce the effects of global climate change, which is termed as blue carbon and noted as an important ecosystem service. However, mangrove ecosystems have experienced a huge decline due to human activities and any rehabilitation and restoration efforts should be undertaken with careful planning to optimise their ecosystem service provision and to improve the success of these programs. The main objective of this study was to model a scenario specific to Southeast Asian mangrove distribution based on zonation, species, and coastal morphology, as well as the estimation of future aboveground biomass carbon content resulting from multiple scenarios of successful mangrove growth. This study provides the first assessment of the differences in the distribution of carbon content in a range of native mangrove species, as well as the relationship between the number of propagules, carbon content, mangrove species, and the percentage of living mangroves. The potential location for mangrove planting was dominated by zone 4 inundated by spring high tides, with a suitable area of 4,081,325 ha the next largest area was zone 2, inundated by medium high tides, with a potential area of 2,080,475 ha, followed by zone 3, inundated by normal high tides, with an area of 1,685,800 ha. This study is expected to serve as a reference for mangrove ecosystem conservation and optimisation of carbon storage, especially in Southeast Asia.

WAVE TRANSMISSION AND DISSIPATION BY HYBRID (VEGETATED WITH MANGROVE) BREAKWATERS

In recent years a group of studies for coastal protection (Hashim and Catherine (2013), Maza et al. (2018), Tomiczek et al. (2020), among others) have been carried out to determine drag coefficients in mangrove forests due to ocean waves. Following the mangrove hybrid platform concept by Tagaki (2019), and actual projects such as the mangrove rehabilitation site in the Jakarta Fishing Port, the main objective of this study was to propose and test a hybrid structure capable of controlling wave energy via breaking and dissipation. The experimental tests focused on determining the rates of the wave energy distribution (reflection, transmission and dissipation) due to the presence of an afforested mangrove zone in the upper part of the breakwater. A fixed-bottom small-scale model was tested under normal and extreme marine regimes. The prototype dimensions of the breakwater are total height 5.70 m, crest width 10 m, seaside slope 2:1 (H:V) and leeward slope (1.5:1). The barrier is composed of a rigid bottom built of artificial elements (cubipods) and a long crown intended to be vegetated (with red mangroves, for example). The rationale behind this configuration is to provide ecosystem services by an artificially built mangrove forest protected by the rigid bottom. The experimental program consisted of 54 experiments divided into 7 groups corresponding to regular and irregular waves, mean and extreme and high and low tide conditions. Other variables of interest were the density and spatial distribution of mangroves, such as core materials.

The distribution of mangrove area, mangrove density, and species diversity on the North Coast of Jakarta

The distribution of mangrove area, density, and species diversity on the North Coast of Jakarta indicate the mangrove adaptation to live and grow in permanent water inundation areas. Therefore, this research aimed to analyze the distribution and mapping of the mangrove ecosystem in permanent water inundation area using the index of mangrove density, diversity, and geographical information system. The results showed that soil water salinity ranged from 5.6 to 7.0 ppt, water salinity ranged from 0.1 to 9.8 ppt, soil water pH ranged from 6.25 to 7,0, water pH ranged from 5.83 to 6.5, soil nitrate ranged from 12.2 to 22.8 mg/L, soil phosphate ranged from 1.7 to 14.8 mg/L, soil pyrite ranged from 0.12 to 0.3 mg/L, and soil texture varied from silt loam to silty clay loam. The mangrove ecosystem on the North Jakarta was dominated by a very rare density and low–moderate diversity, with a density between 440–1,250 trees/ha. The distribution of mangrove area also showed a very rare density from 0.18 ha (2000) to 166.95 ha (2020), a rare from 197.03 ha (2000) to 359,72 ha (2020), the moderate from 263.65 ha (2000) to 351.09 ha (2020), the dense from 591.78 (2000) to 273.92 ha (2020), and the very dense from 486.35 ha (2000) to 98.91 ha (2020). The mangrove ecosystem in the North Coast Jakarta was dominated by Avicennia marina, Rhizophora mucronata, Rhizophora apiculata, Rhizophora stylosa, Nypa frutican, Sonneratia alba and Sonneratia caseolaris. The conclusions of this research showed that the mangrove ecosystem inJakarta is degraded because it is dominated by rare- very rare of mangrove density Keywords: mangrove distribution, mangrove density and diversity, North Coast of Jakarta, permanent water inundation

Changes in density level and mangrove land cover on Teluk Pandan Coast, Lampung, Indonesia, after 10 years of community-based management

Abstract. Hasani Q, Anisa A, Damai AA, Yuliana D, Yudha IG, Julian D. 2023. Changes in density level and mangrove land cover on Teluk Pandan Coast, Lampung, Indonesia, after 10 years of community-based management. Biodiversitas 24: 3735-3742. The mangrove ecosystem in the Teluk Pandan coastal area, Pesawaran District, Lampung Province, Indonesia, is part of the mega-biodiversity of mangroves in Indonesia. Specifically, the mangrove in this region has changed due to tourism, aquaculture, settlement activities and coastal abrasion. This study aimed to assess the changes in density level and area change of the mangrove forests at five coastal villages in Teluk Pandan during the period of community management from 2010 to 2020. The effort and success of the rehabilitation were reported in this study can be useful as a consideration of sustainable management of mangrove ecosystem both in Lampung and in other areas in Indonesia. Mangrove area was estimated through field surveys and data processing of satellite imagery from Landsat 5 in 2010 and Landsat 8 in 2020. The mangrove density level and area change were calculated by layering images of mangrove distribution from different years. The classification of mangrove density was determined based on the NDVI value. Satellite imagery was compared with field data collected from 20 observation points at five villages to ensure the density level and interpretation accuracy. Image data analysis showed the changes in mangrove area from 109.80 ha in 2010, an increase of 16.39% to 127.80 ha in 2020. The area of mangrove forest in the rare category decreased by 49.35%, the moderate category increased by 39.13%, and the dense category increased by 109.71%. The study confirmed the successful effort to manage and preserve mangroves in Teluk Pandan Sub-district. Eventually, community-based mangrove management (CBMM) and cross-sectoral and multi-stakeholder management (co-management) has become the core strategy in the successful management of mangrove at five coastal villages in Teluk Pandan Sub-district.

Deep Learning-Based Classification of High-Resolution Satellite Images for Mangrove Mapping

Detailed information about mangroves is crucial for ecological and environmental protection and sustainable development. It is difficult to capture small patches of mangroves from satellite images with relatively low to medium resolution. In this study, high-resolution (0.8–2 m) images from Chinese GaoFen (GF) and ZiYuan (ZY) series satellites were used to map the distribution of mangroves in coastal areas of Guangdong Province, China. A deep-learning network, U2-Net, with attention gates was applied to extract multi-scale information of mangroves from satellite images. The results showed that the attention U2-Net model performed well on mangrove classification. The overall accuracy, precision, and F1-score values were 96.5%, 92.0%, and 91.5%, respectively, which were higher than those obtained from other machine-learning methods such as Random Forest or U-Net. Based on the high-resolution mangrove maps generated from long satellite image time series, we also investigated the spatiotemporal evolution of the mangrove forest in Shuidong Bay. The results can provide crucial information for government administrators, scientists, and other stakeholders to monitor the dynamic changes in mangroves.

Fine-scale mapping of Spartina alterniflora-invaded mangrove forests with multi-temporal WorldView-Sentinel-2 data fusion

Mangrove forests, a critical component of blue carbon ecosystems, make a significant contribution to mitigating climate change and maintaining biodiversity. But in China, they have been suffering from severe invasion by Spartina alterniflora (S. alterniflora). Accurate information on spatial distribution of mangroves and S. alterniflora is a prerequisite to protecting indigenous mangrove ecosystems and managing S. alterniflora invasion. However, the classification performance is often constrained by two major issues: (1) A single-date image, regardless of acquisition time, hardly provides optimal spectral separability among evergreen mangroves, deciduous S. alterniflora and mudflats; (2) Due to the gradual invasion process, the mixtures between land cover classes are prevalent in moderate-resolution images. The use of high-resolution (finer than 2 m) image time series could effectively solve these two issues. However, due to frequent cloud cover in coastal areas and long revisit time of high-resolution satellite sensors, the collection of high-resolution image time series is still a great challenge, let alone substantial expenses. In this study, we proposed a new multi-temporal classification approach to fine-scale mapping of exotic S. alterniflora and native mangroves using synthetic high-resolution image time series derived from spatiotemporal fusion of WorldView-2 and Sentinel-2 data. A total of six synthetic WorldView-2-like images in different phenological periods were produced by the Flexible Spatiotemporal DAta Fusion (FSDAF) method. With the combination of the original and synthetic images, both types of image-based multi-temporal features and pixel-based image compositing features were extracted and evaluated in the following Random Forest classifications. Monte Carlo cross-validation was adopted to provide robust accuracy estimates, and a spatially explicit confidence map was generated to show classification uncertainty and potential errors. In order to further demonstrate the necessity of generating synthetic WorldView-2 images, the entire classification process was repeated using Sentinel-2 images at 10-m spatial resolution and the comparison between fine- and moderate-resolution classification results was made in terms of classification accuracies, classification maps and fractional abundances. Our results show that the spectral profiles of S. alterniflora and mangroves generated from the synthetic WorldView-2 images were consistent with the ones from the paired Sentinel-2 images. Meanwhile, the spatial details of high landscape heterogeneity, unrecognizable in the Sentinel-2 images, were revealed by the synthetic WorldView-2 images. Compared to the single-date classification with the original WorldView-2 image, most of multi-temporal classifications using both the original and synthetic images provided more accurate results, with the overall accuracy raised by up to 3.9%. Among various temporal features adopted in this study, the use of the image-based, stacked spectral reflectance and vegetation index features of all original and synthetic images produced the best classification performance, increasing the producer's and user's accuracies of mangroves, S. alterniflora and mudflats by 2.5%–7.1%. Finally, the Sentinel-2 classification accuracies were generally lower than the WorldView-2 counterparts across all temporal features, with a 6% difference in the highest overall accuracy between the two. Prediction errors of the moderate-resolution classification were often found in heterogeneous landscapes, where S. alterniflora was mixed with mangroves or mudflats. Considering the availability of moderate-resolution data with high revisit frequencies, such as Sentinel-2A/B and Landsat 8/9, future fine-scale mapping exercises might benefit from the multi-temporal classification approach with spatiotemporal fusion of moderate- and high-resolution data, alleviating the problem of the scarcity of high-resolution data in cloudy areas.

How exotic Sonneratia species affect the spatiotemporal dynamics of mangroves in Shenzhen Bay, China: A remote sensing perspective

Mangroves are essential forest communities in tropical and subtropical coastal zones, providing unique ecological functions and significant social and economic value. Accurate and efficient monitoring of mangroves is crucial for their protection and management. The impact of exotic species on native species is still debated, especially for mangroves, the spatiotemporal dynamics of introduced species and native mangrove species need to be closely monitored. This study aimed to investigate how exotic mangrove species affects the spatial dynamics of mangroves in Shenzhen Bay, China. Yearly Landsat images from 2000 to 2011 and Chinese high spatial resolution images during 2012–2022 were obtained and the pixel-based and multiscale object-based methods were used to obtain mangrove distribution. The results showed that: (1) Overall, mangroves in the study area increased from 281.51 ha to 526.43 ha from 2000 to 2022, with different spatiotemporal patterns in Shenzhen (+5.14%) and Hong Kong (+2.38%); (2) rapid spread of Sonneratia species was one of the main contributions to the growth of mangrove hotspots, and growth hotspots were mainly concentrated in the estuary delta; and (3) Sonneratia mangrove species was dominant in interspecific competition, not only invading the habitat of local mangroves, but also preventing the expansion of native mangrove growth. The results provide a reference for fine-scale and accurate mangrove mapping with high spatial and temporal resolutions, and highlight the need to pay more attentions to the spread and invasive potential of exotic mangrove species in the study area, as well as cooperation in adjacent reserves.

Conservation and Restoration of Mangroves in Response to Invasion of Spartina alterniflora Based on the MaxEnt Model: A Case Study in China

In China, the invasion of Spartina alterniflora is an important driver for the decrease of mangrove area and ecological service functions related to this habitat. In the past few decades, S. alterniflora clearing and mangrove restoration projects have mainly focused on the areas where it is already changed but ignored the potential distribution areas. This study suggested that implementation of mangrove protection prior to the areas with the threat of S. alterniflora invasion could greatly improve protection efficiency and save costs. Thus, using Maximum Entropy Modeling (MaxEnt), we estimated the potential spatial distribution of both mangroves and S. alterniflora in China, considering the current distribution data, topographical, sediments, sea surface temperature and bioclimatic variables. What’s more, we identified and calculated the potential distributed areas in each province. We aimed to explore (i) the key factors determining the distribution of mangrove and Spartina alterniflora along the coastline and (ii) the hotspots of their competitive occurrence, including S. alterniflora invasion areas and mangroves degradation areas, in order to support mangrove conservation. The model showed that the distance to the coastline and the topography play important roles in the distribution of S. alterniflora, while mangroves were more sensitive to the range of the annual sea surface temperature. Our results furthermore confirm that S. alterniflora has a wider potential distribution area (~10,585 km2) than mangroves (~9124 km2) at the coastline of China; and predict the provinces Zhangzhou, Quanzhou, Zhanjiang, Beihai and Wenzhou as hotspots for the competition between mangroves and S. alterniflora. We propose that priority should be given to the protection or restoration of mangrove plants in those areas which are co-suitable for mangroves and S. alterniflora. In these areas, management measures should be conducted that hinder S. alterniflora invasions or clear existing S. alterniflora plants, firstly. This study provides guidance for the management of native species by preventing biological invasion.

Perbandingan Beberapa Metode Klasifikasi Menggunakan Citra Landsat dan Sentinel Untuk Pemetaan Sebaran Mangrove Di Kawasan Ekowisata Mangrove PIK Jakarta Utara

Mangroves are one of the coastal ecosystems that have many functions and have a very large role for living things associated with mangroves. One of the mangrove ecosystems in DKI Jakarta is in the Mangrove Ecotourism Area of the Sedyatmo Toll Road, North Jakarta. Remote sensing technology is the right method for mangrove monitoring activities that are efficient, effective and wide area coverage. Mangrove mapping is one of the remote sensing techniques to determine the distribution of mangroves in a region. This study aims to assess mangroves and compare the accuracy of the supervised classification method (Maximum Likelihood, Minimum Distance) and object based classification in the distribution of mangroves in the Mangrove Ecotourism Area of the Sedyatmo Toll Road using Landsat 8 and Sentinel-2A images. Comparison of the results of the supervised classification and object based classification of the two images to be tested for accuracy using a confusion matrix. The results showed that the mangroves were evenly distributed along the Sedyatmo toll road and its surroundings with an average mangrove area of >60 ha. In Landsat 8 imagery, the Overall Accuracy for the classification of Maximum Likelihood is 87,50%, Minimum Distance is 75,00% and object based classification is 89,83%. Sentinel-2A image classification results Overall Accuracy classification method Maximum Likelihood 89,83%, Minimum Distance 77,50%, and object-based classification 90,00%. The results of the Overall Accuracy show that object-based classification is better than the Maximum Likelihood and Minimum Distance classifications in mapping the distribution of mangroves on Landsat 8 and Sentinel-2A images.

A Study on Spatial Distribution Extraction of Tidal Inundated Mangroves Based on High and Low Tide Level Images

A majority of mangroves are located in the coastal intertidal zone and are subject to tidal periodic inundation. However, the previous vegetation indices used for extracting the spatial distribution of mangroves were not able to effectively extract submerged mangroves, and the applicability of the vegetation indices used on different spatial resolution images obtained from different sensors was not verified. In this study, a new vegetation index, namely the intertidal mangrove identification indices (IMIIs), was proposed, based on GF-2 images of high and low tide levels. Meanwhile, other commonly used vegetation indices were also extracted. All the vegetation indices were used to extract the spatial distribution of mangroves under tidal inundation, and applicability tests of the vegetation indices were conducted on Sentinel-2 images in three different regions. It was found that the IMIIs proposed based on GF-2 images of high and low tide levels can extract submerged mangroves relatively well, and the spatial distribution extraction results of mangroves are better than those of other vegetation indices, with IMII2 outperforming IMII1. At the same time, IMIIs have good applicability in medium resolution Sentinel-2 images, and there are relatively large differences in the extraction results of mangrove spatial distribution among different vegetation indices in areas with significant impact of tidal inundation. Among all vegetation indices, the extraction results of IMIIs are relatively superior. In most cases, multi variables collaborative application can improve the accuracy of mangrove spatial distribution extraction results. Based on the results of this study, it was concluded that the IMIIs proposed in this study can accurately extract the spatial distribution of mangroves inundated by tides from both medium- and high-resolution images, providing accurate basic data for effective management and scientific protection of mangrove resources.

Assessment of long-term mangrove distribution using optimised machine learning algorithms and landscape pattern analysis.

Mangrove ecosystems provide numerous benefits, including carbon storage, coastal protection and food for marine organisms. However, mapping and monitoring of mangrove status in some regions, such as the Red Sea area, has been hindered by a lack of data, accurate and precise maps and technical expertise. In this study, an advanced machine learning algorithm was proposed to produce an accurate and precise high-resolution land use map that includes mangroves in the Al Wajh Bank habitat in northeastern Saudi Arabia. To achieve this, high-resolution multispectral images were generated using an image fusion technique, and machine learning algorithms were applied, including artificial neural networks, random forests and support vector machine algorithms. The performance of the models was evaluated using various matrices, and changes in mangrove distribution and connectivity were assessed using the landscape fragmentation model and Getis-Ord statistics. The research gap that this study aims to address is the lack of accurate and precise mapping and assessment of mangrove status in the Red Sea area, particularly in data-scarce regions. Our study produced high-resolution mobile laser scanning (MLS) imagery of 15-m length for 2014 and 2022, and trained 5, 6 and 9 models for artificial neural networks, support vector machines and random forests (RF) to predict land use and land cover maps using 15-m and 30-m resolution MLS images. The best models were identified using error matrices, and it was found that RF outperformed other models. According to the 15-m resolution map of 2022 and the best models of RF, the mangrove cover in the Al Wajh Bank is 27.6 km2, which increased to 34.99 km2 in the case of the 30-m resolution image of 2022, and was 11.94 km2 in 2014, indicating a doubling of the mangrove area. Landscape structure analysis revealed an increase in small core and hotspot areas, which were converted into medium core and very large hotspot areas in 2014. New mangrove areas were identified in the form of patches, edges, potholes and coldspots. The connectivity model showed an increase in connectivity over time, promoting biodiversity. Our study contributes to the promotion of the protection, conservation and planting of mangroves in the Red Sea area.

Geospatial Assessment of Long-Term Changes (1937–2019) in Mangrove Vegetation and Shoreline Dynamics of Godavari Estuary, East Coast of India

Godavari mangroves are the second largest mangrove ecoregion of India located on its eastern coast. Mangroves perform major ecological functions including shoreline stabilization and coastal protection. They have undergone serious alterations, largely induced by human activities resulting in increased vulnerability to coastal flooding. A reliable database on mangroves distribution and temporal changes is essential for their effective management and conservation. Present study analyzes the long-term changes in mangroves, as well as the geomorphological changes along the coast of Godavari Estuary over a span of 82 years (1937–2019), using topographical maps, remotely sensed multi-temporal satellite imageries for five time periods. Results indicated that the rate of land uses conversions of agricultural fields, degraded areas, mudflats and mangrove vegetation into aquaculture significantly increased during the late 1990s. About 40 percent of it was constructed on mangrove areas between 1980 and 2019. The area under aquaculture was estimated to be 6,388.62 ha in 2000, almost doubling-up to 11,924.67 ha in 2019. Mangrove cover in this region increased by 15.95 percent between 2000 and 2019 (including 11.9 percent in Coringa Wildlife Sanctuary) due to increased protection, consequent regeneration and accretion. Shift in Hope Island spit was observed in north and northwest directions, gradually growing nearly 3.84 km. High-resolution declassified satellite data were found very helpful for long-term mangrove mapping and analyzing geomorphological changes; enabling a better understanding of these regions to help decision makers/planners to find better solutions to existing coastal issues. The paper concludes with some recommendations to restore and conserve the existing mangrove cover in the study area.

Mangrove Distribution and Estimation of Canopy Closure Condition: Employing the Simple Hemispherical Photography Method within the Mangrove Community of Waiheru Village

The canopy closure within Waiheru Village's mangrove community is crucial in shielding residential areas from robust winds and providing shade for associated aquatic organisms, thereby mitigating the effects of direct sunlight. Furthermore, the shading provided by the mangrove canopy contributes to the area's carrying capacity for developing mangrove-based ecotourism. This study aims to investigate the distribution of mangrove species, substrate distribution, and the condition of the mangrove canopy closure. Stratified Random Sampling was employed for the data collection on mangroves and substrates, while the Hemispherical Photography method was utilized to gather canopy cover data. The analysis revealed the presence of 11 mangrove species from seven different families, with Rhizophora mucronata exhibiting the most extensive growth distribution compared to other species. Two substrate types, sandy and sandy mud, were also identified. The mangrove canopy closure in Waiheru Village remains in favorable condition, as most observation stations demonstrate a high proportion of dense and moderate canopy closure.

Protective effect of ecological embankment on a building subjected to tsunami bores

The mangrove has a remarkable wave reducing effect, and it is arranged around the embankment to form an ecological embankment (eco-embankment), which complement each other's strengths. The tsunami wave simulated by the dam breaking wave is used in the flume to impact the test models. By measuring the tsunami bore height, transmission coefficient and impact pressure, and observing the flow state during the impact process, the wave elimination effect and protection effect of the eco-embankment are studied. The results show that the bore height is related to the initial water depth and the reservoir water level. The change of water level in the eco-embankment setting area (front, top, and behind of embankment) is related to the bore height, the location and the distribution density of mangroves. The transmission coefficient increases linearly with the relative water depth, but the magnitude of the increase is different for each eco-embankment model. Based on the experimental data, the equations for estimating the transmission coefficient are proposed. When tsunami waves impact buildings protected by embankments or eco-embankments, the pressure decreases and the time history of pressure appear a reflection stage compared to an unprotected building, this stage will change with the initial water depth and the distribution density of mangroves. Finally, based on the measured pressure data, the equations for estimating the dimensionless quasi-steady pressure for different models and different mangrove distribution densities are proposed as functions of relative height and Froude number, the calculated value is in good agreement with the measured value.

Distribution of mangroves with different aerial root morphologies at accretion and erosion sites in Ca Mau Province, Vietnam

Aerial roots are a vital feature that allow mangroves to survive in anaerobic and unstable soil conditions. Mangrove species have different aerial root characteristics and show their own site-specific distribution. The distribution of three types of aerial roots with different morphological characteristics was investigated between accretion and erosion sites in Ca Mau, Vietnam. Stilt roots, pneumatophores and knee roots were the three main aerial root types in the study area. Stilt roots of Rhizophora apiculata BL. and pneumatophores of Avicennia species were the two most abundant root types at the study sites, dominating erosion and accretion sites, respectively. Stilt roots had a higher number of primary roots in seaward plots than in landward plots (p < 0.05), supporting the ability of R. apiculata to withstand erosion of the surface. Tidal erosion moved away sediment and exposed roots, which resulted in higher aboveground stilt root height in seaward plots than in landward plots at erosion sites (p < 0.05). The higher density and biomass of pneumatophores in seaward plots than those in landward plots at accretion sites (p < 0.05) confirmed the adaptation of Avicennia to newly accreted sites where tidal inundation and anaerobic conditions limited mangrove growth. The density of A. alba decreased with the distance from the sea at both erosion and accretion sites, implying that this species was a pioneer species adapted to newly accreted sites or disturbed sites among mangrove species. Bruguiera parviflora with knee roots was distributed in more stable conditions. Mangrove species with different root types displayed a zonal distribution with increasing distance from the shoreline. This distribution reflects mangrove species adaptabilities and species-specific roles in the context of coastal processes and site conditions, which should be considered in coastal mangrove restoration.

Simulation and Prediction of Sea Level Rise Impact on the Distribution of Mangrove and Spartina alterniflora in Coastal China

Sea level rise (SLR) has a significant impact on the vegetation ecosystem in coastal wetlands. Taking coastal China as the study area, the SLAMM (sea level rise affecting marsh model) was used to simulate the continuous long-term (2015–2100) effects of the spatiotemporal changes in mangrove and Spartina alterniflora in the four shared socioeconomic pathway scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) of sea level rise by 2100; then, ArcGis was used to assess and compare the impact of SLR on land use. The results are as follows. (1) The dramatic reduction in the vegetation area is positively correlated with the rate of sea level rise. (2) Tidal differences and sedimentation rates affect the response of mangrove and S. alterniflora distribution to sea level rise, as well as interactions between organisms. (3) The reasonable land use of coastal wetlands is important to researchers. Land use is one of the tools for effective mangrove conservation. In conclusion, in scientific research and production practice, it is important to combine the biotic and abiotic factors affecting the distribution of mangroves and S. alterniflora.

Tidal creeks mediate micro-climate within artificial mangroves at their northmost boundary in China

One of the primary constraints for mangrove restoration is the low temperature in relatively high latitude regions. Yueqing Bay, at a latitude of 28.20°N, is the northmost region for the artificial mangrove forests in China. It is hypothesized that in this region, the micro-climate nearby tidal creeks can benefit the growth of mangroves, as the inundation process can mediate air temperature and soil temperature. To test this hypothesis, field observation was conducted to measure mangrove characteristics, hydrology and air/soil temperature within a channelised mangrove forest and compare variations between a tidal creek and its adjacent platform. LiDAR data and field measurement both indicated a height decrease of mangrove trees (Kandelia obovata) from the tidal creek edge to the platform. This pattern suggested that the presence of tidal creeks was able to promote the growth of mangrove in their northmost boundary and the mediation of microclimatic condition should be further investigated. The temperature profile data revealed that the key zone of temperature affected by tidal inundation was within a range of 5 cm and -15 cm referring to bed levels. Temperature monitoring in the winter revealed that compared with the platform, a mean increase of 0.6 °C in both air temperature and soil temperature were found in the tidal creek. However, spring tides and neap tides showed different effects on temperature mediation by the presence of tidal creeks. The greatest temperature increase was observed to occur in neap tides, reaching maximum of 9 °C in air and 3 °C in soil. Thus, the warming effects of tidal creeks in this region was most important in neap tides. In the northmost boundary of mangrove distribution in China, winter low temperature was considered to be the key restraint for mangrove restoration. Field survey found the growth of mangroves reached a maximal along the tidal creek edge in this region. This pattern was explained by the fact that the presence of tidal creeks increased winter temperature of mangroves and channelisation was found to be a potential technique to promote the growth of artificial mangroves in the relatively high latitude regions.

Groundwater discharge and saltwater-freshwater mixing in a mangrove wetland over tidal cycles: A field and modeling study

Material transport and transformations in mangrove wetlands are closely related to seawater-groundwater mixing processes, which can influence mangrove growth and development. Therefore, a clearer understanding of groundwater and salt transport dynamics in aquifers beneath mangrove wetlands is needed to accurately estimate chemical fluxes to mangrove ecosystems. We established a multi-level groundwater monitoring profile in a mangrove wetland and constructed a numerical model of tidally-driven groundwater flow and salt transport that was calibrated to salinity and pore water pressure. Model results indicated that 99% of groundwater discharge to the mangrove wetland was saltwater and that this discharge accounted for 33% of total discharge over a spring-neap tidal cycle. Tidal creeks that cross-cut the wetland received the remaining 67% of total discharge. Seawater infiltration from tidal action across the wetland formed a subsurface saltwater-freshwater mixing zone with a geometry that followed the undulation of a high permeably layer at depth. Model sensitivity tests showed that salinity distributions and groundwater discharge patterns were controlled strongly by wetland topography and anisotropy. Model cases with a gently sloping and flat mangrove platform led to substantially less salt mass in the subsurface compared to the base case with mangrove topographic relief. Models with lower anisotropy allowed salt to penetrate through the high-permeability layer to the base of the aquifer. The spatial patterns of fresh and saline groundwater discharge and mixing processes within mangrove wetlands as shown in this study may have implications for mangrove tree nutrient availability and for the prevalence and spatial distribution of mangroves along coastlines.