Mangrove Biomass Research Articles

Carbon Sequestration Assesment of Mangrove Ecosystem in Karang Anyar Village, Tanggamus Regency

Mangroves is a ecosystem can absorb carbon more efective than teresterial vegetataion. The goal of this research is to analyze effectively carbon absorption in the mangrove aea in the Karang Anyar Village. The research was conducted in Karang Anyar Village. Survey and tree sampling were carried out from Juni to August 2024. Biomass measurements provided information on carbon sequestrtaion. Data obtained was analyzed using allometric equation. Results showed that mean carbon sequestration of the mangrove biomass in Karang Anyar Village was 40,45-69,24 kg C/m2. Carbon sink in mangrove sediment was 402,15-907,95 kg C/m2. This research showed that mangrove ecosystem in Karang Anyar Village held sufficiently high carbon stock. Nevertheless, the future study needs to be directed to carbon stock comparison with other locations in Lampung.

Precision in mapping and assessing mangrove Biomass: Insights from the Persian Gulf coasts

This groundbreaking research makes a contribution to climate change adaptation studies by filling a crucial knowledge gap related to the precise evaluation of mangrove biomass—an essential element influencing the future trends of coastal ecosystems. Specifically, the study concentrates on the Hara Biosphere Reserve (HBR) on the coasts of the Persian Gulf (PG), aiming to generate precise maps of mangrove biomass. The methodological approach involves a comprehensive analysis, including the utilization of Landsat imagery to establish an NDVI map of mangroves, the application of the Cumulative Sum (CUSUM) method to determine a threshold NDVI value for distinguishing between tall and dwarf mangroves, and the subsequent mapping of their distribution in both coastal and island zones. Additionally, the study calculates above-ground biomass (AGB) and below-ground biomass (BGB) values in sample plots, develops a regression relationship between biomass and NDVI values, and integrates maps of tall and dwarf mangrove extent with spatial variations in AGB and BGB. Noteworthy outcomes include the identification of a threshold NDVI value (0.63) for distinguishing mangrove types and revealing distinct biomass values for mangroves in both coastal and island zones. Significantly, tall mangroves positioned on the seaward edges exhibit higher biomass in both zones than dwarf mangroves. These findings shed light on the potential exacerbation of climate change impacts, such as rising sea levels and changing tidal range on mangroves of the coasts of the PG due to the heightened productivity and specific spatial distribution of tall mangroves. Recognizing these structural characteristics and production disparities is crucial for developing effective climate change adaptation programs. Integrating such insights into management strategies is emphasized as pivotal for enhancing the efficiency and success of these programs, presenting a robust solution for protecting mangroves in diverse coastal areas.

Historical ecological monitoring and appraisal for extractive uses and other values in Malaysia unveils consequences of regime shifts in 120 years of mangrove management

Matang Mangrove Forest Reserve (MMFR) in Peninsular Malaysia, with its ‘management plans’ traced back to 1904, is the longest-managed mangrove forest for timber (pole/charcoal) production through intermediate thinning and final felling (or clear-felling) operations. For 115 years, the mangroves in the productive zones have been harvested under a 30-year rotation cycle. The 10-year management plans released by the Forestry Department have been supporting silvicultural management. Despite the long management history, the mangrove biomass and quality were found to have decreased in recent years. Therefore, we analyzed all the available management plans between 1904 and 2019 to summarize both qualitative and quantitative data (i.e., silviculture policy/practice and trading) in search of the shifts in management practices. A comparison with relevant literature on the MMFR was also made to evaluate the potential issues of scientific concern in the ongoing management. We found that the higher yield (per ha) of charcoal and poles in the past 20 years resulted from exploiting the restrictive productive zones (=forest that is environmentally sensitive and marginally productive). With a policy inclined greatly toward the financial outcomes of timber-based products, the current silviculture practice may turn out to be unsustainable if any impacts like extreme weather, tree dieoff, sea-level rise, etc., affect mangroves in the future. We discuss the dilemma between greenwood harvesting and the protection of a diverse range of ecosystem service. This study sheds light on the strengths and weaknesses of historic and current mangrove timber harvesting regimes in MMFR and can contribute to supporting future sustainable mangrove management in Matang, and other forest formation.

Multi-sensor Approach for the Estimation of Above-Ground Biomass of Mangroves

Multi-sensor Approach for the Estimation of Above-Ground Biomass of Mangroves

Carrying capacity for tree biomass of a subtropical mangrove along a river in Japan inferred from forest structural features

AbstractA subtropical mangrove along the Miyara River in Ishigaki Island, Japan was studied for evaluating the carrying capacity for biomass of the mangrove stands. The stem diameters D, tree height H, and fine roots mass were measured, while aboveground biomass (AGB) and belowground coarse root biomass (BGBcoarse) were estimated. The AGB, BGBcoarse, and fine root mass were estimated as 130, 31, and 13 Mg ha−1 in the Rhizophora stylosa; 271, 94, and 11 Mg ha−1 in the downstream Bruguiera gymnorrhiza; and, 228, 81, and 6.4 Mg ha−1 in the upstream B. gymnorrhiza stand, respectively. The AGB and BGBcoarse in the R. stylosa stand were significantly lower than B. gymnorrhiza stands, and fine root mass was significantly higher than upstream B. gymnorrhiza stand. Significantly lower mean individual phytomass wt specific to tree density ρ of R. stylosa stand than B. gymnorrhiza stand in the ρ − wt relationship denoted the lower carrying capacity for AGB of R. stylosa than that of B. gymnorrhiza. The results showed that high soil pore water salinity and low pH at the downstream did not limit biomass and potential canopy height Hmax of mangrove along a river gradient but AGB and BGBcoarse differed between different species at the same edaphic environment. Analysis of aboveground and belowground biomass variations between stands of two mangrove species along environmental gradients from upstream to downstream could be useful in assessing the consequences of sea level rise in relation to climate change on the evolution of blue carbon dynamics.

Estimation of carbon storage of tropical mangroves in the North Maluku Islands region

The mangroves possess a remarkable capacity to absorb carbon dioxide (CO2), surpassing tropical rainforests by fourfold. This underscores the crucial role played by mangroves in global efforts to combat climate change. This study aimed to assess the biomass, carbon content, and CO2 absorption capabilities of mangrove ecosystems. Data collection followed the line transect method, utilizing the Mangrove Watch guide, which involved recording the diameter of mangroves at breast height (DBH), typically around 1.3 meters above the ground, as well as identifying the mangrove species and quantifying the number of stands for each tree species. The analysis of mangrove biomass, carbon content, and CO2 absorption capacity was conducted through an allometric modeling approach. The findings revealed the presence of seven distinct mangrove tree species at the study site, namely Rhizophora mucronata, R. apiculata, R. stylosa, Sonneratia alba, Bruguiera gymnorrhiza, Xylocarpus granatum, and Ceriops decandra. The mangrove density in this area was recorded at 1406 trees per hectare, with a corresponding biomass of 630,508 tons per hectare, a carbon content of 246,035 tons of carbon per hectare, and an impressive CO2 absorption capacity of 902,127 tons of CO2 per hectare. Notably, the mangrove vegetation in this research site exhibited a substantial capacity for CO2 absorption and biomass storage, surpassing many other locations in different regions. These findings underscore the significant role that island mangrove ecosystems can play in mitigating the effects of climate change.

Standing carbon stock of Thane Creek mangrove ecosystem: An integrated approach using allometry and remote sensing techniques

The study quantified the carbon storage potential of the Avicennia marina dominated mangrove ecosystem in Thane Creek, Maharashtra, India. Above-ground tree biomass was quantified using Allometry technique and Allometry - Remote Sensing Integrated technique to avoid destructive methods of biomass estimation. The mangroves along both the banks of Thane Creek were divided into ten stations, and the study was conducted. New allometric equations for A. marina were generated using the equations available in literature and field data on diameter at breast height. In the integrated method, Normalized Difference Vegetative Index (NDVI) map was merged with the ground data and generated the biomass map. The carbon contents of different mangrove biomass components and the sediment were quantified to assess the carbon stock of the ecosystem. The above ground biomass estimated using allometric approach and integrated approach was 84.83 and 111.31 Mg ha−1, respectively. The performance of the biomass estimation methods was evaluated using Root Mean Square Error (RMSE), showing 6.21 Mg ha−1 suggesting a good fit. The estimated mean total carbon stock through Allometry technique is 116.58 Mg C ha−1 whereas the integrated technique showed it to be 127.89 Mg C ha−1. The baseline information on the mangrove carbon stock distribution will serve as a valuable input for assessing carbon dynamics in the mangrove ecosystems, and monitoring and management of Thane Creek Mangroves as well as other similar ecosystems.

Mangrove biomass and carbon estimates for REDD+ from national forest inventory in two regions of Myanmar

Myanmar has the second largest area of mangrove forests in South East Asia while suffering high deforestation rates and forest degradation. However, monitoring results from existing studies in mangrove forests vary widely while specific estimates on carbon density for this forest type are deficient. Also, data from mangrove inventory plots used for the 2018 Myanmar forest reference level refer only to commercial timber and do not include other carbon pools. The results in this study based on four carbon pools allow for updating the emission factors in mangrove forests expressed in CO2 from 125.43 ± 15.06 Mg ha –1 to 1 377.07 ± 67.04 Mg ha –1 for Ayeyarwady region (Pyapon, Pathein, Latputta districts) and 1 583.27± 75.18 Mg ha –1 for Tanintharyi region (Kawthaung, Dawei districts) and can be used in (sub)national or jurisdictional forest reference level for REDD+. In addition, the georeferenced biomass estimates are useful for the calibration of space-based models of biomass estimation.

Do global change variables alter mangrove decomposition? A systematic review

AbstractAimGlobal change is expected to modify the magnitude and trajectory of organic matter decomposition in mangrove ecosystems. Yet, the degree and direction of that change is unknown, especially considering the large C storage potential that mangroves provide. We performed a systematic review of primary literature to examine the relationships between genus‐specific litter quality, latitude or other global change proxies and decomposition of mangrove litter fractions.LocationGlobal.Time Period1976–2021.TaxonMangroves.MethodsWe compiled a dataset of 480 decomposition rates, including species, litter fraction, latitude, and relevant biophysical data. We investigated the influence of genera, tissue type, latitude, and global change proxies on decomposition rates using linear models and qualitative approaches. We also performed calculations to determine the potential importance of the decomposition process on the root litter biomass C pool in the context of blue C significance.ResultsCollectively, latitudinal relationships suggest that factors other than temperature, such as tissue type and genus, may regulate decay rates within mangroves' distributional range. Decay rates of leaf litter, roots, and wood converged on a value of 0.009 ± 0.0005, 0.002 ± 0.0001, and 0.001 ± 0.0003, respectively, across continents and geomorphological settings. Our calculations suggest that small changes in decomposition rate will not elicit large changes in blue C storage potential.ConclusionsThe main drivers behind variability in mangrove biomass decay rates detected across the distributional range remain uncertain. However, the small latitudinal range that mangroves inhabit and the submerged environment within which litter decomposes suggest that decay depends on species‐specific responses or biotic interactions among species to global change drivers. Few studies have examined global change impacts directly, and variability in decay and lack of representation of some mangrove groups in the literature suggest that implications for blue C are important to consider.

Application of multispectral UAV to estimate mangrove biomass in Vietnam: A case study in Dong Rui commune, Quang Ninh Province

Mangroves play an important role in coastal estuarine areas with different ecological functions, such as reducing the impact of waves and currents, accumulating biomass and sequestering carbon. However, estimation of terrestrial biomass in mangrove areas, especially in Vietnam, has not been fully studied. The application of unmanned aerial vehicles (UAV), mounted with multispectral cameras combined with field verification is an effective method for estimating terrestrial biomass for mangroves, as it reduces field survey time and allows for greater spatial range research. In this study, ground biomass was estimated for the mangrove area in the Dong Rui commune, based on multispectral image data obtained from UAV and survey results in 16 standard cells measuring actual biomass according to four regression models: Log-Log, Log-Lin, Lin-Log and Lin-Lin. The results of comparing the data from these four models show that the log-log model has the highest accuracy with a high correlation coefficient (R2 = 0.831). Based on the results of the analysis and selection of ground-based biomass estimation models, a biomass map was established for the UAV flying area in the Dong Rui mangrove forest with biomass values ranging from 20 Mg/ha to 150 Mg/ha. In summary, we present a biomass estimation method through four basic linear regression models for mangrove areas, based on multispectral image data obtained from ultrahigh-resolution UAV. The resulting research results can serve as a basis for managers to calculate and synchronise the payment of carbon services, thus contributing to effectively promoting the livelihoods of local people.

WHAT IS THE TRUE CARBON FRACTION VALUE OF MANGROVE BIOMASS?

Carbon stock in mangrove stands is estimated through the biomass approach multiplied by the value of the mangrove carbon fraction. Many researchers use the value of 47% as the carbon fraction value for all mangrove species which should be based on the actual carbon content value. The research was conducted using the literature review method using a database ScienceDirect and Google Scholar until 2022. The search strategy was carried out using keywords: mangrove biomass, mangrove carbon stock, organic carbon of mangrove, carbon fraction of mangrove biomass, and chemical composition of mangrove biomass. The results showed that the value of the carbon fraction with the approach of organic carbon content was 46.4% and lower than the value of the carbon fraction with the approach of compounds making up mangrove biomass, which was 46.82%. This value was contributed by carbohydrates at 26.20%, amino acids 2.97%, tannins 3.22%, lignins 3.38%, fatty acids 7.69%, triterpenoids 3.17%, and n-alkanes 0.19. %. The estimation of mangrove carbon stock in forests with homogeneous species can use the value of carbon fraction in each mangrove species, namely 46.3% for B. gymnorrhiza, 45.9% for R. apiculata, and 47.1% for S. alba. Meanwhile , a carbon fraction value of 46.82% can be used for all true mangrove species to estimate the carbon stock in forests with heterogeneous mangrove species.

Effect of physiographic type and harvesting age on biomass yield, chemical composition, and carbon sequestration of mangrove plantations for biofuel feedstock production

Many coastal communities of SE-Asia, including Thailand have managed mangrove forests for charcoal production. However, understanding and managing the harvesting age of mangrove plantations in different ecotypes is limited for sustainable biofuel production. Therefore, the objectives of this research were to determine the effect of physiographic type and harvesting age on the biomass yield, chemical composition, CO2 adsorption of aboveground mangrove biomass. The data were collected during 2018–2019 from two geographical types including the riverine and basin mangrove plantations in Samut-Songkhram, Thailand. The experimental plots were selected at different ages (5, 10, and 15 years). The riverine mangrove forest had higher dry aboveground woody biomass, calorific value, and CO2 adsorption than did the basin mangrove forest. For both mangrove ecotypes, there were no significant differences in chemical elements. Extending harvesting age from 5 to 15 years tended to increase the woody biomass yield and quality, and CO2 adsorption of mangrove forests. With increasing harvesting age, the dry aboveground woody biomass, calorific value, and CO2 adsorption of mangroves increased 34.4–283.9 t ha−1, 3841.1- 3924.9 kcal kg−1, and 55.6–453.4 t CO2 ha−1, respectively, but ash and N content decreased 4.8–3.4% and 0.2–0.1%, respectively. Compared with other ages, extending harvest until 15 years yielded the highest potential biomass for biofuel feedstock production and carbon sequestration in both mangrove ecotypes.

The carrying capacity of estuarine mangroves in maintaining the coastal urban environmental health of Southeast Sulawesi, Indonesia

This study aims to elucidate the carrying capacity of estuarine mangroves in Southeast Sulawesi, to maintain environmental health of its coastal cities. The concentrations of mercury (Hg), Copper (Cu), Manganese (Mn), Lead (Pb), Zinc (Zn), and Nickel (Ni) were analyzed in sediments and mangrove tissues samples from Kendari bay and Tinanggea estuaries. This was followed by the determination of translocation and bioaccumulation factors, as well as the total accumulation of heavy metals on a landscape level. The results showed that the sediment in Kendari Bay had higher heavy metal concentrations than in Tinanggea, indicating the anthropogenic impact of the highly populated city of Kendari. Moreover, the roots and stems of mangroves had higher heavy metal concentrations than the leaves. Overall, the Bioconcentration Factors (BCF) of Hg, Cu, Mn, Pb and Zn metals were >1, indicating that estuarine mangroves have a higher phytoremediation capacity for heavy metals. Estuarine mangrove biomass also enables the high accumulation of heavy metals in both Kendari bay and Tinanggea, signifying the greater phytoremediation potential of urban estuarine mangroves. Based on these findings, the study supports the conservation and management of mangroves in urban estuaries to maintain the environmental health of coastal cities.

A Review of SAR Image Processing for Mangrove above Ground Biomass Estimation

Mangrove biomass monitoring has become critical today, as it aids in measuring the amount of carbon that will be contained in these forests in the future. Remote sensing is possibly the solution for estimating AGB on a large scale. It allows biomass assessments over large areas, providing a spatially comprehensive measure of forest biomass variance in a relatively short time and at a low cost. Because of the penetration capability of radar remote sensors, the high-frequency L-band and P-band can be used to measure aboveground biomass effectively. The study emphasizes the importance of Synthetic Aperture Radar imaging and the correlation between backscatter reflectance of remotely sensed data and live biomass over a given area. Despite many studies on the use of machine learning algorithms for biomass estimation, no single model fits all problems. Furthermore, finding the best machine learning model is critical for advancing global expertise in the field of mangrove forest management. The hybrid models such as extreme gradient boosting regression (XGBR) and extreme Gradient Boosting (XBoost) are also used along with regression models linear regression, multilayer perceptron (MLP), and machine learning approaches like support vector Machine (SVM), random and random forest (RF) is used in mangrove studies. In comparison to the allometric equations based on ground truth data, remote sensing methods are coming up as an effective tool for AGB estimation of mangroves. This vision survey focuses on SAR radar remote sensing-based studies in mangrove forest biomass estimation and the limitation of SAR imaging in AGB estimation.

Korelasi indeks keanekaragaman dan kerapatan tegakan dengan simpanan karbon mangrove Estuari Perancak

Land use change is a huge threat for mangrove ecosystems,which are known for their high carbon sequestration and storage capacity.Vegetation restoration efforts are often undertaken, but fail to restore optimal ecosystem carbon sequestration. The mangrove forest of Perancak Estuary with a history of restoration project was made the subject of this research. The objectives include: (i) estimation of mangrove biomass and sediment carbon stock; (ii) comparison of restored, mixed and natural mangroves’ total carbon stock; (iii) correlational analysis between stand density and diversity indices with ecosystem carbon stock. Nine sampling points were determined within three mangrove categories (mixed, natural, restored). Stand characteristics and diameter at breast height (DBH) were measured to allometrically estimate biomass carbon. Sediment carbon was analyzed with Loss on Ignition (LOI) method. Correlational analysis was done with Pearson’s correlation coefficient. Total ecosystem carbon stock is 4472,93 tonnes ha-1 (biomass C: 4046,31 tonnes ha-1; sediment C: 426,62 tonnes ha-1). Highest carbon stock value was found on restored mangroves due to high contribution of sediment C offsetting its low biomass C. Lowest carbon stock value was found on natural mangroves due to decreased root biomass production and increased decomposition due to change in tidal regimes. There is a strong positive correlation between stand density and biomass carbon. Simpson index of diversity has a stronger (though non significant) correlation with biomass carbon than Shannon-Wiener index.

Carbon Sequestration of Above Ground Biomass Approach in the Rehabilitated Mangrove Stand at Jepara Regency, Central Java, Indonesia

Highlight Research Mangrove rehabilitation area has a better potential for carbon sequestration The more trees that grew and developed with a large DBH size the more affected the biomass, carbon content and carbon sequestration of mangroves. Among the four species studied, mucronatais characterized by highest carbon density storage Temperature and salinity affect the value of mangrove biomass, carbon content, and carbon sequestration Abstract Among its many advantages, mangroves have a function as carbon sequestration and storage. The aim of this study was to determine the differences in the ability of various rehabilitated mangrove species of carbon Sequestration of Above-Ground Biomass. This study was conducted from June 2020 to December 2021 in Kedung, Mlonggo, and Keling Subdistricts, Jepara Regency, Central Java, Indonesia. The mangrove plantation was a result of a rehabilitation programme sponsored by a society and the local government since 2009. Carbon sequestration measurement in tree biomass was estimated by a non-destructive method i.e., by measuring the Diameter at Breast Height (DBH). Statistical analysis to determine the relationship between carbon storage in several species of mangroves and the environmental factors were performed using XL stat 2022. There were 4 (four) mangrove species found i.e., Avicennia marina (Forssk) Vierh, Rhizophora apiculata (Blume), Rhizophora mucronata (Lamk), and Sonneratia alba Sm. The highest CO2 absorption (397.21 tons ha-1) was obtained both in Kedung and Mlonggo stations with R. mucronata, whereas in Keling station with R. apiculata the absorption was 54.27 tons ha-1. The results of Principal Component Analysis (PCA) showed that the number of trees and DBH had a relationship with biomass, carbon content, and carbon absorption. Diameter at Breast Height in mangrove species can be used as indicators to assess carbon sequestration in Above Ground Biomass.

SYSTEMATIC STUDY OF CARBON SEQUESTRATION OF MANGROVE FORESTS AT RAIGAD DISTRICT COAST, MAHARASHTRA, INDIA

Mangrove forests are highly productive ecosystems with carbon sequestration rate almost equivalent to tropical green forests. Mangroves distribute proportionally more carbon below ground and possess higher below to above ground carbon mass ratio as compared to any other forests (Kathiresen, 2004). Mangrove is amongst the most carbon rich biomes containing more than 950 tC/H. The said study overlooks destructive and non-destructive methods of the carbon sequestration. It is conducted as a comparative assessment of the carbon sequestration potential of mangrove and non-mangrove regions. By means of methodology of calculating Soil Bulk Density (gcm -3) and Total Organic Carbon (TOC) in mangroves soils (El Wakeel and Riley, 1956) and Carbon Sequestration Rate (CSR) is estimated based on the sediment rates and TOC content of the soil (Duan Xiaonan et al (2008). The systematic assessment conducted at West Coast of Maharashtra; shows mangrove region with Avicinnia marina species and in non–mangrove region total carbon in soil (%) recorded 17.15% and 4.52 percent respectively. Total Soil Carbon Stock recorded is 431 million g / Ha at mangrove region and 105.7 million g / Ha at non mangrove region. After methodical estimation of biomass and carbon stock of mangroves (English et.al, 1997 and Kaufman and Donato, 2012), total carbon stock of mangrove stand was recorded 393.14 mg/Ha and that of non-mangrove stand was recorded to be 91.7 mg/Ha. It shows that mangroves absorb almost 315.14 percent more carbon than non-mangrove region. In other words, carbon stock in Avicinnia marina stand found to be almost 3 times more than non-mangrove zone.

Carbon Absorption Value of Bruguiera gymnorrhiza in the Coastal Area of Dulupi Village, Boalemo District

Carbon dioxide (CO2) levels in nature are increasing along with the development of human civilization. Mangrove forests can absorb and store carbon in large quantities and a long time so that it can become a strategy in mitigating climate change. This study aims to determine the Carbon Absorption Value of Above Surface Bruguiera gymnorrhiza in the Dulupi Coastal Mangrove Area, Boalemo Regency. This research is a quantitative descriptive study by measuring the density of Bruguiera gymnorrhiza mangrove vegetation using the distance method (Point-Centered-Quarter-Method). The density value of the mangrove species Bruguiera gymnorrhiza found in the coastal area of ​​Dulupi Village, Boalemo Regency is 12.49 trees/ha with an average distance of 11,231 m/tree. The calculation results of the total stem biomass value obtained from the sum of each individual Bruguiera gymnorrhiza mangrove biomass obtained a value of 12,251.37 Kg. The carbon absorption content in the leaves of the mangrove species Bruguiera gymnorrhiza in the coastal area of ​​Dulupi Village, Boalemo Regency, from all sample trees was 449.26 kg C/cm2 with an average carbon content of each sample tree's leaves of 17.97 kg C/cm2. So that the total carbon absorption potential of the stems and leaves of the Brugueira gymnorrizha mangrove species is 12,700.63 kg C/cm2.

Mangrove biomass sequestration in Benoa Bay

Mangrove ecosystems are coastal ecosystems that can store carbon three times higher than all other forests on earth. Current conditions show a decrease in mangrove forests and damage to mangrove ecosystem conditions that impact reducing mangrove carbon sequestration. Data relating to the potential of sustainable mangrove biomass is currently lacking, so research is needed. The purpose of this study was to determine changes in the amount of mangrove biomass at permanent stations temporally. This research was conducted at 10 sample points in the Benoa Bay area using a stratified purposive sampling method with a quadrant transect measuring 10 meters x 10 meters. Data were collected by measuring DBH on each mangrove stand within the transect. Data analysis was conducted using the common allometric equation by including the wood-specific gravity per species. In general, there was an increase in the average biomass in each plot with an average of 1.315 tons/ha at six months different. This shows that the larger the diameter of the stand, the greater the biomass produced.

Aboveground Biomass Estimation of Mangrove Ecosystem in the Anambas Islands Using Remote Sensing Data

The Anambas Islands is located in the Natuna Sea - the southern part of the South China Sea, encompassing vital marine ecosystems. Among these ecosystems, the mangrove stands out as crucial in the Anambas, playing an important role in providing a range of ecosystem services. However, spatial information regarding the condition of this ecosystem is very limited. In this study, our focus was on estimating and mapping the aboveground biomass (AGB) of mangroves across the Anambas using a combination of field survey and satellite remote sensing data. We employed seven vegetation indices along with five regression methods to determine the most suitable combination for producing an AGB. Our findings revealed that the incorporation of Sentinel-2 remote sensing images and field survey data can be used to model the AGB. The best combination model was the Modified Soil Adjusted Vegetation Index (MSAVI) and polynomial regression, achieving an accuracy of 72.09%. Anambas was estimated to possess a potential AGB of 369,371.47 tonnes and a carbon stock of 173,604.59 tonnes. These findings provide valuable information for regional conservation strategies, including the identification of protected zones, the establishment of a baseline for mangrove conditions, and the assessment of carbon credit in the Anambas.