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Roots play a fundamental role in forest ecosystems, but obtaining samples from deep layers remains a challenging process due to the methodological and financial efforts required. In our quest to understand the dynamics of Eucalyptus roots, we raise three fundamental questions. First, we inquire about the average extent of the roots of two contrasting Eucalyptus genotypes. Next, we explore the factors that directly influence the growth and depth of these roots, addressing elements such as soil type, climate, and water availability. Lastly, we investigate how the variation in Eucalyptus species may impact root growth patterns, biomass, and carbon stock. In this study, we observed that the maximum root depth increased by an average of 20% when genotypes were grown on sites with higher water availability (wet site). E. urophylla stands had a higher biomass and carbon stock (5.7 Mg C ha−1) of fine roots when cultivated on dry sites (annual rainfall~727 mm) than the wet sites (annual rainfall~1590 mm). In E. grandis × E. camaldulensis stands, no significant differences were observed in the stock of fine root biomass (3.2 Mg C ha−1) between the studied environments. Our results demonstrated that genotypes with greater drought tolerance (E. grandis × E. camaldulensis) tend to maintain higher stocks of fine root biomass (3.2–6.3 Mg ha−1) compared to those classified as plastic (E. urophylla), regardless of the edaphoclimatic conditions of the cultivation site. Finally, our research helps understand how Eucalyptus trees adapt to their environment, aiding sustainable forest management and climate change mitigation. We also provide a practical tool to estimate underground biomass, assisting forest managers and policymakers in ensuring long-term forest sustainability.

Lowland tropical rainforests provide an abundance of biodiversity as well as dynamic and stable ecosystems. These forests include tropical peat forests in various locations and forest types that have vegetation structure and composition characteristics, and carbon stocks that still need to be explored more deeply. Research on the structure and the composition of the vegetation and carbon stock in the old secondary peat forest was carried out in the protected areas of Bukit Batu, Riau Province, and Muara Merang, South Sumatra Province. Based on a 1-hectare permanent plot established in Bukit Batu and Muara Merang, 25 subplots of 20 m by 20 m were established in each location for measurement purposes. The results showed that Bukit Batu and Muara Merang had 42 and 36 species belonging to 26 and 20 families, respectively. Bukit Batu had a species diversity index (H’) of 2.93, and the dominant tree species were Palaquium xanthochymum with an importance value index (IVI) = 66.27%, Eugenia sp. (IVI = 32.76%), and Litsea sp. (IVI = 18.39%). The Muara Merang location had a species diversity index (H’) of 2.82, and the dominant tree species were Eugenia sp. (IVI = 60.88%), Alseodaphne insignis (IVI = 26.34%), and Adenanthera pavonina (IVI = 22.11%). In Bukit Batu, forest stands with a diameter of ≥10 cm contained a biomass of 178.10 tonnes/ha and carbon stock of 83.70 tonnes C/ha, which is equal to 307.20 tonnes CO2/ha. Meanwhile, in Muara Merang, it was 190.41 tonnes/ha and 89.49 tonnes C/ha, which is equal to 328.44 tonnes CO2/ha. This research, especially that in Bukit Batu, Riau Province, enriches the data and information available to date and is very useful in supporting restoration practices in Riau Province’s Giam Siak Kecil Biosphere Reserve, which was designated by UNESCO as part of the Man and Biosphere Program.

Spatialization of biomass and carbon stocks is essential for a good understanding of the forest stand and its characteristics, especially in degraded Mediterranean cork oak forests. Furthermore, the analysis of biomass and carbon stock changes and dynamics is essential for understanding the carbon cycle, in particular carbon emissions and stocks, in order to make projections, especially in the context of climate change. In this research, we use a multidimensional framework integrating forest survey data, LiDAR UAV data, and extracted vegetation indices from Landsat imagery (NDVI, ARVI, CIG, etc.) to model and spatialize cork oak biomass and carbon stocks on a large scale. For this purpose, we explore the use of univariate and multivariate regression modeling and examine several types of regression, namely, multiple linear regression, stepwise linear regression, random forest regression, simple linear regression, logarithmic regression, and quadratic and cubic regression. The results show that for multivariate regression, stepwise regression gives good results, with R2 equal to 80% and 65% and RMSE equal to 2.59 and 1.52 Mg/ha for biomass and carbon stock, respectively. Random forest regression, chosen as the ML algorithm, gives acceptable results, explaining 80% and 60% of the variation in biomass and carbon stock, respectively, and an RMSE of 2.74 and 1.72 Mg/ha for biomass and carbon stock, respectively. For the univariate regression, the simple linear regression is chosen because it gives satisfactory results, close to those of the quadratic and cubic regressions, but with a simpler equation. The vegetation index chosen is ARVI, which shows good performance indices, close to those of the NDVI and CIG. The assessment of biomass and carbon stock changes in the study area over 35 years (1985–2020) showed a slight increase of less than 10 Mg/ha and a decrease in biomass and carbon stock over a large area.

This study examines the impact of silvicultural and land-use management practices on carbon sequestration in peri-urban forest ecosystems, with a particular focus on human-induced carbon dynamics. The study area’s complex profile spans from a compact native forest to varying degrees of fragmentation. This included areas undergoing secondary succession forest without silvicultural interventions (No-SI) alongside sites subjected to high-intensity (High-SI) and low-intensity silvicultural interventions (Low-SI). The research assessed carbon stocks and sequestration in different carbon pools (living biomass, dead organic matter and soil) using field data, allometric equations and laboratory analysis. Findings reveal a significant correlation between the intensity of anthropogenic interventions and variations in carbon stocks. The CASMOFOR model facilitated the reconstruction of carbon stock and carbon-stock change dynamics over four decades (1980–2022), showing disparities in carbon storage capabilities linked to the structural characteristics of the sites. The Low-SI site had the highest carbon stock in all carbon pools (378 tonnes C ha−1), which is more than double compared to High-SI (161 tonnes C ha−1) or No-SI sites (134 tonnes C ha−1). However, the secondary succession forest (No-SI) demonstrated the highest annual carbon stock change (4.4 tonnes C ha−1 year−1), two times higher than the Low-SI mature stand (2.2 tonnes C ha−1 year−1), emphasising the resilience of forest ecosystems to recover and sustain carbon sequestration capacities after harvesting if forest land use remains unchanged. The study underscores the significant importance of anthropogenic interventions on carbon dynamics, especially for living tree biomass, which has consequences in enhancing carbon sequestration and contributing to emission reduction targets.

The spatial–temporal distribution and evolution characteristics of carbon stock under the influence of land use changes are crucial to the scientific management of environmental resources and the optimization of land spatial layout. Taking the Xiamen–Zhangzhou–Quanzhou urban agglomeration in the southeastern coastal region of China as an example, based on seven land use types from 1990 to 2020, including cultivated land, woodland, and construction land, we quantitatively investigate the spatial–temporal patterns of carbon stock development and the spatial correlation of carbon stock distribution. Additionally, two scenarios for the development of urban and ecological priorities in 2060 are established to investigate the effects of land use changes on carbon stock. The results indicate that (1) the research area has formed a land use spatial pattern centered around urban construction in the eastern bay area, with the western forest area and coastal forest belt serving as ecological barriers. Carbon stock is influenced by land use type, and the distribution of total carbon stock exhibits a spatial aggregation phenomenon characterized by “low in the southeast, high in the north, and medium in the center”. (2) Distance of trunk and secondary roads, elevation, slope, watershed borders, population size, and gross domestic product (GDP) factors are the main drivers of the growth of land use types. The primary causes of the reduction in carbon stock are the widespread conversion of cultivated land, woodland, and grassland into construction land, as well as water and unused land. (3) In 2060, there will be a decrease of 41,712,443.35 Mg in the urban priority development scenario compared to 2020, and a decrease of 29,577,580.48 Mg in the ecological priority development scenario. The estimated carbon stock under the two scenarios varies by 12,134,862.88 Mg. The average carbon storage of Zhangpu County, Quangang County, and Jimei County is expected to rise by one level under the ecological protection scenario, indicating that the vast forest area can become a potential area to maintain carbon stock. It is crucial to encourage the coordinated development of peri-urban agroforestry and ecological barriers, as well as to establish a harmonious spatial pattern of land use and carbon stock at the scale of urban agglomerations.

Mangroves are the remarkably productive ecosystems of the world which losses its natural existence to a great portion and presently emphasis is given on its plantation for future conservation. Thus, present study focused on the development of biomass models for the Sonneratia caseolaris (L.) and Sonneratia apetala (Buch-Ham), and assessment of carbon stock for the plantation of central coastal areas of Bangladesh. Semi-destructive approach was applied for estimating the biomass of trees. The best-fit TAGB models for S. apetala and S. caseolaris plantations were Ln (TAGB) = -1.89 + 2.10 * Ln(D) + 0.23*Ln(H), and Ln (TAGB) = -3.09 + 2.31*Ln(D) + 0.35*Ln(H), respectively. Carbon stocks in TAGB and below-ground were estimated for a young mangrove plantation (40 years) with Sonneratia apetala separately. The mean ecosystem carbon stock (above- and below-ground) of young and mature were estimated to be 350.53 ± 14.23 t C/ha and 483.64 ± 16.35 t C/ha, respectively which varied significant (p

The global interest in increasing the world's carbon stocks is skewed towards perennial woody ecosystems. But a continuous shortage of land stands in the way of achieving the goal. We must therefore aim to explore viable alternatives. The banana as a potential carbon sequester attracted little attention from researchers. Therefore, this study aimed at estimating the potential of bananas in different states of India as potential carbon sequesters. Data was collected from twelve major banana producers between January 2021 and December 2022. One hundred banana gardens were sampled in each of the 12 banana-producing states, covering the major bananas grown (AAA, AAB, and ABB). The above-ground (AGB) and below-ground (BGB) biomass were calculated using the allometric equation with pseudostem volume as the allometric parameter. The dry weight obtained from the allometric equations was then converted to carbon using a dry weight to carbon conversion factor. Sequestered carbon varied with the AAA, AAB, and ABB of bananas. Banana plant carbon stock was also found to be very small, ranging from 2.573 to 6.407 t/ha, compared with very high soil carbon ranging from 39.55 to 77.14t. In all the banana-cultivating states, the proportion of carbon contained in the plant to that in the soil was only 8.286 percent, and that of soil carbon accounted for 91.714%. At the national level, the banana crop sequestered 48.627 million metric tonnes of carbon, with soil carbon accounting for 44.798 metric tonnes and plant carbon accounting for only 3.828 metric tonnes per year. Despite these small amounts of plant carbon, the banana cropping system enriches the soil by enabling much more carbon to be sequestered into the soil in amounts comparable to other perennial plantations.

Mangroves are one of the coastal vegetation that can mitigate carbon (carbon sink and carbon storage). This study aimed to determine the potential for soil carbon stock found under stands of mangroves in Lembar Bay, West Lombok, and West Nusa Tenggara. The research began with the identification of the species and then proceeded toa sampling of the soil, which was then analyzed using the Walkley and Black method. The results showed that there were ten species of mangroves, namely, Rhizophora stylosa, Avicennia lanata, Avicennia marina, Bruguiera gymnorrhiza, Ceriops decandra, Excoecaria agallocha, Lumnitzera racemosa, Scyphiphora hydrophyllacea, Thespesia populnea, and Xylocarpus maluccensis. The highest soil carbon content percentage was found in the lower soil of the A. lanata (1.43 %C) mangrove, and the lowest was found in the lower-stand soil of E. agallocha (0.21 %C). Meanwhile, the carbon sinks per meter were 0.002-0.066 gC/m2, with an average of 0.020±0.020 gC/m2. The estimated total soil carbon sink in 10 mangrove stands was 0.20-6.60 tons C/ha, with an average of 2.18±2.010 tons C/ha. The average total estimated soil carbon stock found in 20.49 ha of the mangrove area studied was 44.67 tonsC, which is equivalent to 263.69 tonsC in a mangrove area of ​​120.96 ha in Lembar Bay.

We investigated the impact of land use types and topographical variables on the diversity of wood species and their carbon stocks in the studied agroecosystems. A generic allometric equation developed for woody plants in agricultural landscapes was used to estimate the carbon stock. We used a mixed-effects linear model using the lmer function in the lme4 package to test the effects of land use types and topographic variables on wood species diversity (Shannon diversity) and stem carbon stock potential. Our study result showed that there is significantly higher woody diversity (P < 0.05) in forests, home gardens and riverine than in grazing lands and croplands. Conversely, woody DBH (cm) and height (m) are relatively higher for croplands followed by grazing land, but lower for home garden and forest land use. There is a statistically significant difference between land use types in their carbon stock (χ² (4) = 18.164, p=0.0011), with forest having the highest total carbon stock, followed by home gardens, but grazing land having the relatively lower total carbon stock of woody species. The study finds that species diversity has a positive and significant (P0.05) effect on aboveground and belowground carbon stock. The tree species' structural attributes such as height, DBH size, and basal area (BA) have a positive and statistically significant (P < 0.05) effect on carbon stock. The study also found that only a few high DBH class (old growth) tree individuals that are deliberately spared in cropland and grazing land matrix have a high carbon stock contribution. For example, seven species, Podocarpus falcatus, Ficus vasta, Prunus africana, Schefflera abyssinica, Ficus sur, Ekebergia capensis, and Apodytes dimidiate, contribute an estimated 70% of the estimated total carbon stock in the landscapes. These results indicate the need to protect such scattered old-trees in agricultural landscapes both for biodiversity conservation and carbon sequestration thereby integrating climate change adaptation and mitigation strategies into subsistence farming systems.

Over the last two decades, bamboo has received increasing attention owing to its socio-economic and environmental importance. Environmentally, bamboo plays an important role in carbon sequestration, thus enhancing climate change mitigation. In Cameroon, knowledge about the importance of Bambusa vulgaris Schrad. ex J.C.Wendl. to climate change mitigation is deficient, despite the fact that it is the most abundant bamboo species in Cameroon's Bimodal rainforest agroecological zone (Agroecological zone 5 - AEZ5). This study was initiated to develop allometric equations and estimate carbon stocks of B. vulgaris in Cameroon's AEZ5. The destructive, clump-based method was used for bamboo biomass data collection on 40 clumps and 86 culms. Regression analyses were performed to obtain allometric models for B. vulgaris biomass prediction which were used for B. vulgaris carbon stocks estimation in AEZ5. The best allometric model for culms was obtained when all predictive variables including age, diameter and height were considered into the model. For clump, the best model was obtained when the number of culms per clump, girth and average diameter were considered in the model. Model quality adjustment was better for clump aboveground biomass (AGB) compared to those of culm AGB. The model of B. vulgaris of the evergreen rainfall forest was validated with a bias of 45.5 %. Bamboo aboveground biomass proportions were 77 %, 15 % and 8 %, respectively for culms, branches and leaves. The mean density and carbon stocks of B. vulgaris were estimated at 2,0679 culms.ha−1, 257 clumps.ha−1, and 61.65 tC ha−1. B. vulgaris has a veritable carbon sequestration capacity which policymakers should consider in climate change mitigation strategies like those linked to payments for ecosystem services, voluntary carbon stocks market, Bonn Challenge, AFR100 initiative, and the Paris agreement ratified by the government of Cameroon.

Urban trees and forests play a vital role in maintaining the balance of urban ecosystems and mitigating global warming. However, due to the lack of data and information on the potential of urban forests, their importance remains largely unknown. This study aims to describe citizens' perceptions of trees and assess the forest community's density, diversity, and carbon stock in the residential area of Bobo-Dioulasso, the second-largest city in Burkina Faso.To carry out the study, tree inventories, and interviews were conducted on 240 selected dwellinghouses using a two-stage stratified sampling approach. The sample was allocated proportionally to three strata based on their population size: the center town (20 %), pericenter (20 %), and periphery (60 %). Trees were found in 86 % ± 0.5 % of dwellings, with an average of four trees per dwellinghouse (4 ± 1). About 63 % of households reported planting trees in their homes, including along roadsides. The main motivations for planting trees were for fruits, shading, and ornamental purposes. However, factors such as discomfort, property ownership, and management costs discouraged some residents from planting more trees.A total of 934 trees belonging to 69 species and 30 botanic families were counted in the study sample. The most abundant species families were Anacardiaceae, Moraceae, and Moringaceae. Mangifera indica (41 %), Ficus polita (12 %), and Moringa oleifera (8 %) had the highest relative densities of all species found in dwellings.Using existing allometric equations, the study estimated that the residential area trees stored about 210,000 tons of carbon dioxide equivalent. Based on these findings, it is recommended that city governments implement an action plan to promote urban forestry to strengthen and protect urban forest cover.

Under the background of global climate change, the role of carbon storage in mitigating the increase of atmospheric CO2 concentrations is of paramount importance. However, land use and land cover change (LULC) resulting from urban sprawl disturbs the level and distribution of carbon storage. This study aims to explore the spatiotemporal variability of carbon storage and the correlations between that and urban development for China’s 369 cities in 2000, 2010, and 2020. The InVEST model and several multiple linear regression models are employed and the results show that: (1) Cities in western China sequester a large amount of carbon (maximum greater than 2000 TgC) and only some of them, from 2010 to 2020, can maintain a positive change in carbon storage. The rest of China shows a negative change, but a higher carbon storage per area (maximum greater than 0.01 TgC/km2 in the east). Moran's I shows that such variability has a significant spatial autocorrelation. (2) The intensification of the population, the growth of economy, and urbanization are the main factors influencing carbon storage, which are not only reflected on the national scale but also have different local characteristics in different regions. Cities in China's inland regions (e.g., western, some central, and northeastern China), most of which are developing cities, show more diversified impacts of their urban development on carbon storage. However, in developed cities, mostly concentrated in the eastern region, such impacts and variations show a more unified trend. Considering that environmental policy is often a national action, therefore, to strengthen the carbon sequestration capacity of cities, it is necessary to formulate not only a unified leading policy from the national level but also the practical policies of local governments of cities that match their development stages.

Even though, the blue carbon ecosystems are gaining keen research interest around the globe, the carbon stock of South-West coast of India was poorly reported, and this study is a pioneer attempt and will be an important document for filling the gaps in uncertainties in global carbon stock assessment and also will increase knowledge on biomass variability among mangrove species and mangrove habitats. The study also highlighted the vital role of biomass carbon pool for long-term soil carbon burial. We estimated the above and below-ground biomass carbon stock of 13 mangrove species using two common allometric equations and species-specific equations and reported a very high mean total living biomass carbon stock of Kochi mangroves at 237.19 ± 113.82 Mg C ha−1, 295.78 ± 143.14 Mg C ha−1, and 272.42 ± 132.78 Mg C ha−1 according to Chave's, Komiyama equation and species-specific equation respectively corresponding to carbon dioxide equivalent (CO2e) of approximately 4,37,774.51 Mg CO2e. The biomass stock was significantly differed between the stations (p = 0.000) and also within species (p = 0.020). Among the mangrove species, Avicennia officinalis contributed highest and Bruguiera sexangula contributed least. Variation was observed for biomass stock of mangroves with large trunk diameter while comparing different allometric equations and therefore projected the need for the development of site- and species-specific equations for solving the uncertainty in global mangrove carbon stock. The study observed that dominant mangrove vegetation type, salinity and also the geomorphology of mangrove habitat had strong influence on variability in biomass stock within a small regional area. The study also suggests that understanding the structure and biomass carbon storage of each regional mangrove habitats can be wisely used in mangrove restoration and conservation programmes and in turn for nature-based solutions for climate change mitigation efforts. [ABSTRACT FROM AUTHOR]

Food production in sandy soils has evolved significantly, most notably through the advent of integrated crop–livestock systems (ICLSs). ICLSs increase soil cover, which maintains soil moisture and sequesters carbon (C). Here we investigate the influence of ICLSs on soil physical, chemical, and biochemical properties, and grain yield (GY) in tropical sandy soils in short-time. We compared seven ICLSs in two consecutive crops seasons (with soybean or maize as cash crops) in southeastern Brazil. These were (1) corn + Urochloa brizantha cv. BRS Paiaguás—soybean (ICL-Paiaguás); (2) corn + U. brizantha cv. BRS Piatã—soybean; (3) corn + U. ruziziensis—soybean; (4) corn–soybean under conventional tillage (CT) as a negative control; (5) corn–soybean under no-tillage (NT) as a positive control; (6) Paiaguás grass—continuous grazing (Perennial Paiaguás); (7) and Piatã grass—continuous grazing (Perennial Piatã). Soybean and corn GY data, soil physical and chemical attributes, and soil enzymatic activity were subjected to descriptive statistics and multivariate analysis. CT and NT shared high loadings of H + Al, Al, and soil temperature and low loadings of soil pH, SOM physical and chemical fractions, cationic exchange capacity, and arylsulfatase activity. ICL-Paiaguás and Perennial Piatã had a similarly high loading of total N, humin, total organic carbon, and mineral-associated carbon stocks. The fulvic acid fraction was the most sensitive to C accumulation in the sandy soil under ICLSs. Soil water and thermal regimes were limiting in both CT and NT. The study not only confirms the capacity of conservation mechanisms to enhance soil-based ecosystem functions, but it also highlights the potential of ICLSs to aid sustainable food production even in the context of tropical sandy soils, which frequently receive limited attention in intensive agricultural practices. [ABSTRACT FROM AUTHOR]

Vegetation absorbs carbon dioxide (CO2) emissions during photosynthesis. Covering more areas with trees will increase the CO2 absorption capacity more substantially than other vegetation like bushes, grasses, or rice fields. Trees convert the CO2 captured during photosynthesis into organic carbon to be stored in biomass. Woody trees account for approximately 60% of the total aboveground tree biomass, and trunks, where food reserves produced in photosynthesis are stored, have relatively large biomass compared to other parts of the tree. The biomass of a vegetation stand determines the optimization of air pollutant absorption in urban areas. Yogyakarta City is the center for tourism, education, and cultural activities in Indonesia, which is vulnerable to land-use conversion, a factor of the shrinking green space. This study aimed to estimate carbon stock from vegetation biomass in Yogyakarta City using the remote sensing product SPOT-7 imagery. To calculate the vegetation biomass, the diameter at breast height (DBH) of stands was measured in the field. Then, statistical analyses were performed to determine the correlation and regression between the actual or observed biomass and the Normalized Difference Vegetation Index (NDVI) value derived from the SPOT-7 image. The regression model used was y = 1.4277x - 0.0849. The total biomass produced in Yogyakarta City was estimated at 1,399,487.1 tonnes, which contained 643,764.1 tonnes of carbon stock. [ABSTRACT FROM AUTHOR]

Information on carbon stock in recreational forests is limited in many countries, including Malaysia. Policymakers and resource managers with a lack of such information may make inappropriate decisions in managing forest resources. To address this problem, present study used primary sources of data to assess the carbon stock in Ayer Keroh Recreational Forest (AKRF). This study also used allometric equations to determine the amount of carbon stock in AKRF, which estimated at 449.80 Mg carbon per hectare. The finding indicates society can benefit significantly from multiple ecosystem services even if a forest is established for a single purpose. [ABSTRACT FROM AUTHOR]

Wood specific gravity (WSG) is one of the important variables in biomass and carbon stock estimation through non-destructive method. Present study was conducted in a tropical dry deciduous forest in central India. A non-destructive method was adopted for biomass estimation. Habitat specific WSG of all the species present in the study area was determined using maximum moisture content method. Reported WSG values of the same species were procured from global wood density database. The present paper deals with the comparison of biomass and carbon stock of mature individuals estimated using habitat specific WSG and WSG procured from the database for the same species. Further, comparison was made among biomass and carbon values estimated using habitat specific WSG and without WSG for juvenile individuals. Procured WSG from database for different tree species were found to be higher in most cases than the WSG determined in the habitat. Results envisage that biomass estimates using non habitat specific WSG (database) over-estimate the biomass and carbon stock. Total biomass (including both mature and juvenile individuals) per hectare was 24.2% higher with reported WSG for mature individuals and without WSG for juvenile individuals than using habitat specific WSG for both mature and juvenile individuals. It is calculated that using WSG from data base may result in increased AGB by 1.5 × 108 Mg and 6.6 × 108 Mg at state and national level respectively. We suggest the consideration of habitat specific WSG for biomass and carbon estimation in non-destructive method for both mature and juvenile individuals. [ABSTRACT FROM AUTHOR]

Mangroves are imperative to coastal systems, providing security against extreme weather events by acting as natural barriers. These halophytic plants play a crucial role in mitigating global warming and act as an invaluable resource for consumption. Despite being resilient, mangroves exhibit sensitivity to climatic (e.g., land surface temperature, salinity, etc.) and artificial factors (e.g., land use land cover changes). Numerous past studies recorded the relationship between mangrove growth & development with the constituents above, but those were mostly restricted to visual observation/pattern recognition and single regression analysis. Also, evaluating the simultaneous exploration of multiple aspects influencing mangrove evolution was not prominent. Therefore, the main objective of this study was to focus on the impact of both salinity and land surface temperature on mangrove biomass by the joint venture of remote sensing, geographic information system and several machine learning algorithms. The study considered appropriate mangrove site selections by preprocessing the acquired satellite images. Also, mathematical computations were performed on the raster layers to determine the previously mentioned natural aspects. Finally, several types of regression analysis were conducted to delineate potential patterns governing mangrove vegetation health under temperature and salinity. Mangroves' relationship with temperature and salinity showed an insignificant coefficient of determination. However, the generated response curves postulated that high mangrove biomass could be achieved for a specific temperature window (30-33 °C), and vegetation health could deteriorate at increasing salinity. Overall, the combined effects of surface temperature and salinity on mangrove vegetation were significantly more (i.e., maximum coefficient of determination of 0.31) than individual components alone. [ABSTRACT FROM AUTHOR]

Long-term mono-conservation tillage may not meet the needs to improve soil organic carbon (SOC) sequestration and soil structure stability. A 12-year field experiment was conducted in Northwest China to explore the mechanisms of tillage for improving SOC sequestration, humic substances and soil structure. Rotational tillage, no-tillage and subsoiling increased wheat yield, maize yield and crop residue C by 3%–15%, 8%–15% and 4%–15%, respectively. Meanwhile, rotational tillage, no-tillage and subsoiling increased the conversion rate of crop residue C, resulting in 25%–73% higher SOC sequestration than plowing. Fulvic acid, humic acid and SOC were increased by no-tillage at 0–0.1 m depth, by subsoiling at 0–0.1 m and 0.2–0.4 m depths and by rotational tillage at 0–0.4 m depths. Humic acid and fulvic acid improved soil aggregation. No-tillage increased mean weight diameter (MWD) at 0–0.1 m depth. Rotational tillage and subsoiling improved aggregate stability at 0–0.4 m depths. Due to higher aggregate stability, rotational tillage, no-tillage and subsoiling increased SOC concentrations within macroaggregate and microaggregate, contributing to SOC sequestration. No-tillage rotated with subsoiling had the highest crop yield, SOC stock and MWD, which was the optimal practice in Northwest China. [ABSTRACT FROM AUTHOR]

A study was conducted during 2019-20 to document the predominant tree species, biomass, carbon stock and sequestration of undisturbed natural forest lands (40 years) across the 18 mandals of the Vikarabad district (3386 sq. km area with 109,325 population) of Telangana state. Results revealed that the predominant tree species consisted of Eucalyptus grandis, Tectona grandis, Azadirachta indica and Ficus benghalensis. The highest total biomass, carbon stock and sequestration were registered with Eucalyptus grandis (179.08, 89.54 and 328.62 tonne ha-1 respectively) followed by Ficus benghalensis (140.66, 70.33 and 258.10 tonne ha-1 respectively) and Tamarindus indica (51.60, 25.80 and 94.68 tonne ha-1 respectively) and minimum with Pongamia pinnata (0.31, 0.15 and 0.57 tonne ha-1 respectively). Deviation in volume, carbon stock and sequestration was due to the variation in height, girth and biomass of individual tree species. The results identified the potent tree species with high C stocks and sequestration for regions with similar climates and useful for environmental education to the people for climate change mitigation. [ABSTRACT FROM AUTHOR]

Uncertainties continue to prevail in the potential of natural forests and plantations in carbon stock assessment. The present study was carried out to assess the carbon stock in natural and plantation forests of Manipur using geo-informatics in Imphal East and West districts. The integrated approach of geospatial technology, along with field inventory based data, was used in spatial modeling of biomass carbon of selected natural and plantation forests. The stand density was similar for both LNG and TRS forests (680 individuals ha−1) and lowest for KHP forest (640 individuals ha−1). Paulownia fortunei (770 individuals ha−1) showed highest density among tree species while Tectona grandis (54.07 m2 ha−1) followed by Gmelina arborea (42.18 m2 ha−1) had higher basal area compared to other tree species. The soil moisture content (%) in the natural forest ranged from 19.13 ± 0.47 to 26.9 ± 0.26%. The soil moisture content in the plantation forest ranged from 19.16 ± 0.98 to 25.83 ± 0.06%. The bulk density of natural forests ranged from 1.27 g cm−3 to 1.37 g cm−3 while for plantation forests it ranged from 1.18 g cm−3 to 1.34 g cm−3. Among the studied sites of natural forest, TRS forest had both the highest AGBC value of 132.74 t ha−1 as well as the BGBC value of 38.49 t ha−1. Similarly, among the plantations, T. grandis plantation showed the highest AGBC (193 t ha−1) and BGBC (55.97 t ha−1). On the other hand, Tharosibi forest and T. grandis plantation had the highest total carbon stock for natural and plantation forest with values of 274.824 t ha−1 and 390.88 t ha−1, respectively. The total above-ground carbon stock estimated for the natural forest of KHP, LNG and TRS were 109.60 t ha−1, 79.49 t ha−1 and 132.74 t ha−1, respectively. On the other hand, the estimated total above-ground carbon stock in plantation of GA, PD, PF and TG were 62.93 t ha−1 62.81 t ha−1, 45.85 t ha−1 and 193.82 t ha−1. In the present study, the relationship with the biomass was observed to be better in SAVI compared to NDVI and TVI. The linear regression analysis performed to determine the relationship between the estimated and predicted biomass resulted in a correlation coefficient of R2 = 0.85 for the present study area, which is an indication of a good relationship between the estimated and predicted biomass. [ABSTRACT FROM AUTHOR]

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The existence of forest park areas plays an essential role as carbon sequestration can reduce the concentration of greenhouse gases in the atmosphere. Analysis of carbon potential is essential in determining the amount of available carbon potential. This study aims to analyze the carbon potential in the forest park area Pocut Meurah Intan Forest Park. The study used a descriptive method with the sampling technique of the path system. Data analysis and calculation of carbon potential using allometric equations to calculate the total biomass. Spatial analysis using Arc.GIS 10.4 software and the carbon content analysis was carried out using the ashing method. The results showed that the potential carbon stock of Pocut Meurah Intan Forest Park was 640,282 tons. The carbon potential is the carbon stored above the ground in the form of carbon from above-ground biomass (trees, poles, saplings, undergrowth) and organic matter (necromass and litter). The highest carbon potential was found in the secondary dryland forest land cover with a total of 555,204 tons or 167.6 tons ha-1, followed by shrubs of 78,949 tons or 33.3 tons ha-1, and the lowest potential carbon stock was found in the open field of 303 tons or 2.8 tons ha-1. The increase in land cover in secondary dryland forests causes increased carbon storage. The low potential for carbon stocks is due to land clearing and a small number of stands, resulting in a decrease in potential carbon stocks. [ABSTRACT FROM AUTHOR]

The annual average increase in carbon dioxide (CO2) concentration is touching new heights every year. Global climate change and warming are twin outcomes of record-breaking CO2 levels. The trees outside forests (TOF) are the most promising and suitable components in the ecosystem for combating global warming via carbon (C) sequestration. Urban university campuses are the hotspot regions of TOF. We have attempted to quantify the C stock, C sequestration potential, and C credit value of dominant tree species at Maharshi Dayanand University (MDU), Rohtak. Different volumetric and biomass equations were used for biomass computation. We assessed a total of 29,442 trees (top 10) for measuring phytosociological parameters like total tree count, age, height (H), and diameter at breast height (DBH) to quantify the amount of C stored. The total C stock, C sequestration rate, and monetary value were 78.67 (Mg C ha−1), 19.05 (Mg CO2 ha−1 year−1), and 23,101.59 $ year−1, respectively. Eucalyptus globulus is the most dominant tree species on the campus and topped almost all the quantitative characteristics like total tree count (~40 %), age (25 years), density (D) (55.35 trees ha−1), and total C stock (16.06 ± 9.90 Mg C ha−1). Tree basal area (BA), D, diversity, and H positively affected the total C stocks. When the C market becomes operational, these C credits can be traded while generating additional income for the university. The results from this study can also help calculate the total C footprint of the campus. [ABSTRACT FROM AUTHOR]

Through this study, we established equations for estimating the standing tree carbon stock based on 24 tree species in multiple size classes in a case study at the Ngao Demonstration Forest (NDF) in northern Thailand. Four hundred thirty-nine wood samples from trees in mixed deciduous forest (MDF), dry dipterocarp forest (DDF), and dry evergreen forest (DEF) were collected using non-destructive methods to estimate aboveground carbon equations through statistical regression. The equations were established based on four criteria: (1) the coefficient of determination (R2), (2) standard error of estimate (SE), (3) F-value, and (4) significant value (p-value, α ≤ 0.05). The aboveground carbon stock (C) equations for standing trees in the MDF was C = 0.0199DBH2.1887H0.5825, for DDF was C = 0.0145DBH2.1435H0.748, for DEF was C = 0.0167DBH2.1423H0.7070, and the general equation for all species/wood density groups was C = 0.017543DBH2.1625H0.6614, where DBH is tree diameter at breast height, and H is tree total height. The aboveground carbon stock in the DDF, MDF, and DEF was 142, 53.02, and 12 tons/ha, respectively, and the estimated aboveground carbon stock in the Mae Huad sector at the NDF was 61 tons/ha. [ABSTRACT FROM AUTHOR]

The aboveground carbon sequestration rate (ACSR) of forests serves as an indicator of their carbon sequestration capacity over time, providing insights into the potential carbon sequestration capacity of forest ecosystems. To explore the long-term Spatiotemporal variation of ACSR in the transitional ecotone of the eastern Tibetan Plateau under climate change scenarios, we utilized a forest landscape model that was parameterized with forest inventory data from the eastern Tibetan Plateau to simulate this ecological function changes. The study found that climate warming had significant effect on forests ACSR in different types of forests. ACSR was significantly reduced (p<0.05) in cold temperate coniferous and temperate coniferous forests, whereas it was significantly increased in deciduous broad-leaved forests. However, the impact of climate warming on evergreen broad-leaved forests was found to be negligible. At the species level, climate warming has mostly suppressed the ACSR of coniferous trees, except for Chinese hemlock. The main dominant species, spruce and fir, have been particularly affected. Conversely, the ACSR of most broad-leaved trees has increased due to climate warming. In addition, at the landscape scale, the ACSR within this region is expected to experience a steady decline after 2031s-2036s. Despite the effects of climate warming, this trend is projected to persist. In conclusion, the forests ACSR in this region will be significantly affected by future climate warming. Our research indicates that climate warming will have a noticeable suppressive effect on conifers. It is imperative that this factor be taken into account when devising forest management plans for the future in this region. [ABSTRACT FROM AUTHOR]

Mangrove forests provide valuable ecosystem services to coastal communities across tropical and subtropical regions. Current anthropogenic stressors threaten these ecosystems and urge researchers to create improved monitoring methods for better environmental management. Recent efforts that have focused on automatically quantifying the above-ground biomass using image analysis have found some success on high resolution imagery of mangrove forests that have sparse vegetation. In this study, we focus on stands of mangrove forests with dense vegetation consisting of the endemic Pelliciera rhizophorae and the more widespread Rhizophora mangle mangrove species located in the remote Utría National Park in the Colombian Pacific coast. Our developed workflow used consumer-grade Unoccupied Aerial System (UAS) imagery of the mangrove forests, from which large orthophoto mosaics and digital surface models are built. We apply convolutional neural networks (CNNs) for instance segmentation to accurately delineate (33% instance average precision) individual tree canopies for the Pelliciera rhizophorae species. We also apply CNNs for semantic segmentation to accurately identify (97% precision and 87% recall) the area coverage of the Rhizophora mangle mangrove tree species as well as the area coverage of surrounding mud and water land-cover classes. We provide a novel algorithm for merging predicted instance segmentation tiles of trees to recover tree shapes and sizes in overlapping border regions of tiles. Using the automatically segmented ground areas we interpolate their height from the digital surface model to generate a digital elevation model, significantly reducing the effort for ground pixel selection. Finally, we calculate a canopy height model from the digital surface and elevation models and combine it with the inventory of Pelliciera rhizophorae trees to derive the height of each individual mangrove tree. The resulting inventory of a mangrove forest, with individual P. rhizophorae tree height information, as well as crown shape and size descriptions, enables the use of allometric equations to calculate important monitoring metrics, such as above-ground biomass and carbon stocks. [ABSTRACT FROM AUTHOR]

Forest provides ecosystem services (ES) for community well being through local livelihoods. Tropical sal forest of West Bengal, India is not an exception, rather the tribal communities in forest fringe villages rely on it. The present study aims to quantify and estimate the values of provisioning and regulating ES and their contribution towards local livelihoods. The study revealed variation in provisional services quantity among the villages with highest percentage contribution by fodder and highest monetary value for fuelwood. Estimated monetary value of provisioning ES was INR 1859.00 person-1 year-1. Regulatory services that included carbon stock estimation (68.71 tC ha-1) have potential to sequester 252.17 tCO2 ha-1. Estimated monetary value of trees under regulatory services was INR 25,0221.00 ha-1. The stakeholder perception of such services showed positive responses, supporting the results of ES estimation and valuation. Income from forest products contributed 24% of total household income. Total economic value of ES in the study area was INR 13.052 billion year-1. Thus, studies are required for better understanding of the ES contribution to human well-being of a region to develop sustainable livelihood framework and proper forest management strategies for biodiversity conservation. [ABSTRACT FROM AUTHOR]

In Cameroon, cocoa is produced in association with trees within agroforestry systems (SAF). With their structure similar to that of forests, SAF based on cocoa trees are eligible for the REDD+ mechanism. In forest-savannah transition zones, cocoa-based SAF are established under clearing of forests and savannahs. This study aims to evaluate the woody diversity and carbon stocks of SAF based on cocoa trees in the locality of Makenéné. A floristic inventory of individuals with DBH≥5 cm was carried out in 41 SAF based on cocoa trees of 2400 m², including 18 SAF under savannahs, 23 SAF under forests and 6 controls including 3 plots in the forests of 2400 m² (positive control) and 3 in savannahs of 500 m² (negative control). The estimation of carbon stocks was made using allometric equations. 85 woody species were recorded in forests, 44 and 27 species in SAF based on cocoa trees under forests and savannahs and 7 species in savannahs. Diversity indices are low in SAF based on cocoa trees and raised in forests. The species that store the most carbon in cocoa-based SAF are Dacryodes edulis, Elaeis guineensis and Milicia excelsa while in forests, the species that store the most carbon are Ceiba pentandra, Milicia excelsa and Terminalia superba. The highest carbon stocks are found in forests (135.956 ± 13.70 tC/ha) and SAF under forests (55.814 ± 36.24 tC/ha). The sequestered CO2 produces an economic value of 1465602.98 FCFA /ha for forests, 601671.42 FCFA /ha and 245921.28 FCFA /ha for SAF under forests and savannahs respectively and 182568.11 FCFA /ha for wooded savannahs. SAF based on cocoa trees from the locality of Makénéné are diversified and contribute to climate change mitigation. [ABSTRACT FROM AUTHOR]

Copyright of Ciência Florestal (01039954) is the property of Ciencia Florestal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

he diversity of plants and vegetation in the UNHAS City Forest has a positive impact on the environment. One type of plant species in the UNHAS urban forest is Teak (Tectona grandis L.f.). The community views Teak as a plant that only has economic potential because of the quality of its wood, but it is also necessary to know that this plant is suspected to have potential as an environmental service provider. Therefore, it is necessary to understand the ability of teak plants to absorb carbon dioxide. In this study, carbon stored in teak stands (Tectona grandis L.f.) was measured using a case study in the City Forest at the Hasanuddin University Campus. The method of collecting Emission data were collected from the Aksara Bappenas website, which was used to collect data on the potential of biomass in this study using nondestructive methods. The data collected included the diameter, height, and specific gravity of teak trees. The teak plant diameter was determined by surveying each individual teak plant. The emissions produced by Makassar City in 2022 will be 6,944,242.74 tons of CO2eq. Teak trees located in the urban forest of Hasanuddin University then succeeded in reducing 455.93– 482.48 tons of CO2eq according to carbon absorption calculations. The economic value of carbon reserves located in teak stands in the urban forest of Hasanuddin University ranged from USD 206.76/IDR 2,998,020 tons/ha to USD 218.8/IDR 3,172,600 tons/ha. [ABSTRACT FROM AUTHOR]

Fifty per cent of European peatlands are in a damaged state. While intact peatlands are natural carbon sinks, degraded sites release important amounts of greenhouse gases into the atmosphere, contributing to global warming. Restoration of the hydrological functionality of peatlands has proved to be an efficient tool to avoid these emissions. In France, Tuffnell & Bignon's ministerial report (2019) emphasized the need for peatlands 'integration into the National Low Carbon Strategy, targeting carbon neutrality by 2050. However, current knowledge regarding French peatlands' distribution and carbon stocks is insufficient and does not allow decision makers and managers to prioritize areas for restoration. The most complete database to date is the 1949 Atlas, an inventory of exploitable peat deposits that was conducted during WWII for peat exploitation as fuel. Until its digitalization, the latter database was archived and never used in a scientific study. It provides detailed information about peatland surfaces, peat thicknesses and carbon contents at that time. We estimated peat carbon stocks from French peatlands to be 111 Mt C in 1949 for 63,290 ha identified as peaty sites, the equivalent of 3% of the organic carbon contained in the upper 30 centimetres of French soils. 34% of this stock was held in Lower Normandy (37.7 Mt C) and 12% in the Picardy's region (13.0 Mt C), in large lowland peatlands. However, not all peatlands were prospected in the 1949 inventory and the characteristics of the prospected peatlands may have changed with anthropic disturbances of the last decades, such as draining or climate change. These first results highlight the need for a recent inventory of French peatlands and carbon stocks based on local data aggregation. Data from the 1949 Atlas could help constituting this new inventory but should be validated before being used to describe the present. [ABSTRACT FROM AUTHOR]

The foremost role of forest vegetation in storing biomass and carbon (C) stock constitutes one of the main nature-based solutions to mitigate climate change. In this study, we aimed to quantify biomass and C stock partitioning in multiple vegetation strata (tree, shrub, herb, and ground floor layers) of major forest types in Jammu and Kashmir, Western Himalaya, India. We used a stratified random cluster sampling strategy to collect field data in 96 forest stands of 12 forest types (altitudinal range: 350 to 3450 m) in the study region. We evaluated the degree to which the carbon stock of the entire ecosystem was dependent on the multiple vegetation strata using the Pearson method. Across all the forest types, the average total ecosystem-level biomass was estimated to be 181.95 Mgha−1 (range: 60.64–528.98). Forest strata-wise, the maximum biomass of 172.92 Mgha−1 (range: 50.64-514.97) was found in the tree vegetation, followed by 5.58 Mgha−1 (range: 2.59–8.93) in understory vegetation (shrubs and herbaceous), and 3.44 Mgha−1 (range: 0.97 and 9.14) in the forest floor. The total ecosystem-level biomass showed a peak at mid-elevation coniferous forest types, whereas the lowest was observed in low-elevation broad leaved forest types. At the ecosystem-level, on average, the understory contributed 3% and the forest floor 2% to the total C stock across the forest types. The shrub layer contributed up to 80% of total understory C, with the herbaceous layer accounting for the remaining 20%. The ordination analysis clearly shows that anthropogenic and environmental variables significantly (p ≤ 0.002) influence the forest types' C stock in the region. Our findings have significant implications for conserving natural forest ecosystems and restoring degraded forest landscapes in this Himalayan region, which in turn can lead to better carbon sequestration and climate mitigation outcomes. [ABSTRACT FROM AUTHOR]

A growing number of initiatives at global, regional and national scales propose to plant millions, billions or even trillions of trees as a simple solution to resolve complex environmental problems. However, tree planting is much more complicated than it seems. We summarize the multifaceted decision‐making process needed and offer guidelines to increase the success of the proposed ambitious efforts to increase tree cover world‐wide. Given the varied definitions of and motivations for tree planting, it is critical that stakeholders work together to clearly define the biophysical and socioeconomic goals of each project. Then a series of questions must be addressed about where and how (e.g. planting trees vs. allowing for natural forest regrowth) to most effectively achieve these goals and minimize unintended negative consequences, as well as how, when and by whom success of efforts will be evaluated. Key guidelines to successfully increase tree cover include: (a) first addressing the underlying drivers of deforestation; (b) integrating decision‐making across scales from local to global; (c) tailoring tree planting strategies to clearly stated project goals and planning, adaptively managing and evaluating success over a sufficiently long timeframe; (d) focusing on the forest ecosystem as a whole, and not just the trees; (e) coordinating different land uses and (f) involving stakeholders at all stages of the planning process. Synthesis and applications. Tree planting, along with other strategies to increase tree cover in appropriate locations and contexts, can make a valuable contribution to ensuring the ecological and social well‐being of our planet in coming decades, but only if these efforts are considered as one component of multifaceted solutions to complex environmental problems and are carefully planned, implemented and monitored over a sufficiently long time‐scale with stakeholder engagement and broader consideration of socio‐ecological complexities.

As a key ecosystem for climate change mitigation, wetlands play an irreplaceable role in carbon capture and sequestration. The analysis of wetland carbon stocks and their influencing factors, as well as the prediction of carbon sequestration potential, are of great significance to the conservation and management of wetlands and the achievement of the national "double carbon" target.This study employed ArcGIS 10.8 to vectorize the wetland distribution map of the Wetland Protection and Development Plan of Guizhou Province (hereinafter referred to as the Plan) for three periods (1999-2009, 2010-2018, and 2018-present, respectively) by means of remote sensing visual interpretation and zoned them according to the intensity of karst development in Guizhou Province. The changes in wetland area and carbon stock in Guizhou Province were estimated and analyzed using the life belt research method and biomass estimation method, and the total carbon stock and carbon stock per unit area of key wetlands were estimated and compared with those of all wetlands in Guizhou Province. A calculation model was used to estimate the carbon sequestration potential of the key wetlands in Guizhou Province.The Origin software was applied to analyze the data on all relevant impact factors. The results showed that: ①The area of wetlands in Guizhou Province was 216, 526.95 hm2, 209, 726.85 hm2, and 255, 440.53 hm2 in the pre-, mid-, and late-planning periods, respectively, with an overall decrease and then increase, and the total area increased by 38, 913.58 hm2; ② The wetland carbon stock in Guizhou Province was 3.78×106 t in the late stage of planning, increasing significantly to more than 6 times of that in the early stage of planning(5.97×105 t), among which the carbon stock of the key wetlands was 3.24×106 t, accounting for 85.71% of the province's wetland carbon stock; ③ The carbon sequestration potential of the keywetlands in Guizhou Provincewas 1.14×104 t C/a, and the total carbon sequestration of wetlands is expected to reach 7.99×106 t C and 8.34×106 t C by 2030 and 2060, respectively; and ④ The carbon stock of the key wetlands was positively correlated with DIC concentration, organic carbon content and wetland area and negatively correlated with temperature, indicating thattemperature, DIC concentration, organic carbon content and wetland area had a strong influence on the carbon stock of the key wetlands in Guizhou Province.The results of this study will not only facilitate the understanding of the current status of wetland carbon sequestration in Guizhou Province but also provide a theoretical reference for the contribution of regional wetland ecosystems to the "3060" dual carbon target.

Abstract Background In Ethiopia, highland bamboo has been cultivated in various niches: farmlands, riverbanks, woodlot boundaries, and homesteads, and agroforestry systems. However, the biomass and carbon storage of potential of bamboo forests across niches is not well characterized in Ethiopia. Therefore, this study was conducted to estimate the biomass and carbon storage potential of highland bamboo plantations in northwestern Ethiopia. To this end, a total of 60 circular plots measuring 100 m2 with a radius of 5.64 m were randomly established on the homestead, woodlot, and riverbank plantation niches to conduct the inventory. The biomass storage of bamboo was calculated based on previously published allometric equations. Biomass and carbon stock variations among age-classes and niches of bamboo forests were analyzed using analysis of variance (ANOVA) and subsequent pairwise means comparisons of carbon stocks among niches were performed via post hoc Tukey test at p

Mangroves occur in coastal intertidal zones and play an important role in terrestrial and marine carbon cycles. Accurate estimations of mangrove carbon stocks and sequestration potential can help quantify the contribution of mangroves to addressing climate change and achieving carbon neutrality goals. The carbon stocks and burial rates of different mangrove communities and regions in Guangdong Province were studied through literature collection and data integration. The soil carbon densities of the Rhizophora stylosa and Bruguiera gymnorhiza communities were 0.27 and 0.23 Gg C/hm2, respectively, while the soil carbon density of the Kandelia obovata community was the lowest at only 0.13 Gg C/hm2. The area of mangroves in Guangdong Province is 9,106.2 hm2, the total carbon stock is 1,542.02 Gg C, and the soil carbon density is 0.23 Gg C/hm2. The total carbon reserves of mangroves in thirteen regions are in the following order: Zhanjiang (894.5 Gg C) > Yangjiang (195.4 Gg C) > Jiangmen (97.7 Gg C) > Zhuhai (91.0 Gg C) > Maoming (59.6 Gg C) > Shantou (51.4 Gg C) > Zhongshan (49.2 Gg C) > Huizhou (36.1 Gg C) > Guangzhou (35.1 Gg C) > Shenzhen (18.3 Gg C) > Shanwei (10.8 Gg C) > Dongguan (2.83 Gg C) > Chaozhou (0.11 Gg C). Using the 210Pb method, the sediment accretion rate was found to be 13.47 mm/a. Qi'ao Island had the highest sediment compaction rate of 31.5 mm/a, followed by Zhenhai Bay, with 16.5 mm/a, Shenzhen Futian, with 15.9 mm/a, and Leizhou Bay, with the lowest sediment compaction rate of 7.3 mm/a. The carbon sequestration capacity of Guangdong province is approximately 2.96 Gg C/a, with the Leizhou Peninsula having the highest (6.05 Gg C/a) and Futian, Shenzhen having the lowest (0.66 Gg C/a) capacities. The carbon storage of mangroves in Guangdong Province was 1,542.02 Gg C, which was higher than that in other regions. The carbon sequestration capacity of the mangroves was relatively strong. Therefore, the protection and restoration of local mangroves may substantially contribute to the mitigation of climate change while providing additional benefits. This assessment, on a provincial scale, provides insights into blue carbon sequestration capacity, thus contributing to the synchronous progression of blue carbon management.