ABSTRACT Mangroves can retain both autochthonous and allochthonous marine and/or terrestrial organic carbon (OC) in sediments. Accurate quantification of these OC sources is essential for

the proper allocation of blue C credits. Here, we conduct a global-scale analysis of sediments autochthonous and allochthonous OC contributions in estuarine and marine mangroves using stable

isotopes. Globally, mangrove-derived autochthonous OC was the main contributor to estuarine and marine mangrove top-meter soil organic carbon (SOC) (49% and 62%, respectively). Less marine

allochthonous OC (21%) was deposited than terrestrial allochthonous OC (30%) in estuarine mangrove sediments. Estuarine mangroves accumulated more SOC in sediments than marine mangroves (282

underlining the necessity of accurate OC source quantification for the effective allocation of blue carbon credits. SIMILAR CONTENT BEING VIEWED BY OTHERS SOIL ORGANIC CARBON STOCKS

INCREASED ACROSS THE TIDE-INDUCED SALINITY TRANSECT IN RESTORED MANGROVE REGION Article Open access 13 November 2023 SEAGRASS BLUE CARBON STOCKS AND SEQUESTRATION RATES IN THE COLOMBIAN

CARIBBEAN Article Open access 26 May 2021 LARGE CONTRIBUTIONS OF PETROGENIC AND AGED SOIL-DERIVED ORGANIC CARBON TO ARCTIC FJORD SEDIMENTS IN SVALBARD Article Open access 20 October 2023

INTRODUCTION Mangrove forests are one of the most productive blue carbon ecosystems (BCEs), offering a range of ecosystem services including fisheries production, coastal protection,

sediment fixation, and notably, carbon sequestration1,2,3. Mangrove sediments hold approximately 70% of the whole ecosystem's carbon (C) storage, varying in magnitude geographically,

which is primarily determined by coastal environmental settings (CES, such as estuarine and marine mangroves)4,5. Blue C ecosystems not only sequester atmospheric carbon dioxide (CO2)

through biogenic processes but also serve as repositories for C transported from external sources4,6. Mangrove sediments, in particular, accumulate both allochthonous organic carbon (OC)

from marine or terrestrial origins, facilitated by tidal exchanges, and autochthonous OC derived from mangrove vegetation. Accurate quantification of these OC fractions is essential for the

proper allocation of C credits under certification standards such as the Verified Carbon Standard (VCS) methodology (VM0033)7. Specifically, the VCS protocol requires the deduction of

allochthonous C contributions from the total C sequestration calculations in tidal wetland restoration initiatives8. This distinction not only aligns with the additionality

principle—guaranteeing that C credits support authentic greenhouse gas reduction efforts—but also ensures the strategic deployment of resources to projects with tangible climate mitigate

benefits7,9,10. Thus, the study of sediment OC sources in mangroves is not merely an academic pursuit but a practical necessity for validating the environmental and economic value of tidal

wetland restoration projects. Here, we conduct global-scale analysis of the provenance of soil organic carbon (SOC) sources in mangroves. This study incorporates a comprehensive dataset of

stable isotope signatures, nitrogen to carbon ration (N/C) values and SOC of mangrove sediments, along with relevant environmental and socioeconomic information, including the proximity of

mangroves to rivers. We identified the sources of OC, compared SOC stocks between estuarine and marine mangroves and employed machine learning algorithms to explore the primary factors

influencing SOC sources in mangroves. By shedding light on the SOC sources under different CESs, this study offers new insights into the variations in mangrove SOC, thereby contributing to a

more comprehensive understanding of C cycling in BCEs. RESULTS AND DISCUSSION ORGANIC CARBON SOURCES OF MANGROVE SEDIMENTS This study first compiled 441 observations of δ13C values of

mangrove sediments worldwide, covering most of the mangrove distributed areas (Fig. S1). δ13C values varied from −30.7‰ (_Rhizophora apiculata_ and _Avicennia marina_ forest sediments in

Malaysia) to −6.20‰ (_Sonneratia alba_ forest sediments in Tanzania), with the mean value of −25.1‰ (Fig. S1). Surprisingly, the mangrove sediment δ13C value was less influenced by dominant

species and CES. Locations (longitude and latitude), tidal range, mean annual temperature (MAT), salinity, total nitrogen content and soil particle size fraction were the main drivers of

mangrove sediment δ13C variation (Table S1). Our analysis of global observations revealed that mangrove plant-derived autochthonous OC is the main contributor to the top-meter SOC in both

estuarine and marine mangrove sediments, accounting for 49% and 62% respectively (Fig. 1). In estuarine mangroves, terrestrial OC contributed a notable 30%, contrasting with less marine OC

deposition (21%) (Fig. 1a). Continental values of autochthonous OC varied from 15% in South Africa to 57% in South America (Table 1). To identify the sources of OC, we considered mangrove

litterfall and belowground root production as endmembers, using their mean values for source identification. However, it is worth noting that the contribution of autochthonous OC to the

sediment may be underestimated in this study, as mangrove roots and woody materials may have slightly more enriched δ13C values than leaves4, and our dataset primarily consisted of mangrove

leaves. The contributions of different OC sources were significantly influenced by CES, with varying contributions observed across different countries (Fig. 1, Fig. S2, Table. S2 and Table. 

S3). In marine mangrove sediments, marine allochthonous OC accounted for 38% of the total OC, with autochthonous OC contributing the remaining 62% (Fig. 1b). Individual values of

autochthonous OC contribution ranged from 13% in Iran to 92% in Thailand (Fig. 1a and Table. S3). Autochthonous OC contribution was the highest in South Africa (73%) and the lowest in South

Asia (35.7%, Table 1). Marine OC contributions tended to increase with particulate organic carbon (POC), while factors like canopy height and mean annual precipitation (MAP) were linked to

lower proportional marine OC contributions (Fig. S2a and Figs. S3d, h, j). In estuarine regions, mangrove sediments were found to contain a smaller amount of marine OC compared to

terrestrial OC (Fig. 1a), consistent with previous findings11. The marine OC retained in mangrove sediments is highly regulated by carbon accumulation rate (CAR) and POC contents (Fig. S2a).

Marine particles usually had low OC content, therefore higher sedimentation of marine particles would cause less particulate organic matter (OM) to be imported into estuarine mangroves12.

Instead, abundant POC can continuously provide C sources for mangrove sediments, resulting in more marine OC retained13. Mangrove autochthonous OC contributions were mainly regulated by

location, soil properties, and climatic conditions (Fig. S2b). Autochthonous OC contribution decreased along with longitude (Fig. S4a). Higher MAT and MAP favored plant OC input into soils.

Areas with intense anthropogenic activities or greater development might exhibit a greater autochthonous OC contribution (Figs. S4e and l). It is worth noting that areas with high population

density exhibit higher autochthonous contributions to sediment OC. Anthropogenic nutrient fluxes can act as fertilizers for mangroves, enhancing their growth and consequently increasing the

input of autochthonous OC14,15. Generally, terrestrial allochthonous OC only contributes to OC in estuarine mangrove sediments, which are more susceptible to anthropogenic activities (Fig. 

S2c and Figs. S5c, l). Terrestrial OM is abundant in lignin-phenols, while marine OM is characterized by low C/N ratios and simple composition, which might result in the preferential

decomposition of light fractions in marine OM11,16. We found that greater GDP and human development index (HDI) were negatively correlated with terrestrial OC contribution (Fig. S5c, l).

Anthropogenic activities such as extensive water use for agricultural purposes will reduce the river’s natural flow downstream, which could decrease the C exchange between mangroves and

rivers17. Eutrophic estuaries under intense anthropogenic activities have been found to exhibit high OC decomposition, leading to increased C emissions18. Moreover, dam construction might

have influence on the terrestrial OC retained in mangroves due to blocking the river and the terrestrial OC transported by the river19. SOC STOCKS OF ESTUARINE AND MARINE MANGROVES The areal

extent of estuarine mangroves is far less than marine mangroves, being 43,669 km2 and 103,573 km2, respectively (Fig. 2d, Table. S4 and S5). Globally, SOC stock per unit area was

significantly higher in estuarine mangroves (282 ± 8.1 Mg C ha−1) than marine mangroves (250 ± 5.0 Mg C ha−1, _P_ < 0.05, Figs. 2a, b, c). Combining the mangrove distribution and the

Kriging interpolation, the SOC stocks of the estuarine and marine mangroves were 1502 ± 154 Tg C and 3025 ± 345 Tg C, respectively (Figs. S6, Table S4 and S5). Autochthonous and marine

allochthonous contribution to sediment OC in estuarine mangroves was lower than in marine mangroves (Fig. 1), which can be attributed to the additional input of terrestrial allochthonous

OC20. Estuarine mangroves held greater SOC stock per unit area than marine mangroves (Fig. 2c), indicating the contribution of terrestrial allochthonous OC to mangrove sediments. The

observed pattern was in accordance with that reported by Donato, et al.1. Conversely, Weiss, et al.20 reported a higher sediment SOC stock in marine mangroves (570 Mg C ha−1) than in the

estuarine mangroves (310 Mg C ha−1), and a global synthesis showed that marine mangroves presented a greater C density than estuarine mangroves5. The disparity could be caused by variance in

sampling size. Previous global synthesis resulted from field sampling of 81 observations from 27 sites5, while this study used a much larger dataset of 2356 observations worldwide. As such,

the extensive sampling variance may account for the differences observed in the results. Despite accounting for only 33% of the global mangrove SOC stock (Fig. 3), estuarine mangroves may

face more threats than marine mangroves due to the influx of terrestrial pollutions (including the nitrogen and phosphorus nutrients) carried by rivers, facilitating anthropogenic and

environmental changes within estuarine mangrove ecosystems21. IMPLICATIONS There is increasing interest in using blue carbon ecosystems (BCEs) for their potential climate mitigation and

adaptation benefits through management interventions. This study provided a global dataset of the mangrove sediment OC sources, which can guide future mangrove restoration projects to

receive VCS-approved C credits8. Generally, utilized by microbes and transformed into more recalcitrant C (like mineral-associated OC), allochthonous OC can be more stable than autochthonous

OC when deposited in mangrove sediments22. This global-scale analysis of the provenance of soil OC sources in mangroves reveals the intricate balance between autochthonous and allochthonous

OC contributions to the C sequestration capacity of mangrove sediments. The findings underscore the predominant role of mangrove-derived autochthonous OC in both estuarine and marine

settings, while also highlighting the significant, though variable, contribution of allochthonous OC from terrestrial and marine sources8, facilitated by the later C flux. This distinction

is crucial for the development and implementation of C crediting mechanisms, such as those prescribed by the VCS8, which require accurate accounting of allochthonous and autochthonous OC

sources to ensure that credits support genuine greenhouse gas reduction efforts9. The refinement of our understanding and ability to identify OC sources in these BCEs are important research

areas that can lead to improvements of the calculation of C credit. Moreover, our exploration of how factors such as CAR, POC and socioeconomic variables like GDP and HDI impact the

contributions of different OC sources offers vital insights into the anthropogenic and natural processes affecting mangrove carbon sequestration. The correlation between higher GDP and HDI

with autochthonous OC contributions, for instance, suggests that economic development and human activities can significantly influence mangrove C dynamics, potentially through the

enhancement of mangrove growth via anthropogenic nutrient inputs. Future research should aim to further refine our understanding of OC sources in mangrove sediments, incorporating additional

isotopic analyses and considering the impacts of global challenges such as climate change, deforestation, and land use change. Only through such comprehensive and nuanced approaches can we

fully understand the climate mitigation potential of mangroves and ensure the preservation of their invaluable ecosystem services for future generations. METHODS ORGANIC CARBON SOURCE

IDENTIFICATION We compiled published data on isotope (δ13C, δ15N) and N/C values of global mangrove sediments from the Web of Science using combinations of keywords “mangrove C* source”,

“mangrove isotope”, “mangrove source”, utilizing 100 studies and 441 observations. The database should meet the following requirements: (1) parameters that used to calculate the OC sources

should be reported (either δ13C and N/C or δ13C and δ15N); (2) the work must have been published in peer-reviewed publications; (3) the study must have been a field study in natural

conditions without artificial manipulation. The relative contribution of marine (phytoplankton and macroalgae), mangrove, and terrestrial organic matter to the carbon pools in the top meter

of the mangrove sediments was estimated using two-tracer stable isotope analysis in R (MixSIAR), one of the more modern Bayesian mixing models23. From the literature, we collected isotope

and N/C values for mangrove tissues, riverine POM, phytoplankton, and microalgae to generate mangrove, terrestrial and marine endmembers. Phytoplankton and macroalgae were combined as a

single OC source since their published δ13C or δ15N and N/C were largely overlapped. The average values of those end members were calculated and then used for OC source identification for

the geographically nearest estimate. When the δ13C and N/C values are reported in a study, we preferred to use those values to determine the OC sources. When only δ15N and N/C were reported

in a study, those values were used. Therefore, 362 observations of OC source were identified by δ13C and N/C values, with the rest identified by δ15N and N/C values. We assumed a standard

deviation (SD) equals 0.5 or 0.005 to reflect similar variability of the isotope or N/C values as for the replicated sources of OC24. We looked through all of the collected publications and

we find that among 441 isotope data, 164 of them reported their locations to tidal/ river channel margins, and most of the sampling sites were fringe mangroves (_n_ = 129), while only 25 and

16 were located in interior and transition zones, respectively. This corresponds to our concerns that most of the samples were fringe mangroves because of the easy access and might have

influence on the results. We further conducted analysis to test whether sampling location (interior or fringe) would have influence on the marine OC, mangrove OC and terrestrial OC

contribution to mangrove sediments using GAM, respectively (Table. S7–S9). Models were built by the influencing factors ranks top 30% in each OC random forest model to prevent overfitting.

For the continental or global average OC source contributions, we used the estuarine or mangrove SOC stock to calculated the weighted average. For the detailed information of the datasets,

please check the supporting Excel spreadsheet file. PRIMARY REGULATORS OF ORGANIC CARBON SOURCES The 441 isotope observations were further separated into estuarine and marine mangroves

according to the following conditions: (1) if the sampling site was clearly defined as estuarine or marine mangroves, we used its original classification; (2) when the sampling site did not

meet condition 1, but the sampling map were provided in the literature, we classified estuarine or marine mangroves by the appearance of river or estuaries; (3) if the condition 1 and 2 were

not meet, we used the global estuarine and marine mangrove maps generated in the following steps (Estuarine and marine mangrove mapping) to identify their environmental settings25,26,27.

Additional data were collected to find the primary regulators of OC sources in mangrove sediments. Reported soil properties, including pH, salinity, and particle size (sand, silt and clay

content), were collected. Not all studies reported soil and vegetation properties, data from the nearest site are used to complete the datasets. Mangrove canopy heights were extracted from

public Google Earth Engine (GEE) datasets as vegetation properties in this study28. Open-access global datasets were used to extract the geomorphic and climatic properties. Tidal range and

mean sea level were extracted from Muis, et al.29 in Copernicus platform (https://cds.climate.copernicus.eu/cdsapp#!/dataset/sis-water-level-change-indicators-cmip6?tab=overview). The

particulate organic matter (POC) data were extracted in GEE entitled with Ocean Color SMI: Standard Mapped Image MODIS Aqua data.

(https://developers.google.com/earth-engine/datasets/catalog/NASA_OCEANDATA_MODIS-Aqua_L3SMI). We use the Coastal DEM database30 to retrieve the coastal elevation. We additionally calculated

the relationship of the site elevation within the tidal frame (Z*MHHW) using the following equition31,32: $${Z}_{{MHHW}}^{*}=\frac{{Elevation}-{MSL}}{{MHHW}-{MSL}}$$ where the Elevation is

the data extracted from the above-mentioned DEM datasets, MSL is mean sea level, MHHW is mean higher high water extracted from Muis, et al.29. Recent 60-year relative sea level rise (RSLR)

was provided by Wang, et al.33. The nearest tide gauge data were chosen as the corresponding RSLR of our sampling site. Climatic properties, including mean annual temperature (MAT) and mean

annual precipitation (MAP), were collected from WorldClim (https://www.worldclim.org). Additionally, anthropogenic activities might influence the OC sources of mangrove sediments. Therefore,

socioeconomic properties include gross domestic production (GDP), human development index (HDI), population density, and urbanization. The global urbanization dataset was from Li, et al.34,

and we used the mean value between 2000 to 2013 because most of the collected observations were in this range. GDP and HDI data were from Kummu, et al.35. Population density data were from

the WorldPop website (https://www.worldpop.org). All these socioeconomic databases were available in GEE. Random forest is an integrated machine-learning approach that generates multiple

decision trees and captures nonlinear interactions36. Random forest was applied to the soil, vegetation, geomorphic, climatic, and socioeconomic properties as mentioned above to find the

primary regulators of OC sources in mangrove sediments. Models were separately conducted for the relative contribution of mangrove, marine, and terrestrial OC to mangrove sediments. The

percentage increases in the mean squared error (%lncMSE) were used to assess the relative importance of each influencing factor using the “randomForest” package37. Moreover, we used

“rfPermute” package to assess the significance of each influencing factors38. We used the general additive models (GAM) to determine the general negative or positive patterns. Factors that

ranked at the top 60% in the random forest model were analyzed in the GAM to see their influence on the marine, mangrove, and terrestrial OC source contribution to mangrove sediments. When

none of those factors is significant in the GAM, we still plot the correlation charts between each influencing factor and OC source contribution to see the trend. ESTUARINE AND MARINE

MANGROVES MAPPING The mapping of estuarine and marine mangroves contains two steps, the mapping of global mangroves and the mapping of estuarine regions. The Global Mangrove Watch datasets

are the most commonly used mangrove datasets with public access. Therefore, we extracted the global mangrove distribution in 2020 from Global Mangrove Watch39. For the estuarine region

mapping, we applied a mask of the global estuary distribution developed by Sea Around Us project to mangrove distribution25,26,27. However, we noticed that the estuary distribution only

convers the water, while mangroves around the estuary was overlooked. We therefore combine the estuary distribution with the sampling point in our collection which was clearly defined as

estuarine mangroves to manually draw the boundaries between estuarine and marine mangroves (Fig. S7). SOC STOCKS IN ESTUARINE AND MARINE REGIONS We constructed a comprehensive global

mangrove SOC stock database, collecting as many experiments that fulfilled our criteria as possible. The basic topsoil (0–1 m) mangrove SOC stock per unit area was from Ouyang and Lee40. We

searched the _Web of Science, China Knowledge Resource Integrated Database_ using combinations of keywords “mangrove Carbon”, “mangrove C* stock”, “mangrove SOC” that were published after

2020, and our unpublished field survey data across China. The database should meet the following requirements: (1) SOC stocks or parameters necessary for estimating SOC stocks (bulk density

(BD), SOM or SOC concentration) were reported; (2) the work must have been published in peer-reviewed publications; (2) the study must have been a field study in natural conditions without

artificial manipulation. We further fulfill our dataset with data from Coastal Carbon ATLAS41 (mostly published after 2020 or unpublished data). The final database has 2356 SOC observations,

where 1682 observations were extracted from Ouyang and Lee40, 476 observations were additionally added and 198 observations are from Coastal Carbon ATLAS. To compare the SOC stocks per unit

area in global estuarine and marine mangroves, we used one-way ANOVA to determine the significance. We then analyzed those differences in each country where data were collected to see

whether this pattern applies to the national scale. To estimate the total SOC stock in estuarine and marine mangroves, we conducted the Kriging interpolation in GEE using the collected SOC

stock datasets and mangrove mappings. DATA AVAILABILITY The estuarine and marine mangrove distribution in 2020 generated in this study has been deposited in Data Center of South China

National Botanical Garden, CAS (https://cstr.cn/32129.11.scbg.n57jtsGX) and the Figshare

(https://figshare.com/articles/dataset/Global_marine_and_estuarine_mangrove_distribution_in_2020/27129174). The source data used for organic carbon source identification has been deposited

in Data Center of South China National Botanical Garden, CAS (https://cstr.cn/32129.11.scbg.n57jtsGX) and the Figshare

(https://figshare.com/articles/dataset/Source_data_of_A_global_assessment_of_mangrove_soil_organic_carbon_sources_and_implications_for_blue_carbon_credit_/27129219?file=49475862). Source

data are provided with this paper. CODE AVAILABILITY All custom code that has been used in this study is available from authors by request. REFERENCES * Donato, D. C. et al. Mangroves among

the most carbon-rich forests in the tropics. _Nat. Geosci._ 4, 293–297 (2011). Article  ADS  CAS  Google Scholar  * Wang, F. et al. Coastal blue carbon in China as a nature-based solution

towards carbon neutrality. _Innovation_ 4, 100481 (2023). PubMed  PubMed Central  CAS  Google Scholar  * Wang, F. et al. Global blue carbon accumulation in tidal wetlands increases with

climate change. _Natl Sci. Rev._ 8, nwaa296 (2021). Article  PubMed  CAS  Google Scholar  * Saintilan, N., Rogers, K., Mazumder, D. & Woodroffe, C. Allochthonous and autochthonous

contributions to carbon accumulation and carbon store in southeastern Australian coastal wetlands. _Estuar., Coast. Shelf Sci._ 128, 84–92 (2013). Article  ADS  CAS  Google Scholar  * Rovai,

A. S. et al. Global controls on carbon storage in mangrove soils. _Nat. Clim. Change_ 8, 534–538 (2018). Article  ADS  CAS  Google Scholar  * Watanabe, K. & Kuwae, T. How organic carbon

derived from multiple sources contributes to carbon sequestration processes in a shallow coastal system? _Glob. Chang Biol._ 21, 2612–2623 (2015). Article  PubMed  PubMed Central  ADS 

Google Scholar  * Needelman, B. A. et al. The science and policy of the verified carbon standard methodology for tidal wetland and seagrass restoration. _Estuaries Coasts_ 41, 2159–2171

(2018). Article  CAS  Google Scholar  * Emmer, I. M. et al. Vol. _VCS Module, v 2.1. Verra_ (Verified Carbon Standard) (Washington, D.C., 2023). * Komada, T. et al. “Slow” and “fast” in blue

carbon: Differential turnover of allochthonous and autochthonous organic matter in minerogenic salt marsh sediments. _Limnol. Oceanogr._ 67, https://doi.org/10.1002/lno.12090 (2022). *

Houston, A., Garnett, M. H. & Austin, W. E. N. Blue carbon additionality: new insights from the radiocarbon content of saltmarsh soils and their respired CO2. _Limnol. Oceanogr._

https://doi.org/10.1002/lno.12508 (2024). * Prasad, M. B. K., Kumar, A., Ramanathan, A. L. & Datta, D. K. Sources and dynamics of sedimentary organic matter in Sundarban mangrove estuary

from Indo-Gangetic delta. _Ecol. Process._ 6, 8 (2017). Article  Google Scholar  * Etemadi, H. _Assessment And Predicting Climate Change Influence On Iran Mangrove Forests: A Case Study

Within The Jask Mangrove Protected Area._ PhD thesis, Tarbiat Modarres University, (2014). * Bouillon, S., Dahdouh-Guebas, F., Rao, A., Koedam, N. & Dehairs, F. Sources of organic carbon

in mangrove sediments: variability and possible ecological implications. _Hydrobiologia_ 495, 33–39 (2003). Article  CAS  Google Scholar  * Lee, S. Y. From blue to black: anthropogenic

forcing of carbon and nitrogen influx to mangrove-lined estuaries in the South China Sea. _Mar. Pollut. Bull._ 109, 682–690 (2016). Article  PubMed  CAS  Google Scholar  * Capdeville, C. et

al. Limited impact of several years of pretreated wastewater discharge on fauna and vegetation in a mangrove ecosystem. _Mar. Pollut. Bull._ 129, 379–391 (2018). Article  PubMed  CAS  Google

Scholar  * Bao, H., Wu, Y., Tian, L., Zhang, J. & Zhang, G. Sources and distributions of terrigenous organic matter in a mangrove fringed small tropical estuary in South China. _Acta

Oceanologica Sin._ 32, 18–26 (2013). Article  CAS  Google Scholar  * Booi, S., Mishi, S. & Andersen, O. Ecosystem services: a systematic review of provisioning and cultural ecosystem

services in estuaries. _Sustainability_ 14, 7252 (2022). Article  Google Scholar  * Li, X. F., Qi, M. T., Gao, D. Z., Liu, M. & Hou, L. J. Switches of methane production pathways and

emissions with human activity intensity in subtropical estuaries. _J. Hydrol._ 612, 128061 (2022). Article  CAS  Google Scholar  * Syvitski, J. et al. Earth’s sediment cycle during the

Anthropocene. _Nat. Rev. Earth Environ._ 3, 179–196 (2022). Article  ADS  Google Scholar  * Weiss, C. et al. Soil organic carbon stocks in estuarine and marine mangrove ecosystems are driven

by nutrient colimitation of P and N. _Ecol. Evolution_ 6, 5043–5056 (2016). Article  Google Scholar  * Jennerjahn, T. C. et al. Biogeochemistry of a tropical river affected by human

activities in its catchment: Brantas River estuary and coastal waters of Madura Strait, Java, Indonesia. _Estuar. Coast. Shelf Sci._ 60, 503–514 (2004). Article  ADS  CAS  Google Scholar  *

Qin, G. M. et al. Contributions of plant- and microbial-derived residuals to mangrove soil carbon stocks: Implications for blue carbon sequestration. _Funct. Ecol._ 38, 573–585 (2024).

Article  CAS  Google Scholar  * Stock, B. C. & Semmens, B. X. MixSIAR GUI user manual. Version 3.1. Retrieved from https://github.com/brianstock/MixSIAR/. (2016). * Röhr, M. E. et al.

Blue carbon storage capacity of temperate eelgrass (Zostera marina) meadows. _Glob. Biogeochemical Cycles_ 32, 1457–1475 (2018). Article  ADS  Google Scholar  * Alder, J. et al. in _The Sea

Around Us Newsletter_. 15, 1–2 (2003). * Watson, R. et al. in _The Sea Sround Us Newsletter_. 22, 1–8 (2004). * Woodroffe, C. in _Tropical Mangrove Ecosystems_ (ed A. I. Robertson, Alongi,

D. M.) 7–41 (American Geophysical Union, 1992). * Lang, N. C., Jetz, W., Schindler, K. & Wegner, J. D. A high-resolution canopy height model of the Earth. _Nat. Ecol. Evol._ 7,

https://doi.org/10.1038/s41559-023-02206-6 (2023). * Muis, S. et al. (ed _Copernicus Climate Change Service (C3S) Climate Data Store (CDS))_ (2022). * Kulp, S. A. & Strauss, B. H. New

elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding. _Nat. Commun._ 10, 5752 (2019). Article  PubMed  PubMed Central  ADS  CAS  Google Scholar  *

Swanson, K. M. et al. Wetland Accretion Rate Model of Ecosystem Resilience (WARMER) and Its Application to Habitat Sustainability for Endangered Species in the San Francisco Estuary.

_Estuaries Coasts_ 37, 476–492 (2014). Article  Google Scholar  * Holmquist, J. R. & Windham-Myers, L. A Conterminous USA-Scale Map of Relative Tidal Marsh Elevation. _Estuaries Coasts_

45, 1596–1614 (2022). Article  PubMed  Google Scholar  * Wang, F., Lu, X., Sanders, C. J. & Tang, J. Tidal wetland resilience to sea level rise increases their carbon sequestration

capacity in United States. _Nat. Commun._ 10, 5434 (2019). Article  PubMed  PubMed Central  ADS  CAS  Google Scholar  * Li, X. C. et al. Global urban growth between 1870 and 2100 from

integrated high resolution mapped data and urban dynamic modeling. _Commun. Earth Environ._ 2, 201 (2021). Article  ADS  Google Scholar  * Kummu, M., Taka, M. & Guillaume, J. H. A. Data

descriptor: gridded global datasets for gross domestic product and human development index over 1990–2015. _Sci. Data_ 5, 180004 (2018). Article  PubMed  PubMed Central  Google Scholar  *

Breiman, L. Random forests. _Mach. Learn._ 45, 5–32 (2001). Article  Google Scholar  * Liaw, A. & Wiener, M. Classification and regression by randomForest. _R. N._ 2, 18–22 (2002).

Google Scholar  * Archer, E. et al. _rfPermute: Estimate Permutation p-Values for Random Forest Importance Metrics_. R package version 2.5.2., https://CRAN.R-project.org/package=rfPermute

(2023). * Bunting, P. et al. Global mangrove extent change 1996–2020: global mangrove watch version 3.0. _Remote Sensing_ 14, https://doi.org/10.3390/rs14153657 (2022). * Ouyang, X. &

Lee, S. Y. Improved estimates on global carbon stock and carbon pools in tidal wetlands. _Nat. Commun._ 11, 317 (2020). Article  PubMed  PubMed Central  ADS  CAS  Google Scholar  *

Holmquist, J. R. et al. The coastal carbon library and atlas: open source soil data and tools supporting blue carbon research and policy. _Glob. Change Biol._ 30, e17098 (2024). Article  CAS

  Google Scholar  Download references ACKNOWLEDGEMENTS This study was funded by the National Natural Science Foundation of China (42471067), the Alliance of National and International

Science Organizations for the Belt and Road Regions (ANSO-CR-KP-2022-11), the National Key R&D Program of China (2023YFE0113103, 2023YFF1304504, 2021YFC3100400), the CAS Project for

Young Scientists in Basic Research (YSBR-037), Guangdong Basic and Applied Basic Research Foundation (2021B1515020011, 2021B1212110004, 2023A1515010946), the CAS Youth Innovation Promotion

Association (2021347), the National Forestry and Grassland Administration Youth Talent Support Program (2020BJ003), Key-Area Research and Development Program of Guangdong Province

(2022B1111230001), Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (SML2023SP218), Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden

(2023B1212060046), and the MOST Ocean Negative Carbon Emissions project. All funding was received by FW. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Xiaoliang Research Station of Tropical

Coastal Ecosystems, Key Laboratory of Vegetation and Management of Degraded Ecosystems, the CAS Engineering Laboratory for Ecological Restoration of Island and Coastal Ecosystems, and

Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, P.R. China Jingfan Zhang, Shuchai Gan, Jinge Zhou, Xingyun Huang,

 Han Chen, Hua He & Faming Wang * University of Chinese Academy of Sciences, Beijing, P.R. China Jingfan Zhang, Jinge Zhou, Xingyun Huang, Han Chen & Hua He * Chinese Research

Academy of Environmental Sciences, Beijing, P.R. China Pingjian Yang * School of Natural Sciences, Macquarie University, Sydney, NSW, Australia Neil Saintilan * National Marine Science

Centre, School of Environment, Science and Engineering, Southern Cross University, Coffs Harbour, NSW, Australia Christian J. Sanders * School of Ecology, Hainan University, Haikou, P.R.

China Faming Wang * Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, P.R. China Faming Wang Authors * Jingfan Zhang View author publications You can also search for this

author inPubMed Google Scholar * Shuchai Gan View author publications You can also search for this author inPubMed Google Scholar * Pingjian Yang View author publications You can also

search for this author inPubMed Google Scholar * Jinge Zhou View author publications You can also search for this author inPubMed Google Scholar * Xingyun Huang View author publications You

can also search for this author inPubMed Google Scholar * Han Chen View author publications You can also search for this author inPubMed Google Scholar * Hua He View author publications You

can also search for this author inPubMed Google Scholar * Neil Saintilan View author publications You can also search for this author inPubMed Google Scholar * Christian J. Sanders View

author publications You can also search for this author inPubMed Google Scholar * Faming Wang View author publications You can also search for this author inPubMed Google Scholar

CONTRIBUTIONS J.Z. and F.W. conceived and designed the study. J.Z. collected the data and conducted the analysis, and J.Z. and F.W. prepared and wrote the draft. S.G., P.Y., J.Z. (Jinge

Zhou), X.H., H.C., H.H., N.S., and C.S. helped revise the draft. CORRESPONDING AUTHOR Correspondence to Faming Wang. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing

interests. PEER REVIEW PEER REVIEW INFORMATION _Nature Communications_ thanks Steve Crooks and the other, anonymous, reviewers for their contribution to the peer review of this work. A peer

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organic carbon sources and implications for blue carbon credit. _Nat Commun_ 15, 8994 (2024). https://doi.org/10.1038/s41467-024-53413-z Download citation * Received: 04 June 2024 *

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