Getting the best of carbon bang for mangrove restoration buck

Domain: earth_science
Published: 2025-02-03
Editorial outcome: minor_revision

Abstract
Mangrove loss has reduced its carbon (C) sink function and ecosystem services. To effectively allocate climate finance for mangrove restoration, a thorough assessment of restoration potential is necessary. Here we show a net loss of ecosystem service value (ESV) of 29.2 billion USD ($) due to land changes in mangroves from 1996 to 2019. The estimated mangrove ESV in 2019 amounts to $894 billion yr−1, mainly provided by regulating and provisioning services (57.4% and 19.7%). Over the next two decades, we project that the restoration of mangroves would necessitate an investment of $40.0–52.1 billion, yielding net gains in ESV of $231–725 billion. The global benefit-cost ratio (BCR) of mangrove restoration ranges from 6.35 to 15.0, demonstrating that such projects are highly cost-effective. Furthermore, an estimated of 19.4 TgC can be sequestrated in mangrove soils based on a 20-year mangrove restoration program, which can generate $68.6–$236 million via blue C trading. Our findings highlight the significant opportunities for blue C restoration projects to mitigate climate change and support livelihoods.

Introduction
United Nations adopted 17 Sustainable Development Goals (SDGs) in 2015, with the intention of solving some of the planet’s biggest challenges by 2030 and building a better and more sustainable future for everyone1. Mangrove forests, as a highly productive blue carbon ecosystems (BCEs), are particularly important carbon (C) sinks, which is a critical way to reduce atmospheric carbon dioxide (CO2) concentration and accomplish SDGs related to climate action and biodiversity conservation2–4.

However, over the past two decades, mangrove have faced numerous threats, including sea level rise5, storm impacts6, erosion and progradation6, along-shore development7, and direct human activities8, which leads to substantial losses of global mangroves9. The following loss of C and ecosystem service have been recognized worldwide, and substantial restoration efforts have been put into mangrove ecosystems10–12. For example, China has achieved significant success in mangrove restoration, with an increase of 70% of the mangrove coverage from 2000 to 201813. Mangrove restoration directly enhances soil organic carbon (SOC) sequestration and holds great potential for achieving various policy objectives related to biodiversity conservation, climate change mitigation, and sustainable development14. Therefore, mangrove restoration was reported to be a cost-effective practice11.

Aquaculture areas and tidal flats present suitable opportunities for mangrove restoration and are currently the primary locations where such efforts are undertaken15. While many studies have investigated the ecological drivers and outcomes of mangrove restoration, there is a research gap in addressing the associated economic benefits at country-level and specific mapping of potential mangrove restoration areas11,12. Analyzing the investment and returns of mangrove restoration is crucial, as it provides compelling evidence for stakeholders and policymakers to support these efforts. Therefore, a comprehensive global analysis of the economic benefits of mangrove restoration is urgently needed to support blue C ecosystem services and promoting sustainable development.

In this study, we tracked land changes in global mangrove ecosystems from 1996 to 2019. We incorporated 846 mangrove ecosystem service value (ESV) observations along with ESVs of 10 corresponding land use types during mangrove change to analyze net changes in ESV. By integrating these ecological parameters with economic factors, we were able to estimate the costs and potential returns of mangrove restoration initiatives. This study aims to assess the outcomes of mangrove change and the investment and benefits of potential mangrove restoration by: (1) evaluating net changes in ESV caused by land changes in mangroves between 1996 and 2019; (2) identifying potential restoration areas for mangrove restoration; (3) performing a cost-benefit analysis of potential restoration activities; and (4) assessing the economic returns of mangrove restoration through blue carbon trading.

Results
Ecosystem service value (ESV) was divided into four main categories: provisioning, regulating, cultural and supporting. Regulating and cultural service were the main ecosystem service types, contributing 41.2% and 39.1% to the global ESV per unit area (Fig. 1a and Table S3). About 57.4% of the global mangrove ESV was provided by regulating services, followed by 19.7% by provisioning, 18.4% by cultural and 4.46% by supporting services (Table S4). One of the most talked about mangrove ecosystem services has been C sequestration due to the growing recognition of the effectiveness of mangroves in climate regulation through pulling carbon out of the atmosphere16,17. Among 18 ESV subcategories, the contribution of climate regulating value to total ESV reached 12.9%, indicating the importance of mangrove C sequestration (Source data file).

Mangroves have suffered significant losses during the past two decades, with global areal extents decreasing from 152,604 km2 in 1996 to 147,605 km2 in 201918. Lost mangroves were mainly turned into permanent water (54%, 5613 km2), tidal flats (22.4%, 2327 km2) and aquacultures (22.2%, 2302 km2, Table 1). Global mangrove ESV was 894 billion USD ($) year−1 in 2019, with $483, $35.4, $29.1, $226, and $121 billion year−1, in Asia (mainly Southeast Asia), Africa, Oceania, North America, and South America, respectively (Fig. 1b, Tables S1 and S2). Top five countries with the greatest mangrove ESV was valued at $320 billion year−1 in Indonesia, $124 billion year−1 in Mexico, $79.6 billion year−1 in Brazil, $75.9 year−1 in Malaysia, and $56.7 billion year−1 in United States (Fig. 1b and Table S1). However, mangrove ESV was not necessarily corresponds to its areal extent but also decided by economic conditions11.

Compared to 1996, mangrove ESV decreased by $43.9 billion yr−1, with the loss of mangrove ecosystem services at $13.0 and $29.2 billion yr−1 in the Americas and Asia (Fig. 2a). Some countries gained mangrove ESV, such as Suriname ($108 million yr−1), Bangladesh ($40.9 million yr−1), French Guiana ($34.8 million yr−1), Cameroon ($14.0 million yr−1) and New Zealand ($11.7 million yr−1, Fig. 2a and Table S1). Specifically, the loss of mangroves would release considerable C into atmosphere, since climate regulating plays a significant role in mangrove ecosystem services.

The net change of ESV in mangroves ecosystems was further estimated by combining land change types and their corresponding ESVs. Mangrove loss has led to $29.2 billion net ESV loss per year, with the greatest net ESV loss in Indonesia, reaching $17.5 billion year−1. Countries such as Philippines, Bahamas, Unites States had a net ESV gain of $301, $114 and $110 million year−1 (Fig. 2b and Table S5). Interestingly, some countries gained ESV despite losing mangroves. This can be attributed to other land-use types, such as permanent water bodies, providing substantial ESV—sometimes even exceeding that of mangroves. For example, permanent water can provide ESV reaching $24,622 ha−1 year−1 in Vietnam, compared with the $10,946 ha−1 year−1 provided by mangroves, as 79% of the mangroves were turned into water. Another reason is that even when mangrove provides the greatest ESV among all land use types, the extent of ESV change is different during mangrove gains and losses. For instance, 89% of the lost mangroves in United States were turned into water, while 73% of the gained mangroves were from salt marshes and tidal flats. The ESV provided by water was almost the same as that provided by mangroves ($240,285 ha−1 year−1 compared with $240,314 ha−1 year−1), while much lower ESV was provided by salt marshes and tidal flats ($26,027 ha−1 year−1 and $38,689 ha−1 year−1). Therefore, net changes in ESV depend on the dynamics of mangrove conversion and the differences in ESV between mangroves and other land-use types. However, certain ecosystem services provided by mangroves – such as coastal protection and supporting coastal life circles – are irreplaceable3,4,19. Hence, ESV alone is not the sole criterion to evaluate the ecological risks of mangrove losses, changes in ecosystem service types should be considered.

We assumed that mangrove restoration mainly occurs in aquacultures and tidal flats that converted from former mangroves to ensure a suitable growing environment14,20,21. We conducted a cost-benefit analysis across multiple time frames (10, 20, 30 and 40 years) and social discount rate (8%, 4.5%, and −2%), and reported results in the main text based on a 20-year time frame.

Globally, mangrove restoration on aquacultures costs $13.1–17.1 billion at different social discount rate. Asia incurs the highest cost ($11.1–$14.5 billion), given its widespread aquaculture industry (Figure S1a and Table S6). Restoration costs in South America, Africa, and Oceania were $0.66–$0.86 billion, $0.11–$0.14 billion, $0.11–$0.14 billion, respectively (Fig. 3a, Figure S1a and Table S6). The cost of mangrove restoration on tidal flats is most costly in the Americas ($13.1–$17.1 billion), where the previous mangroves were most converted into tidal flats, followed by Asia ($9.41–$12.3 billion) (Figure S1b and Table S6). The global cost for mangrove restoration on tidal flats is $26.9–$35.0 billion, and restoring both aquaculture and tidal flats raises the global cost to $40.0–$52.1 billion, with Asia and the Americas bearing the majority of the expense ($20.5–$26.7 billion and $15.0–$19.5 billion, respectively) (Fig. 3a and Table S6).

If mangrove restoration is conducted on all the suitable aquacultures and tidal flats, global ESV gains range from $254 to $783 billion with a net ESV gain of $231 to $724 billion. Asia accounts for most of the net ESV gains ($186–$575 billion, Table S7). Surprisingly, there was a net ESV loss in Oceania and Africa during mangrove restoration, mainly because the relatively high ESV for tidal flats ($38,106 ha−1 year−1) and aquacultures ($9,588 ha−1 year−1) compared to mangroves ($7,994 ha−1 year−1 in Australia), which is similarly observed in Tanzania (Table S7).

The global benefit-cost ratio (BCR) of mangrove restoration over the next 20 years is 6.35–15.0. Mangrove restoration had the highest returns in Asia (average: 9.36–22.1), while got lower returns but still a cost-effective ecological management in Oceania (1.21–2.86) and Africa (1.22–2.88, Table S8). Countries such as India, Ecuador, Thailand, has extremely high BCR, reaching more than 100, followed by Bangladesh, Colombia, China, Vietnam, Costa Rica, American Samoa and Indonesia, with their BCR over 20 (Fig. 4a).

When accounting for the hidden cost of losing ESV from aquaculture and tidal flats, the net BCR was then calculated by subtracting the ESV of aquaculture (including fishery revenue) and tidal flats on the basis of the restored mangrove ESV. The global average net BCR is 5.78–13.9, with India, Ecuador, Thailand, Bangladesh, China, Colombia, Costa Rica, Vietnam and Indonesia generating substantial net ESV gains (net BCR: 21.7–137, Fig. 4b). The BCR improves over longer restoration periods since initial investments like planting and engineering are fixed, and only ongoing management costs are added annually (Table S8).

While the global average BCR and net BCR suggest that mangrove restoration is highly beneficial, this trend does not apply universally. Countries like India, Ecuador, Thailand which has extremely high BCR and level up the global average, while 22 countries had BCR of less than 1, with 49 countries which had no observations of any ESV and cost, had BCR of 2.21 calculated by mean values (Fig. 4 and Table S8). Overall, mangrove restoration is a cost-effective but not very profitable ecosystem management for some regions and countries. If net BCR is used to evaluate feasibility, results are less encouraging: 23% of countries have BCRs less than 1, and 34% of the countries can gain net benefits (Fig. 4). For countries with developed fisheries such as Indonesia, Myanmar and Vietnam, building integrated mangrove aquaculture systems (IMAS)22–24 by maintaining partial ESV provided by aquacultures is a good practice to further improve the BCR.

As a highly productive BCEs, mangrove soils have great ability of C sequestration. By compiling 324 observations of mangrove C accumulation rate (CAR), we were able to estimate the amount of C sequestrated in mangrove soils through mangrove restoration programs. Globally, an annual increase of 1.35 Tg SOC stock is expected from mangrove restoration, with 19.4 Tg SOC stock gained based on a 20-year time scale (supposing newly restored mangrove started to provide ecosystem services from the 5th year and an annual decay rate of 0.125, Table S9). Countries with large potential mangrove restoration areas would witness substantial increase in SOC stocks, such as Indonesia (11.4 Tg), Brazil (1.04 Tg), Malaysia (0.88 Tg), Ecuador 0.86 Tg) and Philippines (0.41 Tg).

The economic return on investment of mangrove restoration was analyzed using blue C marketing as a proxy based on the market price of its climate mitigation potential (CMG). The annual increase of 4.95 million tCO2e from 1.35 Tg of SOC stock would yield $68.6–$236 million and $129–$444 million, based on global blue C prices of $5 and $9.4 per tCO2e, respectively (Fig. 3b, Tables S9 and S10). Asia would see the highest economic returns ($41.6–$219 million), followed by the Americas ($20.7–$133.8 million), Oceania ($3.82–$24.7 million), and Africa ($2.51–$16.3 million) (Table S10). Key contributors to global CMP and economic gains include Indonesia, Brazil, Malaysia, Ecuador, the Philippines, the Bahamas, and Australia, collectively accounting for 80% of the global CMP and generating substantial returns (Tables S9 and S10).

Despite economic benefits ranging from $68.6 to $444 million over a 20-year period, blue C trading alone may not break even. Zeng et al.26 reported a quite high net present values (NPVs) for mangrove restoration by including both biomass and soil C. Besides that, different approaches were used to analyze the additionality of SOC stock. In this study, we used the CAR to estimate the annual soil C sequestration when conducting restoration, while Zeng, et al.26 used the annual deforestation rate to estimate the C loss if no restoration were conducted. Our methods can give a more accurate analysis of sediment C sequestration.

The primary goal of this study is to present comprehensive data on mangrove restoration rather than to promote its economic benefits. The motivation of mangrove restoration should be the protection of natural resources and sustainable development instead of the pursuit of greater profits. It is all very well to be able to commercialize mangrove restoration and reap huge ecological and economic profits, but this should not be the only standard to evaluate the feasibility of mangrove restoration. The main goal of these practices is to share scientific knowledge and technology, research capacity development and transfer of marine technology. Besides that, C trading was included to better support mangrove restoration initiatives by linking respective communities to international markets. International funding mechanisms, such as the Green Climate Fund could support large-scale mangrove restoration projects by forming collaboration between local authorities, experts and farmers to perform mangrove restoration and boost the income of farmers, fisherfolks, and other rural business, such as beekeeping and honey production. Furthermore, Climate-resilient housing and community-based disaster risk management, vulnerability assessments and planning process are also being scaled up to ensure the long-term growing benefits. (https://www.greenclimate.fund).

Although mangrove autochthonous organic carbon (OC) is the main contributor to OC in mangrove sediments, allochthonous marine and/or terrestrial OC also accounts for a considerable proportion27. When considering blue C trading based on CMP, not all newly accumulated C in mangrove sediments are newly generated, part of them were found to be allochthonous ‘old C’, whose CMP were double counted. Secondly, ESVs were calculated by adding all types of ESVs in certain ecosystems, but since some countries lack complete data on all 18 ESV categories, missing values were considered as zero. Therefore, ESVs might be underestimated due to insufficient research efforts, and the BCR is thus quite conservative in this study. We further conducted a sensitivity analysis by filling missing values of 18 ESV subcategories using the global average value adjusted to local socio-economic values and reported the most ideal scenario for mangrove restoration (global BCR: 13.8–32.6; global net BCR: 13.2–31.9, Table S11, Source data file). We recognize the complexities in securing funding, negotiating with governments and local communities, executing restoration activities, and managing post-restoration maintenance. In our cost calculations, we included expenses for engineering, planting, labor, management, and maintenance but excluded the costs of securing funding due to a lack of consistent reporting across over 100 countries, preventing accurate estimates. Furthermore, mangrove restoration are at risk of replantation failure21, rising sea levels, and socioeconomic emergency, which should be carefully evaluated before conducting mangrove restoration.

Methods
Data collection
To analyze the net ecosystem service value (ESV) changed during land use shifts in mangrove ecosystems from 1996 to 2019, we collected ESVs of coastal ecosystems (salt marshes and tidal flats) and other terrestrial ecosystems. ESV of mangroves, salt marshes, tidal flats, forests, shrubs, grasslands, agricultures and water were extracted from Ecosystem Service Valuation Database (ESVD: https://www.esvd.info/ourdatabase). Since evaluating mangrove ESV is very crucial for this study, we further added additional data to it by searching Web of Science using combinations of keywords “mangrove ecosystem service”, “mangrove ecosystem service value” and “mangrove ESV”. Since ESVs of aquacultures and urban areas were not included in ESVD datasets, we got those data by searching Web of Science using combinations of keywords “aquaculture ecosystems service*”, “aquaculture ESV”, “urban area ecosystems service*”, “urban area ESV”, “ecosystem service* land change”, “ecosystem service* land cover change” and “ecosystem service* LULC”. There were 871 observations of mangrove ESV (689 from ESVD and 182 from our collected datasets), 146 observations of salt marsh ESV, 63 observations of tidal flat ESV, 3280 observations of water ESV, 967 observations for forest ESV, 104 observations of shrub ESV, 50 observations of grassland ESV, 983 observations of agriculture ESV, 94 observations of aquaculture ESV (most of them were reported as fishery revenue), 44 observations of urban area ESV. For bare lands, we use value of 40 2020 USD ha−1 yr−1 from Costanza, et al.28.

We constructed a comprehensive global mangrove carbon accumulation rate (CAR) database to evaluate the mangrove C sequestration ability during mangrove restoration, collecting as many experiments that fulfilled our criteria as possible. The basic CAR data was from Wang, et al.4. We searched the Web of Science, China Knowledge Resource Integrated Database using combinations of keywords “mangrove carbon”, “mangrove C* accumulation”, “mangrove SOC accumulation”, “mangrove C* accretion” that were published after 2021. The database should meet the following requirements: (1) 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. Where studies made available both soil accretion rate (SAR) and C density, the CAR was calculated as:

CAR (gCm−2y−1) = C density (gcm−3) × SAR (mmy−1) × 103 (1)

The final database has 314 CAR observations, where 213 observations were extracted from Wang, et al.4, 111 observations were additionally added by searching Web of Science. The geostatistical principle assumes vegetation distribution gradually changes with environmental factors29. Therefore, we assumed that the mangrove CAR of a sampling site might have the highest similarity to the nearest sampling point. Combining the mangrove mapping in 2019 with Kriging interpolation, mangrove total CAR was analyzed in Google Earth Engine (GEE). Then, the country-level average CAR was calculated as follows:

CARmeanX = CARtotalX / Area totalX (2)

where CARmeanX is the average CAR of a country, CARtotalX is the total C accumulated per year in a country, Area totalX is the mangrove distribution area of a country. The purpose of this step rather than directly calculating the mean values of these CAR observations is to include the spatial variety of mangrove CAR and filling the missing values for countries as much as possible.

Land changes in mangrove ecosystems
The global mangrove distribution in 1996 and 2019 were extracted from Global Mangrove Watch18. Tidal flats distribution of the corresponding year were from Murray, et al.7. Salt marsh distribution were generated by subtracting the above-mentioned mangrove and tidal flats distribution from global tidal wetland mapping9. Aquaculture mapping were generated by visual interpretation using high resolution data on Google Earth. Other land use types were categorized into forests, shrubs, grasslands, agricultures, bare lands, urban areas and permanent water according to “Land cover classification gridded maps from 1992 to present derived from satellite observations” on Copernicus platform (https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-land-cover?tab=overview). Therefore, land use types were classified into 11 classes in this study.

Ecosystems service value and its changes in global mangroves
ESV data from extracted from the ESVD website (https://www.esvd.info) were standardized into 2020 USD in the TEEB database30. ESV data collected by ourselves (mangroves, aquacultures and urban areas) were also standardized into 2020 USD by using the official exchange rates to convert the economic estimates reported in the original studies into the official local currency. These values were then adjusted to 2020 local currency using official gross domestic product (GDP) deflators. Finally, the purchase power parity (PPP) conversion factors were used to convert the values to 2020 USD11. Mangrove ESV was divided into four main categories and 18 subcategories (provisioning: food, medicinal resources, raw materials and water; regulating: air quality regulating, climate regulating, erosion prevention, moderation of extreme events, regulation of water flows waste treatments; cultural: aesthetic information, existence and bequest values, information for cognitive development, inspiration for culture, art and design, opportunities for recreation and tourism; supporting: maintenance of genetic diversity, maintenance of life cycles, maintenance of soil fertility). Mangrove ESV categories were compared at country-level and calculated as follows:

ESVcategoryN = Σn i=1 ESVmean subNi (3)

where ESVcategoryN is certain mangrove ESV categories, such as regulating, n is the number of ESV subcategories, ESVmean subNi is the corresponding ESV subcategories under that ESV category. It should be noted that, not all ESV subcategories were reported in one study. The missing values were treated as 0.

Country-level mangrove total ESV were calculated as follows:

ESVtotalsub = Σ18 i=1 ESVmeani (4)

ESVtotalothers = Σx i=1 ESVtotali (5)

ESVtotal = ESVtotalsub + ESVtotalothers (6)

where ESVtotalsub is sum of mean values of each ESV categories in each country, ESVmeani is mean values of certain ESV categories in each country, ESVtotalothers is the sum of studies that directly reported the total mangrove ESV, ESVtotali is the total mangrove ESV in that study, n is numbers of studies that directly reported the total ESV. ESVtotal is the final country-level mangrove total ESV. Values of different mangrove ESV types and its contribution to the total mangrove ESV per year in each country were calculated as follows:

ESVcateNcountryX = ESVcategoryN × Area (7)

Contribution categoryN = ESVcateNcountryX / Total (8)

where ESVcateNcountryX is the ESV of certain categories per year in each country, Area is the mangrove distribution area, Contribution categoryN is the relative contribution of certain ESV categories in each country. The contribution of ESV categories at global scale is weighted as follows:

ESVcateNglobal = Σm i=1 ESVcateNcountryX (9)

ESVTotalglobal = Σ4 i=1 ESVcateNglobal (10)

Contribution cateN global = ESVcateNglobal / Totalglobal (11)

where ESVcateNglobal is the global value of certain ESV categories per year, m is the number of countries with ESV observations, ESVTotalglobal is the global total ESV per year, Contribution cateN global is the contribution of certain ESV categories at global level. For countries that did not have their own observations of ESV, mean values of the total ESV were used. Specifically, considering the unbalanced developing status worldwide, before calculating mean values, total ESV in each country were standardized into the total ESV in United States, and then the mean values were transformed into their local total ESV. For example, using ESV in country A and B to calculate the mean ESV and transformed into ESV in country C which had no ESV observations:

ESVmean = (ESV A + ESV B) / 2 (12)

ESV C = (ESVmean × Exchange rate C) / PPP C (13)

where ESV A is the observation value of ESV in country A and was standardized into 2020 USD, ESV B is the observation value of ESV in country B and was standardized into 2020 USD, ESVmean is the mean ESV values based on ESVs of country A and B, Exchange rate C is the official exchange rate between country C and United States, PPP C is the PPP of country C, and ESV C is estimation of ESV in country C.

The change in mangrove ecosystem service value was calculated as follows:

ESV change = ESV mangrove − ESV others (14)

where ESV change is the net ESV change, ESV mangrove is the ecosystem service value of the previously existing mangrove, and ESV others is the ecosystem value change of the converted land use (salt marshes, tidal flats, forests, shrublands, grasslands, agricultures, water, aquacultures, urban areas and bare land). ESV others was calculated as the ESV mentioned above.

Cost-benefit analysis
Mangrove restoration on tidal flats and aquacultures is the most common practice in mangrove restoration14,20,21. We considered the tidal flats and aquacultures converted from mangroves were suitable for replanting mangroves because the hydrology conditions were not greatly disrupted15. Therefore, the potential mangrove restoration areas included aquaculture and tidal flats. The cost of mangrove restoration included planting cost, labor cost, transportation cost, and maintenance cost. Considering the large variance in socio-economic conditions across countries and regions, all cost was transformed into 2020 USD using local currency and purchasing power parity, similar as the ESVs11. Mangrove ESV of restored mangroves was considered as the economic benefits of mangrove restoration.

The economic benefits of restoration were estimated decennially from 10 to 40 years at social discount rates of −2%, 4.5%, and 8%, where the negative value reflects the possibility that conditions will deteriorate in the future due to ecological degradation and resource depletion31. The net-present annual total economic benefit is estimated starting in the 5th year by summing up the estimated values for mangrove ESV. The total cost of mangroves is the sum of plantation, engineering, labor, transportation, and maintenance cost and with an annual management cost component of up to 2.5% of the capital cost31. The benefit-cost ratio (BCR) of mangrove restoration was then calculated follows11:

BCR = PV[Benefits] / PV[Costs] = (ΣT t=5 B / (1+r)t) / (C + ΣT t=1 C / (1+r)t) (15)

Where PV is the present value; t is the year of calculation, B is the total economic benefits; C is the costs (including total initial cost and management cost); and r is the discount rate. When conducting mangrove restoration, aquacultures and tidal flats were transformed into mangroves, while their ESVs were replaced by mangrove ESV. When calculating BCR, benefits were considered as restored mangrove ESV, while the hidden cots, the loss of aquaculture and tidal flat ESV were neglected. Therefore, we proposed ‘net BCR’ to evaluate the net benefit considering the ESV loss of aquaculture and tidal flats.

Blue carbon trading
We further evaluate the economic return of mangrove restoration by blue C trading. The blue C price is based on its climate mitigation potential (CMP), which was calculated by applying a conversion factor (3.67) to the SOC stock32. Specifically, SOC stock is the accumulated SOC stock each year, calculated by the CAR. We also considered the annual decay rate of 0.1 to SOC specific to mangrove forests25.

SOCstock acc = CAR × 0.01 (16)

CMP = SOCstock acc × D × (1 − decay rate) (17)

where SOCstock acc is the accumulated SOC stock per year (Mg Cha−1 y−1), CAR is the carbon accumulating rate (g Cm−2 y−1), CMP is the climate mitigation potential, D is the conversion factor (3.67).

We estimated the economic return of mangrove restoration using the present values (PVs) as the proxy based on the following simplifying assumptions from previous studies: (1) a constant blue C price of 5 t−1 CO2e USD and 9.4 t−1 CO2e USD for the first five years, roughly matching the average C price of all avoided deforestation projects recorded by Forest Trends’ Ecosystem Marketplace reports between 2006-201833; (2) After the first five years of mangrove restoration started providing ecosystem service (the 10th year of mangrove restoration), we assumed a 5% price appreciation for the following years over a 10 to 40-year restoration time frame34; (3) the social discount rate of −2%, 4.5% and 8% were applied. Therefore, the PV were calculated as follows:

V total = CMP × market price (18)

PV Financial = ΣT t=5 V total / (1+r)t + ΣT t=10 V total × (1+5%)t−9 / (1+r)t (19)

where V total is the total market value of the mangrove SOC and PV Financial is the accumulated economic gains of mangrove restoration at a 10 to 40-year time frame.

Sensitivity analysis
Mangrove ESVs were divided into 18 subcategories as above-mentioned, but most of these studies did not cover all of them. For example, the ESVD database only provide the “existence, bequest value” and “Food provision” of mangroves in Australia. We believe that mangroves can provide more types of ecosystem services in Australia and other countries than recorded. Therefore, the ESV gain and BCR might be underestimated. We further conducted a sensitivity analysis to show the maximum ESV gain and BCR that can be achieved by fulfilling the all 18 ESV subcategories with the global mean value. These mean values were further adjusted to match the local socio-economic conditions according to PPP and local exchange rate. These maximum values show the most ideal scenario for mangrove restoration, however, might be hard to achieve because mangroves cannot provide all types of ecosystem service at one location.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This is a conceptually interesting study that appears to try to use soil organic carbon (SOC) data collected from literature around the world to understand what the affects the distribution of SOC stock. Separately, the study appears to map change of mangrove extents and relate these to drivers of change. Last, the study analyzes the cost vs benefits ratio of mangrove restoration. The manuscript describes an extensive dataset that I believe would have required an impressive amount of work to collect.\nHowever, I believe that this manuscript suffers from several major flaws at this point of time. I highlight some of the most immediate concerns I have, but it should be noted that there exist more issues with this manuscript that is not covered in this review. I hope that these comments are useful and viewed as constructive.\n1) Fundamentally, the manuscript is not cohesive and does not have a narrative that is easy to follow. All three segments of the analyses only relate to each other in as far as they focus on mangroves. It seems more appropriate that each segment should be its own manuscript and not lumped together. This is also not helped by the writing, which is clumsy in places and grammatically problematic in others. Severe editing and rewriting should be done to refocus the objective of the MS.\n2) Parts of the manuscript lack originality. The analyses of mangrove change and what drives it appears to be very similar to what Nick Murray and Liza Goldberg did previously. I don’t really understand why this is repeated again, particularly when these two datasets are easily available online.\n3) The authors appear to suggest/assume that a loss of mangrove results in direct loss of SOC, and change in extent of mangrove means a direct loss of SOC. I am not a soil expert, but I do not believe that this is how forest loss and erosion works.\n4) I am also not convinced by the calculations of benefits here as well. Is the price of carbon reliable and reflective of current mangrove projects? Are there projects that are based on SOC stocks alone? Is a 20 year restoration project believable? These feel like a house of cards, where the absence of in depth thinking and justification makes the whole analyses and results not believable.\n5) I think the manuscript might be mixing up some basic concepts and terms. For example, I am not sure if the manuscript is really calculating the benefits of hypothetical restoration projects (what goes into a mangrove restoration project? how is it funded?). There is also confusion over climate finance and conservation funding.\nWhile the topic is interesting, I believe that the manuscript should be majorly rewritten before being sent out.", "reviewer_2": "Promoting mangrove restoration is a crucial strategy in the fight against climate change. It leverages the ecosystem's capacity to sequester carbon efficiently while providing a range of other ecological and socio-economic benefits. This study aims to investigate the spatiotemporal dynamics of mangrove blue carbon stocks and conduct an investment-benefit analysis of potential mangrove restoration—important questions indeed. The idea of tracking global mangrove SOC stock dynamics is innovative. However, there are some concerns regarding the quality of data and methodology, detailed below.\nSOC stock data: The authors updated the database by searching several databases with keywords, but it is unclear whether this constitutes a systematic review. Data from peer-reviewed literature may be subject to publication bias. How was the quality of the SOC stock data ensured? What are the data resolutions? As presented, the data lack specificity and do not adequately convey scientific rigor. How was data aggregation conducted for each country? Please also provide more details on additional data collection. Are these data from the searched literature or from Ouyang and Lee (2020)? What is the resolution of these additional data, including open-access global data?\nSOC stock change during mangrove loss and gains: A paper published in 2020 titled “Quantifying net loss of global mangrove carbon stocks from 20 years of land cover change” appears similar to this study. What advances does this study offer in terms of data and methodology? How accurate are the mangrove distribution and land use change maps? The resolution of maps used needs to be indicated in the methodology.\nSOC Stock in new mangroves: Insufficient detail has been provided about the SOC stock in newly gained mangroves. Were these stocks considered equivalent to natural mangroves? Regenerated and/or planted mangroves need 30 to 40 years to attain similar structural characteristics to natural mangroves. Was this factor accounted for in calculating mangrove SOC stock change from 2000 to 2020?\nCost-benefit analysis: The sources of data used for the cost-benefit analysis are unclear. Where did the data for the costs in these five categories originate? How was the cost of mangrove restoration on tidal flats and aquaculture quantified? What does the ecosystem services value from ESVD look like? Which ecosystem services were considered in the cost-benefit analysis, and how were the benefits calculated? These critical explanations are needed in the Methodology to understand the robustness of the results.\nInvestment-benefit analysis: While this study emphasizes the importance of blue carbon in mangroves, blue carbon sequestration is not the only ecosystem service with market value. Capture fisheries and ecotourism also have significant market values. For instance, the estimated annual economic contribution of tourism in the Sundarbans mangroves to the Bangladesh economy is USD 53 million. A global investment-benefit analysis of mangrove restoration should consider these aspects case by case to provide science-based information for decision-making. If you only consider blue carbon market, the result and discussion need to be more focused on this aspect.\nLines 205 to 208: Why is mangrove ESV less than the values provided by aquaculture in Thailand and the Philippines? Is it due to the larger extent of aquaculture in these countries, or are there other reasons for this result?\nLines 244 to 246: The statement “mangrove restoration is not monetarily worth it for countries such as Tanzania, Costa Rica, and Kenya” is discomforting since these countries are actively restoring mangroves. It is more important to understand the variance of ecosystem services value across countries.\nWebsite:\nRestoration of mangrove ecosystem in Tanzania for enhancement of local communities | Department of Economic and Social Affairs\nCommunity project helps Kenya aim for climate goals one mangrove tree at a time (mongabay.com)\nLines 344 to 345: How is the level of confidence determined? The methodology lacks mention of the confidence level in the validity of global estimates.\nIn general, the lack of specification in data description makes it difficult to understand the rationale and robustness of the results and discussion. I recommend that the authors provide more detailed information in the Methods section to enhance clarity and rigor.\nAdditional Comments\n• The authors should improve the language, using \"et al.\" instead of listing names of authors in Lines 301, 443, 485, 506, etc.\n• Need more concise delivery of key messages to reach a broader audience.", "reviewer_3": "General comments:\nThe manuscript \"Getting the Best of Carbon Bang for Mangrove Restoration Buck\" is a comprehensive and insightful contribution to the field of coastal blue carbon. Mangrove forests are vital ecosystems that offer numerous services essential for the planet’s health and human well-being. However, limited climate finance for mangrove restoration has raised the critical question of where to prioritize conservation and restoration efforts globally to maximize their carbon sequestration potential. Zhang et al.’s study tries to identify the driving forces behind the carbon stock capacity of mangrove ecosystems , providing insights for strategic prioritization of climate finance for mangrove conservation and restoration efforts. They found that several factors, including sediment supply, salinity, temperature, precipitation, elevation, and canopy height, regulate the stocks of organic carbon in mangrove soils. Moreover, the global extent of mangroves has significantly declined over the past two decades. A significant portion of this loss (52%) is attributed to direct human activities. Additionally, they also estimated the value of ecosystem services provided by mangroves, which, while significant, has declined over time due to mangrove loss. This study also provides a global map product showing priority areas for mangrove restoration. They found that restoration of mangroves over the next two decades would require an investment of 1.36 to 1.77 billion USD, resulting in gains in ecosystem service value ranging from 31 to 99 billion USD.\nTotally, this study effectively addressed the critical issue of mangrove carbon sequestration and the financial implications of restoration efforts. The following aspects are particularly commendable: 1/The extensive dataset comprising 2222 mangrove SOC measurements and corresponding environmental factors provides a robust foundation for the analysis. This comprehensive data collection enhances the credibility and reliability of the study's findings. The application of machine learning techniques to investigate the spatial variability of mangrove SOC stocks and identify regulatory factors is a significant strength. This modern approach allows for more accurate and detailed insights.\n2/The detailed investment-benefit analysis for mangrove restoration, including calculations of benefit-cost ratios and financial returns, is particularly valuable. This analysis provides compelling evidence for policymakers and stakeholders to support mangrove restoration initiatives.\n3/The manuscript highlights the broader ecosystem services provided by mangroves, beyond carbon sequestration. This holistic view underscores the multifaceted benefits of mangrove ecosystems, enhancing the argument for their restoration.\nEspecially, I like the study's global scope, which examines mangrove SOC stocks across various regions, and offers a comprehensive understanding of the issue. This perspective is crucial for developing effective global strategies for mangrove conservation and restoration.\nAlthough I still have some specific comments below, I think this study is well-written, and well organized, which worth a timely publication in a high-rank journal, like Nature Communications or Other Nature or Science sister journals.\nSpecific Comments:\nTitle: Looks good for me.\nAbstract: The abstract is informative but could be more concise. Focus on the key findings and their implications to make it more meaningful.\nIntroduction: Clearly state the research objectives at the end of the introduction to guide readers on what to expect in the following sections. For example, this study provides a global map of potential mangrove restoration sites, I suggest the authors also mention this in the introduction. Carbon stocks of mangrove forests are also affected by environmental conditions (e.g., estuarine vs. oceanic). See https://doi.org/10.1016/j.scitotenv.2023.167511.\nMethods: Elaborate on the machine learning techniques used, including the selection of parameters and the validation process. I also suggest the authors to clarify the criteria for selecting the studies included in the dataset to ensure that readers and reviewers can well understand their methods.\nResults: Present key results more prominently, possibly with the use of summary tables or bullet points for critical findings. The current version only has figures in the main text. One or two tables are needed. Their Supplementary Materials have many tables, I suggest authors to move one or two tables to the main text.\nDiscussion:\nI suggest the authors discuss the implications of the findings in the context of climate change and human disturbance, compare and contrast their results with previous studies to highlight the contributions of this work.\nEspecially, the authors should suggest specific actions for policymakers and stakeholders based on the study’s findings.\nReferences:\nSome references need to be updated, especially, there are several recent good publications on the mangrove blue carbon."}, "author_response": "This is a conceptually interesting study that appears to try to use soil organic carbon\n(SOC) data collected from literature around the world to understand what the affects\nthe distribution of SOC stock. Separately, the study appears to map change of mangrove\nextents and relate to these drivers of change. Last, the study analyzes the cost vs benefits\nratio of mangrove restoration. The manuscript describes an extensive dataset that I\nbelieve would have required an impressive amount of work to collect.\nHowever, I believe that this manuscript suffers from several major flaws at this point\nof time. I highlight some of the most immediate concerns I have, but it should be noted\nthat there exist more issues with this manuscript that is not covered in this review. I\nhope that these comments are useful and viewed as constructive.\n1) Fundamentally, the manuscript is not cohesive and does not have a narrative that is\neasy to follow. All three segments of the analyses only relate to each other in as far as\nthey focus on mangroves. It seems more appropriate that each segment should be its\nown manuscript and not lumped together. This is also not helped by the writing, which\nis clumsy in places and grammatically problematic in others. Severe editing and\nrewriting should be done to refocus the objective of the MS.\nResponse: Thanks for this comment. We have focused on the global estimation of\necological and economic benefits during mangrove restoration. we tracked land use\nchanges in global mangrove ecosystems from 1996 to 2019. We incorporated a\ncomprehensive dataset comprising 2257 mangrove SOC measurements, 846 mangrove\nESV observations along with SOC stocks and ESVs of 10 corresponding land use types\nduring mangrove change to analyzing net changes in SOC stock and ESV. By\nintegrating these ecological parameters with economic factors, we were able to estimate\nthe costs and potential returns of mangrove restoration initiatives. This study aims to\nassess the outcomes of mangrove change and the investment and benefits of potential\nmangrove restoration by: (1) evaluating net changes in SOC stocks and ESV caused by\nland use changes in mangroves between 1996 and 2019; (2) identifying suitable sites\nfor mangrove restoration; (3) performing a cost-benefit analysis of potential restoration\nactivities; and (4) assessing the economic returns of mangrove restoration through blue\ncarbon trading.\n2) Parts of the manuscript lack originality. The analyses of mangrove change and what\ndrives it appears to be very similar to what Nick Murray and Liza Goldberg did\npreviously. I don’t really understand why this is repeated again, particularly when these\ntwo datasets are easily available online.\nResponse: Thanks for this comment. The purpose of this change analysis is to detect\nthe specific land use types which mangrove had transformed from or turned into and\ntherefore, to calculate net changes of SOC stock and ESV. Furthermore, this approach\nenabled us to find the potential mangrove restoration sites, which are defined as\naquaculture and tidal flats that were previously mangroves. These datasets have\ndetected the natural and direct human-driven process that cause mangrove change, but\nthey did not present the detailed land use change types in mangrove ecosystems. In the\nrevised manuscript, we first mapped aquaculture in mangrove change areas by visual\ninterpreting using high-resolution images in Google Earth in 1996 and 2019. Then,\nglobal land use classification from Copernicus Climate Change Service 1 were used to\ndetermine the land use change in mangrove ecosystems. Finally, mangrove lost or\ngained areas were classified into 10 types: saltmarshes, tidal flats, permanent water,\nforest, shrub lands, grasslands, agriculture, aquaculture, urban area and bare land.\n3) The authors appear to suggest/assume that a loss of mangrove results in direct loss\nof SOC, and change in extent of mangrove means a direct loss of SOC. I am not a soil\nexpert, but I do not believe that this is how forest loss and erosion work.\nResponse: Thanks for this comment. We did not assume that the loss of mangrove\nwould result in direct loss of SOC or ESV. Mangrove SOC stock change and net SOC\nstock change were separately estimated. Mangrove SOC stock change only depended\non mangrove losses or gains. While the net SOC stock change was calculated as:\n𝑆𝑂𝐶 = 𝑆𝑂𝐶 −𝑆𝑂𝐶\n𝑙𝑜𝑠𝑠 𝑜𝑡ℎ𝑒𝑟𝑠_𝑙𝑜𝑠𝑠 𝑚𝑎𝑛𝑔𝑟𝑜𝑣𝑒_𝑙𝑜𝑠𝑠\n𝑆𝑂𝐶 = 𝑆𝑂𝐶 −𝑆𝑂𝐶\n𝑔𝑎𝑖𝑛 𝑚𝑎𝑛𝑔𝑟𝑜𝑣𝑒_𝑔𝑎𝑖𝑛 𝑜𝑡ℎ𝑒𝑟𝑠_𝑔𝑎𝑖𝑛\n𝑆𝑂𝐶 = 𝑆𝑂𝐶 −𝑆𝑂𝐶\n𝑛𝑒𝑡 𝑔𝑎𝑖𝑛 𝑙𝑜𝑠𝑠\nwhere 𝑆𝑂𝐶 is the SOC stock change during mangrove loss, 𝑆𝑂𝐶 is the\n𝑙𝑜𝑠𝑠 𝑜𝑡ℎ𝑒𝑟𝑠_𝑙𝑜𝑠𝑠\nSOC stocks of mangrove-turned other land use types, 𝑆𝑂𝐶 is the\n𝑚𝑎𝑛𝑔𝑟𝑜𝑣𝑒_𝑙𝑜𝑠𝑠\nmangrove SOC stocks of lost pixels, 𝑆𝑂𝐶 is the SOC stock change during\n𝑔𝑎𝑖𝑛\nmangrove gain, 𝑆𝑂𝐶 is the mangrove SOC stocks of gained pixels,\n𝑚𝑎𝑛𝑔𝑟𝑜𝑣𝑒_𝑔𝑎𝑖𝑛\n𝑆𝑂𝐶 is the SOC stocks of other land use types that turned into mangroves,\n𝑜𝑡ℎ𝑒𝑟𝑠_𝑔𝑎𝑖𝑛\n𝑆𝑂𝐶 is the net SOC stock change during land use changes in mangrove ecosystems\n𝑛𝑒𝑡\nfrom 1996 to 2019. For aquaculture, urban area and permanent water, the loss of\nmangrove SOC equals to the net SOC loss. SOC stock of salt marshes and tidal flats,\nwere firstly extracted from Coastal ATLAS and then use the mean values in each\ncountry for mangrove change areas. For countries that do not have saltmarsh or tidal\nflat SOC observations, global average values were used. For terrestrial ecosystems, we\nuse SoilGrids 2 to calculate the top-meter SOC stock in Google Earth Engine. We\nunderstand that SOC change during land use shifts is very complicated, containing\nvarious biogeochemical process (root exudation, microbial shifts, nutrient conditions\nand etc.) and the change of SOC stock does not happen directly. We simplified this\nprocess by using the difference of SOC stock in these ecosystems when conducting\nlarge-scale analyses.\n4) I am also not convinced by the calculations of benefits here as well. Is the price of\ncarbon reliable and reflective of current mangrove projects? Are there projects that are\nbased on SOC stocks alone? Is a 20 year restoration project believable? These feel like\na house of cards, where the absence of in depth thinking and justification makes the\nwhole analyses and results not believable.\nResponse: Thanks for this comment. We understand that there are a lot of uncertainties\nin the benefit-cost analyses, however, we have tried our best to make it as accurate as\npossible for large-scale analyses. A constant blue C price of 5 t-1CO e USD and 9.4 t-\n2\n1CO e USD for the first five years, roughly matching the average C price of all avoided\n2\ndeforestation projects recorded by Forest Trends’ Ecosystem Marketplace reports\nbetween 2006-20183. After the first five years of mangrove restoration started providing\necosystem service (the 10th year of mangrove restoration), we assumed a 5% price\nappreciation for the following years over a 10 to 40-year restoration time frame4.\nMoreover, a social discount rate of -2%, 4.5% and 8% were applied, where the negative\nvalue reflects the possibility that conditions will deteriorate in the future due to\necological degradation and resource depletion5.We understand that the blue C market\nprice cannot be the same in each country, therefore the local currency and purchasing\npower parity were applied to the market price to generate blue C price in different\ncountries. Mangrove projects are based on several aspects such as regulation for\nextreme events, education, food and raw material supply, climate regulation, and etc.\nTherefore, besides the financial profit from blue C marketing, the ecological benefits\nwere also estimated by using ESV generated from mangrove restoration as a proxy. The\n20-year time frame was adopted by most of the related studies and we use that in this\nstudy to better compare results from different study. To address this concern, we\nconduct these analyses for a 10, 20, 30 and 40-year time frame to give more detailed\ninformation.\n5) I think the manuscript might be mixing up some basic concepts and terms. For\nexample, I am not sure if the manuscript is really calculating the benefits of hypothetical\nrestoration projects (what goes into a mangrove restoration project? how is it funded?).\nThere is also confusion over climate finance and conservation funding.\nResponse: Thanks for this comment. We acknowledged that the process of raising\nfunding, negotiating between governments and local residence, conducting mangrove\nrestoration and the afterward maintenance is complicated. In this study, we calculated\nthe cost of mangrove restoration as the cost of engineering, planting, labor,\nmanagement, and maintenance, however, we did not include the funding process\nbecause the cost of it is less reported and we cannot carry out a relative accurate\ncalculation for over 100 mangrove countries. We highlighted this the process before\nconducting restoration projects was also important in ‘Limitation’ in our revised\nmanuscript.\nWhile the topic is interesting, I believe that the manuscript should be majorly rewritten\nbefore being sent out.\nResponse: Additional data was added by searching Web of Science using several\nkeywords with the publication year after 2020 which is the year after Ouyang and Lee\n(2020). All the publication should be peer-reviewed and not including conference\npapers, and only reported the field data without any experimental treatments. When\nstudy reported SOC stock over multiple soil layers, we recorded all the data, when study\nonly reported the SOC stock of 0-1 m soil layers, we use this data for the global\nsynthesis, when study reported SOC stock of soil layers above 1 m, we recorded these\ndata and we apply a conversion factor to calculate the above meter SOC stock. The\nconversion factor was the average ration of upper layer SOC stock to the above-meter\nSOC stock (eg: SOC stock (0-20 cm)/ SOC stock (0-100 cm)). We also included the\nunpublished data from our field survey across China. Moreover, the mangrove SOC\nstock of 0-1 m from the Coastal ATLAS were included into the final datasets. Therefore,\nthe final mangrove SOC dataset includes four parts: observations from Ouyang and Lee\n(2020), additional studies by searching Web of Science, unpublished data from field\nsurvey across China and Coastal ATLAS. SOC stock was calculated using 2257 data\npoints (longitude, latitude, SOC stock, SOC stock standard error) and conducting\nKriging interpolation on mangrove distributions from Global Mangrove Watch.\nTherefore, the global mangrove SOC stock map were generated, and we aggregate\nresults for each country by dividing the SOC stock map along the border and calculating\nthe country-level mangrove total SOC stock. In the revised version, we deleted the\n‘finding the major regulator of mangrove SOC stock’, therefore, no additional datasets\nwere used. However, we provide some details if you are still interested. The soil\nproperties including nitrogen content, phosphorus content, sand, clay and silt content,\nwere collected by tracing back to all the collected literatures. The aboveground and\nbelowground biomass were extracted from SWAMP datasets. The mangrove canopy\nheight was extracted from Lang, et al. 6 at a resolution of 30 m. The tidal range, mean\nsea level, mean high water spring were extracted from diva site. The DEM data were\nextracted from CoastalDEM at the resolution of 30 m. Climatic data including mean\nannual temperature and mean annual precipitation were extracted from the WorldClim\nat the resolution of 30 m. Only part of the collected literatures reported soil properties\nand biomass data, for the rest of them, we use values in the nearest site to fill the missing\nvalue.\nResponse: Thanks for this comment. The 2020 paper reported the mangrove soil C and\nbiomass C change from 1996-2016 due to the land use change. We cannot say that our\nanalysis is more advanced, but there are a lot of differences. First, we detected the land\nuse types during mangrove losses and gains by layering aquaculture mapping and\nglobal land use land cover maps over the mangrove change areas, which enables us to\ninvestigate the net change of SOC stock and ecosystem service value (ESV). Second,\nwe calculated the mangrove SOC stock loss and the net SOC stock loss by including\nSOC stock data in terrestrial (forest, shrubland, agriculture, bare land, grass land)\nusing SoilGrids dataset, and SOC stock data in coastal wetland (salt marsh and tidal flat)\nusing CoastaL ATLAS, which is the major improvement of this study. Last, this study\nhad longer time scale, ranged from 1996 to 2019. However, we did not include the\nbiomass C into this study since the main focus is the soil C. The importance of analyzing\nthe net SOC stock change instead of the mangrove SOC stock change is to investigate\nwhether mangrove loss would cause greater SOC stock loss than it appears to be. The\nresult showed that, mangrove loss induced greater net SOC stock loss than mangrove\nSOC loss because large number of mangroves were turned into aquaculture and\npermanent water, where the loss of mangrove resulted in the loss of SOC stocks, while\nmangroves mainly gained from salt marshes and tidal flats, where the extent of SOC\nstock increase is not . This improved method highlighted that more SOC stock were\nlost caused by land use changes in mangroves. In the revised manuscript, we use the\nmangrove distribution map from Global Mangrove Watch, which is the same as the\n2020 paper, and the land use land change classification were extracted from Copernicus\nClimate Change Service 1. There was no public global aquaculture distribution,\ntherefore, we developed our own’s through expert visual interpreting using high-\nresolution images in Google Earth.\nResponse: Thanks for this comment. We were aware that there is a process for\nregenerated and planted mangroves to obtain the similar structural characteristic to\nnatural mangroves. For C accumulation, there were studies showing that regenerated or\nrestored mangroves has similar C accumulation rate as the natural mangroves even at\nthe early stage7-9. Moreover, mangrove sediments, in particular, accumulate both\nallochthonous OC from marine or terrestrial origins, facilitated by tidal exchanges, and\nautochthonous OC derived from mangrove vegetation 10-12, where the C accumulation\nwould be less impacted than that in biomass. Therefore, we use the same SOC stock\nper unit area to calculate the mangrove C loss and gain.\nResponse: Thanks for this comment. The data for the cost of mangrove restoration was\ncollected from Su et al., 2021. We then updated these data by searching relevant\nkeywords (mangrove restoration cost, mangrove management cost, mangrove cost, and\netc.) in Web of Science. All the data then standardized into 2020 USD. The cost of\nmangrove restoration on tidal flats and aquaculture were quantified by applying the cost\nof mangrove restoration per unit area to the total areal extent of aquaculture and tidal\nflats that used to be mangroves, and the management cost at 2.5% of the total capital\ncost were aggregated every year of the restoration. Specifically, cost of mangrove\nrestoration was different in each country even using the global average value because\nof the different development status, local currency and purchasing power parity were\napplied to calibrate the cost to the local value. In the revised manuscript, we categorized\nthe ESV into four categories and 18 sub categories (provisioning: food, medicinal\nresources, raw materials and water; regulating: air quality regulating, climate regulating,\nerosion prevention, moderation of extreme events, regulation of water flows waste\ntreatments; cultural: aesthetic information, existence and bequest values, information\nfor cognitive development, inspiration for culture, art and design, opportunities for\nrecreation and tourism; supporting: maintenance of genetic diversity, maintenance of\nlife cycles, maintenance of soil fertility), and all types of ESV were calculated in the\ncost-benefit analysis by adding up all types of ESV as the total ESV. We have attached\nthe original data for cost of mangrove restoration and different types of ESV in the\nrevised version.\nResponse: Thanks for this comment. Stating ‘blue C marketing is the only way to\ngenerate financial benefits from mangrove restoration’ was lack of consideration and\nwe deleted that in the revised manuscript. Since the topic of this manuscript is SOC,\nwe therefore focused on the blue C marketing and we have stated that in methods,\ndiscussion and limitations that mangrove restoration might generate more financial\nprofits through fishery and tourism.\nResponse: Thanks for this comment. In the revised manuscript, we have updated our\nESV datasets for mangroves and other land use types including aquaculture. With more\ndata included, mangrove has greater ESV than aquaculture across different countries,\nthis bias might be caused by insufficient data. But in Southeast countries like Thailand\nand Philippines, the ESV of mangrove are similar as that of aquacultures, probably\nbecause of these countries have well-developed fisheries.\nResponse: Thanks for this comment. We truly apologize for this statement, we have no\nintention to make anyone uncomfortable. We understand that the variance of ESV\nacross countries is mainly caused by the different development status or the attitude\nand policies of the local government towards mangrove ecosystems. In the revised\nmanuscript, we avoided such discomforting statements and explain the variance of ESV\nacross countries. Moreover, we discussed the motivation and goals of mangrove\nrestoration as ‘The motivation of mangrove restoration should be the protection of\nnatural resources and sustainable development rather than the pursuit of greater profits.\nIt is all very well to be able to commercialize mangrove restoration and reap huge\necological and economic returns, but this should not be the only standard to evaluate\nthe feasibility of mangrove restoration. The main goal of these practices is to share\nscientific knowledge and technology, research capacity development and transfer of\nmarine technology. Besides that, C trading was included to better support mangrove\nrestoration initiatives by linking respective communities to international markets.’\nResponse: Thanks for sharing. We have referenced these websites and add related\ndiscussions.\nResponse: For mangrove SOC stock, we reported the standard value, and for cost and\nbenefit analysis, we incorporate different social discount rate at -2.5%, 4% and 8.5%\nand different blue C market price at 5 t-1CO e USD and 9.4 t-1CO e USD for the\n2 2\nuncertainty. Moreover, we extended our time scale from 20 years to 40 years and\nprovided the decadal estimation.\nResponse: Thanks for this comment. We have updated the methods, discussion and\nlimitation to provide more detailed information. Moreover, we have attached all the\noriginal data to enhance clarity and rigor.\nResponse: Thanks for this comment. We have checked all the references, grammars\nand reframe the whole manuscript to be more concise and easier to understand.\nResponse: Thanks for this comment. We have revised the abstract to a more concise\nversion and convey the most important finding and implications to a broader audience.\nResponse: Thanks for this comment. The reviewer #1 and reviewer #2 thought that our\nmanuscript contains too much information and were not connected very well. They\nsuggest that we should write them separately instead of putting them together.\nTherefore, in the revised manuscript, we deleted ‘major regulators of mangrove SOC\nstock’ and focused on the changes in SOC stock and ecosystem service value during\nland use changes in mangrove ecosystem and the cost-benefit analysis of the following\nmangrove restoration. Thanks for the suggestion that environmental settings can\ninfluence the mangrove SOC stock. Our recent global synthesis also reached the same\nconclusion by comparing C sources in estuarine and marine mangroves. Though deleted\nin the revised version, we still consider variance in global mangrove SOC stocks is\nworthy investigating.\nResponse: Thanks for this comment. We have added more detailed information for\nliterature and dataset selection process to enhance the clarity of this study. Besides that,\nwe have attached all the raw data related to mangrove SOC stock, land use types during\nmangrove losses and gains, carbon accumulation rate, ecosystem service value.\nResponse: Thanks for this comment. We have added Table. 1 to the main text\ndescribing the land use change types during mangrove losses and gains, and deleted\nsome tables in supplementary materials since we have reframed this manuscript.\nFurthermore, we moved some supplementary tables an Excel table to be more readable,\nsince some of them are too long.\nResponse: Thanks for this comment. We have added the related discussion by giving\nto highlight the potential for the coastal blue C project to mitigate climate change and\nsimultaneously support livelihood ‘The motivation of mangrove restoration should be\nthe protection of natural resources and sustainable development rather than the pursuit\nof greater profits. It is all very well to be able to commercialize mangrove restoration\nand reap huge ecological and economic returns, but this should not be the only standard\nto evaluate the feasibility of mangrove restoration. The main goal of these practices is\nto share scientific knowledge and technology, research capacity development and\ntransfer of marine technology. Besides that, C trading was included to better support\nmangrove restoration initiatives by linking respective communities to international\nmarkets.’\nResponse: Thanks for this comment. We have added more up-to-date references to the\nrevised manuscript related to blue carbon and coastal management."}, {"round": 2, "reviewer_comments": {"reviewer_2": "I appreciate the reception of my comments by the authors. The revisions are impressive, particularly in terms of the substantial data collection and reanalysis, which have strengthened the manuscript. The elaboration in the methods section is commendable, adding clarity and rigor to the study. However, I still have some concerns with the revised manuscript, as outlined below.\n1. The authors changed the structure of the manuscript from a separate \"Results – Discussion – Conclusion\" format to a combined \"Results & Discussion – Conclusion\" format. While this restructuring may have been intended to streamline the narrative, it does not adequately address the issue raised by Reviewer 1 regarding the lack of cohesion. Instead, it increases inconsistency in the storyline. Each section of the results could almost stand as an individual study, making the manuscript feel fragmented. This diversity in findings may overwhelm readers, making it difficult to capture the key messages of the paper.\n2. While the authors performed a great amount of data collection and analysis in this study, the presence of missing values (as acknowledged in the Limitation section) makes it important to include uncertainty analysis and/or sensitivity analysis to test the robustness of results. It is not very convincing of the BCR results at the country level when the missing data being treated as 0.\n3. The methods used to calculate restoration costs at the continental scale require further explanation. Specifically, it is unclear whether regional heterogeneity in restoration costs was considered. Given the large variance in socio-economic conditions across countries and regions, this factor could significantly affect BCR calculations at the country level.\n4. The revised objectives include \"identifying suitable sites for mangrove restoration.\" However, the findings presented in the manuscript do not fully align with this stated objective. The analysis assumes that tidal flats and aquaculture areas previously converted from mangroves are suitable for restoration, but suitability requires more in-depth evaluation beyond spatial identification. These areas should be described as \"potential restoration areas\" rather than \"suitable restoration areas.\"\n5. The idea of calculating the net BCR that accounts for the hidden loss of aquaculture and tidal flat ESV is intriguing. However, another significant hidden loss in aquaculture is its economic revenue. By not accounting for the economic revenue generated by aquaculture, the net BCR for restoring mangroves in aquaculture areas might be overestimated.", "reviewer_3": "This is my second round to review this MS. This study is an exemplary contribution to the field of blue carbon and mangrove restoration. Firstly, the study provides a holistic approach to mangrove restoration by integrating ecological, economic, and spatiotemporal dimensions. The combination of soil organic carbon (SOC) stock assessment, ecosystem service valuation (ESV), and cost-benefit analysis establishes a robust framework for assessing the feasibility and impacts of mangrove restoration at a global scale. The inclusion of over 2,257 SOC observations and 846 ESV records reflects the extensive effort in data collection and synthesis. The findings emphasize the cost-effectiveness of mangrove restoration, with a high benefit-cost ratio (BCR) and substantial net gains in ESV. This work provides actionable insights for policymakers and stakeholders, highlighting the importance of targeted investments in mangrove restoration projects. Moreover, The global scope of this stuyd, coupled with country-specific analyses, ensures relevance to diverse geographical contexts. The authors identified high-priority regions for restoration of global mangroves, making it valuable for both international and local decision-makers. The authors also discuss potential uncertainties in their estimates in this revision, such as assumptions regarding SOC dynamics and ESV calculations. This enhances the credibility of the work and sets a foundation for future studies to build upon. Totally, I suggest that this paper is not only timely but also essential for advancing knowledge in blue carbon and mangrove restoration, with strong potential for high-impact publication. Congratulations to the authors for their commendable effort in addressing such a critical topic!\nSpecific comments:\n1. Explicitly state how the study fills gaps in prior work, such as limitations in earlier studies on SOC loss and restoration (e.g., lack of detailed cost-benefit analysis or specific mapping of restoration sites).\n2. Add details on how ecosystem service categories (e.g., cultural vs. provisioning) were weighted in the overall ESV calculations.\n3. Discuss how international funding mechanisms, such as the Green Climate Fund, could support large-scale mangrove restoration projects.\n4. Some sentences are overly complex. Simplify technical jargon and ensure concise phrasing, especially in the abstract and introduction."}, "author_response": "Response: Thanks for this comment. We considered the key point of this study is the ecosystem services of mangroves and cost-benefit analysis of the potential mangrove restoration. Upon reflection, we understand that including the SOC stock change in the Results and Discussion section introduced excessive detail and risked overwhelming the reader, as SOC stock is only one aspect of the ecosystem services provided by mangroves. Therefore, we decided to incorporate SOC into mangrove restoration by: (1) showing the contribution of climate regulating service value (usually represented by C sequestration) to the total ESV provided by mangroves; (2) estimating the amount of C sequestrated in restored mangrove soils and the economic return through blue C trading, as C sequestration is an important ecosystem services provided by mangroves. The new storyline of this study is: (1) the current status and changes of ecosystem service value of mangrove ecosystem services; (2) the cost-benefit analysis of the potential mangrove restoration; (3) the potential blue C trading benefits by mangrove restoration.\nThe revised storyline now emphasizes that mangrove loss would induce massive loss of mangrove ecosystem services (SOC stock is one aspect of ecosystem services) and mangrove restoration is needed to alleviate this loss. We have retained references to C accumulation during mangrove restoration and the associated revenue from blue carbon marketing to support the economic perspective of the analysis.\nWe hope this restructuring enhances the manuscript's clarity and improves the reader's experience by presenting a more cohesive and focused narrative.\nThank you again for your constructive suggestions, and we look forward to your further feedback.\nResponse: Thanks for this comment. We now add a sensitivity analysis of BCR and net BCR in the revised manuscript. The current BCR and net BCR were relatively conservative, since we only collected the reported ESV categories, while some ESV types that were not investigated by these studies were overlooked. We fulfilled the 18 mangrove ESV categories with the corresponding average ESV at the country level.\nThe new country-level ESVs were considered as the maximum ESV of mangroves and the BCR and net BCR calculated from that represents the most positive scenario of mangrove restoration. We added this sensitivity analysis to “Limitations” in line 236-240: “We further conducted a sensitivity analysis by filling missing values of 18 ESV subcategories using the global average value adjusted to local socio-economic values and reported the most ideal scenario for mangrove restoration (global BCR:13.8–32.6; global net BCR:13.2–31.9, Table S11, Source data file).”, “Methods” in line 448-458: “Mangrove ESVs were divided into 18 subcategories as above-mentioned, but most of these studies did not cover all of them. For example, the ESV database only provide the “existence, bequest value” and “Food provision” of mangroves in Australia. We believe that mangroves can provide more types of ecosystem services in Australia and countries than recorded. Therefore, the ESV gain and BCR might be underestimated. We further conducted a sensitivity analysis to show the maximum ESV gain and BCR that can be achieved by fulfilling the all 18 ESV subcategories with the global mean values. These mean values were further adjusted to match the local socio-economic conditions according to PPP and local exchange rate. These maximum values show the most ideal scenario for mangrove restoration, however, might be hard to achieve because mangroves cannot provide all types of ecosystem service at one location.”\nWe also updated the “Supporting materials” and “Source data file”.\nResponse: Thanks for this comment. The regional heterogeneity in restoration costs were considered in this study, similar from that in estimating ESVs. The restoration cost was adjusted to 2020 USD according to local exchange rate and the PPP (purchasing power parity). Therefore, we considered the BCR at the country level to reflect the socio-economic conditions. We have added the details of mangrove restoration cost in “Methods” in line 397-399: “Considering the large variance in socio-economic conditions across countries and regions, all cost was transformed into 2020 USD using local currency and purchasing power parity, similar as the ESVs.”\nResponse: Thanks for this comment. We have changed “identifying suitable sites for mangrove restoration” into “identifying potential restoration areas” across this manuscript.\nResponse: Thanks for this comment. The economic revenue of aquaculture is the major part of its ESV and were included in this study. The reported ESVs of aquaculture were divided into 13 subcategories: fishery revenue, nitrogen removal, recreation, raw materials, gas regulation, climate regulation, environmental cleaning, hydrological regulation, soil conservation, maintenance of nutrient cycling, maintenance of biological diversity, aesthetic landscape and water supply. We now specify that the fishery revenue was included in aquaculture ESV in “Cost-benefit analysis” in line 160-165: “When accounting for the hidden cost of losing ESV from aquaculture and tidal flats, the net BCR was then calculated by subtracting the ESV of aquaculture (including fishery revenue) and tidal flats on the basis of the restored mangrove ESV.” and “Methods” in line 281-282: “94 observations of aquacultures (most of them were reported as fishery revenue)”. We also have provided the data of ESVs of all 10 land use types related to mangrove change in “Source data file”.\nResponse: Thanks for this comment. We have incorporated SOC into mangrove restoration by: (1) showing the contribution of climate regulating service value (usually represented by C sequestration) to the total ESV provided by mangroves; (2) estimating the amount of C sequestrated in restored mangrove soils and the economic return through blue C trading, because Reviewer#2 suggest that too much information would overwhelm readers and we set our key points as “large amount of ecosystem service value has been lost due to mangrove loss, and to alleviate this loss, mangrove restoration is needed. The cost-benefit analysis of potential mangrove restoration can provide practical information to policy makers and stakeholders.” We now state how this study fills gaps in prior work in introduction in line 58-60: “While many studies have investigated the ecological drivers and outcomes of mangrove restoration, there is a research gap in addressing the associated economic benefits at country-level and specific mapping of potential mangrove restoration areas.”\nResponse: Thanks for this comment. We compare the average value of ESV categories at country level, specifically, values of each categories were calculated as the sum of its subcategories. At global scale, all ESV categories of one country were weighted by its mangrove areal extent. We have added a detailed description of that in methods in line 337-344: “Mangrove ESV categories were compared at country-level and calculated as follows:\n𝑛\n𝐸𝑆𝑉 = ∑𝐸𝑆𝑉\n𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦𝑁 𝑚𝑒𝑎𝑛_𝑠𝑢𝑏𝑁_𝑖\n𝑖=1\nwhere 𝐸𝑆𝑉 is certain mangrove ESV categories, such as regulating, 𝑛 is the\n𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦𝑁\nnumber of ESV subcategories, 𝐸𝑆𝑉 is the corresponding ESV\n𝑚𝑒𝑎𝑛_𝑠𝑢𝑏𝑁_𝑖\nsubcategories under that ESV category. It should be noted that, not all ESV\nsubcategories were reported in one study. The missing values were treated as 0.” and\nline 353-368: “Values of different mangrove ESV types and its contribution to the total\nmangrove ESV per year in each country were calculated as follows:\n𝐸𝑆𝑉 = 𝐸𝑆𝑉 ×𝐴𝑟𝑒𝑎\n𝑐𝑎𝑡𝑒𝑁_𝑐𝑜𝑢𝑛𝑡𝑟𝑦𝑋 𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦𝑁\n𝐸𝑆𝑉\n𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦𝑁\n𝐶𝑜𝑛𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛 =\n𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦𝑁 𝐸𝑆𝑉\n𝑇𝑜𝑡𝑎𝑙\nwhere 𝐸𝑆𝑉 is the ESV of certain categories per year in each country,\n𝑐𝑎𝑡𝑒𝑁_𝑐𝑜𝑢𝑛𝑡𝑟𝑦𝑋\n𝐴𝑟𝑒𝑎 is the mangrove distribution area, 𝐶𝑜𝑛𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛 is the relative\n𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦𝑁\ncontribution of certain ESV categories in each country. The contribution of ESV\ncategories at global scale is weighted as follows:\n𝑚\n𝐸𝑆𝑉 = ∑𝐸𝑆𝑉\n𝑐𝑎𝑡𝑒𝑁_𝑔𝑙𝑜𝑏𝑎𝑙 𝑐𝑎𝑡𝑒𝑁_𝑐𝑜𝑢𝑛𝑡𝑟𝑦𝑋\n𝑖=1\n4\n𝐸𝑆𝑉 = ∑𝐸𝑆𝑉\n𝑇𝑜𝑡𝑎𝑙_𝑔𝑙𝑜𝑏𝑎𝑙 𝑐𝑎𝑡𝑒𝑁_𝑔𝑙𝑜𝑏𝑎𝑙\n𝑖=1\n𝐸𝑆𝑉\n𝑐𝑎𝑡𝑒𝑁_𝑔𝑙𝑜𝑏𝑎𝑙\n𝐶𝑜𝑛𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛 =\n𝑐𝑎𝑡𝑒𝑁_𝑔𝑙𝑜𝑏𝑎𝑙 𝐸𝑆𝑉\n𝑇𝑜𝑡𝑎𝑙_𝑔𝑙𝑜𝑏𝑎𝑙\nwhere 𝐸𝑆𝑉 is the global value of certain ESV categories per year, 𝑚 is\n𝑐𝑎𝑡𝑒𝑁_𝑔𝑙𝑜𝑏𝑎𝑙\nthe number of countries with ESV observations, 𝐸𝑆𝑉 is the global total\n𝑇𝑜𝑡𝑎𝑙_𝑔𝑙𝑜𝑏𝑎𝑙\nESV per year, 𝐶𝑜𝑛𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛 is the contribution of certain ESV\n𝑐𝑎𝑡𝑒𝑁_𝑔𝑙𝑜𝑏𝑎𝑙\ncategories at global level.”\n.\nResponse: Thanks for this comment. We now added several sentences in “Economic returns of mangrove restoration” to discuss how international funding mechanism could support large-scale mangrove restoration projects in line 219-226 “International funding mechanisms, such as the Green Climate Fund could support large-scale mangrove restoration projects by forming collaboration between local authorities, experts and farmers to perform mangrove restoration and boost the income of farmers, fisherfolks, and other rural business, such as beekeeping and honey production. Furthermore, Climate-resilient housing and community-based disaster risk management, vulnerability assessments and planning process are also being scaled up to ensure the long-term growing benefits. (https://www.greenclimate.fund).”\nResponse: Thanks for this comment. We have simplified technical jargon and rephrasing to make this manuscript easy to read."}]

Decision letter