COMMENTARY Going Local: How Coastal Environmental Settings Can Help

10.1029/2022GL101979
Improve Global Mangrove Carbon Storage and Flux Estimates
Key Points:
Pierre Taillardat1 
• C arbon burial rates between mangrove
sedimentary and geomorphic types 1
NUS Environmental Research Institute, National University of Singapore, Singapore, Singapore
were analyzed in Breithaupt and
Steinmuller (2022, https://doi.
org/10.1029/2022GL100177)
• Greater carbon burial rates were Abstract  The magnitude and variability of mangrove carbon storage are uncertain and still being discussed.
reported in terrigenous deltas and In a recent article, Breithaupt and Steinmuller (2022, https://doi.org/10.1029/2022GL100177) completed a
estuaries rather than in lagoons and literature review and compared mangrove organic carbon burial rates between different coastal environmental
carbonate settings
• Comparing carbon burial rates with settings (CES) that integrate sedimentary supply (terrigenous vs. carbonate) and hydrogeomorphic settings
other stocks and fluxes between (delta, estuary, lagoon, open coast). They found greater burial rates in terrigenous delta and estuaries while
mangrove types can help refine the lower rates were reported in lagoons and carbonate settings. Surprisingly, these CES relationships do not
global mangrove carbon budget
strictly match previous mangrove soil carbon stock estimates but were consistent with biomass stocks. The
CES approach used by Breithaupt and Steinmuller should be used for other mangrove carbon stocks and fluxes
Correspondence to: estimates to refine our understanding of mangrove carbon cycling and storage.
P. Taillardat,
taillardat.pierre@nus.edu.sg
Plain Language Summary  Mangrove forests are intertidal ecosystems efficient at trapping carbon
in their sediments. While this ecological process is well recognized, the quantity of carbon being deposited
Citation:
is still uncertain. Considering the growing number of studies that have collected samples to estimate carbon
Taillardat, P. (2022). Going local: How
coastal environmental settings can help
burial rates, Breithaupt and Steinmuller (2022, https://doi.org/10.1029/2022GL100177) recently published
improve global mangrove carbon storage a meta-analysis to compile and compare carbon burial between mangrove types. Their study reported great
and flux estimates. Geophysical Research variability between mangrove types based on their sediment supply and geomorphological configuration. Their
Letters, 49, e2022GL101979. https://doi.
org/10.1029/2022GL101979
results are interesting because they go against previous estimates of mangrove carbon stocks distribution. Also,
the approach used has the potential to be applied to other components of the mangrove carbon budget. Doing so
Received 4 NOV 2022 would improve our fundamental understanding of carbon cycling in mangrove ecosystems. It would also help
Accepted 7 NOV 2022 refine carbon storage estimates for future conservation projects interested in generating carbon credits.

1. Introduction
Mangrove forests are highly productive ecosystems located along diverse tropical and subtropical coastal land-
forms. Their ecological efficiency at fixing atmospheric carbon dioxide (CO2) through photosynthesis and preserv-
ing this so-called “blue carbon” in their water-saturated soils over large time scales have caughed the attention of
researchers over the last three decades (Macreadie et al., 2019; Twilley et al., 1992). There is clear evidence that
mangrove forests and other blue carbon ecosystems (BCE) effectively keep carbon away from the atmosphere and
can contribute to mitigating climate change at the national and global scale (Macreadie et al., 2021; Taillardat,
Friess, & Lupascu, 2018). Consequently, BCE have gained interest within governmental and corporate entities
interested in offsetting their greenhouse gas (GHG) emissions (Friess et al., 2022). While some researchers are
interested in bridging the gap between scientific knowledge and carbon market operational needs (Macreadie
et al., 2022), others are calling for caution as fundamental research gaps and conceptual approaches challenge the
effectiveness of implementing blue carbon as a reliable carbon removal strategy (Williamson & Gattuso, 2022).

The ecological heterogeneity of mangrove forests prevents robust estimates of carbon burial potential at both
local and global scales. Unlike terrestrial forests, mangrove primary productivity and soil carbon preservation
are influenced by sediment types and physical forces (e.g., river, tides, wave) which control the hydrology, nutri-
ent supply, sediment origins and soil biogeochemical properties (Twilley et al., 2018; Woodroffe et al., 2016).
Despite this acknowledged spatial variability, the majority of the global mangrove carbon burial estimates have
© 2022. The Authors.
This is an open access article under upscaled an average or median plot-scale burial value (Alongi,  2014,  2020; Bouillon et  al.,  2008; Breithaupt
the terms of the Creative Commons et al., 2012; Chmura et al., 2003; Pérez et al., 2018). Although those global extrapolations are useful to constrain
Attribution License, which permits use, the fundamental knowledge gap of mangrove carbon cycling, they also hamper our comprehensive understanding
distribution and reproduction in any
medium, provided the original work is of mangrove carbon variability across space. Consequently, refined quantifications are necessary to integrate
properly cited. mangrove carbon storage in countries' Nationally Determined Contributions (Martin et al., 2016) and generate

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Figure 1.  (a) Boxplots of measured mangrove soil organic carbon (SOC) burial rates (gC m −2 y −1) by geomorphic class from Breithaupt and Steinmuller (2022). (b)
Boxplots of measured SOC density (mgC m −3) from Rovai et al. (2018). (c) Boxplots of modeled SOC stocks (MgC ha −1) from Rovai et al. (2021). The n values at the
bottom of each panel indicate the number of samples integrated to produce the boxplot. Boxplots span the interquartile range (25%–75% quartiles), whiskers 5%–95%
of observations, horizontal lines are the medians and circle points represent the outliers. One outlier for terrigenous delta in panel (a) is not shown as its value is
1,749 gC m −2 y −1. The arheic category present in Rovai et al. (2018, 2021) was removed since it could not be compared with Breithaupt and Steinmuller (2022).

carbon credits that could appeal to the corporate sector interested in offsetting their carbon burden through the
voluntary carbon market (Friess et al., 2022).

2.  Coastal Environmental Settings Explain Macroscale Mangrove Soil Organic

Carbon Burial Variability
In their recent paper published in Geophysical Research Letters, Breithaupt and Steinmuller (2022; https://doi.
org/10.1029/2022GL100177) addressed this issue by combining plot-scale carbon burial rates from mangroves
around the world with a macroscale mangrove typology. Their analysis is based on an updated version of the
mangrove carbon burial data set from Breithaupt et al. (2012), combined with a coastal environmental settings
(CES) classification from Worthington et al. (2020), that combined sedimentary types (terrigenous vs. carbonate)
and geomorphic settings (delta, estuary, lagoon, open coast). Breithaupt and Steinmuller show that, by including
relevant new studies from the last 10 years, the number of observations more than tripled. The updated data set
totalizes 205 observations. Despite a larger statistical population, the data were non-normally distributed. Hence,
the data set from Breithaupt and Steinmuller confirms that the arithmetic mean traditionally used to estimate
carbon burial rates at the global scale is statistically inaccurate. Additionally, Breithaupt and Steinmuller demon-
strate that the “one value fits all” type of approach is ecologically inappropriate. Between sedimentary types,
the mangrove soil organic carbon (SOC) burial adjusted mean for terrigenous settings (n = 137) was about 55%
greater than for carbonate settings (n = 68). However, the differences between terrigenous and carbonate settings
were less obvious when those sedimentary settings were compared between geomorphic types (e.g., no signifi-
cant difference was reported between terrigenous lagoons and carbonate lagoons). Between geomorphic settings,
significant differences were also reported with maximum burial rates of 217.2 (148.0–308.2) gC  m −2  yr −1
(adjusted mean and 95% confidence interval in brackets) in terrigenous delta and a minimum value of 53.7
(39.3–71.7) and 63.6 (95.0–205.0) gC m −2 yr −1 in carbonate and terrigenous lagoons, respectively.

The differences revealed by Breithaupt and Steinmuller can be explained by the different hydrological and sedi-
mentary dynamics typically observed between the different CES. Terrigenous deltas are river-dominated and
localized in wide-fan-shaped alluvial plains (Worthington et al., 2020). Consequently, river-derived allochtho-
nous (i.e., non-local) organic and inorganic materials get deposited in those intertidal sediments. Nutrients are
also brought in which stimulates mangrove primary productivity and associated burial of autochthonous (i.e.,
local) OC (Twilley et al., 2018). As a result, terrigenous deltas represent a carbon burial hotspot (Figure 1a).
On the other hand, carbonates and lagoons have the lowest carbon burial rates (Figure 1a). This is explained
by the limited lateral exchange with the surrounding environments. Carbonate mangroves are found in karstic
environments and on oceanic islands (Twilley et  al.,  2018; Worthington et  al.,  2020). Hence, autochthonous

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input represents the majority of the carbon being buried. Consequently, those environments are typically
nutrient-limited (Rovai et al., 2021).

3.  Carbon Burial Rates Versus Carbon Content: A Mangrove Soil Organic Carbon
Paradox?
The work presented by Breithaupt and Steinmuller offers opportunities to compare carbon burial rates with other
components of the mangrove carbon cycle. For instance, Rovai et al. (2018, 2021) described mangrove soil carbon
density and soil carbon stocks using CES classification adapted from Dürr et al. (2011). To allow comparability
between the studies, data categories from Breithaupt and Steinmuller were reorganized in this Commentary so
that carbonate would represent one single category instead of three subgroups (i.e., carbonate estuary, carbonate
lagoon, carbonate open coast). Similarly, “delta (large river)” and “small delta” from Dürr et al. (2011) were
merged into one category “delta.” Surprisingly, opposite trends are observed when carbon burial rates (Figure 1a)
are compared with SOC density (Figure 1b) and, although less clearly, modeled SOC stocks (Figure 1c). While
the greater SOC density and SOC stocks were reported for carbonate settings (Figures 1b and 1c), it represented
the second lowest carbon burial rate (Figure 1a). Conversely, terrigenous delta and terrigenous estuary repre-
sent  the environmental settings with the lowest SOC stocks (Figures 1b and 1c) despite having the highest carbon
burial rates (Figure 1a). This suggests a “mangrove soil organic carbon paradox.” Three reasons can explain this
contradiction.

First, an inconsistency between the two CES classifications exists. As a consequence, some sites classified as
one category are accounted as a different type in the other classification. This affects the comparability of the
data set, although it is unlikely that the difference would substantially influence the overall results and trends
presented here (Figure 1). While the studies called for a need to enhance consistency between the mangrove clas-
sification and analysis, they did not follow one another. Hence, future studies should strictly follow one mangrove
classification to facilitate comparison. Since the typology from Worthington et al. (2020) is available and easily
accessible for Geographic Information System analysis, it should represent the mangrove typology reference.

Second, soil depth requires to be considered and reported to provide total soil SOC stock estimates. Most studies
and syntheses documenting mangrove SOC stocks have provided estimates for the top meter only (e.g., Atwood
et al., 2017; Jardine & Siikamäki, 2014; Poulter et al., 2021). This was also the case for the data set presented
in Figures 1b and 1c (Rovai et al., 2018, 2021). However, studies quantifying carbon at deeper depths reported
greater carbon stocks (Donato et al., 2011; Sanderman et al., 2018; Sanders et al., 2016). When only looking at
the first meter of soil, it makes sense that higher carbon densities are reported in lagoons and carbonate settings
(Figure 1) since the SOC they store is not being “diluted” by allochthonous inorganic sediment deposition as
reported in terrigenous delta and estuaries. However, it is important to stress that soil carbon density does not
equal total SOC stocks. Likely, the timeframe of SOC accumulation within the first top meter is greater in the
lagoons and carbonate settings is greater than in river- and tide-dominated settings, since sediment accretion is
expected to be lower (Krauss et al., 2014; MacKenzie et al., 2016). Thus, a mangrove carbon SOC stocks global
analysis that integrate soil depth is needed to reconcile SOC burial rates and stocks estimates.

A third explanation may be related to the methods used to estimate SOC content. Sanderman et al. (2018) reported
a lack of consistency between studies and transparency in the method used. One critical component is to know
if inorganic carbon and roots were effectively removed from the reported SOC concentration. A good common
practice is to follow the protocol described by Kauffman and Donato (2012).

4.  Coastal Environmental Settings Can Help Refine Other Key Components of the
Mangrove Carbon Budget
The approach presented by Breithaupt and Steinmuller is a new contribution to enhance our understanding of
mangrove carbon storage. Such an approach, as shown in the paragraph above, can help put individual compo-
nents of the mangrove carbon cycle into perspective. CES are influencing mangrove biogeochemical budget
inputs and outputs. A complete reanalysis of mangrove storage and exchange following the approach proposed by
Breithaupt and Steinmuller is therefore needed.

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In addition to SOC, Rovai et  al.  (2021) assessed how CES explain aboveground biomass spatial variability.
The absolute biomass carbon stocks ranking between environmental settings were similar to the one reported
by Breithaupt and Steinmuller for SOC burial rates. Terrigenous deltas and estuaries had significantly higher
biomass carbon stocks than lagoons and carbonates settings (Rovai et al., 2021). Fluvial sediment supply and
nutrient input physically and chemically help mangrove vegetation productivity. On the other hand, the absence
of those allochthonous resources may explain the lowest biomass stocks in lagoons and carbonate settings (Rovai
et al., 2021).

Carbon losses from mangroves, to the atmosphere or coastal waters, are also likely to vary between CES. For
instance, methane (CH4) emission rates and processes are highly variable and still poorly documented (Rosentreter
et al., 2021). The driving forces are unclear although anoxic conditions, presence (or absence) of sulfides and
salinity have been identified to influence the release of CO2 and CH4 (Neubauer & Megonigal, 2022). Tidal pump-
ing is another mechanism that influences the mangrove carbon budget (Maher et al., 2018; Santos et al., 2021)
that may vary with hydrogeomorphic settings. Observations from multiple study sites suggest that the magnitude
of carbon export and release, including CO2 and CH4, fluctuates over daily, semi-diurnal, spring-neap-spring and
seasonal cycles (e.g., Call et al., 2015, 2019; Taillardat, Willemsen, et al., 2018; Taillardat, Ziegler, et al., 2018).
Hence, quantifying the respective contribution of GHG emissions and tidal exchange within and between CES
will help refine mangrove carbon exchange estimates and their implication for the coastal and global carbon
budget.

5.  Summary and Outlook

Breithaupt and Steinmuller set an important baseline for explaining the effect of CES on mangrove carbon
cycling. The presented carbon burial rates require to be compared with other mangrove carbon fluxes and stocks
such as net primary productivity, biomass, ecosystem respiration, aquatic export and soil carbon stocks (that
integrates soil depth and associated carbon content). To allow accurate comparison, a consistent mangrove clas-
sification needs to be employed such as the one presented by Worthington et al. (2020). In addition to this need
for interdisciplinarity and classification consistency, three challenges relevant for future carbon management and
conservation initiatives will also need to be adressed.

First, SOC burial rate variability is also important within each CES. Lugo and Snedaker  (1974) proposed a
conceptual model to describe the microtopographic and ecological zonation within each environmental setting
(i.e., interior, basin, fringe, riverine). This heterogeneity adds another layer of complexity in the pursuit of
understanding mangrove ecological dynamics and associated carbon processes. For example, Hatje et al. (2021)
reported that the burial rate variability along an intertidal gradient in a Brazilian mangrove was as important
as the global variability. Nevertheless, the same environmental variables seem to be influencing the different
burial rates at the microscale which could suggest that the geomorphic approach proposed by Breithaupt and
Steinmuller could also be relevant along intertidal gradients.

Second, clarifying the contribution of allochthonous SOC burial in mangroves is essential for carbon credits
allocation. While mangroves on terrigenous deltas have high SOC burial and sedimentation rates, a substantial
fraction of it is coming from outside the ecosystem boundaries. Hence, if this carbon has only been moved down-
stream and did not originate from mangrove vegetation photosynthesis, it should not be accounted as such unless
it is demonstrated that preservation remains thanks to mangrove soil conditions (Jennerjahn, 2020; Williamson
& Gattuso, 2022). Otherwise, this would lead to a risk of double counting carbon sequestration gains between
the original ecosystem and mangroves. Conversely, marine organic matter produced and stored in the mangrove
ecosystem boundaries such as seaweed, benthic microalgae, plankton and epiphytes should be included in carbon
inventories since the represent a key, yet overlooked, constituent of this BCE. Demonstrating the origin and
proportion of the SOC stored in mangroves is still a challenge. The combination of carbon and nitrogen isotopes
along with environmental DNA has shown promising results but that still requires to be streamlined (Geraldi
et al., 2019).

Third, anticipating the effect of environmental change such as sea level rise, eutrophication, warming temper-
atures and atmospheric CO2 concentrations on carbon burial rates and preservation is essential. This would
require identifying a baseline that would not have been affected by environmental changes to demonstrate the

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“permanence” of the carbon stocks and that the newly stored SOC remains a long-term carbon removal approach,
despite the risk of coastal erosion, sediment deprivation and enhanced organic matter decomposition.

Data Availability Statement

Data is available through Breithaupt and Steinmuller (2022) and Rovai et al. (2018, 2021).

Acknowledgments References
The author would like to thank
Angelicque White, Editor at Geophysical Alongi, D. M. (2014). Carbon cycling and storage in mangrove forests. Annual Review of Marine Science, 6(1), 195–219. https://doi.org/10.1146/
Research Letters for the invitation to annurev-marine-010213-135020
write this Commentary. The author is Alongi, D. M. (2020). Global significance of mangrove blue carbon in climate change mitigation. Science, 2(3), 67. https://doi.org/10.3390/
also grateful to Joshua L. Breithaupt and sci2030067
André Rovai for clarifying and sharing Atwood, T. B., Connolly, R. M., Almahasheer, H., Carnell, P. E., Duarte, C. M., Lewis, C. J. E., et al. (2017). Global patterns in mangrove soil
their data sets. carbon stocks and losses. Nature Climate Change, 7(7), 523–528. https://doi.org/10.1038/nclimate3326
Bouillon, S., Borges, A. V., Castañeda-Moya, E., Diele, K., Dittmar, T., Duke, N. C., et al. (2008). Mangrove production and carbon sinks: A
revision of global budget estimates. Global Biogeochemical Cycles, 22(2), GB2013. https://doi.org/10.1029/2007GB003052
Breithaupt, J. L., Smoak, J. M., Smith, T. J., Sanders, C. J., & Hoare, A. (2012). Organic carbon burial rates in mangrove sediments: Strengthening
the global budget. Global Biogeochemical Cycles, 26(3), 1–11. https://doi.org/10.1029/2012GB004375
Breithaupt, J. L., & Steinmuller, H. E. (2022). Refining the global estimate of mangrove carbon burial rates using sedimentary and geomorphic
settings. Geophysical Research Letters, 1(18), e2022GL100177. https://doi.org/10.1029/2022GL100177
Call, M., Maher, D. T., Santos, I. R., Ruiz-Halpern, S., Mangion, P., Sanders, C. J., et al. (2015). Spatial and temporal variability of carbon diox-
ide and methane fluxes over semi-diurnal and spring-neap-spring timescales in a mangrove creek. Geochimica et Cosmochimica Acta, 150,
211–225. https://doi.org/10.1016/j.gca.2014.11.023
Call, M., Sanders, C. J., Macklin, P. A., Santos, I. R., & Maher, D. T. (2019). Carbon outwelling and emissions from two contrasting mangrove
creeks during the monsoon storm season in Palau, Micronesia. Estuarine, Coastal and Shelf Science, 218, 340–348. https://doi.org/10.1016/j.
ecss.2019.01.002
Chmura, G. L., Anisfeld, S. C., Cahoon, D. R., & Lynch, J. C. (2003). Global carbon sequestration in tidal, saline wetland soils. Global Biogeo-
chemical Cycles, 17(4), 1111. https://doi.org/10.1029/2002gb001917
Donato, D. C., Kauffman, J. B., Murdiyarso, D., Kurnianto, S., Stidham, M., & Kanninen, M. (2011). Mangroves among the most carbon-rich
forests in the tropics. Nature Geoscience, 4(5), 293–297. https://doi.org/10.1038/ngeo1123
Dürr, H. H., Laruelle, G. G., van Kempen, C. M., Slomp, C. P., Meybeck, M., & Middelkoop, H. (2011). Worldwide typology of nearshore
coastal systems: Defining the estuarine filter of river inputs to the oceans. Estuaries and Coasts, 34(3), 441–458. https://doi.org/10.1007/
s12237-011-9381-y
Friess, D. A., Howard, J., Huxham, M., Macreadie, P. I., & Ross, F. (2022). Capitalizing on the global financial interest in blue carbon. PLOS
Climate, 1(8), e0000061. https://doi.org/10.1371/journal.pclm.0000061
Geraldi, N. R., Ortega, A., Serrano, O., Macreadie, P. I., Lovelock, C. E., Krause-Jensen, D., et al. (2019). Fingerprinting blue carbon: Rationale
and tools to determine the source of organic carbon in marine depositional environments. Frontiers in Marine Science, 6, 1–9. https://doi.
org/10.3389/fmars.2019.00263
Hatje, V., Masqué, P., Patire, V. F., Dórea, A., & Barros, F. (2021). Blue carbon stocks, accumulation rates, and associated spatial variability in
Brazilian mangroves. Limnology & Oceanography, 66(2), 321–334. https://doi.org/10.1002/lno.11607
Jardine, S. L., & Siikamäki, J. V. (2014). A global predictive model of carbon in mangrove soils. Environmental Research Letters, 9(10), 104013.
https://doi.org/10.1088/1748-9326/9/10/104013
Jennerjahn, T. C. (2020). Relevance of allochthonous input from an agriculture-dominated hinterland for “Blue Carbon” storage in
mangrove sediments in Java, Indonesia. Dynamic Sedimentary Environments of Mangrove Coasts, 393–414. https://doi.org/10.1016/
B978-0-12-816437-2.00017-3
Kauffman, J. B., & Donato, D. C. (2012). Protocols for the measurement, monitoring and reporting of structure, biomass and carbon stocks in
mangrove forests (p. 50). CIFOR. Working Paper 86.
Krauss, K. W., Mckee, K. L., Lovelock, C. E., Cahoon, D. R., Saintilan, N., Reef, R., & Chen, L. (2014). How mangrove forests adjust to rising
sea level. New Phytologist, 202(1), 19–34. https://doi.org/10.1111/nph.12605
Lugo, A. E., & Snedaker, S. C. (1974). The ecology of mangroves. Annual Review of Ecology and Systematics, 5(1), 39–64. https://doi.
org/10.1146/annurev.es.05.110174.000351
MacKenzie, R. A., Foulk, P. B., Klump, J. V., Weckerly, K., Purbospito, J., Murdiyarso, D., et al. (2016). Sedimentation and belowground carbon
accumulation rates in mangrove forests that differ in diversity and land use: A tale of two mangroves. Wetlands Ecology and Management,
24(2), 245–261. https://doi.org/10.1007/s11273-016-9481-3
Macreadie, P. I., Anton, A., Raven, J. A., Beaumont, N., Connolly, R. M., Friess, D. A., et al. (2019). The future of blue carbon science. Nature
Communications, 10(1), 1–13. https://doi.org/10.1038/s41467-019-11693-w
Macreadie, P. I., Costa, M. D. P., Atwood, T. B., Friess, D. A., Kelleway, J. J., Kennedy, H., et al. (2021). Blue carbon as a natural climate solution.
Nature Reviews Earth & Environment, 2(12), 826–839. https://doi.org/10.1038/s43017-021-00224-1
Macreadie, P. I., Robertson, A. I., Spinks, B., Adams, M. P., Atchison, J. M., Bell-James, J., et al. (2022). Operationalizing marketable blue
carbon. One Earth, 5(5), 485–492. https://doi.org/10.1016/j.oneear.2022.04.005
Maher, D. T., Call, M., Santos, I. R., & Sanders, C. J. (2018). Beyond burial: Lateral exchange is a significant atmospheric carbon sink in
mangrove forests. Biology Letters, 14(7), 20180200. https://doi.org/10.1098/rsbl.2018.0200
Martin, A., Landis, E., Bryson, C., Lynaugh, S., Mongeau, A., & Lutz, S. (2016). Blue carbon—Nationally determined contributions inventory.
In Ap-pendix to: Coastal blue carbon ecosystems. Opportunities for Nationally Determined Contributions (GRID Arendal).
Neubauer, S. C., & Megonigal, J. P. (2022). Biogeochemistry of wetland carbon preservation and flux. https://doi.org/10.1002/9781119639305.ch3
Pérez, A., Libardoni, B. G., & Sanders, C. J. (2018). Factors influencing organic carbon accumulation in mangrove ecosystems. Biology Letters,
14(10), 20180237. https://doi.org/10.1098/rsbl.2018.0237

TAILLARDAT 5 of 6
 Geophysical Research Letters 10.1029/2022GL101979

Poulter, B., Fluet-Chouinard, E., Hugelius, G., Koven, C., Fatoyinbo, L., Page, S. E., et al. (2021). A review of global wetland carbon stocks and
management challenges (pp. 1–20). https://doi.org/10.1002/9781119639305.ch1
Rosentreter, J. A., Al-Haj, A. N., Fulweiler, R. W., & Williamson, P. (2021). Methane and nitrous oxide emissions complicate coastal blue carbon
assessments. Global Biogeochemical Cycles, 35(2), 1–8. https://doi.org/10.1029/2020GB006858
Rovai, A. S., Twilley, R. R., Castañeda-Moya, E., Midway, S. R., Friess, D. A., Trettin, C. C., et al. (2021). Macroecological patterns of forest
structure and allometric scaling in mangrove forests. Global Ecology and Biogeography, 30(5), 1000–1013. https://doi.org/10.1111/geb.13268
Rovai, A. S., Twilley, R. R., Castañeda-Moya, E., Riul, P., Cifuentes-Jara, M., Manrow-Villalobos, M., et al. (2018). Global controls on carbon
storage in mangrove soils. Nature Climate Change, 8(6), 534–538. https://doi.org/10.1038/s41558-018-0162-5
Sanderman, J., Hengl, T., Fiske, G., Solvik, K., Adame, M. F., Benson, L., et al. (2018). A global map of mangrove forest soil carbon at 30 m
spatial resolution. Environmental Research Letters, 13(5), 055002. https://doi.org/10.1088/1748-9326/aabe1c
Sanders, C. J., Maher, D. T., Tait, D. R., Williams, D., Holloway, C., Sippo, J. Z., & Santos, I. R. (2016). Are global mangrove carbon stocks
driven by rainfall? Journal of Geophysical Research: Biogeosciences, 121(10), 2600–2609. https://doi.org/10.1002/2016JG003510
Santos, I. R., Burdige, D. J., Jennerjahn, T. C., Bouillon, S., Cabral, A., Serrano, O., et al. (2021). The renaissance of Odum's outwelling hypoth-
esis in “Blue Carbon” science. Estuarine, Coastal and Shelf Science, 255, 107361. https://doi.org/10.1016/j.ecss.2021.107361
Taillardat, P., Friess, D. A., & Lupascu, M. (2018). Mangrove blue carbon strategies for climate change mitigation are most effective at the
national scale. Biology Letters, 14(10), 20180251. https://doi.org/10.1098/rsbl.2018.0251
Taillardat, P., Willemsen, P., Marchand, C., Friess, D. A., Widory, D., Baudron, P., et  al. (2018). Assessing the contribution of porewater
discharge in carbon export and CO2 evasion in a mangrove tidal creek (Can Gio, Vietnam). Journal of Hydrology, 563, 303–318. https://doi.
org/10.1016/j.jhydrol.2018.05.042
Taillardat, P., Ziegler, A. D., Friess, D. A., Widory, D., Truong Van, V., David, F., et al. (2018). Carbon dynamics and inconstant porewater
input in a mangrove tidal creek over contrasting seasons and tidal amplitudes. Geochimica et Cosmochimica Acta, 237, 32–48. https://doi.
org/10.1016/j.gca.2018.06.012
Twilley, R. R., Chen, R. H., & Hargis, T. (1992). Carbon sinks in mangroves and their implications to carbon budget of tropical coastal ecosys-
tems. Water, Air, & Soil Pollution, 64(1–2), 265–288. https://doi.org/10.1007/BF00477106
Twilley, R. R., Rovai, A. S., & Riul, P. (2018). Coastal morphology explains global blue carbon distributions. Frontiers in Ecology and the Envi-
ronment, 16(9), 503–508. https://doi.org/10.1002/fee.1937
Williamson, P., & Gattuso, J. P. (2022). Carbon removal using coastal blue carbon ecosystems is uncertain and unreliable, with questionable
climatic cost-effectiveness. Frontiers in Climate, 4, 1–14. https://doi.org/10.3389/fclim.2022.853666
Woodroffe, C. D., Rogers, K., McKee, K. L., Lovelock, C. E., Mendelssohn, I. A., & Saintilan, N. (2016). Mangrove sedimentation and response
to relative sea-level rise. Annual Review of Marine Science, 8(1), 243–266. https://doi.org/10.1146/annurev-marine-122414-034025
Worthington, T. A., zu Ermgassen, P.  S. E., Friess, D. A., Krauss, K. W., Lovelock, C. E., Thorley, J., et  al. (2020). A global biophysical
typology of mangroves and its relevance for ecosystem structure and deforestation. Scientific Reports, 10(1), 1–11. https://doi.org/10.1038/
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