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https://doi.org/10.1038/s43247-025-02035-4
Permanence risks limit blue carbon
financing strategies to safeguard
Southeast Asian mangroves
Check for updates
Valerie Kwan 1,DanielA.Friess
2, Tasya Vadya Sarira 3& Yiwen Zeng 4,5
Conserving Southeast Asia’s mangroves is a vital natural climate solution, and their protection could
be supported by blue carbon credits. However, such financing strategies expose conservation efforts
to socioeconomic and climate change permanence risks. Here, we evaluate the potential impacts of
permanence risks on the ability of blue carbon financing to safeguard mangroves. Using opportunity
costs associated with oil palm, rice and aquaculture land use conversion as indicators of
socioeconomic risks, and predicted cyclones and sea-level rise as indicators of climate change risks,
we find that 85% of mangroves are likely to experience some form of permanence risk. Diverse funding
sources and risk mitigation measures need to be contextualised in a long time horizon to maintain
conservation viability into the future. Understanding how these risks interact and affect mangrove
conservation efforts over timescales relevant to carbon permanence is key to minimizing risks and
ensuring positive socio-ecological outcomes.
Mangroves are an important coastal ecosystem that provides substantial
benefits to people1. Despite this, mangroves have experienced substantial
rates of loss globally. Although the rate of mangrove loss is lowerin the 21st
Century2compared to historically, their conservation is often constrained
by socioeconomic and environmental factors3,4. One promising way to
expand conservation efforts leverages the ability of mangroves to sequester
carbon dioxide from the atmosphere andstore it at high densities over long
timescales, known as blue carbon. Effective management of blue carbon
habitats has the potential to contribute to climate change mitigation,
allowinggovernments and businesses to use theconservation of threatened
mangrove habitats and their restoration as a means of meeting climate
goals5,6.
Fungible blue carbon credits are being sold through market-based
mechanisms that can sustainably fund the protection of blue carbon habitats
to meet climate goals7,8. The conservation of mangroves through blue car-
bon credit financing could be especially important for regions such as
Southeast Asia, where 32% (4.7 Mha) of the world’s mangroves are found9.
In this region, although commodities-driven deforestation has declined by
77% since 2000, high rates of human-driven deforestation persist at 0.2%
loss per year2. The conservation of 0.6 Mha of mangroves in Southeast Asia
via carbon credits is potentially profitable10, although in practice, credit sales
may cover a fraction of total costs (e.g. Cispatá Bay in Colombia, ~70% of
costs covered11,12). Indeed, recognition of this potential has led to a growing
interest in establishing such mangrove-avoided deforestation conservation
projects across the region, and support from major financial institutions and
governments5,6.
The growing interest in carbon credits as a tool for conservation is,
however, matched by an increasing scrutiny of various risks that threaten
carbon permanence of such projects13,14. Socioeconomic constraints and
climate change are two of the key barriers that could limit the efficacy of
carbon credits as a conservation measure11,15,16. In particular, implicit costs,
such as land uses more profitable than conservation, are often unaccounted
for but are likely to threaten the viability of avoided deforestation projects,
especially if alternative values are perceived to be higher than the value of
conservation. For instance, mangrove areas have historically been converted
into agriculture and aquaculture commodities production to generate
income17. Forgoing revenue generated from commodities to operationalise
avoided deforestation projects represents opportunity costs that are often
intertwined with governance and issues of benefit sharing15.Withoutade-
quate and equitable compensation for forgone revenue, land conversion to
commodities is more likely to persist and threaten carbon permanence.
Additionally, mangroves are also vulnerable to climate change impacts.
Over the long term, changing biophysical conditions, such as more intense
and frequent storm damage, or increasing inundation with sea-level rise, are
1School of the Environment, The University of Queensland, St Lucia, QLD, Australia. 2Department of Earth and Environmental Sciences, Tulane University, New
Orleans, LA, USA. 3Nicholas School of the Environment, Duke University Marine Lab, Beaufort, NC, USA. 4Asian School of the Environment, Nanyang Techno-
logical University, Singapore, Singapore. 5School of Social Sciences, Nanayang Technological University, Singapore, Singapore. e-mail: v.kwan@uq.edu.au;
yiwen.zeng@ntu.edu.sg
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threats to mangrove forest integrity and their ability to store carbon18,19.
Understanding how socioeconomic and climate change risks can threaten
the permanence of avoided deforestation projects funded via blue carbon
market-based strategies is key to prioritising conservation efforts and
mitigating risks.
Here, we assess how socioeconomic and climate change risks impact
the long-term viability and potential of blue carbon financing to serve as the
primary means of mangrove conservation across Southeast Asia. We cal-
culate the baseline extent of investible mangroves within 0.01˚spatial units.
We define investible mangroves as mangrove areas that would minimally
fulfil the additionality criterion for carbon credit certification, according to
the United Nations Framework Convention on Climate Change, Reducing
Emissions from Deforestation and Forest Degradation (REDD) and REDD
+programmes10,14,20. This follows a business-as-usual scenario of mangrove
loss without conservation interventions, using the annual baseline rate of
deforestation10 (0.24 ± 0.54 ha yr−1per spatial unit). Next, we evaluate the
financial viability of mangrove-avoided deforestation projects through the
generation of fungible carbon credits.
We quantify the magnitude of socioeconomic risk based on forgone
commodities production from the three major drivers of mangrove forest
loss in the region—cultivation of oil palm, rice and aquaculture17.We
estimate the spatially explicit opportunity cost from potential commodities
production revenue in mangrove areas across Southeast Asia21–24,andcal-
culate the fraction of total costs covered by the potential revenue generated
from per tonne of carbon (one carbon credit). A spatial unit with a smaller
fraction of the costs covered is considered to be more vulnerable to land
conversion in the future, thus facing a higher degree of socioeconomic
permanence risk. In addition, we quantify the magnitude of climate change
permanence risks compounding socioeconomic permanence risks. Speci-
fically, we calculate the cumulative probability of impact from Category 3
cyclones and mangrove submergence from sea-level rise over 25-, 50-, 75-,
100-year permanence timeframes18,25,26.
Results
This analysis shows that 2.1 Mha—or 43% of the mangrove forests across
Southeast Asia—fulfil the fundamental additionality requirement for the
sale of carbon credits under an avoided deforestation scenario. Without
considering socioeconomic and climate change risks, the idealised project
establishment and maintenance costs of all investible mangrove areas can be
fully offset by carbon credits at the current carbon price of US$29.72 t−1
CO
2
e (carbon dioxide equivalent)27 in this analysis.
We find that the inclusion of forgone commodities revenue as an
indicator of relative socioeconomic risk can have major impacts on the
financial sustainability of avoided deforestation projects and carbon per-
manence (Fig. 1). At US$29.72 t−1CO
2
e, 0.9 Mha (range: 0.7–1.1 Mha) of
mangrove areas or 45% (range: 34–51%) of investible mangroves have less
than 30% of costs covered by carbon credits and are more likely to
experience permanence risk from land-use conversion to oil palm planta-
tions, while 38% (range: 0–55%) of these mangroves are more likely to be at
risk from conversion to rice plantations. About 62% (range: 62–63%) of
investible mangroves are more likely to be at risk from conversion to
aquaculture ponds. Increasing carbon prices can help mitigate such socio-
economic risks and a greater proportion of areas will be more financially
viable (Fig. 1). Importantly, over various timeframes and carbon prices,
potential revenue from aquaculture production far exceeds that of blue
carbon financing (median: US$4.5–4.9 million versus US$0.1–0.9 million
per spatial unit), and any carbon price between US$29.72 and US$200 t−1
CO
2
e fails to increase the proportion of investible mangroves with at least
30% of costs covered by carbon credits (Fig. 1).
The potential for conversion to oil palm plantations, rice fields and
aquaculture ponds could also represent compounding permanence risks.
Investible mangroves in Myanmar, eastern Indonesia and the Philippines
are likely to experience the least number of socioeconomic permanence risks
assessed, whereas mangroves around southwest Thailand, Peninsular
Malaysia, Sumatra Indonesia and Borneo are likely to experience higher
Oil palm Aquaculture
25 years 75 years 100 years
50 100 150 200 50 100 150 200 50 100 150 200
0.00
0.25
0.50
0.75
1.00
0.00
0.25
0.50
0.75
1.00
0.00
0.25
0.50
0.75
1.00
0.00
0.25
0.50
0.75
1.00
Carbon price US$ /tCO2e
Proportion of investible mangroves
Cost covered by carbon credits 0 to 10% 10 to 30% 30 to 50% 50 to 70% 70 to 100% > 100%
Climate change risk 0% 0 to 10% 10 to 50% > 50%
Fig. 1 | Permanence risks can have major impacts on mangrove conservation via
carbon credits. Modelled area of investible mangroves in Southeast Asia, with the
proportion of project and opportunity costs associated with socioeconomic risks
matched by carbon credits in a 25-year project (median estimates), from the current
carbon unit price of US$29.72 to US$200 t−1CO
2
e (carbon dioxide equivalent). All
carbon credits at the Global Climate Impact X carbon credit auction held in June
2023 were sold at US$29.72 t−1CO
2
e, although the highest bidded carbon unit price
was US$50 t−1CO
2
e (dotted line). Climate change risk from Category 3 cyclones and
sea-level rise indicated by opacity.
https://doi.org/10.1038/s43247-025-02035-4 Article
Communications Earth & Environment | (2025) 6:57 2
Content courtesy of Springer Nature, terms of use apply. Rights reserved
levels of risk (Fig. 2). In total, 30% of investible mangroves across Southeast
Asia are likely to experience all three socioeconomic permanence risks
considered in this study.
We find that although medium-term (i.e. 25 years) climate change risk
during a project’s duration can be largely minimal, the longer-term per-
manence risk can be substantial. Considering mangrove areas with at least
30% of costs covered at the current c arbon price, only 4–5% have more than
a 50% chance of experiencing climate change risk over a 25-year period.
Over a 50-year period, 27–30% of mangrove areas can be expected to
experience climatechangerisk(Fig.1). Over 75 and 100 years, this increases
further to 33–39% of mangrove areas. More than half of the total investible
mangrove areas have a non-zero likelihood of facing at least one major
cyclone event or experiencing sea-level rise within 100 years. Mangroves at a
low risk of damage from cyclones and submergence from sea-level rise over
a 100-year timeframe are mostly found on the southwestern coast of
Thailand, the western coast of Peninsular Malaysia, Sumatra Indonesia,
Borneo, and eastern Indonesia (Fig. 3).
Taken together, we estimate that 1.8 Mha or 85% of investible man-
grove areas are likely to experience some form of permanence risk at the
current carbon unit price over the next 100 years, which threatens
15.9 Mt CO
2
eyr
−1of climate change mitigation potential, across all three
uncertainty scenarios. Conversely, there are 0.3 Mha of mangroves that
could experience minimal socioeconomic and climate change risks, which
could contribute 2.4 Mt CO
2
eyr
−1of climate change mitigation. These areas
(e.g. eastern Indonesia) represent conservation priorities where avoided
deforestation projects are more likely to maintain lower levels of risks from
commodities production development, cyclone damage and submergence
from sea-level rise.
Discussion
Our study suggests that despite the huge potential for blue carbon financing
to conserve a large proportion of the region’s mangrove areas, roughly only
15% of these investible areas are at low risk of conversion to commodities
production or climate change impacts over the next 100 years. This trans-
lates to a climate change mitigation potential equivalent to over a quarter of
the net emissions from the Agriculture, Forestry and Other Land Use sector
of Thailand in 2015 (8.3 MtCO
2
e)28.
Aquaculture is likely to pose the greatest socioeconomic risk to
mangrove-avoided deforestation projects in the near term. Aquaculture
has been an essential economic activity in Southeast Asia over the last ~50
years. Between 2000 and 2012 alone, about 30% of mangroves were
converted to aquaculture, with hotspots occurring in Indonesia, Cam-
bodia and the Philippines17. Consideration of socioeconomic permanence
risks is needed to moderate the promises of continued conservation
benefits during and beyond project timeframes, and to calibrate con-
servation interventionsand standards to mitigate future risks. Pressingly,
30% of investible mangroves are expected to encounter compounding
socioeconomic risks, which suggests that long-term conservation in these
areas may face greater uncertainty. The potential additive or synergistic
effect of multiple options for converted land use, which potentially
increases opportunity costs, will likely pose a major hinderance to man-
grove conservation. Yet, heterogenous local contexts will also heavily
influence such land-use decisions, making it difficult to disentangle the
potential effects of interacting socioeconomic permanence risks.
Accordingly, opportunity cost is not the only factor that defines socio-
economic permanence risks. Many factors, such as governance and eco-
nomic infrastructures, influence land-use conversion for commodities
production. For example, market liberalisation fetches higher prices for
commodities and could exacerbate mangrove deforestation by encoura-
ging production29, although commodity-driven deforestation has
declined by 77%, which is attributed to production intensification instead
of expansion2,30. This statistic also implies that since defining additionality
by baseline deforestation rate assumes linearity, socioeconomic risks
could be considerably underestimated or overestimated for some areas.
Fig. 2 | Socioeconomic risk hotspots in Southeast Asia. Spatially explicit map of Southeast Asia investible mangroves that fulfil the additionality criteria, where most land
parcels are suitable for land conversion to a combination of oil palm, rice and aquaculture commodities production, aggregated to 10 km resolution.
https://doi.org/10.1038/s43247-025-02035-4 Article
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Our findingsalso highlight the needfor mangrove conservation policy
to consider blue carbon financing within a wider portfolio of different
funding approaches11,15. We show that, at the current carbon unit price,
about 1.3 Mha or 63% of investible mangroves across Southeast Asia could
generate larger revenue from commodity production than carbon markets.
While this estimate is based on simplifying assumptions (e.g. project cost
and production yields; see Methods for more details), it nevertheless
highlights the potential and need for blended finance to close the funding
gap. Globally, a number of conservation projects arebeing considered and
are currently in the pre-feasibility stage, and few have successfully trans-
acted carbon credits11. Uncertainty about return on investment also points
to the vital role of multiple financing approaches. Here, we identified some
areas to be at high risk of conversion to commodities production but are
less exposed to climate change impacts (e.g. southwest Thailand, Peninsula
Malaysia, Sumatra Indonesia, Borneo); mangrove conservation here is
likely to be more viable in the long run if additional funding sources such as
non-profit public and philanthropic funds are secured11,15.Forexample,
about 70% of programme costs at Cispatá Bay, Colombia is covered by
credit sales, while the remaining 30% is supplemented by government
funding and biodiversity loss compensation11,12. Other ecosystem services
or co-benefits, such as coastal protection, could also be leveraged in novel
funding mechanisms15,31. With a similar effect of increasing the profit
margins of mangrove conservation, closing the price gap between com-
pliance and voluntary markets could also help incentivise the establish-
ment of more mangrove conservation projects while mitigating
permanence risks32. Further, although the Kunming-Montreal Global
Biodiversity Framework target of protecting 30% of mangrove areas has
already been achieved32, policy mechanisms such as the expansion of
protected areas could remain effective conservation measures3.However,
the designation of marine protected area status does not necessarily negate
permanence risks. For example, with increasingly fewer non-protected
areas viable for commodities production, there are instances of
exploitation occurring within conservation areas2. Moreover, natural dri-
vers of mangrove loss, such as extreme weather events and changes to
hydrology, can operate across a large spatial scale and affect mangroves
regardless of protection status.
Conservation of areas facing a moderate degree of risk can still be viable
if mitigation measures are in place. Measures need to be adaptable to a
changing climate, in order to address both socioeconomic and climate
change permanence risks and secure the continued climate change miti-
gation potential of these habitats11. Approaches towards socioeconomic risk
mitigation could include community- and indigenous-managed protected
areas, and promoting sustainable livelihoods13. To build climate resilience,
landward migration of mangroves in response to sea-level rise should be
factored into conservation plans33. Currently, a large proportion of South-
east Asia’s coastline is fronted by coastal defences or other infrastructure34,
so the opportunity for large-scale landward migration is expected to be
limited for many locations. Re-engineering of existing topographical bar-
riers and reassessment of planned coastal development in anticipation of
future mangrove landward migration is a priority. Climate change impacts
not examined in this work include changes in precipitation and increasing
temperatures; however, these stressors are predicted to have less substantial
negative impacts on mangroves in Southeast Asia35. Synergistic interactions
between stressors can potentially exacerbate impacts. For example, as higher
latitudes get warmer, latitudinal range expansion of tropical species is pre-
dicted to occur. The new forest communities may have reduced resilienc e to
cyclones, thus amplifying the magnitude of cyclone damage36. Nonetheless,
the prediction of climate change and its impacts, such as cyclone
trajectories37, carry a large degree of uncertainty, which suggests a con-
servative risk model affecting carbon permanence may best inform miti-
gation measures.
Both socioeconomic and climate change permanence risks are critical
considerations, and existing standards already incorporate some degree of
these risks within their methods and approaches for the implementation
Fig. 3 | Climate change risk hotspots in Southeast Asia. Investible mangroves in Southeast Asia that have a non-zero likelihood of impact from sea-level rise and cyclones
within 100 years, aggregated to 10 km resolution.
https://doi.org/10.1038/s43247-025-02035-4 Article
Communications Earth & Environment | (2025) 6:57 4
Content courtesy of Springer Nature, terms of use apply. Rights reserved
and expansion of mangrove blue carbon projects. For instance, buffer credits
can be used to incentivise project developers to guard against permanence
risks. A proportion of carbon credits generated from carbon projects must
be withheld from sale and only released if project integrity is maintained for
afixed number of years38. However, some terrestrial projects are close to
exhausting their buffer pools due to high frequencies of natural drivers of
carbon loss39, which may be observed in mangroves in high-risk areas in the
future. Carbon verification methodologies such as Verra’s VM0007 incor-
porate a non-permanence risk tool that includes estimating the risk of sea-
level rise within a project boundary, and assesses the level of climate change
impacts for designation of projects38. Strengthening such mitigation actions
will be necessary for conservation interventions to generate positive con-
servation outcomes over the long term.
Ultimately, we show that permanence risks from socioeconomic and
climate change sources could severely limit the ability of blue carbon
financing to support mangrove conservation efforts across Southeast Asia.
At the recently transacted carbon price of US$29.72 t−1CO
2
e, we find that
38–62% of mangroves, which technically qualify for carbon markets to
support operational and establishment cost of conservation, face the risk of
conversion to commodities production. We also find that a further 33–39%
of mangroves facing low socioeconomic risk are likely to be impacted by
cyclones or sea-level rise within the next 75–100 years. Our results illustrate
the importance of considering the permanence of conservation interven-
tions beyond project timeframes. These considerations can aid conservation
planning to maximise the long-term financial viability while minimising
risks for conservation action to bring about positive socio-ecological
outcomes.
Methods
Firstly, we mapped investible mangrove areas across Southeast Asia that
meet the additionality requirement for the issuance of carbon credits. Then,
we evaluated the socioeconomic risk as opportunity costs associated with
suitability for mangrove conversion into commodities production. Lastly,
we modelled future climate risk using predicted cyclone wind speeds and
decadal vulnerability to sea-level rise as indicators of annual mangrove
persistence.
Spatial units were created as 0.01˚cells to assign country codes to each
unit. Global mangrove change from 1996 to 202040 was used to identify the
net mangrove area change within each spatial unit. A negative net change
was indicative of qualification for carbon credits under an avoided defor-
estation methodology; these spatial units contained investible threatened
mangroves that fulfil the additionality criterion. Spatial units with a positive
net change were removed from the analysis. The baseline net change was
divided by the number of years (i.e. 24 years) to determine annualised rate of
mangrove loss without further conservation intervention, assuming that the
rate of forest loss remained constant in the future.
We excluded mangroves within the World Database on Protected
Areas from the current global mangrove extent layer40 based on the
assumption that the land conversion of mangroves to agriculture within
protected areas was prohibited. The area of current unprotected mangroves
were calculated for each spatial unit. Mangrove carbon stocks on a spatial
unit level were calculated based on global datasets at 30 m resolution41,42
(belowground biomass calculated as AGB +0.073 *AGB1.32)43, with bio-
mass converted to carbon stock by multiplying by 0.47510. Carbon seques-
tration rate was taken as 163 gC m−2yr−1(see ref. 44).
For socioeconomic risks, we calculated opportunity costs associated
with oil palm, rice, and aquaculture commodity production17 from suit-
ability maps for mangrove conversion21–23. Areas demarcated as high agri-
cultural suitability for future oil palm development21 were considered to be
vulnerable forests. We considered areas with Global Agro-Ecological Zones
Crop suitability index greater than 7500 for high input rain-fed rice for the
period of 2041–2070 to be forests vulnerable to conversion to rice
plantation17,22. For example, in Indonesia, the dominant rice varieties are
IR64, IR36, Lematang and Sei Lilin45.
There are no aquaculture suitability layers encompassing Southeast
Asia; we followed the methodology in Giap et al.23 which derived shrimp
aquaculture suitabilityfor Vietnam through spatial analysis, and applied it
to Southeast Asia (see Table 1for spatial layers). This is justified by the
main aquaculture products of Southeast Asia being crustaceans such as
whiteleg shrimp, giant tiger prawn, and Indo-Pacific swamp crab46.
Briefly, three groups of factors –potential for pond construction, soil
quality, and availability of infrastructure –were considered to contribute
towards suitability for aquaculture development. The pixel values of all
factor layers were extracted for each spatial unit. The weights used here
were as determined in Giap et al.23, with more emphasis given to potential
for pond construction, than soil quality and infrastructure. Lastly, scores
of the three groups of factors were summed to calculate the overall suit-
ability score, where we set 80 as the threshold for aquaculture suitability.
We note that our aquaculture suitability layer was not validated by
ground-truth data.
Opportunity costs for each spatial unit was calculated based on
country-level FAO data for gross production value, harvested area, and
production quantity46,47 (Supplementary Table 1), and suitable conversion
area. Suitable conversion area was taken to be the lower value between
existing mangrove area, and palm, rice, aquaculture suitability, respectively.
Greenhouse gas emissions from alternative land uses were calculated as
CO
2
equivalent (CO
2
e)48–50 (Supplementary Table 2). Total carbon abate-
mentwascalculatedasthesumofavoided mangrove biomass carbon loss
based on the annualised rate of deforestation, mangrove carbon seques-
tration and the total avoided emissions from land-use conversion across the
project timeframe.
The net present value was calculated as the sale of carbon credits from
total carbon abatement minus forgone commodities revenue, based on 25-,
50-, 75- and 100-year project timeframe, and at a 10% risk-adjusted dis-
count rate. The annual maintenance and establishment costs were estimated
from terrestrial conservation projects, following previously estimated
averages (US$25 ha−1and US$232 ha−1, respectively)51. Net present value
was modelled over a range of carbon unit prices from the recently transacted
price of US$29.7227 to 200 t−1CO
2
e. A positive net present value indicated
that the spatial unit faced a low risk of impermanence due to less likely
conversion to commodities production, and can potentially be conserved
with financing from blue carbon credits.
The landfall windspeed of a Category 3 cyclone, noted for the
destruction of mangrove canopy and forest structure, was determined to
be 20.83 ms−1(see ref. 36). The probability of a destructive cyclone
occurring in any given year was defined as the inverse of the earliest return
period to exceed the windspeed threshold, for a range of return periods
from 10 years up to 10,000 years26. The probability of a destructivecyclone
occurring at least onceover each avoided mangrove deforestation project
timeframe was modelled as the cumulative density function of a binomial
distribution. Future climate risk was based on decadal vulnerability to sea-
level rise for each spatial unit at RCP618. Then,we calculate the cumulative
annual probability of mangrove being impacted from cyclones and sea-
level rise.
Uncertainties were derived from four sources (Supplementary
Table 3). First, the root:shoot ratios used to calculate belowground bio-
mass from aboveground biomass were based on 95% confidence interval
of values reported for mangrove belowground biomass allometric
equation43, resulting in multipliers values of 0.906 and 1.134 for total
biomass carbon stock. Secondly, the establishment cost of US$232 ha−1
and an annual maintenance cost of US$25 ha−1was multiplied by 1.2, 1.0
and 0.8 for lower, medium and upper estimates10,51. Thirdly, uncertainties
in prices of rice, oil palm, and fish were based on the average annual price
change in nine years from OECD-FAO Agricultural Outlook
2023–203252. This resulted in a 1.51% annual price increase for palm oil,
0.57% for rice, and 1.27% for fish. Lastly, greenhouse gas emissions from
alternative land uses were based on 95% confidence intervals reported in
IPCC reports48–50.
https://doi.org/10.1038/s43247-025-02035-4 Article
Communications Earth & Environment | (2025) 6:57 5
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Data availability
Script for aquaculture suitability spatial analysis available at: https://code.
earthengine.google.com/074fc11afa5943f7c0db5b25008749de.Datafiles
and code to reproduce all other results and figures are available at https://doi.
org/10.5281/zenodo.1463052053.
Received: 13 September 2024; Accepted: 14 January 2025;
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Table 1 | Layers used for aquaculture suitability spatial analysis, following Giap et al.23 on shrimp farming suitability in Vietnam
Layers used in Giap et al.23 Layers used in this study Factor group Pixel value Score
Land-use type N.A.*
Slope NASA NASADEM Digital Elevation 30 m Potential for pond construction 0–24
2–53
5–10 2
>10 1
Soil thickness Global 1-km Gridded Thickness of Soil, Regolith, and Sedimentary Deposit
Layers
Potential for pond construction >1 4
0.5–13
<0.5 2
Elevation SRTM Digital Elevation Data Version 4 Potential for pond construction 2–2.5 4
2.5–4or1–23
4–52
>5 or <1 1
Soil type N.A.
Soil pH OpenLandMap Soil pH in H
2
O at 0 cm Soil quality 60–70 4
50–60 3
40–50 or 70–80 2
<40 or >80 1
Clay content OpenLandMap Clay Content at 0 cm Soil quality >35 4
18–35 3
<18 2
Distance to sea N.A.
Water source N.A.
Distance to roads Global Roads Inventory Project Infrastructure <500 4
500–1000 3
1000–2000 2
>2000 1
Population density GPWv411: Population Density (Gridded Population of the World
Version 4.11)
Infrastructure <500 4
500–1000 3
1000–2000 2
>2000 1
Distance to market N.A.
Distance to hatchery N.A.
*N.A. indicates either similar conditions assumed within mangroves, so the layer was not used, or, regional-scale data could not be found.
https://doi.org/10.1038/s43247-025-02035-4 Article
Communications Earth & Environment | (2025) 6:57 6
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Acknowledgements
Y.Z. acknowledges support from the NTU Start-Up Grant (03INS002001C210).
This research is supported by the Ministry of Education, Singapore, under its
MOE AcRF Tier 3 Award MOEMOET32022-0006.
https://doi.org/10.1038/s43247-025-02035-4 Article
Communications Earth & Environment | (2025) 6:57 7
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Author contributions
V.K.: conceptualisation, formal analysis, writing—original draft, writing—review
and editing. D.A.F.: conceptualisation, writing—review and editing. T.V.S.:
conceptualisation, writing—review and editing. Y.Z.: conceptualisation,
supervision, writing—review and editing.
Competing interests
The authors declare no competing interests.
Additional information
Supplementary information The online version contains
supplementary material available at
https://doi.org/10.1038/s43247-025-02035-4.
Correspondence and requests for materials should be addressed to
Valerie Kwan or Yiwen Zeng.
Peer review information Communications Earth & Environment thanks
Juan Gaitan Espitia, Chuancheng Fu and the other, anonymous, reviewer(s)
for their contribution to the peer review of this work. Primary Handling
Editors: Ariel Soto-Caro and Martina Grecequet. A peer review file is
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