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Challenges and opportunities for achieving Sustainable Development Goals through restoration of Indonesia’s mangroves

Nature Ecology & Evolution volume 7, pages 62–70 (2023)Cite this article

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Abstract

Indonesia, the most mangrove-rich nation in the world, has proposed the most globally ambitious mangrove rehabilitation target (600,000 ha) of any nation, to be achieved by 2024 to support multiple Sustainable Development Goals (SDG 1–3, 6, 13 and 14). Yet, mangrove restoration and rehabilitation across the world have often suffered low success rates and been applied at small scales. Here, we identify 193,367 ha (estimated costs at US$0.29–1.74 billion) that have the potential to align with the national mangrove rehabilitation programme. Despite being only 30% of the national target, our robust assessment considered biogeomorphology, 20 years of land-use and land-cover change and state forest land status, all key factors moderating mangrove restoration success which have often been neglected in Indonesia. Increasing subnational government representation in mangrove governance as well as improving monitoring and evaluation will increase the likelihood of achieving the mangrove rehabilitation targets and reduce risks of failure. Rehabilitating and conserving mangroves in Indonesia could benefit 74 million coastal people and can potentially contribute to the national land-sector emissions reduction of up to 16%.

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Fig. 1: Distribution and potential area of mangrove restoration opportunity for three scenarios (low, medium and high) in Indonesia.
Fig. 2: Location and area of mangrove loss across Indonesia between 2001 and 2020.
Fig. 3: Geographical distribution of mangrove revegetation, restoration and rehabilitation study locations between 1990 and 2020 in Indonesia.
Fig. 4: The distribution of mangrove loss area (in hectares) between 2001 and 2020 in Indonesia.

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Data availability

All data are available in the main text or the Supplementary Information. Results data from this study on mangrove restoration potential area by region in Indonesia can be accessed through the following figshare repository link: https://doi.org/10.6084/m9.figshare.19636458. The generated spatial results data on mangrove restoration potential area in Indonesia can be directly accessed in Google Earth Engine using the following asset ID: projects/ee-mangroverestoration/assets/Indo_mangrove_restore.

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Acknowledgements

This work was funded by the Ministry of Education and Culture Republic of Indonesia under the World Class University Program of Universitas Sumatera Utara Year 2020 (grant no. 1879/UN5.1.R/SK/PPM/2020). This study was part of the Newton Fund project MOMENTS and supported by a research grant from the Indonesian Science Fund and Indonesia Endowment Fund for Education (DIPI/LPDP grant no. NE/P014127.1) and National Geographic Society Research and Exploration grant (NGS-68810R-20). S.D.S. was supported by NERI Integrated Tropical Peatlands Research Programme (R-706-000-062-720). D.M. was supported by the United States Agency for International Development grant no. MTO 069033.

Author information

Author notes

  1. These authors contributed equally: Sigit D. Sasmito, Mohammad Basyuni.

  2. These authors jointly supervised this work: Sigit D. Sasmito, Mohammad Basyuni.

Authors and Affiliations

  1. NUS Environmental Research Institute, National University of Singapore, Singapore, Singapore

    Sigit D. Sasmito

  2. Department of Geography, National University of Singapore, Singapore, Singapore

    Sigit D. Sasmito

  3. Department of Forestry, Faculty of Forestry, Universitas Sumatera Utara, Medan, Indonesia

    Mohammad Basyuni

  4. Center of Excellence for Mangrove, Universitas Sumatera Utara, Medan, Indonesia

    Mohammad Basyuni

  5. Banyuwangi, Indonesia

    Age Kridalaksana

  6. Denpasar Bali, Indonesia

    Meli F. Saragi-Sasmito

  7. School of Biological Sciences, The University of Queensland, St Lucia, Queensland, Australia

    Catherine E. Lovelock

  8. Center for International Forestry Research, Bogor, Indonesia

    Daniel Murdiyarso

  9. Department of Geophysics and Meteorology, IPB University, Bogor, Indonesia

    Daniel Murdiyarso

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Contributions

Conceptualization of this work was by S.D.S. and M.B. The methodology was developed by S.D.S., M.B., A.K. and M.F.S. Investigations were undertaken by S.D.S., M.B., A.K., M.F.S., C.E.L. and D.M. Visualization was by S.D.S. and A.K. Funding was obtained by S.D.S. and M.B. The project was administered by S.D.S. and M.B. with supervision by C.E.L. and D.M. The original draft was written by S.D.S. and M.B. who, along with A.K., M.F.S., C.E.L. and D.M., were involved in reviewing and editing the final manuscript.

Corresponding authors

Correspondence to Sigit D. Sasmito or Mohammad Basyuni.

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Nature Ecology & Evolution thanks Liza Goldberg, Mark Huxham, Lisa Schindler Murray and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Key mangrove management and conservation policies in Indonesia and relevant international environmental agenda between 1990 and 2030.

A further detailed list of mangrove management policies in Indonesia is described in Supplementary Table 1.

Extended Data Fig. 2 Mangrove restoration opportunity scenarios according to their loss drivers or the latest land use types, namely erosion, commodities, settlement, non-productive conversion, climate event and deforested mangrove.

a, national distribution of restoration opportunity scenarios at 1 degree grid, b, selected grids of restoration opportunity scenarios distribution in South Sumatra, Riau, North Kalimantan, East Kalimantan, and West Kalimantan province, c, the proportion and area of restoration opportunity scenarios across all provinces in Indonesia according to loss drivers documented by Goldberg et al.12 (see methods section for detailed description how this study overlaid loss drivers data with tree cover loss data by Hansen et al.33). Mangrove loss drivers such as erosion, settlement, and climate event were considered of having a low restoration opportunity scenario, while other drivers including commodities and non-productive conversion were a medium scenario. The high restoration opportunity scenario was only considered in areas where mangroves are deforested (living biomass is removed with minimal soil and hydrological disturbance). Further description of the scenarios classification for each loss driver is provided in Supplementary Table 4.

Extended Data Fig. 3 Mangrove restoration opportunity scenarios according to their forest land status in Indonesia, namely other land use allocation, production and protected forests.

a, national distribution of restoration opportunity scenarios at 1 degree grid, b, selected grids of restoration opportunity scenarios distribution in South Sumatra, Riau, North Kalimantan, East Kalimantan, and West Kalimantan province, c, the proportion and area of restoration opportunity scenarios across all provinces in Indonesia according to the national standard for land status by Ministry of Environment and Forestry35. A low opportunity scenario was given to areas belonging to other land use allocations (area penggunaan lain or APL), where this specific land status is commonly associated with private land ownership. Medium and high restoration opportunity scenarios were respectively assigned to areas under production forest (hutan produksi) and protected forest (hutan lindung) designations. Further description of the scenarios classification for each loss driver is provided in Supplementary Table 4.

Extended Data Fig. 4 Mangrove restoration opportunity scenarios according to multiple biogeomorphological settings.

The mangrove typologies included in this study are delta-terrigenous, estuary-terrigenous, open coast-carbonate, open coast-terrigenous, and others (an area that does not belong to any settings described by Worthington et al.34). a, national distribution of restoration opportunity scenarios at 1 degree grid, b, selected grids of restoration opportunity scenarios distribution in South Sumatra, Riau, North Kalimantan, East Kalimantan, and West Kalimantan province, c, the proportion and area of restoration opportunity scenarios across all provinces in Indonesia according to biogeomorphological typology. The low scenario was assigned to areas located in both open coast-carbonate and open coast-terrigenous settings. A medium scenario was given to areas located in delta-terrigenous and other settings. Estuary-terrigenous was the only setting with a high restoration opportunity scenario. Further description of the scenarios classification for each loss driver is provided in Supplementary Table 4.

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2 and Tables 1–14.

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Sasmito, S.D., Basyuni, M., Kridalaksana, A. et al. Challenges and opportunities for achieving Sustainable Development Goals through restoration of Indonesia’s mangroves. Nat Ecol Evol 7, 62–70 (2023). https://doi.org/10.1038/s41559-022-01926-5

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