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Hydro-geomorphological drivers across scales shape the trajectory of coastal wetland restoration

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Abstract

Coastal wetlands provide essential ecosystem services but continue to decline globally, driving demand for effective restoration. Managed realignment, which relocates sea defenses landward to reinstate tidal exchange, is a key nature-based solution for creating self-sustaining wetlands. However, unpredictable restoration outcomes highlight the need for a framework to understand the underlying physical drivers and prioritize sites. Using four decades of satellite data from 69 global sites, we show that over 80% of the restoration projects maintained or expanded wetlands. These trajectories are primarily shaped by regional sediment supply, local tide-relative elevation, and internal tidal creek connectivity. Extending this framework globally, we estimate about 920 square kilometres of wetlands lost since the 1990s could be restored under current physical conditions. Recoverable areas in Asia, the Americas, and Europe exceed the 30% target of the Kunming-Montreal Global Biodiversity Framework. By linking outcomes to multi-scale physical contexts, our results provide a framework for prioritizing restoration and advancing global biodiversity and climate goals.

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Data availability

The primary datasets generated in this study have been deposited in the Figshare database under [https://doi.org/10.6084/m9.figshare.31143697]75. The tidal wetland restoration site data used in this study are available in the OMReg, NOAA Restoration Atlas [https://www.fisheries.noaa.gov/resource/map/restoration-atlas], and ACRN databases. The Landsat imagery used in this study is available in the U.S. Geological Survey database [http://earthexplorer.usgs.gov] and the Google Earth Engine database [https://earthengine.google.com]. The high-resolution historical imagery used in this study is available in Google Earth. The surface total suspended matter (TSM) data used in this study are available in the GlobColour archive database [http://hermes.acri.fr/]. The elevation data for European sites used in this study are available in the Flanders mapping portal for Belgium [https://www.vlaanderen.be/], the IGN portal for France [https://geoservices.ign.fr/], the BKG metadata portal for Germany [https://mis.bkg.bund.de/], the CNIG download portal for Spain [https://centrodedescargas.cnig.es/], the UK Environment Agency database via [https://data.gov.uk] for the UK, and the Google Earth Engine database under the catalog AHN Netherlands 0.5 m DEM for the Netherlands [https://developers.google.com/earth-engine/datasets/catalog/AHN_AHN2_05M_INT]. The elevation data for sites in the Americas used in this study are available in the Google Earth Engine database under the catalogs Canadian Digital Elevation Model for Canada [https://developers.google.com/earth-engine/datasets/catalog/NRCan_CDEM] and USGS 3DEP 1 m National Map for the United States [https://developers.google.com/earth-engine/datasets/catalog/USGS_3DEP_1m]. The elevation data for Australian sites used in this study are available in the Google Earth Engine database under the catalog Australian 5 M DEM https://developers.google.com/earth-engine/datasets/catalog/AU_GA_AUSTRALIA_5M_DEM. The local tidal data used in this study are available in the Reeds Nautical Almanac 202076, and in the NOAA Tides & Currents [https://tidesandcurrents.noaa.gov/], Fisheries and Oceans Canada [https://tides.gc.ca/en], and Australian Hydrographic Office [https://www.hydro.gov.au/prodserv/publications/ahp11.htm] databases. The global tidal wetland loss data used in this study are available in the Global Tidal Wetland Change Dataset database [https://developers.google.com/earth-engine/datasets/catalog/JCU_Murray_GIC_global_tidal_wetland_change_2019]. The TPXO tidal model data used to derive the global tidal range in this study are available at [https://www.tpxo.net/home]. The global wetland elevation data used in this study are available in the DeltaDTM v1.1 database under accession code 10.4121/21997565.v4 [https://doi.org/10.4121/21997565.v4]. The coastline base maps used in the figures are available from Natural Earth [https://www.naturalearthdata.com/].

Code availability

The custom code used to analyze the data in this study has been deposited in the Figshare database [https://doi.org/10.6084/m9.figshare.31143697].

References

  1. Costanza, R. et al. Changes in the global value of ecosystem services. Glob. Environ. Change 26, 152–158 (2014).

    Google Scholar 

  2. Mcleod, E. et al. A blueprint for blue carbon: toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2. Front. Ecol. Environ. 9, 552–560 (2011).

    Google Scholar 

  3. Murray, N. J. et al. High-resolution mapping of losses and gains of Earth’s tidal wetlands. Science 376, 744–749 (2022).

    Google Scholar 

  4. Barbier, E. B. et al. Coastal ecosystem-based management with nonlinear ecological functions and values. Science 319, 321–323 (2008).

    Google Scholar 

  5. Cohen-Shacham, E., Walters, G., Janzen, C. & Maginnis, S. Nature-Based Solutions to Address Global Societal Challenges (IUCN, 2016).

  6. Fargione, J. E. et al. Natural climate solutions for the United States. Sci. Adv. 4, eaat1869 (2018).

    Google Scholar 

  7. Temmerman, S. et al. Ecosystem-based coastal defence in the face of global change. Nature 504, 79–83 (2013).

    Google Scholar 

  8. Bayraktarov, E. et al. The cost and feasibility of marine coastal restoration. Ecol. Appl. 26, 1055–1074 (2016).

    Google Scholar 

  9. Liu, Z., Fagherazzi, S. & Cui, B. Success of coastal wetlands restoration is driven by sediment availability. Commun. Earth Environ. 2, 44 (2021).

    Google Scholar 

  10. Seddon, N. et al. Global recognition of the importance of nature-based solutions to the impacts of climate change. Glob. Sustain. 3, e15 (2020).

    Google Scholar 

  11. Esteves L. S. What is managed realignment? in Managed realignment: A viable long-term coastal management strategy? (Springer, 2014).

  12. Macreadie, P. I. et al. The future of Blue Carbon science. Nat. Commun. 10, 3998 (2019).

    Google Scholar 

  13. ABPmer. OMReg – A database of completed coastal habitat creation schemes and other adaptation projects. https://www.omreg.net/ (2026).

  14. Australasian Coastal Restoration Network (ACRN). Database for Marine and Coastal Restoration Projects in Australia and New Zealand. https://www.acrn.org.au/ (2026).

  15. National Oceanic and Atmospheric Administration (NOAA). Restoration Atlas for the United States. https://www.fisheries.noaa.gov/resource/map/restoration-atlas/ (2026).

  16. Wolters, M., Garbutt, A. & Bakker, J. P. Salt-marsh restoration: evaluating the success of de-embankments in north-west Europe. Biol. Conserv. 123, 249–268 (2005).

    Google Scholar 

  17. Liu, Z. et al. A global meta-analysis on the drivers of salt marsh planting success and implications for ecosystem services. Nat. Commun. 15, 3643 (2024).

    Google Scholar 

  18. Grandjean, T. J. et al. Critical turbidity thresholds for maintenance of estuarine tidal flats worldwide. Nat. Geosci. 17, 539–544 (2024).

    Google Scholar 

  19. Kirwan M. L., Guntenspergen G. R. Influence of tidal range on the stability of coastal marshland. J. Geophys. Res. Earth Surface 115, 0 (2010).

  20. Ladd, C. J., Duggan-Edwards, M. F., Bouma, T. J., Pagès, J. F. & Skov, M. W. Sediment supply explains long-term and large-scale patterns in salt marsh lateral expansion and erosion. Geophys. Res. Lett. 46, 11178–11187 (2019).

    Google Scholar 

  21. Belliard, J. P., Gourgue, O., Govers, G., Kirwan, M. L. & Temmerman, S. Coastal wetland adaptability to sea level rise: the neglected role of semi-diurnal vs. diurnal tides. Limnol. Oceanogr. Lett. 8, 340–349 (2023).

    Google Scholar 

  22. Turner, R. K., Burgess, D., Hadley, D., Coombes, E. & Jackson, N. A cost–benefit appraisal of coastal managed realignment policy. Glob. Environ. Change 17, 397–407 (2007).

    Google Scholar 

  23. Bilkovic, D. et al. Nursery habitat use by juvenile blue crabs in created and natural fringing marshes. Ecol. Eng. 170, 106333 (2021).

    Google Scholar 

  24. Guthrie, A. G. et al. Ecological equivalency of living shorelines and natural marshes for fish and crustacean communities. Ecol. Eng. 176, 106511 (2022).

    Google Scholar 

  25. Hagger, V., Waltham, N. J. & Lovelock, C. E. Opportunities for coastal wetland restoration for blue carbon with co-benefits for biodiversity, coastal fisheries, and water quality. Ecosyst. Serv. 55, 101423 (2022).

    Google Scholar 

  26. Möller, I. et al. Wave attenuation over coastal salt marshes under storm surge conditions. Nat. Geosci. 7, 727–731 (2014).

    Google Scholar 

  27. Beck, M. W. et al. The identification, conservation, and management of estuarine and marine nurseries for fish and invertebrates. BioScience 51, 633–641 (2001).

    Google Scholar 

  28. Barbier, E. B. et al. The value of estuarine and coastal ecosystem services. Ecol. Monogr. 81, 169–193 (2011).

    Google Scholar 

  29. Murray, N. J. et al. The global distribution and trajectory of tidal flats. Nature 565, 222–225 (2019).

    Google Scholar 

  30. Schuerch, M. et al. Future response of global coastal wetlands to sea-level rise. Nature 561, 231–234 (2018).

    Google Scholar 

  31. Reed D. J. Understanding tidal marsh sedimentation in the Sacramento-San Joaquin delta, California. J. Coastal Res. 36, 605–611 (2002).

  32. Peteet, D. M. et al. Sediment starvation destroys New York City marshes’ resistance to sea level rise. Proc. Natl. Acad. Sci. USA 115, 10281–10286 (2018).

    Google Scholar 

  33. Balke, T., Stock, M., Jensen, K., Bouma, T. J. & Kleyer, M. A global analysis of the seaward salt marsh extent: the importance of tidal range. Water Resour. Res. 52, 3775–3786 (2016).

    Google Scholar 

  34. Van Belzen, J. et al. Vegetation recovery in tidal marshes reveals critical slowing down under increased inundation. Nat. Commun. 8, 15811 (2017).

    Google Scholar 

  35. Ma, S. et al. Hydrological control of threshold transitions in vegetation over early-period wetland development. J. Hydrol. 610, 127931 (2022).

    Google Scholar 

  36. Temmerman, S. et al. Vegetation causes channel erosion in a tidal landscape. Geology 35, 631–634 (2007).

    Google Scholar 

  37. Morzaria-Luna, L., Callaway, J., Sullivan, G. & Zedler, J. Relationship between topographic heterogeneity and vegetation patterns in a Californian salt marsh. J. Veg. Sci. 15, 523–530 (2004).

    Google Scholar 

  38. O’Brien, E. L. & Zedler, J. B. Accelerating the restoration of vegetation in a southern California salt marsh. Wetl. Ecol. Manag. 14, 269–286 (2006).

    Google Scholar 

  39. Flores-Verdugo, F., Zebadua-Penagos, F. & Flores-de-Santiago, F. Assessing the influence of artificially constructed channels in the growth of afforested black mangrove (Avicennia germinans) within an arid coastal region. J. Environ. Manag. 160, 113–120 (2015).

    Google Scholar 

  40. Fivash, G. S. et al. Early indicators of tidal ecosystem shifts in estuaries. Nat. Commun. 14, 1911 (2023).

    Google Scholar 

  41. Mossman, H. L., Davy, A. J., Grant, A. & Elphick, C. Does managed coastal realignment create saltmarshes with ‘equivalent biological characteristics’ to natural reference sites? J. Appl. Ecol. 49, 1446–1456 (2012).

    Google Scholar 

  42. Sanderson, E. W., Ustin, S. L. & Foin, T. C. The influence of tidal channels on the distribution of salt marsh plant species in Petaluma Marsh, CA, USA. Plant Ecol. 146, 29–41 (2000).

    Google Scholar 

  43. Temmerman, S., Govers, G., Meire, P. & Wartel, S. Modelling long-term tidal marsh growth under changing tidal conditions and suspended sediment concentrations, Scheldt estuary, Belgium. Mar. Geol. 193, 151–169 (2003).

    Google Scholar 

  44. Wallace, K. J., Callaway, J. C. & Zedler, J. B. Evolution of tidal creek networks in a high sedimentation environment: a 5-year experiment at Tijuana Estuary, California. Estuaries 28, 795–811 (2005).

    Google Scholar 

  45. Ganju, N. K. Marshes are the new beaches: integrating sediment transport into restoration planning. Estuaries Coasts 42, 917–926 (2019).

    Google Scholar 

  46. Raposa, K. B. et al. Evaluating thin-layer sediment placement as a tool for enhancing tidal marsh resilience: a coordinated experiment across eight US national estuarine research reserves. Estuaries Coasts 46, 595–615 (2023).

    Google Scholar 

  47. Studds, C. E. et al. Rapid population decline in migratory shorebirds relying on Yellow Sea tidal mudflats as stopover sites. Nat. Commun. 8, 14895 (2017).

    Google Scholar 

  48. Stephenson, P. J., Ntiamoa-Baidu, Y. & Simaika, J. P. The use of traditional and modern tools for monitoring wetlands biodiversity in Africa: challenges and opportunities. Front. Environ. Sci. 8, 61–61 (2020).

    Google Scholar 

  49. Cadier, C., Bayraktarov, E., Piccolo, R. & Adame, M. F. Indicators of coastal wetlands restoration success: a systematic review. Front. Mar. Sci. 7, 600220–600220 (2020).

    Google Scholar 

  50. Chen, Y. et al. Differential sediment trapping abilities of mangrove and saltmarsh vegetation in a subtropical estuary. Geomorphology 318, 270–282 (2018).

    Google Scholar 

  51. Schwarz, C., van Rees, F., Xie, D., Kleinhans, M. G. & van Maanen, B. Salt marshes create more extensive channel networks than mangroves. Nat. Commun. 13, 2017 (2022).

    Google Scholar 

  52. Morris J. T. et al. Mangrove trees outperform saltmarsh grasses in building elevation but collapse rapidly under high rates of sea-level rise. Earth’s Future 11, e2022EF003202 (2023).

  53. Chen, Y., Chen, L., Zhang, Z. & Cai, T. Tidal creeks mediate micro-climate within artificial mangroves at their northmost boundary in China. Ecol. Eng. 192, 106970 (2023).

    Google Scholar 

  54. Fischman, H. S., Crotty, S. M. & Angelini, C. Optimizing coastal restoration with the stress gradient hypothesis. Proc. R. Soc. B 286, 20191978 (2019).

    Google Scholar 

  55. Kirwan, M. L., Temmerman, S., Skeehan, E. E., Guntenspergen, G. R. & Fagherazzi, S. Overestimation of marsh vulnerability to sea level rise. Nat. Clim. Change 6, 253–260 (2016).

    Google Scholar 

  56. Kirwan, M. L. & Megonigal, J. P. Tidal wetland stability in the face of human impacts and sea-level rise. Nature 504, 53–60 (2013).

    Google Scholar 

  57. Kirwan, M. L. et al. Limits on the adaptability of coastal marshes to rising sea level. Geophys. Res. Lett. 37, L23401 (2010).

    Google Scholar 

  58. Kirwan, M. & Temmerman, S. Coastal marsh response to historical and future sea-level acceleration. Quat. Sci. Rev. 28, 1801–1808 (2009).

    Google Scholar 

  59. Giri, C. et al. Status and distribution of mangrove forests of the world using Earth observation satellite data. Glob. Ecol. Biogeogr. 20, 154–159 (2011).

    Google Scholar 

  60. Hamilton, S. E. & Casey, D. Creation of a high spatio-temporal resolution global database of continuous mangrove forest cover for the 21st century (CGMFC-21). Glob. Ecol. Biogeogr. 25, 729–738 (2016).

    Google Scholar 

  61. Friess, D. A. The diversity of mangrove forests and geographical biases in their research. Bull. Mar. Sci. 101, 1063–1082 (2025).

    Google Scholar 

  62. Syvitski, J. P., Vorosmarty, C. J., Kettner, A. J. & Green, P. Impact of humans on the flux of terrestrial sediment to the global coastal ocean. Science 308, 376–380 (2005).

    Google Scholar 

  63. Roy, P. S. et al. Structure and function of south-east Australian Estuaries. Estuar. Coast. Shelf Sci. 53, 351–384 (2001).

    Google Scholar 

  64. Laengner, M. L., Siteur, K. & van der Wal, D. Trends in the seaward extent of saltmarshes across Europe from long-term satellite data. Remote Sens. 11, 1653 (2019).

    Google Scholar 

  65. Laengner, M. L. & van der Wal, D. Satellite-derived trends in inundation frequency reveal the fate of saltmarshes. Front. Mar. Sci. 9, 942719 (2022).

    Google Scholar 

  66. Marani, M. et al. On the drainage density of tidal networks. Water Resources Res. 39, 2 (2003).

  67. Kearney, W. S. & Fagherazzi, S. Salt marsh vegetation promotes efficient tidal channel networks. Nat. Commun. 7, 12287 (2016).

    Google Scholar 

  68. Hadfield, J. D. MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. J. Stat. Softw. 33, 1–22 (2010).

    Google Scholar 

  69. Ogle, K., Liu, Y., Vicca, S. & Bahn, M. A hierarchical, multivariate meta-analysis approach to synthesising global change experiments. N. Phytol. 231, 2382–2394 (2021).

    Google Scholar 

  70. Pronk, M. et al. DeltaDTM: a global coastal digital terrain model. Sci. Data 11, 273 (2024).

    Google Scholar 

  71. Wang, C. et al. Different coastal marsh sites reflect similar topographic conditions under which bare patches and vegetation recovery occur. Earth Surf. Dyn. 9, 71–88 (2021).

    Google Scholar 

  72. Sullivan, M. J. P., Davy, A. J., Grant, A. & Mossman, H. L. Is saltmarsh restoration success constrained by matching natural environments or altered succession? A test using niche models. J. Appl. Ecol. 55, 1207–1217 (2018).

    Google Scholar 

  73. Stralberg, D. et al. Evaluating tidal marsh sustainability in the face of sea-level rise: a hybrid modeling approach applied to San Francisco Bay. PLoS ONE 6, e27388 (2011).

    Google Scholar 

  74. Team RC. R.: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021).

  75. Ren, J. et al. Code and data for: “Hydro-geomorphological drivers across scales shape the trajectory of coastal wetland restoration”. figshare https://doi.org/10.6084/m9.figshare.31143697 (2026).

  76. Perrin, T. & Mark, F. Reeds Nautical Almanac 2020 (Bloomsbury Publishing, 2019).

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 32501413 to J.R. and 32573518 to S.W.), the National Key R&D Program of China (Grant No. 2023YFD2401903 to S.W.), the Natural Science Foundation of Shanghai (Grant Nos. 24ZR1481200 to J.R. and 23ZR1479000 to S.W.), and the Central Public-interest Scientific Institution Basal Research Fund (ECSFR, CAFS; Grant No. 2025YC01 to J.R.).

Author information

Authors and Affiliations

  1. East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai, China

    Junlin Ren 
    (任君临), Sikai Wang 
    (王思凯), Tingting Zhang 
    (张婷婷), Ping Zhuang 
    (庄平) & Feng Zhao 
    (赵峰)

  2. College of Marine Living Resource Sciences and Management, Shanghai Ocean University, Shanghai, China

    Junlin Ren 
    (任君临)

  3. Key Laboratory of East China Sea Fishery Resources Exploitation, Ministry of Agriculture and Rural Affairs, Shanghai, China

    Junlin Ren 
    (任君临), Sikai Wang 
    (王思凯), Tingting Zhang 
    (张婷婷), Ping Zhuang 
    (庄平) & Feng Zhao 
    (赵峰)

  4. Shanghai Engineering Technology Research Center for Fisheries Resource Enhancement and Ecological Restoration in the Yangtze River Estuary, Shanghai, China

    Junlin Ren 
    (任君临), Sikai Wang 
    (王思凯), Tingting Zhang 
    (张婷婷), Ping Zhuang 
    (庄平) & Feng Zhao 
    (赵峰)

  5. School of Life Sciences, Fudan University, Shanghai, China

    Jun Ma 
    (马俊) & Ting Zhang 
    (张婷)

  6. Key Laboratory of Marine Ecological Monitoring and Restoration Technologies, Ministry of Natural Resources, Shanghai, China

    Chuyu Cheng 
    (程楚钰)

  7. East China Sea Ecology Center, Ministry of Natural Resources, Shanghai, China

    Chuyu Cheng 
    (程楚钰)

  8. School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, China

    Kang Zhang 
    (张康)

  9. State Key Laboratory for Vegetation Structure, Function and Construction (VegLab), Ministry of Education Key Laboratory for Earth Surface Processes, and College of Urban and Environmental Sciences, Peking University, Beijing, China

    Changlin Xu 
    (徐长林)

  10. Department of Estuarine and Delta Systems, Royal Netherlands Institute for Sea Research (NIOZ), Yerseke, The Netherlands

    Johan van de Koppel, Daphne van der Wal & Tjeerd J. Bouma

  11. Conservation Ecology Group, Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, The Netherlands

    Johan van de Koppel

  12. Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands

    Daphne van der Wal

  13. Faculty of Geosciences, Department of Physical Geography, Utrecht University, Utrecht, The Netherlands

    Tjeerd J. Bouma

  14. State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou, China

    Fangyan Cheng 
    (成方妍)

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  1. Junlin Ren 
    (任君临)

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  2. Sikai Wang 
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  6. Chuyu Cheng 
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  7. Kang Zhang 
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  8. Changlin Xu 
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  14. Feng Zhao 
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Contributions

All authors contributed intellectual input to this study. J.R. and F.Z. designed the study. J.R. compiled the managed realignment database, conducted the analyses, created the figures, and wrote the first draft of the manuscript. S.W., T.Z. (Tingting), C.C., K.Z. and C.X. contributed to data processing, methodological development, and/or data curation. D.v.d.W., J.v.d.K. and T.J.B. provided conceptual input and domain expertise and contributed to interpretation of results. J.M., T.Z. (Ting), F.C. and P.Z. contributed to the interpretation of findings and critically revised the manuscript for important intellectual content. All authors reviewed, edited, and approved the manuscript.

Corresponding author

Correspondence to
Feng Zhao 
(赵峰).

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Ren, J., Wang, S., Zhang, T. et al. Hydro-geomorphological drivers across scales shape the trajectory of coastal wetland restoration.
Nat Commun (2026). https://doi.org/10.1038/s41467-026-71992-x

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