Adame, M. F. et al. All tidal wetlands are blue carbon ecosystems. BioScience 74, 253–268 (2024).

Article 

Google Scholar
 

Donato, D. C. et al. Mangroves among the most carbon-rich forests in the tropics. Nat. Geosci. 4, 293–297 (2011).

Article 
CAS 

Google Scholar
 

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

Article 

Google Scholar
 

O’Donnell, K. L. et al. Saltwater intrusion and sea level rise threatens US rural coastal landscapes and communities. Anthropocene 45, 100427 (2024).

Article 

Google Scholar
 

Choat, B. et al. Global convergence in the vulnerability of forests to drought. Nature 491, 752–755 (2012).

Article 
CAS 

Google Scholar
 

Chambers, J. Q. et al. Hurricane Katrina’s carbon footprint on US Gulf Coast forests. Science 318, 1107–1107 (2007).

Article 
CAS 

Google Scholar
 

Kirwan, M. L. & Gedan, K. B. Sea-level driven land conversion and the formation of ghost forests. Nat. Clim. Change 9, 450–457 (2019).

Article 

Google Scholar
 

McDowell, N. et al. Processes and mechanisms of coastal woody-plant mortality. Glob. Change Biol. 28, 5881–5900 (2022).

Article 
CAS 

Google Scholar
 

Ury, E. A., Yang, X., Wright, J. P. & Bernhardt, E. S. Rapid deforestation of a coastal landscape driven by sea-level rise and extreme events. Ecol. Appl. 31, e02339 (2021).

Article 

Google Scholar
 

White, E., Ury, E. A., Bernhardt, E. S. & Yang, X. Climate change driving widespread loss of coastal forested wetlands throughout the North American coastal plain. Ecosystems 25, 812–827 (2022).

Article 

Google Scholar
 

Williams, K., MacDonald, M. & Sternberg, L. daS. L. Interactions of storm, drought, and sea-level rise on coastal forest: a case study. J. Coast. Res. 19, 1116–1121 (2003).


Google Scholar
 

Conner, W. H. Ecology of Tidal Freshwater Forested Wetlands of the Southeastern United States (Springer, 2007).

Book 

Google Scholar
 

Powell, E. et al. Spaceborne lidar observations reveal impacts of inundation on coastal forest structure across the US mid-Atlantic. Estuar. Coast. Shelf Sci. 323, 109372 (2025).

Article 

Google Scholar
 

Smart, L. S. et al. Aboveground carbon loss associated with the spread of ghost forests as sea levels rise. Environ. Res. Lett. 15, 104028 (2020).

Article 
CAS 

Google Scholar
 

Smith, A. J. & Kirwan, M. L. Sea level-driven marsh migration results in rapid net loss of carbon. Geophys. Res. Lett. 48, e2021GL092420 (2021).

Article 
CAS 

Google Scholar
 

Carmichael, M. J., Helton, A. M., White, J. C. & Smith, W. K. Standing dead trees are a conduit for the atmospheric flux of CH4 and CO2 from wetlands. Wetlands 38, 133–143 (2018).

Article 

Google Scholar
 

Martinez, M. & Ardón, M. Drivers of greenhouse gas emissions from standing dead trees in ghost forests. Biogeochemistry 154, 471–488 (2021).

Article 
CAS 

Google Scholar
 

Williams, K., Ewel, K. C., Stumpf, R. P., Putz, F. E. & Workman, T. W. Sea-level rise and coastal forest retreat on the west coast of Florida, USA. Ecology 80, 2045–2063 (1999).

Article 

Google Scholar
 

Smith, I., Fiorino, G., Grabas, G. & Wilcox, D. A. Wetland vegetation response to record-high Lake Ontario water levels. J. Gt Lakes Res. 47, 160–167 (2021).

Article 

Google Scholar
 

Tully, K. et al. The invisible flood: the chemistry, ecology, and social implications of coastal saltwater intrusion. BioScience 69, 368–378 (2019).

Article 

Google Scholar
 

Bhattachan, A. et al. Evaluating the effects of land-use change and future climate change on vulnerability of coastal landscapes to saltwater intrusion. Elem. Sci. Anthr. 6, 62 (2018).

Article 

Google Scholar
 

Sallenger, A. H., Doran, K. S. & Howd, P. A. Hotspot of accelerated sea-level rise on the Atlantic coast of North America. Nat. Clim. Change 2, 884–888 (2012).

Article 

Google Scholar
 

Velasquez-Manoff, M. As sea levels rise, so do ghost forests. The New York Times (8 October 2019).

Zee, G., Griswold, L., Manzo, D. & Pereira, I. ‘Ghost forests’ threaten New Jersey’s water, ecosystem. ABC News (29 November 2023).

Cheng, Y. et al. Scattered tree death contributes to substantial forest loss in California. Nat. Commun. 15, 641 (2024).

Article 
CAS 

Google Scholar
 

Dixon, D. J., Zhu, Y., Brown, C. F. & Jin, Y. Satellite detection of canopy-scale tree mortality and survival from California wildfires with spatio-temporal deep learning. Remote Sens. Environ. 298, 113842 (2023).

Article 

Google Scholar
 

Field, C. R., Gjerdrum, C. & Elphick, C. S. Forest resistance to sea-level rise prevents landward migration of tidal marsh. Biol. Conserv. 201, 363–369 (2016).

Article 

Google Scholar
 

Pasquarella, V. J., Elkinton, J. S. & Bradley, B. A. Extensive gypsy moth defoliation in Southern New England characterized using Landsat satellite observations. Biol. Invasions 20, 3047–3053 (2018).

Article 

Google Scholar
 

Bernhardt, E. Coastal freshwater wetlands squeezed between migrating salt marshes and working lands. Sci. Adv. 8, eadd1628 (2022).

Article 

Google Scholar
 

Chen, Y. & Kirwan, M. L. Upland forest retreat lags behind sea-level rise in the mid-Atlantic coast. Glob. Change Biol. 30, e17081 (2024).

Article 

Google Scholar
 

Tully, K. L., Weissman, D., Wyner, W. J., Miller, J. & Jordan, T. Soils in transition: saltwater intrusion alters soil chemistry in agricultural fields. Biogeochemistry 142, 339–356 (2019).

Article 
CAS 

Google Scholar
 

Ury, E. A., Wright, J. P., Ardón, M. & Bernhardt, E. S. Saltwater intrusion in context: soil factors regulate impacts of salinity on soil carbon cycling. Biogeochemistry 157, 215–226 (2022).

Article 
CAS 

Google Scholar
 

Ardón, M., Morse, J. L., Colman, B. P. & Bernhardt, E. S. Drought-induced saltwater incursion leads to increased wetland nitrogen export. Glob. Change Biol. 19, 2976–2985 (2013).

Article 

Google Scholar
 

Kirwan, M. L. et al. Feedbacks regulating the salinization of coastal landscapes. Annu. Rev. Mar. Sci. 17, 461–484 (2025).

Article 

Google Scholar
 

Helton, A. M. et al. Over, under, and through: hydrologic connectivity and the future of coastal landscape salinization. Water Resour. Res. 61, e2024WR038720 (2025).

Article 

Google Scholar
 

Ohenhen, L. O., Shirzaei, M., Ojha, C., Sherpa, S. F. & Nicholls, R. J. Disappearing cities on US coasts. Nature 627, 108–115 (2024).

Article 
CAS 

Google Scholar
 

Osland, M. J. et al. Migration and transformation of coastal wetlands in response to rising seas. Sci. Adv. 8, eabo5174 (2022).

Article 

Google Scholar
 

Maxwell, T. L. et al. Soil carbon in the world’s tidal marshes. Nat. Commun. 15, 10265 (2024).

Aakala, T., Kuuluvainen, T., Gauthier, S. & De Grandpré, L. Standing dead trees and their decay-class dynamics in the northeastern boreal old-growth forests of Quebec. Ecol. Manag. 255, 410–420 (2008).

Article 

Google Scholar
 

Kearney, W. S., Fernandes, A. & Fagherazzi, S. Sea-level rise and storm surges structure coastal forests into persistence and regeneration niches. PLoS ONE 14, e0215977 (2019).

Article 

Google Scholar
 

McDowell, N. et al. Pervasive shifts in forest dynamics in a changing world. Science 368, eaaz9463 (2020).

Article 
CAS 

Google Scholar
 

Lagomasino, D. et al. Storm surge and ponding explain mangrove dieback in southwest Florida following Hurricane Irma. Nat. Commun. 12, 4003 (2021).

Article 
CAS 

Google Scholar
 

White, E. & Kaplan, D. Restore or retreat? Saltwater intrusion and water management in coastal wetlands. Ecosyst. Health Sustain. 3, e01258 (2017).

Article 

Google Scholar
 

Fagherazzi, S. et al. The ecohydrology of coastal ghost forests. Ecohydrology 18, e70020 (2025).

Article 

Google Scholar
 

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

Article 
CAS 

Google Scholar
 

Neville, J. A., Emanuel, R. E., Ardón, M. & Pavelsky, T. Location and design of flow control structures differentially influence salinity patterns in small artificial drainage systems. J. Water Resour. Plan. Manag. 149, 05023002 (2023).

Article 

Google Scholar
 

van Zelst, V. T. M. et al. Cutting the costs of coastal protection by integrating vegetation in flood defences. Nat. Commun. 12, 6533 (2021).

Article 

Google Scholar
 

Fagherazzi, S. et al. Sea level rise and the dynamics of the marsh-upland boundary. Front. Environ. Sci. 7, 25 (2019).

Article 

Google Scholar
 

Du, L. et al. Drainage ditch network extraction from lidar data using deep convolutional neural networks in a low relief landscape. J. Hydrol. 628, 130591 (2024).

Article 

Google Scholar
 

Storm surge overview. NOAA https://www.weather.gov/phi/stormsurge (2025).

National Agriculture Imagery Program (NAIP). USDA Farm Production and Conservation Business Center https://naip-usdaonline.hub.arcgis.com/ (2024).

Brandt, M. et al. An unexpectedly large count of trees in the West African Sahara and Sahel. Nature 587, 78–82 (2020).

Article 

Google Scholar
 

Gu, J. et al. Recent advances in convolutional neural networks. Pattern Recognit. 77, 354–377 (2018).

Article 

Google Scholar
 

Kattenborn, T., Leitloff, J., Schiefer, F. & Hinz, S. Review on convolutional neural networks (CNN) in vegetation remote sensing. ISPRS J. Photogramm. Remote Sens. 173, 24–49 (2021).

Article 

Google Scholar
 

Ouali, Y., Hudelot, C. & Tami, M. An overview of deep semi-supervised learning. Preprint at https://arxiv.org/abs/2006.05278 (2020).

Ronneberger, O., Fischer, P. & Brox, T. U-Net: convolutional networks for biomedical image segmentation. In International Conference on Medical Image Computing and Computer-Assisted Intervention (eds Navab, N. et al.) 234–241 (Springer, 2015).

Tan, M. & Le, Q. V. EfficientNet: rethinking model scaling for convolutional neural networks. In International Conference on Machine Learning 6105–6114 (ICML, 2019).

Deng, J. et al. ImageNet: a large-scale hierarchical image database. In 2009 IEEE Conference on Computer Vision and Pattern Recognition 248–255 (IEEE, 2009).

Abraham, N. & Khan, N. M. A novel focal tversky loss function with improved attention U-Net for lesion segmentation. In 2019 IEEE 16th International Symposium on Biomedical Imaging 683–687 (IEEE, 2019).

Detection surveys. US Forest Service https://www.fs.usda.gov/science-technology/data-tools-products/fhp-mapping-reporting/detection-surveys (2021).

3D Elevation Program. US Geological Survey https://www.usgs.gov/3d-elevation-program (2024).

NOAA Shoreline. NOAA https://shoreline.noaa.gov/med-res.html (2024).

Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).

Article 
CAS 

Google Scholar
 

Coastal Change Analysis Program (C-CAP) regional land cover. NOAA Office for Coastal Management https://coast.noaa.gov/digitalcoast/data/ccapregional.html (2024).

Protected Areas Database of the United States (PAD-US). USGS https://doi.org/10.5066/P96WBCHS (2024).

Ord, J. K. & Getis, A. Local spatial autocorrelation statistics: distributional issues and an application. Geogr. Anal. 27, 286–306 (1995).

Article 

Google Scholar
 

Caldas de Castro, M. & Singer, B. H. Controlling the false discovery rate: a new application to account for multiple and dependent tests in local statistics of spatial association. Geogr. Anal. 38, 180–208 (2006).

Article 

Google Scholar
 

Breiman, L. Random forest. Mach. Learn. 45, 5–32 (2001).

Article 

Google Scholar
 

Hoeppner, S. S., Shaffer, G. P. & Perkins, T. E. Through droughts and hurricanes: tree mortality, forest structure, and biomass production in a coastal swamp targeted for restoration in the Mississippi River Deltaic Plain. For. Ecol. Manag. 256, 937–948 (2008).

Article 

Google Scholar
 

Dormann, C. F. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46 (2013).

Article 

Google Scholar
 

Zhu, M. et al. Class weights random forest algorithm for processing class imbalanced medical data. IEEE Access 6, 4641–4652 (2018).

Article 

Google Scholar
 

Nembrini, S., König, I. R. & Wright, M. N. The revival of the Gini importance?. Bioinformatics 34, 3711–3718 (2018).

Article 
CAS 

Google Scholar
 

Greenwell, B. M. pdp: an R package for constructing partial dependence plots. R. J. 9, 421 (2017).

Article 

Google Scholar
 

National hydrography dataset. US Geological Survey https://www.usgs.gov/national-hydrography/national-hydrography-dataset (2024).

TIGER/Line Shapefiles. US Census Bureau https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html (2024).

National levee database. US Army Corps of Engineers https://levees.sec.usace.army.mil/ (2024).

Ho, D. E., Imai, K., King, G. & Stuart, E. A. MatchIt: nonparametric preprocessing for parametric causal inference. J. Stat. Softw. 42, 1–28 (2011).

Article 

Google Scholar
 

Yeung, H. C. H. et al. Overlooked and extensive ghost forest formation across the US Atlantic coast–data. Zenodo https://doi.org/10.5281/zenodo.16380867 (2025).

Individual tree species parameter maps. US Forest Service https://www.fs.usda.gov/science-technology/data-tools-products/fhp-mapping-reporting/individual-tree-species-parameter-maps (2022).