Identifying driving hydrogeomorphic factors of coastal wetland downgrading using random forest classification models

• Published in: The Science of the total environment 2023-10, Vol.894, p.164995-164995, Article 164995
• Main Authors: He, Keqi, Li, Wenhong, Zhang, Yu, Sun, Ge, McNulty, Steve G., Flanagan, Neal E., Richardson, Curtis J.
• Format: Article
• Language: English
• Subjects: Anthropogenic activities; Climate change; Coastal wetland downgrading; Hydrogeomorphic factors; Machine learning models; Sea-level rise
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2023.164995

Coastal wetlands provide critical ecosystem services but are experiencing disruptions caused by inundation and saltwater intrusion under intensified climate change, sea-level rise, and anthropogenic activities. Recent studies have shown that these disturbances downgraded coastal wetlands mainly through affecting their hydrological processes. However, research on what is the most critical driver for wetland downgrading and how it affects coastal wetlands is still in its infancy. This study examined drivers of three types of wetland downgrading, including woody wetland loss, emergent herbaceous wetland loss, and woody wetlands converting to emergent herbaceous wetlands. By using random forest classification models for the wetland ecosystems in the Alligator River National Wildlife Refuge, North Carolina, USA, during 1995–2019, we determined the relative importance of different hydrogeomorphic processes and the dominant variables in driving the wetland downgrading. Results showed that random forest classification models were accurate (> 97 % overall accuracy) in classifying wetland downgrading. Multiple hydrogeomorphic variables collectively contributed to the coastal wetland downgrading. However, the dominant control factors varied across different types of wetland downgrading. Woody wetlands were most susceptible to saltwater intrusion and were likely to downgrade if the saltwater table was shallower than 0.2 m below the land surface. In contrast, emergent herbaceous wetlands were most vulnerable to inundation and drought. The favorable groundwater table for emergent herbaceous wetlands was between 0.34 m above the land surface and 0.32 m below the land surface, beyond which the emergent herbaceous wetland tended to disappear. For downgraded woody wetlands, their distance to canals/ditches played a crucial role in determining their fates after downgrading. The machine learning approach employed in this study provided critical knowledge about the thresholds of hydrogeomorphic variables for the downgrading of different types of coastal wetlands. Such information can help guide effective and targeted coastal wetland conservation, management, and restoration measures. [Display omitted] •Wetland downgrading was accurately (> 97 %) classified.•Dominant hydrological mechanisms varied for different types of wetland downgrading.•Woody wetlands were most susceptible to saltwater intrusion.•Emergent herbaceous wetlands were most vulnerable to inundation and drought.•D