Change detection of wetland vegetation under contrasting water-level scenarios in coastal marshes of eastern Georgian Bay

Context Global climate change has resulted in extreme water-level (WL) fluctuations in Eastern Georgian Bay (EGB) and has affected its high-quality wetlands. Beginning in 1999, EGB experienced 14 years of extremely low water levels (Period 1), followed by 6 years of rapidly increasing water levels starting from 2014 (Period 2). During Period 1, trees and shrubs invaded the high marsh, but with inundation, they died out and transitioned into the novel Dead Tree (DT) Zone (DTZ) during Period 2. Objectives We related long-term changes in wetlands vegetation zonation to different levels of anthropogenic impacts and the Vulnerability Index (VI) scores and wetland sensitivity to WL extremes. Methods We used images acquired in 2002-2003 (IKONOS) and 2019 (KOMPSAT-3 and Pleiades-1A/1B) for four areas (19 wetlands) in EGB with varying anthropogenic impact. We used object-based classification to map land cover in two periods, followed by change detection. We related the percent areal cover of DT in wetlands to corresponding VI scores. Results We obtained > 85% overall and > 70% DT mapping accuracies. Wetlands with the least anthropogenic impact had the smallest DTZ. Percentage areal cover of the DTZ was significantly and positively correlated with wetland VI. Without exception, the amount of meadow marsh in wetlands was significantly reduced in Period 2. Conclusions Wetlands with higher VI scores and anthropogenic impact were associated with greater changes in wetland zonation and conversion into DTZ following extremes in water levels. This study provides important insights into how coastal marshes in EGB are responding to extreme water-level fluctuations induced by climate change.