Spatio-Temporal Dynamics of Invasive Spartina Alterniflora and Its Functional Traits' Responding to Hydro-Meteorology

Coastal wetlands represent one of the most critical ecosystem types worldwide, and offer a diverse array of vital ecosystem services. Large-scale and rapid invasion of Spartina alterniflora (S. alterniflora) has imposed significant impacts on coastal wetland ecosystems and biodiversity globally. Tracking dynamic trajectories of S. alterniflora and the rhythmic changes of its vegetation functional traits is important to understand the invasion mechanism. This study proposed a novel time series adaptive threshold segmentation method (NSATS) to extract S. alterniflora. Specifically, for the San Francisco Bay (SFB) of the U.S., the extraction was carried out from 1995 to 2004, while for three representative bays along the coastal zone of China, the extraction was conducted from 2011 to 2020, respectively, and to explore their spatio-temporal distribution patterns. We developed an innovative CCD-HCM method to track the historical growth trajectories of S. alterniflora, and evaluated their growth dynamics. Finally, we explored the phenological rhythm of S. alterniflora functional traits, and clarified the response mechanisms of its vegetation functional traits to hydro-meteorological factors. NSATS showed high accuracy (0.82–0.96) in identifying S. alterniflora. Its invasion was faster in China's bays, with rapid expansion in 2011–2020, especially in YRD. SFB remained stable, with minor changes. Functional traits showed earlier SOS and longer LOS with latitude decrease. Air and water temperatures influence S. alterniflora traits differently across bays. These findings aid in monitoring and controlling its invasion.