AUTHOR=Jia Xin , Yang Juan , Wang Chen , Liu Baolin , Zheng HouYi , Zou Yu , Wang Heng , Zhao Huan 

TITLE=Predicting the regime shift of coastal wetlands based on the bistability features in the intertidal zone: A case study in the Liaohe estuary

JOURNAL=Frontiers in Marine Science

VOLUME=Volume 10 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2023.1126682

DOI=10.3389/fmars.2023.1126682

ISSN=2296-7745

ABSTRACT=Influenced by human activities and natural interference, the worldwide distribution of coastal wetlands is now undergoing rapid evolution. The prediction on the locations of vegetation conversion is greatly important for the management of these coastal ecosystems in terms of early warning. In this paper, a series of waterlines extracted from multiple satellite images were used to generate a high-precision digital elevation model (DEM) in the intertidal zone of the Liaohe estuary. Based on the characteristics of the alternative stable state in elevation and normalized difference vegetation index (NDVI), the Logistic model was used to predict the potential locations of vegetation expansion by combining geomorphic factors, such as elevation, slope, and annual changing rate of elevation as explanatory variables. The results were as follows. (1) There are two stable states existing in the study area, i.e., low-lying tidal flats and high-lying salt marshes. When the geomorphic parameters exceeded the thresholds, the stable state transition would occur. (2) The elevation is the best explainer in the single-factor simulation by using the Logistic model, while the slope is the worst. When multiple factors simulations were conducted, the prediction with the elevation, slope, and annual elevation change rate was the best, with R2 =0.739, and the overall accuracy of prediction reached 88.6%. The Logistic model was suitable for predicting the evolution of coastal wetlands controlled by geomorphic factors. The practice attempts in more types of estuaries will be necessary to evaluate the reliability of the Logistic Model in prediction vegetation conversion.