Machine learning prediction on wetland succession and the impact of artificial structures from a decade of field data

The artificial structures can influence wetland topology and sediment properties, thereby shaping plant distribution and composition. Macrobenthos composition was correlated with plant cover. Previous studies on the impact of artificial structures on plant distribution are scarce in incorporating time-series data or extended field surveys. In this study, a machine-learning-based species distribution model with decade-long observation was analyzed to investigate the correlation between the shift in the distribution of B. planiculmis, artificial structure-induced elevation changes and the expansion of other plants, as well as their connection to soil properties and crab composition dynamics under plants in Gaomei Wetland. Long short-term memory model (LSTM) with Shapley additive explanations (SHAP) was employed for predicting the distribution of B. planiculmis and explaining feature importance. The results indicated that wetland topology was influenced by both artificial structures and plants. Areas initially colonized by B. planiculmis were replaced by other species. Soil properties showed significant differences among plant patches; however, principal component analysis (PCA) of sediment properties and niche similarity analysis showed that the niche of plants was overlapped. Crab composition was different under different plants. The presence probability of B. planiculmis near woody paths decreased according to LSTM and field survey data. SHAP analysis suggested that the distribution of other plants, historical distribution of B. planiculmis and sediment properties significantly contributed to the presence probability of B. planiculmis. A sharp decrease in SHAP values with increasing NDVI at suitable elevations, overlap in PCA of sediment properties and niche similarity indicated potential competition among plants. This decade-long time-series field survey revealed the joint effects of artificial structure and vegetation on the topology and soil properties dynamics. These changes influenced the plant distribution through potential plant competition. LSTM with SHAP provided valuable insights in the underlying the mechanisms of artificial structure effects on the plant zonation process.