Climate change alters the spatial pattern of plant spectral diversity across forest types

Species distribution, spatial distance, and neighboring interact6ions are among the most important drivers of global variation in plant species diversity. However, effects climate change on relationship between interactions diversity remain unknown. Here, we applied 12 machine learning models to assess responses spectral (indicating diversity) forests seven protected forest areas China. Changes 27 climatic variables during two time periods, 1990–2005 2005–2020, were analyzed. The results indicated that intraspecific distance have increased significantly with change. These also provide insights into variations Particularly, contributions plant–plant distances 1990 2000 greater than contribution all types. Our analysis revealed diversity, interactions, closely associated each other sharply shifted under From this perspective, interaction analysis—to a degree community composition—can additional underlying mechanisms changes current global-warming conditions.