Diversity patterns, abiotic and biotic drivers, and future dynamics of native invasive plants on the Qinghai-Tibet Plateau - Xiong, Wanyin; Cheng, Tao; Liu, Shijian; Liu, Xin; Ding, Hechun; Yin, Mengdie; Sun, Wenguang; Zhang, Yazhou (Frontiers in Plant Science, 2025)
IntroductionCompared to alien invasive plants, native invasive plants have long been overlooked. As a result, many biodiversity hotspots are threatened by invasions of native species, yet lack sufficient policy attention and management interventions. This study focuses on native invasive plants on the Qinghai-Tibet Plateau (QTP) as a case study, aiming to provide guidance for regional management and offer insights for related research in other areas.MethodsWe compiled a comprehensive dataset of 83 native invasive plants and environmental drivers on the QTP. Using spatial statistics and ensemble modeling, we analyzed invasion patterns and projected future trends.ResultsA distinct northwest-to-southeast richness gradient was found, with the southeast as the primary invasion hotspot. This pattern aligned closely with allelochemical diversity, primarily benzenoids, terpenoids, and flavonoids. Invasion distribution was jointly influenced by allelochemicals, human activities, and climate. Models projected intensification and northwestward expansion of hotspots, increasing risks to protected areas, with invasive hotspot areas expanding by approximately 178.8×104 km2 across scenarios. Moreover, the MaxEnt model demonstrated extremely high predictive accuracy, with the average test AUC for all species reaching 0.9834.DiscussionWe propose targeted management focusing on the southeastern QTP, including allelochemical monitoring via metabolomics and biocontrol using allelopathy-resistant forage grasses and compound-degrading microbes to improve conservation efficiency and adaptability. Our findings unravel the large-scale mechanisms of alpine plant invasions while translating theoretical advances into practical management strategies for this ecologically critical landscape.