Multiple invasion trajectories induce niche dynamics inconsistency and increase risk uncertainty of a plant invader

Abstract

Our knowledge of how niche dynamic patterns respond to invasion trajectories and influence invasion risk prediction is elusive for the majority of notorious invaders, hindering scientific understanding, biosecurity planning and practice, and management implementation of biological invasions. We used Mikania micrantha, one of the world's worst invasive alien species (IAS), to test the hypothesis that multiple invasion trajectories could induce niche dynamics inconsistency and increase risk uncertainty of IAS. We compiled a robust database of M. micrantha occurrence across its native range in Central and South America and invaded range in China. This database was used to clarify different invaded ranges and invasion trajectories of M. micrantha in China. Principal components analysis of climatic variables associated with the database was used to explore the niche dynamic patterns associated with multiple invasion trajectories of M. micrantha. Maximum entropy algorithm was used to predict the high-risk area of M. micrantha invasion using occurrence datasets for invaded ranges where niches remained conservative, and to detect area changes with the inclusion of occurrence datasets for invaded ranges where niche shifts occurred. M. micrantha invasion occurred in three geographically distinct regions, with conservative climate niches in southern and southeastern China and climatic niche shifts in southwestern China. A high-risk area for M. micrantha invasion spanned multiple provinces and cities and expanded considerably with the inclusion of the occurrence dataset for southwestern China. Our findings contribute to the theoretical understanding of invasion mechanisms and the practical optimization of biosecurity planning and implementation.