Rapid monitoring of Ambrosia artemisiifolia in semi-arid regions based on ecological convergence and phylogenetic relationships

Abstract

Rapid monitoring and early elimination are important measures to control the spread of invasive plants. Ambrosia artemisiifolia is a globally distributed harmful invasive weed. The aim of this study was to clarify the invasion habitat preferences of A. artemisiifolia and the interspecific associations or phylogenetic relationships between this and native species in the Yili River Valley of Xinjiang, China. We identified the preferred habitat types of A. artemisiifolia, and investigated the composition and distribution of native species at the early stage of invasion by targeted sampling at 186 sites. By comparing the associations and phylogenetic distance between A. artemisiifolia and native species with those in Xinjiang and worldwide, we assessed the feasibility of using native species as indicators for rapid monitoring of A. artemisiifolia. A. artemisiifolia displayed an obvious invasive preference for semi-arid areas, particularly road margins (27.96%), forest (21.51%), farmland (19.35%), wasteland (12.37%), residential areas (10.75%), and grassland (8.06%). The composition and distribution of native species were similar across habitats, with more than 50% co-occurrence of A. artemisiifolia with Setaria viridis, Poa annua, Arrhenatherum elatius, Artemisia annua, Artemisia vulgaris, Artemisia leucophylla, Cannabis sativa, and Chenopodium album. A. artemisiifolia was more likely to show co-occurrence with closely related species. Overall, 53.85% of the above indicator native species with high co-occurrence were widely distributed in the potential suitable areas for A. artemisiifolia in Xinjiang. Globally, the species with the highest occurrence belonged to the genera Chenopodium (58%), Bromus, Poa, Setaria, and Trifolium (>40%). Therefore, native species with the strong association and phylogenetic distant relationship to A. artemisiifolia can be employed as indicators for rapid and accurate monitoring in semi-arid areas.