Abstract
A major aim in invasion biology is identifying traits distinguishing alien invasive and alien non-invasive plants. Surprisingly, this approach has been, so far, poorly used to understand why some arable weeds are abundant and widespread while others are rare and narrowly distributed. In the present study, we focused on the characteristics of successful weeds occurring in maize fields, one of the most important crops worldwide. Two national weed surveys conducted in France were used to identify increasing and decreasing species based on 175 and 484 surveyed fields in the 1970s and the 2000s, respectively. Weed trait values related to regional frequency, local abundance, and specialization to maize were identified with phylogenetic generalized least-squares (PGLS). We found a positive relationship between regional frequency and local abundance, i.e., the most widespread weeds were also locally more abundant. We highlighted that weeds with the C4 photosynthetic pathway and summer emergence were more abundant, more frequent, and more specialized to maize crops. More generally, we highlighted two successful strategies: On the one hand, traits related to a general weediness syndrome with rapid resource acquisition (high SLA and Ellenberg-N) and high colonization capacity (seed longevity, fecundity, and wind dispersal); on the other hand, traits related to specific adaptation to spring cultivation (thermophilous species with summer emergence, late flowering, and C4 photosynthetic pathway). Deviations from the abundancy–frequency relationships also indicated that species of the Panicoideae sub-family, species with Triazine-resistant populations, and neophyte species were more abundant than expected by their regional frequency. To some extent, it is therefore possible to predict which species can be troublesome in maize crops and use this information in weed risk assessment tools to prevent new introductions or favor early detection and eradication. This study showed how tools developed in functional and macro-ecology can be used to improve our understanding of weed ecology and to develop more preventive management strategies