Trait differences between naturalized and invasive plant species independent of residence time and phylogeny

The ability to predict which alien plants will transition from naturalized to invasive prior to their introduction to novel regions is a key goal for conservation and has the potential to increase the efficacy of weed risk assessment (WRA). However, multiple factors contribute to plant invasion success (e.g., functional traits, range characteristics, residence time, phylogeny), and they all must be taken into account simultaneously in order to identify meaningful correlates of invasion success. We compiled 146 pairs of phylogenetically paired (congeneric) naturalized and invasive plant species in Australia with similar minimum residence times (i.e., time since introduction in years). These pairs were used to test for differences in 5 functional traits (flowering duration, leaf size, maximum height, specific leaf area SLA], seed mass) and 3 characteristics of species’ native ranges (biome occupancy, mean annual temperature, and rainfall breadth) between naturalized and invasive species. Invasive species, on average, had larger SLA, longer flowering periods, and were taller than their congeneric naturalized relatives. Invaders also exhibited greater tolerance for different environmental conditions in the native range, where they occupied more biomes and a wider breadth of rainfall and temperature conditions than naturalized congeners. However, neither seed mass nor leaf size differed between pairs of naturalized and invasive species. A key finding was the role of SLA in distinguishing between naturalized and invasive pairs. Species with high SLA values were typically associated with faster growth rates, more rapid turnover of leaf material, and shorter lifespans than those species with low SLA. This suite of characteristics may contribute to the ability of a species to transition from naturalized to invasive across a wide range of environmental contexts and disturbance regimes. Our findings will help in the refinement of WRA protocols, and we advocate the inclusion of quantitative traits, in particular SLA, into the WRA schemes.