Human introduction of species around the world is not exhaustive. Comparing characteristics of non-native species that have been introduced with characteristics of non-native species that could be introduced can reveal biases in which species were introduced in the past, and can highlight future threats. We test for introduction biases in non-native trees introduced to Australia using a dataset of 57,958 tree species known globally. We found that: (1) non-native species were selectively introduced, and do not form a random subset of all non-native species, though (2) they do represent the functional trait-space occupied by tree species globally; (3) trees naturalised in numerous countries and introduced for more uses are more likely to be introduced in Australia; and (4) introduction debt can indicate characteristics of potential future non-native introductions. For Australia, tree species from the tropics and global south pose an especially high future invasion risk.

The enemy release hypothesis (ERH) is the best-known hypothesis explaining high performance (e.g., rapid population growth) of exotic species. However, the current framing of the ERH does not explicitly link evidence of enemy release with exotic performance. This leads to uncertainty regarding the role of enemy release in biological invasions. Here we demonstrate that the effect of enemy release on exotic performance is the product of three factors: enemy impact, enemy diversity, and host adaptation. These factors are modulated by seven contexts: time since introduction, resource availability, phylogenetic relatedness of exotic and native species, host-enemy asynchronicity, number of introduction events, type of enemy, and strength of growth-defence trade-offs. ERH-focused studies frequently test different factors under different contexts, leading to inconsistent findings, which characterise current evidence for the ERH. For example, over 80% of meta-analyses fail to consider ecological contexts that can modulate study findings; we demonstrate this by re-analysing a recent ERH synthesis. Structuring the ERH around factors and contexts promotes generalisable predictions about when and where exotic species may benefit from enemy release, empowering effective management. Our mechanistic factor-context framework clearly lays out the evidence required to support the ERH, unifies many enemy-related invasion hypotheses and enhances predictive capacity.

Context dependence impedes accurate prediction in ecology, including the extent and impact of invasion. Using a grassland experiment, we show that the interplay of limiting factors can explain why invasion trends vary with circumstance. By manipulating invader seed dose and physical disturbance and tracking cover of groups of fast and slow invaders in three communities over three years, we examined how seed-, resource- and growth rate-limitation affected the abundance and diversity impacts of invading plants. Evidence indicated that seeds primarily limited cover of resource-acquisitive fast invaders in early and mid successional communities, growth rate limited resource conservative slow invaders in early and mid succession, and resources limited invasion of both groups in late succession. Resident community diversity declined as invader cover increased, consistent with effects of resource limitation. A greater focus on limiting factors in invasion ecology will provide us with a structure for predicting invasion outcomes in different situations.

Phenotypic plasticity can mask population genetic differentiation, reducing the predictability of trait-environment relationships. In short-lived plants, reproductive traits may be more genetically determined due to their direct impact on fitness, whereas vegetative traits may show higher plasticity to buffer short-term perturbations. Combining a multi-treatment greenhouse experiment with global field observations for the short-lived Plantago lanceolata, we 1) disentangled the genetic and plastic responses of functional traits to a set of environmental drivers and 2) assessed the utility of trait-environment relationshisps inferred from observational data for predicting genetic differentiation. Reproductive traits showed distinct genetic differentiation that was highly predictable from observational data, but only when correcting traits for differences in their (labile) biomass component. Vegetative traits showed higher plasticity and contrasting genetic and plastic responses, leading to unpredictable trait patterns. Our study suggests that genetic differentiation may be inferred from observational data only for the traits most closely related with fitness.