Background and aims: Since its emergence in the mid‐20th century, invasion biology has matured into a productive research field addressing questions of fundamental and applied importance. Not only has the number of empirical studies increased through time, but also has the number of competing, overlapping and, in some cases, contradictory hypotheses about biological invasions. To make these contradictions and redundancies explicit, and to gain insight into the field’s current theoretical structure, we developed and applied a Delphi approach to create a consensus network of 39 existing invasion hypotheses.Results: The resulting network was analysed with a link‐clustering algorithm that revealed five concept clusters (resource availability, biotic interaction, propagule, trait and Darwin’s clusters) representing complementary areas in the theory of invasion biology. The network also displays hypotheses that link two or more clusters, called connecting hypotheses, which are important in determining network structure. The network indicates hypotheses that are logically linked either positively (77 connections of support) or negatively (that is, they contradict each other; 6 connections).Significance: The network visually synthesizes how invasion biology’s predominant hypotheses are conceptually related to each other, and thus, reveals an emergent structure – a conceptual map – that can serve as a navigation tool for scholars, practitioners and students, both inside and outside of the field of invasion biology, and guide the development of a more coherent foundation of theory. Additionally, the outlined approach can be more widely applied to create a conceptual map for the larger fields of ecology and biogeography.

Our ability to predict invasions has been hindered by the seemingly idiosyncratic context-dependency of individual invasions. However, we argue that robust and useful generalisations in invasion science can be made by considering “invasion syndromes” which we define as “a combination of pathways, alien species traits, and characteristics of the recipient ecosystem which collectively result in predictable dynamics and impacts, and that can be managed effectively using specific policy and management actions”. We describe this approach and outline examples that highlight its utility, including: cacti with clonal fragmentation in arid ecosystems; small aquatic organisms introduced through ballast water in harbours; large ranid frogs with frequent secondary transfers; piscivorous freshwater fishes in connected aquatic ecosystems; plant invasions in high-elevation areas; tall-statured grasses; and tree-feeding insects in forests with suitable hosts. We propose a systematic method for identifying and delimiting invasion syndromes. We argue that invasion syndromes can account for the context-dependency of biological invasions while incorporating insights from comparative studies. Adopting this approach will help to structure thinking, identify transferrable risk assessment and management lessons, and highlight similarities among events that were previously considered disparate invasion phenomena.

Although uncertainty is an integral part of any science, it raises doubts in public perception about scientific evidence, is exploited by denialists, and therefore potentially hinders the implementation of management actions. As a relatively young field of study, invasion science contains many uncertainties. This may explain why, despite international policies aimed at mitigating biological invasions, the implementation of national‐ and regional‐scale measures to prevent or control alien species has done little to slow the increase in extent of invasions and the magnitude of impacts. Uncertainty is therefore a critical aspect of invasion science that should be addressed to enable the field to progress further. To improve how uncertainties in invasion science are captured and characterized, we propose a framework, which is also applicable to other applied research fields such as climate and conservation science, divided into four components: the need (1) to clearlycircumscribethe phenomenon, (2) to measure and provide evidence for the phenomenon (i.e.,confirmation), (3) to understand the mechanisms thatcausethe phenomenon, and (4) to understand the mechanisms through which the phenomenon results inconsequences. We link these issues to three major types of uncertainty: linguistic, psychological, and epistemic. The application of this framework shows that the four components tend to be characterized by different types of uncertainty in invasion science. We explain how these uncertainties can be detrimental to the implementation of management measures and propose ways to reduce them. Since biological invasions are increasingly tightly embedded in complex socio‐ecological systems, many problems associated with these uncertainties have convoluted solutions. They demand the consensus of many stakeholders to define and frame the dimensions of the phenomenon, and to decide on appropriate actions. While many of the uncertainties cannot be eliminated completely, we believe that using this framework to explicitly identify and communicate them will help to improve collaboration between researchers and managers, increase scientific, political, and public support for invasion research, and provide a stronger foundation for sustainable management strategies.

Non‐native plants often alter environments they invade, favouring their own performance through positive feedbacks. Plant–soil interactions represent one such mechanism, but their complexity (e.g. invader‐induced changes in soil nutrients, microbial communities, etc.) makes inferences of the precise mechanisms that benefit invaders difficult. Here we aimed to determine: (1) whether invasion by Australian acacias (genus Acacia Mill.) changes nitrogen‐fixing soil rhizobial community diversity and structure, and (2) the importance of available rhizobia and overall invader‐induced soil changes as significant facilitators of acacia performance. We sampled soils from various invaded and nearby uninvaded areas in South Africa's Core Cape Subregion and, using next generation sequencing, compared rhizobial communities between invaded and univaded soils. We then determined the relative importance of soil status (invaded vs. uninvaded), in conjunction with rhizobial addition, to the performance of invasive acacias under common garden conditions. Next generation sequencing data revealed that invaded soils generally harboured lower rhizobial diversity and were compositionally more homogenous compared to uninvaded soils. Bradyrhizobium strains, the most common known rhizobia associated with acacias, were more abundant in invaded than uninvaded sites. Our greenhouse experiment found significantly reduced growth performances of acacias in uninvaded relative to invaded soils for most species by site comparisons, and almost no influence of additional rhizobial inoculum. However, the overall relationship between nodulation and growth kinetics was much steeper for plants grown in uninvaded compared to invaded soils. Despite invasive acacias homogenizing nitrogen‐fixing rhizobial community composition and reducing diversity, it appears that mutualist availability poses no significant barrier to acacia establishment. Although acacia‐induced changes to soil conditions enhance plant performance, successful nodulation seems important to early growth performance when encountering novel soil conditions. Synthesis. We provide evidence that invasions by Australian acacias affect the diversity and structure of soil rhizobial communities. Although overall soil changes benefit their performance independent of rhizobia addition, forming successful mutualistic interactions is critical during the establishment phase under novel environmental conditions. Taken together, our results indicate that interactions between soil abiotic and biotic conditions work in concert to enhance invader performance through positive feedbacks.