Can habitat modification in the native range promote invasion?

Highlights : . Invasion success is increasingly viewed as an eco-evolutionary response to anthropogenic disturbance. . The anthropogenically induced adaptation to invade hypothesis considers selection in human-modified habitats within the native range as a potential driver of invasion, shifting attention from post-introduction to pre-introduction evolution. . Human-modified habitats can now be characterised as disturbance continua using scalable predictors, enabling more robust cross-system tests. . Population genomics can identify invasion sources, reconstruct introduction pathways, detect genotype–environment associations, and test whether adaptation arose in native, human-modified habitats or after introduction. . Genomic offset analyses can link genomic variation to expected environmental mismatches, helping to forecast invasion risk. . Time-resolved genomic data and experimental validation provide powerful complements to comparative genomic analyses, strengthening causal inference beyond correlation. Abstract: The anthropogenically induced adaptation to invade (AIAI) hypothesis posits that selection in human-modified habitats within native ranges can adapt populations to invade similarly altered environments elsewhere. Although widely invoked, empirical tests of this hypothesis remain limited because disentangling native-range adaptation from post-introduction evolution is challenging. Here, we clarify how anthropogenic disturbance creates repeatable selective regimes and demonstrate how targeted sampling, population genomics, and genotype–environment associations can disentangle native-range adaptation from post-introduction evolution. Incorporating genomic offset, genetic architecture, nongenetic changes, experiments, and temporal data further strengthens inference. These insights and approaches establish the AIAI hypothesis as a mechanism that explicitly links human disturbance with the evolutionary dynamics of invasive species, providing novel insights into the prediction and management of biological invasions.