Valuing the information hidden in true long-term data for invasion science

Abstract Invasive species pose a significant threat to global biodiversity and human well-being. Despite the widespread use of long-term biomonitoring data in many natural science fields, analysis time series with focus on biological invasions is uncommon. To address this gap, we used twenty macroinvertebrate from highly anthropogenically altered Rhine River, collected over 32 years 1973 2005. We examined adequacy capturing non-native trends explored alpha, beta, gamma diversity several climatic site-specific predictors. Our findings revealed that adequately captured saturating richness time. Additionally, observed an increase both alpha native time, recent dip trends. Beta were more complicated, but eventually increased, contrasting beta diversity. applied models indicate ecosystem, shifts insignificant, while was primarily driving factor. Proximity anthropogenic structures distance outlet only predictors facilitating These highlight value importance for study invasive species, particularly invasion dynamics once again underline naturality ecosystems precede effect climate change.