Niche Expansion in an Invasive Plant Has Significant Influence on the Modelling of Its Current and Future Geographic Distributions

Aim Species distribution models (SDMs) are commonly used to predict distributions of invasive species; however, they rely on assumptions that often go untested for invasive species. To determine what climatic conditions may be suitable for invasion using SDMs, it is critical to assess whether the species occupies the same climatic niche in its native and invaded ranges. If this assumption is not met, current distribution‐climate relationships will not be predictive of future climatic suitability. We examined the influence of climatic niche shifts on SDM predictions using an invasive plant species in North America. Location North America and Europe. Taxon Vincetoxicum rossicum . Methods We quantified niche shift between V. rossicum 's native and invaded ranges and built SDMs varying in training range. Results We found that V. rossicum has expanded its niche in North America into wetter climates and climates where precipitation is more evenly distributed throughout the year. Consequently, native‐ and invasive‐trained models generated markedly different predictions of climatic suitability across North America, with the native‐trained model identifying much more suitable area. Our analysis revealed that a large portion of North American climate space was non‐analogous to the current invaded range. Therefore, the native‐trained model produced predictions across a larger area of North America than the invasive‐trained model. Main Conclusions Given the observed niche shift, invasive‐trained models are likely more reliable for predicting potential spread than native‐trained models. However, native‐trained models, though potentially less reliable, generate broader predictions beyond the geographic extent of the invasive‐trained models. Combining predictions from models trained on each range increases confidence in areas of agreement and highlights regions of uncertainty where they diverge. This study provides a framework for developing biologically informed SDMs for invasive species that have undergone niche shifts, helping to reconcile divergent model predictions and offering more nuanced guidance for invasive species management.