Climate-Driven Prediction of the Future Distribution of Phytolacca americana L. Using a BIOMOD2 Ensemble Modelling Framework

Phytolacca americana L. is an invasive perennial plant that has become increasingly widespread in China, but its current climatic suitability and future redistribution under climate change remain insufficiently quantified. This study aimed to identify the major environmental drivers of P. americana distribution and to project its potential habitat suitability under future climate scenarios. We compiled a national occurrence dataset and retained 683 quality-controlled presence records after taxonomic verification, coordinate checking, and 5 km spatial thinning. A BIOMOD2 ensemble modelling framework was used to integrate nine algorithms, and future projections were generated using CMIP6 climate data under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 across four time periods from 2021 to 2100. The ensemble model showed strong predictive performance, with TSS = 0.804 and ROC = 0.967. May shortwave radiation, January mean temperature, and annual temperature range were identified as the dominant predictors of habitat suitability. Under current climate conditions, highly suitable habitats were mainly concentrated in warm and humid regions of eastern and southern China. Future projections indicated that suitable habitats may expand toward northern, northwestern, and higher-elevation regions, whereas highly suitable habitats may become redistributed or fragmented under stronger climate forcing. Centroid analyses further suggested non-linear, scenario-dependent shifts rather than a simple poleward expansion. These findings provide a spatial basis for early warning, targeted monitoring, and pathway-focused management of P. americana in China.