Modeling the Potential Distribution Patterns of the Invasive Plant Species Phytolacca americana in China in Response to Climate Change

Plants (Basel). 2024 Apr 12;13(8):1082. doi: 10.3390/plants13081082.

Abstract

Phytolacca americana, introduced to China in the 20th century for its medicinal properties, has posed a significant ecological and agricultural challenge. Its prolific fruit production, high reproductive coefficient, adaptability, and toxic roots and fruits have led to the formation of monoculture communities, reducing native species diversity and posing threats to agriculture, human and animal health, and local ecosystems. Understanding its potential distribution patterns at a regional scale and its response to climate change is essential for effective monitoring, management, and control. In this study, we utilized the Maxent model to simulate potential habitat areas of P. americana across three timeframes (current, 2050s, and 2070s) under three climate change scenarios (SSP126, SSP245, and SSP585). Leveraging data from 556 P. americana sites across China, we employed ROC curves to assess the prediction accuracy. Our findings highlight key environmental factors influencing P. americana's geographical distribution, including the driest month's precipitation, the coldest month's minimum temperature, the wettest month's precipitation, isothermality, and temperature annual range. Under current climate conditions, P. americana potentially inhabits 280.26 × 104 km2 in China, with a concentration in 27 provinces and cities within the Yangtze River basin and its southern regions. While future climate change scenarios do not drastically alter the total suitable area, the proportions of high and low-suitability areas decrease over time, shifting towards moderate suitability. Specifically, in the SSP126 scenario, the centroid of the predicted suitable area shifts northeastward and then southwestward. In contrast, in the SSP245 and SSP585 scenarios, the centroid shifts northward.

Keywords: Maxent; Phytolacca americana; biological invasion; climate change; potentially suitable area.