Abstract:

Studying the ecological distribution patterns of invasive species under climate change is critical for developing regional control strategies. To simulate and predict the potential invasion of Solidago canadensis in Fujian under two climate change scenarios (SSP126 and SSP585) in the current and two future periods (2041-2060 and 2061-2080), we used the adopted MaxEnt model based on field survey data and environmental factors (climate, terrain, and soil), and applied the ENM Tool and R language software to optimize the model parameters and data screening. The results showed that the area under the receiver operating characteristic curve (AUC) of the training and test datasets was 0.915, indicating that the simulation effect of the model was good. Temperature seasonality, soil base saturation, altitude, and precipitation in the warmest quarter were the main environmental factors affecting the distribution of Solidago canadensis, with a total contribution rate of 81.7%. The current potential invasion risk area of Solidago canadensis covers approximately 50100 km², accounting for 41.25% of Fujian’s total land area. The high-risk areas for Solidago canadensis invasion based on field surveys and model predictions were mainly concentrated in northern and eastern Fujian, including Nanping, Ningde, and Fuzhou. The risk invasion areas showed a trend of a continuous increase under two future climate scenarios, and the response was more sensitive under the highest carbon emission scenario (SSP585). The trend of Solidago canadensis invasion is mainly from north to south in Fujian, and the distribution center would move from the current Yanping area to Shaxian. This study provides ecological and theoretical support for the risk assessment, monitoring, and early warning, as well as the prevention and control of Solidago canadensis in Fujian Province.

Key words: invasive species, Solidago canadensis, MaxEnt model, climate change

摘要：

研究气候变化下入侵物种生态分布对制定物种分区防控策略至关重要。基于野外调查的加拿大一枝黄花（Solidago canadensis）实地分布数据，该研究综合气候、地形和土壤因子，应用ENM Tool软件和R语言完成数据筛选与参数优化，构建最大熵（MaxEnt）模型，模拟预测了其在福建省当前及未来两个时间段（2041－2060年和2061－2080年）不同气候变化情景（SSP126、SSP585）下的潜在入侵趋势。结果显示，模型预测结果的曲线下的面积（AUC）为0.915，表明模拟效果精确；气温季节性变化、土壤盐基饱和度、海拔和最热季度降水量是影响加拿大一枝黄花分布的主要环境因素，贡献率总和为81.7%。当前，加拿大一枝黄花的入侵风险区面积约为5.01×10⁴ km²，占福建省陆地总面积的41.25%，闽北（南平）和闽东（宁德、福州）等地为入侵高风险区域。在两种未来气候变化情景下，其入侵风险区域均呈现出明显扩散趋势，尤其是在高排放（SSP585）情景下，风险区持续扩增更为明显。入侵扩散趋势主要由北向南扩增，分布中心将由当前的延平向沙县方向转移。研究结果可为福建省加拿大一枝黄花的入侵预警与分区防控提供参考。

关键词: 外来物种入侵, 加拿大一枝黄花, 最大熵模型, 气候变化