基于MaxEnt模型对入侵物种藿香蓟的中国潜在适生区预测研究

Prediction of Potential Suitable Growth Areas for Invasive Species of Ageratum conyzoides L. in China Based on the MaxEnt Model

摘要: 藿香蓟(Ageratum conyzoides L.)，是我国生物入侵恶意入侵植物之一，对被入侵区域的生物多样性构成严重威胁。为了有效防控藿香蓟，采用最大熵模型(MaxEnt)和ArcGIS软件对藿香蓟当前以及2030s、2050s时期，SSP126、SSP245气候模式下在中国的潜在适生区和影响因素进行预测。结果显示：当前适生区预测AUC值为0.929，模型预测结果理想、适生区分布主要受降水和温度的影响。藿香蓟入侵物种的适生区分布范围很广，主要集中在我国华东地区、华中地区、西南地区的南部以及华南地区和台湾省，面积为6.268 × 105 km²。随时间推移，在2030s时期，SSP126、SSP245气候模式下的适生区面积分别为6.485 × 10⁵ km²、6.465 × 10⁵ km²；2050s时期，SSP126、SSP245气候模式下的适生区面积分别为6.472 × 10⁵ km²、6.871 × 10⁵ km²。总体来说，未来气候变化下，藿香蓟的适生区呈现出不断扩张的趋势，建议相关部门基于其潜在适生区的变化趋势制定相应的分级管理策略，以防止进一步扩散。

Abstract: Huoxiangji (scientific name: Ageratum conyzoides L.) is one of the invasive alien plant species in China, posing a severe threat to biodiversity in invaded regions. To effectively control A. conyzoides, the Maximum Entropy Model (MaxEnt) and ArcGIS software were employed to predict its current and future (2030s, 2050s) potentially suitable growth areas and influencing factors under SSP126 and SSP245 climate scenarios in China. The results showed that the current predicted suitable growth area achieved an AUC value of 0.929, indicating excellent model performance. The distribution was primarily influenced by precipitation and temperature. At present, the suitable growth areas of A. conyzoides invasive species are widely distributed, mainly concentrated in southern East China, South China, southern Central China, southern Southwest China, and Taiwan Province, covering an area of 6.268 × 10⁵ km². By the 2030s, the suitable growth areas under SSP126 and SSP245 scenarios are projected to expand to 6.485 × 10⁵ km² and 6.465 × 10⁵ km², respectively. By the 2050s, the areas under SSP126 and SSP245 scenarios are predicted to reach 6.472 × 10⁵ km² and 6.871 × 10⁵ km², respectively. Overall, under future climate change, the suitable growth areas of A. conyzoides are projected to expand continuously. It is recommended that relevant authorities develop tiered management strategies based on the predicted shifts in its potential distribution to prevent further spread.