采用多尺度数据源预测豚草在新疆的潜在分布

Predicting the potential distribution of ragweed in Xinjiang using multi-scale data source

文中基于最大熵模型,分别采用两种尺度数据源(全球及研究区新疆)预测了豚草在新疆的潜在分布,旨在从多角度为新疆的豚草防控工作提供科学依据。结果表明:豚草在新疆的总适生区面积,全球数据预测结果(占17.78%)大于研究区数据预测结果(占0.77%)。降水是豚草在全球和新疆分布的首要限制因子,累计贡献率分别为64.7%、39.9%。建议将涵盖豚草更丰富生态位信息的全球数据预测结果作为长期防控预警的依据,同时可将研究区数据的预测结果用于当前短期的精准防控;此外,在对这些入侵时间短、分布与环境不平衡的物种进行潜在分布预测时,应使用包含其原生范围和入侵范围的数据源。

Maxent niche model was used to predict the potential distribution of ragweed in Xinjiang, with two kinds of scale data(global and Xinjiang), arming to provide scientific basis for the prevention and control of ragweed in Xinjiang from multiple angles. The results showed that the prediction of total suitable area of ragweed in Xinjiang(17.78%) were greater than that of the research area data(0.77%). Precipitation was the primary limiting factor for the distribution of ragweed in the world and Xinjiang, with cumulative contribution rates of 64.7% and 39.9%, respectively. We suggest that the prediction results of global data which covering the richer niche information of ragweed should be used as the basis for long-term prevention and control and early warning. Meanwhile, the prediction results of the research area data can be used for the current short-term accurate prevention and control. In addition, when predicting the potential distribution of these species which with short invasion times and imbalanced between distribution and environment, data including their native range and invasion range should be used.