生物多样性 ›› 2019, Vol. 27 ›› Issue (2): 140-148.doi: 10.17520/biods.2018232

• 研究报告 • 上一篇    下一篇

基于本土最优模型模拟入侵物种水盾草在中国的潜在分布

范靖宇, 李汉芃, 杨琢, 朱耿平   

  1. 天津师范大学生命科学学院, 天津 300387
  • 收稿日期:2018-08-31 接受日期:2018-12-08 出版日期:2019-02-20
  • 通讯作者: 朱耿平
  • 基金项目:
    国家自然科学基金(31401962);国家自然科学基金(31870523)

Selecting the best native individual model to predict potential distribution of Cabomba caroliniana in China

Fan Jingyu, Li Hanpeng, Yang Zhuo, Zhu Gengping   

  1. College of Life Sciences, Tianjin Normal University, Tianjin 300387
  • Received:2018-08-31 Accepted:2018-12-08 Online:2019-02-20
  • Contact: Zhu Gengping

生态位模型预测存在不确定性, 不同模型预测结果差别较大。在生态位保守的前提下, 在本土区域构建经典生态位模型, 利用入侵地独立样本数据检验并选择最优模型, 具有独特优势, 可为入侵物种风险分析提供可靠参考。水盾草(Cabomba caroliniana)是一种恶性水生入侵杂草, 原产于南美洲, 已在我国多个省市建立种群, 本文基于本土最优模型预测其在我国的潜在分布, 以期为其风险分析和综合治理提供依据, 并通过水盾草案例探讨如何提高生态位模型预测准确性的方法。本文按时间顺序梳理了水盾草在我国的分布记录, 然后根据水盾草已有分布记录和其所关联的环境因子比较了不同地理种群所占有的气候生态空间, 测试水盾草在世界入侵过程中的现实生态位保守性。采用两组环境变量和5种算法在南美洲本土地区构建10种生态位模型, 并将其转移至我国, 基于最小遗漏率和记账错率, 利用我国(入侵地)的样本数据选择最优模型预测水盾草在我国的适宜生态空间和潜在分布。研究发现当前水盾草在我国的分布集中在东部水域充沛地区, 沿京杭运河和南水北调工程等向北扩散。生态空间比对中发现水盾草在亚洲与其他大洲所占有的生态空间具有一定的重叠, 其在我国的入侵过程中生态位是保守的。与本土空间相比, 水盾草在我国所占有的生态空间存在较大的生态位空缺, 表明水盾草在我国的潜在分布范围较大。生态位模型预测显示水盾草的适生区主要分布于我国的北京、上海、山东、浙江、江苏、安徽、湖北和湖南等省(市)。水盾草的潜在分布区多聚集在我国东南部, 该地区河流、湖泊、运河和渠道较为密集, 人类活动及自然天敌的缺乏容易助长其入侵趋势, 应在这些适宜地区开展调查, 及时发现疫情并采取相应措施。

关键词: 生态位模型, 最优模型, 水盾草, 潜在分布, 中国

Uncertainty is inherent in ecological niche model predictions and different models yield different predictions. Based on the niche conservatism hypothesis, classic niche models that are calibrated on native areas and transferred to introduced areas for evaluation and prediction have advantages. Cabomba caroliniana is a notorious invasive aquatic weed native to South America that has established populations in China. In this study, independent testing points from China were used to validate and select the best individual model to predict the potential distribution, offering reliable and valuable information for risk analyses of C. caroliniana. The distributional records of C. caroliniana in China were sorted in chronological order, and climate niche dynamics and niche conservatism of C. caroliniana invasions across major continents were investigated using environmental variables associated with observed records. A total of 10 models were then calibrated in native area using two environmental datasets and five model algorithms. The best individual model was used to predict distribution, which was tested and selected based on the criteria of low omission and commission errors of independent introduced points. Results showed that present distribution of C. caroliniana occurs mainly along the eastern coastal areas of China. It has also dispersed northward in rivers and lakes system along Beijing-Hangzhou Grand Canal or South-to-North water diversions. The climate conditions occupied by different continental populations overlap broadly suggesting its climate niche was conserved during the invasion in China. There were many climate spaces that were unfilled when compared to its native niche spaces, suggesting a high invasion potential in these areas. Areas of potential distributions identified by best native individual model include Beijing, Shanghai, Shandong, Zhejiang, Jiangsu, Anhui, Hubei and Hunan provinces. These potential areas were mainly distributed in the southeastern rivers, lakes, canals and channels all with high human activity and no effective natural enemy, which could assist C. caroliniana expansion. Our research demonstrates the need for rigorous surveys in these areas, together with an integrative management action to control further expansion of C. caroliniana.

Key words: ecological niche model, fine-tuned model, Cabomba caroliniana, potential distribution, China

图1

水盾草在中国的分布记录"

图2

两组环境变量下五个洲水盾草的生态位重叠对比图。左侧: A组环境变量, 包括Bio2, Bio3, Bio10, Bio11, Bio15, Bio16, Bio18和Bio19; 右侧: B组环境变量, 包括Bio1, Bio5, Bio6, Bio12, Bio13, Bio14和Bio15。"

图3

基于两组环境变量不同水盾草地理种群的等价性与相似性测试。黑色虚线代表所观察到的实际生态位重叠值, 黑色柱状代表生态位重叠的随机分布频率。左侧: A组环境变量; 右侧: B组环境变量。A组和B组包含的环境变量见图2."

图4

基于两组环境变量构建的本土模型在入侵地(中国)的遗漏率与记账错率比较。左图: A组环境变量, 右图: B组环境变量。A组和B组包含的环境变量见图2."

图5

基于本土随机森林模型对水盾草在我国的潜在分布区预测。左侧: A组环境变量, 右侧: B组环境变量。A组和B组包含的环境变量见图2."

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