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作 者:肖雨沙 郑洁宁 李红春 宋莉英[1] XIAO Yusha;ZHENG Jiening;LI Hongchun;SONG Liying(School of Life Science,Guangzhou University,Guangzhou 510006,China)
出 处:《生态科学》2021年第4期75-82,共8页Ecological Science
基 金:广东省自然科学基金(2018A030313478);广州市科技计划(201707010257);广州大学大学生创新训练项目(201811078098)。
摘 要:采用最大熵物种分布模型(MaxEnt)对南美蟛蜞菊当前、未来2050、2070年在我国适生区分布情况进行预测,探究影响南美蟛蜞菊分布的主要环境因子。模型AUC值达到0.9以上,表明预测结果可信度较高。模型预测结果显示,19个环境因子中贡献率较高的前四位依次是最暖季度降水量(bio 18)、最湿月降水量(bio 13)、最干月降水量(bio 14)、最湿季度降水量(bio 16),可以看出降水量是影响南美蟛蜞菊分布的主导因子。模型预测南美蟛蜞菊在我国总适生区面积为21.85万km^(2),占国土面积的22.77%,表明其入侵风险较高;其中,最佳适生区面积为6.60万km^(2),与其当前分布区基本吻合。在未来气候变化下,南美蟛蜞菊总适生区面积变化不大,但分布格局发生变化,最佳适生区有向西南地区转移的趋势。研究结果为该入侵种的生态风险评估及防控工作提供了重要依据。The distribution model of maximum entropy(MaxEnt)was used to predict potential distribution of Wedelia trilobata in China under current,2050 and 2070 climate conditions,and to explore the main environmental factors affecting its distribution.The areas under the receiver operating characteristic curve(AUC)values were above 0.9,which indicated the high prediction accuracy.Results from the mode showed that the top four with the highest contribution rate among the 19 environmental factors were the precipitation of the warmest quarter(bio 18),precipitation of the wettest month(bio 13),precipitation of the driest month(bio 14)and precipitation of the wettest quarter(bio 16),which suggested that precipitation was the dominant factor affecting the distribution of W.trilobata.The model predicted that the potential distribution area of W.trilobata was 218500 km^(2),accounting for 22.77%of the total land area in China,indicating its high invasive risk.The best suitable area of W.trilobata was 66000 km^(2),which was basically consistent with its current distribution area.With the climate change in future,the total area suitable for W.trilobata in China would remain about the same,while the best suitable area would tend to spread towards southwest China.The research results provided an important reference to the ecological risk assessment and control of this invasive species.
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