生物多样性 ›› 2019, Vol. 27 ›› Issue (8): 873-879.doi: 10.17520/biods.2019060

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东北4种林木干基腐朽病原真菌潜在分布范围预测及其生态位分析

袁海生1, *(), 魏玉莲1, 周丽伟1, 秦问敏1, 崔宝凯2, 何双辉2   

  1. 1. 中国科学院森林生态与管理重点实验室, 中国科学院沈阳应用生态研究所, 沈阳 110164
    2. 北京林业大学微生物研究所, 北京 100083
  • 收稿日期:2019-02-28 接受日期:2019-04-25 出版日期:2019-08-20
  • 通讯作者: 袁海生 E-mail:hsyuan@iae.ac.cn
  • 基金项目:
    科技部科技基础性工作专项(2014FY210400)

Potential distribution and ecological niches of four butt-rot pathogenic fungi in Northeast China

Hai-Sheng Yuan1, *(), Yulian Wei1, Liwei Zhou1, Wenmin Qin1, Baokai Cui2, Shuanghui He2   

  1. 1. CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164
    2. Institute of Microbiology, Beijing Forestry University, Beijing 100083
  • Received:2019-02-28 Accepted:2019-04-25 Online:2019-08-20
  • Contact: Yuan Hai-Sheng E-mail:hsyuan@iae.ac.cn

东北地区木生真菌物种资源丰富, 包括了数十种林木干基腐朽病原真菌。过去对该类真菌曾进行多次调查, 获取了大量物种分布数据, 但对于非重点调查区域是否存在某种真菌物种却不明确。本文选取东北地区具有代表性的4种林木干基腐朽病原真菌, 即红缘拟层孔菌(Fomitopsis pinicola)、落叶松锈迷孔菌(Porodaedalea laricis)、桦剥管孔菌(Piptoporus betulinus)和香栓孔菌(Trametes suaveolens), 根据其地理分布数据和分布地的环境因子数据, 以最大熵模型(MaxEnt)对这些种类在东北地区可能的分布范围进行了模拟预测, 以曲线下面积(area under the receiver operating characteristic curve, AUC)对模型有效性进行评价, 并对各物种的生态位进行了分析。结果显示, 以MaxEnt方法获得的各物种预测模型均获得了较高的AUC值, 分别为0.990, 0.990, 0.989和0.967, 表明4种林木干基腐朽病原真菌预测模型的有效性较高。物种分布模型涉及的环境变量对模型的贡献率显示, 最暖季降水量(Bio18)、温度的年较差(Bio7)、最干季均温(Bio9)等变量对各物种模型贡献率较高。该研究结果为预测4种病原真菌在东北地区的分布范围和科学防治该类病原真菌提供了依据。

关键词: 最大熵模型, 曲线下面积, 干基腐朽病原真菌, 生态位

Lignicolous fungi, including dozens of butt-rot pathogenic fungi, are abundant in Northeast China. In the past decades, many investigations have been carried out on fungal species diversity, and thus plentiful species distribution data has been obtained. However, it is not clear whether there remains a region that has yet to be investigated for the presence of fungal species. In this study, four representative butt-rot pathogenic fungi, Fomitopsis pinicola, Porodaedalea laricis, Piptoporus betulinus and Trametes suaveolens, of Northeast China were selected. Their geographical distribution data and the correlating environmental factors were used to model their potential distribution using the maximum entropy model (MaxEnt). The area under the receiver operating characteristic curve (AUC) was examined to evaluate the model performance. Thus, the ecological niches of these species were analyzed. The results showed that all the species prediction models obtained high AUC values (0.990, 0.990, 0.989 and 0.967), which suggests that the prediction models were effective for the four species. The most effective environmental variables, which were the precipitation of warmest quarter (Bio18), the temperature annual range (Bio7) and the mean temperature of driest quarter (Bio9), were shown to contribute more to the species distribution models than other factors. The results delineate possible distribution ranges for the four pathogenic fungi in Northeast China, thereby offering forest managers a guide for where to focus prevention and treatment efforts for these pathogenic fungi.

Key words: MaxEnt, AUC, butt-rot pathogenic fungi, ecological niches

图1

4种病原真菌子实体。(a)红缘拟层孔菌; (b)落叶松锈迷孔菌; (c)桦剥管孔菌; (d)香栓孔菌。"

图2

东北地区4种病原真菌的采集点"

表1

4个林木干基腐朽病原真菌分布记录点及曲线下面积值"

物种
Species
记录点
Registered presence
训练点数
Number of training points
训练AUC
Training AUC
测试AUC
Test AUC
红缘拟层孔菌 Fomitopsis pinicola 29 9 0.984 0.990
落叶松锈迷孔菌 Porodaedalea laricis 9 3 0.933 0.990
桦剥管孔菌 Piptoporus betulinus 21 7 0.984 0.989
香栓孔菌 Trametes suaveolens 24 7 0.981 0.967

图3

模型预测的4种干基腐朽病原真菌的潜在分布区域。(a)红缘拟层孔菌; (b)落叶松锈迷孔菌; (c)桦剥管孔菌; (d)香栓孔菌。图中白色方块为训练点, 紫色方块为测试点。"

表2

物种分布模型涉及的环境变量及其对模型的贡献率"

编号
Code
环境变量
Environmental variable
贡献率 Contribution (%)
红缘拟层孔菌
Fomitopsis
pinicola
落叶松锈迷孔菌
Porodaedalea
laricis
桦剥管孔菌
Piptoporus betulinus
香栓孔菌
Trametes suaveolens
Bio1 年均温 Annual mean temperature (℃) 6.1 0 11.8 2.9
Bio2 昼夜温差月均值
Mean diurnal range (mean of monthly (max - min temp)) (℃)
0 0.9 0 0
Bio3 等温性 Isothermality ((Bio2/Bio7) × 100) 5.2 0 5.6 4.1
Bio4 温度季节性变化标准差
Temperature seasonality (standard deviation × 100) (C of V)
16.6 0 6.6 34.9
Bio5 最暖月最高温 Maximum temperature of warmest month (℃) 0 0 0 0
Bio6 最冷月最低温 Minimum temperature of coldest month (℃) 0.5 0 2.9 1.7
Bio7 温度的年较差 Temperature annual range (Bio5 - Bio6) (℃) 29.9 4.3 17.6 4.2
Bio8 最湿季均温 Mean temperature of wettest quarter (℃) 0 0 0 0.3
Bio9 最干季均温 Mean temperature of driest quarter (℃) 7 78.8 18.1 0
Bio10 最暖季均温 Mean temperature of warmest quarter (℃) 0 0 0 0
Bio11 最冷季均温 Mean temperature of coldest quarter (℃) 1.5 0 6.7 2.1
Bio12 年降水量 Annual precipitation (mm) 0 0 0 0
Bio13 最湿月降水量 Precipitation of wettest month (mm) 0 0 0.6 0
Bio14 最干月降水量 Precipitation of driest month (mm) 0 0 0 0
Bio15 降水量季节性变异系数
Precipitation seasonality (coefficient of variation) (C of V)
0.5 1.7 0 4.4
Bio16 最湿季降水量 Precipitation of wettest quarter (mm) 0 0 0 0
Bio17 最干季降水量 Precipitation of driest quarter (mm) 5.5 0 4.9 6.9
Bio18 最暖季降水量 Precipitation of warmest quarter (mm) 25 6.2 23.5 36.3
Bio19 最冷季降水量 Precipitation of coldest quarter (mm) 0.8 0 0.4 0.2
ELE 海拔 Elevation (m) 1.4 8.1 1.2 1.8

图4

4种干基腐朽病原真菌分布模型中主要气候因子的响应曲线"

图5

4种干基腐朽病原真菌的三维生态位分布"

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