大地测量与地球动力学

基于贝叶斯方法的内蒙古地区应力场研究

张帆 ¹^,² , 崔丰智 ²^,* , 郝美仙 ² , 杨彦明 ² , 李娟 ² , 杨晓忠 ³

大地测量与地球动力学 | 地震地质 2025,45(3): 252-259

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大地测量与地球动力学 |地震地质 2025 , 45 (3) : 252 -259

基于贝叶斯方法的内蒙古地区应力场研究

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张帆¹^,², 崔丰智²^,*, 郝美仙², 杨彦明², 李娟², 杨晓忠³

作者信息

1 华北电力大学控制与计算机工程学院, 北京市北农路2号, 102206

2 内蒙古自治区地震局, 呼和浩特市哲里木路80号, 010010

3 华北电力大学数理学院, 北京市北农路2号, 102206

通讯作者:

崔丰智，助理工程师，主要研究方向为地震预测方法，E-mail: fengzhicui66@163.com

CUI Fengzhi, assistant engineer, majors in earthquake prediction methods, E-mail: fengzhicui66@163.com

作者简介:

张帆，高级工程师，主要研究方向为地震预测方法，E-mail：spacelessness@163.com

Research on Stress Field in Inner Mongolia Based on Bayesian Method

Fan ZHANG¹^,², Fengzhi CUI²^,*, Meixian HAO², Yanming YANG², Juan LI², Xiaozhong YANG³

Affiliations

1 School of Control and Computer Engineering, North China Electric Power University, 2 Beinong Road, Beijing 102206, China

2 Earthquake Agency of Inner Mongolia Autonomous Region, 80 Jirem Road, Hohhot 010010, China

3 School of Mathematics and Physics, North China Electric Power University, 2 Beinong Road, Beijing 102206, China

ZHANG Fan, senior engineer, majors in earthquake prediction methods, E-mail: spacelessness@163.com

出版时间: 2025-03-15 doi: 10.14075/j.jgg.2024.04.172

文章导航

摘要

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利用内蒙古地区728个震源机制解和2 793次地震事件的14 460条P波极性数据，采用3种不同策略对内蒙古地区应力场进行研究，获得地壳深层应力状态。将内蒙古地区划分为1°×1°网格，分别采用基于初动极性数据的综合震源机制方法、基于震源机制的贝叶斯右手三棱锥方法(BRTM)和极性数据反演结果与震源机制解数据加权融合方法进行反演。结果表明，基于极性数据和基于震源机制的方法具有较好的一致性。由于极性数据更为丰富，可克服震源机制解数据的有限性，获得更多区域的反演结果。将基于极性数据的反演结果与震源机制解数据加权融合后，采用BRTM方法获得125个格点的反演结果，可扩充计算区域和降低结果的不确定性。研究结果显示，内蒙古地区不同区域的应力场在空间上存在较大差异，东部地区主要表现为剪切和拉张特征，大兴安岭主脊表现为剪切特征，两侧盆地表现出拉张特征，东南部的赤峰和通辽一带局部呈现挤压特征，鄂尔多斯地块北缘主要表现出拉张特征，阿拉善地块主要表现出剪切特征；最大主应力方向存在较大差异，而最小主应力方向较为一致。

关键词

构造应力场 / BRTM / 震源机制 / 内蒙古

Abstract

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We investigate the crustal stress field in Inner Mongolia using 728 focal mechanism solutions and 14 460 P-wave polarity data derived from 2 793 earthquakes based on three different strategies. The Inner Mongolia area is divided into 1°×1° grids, and three methods are applied: a composite focal mechanism solution method based on first-motion polarity data, a Bayesian right trihedra method(BRTM) based on focal mechanisms, and a weighted fusion method of polarity and focal mechanism data. The results from polarity-based and focal mechanism-based methods show good consistency. The abundance of polarity data, compared to limited focal mechanism data, enables stress inversion in a wider spatial extent. After weighted fusion of polarity-based results with focal mechanism data, the BRTM successfully obtains stress results at 125 grid points, expanding the coverage and reducing uncertainties. The study reveals significant spatial variations in the stress field across Inner Mongolia area. The eastern regions are dominated by shear and extension, with shearing concentrated along the Daxinganling and extension characterizing the basins on both sides. Localized compression is observed near Chifeng and Tongliao in the southeast. The northern margin of Ordos block exhibits extension characteristics, while the Alxa block displays shear features. The orientations of maximum principal stress exhibit considerable differences, while the minimum principal stress directions remain relatively uniform.

Key words

tectonic stress field / BRTM / focal mechanism / Inner Mongolia

引用本文

张帆, 崔丰智, 郝美仙, 杨彦明, 李娟, 杨晓忠. 基于贝叶斯方法的内蒙古地区应力场研究. 大地测量与地球动力学, 2025 , 45 (3) : 252 -259 . DOI: 10.14075/j.jgg.2024.04.172

Fan ZHANG, Fengzhi CUI, Meixian HAO, Yanming YANG, Juan LI, Xiaozhong YANG. Research on Stress Field in Inner Mongolia Based on Bayesian Method[J]. Journal of Geodesy and Geodynamics, 2025 , 45 (3) : 252 -259 . DOI: 10.14075/j.jgg.2024.04.172

正文

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岩石圈内部构造应力是引发地震及其他构造运动的最直接动力^[1]，板块内部的应力相对均匀且弥散，因此最大水平应力通常与板块运动的绝对方向一致^[2]。地壳形变监测、岩石力学实验及数值模拟技术均可推测并解释构造应力场，除原位应力测量技术外，还可通过地质学和地球物理学等方法来推断应力信息。震源机制能更深入地展现地壳深层的应力状态，有效映射出震源区应力场的动态变化^[3-4]。基于震源机制的应力反演方法通常是基于Wallace-Bott条件^[5]等假设，即作用于特定断层面上的剪切应力方向与该断层面上的实际滑动方向一致，断层在有限时间间隔内滑动，在此期间应力场保持恒定^[6]；每个断层上的滑动事件不会显著扰动周围应力场^[7]。

应用震源机制反演应力的方法主要分为图形方法和分析方法，其中分析方法主要是优化断层滑动运动学函数^[8-11]，而图形方法则在整个震源球面上优化目标函数，无需在震源机制的节点平面之间进行选择，可快速且可靠地对震源机制解数据集进行应力反演^[12-13]。此外，大量小震的极性数据也可应用于应力场估计^[14-17]。内蒙古地区自数字化观测以来已积累超过15 a的观测资料，可为相关地震学研究提供数据基础。本文收集较为丰富的震源机制解和P波极性数据，同时采用多种策略方法获得应力场反演结果，对比各种方法结果的差异，以分析内蒙古地区应力场分布特征及其动力学意义。

1 数据概况

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内蒙古地区强震主要发生在构造块体和次级块体的边界带，且不同区域受不同构造单元控制^[18-19]。本文收集和计算内蒙古地区2008年以来728个震源机制解数据，其中464个来自已有的研究结果^[20-23]，其余264个采用Focmec方法^[24]计算得到。将这些数据根据Kaverina等^[25]的分类原则，按照Anderson^[26]划分方法，分为正断、逆冲和走滑3种基本类型，分别用红色、蓝色和绿色表示(图1(a))。同时，收集2016—2023年中国地震台网发布的观测报告中包括内蒙古及其邻区50 km范围内共计2 973次地震事件的14 460条P波极性数据。图1(b)为P波极性数据分布，图中色标表示各地震的P波极性数据数量。

为对震源机制进行分类，Frohlich等^[27]提出一种图表方法，但该方法存在扭曲问题。Kagan^[28]采用Kaverina等^[25]的投影方法，将震源机制细分为7个类别：正断层(N)、正-走滑断层(N-SS)、走滑-正断层(SS-N)、走滑断层(SS)、走滑-逆断层(SS-R)、逆断-走滑断层(R-SS)和逆断层(R)。图2为震源机制解在弧形三角的分布情况，图中震源机制用圆点表示，分为3大类7个细分类别，色标为地理经度。

2 方法

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本文采用3种不同策略进行计算，第1种策略使用P波极性数据的综合震源机制方法^[14-17]，第2种策略使用震源机制数据的BRTM方法^[13]，第3种策略使用加权融合极性数据和震源机制数据的BRTM方法，该方法可更充分地利用现有的数据资料。为客观地比较3种方法，在计算和数据选取时选择相同参数，将内蒙古地区划分为1°×1°网格点，对于每个格点，考虑周围半径为150 km的圆形区域内数据，相邻格点的数据在一定程度上会发生重叠，既可保证数据的丰富性，又能避免细节信息的丢失。

2.1 综合震源机制方法

综合震源机制方法利用大量无法单独确定震源机制解的小地震的P波极性数据，能降低可用地震的震级下限，适用于数据稀缺地区，在小地震活动频繁的区域，能够揭示局部应力场的细节信息。计算过程采用网格搜索法^[16]，利用最小化矛盾比来确定最优解，确定P轴(压力轴)、B轴(中间轴)和T轴(张力轴)方向，可反映应力场的最大主应力σ₁、中间主应力σ₂和最小主应力σ₃信息。

2.2 贝叶斯右手三棱锥方法(BRTM)

贝叶斯右手三棱锥方法(BRTM)结合了右手三棱锥(RTM)^[29]和贝叶斯推断，通过一组震源机制解反演区域构造应力场。利用球面网格点代表可能的应力状态，对于每个网格点，计算该应力状态能够解释观测数据(即输入的震源机制)比例的量化指标RDM，该指标可表示观测数据与理论模型之间的不匹配程度，计算公式为^[29]：

(1)

$\operatorname{RDM}(\theta, \varphi)=\frac{1}{N} \sum\limits_k \operatorname{sgn}\left[\hat{\boldsymbol{x}}_k(\theta, \varphi) \boldsymbol{M}_k \hat{\boldsymbol{x}}_k^{\mathrm{T}}(\theta, \varphi)\right]$

式中，θ和φ为震源球面上的极坐标角度；M_k为事件k的归一化矩张量；

$ \hat{\boldsymbol{x}}_k(\theta, \varphi)$

为震源球面上某点的归一化笛卡尔向量；N为事件数量。该函数的取值范围在－1~1之间，数值表示该方向作为σ₃或σ₁的概率，RDM值越高，说明该应力状态与观测数据越吻合。

BRTM定义了概率分布函数p(θ₁，φ₁，θ₃，φ₃)，其中(θ₁，φ₁)和(θ₃，φ₃)分别代表主应力轴σ₁和σ₃的极坐标角度，采用边缘概率分布计算每个应力场方向的概率：

(2)

$\begin{gathered}p\left(\theta_1, \varphi_1, \theta_3, \varphi_3\right)= \\p_1\left(\theta_1, \varphi_1\right) p_3\left(\theta_3, \varphi_3\right) p_L\left(\theta_1, \varphi_1, \theta_3, \varphi_3\right)\end{gathered}$

式中，p₁和p₃分别为收缩性和扩张性二面体包含向量(θ，φ)的比例；p_L为满足Lisle准则的比例^[12]，用于确保σ₁和σ₃轴在由震源机制P轴和T轴定义的平面相对侧。该概率分布函数考虑了应力轴的正交性及其他相关的约束条件。

将RDM值作为似然函数，结合均匀分布的先验信息及应力状态之间正交性的约束，计算每个网格点代表的应力状态的后验概率密度。将后验概率密度最大的网格点对应的应力方向作为反演结果，得到区域主应力方向，并计算主应力轴(σ₁，σ₃)的方位角、仰角及Φ_B值^[30]。通过这种方式，BRTM能有效整合震源机制解数据和先验信息，实现对构造应力场的稳健反演。

利用上述方法定义p₁、p₃和p_L：

(3)

$\begin{gathered}p_1(\theta, \varphi)= \\\frac{1}{N} \sum\limits_k\left\{\begin{array}{l}1, \operatorname{sgn}\left[\hat{\boldsymbol{x}}_k(\theta, \varphi) \boldsymbol{M}_k \hat{\boldsymbol{x}}_k^{\mathrm{T}}(\theta, \varphi)\right]>0 \\0, \operatorname{sgn}\left[\hat{\boldsymbol{x}}_k(\theta, \varphi) \boldsymbol{M}_k \hat{\boldsymbol{x}}_k^{\mathrm{T}}(\theta, \varphi)\right] \leqslant 0\end{array}\right.\end{gathered}$

(4)

$\begin{gathered}p_3(\theta, \varphi)= \\\frac{1}{N} \sum\limits_k\left\{\begin{array}{l}1, \operatorname{sgn}\left[\hat{\boldsymbol{x}}_k(\theta, \varphi) \boldsymbol{M}_k \hat{\boldsymbol{x}}_k^{\mathrm{T}}(\theta, \varphi)\right]<0 \\0, \operatorname{sgn}\left[\hat{\boldsymbol{x}}_k(\theta, \varphi) \boldsymbol{M}_k \hat{\boldsymbol{x}}_k^{\mathrm{T}}(\theta, \varphi)\right] \geqslant 0\end{array}\right.\end{gathered}$

(5)

$\begin{gathered}p_L\left(\theta_1, \varphi_1, \theta_3, \varphi_3\right)= \\\frac{1}{N} \sum\limits_k\left\{\begin{array}{l}1, \operatorname{sgn}\left[\left(P_k T_k\right) \boldsymbol{v}_1\right] \neq \operatorname{sgn}\left[\left(P_k T_k\right) \boldsymbol{v}_3\right] \\0, \operatorname{sgn}\left[\left(P_k T_k\right) \boldsymbol{v}_1\right]=\operatorname{sgn}\left[\left(P_k T_k\right) \boldsymbol{v}_3\right]\end{array}\right.\end{gathered}$

式中，P_k和T_k为第k个震源机制的P轴和T轴；v₁和v₃分别为与方向(θ₁，φ₁)和(θ₃，φ₃)相关联的单位向量。

同时，BRTM通过一种参数化方法，使用三元组(θ₁，φ₁，ψ)表示应力状态，其中ψ表示σ₃绕σ₁顺时针旋转的角度。通过这种参数化方法，能够更便捷地计算σ₁方向(θ, φ)的边缘概率分布，从而有效地评估主应力方向的不确定性。

(6)

$p_{\sigma_1}\left(\theta_1, \varphi_1\right)=\int\limits_0^{2 \pi} p\left(\theta_1, \varphi_1, \psi\right) \mathrm{d} \psi$

为呈现BRTM结果，使用Lambert等面积投影(下半球)，在三维球体中利用颜色分布(图3(b))来表示σ₁和σ₃的概率p_σ₁和p_σ₃，其中红色表示p_σ₁值较高，蓝色表示p_σ₃值较高，白色表示p_σ₁和p_σ₃值均较低(即σ₂轴概率高)。图3(a)为包含3个震源机制解数据集的计算结果，红色和蓝色三角形分别代表σ₁和σ₃方向。

2.3 数据融合

为有效整合极性数据和震源机制数据，采用权重分配策略，根据综合震源机制方法使用的极性数据量来分配权重。设定震源机制解和极性数据的权重比为1 ∶100，如果用于计算综合震源机制的数据量在100N~100(N+1)之间，则将综合震源机制方法的反演结果视为N个震源机制解，作为BRTM方法的输入，从而增加可用数据量，同时也能降低由于数据量不足导致的结果不确定性。

3 结果分析

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采用3种策略求解应力场参数，3种策略选用相同的计算参数，均以1°×1°划分格网点，并以150 km为半径选取数据。采用综合震源机制方法计算时，选取最小极性数据为100，距离衰减常数为50 km；BRTM反演时，最小震源机制解数量设置为5。仅使用震源机制解数据时得到102个格网点结果，采用极性数据的综合震源机制方法得到114个格网点结果，通过数据融合方式计算得到125个格网点结果。相较于震源机制解数据，极性数据更为丰富，能够计算出更多的格网点，将两类数据进行融合后，能进一步增加可计算的格网点数量。

图4为3种方法的计算结果对比，采用与震源机制分类类似的方法，根据Kaverina等^[25]的分类原则将应力参数分为3类：拉张(红色)、挤压(蓝色)、剪切(绿色)。图4(a)为利用震源机制解的BRTM获得的应力场结果，图4(b)为利用极性数据的综合震源机制方法得到的结果，图4(c)为数据融合后应用BRTM得到的结果。可以看出，3种方法的计算结果整体上呈现出较高的一致性，但在局部区域仍存在一些差异。图4(a)中东部地区有更多区域表现为剪切特征，而图4(b)中东部地区主要为拉张性质。

对于使用P波极性数据是否能获得可靠的应力场信息，以往的讨论有限，因此本文对基于震源机制解数据的BRTM结果与综合震源机制方法结果进行对比，以评估2种方案的差异。图5分别为2种方法计算结果中不同参数的差异对比，包括应力轴的方位角、仰角和空间夹角(结果越接近夹角越小)。其中，图5(a)为BRTM和综合震源机制方法在σ₁轴方位角上的差值分布，可见差值集中在30°以下，表明2种方法在该参数上的差异较小；图5(b)为σ₃轴方位角差异，大部分差值同样集中在30°以下，差异较小；图5(c)为σ₁轴仰角差异，差值主要集中在20°以下，表明2种方法在σ₁轴仰角上的差异较为微小；图5(d)为σ₃轴仰角差异，差值总体集中在20°以下，部分区域差值较大；图5(e)为σ₁轴夹角差异，差值大多在40°以下，少部分区域差值较大；图5(f)为σ₃轴夹角差异，差值分布与σ₁轴相似，集中在40°以下。由此可见，BRTM和综合震源机制方法在不同参数上的差异总体较小，大部分集中在30°或20°以下，表明2种方法在多数情况下可得到一致的结果，个别区域仍存在差异，说明综合震源机制方法获得的应力场结果是可靠的。

在将数据进行融合并应用BRTM反演之后，可得到更多格网点结果，理论上能降低结果的不确定性。图6(a)为应力轴σ₁和σ₃的概率分布(颜色分布见图3(b))；图6(b)为Φ_B值^[30]的分布情况。Φ_B是描述应力椭球形状的参数，可反映主应力之间的相对大小关系，用于分析地质现象，表达式为：

(7)

$\mathit{Φ}_B=\frac{\sigma_2-\sigma_3}{\sigma_1-\sigma_3}$

Φ_B值介于0~1之间，接近0表示最大主应力占主导，易形成正断层；接近1则表示最小主应力占主导，易形成逆断层；接近0.5表示应力较均匀，易形成走滑断层。低应力比倾向于脆性变形，高应力比则倾向于韧性变形。图7为不同Φ_B值的应力椭球图示，其中Φ_B值较高可能与压缩环境有关(图7(c))，Φ_B值较低可能与拉张环境有关(图7(a))。通过分析Φ_B值的空间分布，识别高值区和低值区，可分析其与地质构造单元的关系，了解应变场的分布和变化特征。由图6(b)可知，内蒙古西部和东部局部区域Φ_B值较高，内蒙古中部和中东部区域Φ_B值较低。

图8为σ₁和σ₃轴的空间分布，每个格网点用正交投影显示，红色线段表示最大主应力，蓝色线段表示最小主应力，在正交投影下，线段的方向表示应力轴的方位角，线段的长度表示应力轴的仰角(与仰角负相关)。内蒙古东部地区的最大主应力方向在空间上呈现旋转趋势，东北部σ₁轴的方位角为NE向，由北至南逐渐旋转为东南部的NW向。该区域应力场受板块运动的影响，太平洋板块、菲律宾海板块和印度洋板块的共同作用形成NEE向应力场，其中太平洋板块的俯冲应力场起主导作用^[31-32]。二连盆地、海拉尔盆地和松辽盆地表现出拉张特征，主张应力方向为NW向，垂直于大兴安岭走向。大兴安岭是中国东部中生代岩浆岩带的西部边界，是一条上地幔内部的构造变异带^[33-34]，大兴安岭主脊断裂带表现为剪切特征，可能与构造单元之间的相对作用有关。大洋板块俯冲于东亚陆缘带岩石圈地幔，产生的挤压应力场可能延伸至大兴安岭重力梯级带附近^[35]，这种影响以挤压为主，同时伴随拉张应力和间接产生的垂向应力，局部区域表现为逆冲特征。大兴安岭盆岭构造是中国东部中生代典型盆-岭构造体系的一部分，包括大兴安岭及其两侧的二连盆地、海拉尔盆地和松辽盆地，反映了上地壳相对于中、下地壳的大规模拆离^[36]，大兴安岭两侧的拉张应力特征可能与俯冲造成的热物质上涌有关。

鄂尔多斯地块北缘的应力场结果与已有研究具有较好的一致性^[17]，主要表现为拉张性质。σ₁轴应力场分布较为复杂，方位角主要为NNE和NS向，局部区域为近EW向。S波分裂结果显示，该区域背景主压应力方向总体上为近NS向，但不同区域存在一定差异^[37]。鄂尔多斯地块的逆时针旋转运动可能来自于岩石圈和软流圈的驱动^[38]。鄂尔多斯地块周缘地区的应力状态以拉张为主，局部区域表现为剪切、挤压特征^[39]。在鄂尔多斯地块东北缘地区，深部物质上涌形成的拉张起主导作用，形成了岱海断陷带内沿NEE向展布的张性或张扭性正断层^[40]。河套地震带的震源机制和应力场特征显示，垂直差异性和水平剪切运动共同控制着该区应力场^[41]。软流圈物质的水平和垂直运动对鄂尔多斯地块周缘断陷盆地的运动特征具有显著影响，这种运动有利于不同方位盆地的剪切走滑、伸展拉张或走滑兼拉张，进而影响该地块及其周缘地区的构造演化^[42]。

阿拉善地块应力场与已有研究结果一致^[17]，表现为剪切特征，与阿拉善地块和鄂尔多斯地块的相对运动有关^[43]，σ₁轴方位角主要为NE向，与青藏地块NE向推挤作用有关。阿拉善地块向东运动，内部发育的近EW向右行走滑构造属过程中的调节构造^[44]。

4 结语

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本文运用内蒙古地区728个震源机制解和14 460条地震P波极性数据，通过综合震源机制、BRTM和数据融合等3种策略研究地壳应力状态，获得以下认识：

1) 对比基于极性数据的综合震源机制方法和基于震源机制解的BRTM，结果显示，二者具有较高的一致性，表明综合震源机制方法获得的结果具有可靠性。

2) 通过将极性数据与震源机制解数据进行加权融合，可扩充用于计算的格网点数量，并以概率的形式呈现结果的不确定性，能够在一定程度上克服震源机制解数据的有限性问题，可为数据稀缺地区的应力场研究提供一种有效的数据扩充手段。

3) 内蒙古地区应力场在空间分布上呈现出显著的异质性，最大主应力方位角在不同区域存在明显差异，最小主应力方位角则比较收敛。内蒙古东部地区应力场呈现出剪切和拉张的复合特性，两侧盆地主要表现为拉张特征，这可能与俯冲作用导致的热物质上涌有关。鄂尔多斯地块北缘应力场则主要表现为拉张性质，这与深部地幔物质上涌、地壳变薄及区域性拉张作用有关。阿拉善地块应力场主要表现为剪切性质，这可能与地块的相对运动和相互作用有关。

基金

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内蒙古自治区自然科学基金(2024MS04021)
内蒙古自治区地震局局长基金(2023GG02)

参考文献

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2025年第45卷第3期

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doi: 10.14075/j.jgg.2024.04.172

接收时间：2024-04-14
首发时间：2026-10-30
出版时间：2025-03-15

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收稿日期：2024-04-14

基金

Natural Science Foundation of Inner Mongolia Autonomous Region(2024MS04021)

内蒙古自治区自然科学基金(2024MS04021)

Director Fund of Earthquake Agency of Inner Mongolia Autonomous Region(2023GG02)

内蒙古自治区地震局局长基金(2023GG02)

作者信息

1 华北电力大学控制与计算机工程学院, 北京市北农路2号, 102206

2 内蒙古自治区地震局, 呼和浩特市哲里木路80号, 010010

3 华北电力大学数理学院, 北京市北农路2号, 102206

通讯作者:

崔丰智，助理工程师，主要研究方向为地震预测方法，E-mail: fengzhicui66@163.com

CUI Fengzhi, assistant engineer, majors in earthquake prediction methods, E-mail: fengzhicui66@163.com

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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