太行山7种药用植物性状特征及其对土壤因子的响应

郭文芳; 陈艳梅; 高飞; 王佳乐

doi:10.12153/j.issn.1674-991X.20230694

太行山7种药用植物性状特征及其对土壤因子的响应

doi: 10.12153/j.issn.1674-991X.20230694

河北师范大学地理科学学院，河北省环境变化遥感识别技术创新中心，河北省环境演变与生态建设重点实验室

基金项目: 国家重点研发计划项目(2021YFB3901104)

详细信息

作者简介:
郭文芳(1999—)，女，硕士研究生，主要从事植被建设与土壤修复研究，2495610042@qq.com

通讯作者:
陈艳梅(1970—)，女，教授，博士，主要从事区域生态系统评估、生态安全与生态补偿机制研究，chenyanmei@hebtu.edu.cn

中图分类号: Q948
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- 被引次数: 0
出版历程
- 收稿日期: 2023-09-24
- 录用日期: 2023-12-28
- 修回日期: 2023-11-13
- 网络出版日期: 2024-02-02

Traits of seven medicinal plants in Taihang Mountains and their responses to soil factors

Hebei Technology Innovation Center for Remote Sensing Identification of Environmental Change, Hebei Key Laboratory of Environmental Change and Ecological Construction, College of Geographical Sciences, Hebei Normal University

摘要

摘要:
为深入了解植物在适应环境的过程中逐渐形成的性状差异及其影响因素，选择太行山地区常见的7种药用植物挂金灯（Alkekengi officinarum）、蕺菜（Houttuynia cordata）、艾（Artemisia argyi）、活血丹（Glechoma longituba）、枸杞（Lycium chinense）、忍冬（Lonicera japonica）和薄荷（Mentha canadensis）为研究对象，通过测定植物光合、结构性状及土壤理化性质，分析不同植物性状差异及其对土壤因子的响应。结果表明：太行山7种药用植物中，薄荷和枸杞表现出较优的性状组合，其光合速率与叶干物质含量较高，蒸腾速率与比叶面积较低，且枸杞的根冠比显著高于其他植物。Spearman相关性分析表明，叶片蒸腾速率、气孔导度与叶干物质含量、植物单株生物量呈显著负相关，胞间CO₂浓度与叶片相对含水率呈显著正相关，水分利用效率与比叶面积呈显著负相关。太行山坡地7种药用植物性状变化主要来源于种间变异，光合和结构性状种间变异系数为11.08%~164.42%，除植物单株生物量和根冠比表现为强变异外，其他性状均表现为中等变异；不同性状种内变异系数平均为28.75%，处于较低水平。植物性状与土壤因子的RDA分析结果表明，土壤pH、黏粒含量对植物性状变异的解释率之和达72.30%，是影响7种药用植物性状特征的主要土壤因子，且电导率与土壤pH、黏粒含量间呈显著正相关；通过因子分析得出，有机碳、全氮、碳氮比与挂金灯、薄荷、艾、枸杞性状变化的相关性较大，土壤含水量与活血丹性状变化相关性较大。综上，太行山地区7种药用植物性状差异明显，可以通过土壤pH、土壤颗粒组成及电导率等影响植物性状，应针对特定的植物品种，进行有差别的土壤改良。
- 药用植物 /
- 性状差异 /
- 适应策略 /
- 土壤因子 /
- 太行山
Abstract:
In order to understand the trait differences of plants gradually formed during the process of adapting to the environment and their influencing factors, seven medicinal plants commonly found in Taihang Mountains were selected as the research objects, including Alkekengi officinarum, Houttuynia cordata, Artemisia argyi, Glechoma longituba, Lycium chinense, Lonicera japonica and Mentha canadensis. The plant photosynthesis, structural traits and soil physicochemical properties were measured to analyze the trait differences and their responses to soil factors. The results showed that among the seven medicinal plants, Mentha canadensis and Lycium chinense showed superior trait combinations, with higher photosynthetic rate and leaf dry matter content, and lower transpiration rate and specific leaf area; the root-to-shoot ratio of Lycium chinense was significantly higher than other plants. Spearman correlation analysis showed that leaf transpiration rate and stomatal conductance were significantly negatively correlated with leaf dry matter content and plant biomass per plant. There was a significant positive correlation between intercellular CO₂ concentration and leaf relative water content, while there was a significant negative correlation between water use efficiency and specific leaf area. The changes in the traits of the seven medicinal plants on Taihang Mountain slope mainly came from interspecific variation, with the variation coefficient of photosynthetic and structural traits ranging from 11.08% to 164.42%. Except for strong variation in plant biomass per plant and root-to-shoot ratio, all other traits showed moderate variation. The average intraspecific variation coefficient of different traits was 28.75%, which was at a low level. The RDA analysis of plant traits and soil factors showed that the sum of the explanatory rates of soil pH and clay content on plant trait variation was 72.30%, which was the main soil factor affecting the traits of the seven medicinal plants, and the soil conductivity was significantly positively correlated with soil pH and clay content. Through factor analysis, the organic carbon, total nitrogen, and C/N ratio were more correlated with the changes of the traits of Alkekengi officinarum, Mentha canadensis, Artemisia argyi and Lycium chinense, and the soil moisture was more correlated with that of Glechoma longituba. In summary, the traits of the seven medicinal plants were obviously different in Taihang Mountains, which could be affected by soil pH, soil particle composition, soil conductivity, and so on. Differentiated soil improvements should be carried out for specific plant varieties.
- medicinal plants /
- traits differences /
- adaptation strategies /
- soil factors /
- Taihang Mountains

HTML全文

图 1 7种药用植物光合性状差异分析（平均值±标准差）

Ao—挂金灯; Hc—蕺菜; Aa—艾; Gl—活血丹; Lc—枸杞; Lj—忍冬; Mc—薄荷。全文同。注：图中不同小写字母表示Y左轴指标在不同药用植物间差异显著，不同大写字母表示Y右轴指标在不同药用植物间差异显著（P<0.05）。

Figure 1. Analysis of differences in photosynthetic traits of seven medicinal plants （mean ± SE)

下载: 全尺寸图片幻灯片

图 2 7种药用植物结构性状差异分析（平均值±标准差）

Figure 2. Analysis of differences in structural traits of seven medicinal plants (mean ± SE)

下载: 全尺寸图片幻灯片

图 3 7种药用植物光合与结构性状的Spearman相关分析

注：*表示P<0.05，**表示P<0.01。全文同。

Figure 3. Spearman correlation analysis of photosynthetic and structural traits of seven medicinal plants

下载: 全尺寸图片幻灯片

图 4 7种药用植物结构土壤理化性质差异分析（平均值±标准差）

Figure 4. Analysis of differences in soil physical and chemical properties of seven medicinal plants (mean ± SE)

下载: 全尺寸图片幻灯片

图 5 7种药用植物性状特征与土壤因子的RDA分析

Figure 5. RDA analysis of seven medicinal plants traits and soil factors

下载: 全尺寸图片幻灯片

表 1 7种药用植物光合性状变异系数

Table 1. Coefficients of variation for photosynthetic traits of seven medicinal plants %　

种类		T_r	P_n	C_i	G_s	WUE
种内变异	Ao	2.23	8.94	1.30	3.84	11.02
	Hc	5.49	11.34	0.32	9.73	5.74
	Aa	7.78	15.68	1.09	4.37	20.34
	Gl	12.18	5.33	1.02	9.25	13.40
	Lc	26.16	15.64	3.35	32.30	30.32
	Lj	131.00	62.38	20.58	136.84	60.63
	Mc	92.19	54.23	16.25	109.12	47.98
种间变异		44.90	41.99	11.08	50.99	68.87

下载: 导出CSV

表 2 7种药用植物结构性状变异系数

Table 2. Coefficients of variation for structural traits of seven medicinal plants %　

种类		SLA	LDMC	RWC	R/S	WAF	TB
种内变异	Ao	13.60	3.15	8.16	30.25	8.53	82.74
	Hc	32.34	25.52	5.49	111.00	3.91	68.03
	Aa	18.98	13.04	12.38	22.99	3.88	42.45
	Gl	12.46	6.16	7.24	12.93	15.18	25.05
	Lc	22.02	24.30	3.55	71.42	4.50	97.99
	Lj	29.83	14.37	10.11	76.22	4.74	19.88
	Mc	26.16	7.08	9.22	112.80	0.97	107.48
种间变异		48.89	43.75	14.35	134.19	16.18	164.42

下载: 导出CSV

表 3 土壤部分指标间相关性分析

Table 3. Correlation analysis between some soil indicators

指标	pH	EC	TOC	CLA
pH	1
EC	0.443^*	1
TOC	−0.282	0.152	1
CLA	0.450^*	0.529^**	0.096	1

下载: 导出CSV

表 4 各主成分旋转载荷、特征值及贡献率

Table 4. Rotational load, eigenvalue and contribution rate of each principal component

指标	第1主成分	第2主成分	第3主成分
T_r	0.468	0.862	0.056
P_n	−0.016	0.933	0.035
C_i	0.707	0.566	0.124
G_s	0.346	0.92	0.014
SLA	0.897	0.098	−0.126
LDMC	−0.882	−0.334	−0.180
RWC	0.859	0.136	0.013
R/S	0.022	0.049	0.996
特征值	3.160	2.923	1.061
贡献率/%	39.502	36.535	13.267
累计贡献率/%	39.502	76.037	89.304

下载: 导出CSV

表 5 各植物性状综合得分（F）与土壤因子的相关性

Table 5. Correlation between comprehensive scores (F) of plant traits and soil factors

项目	pH	SWC	EC	TN	TOC	CLA	C/N
F(Ao)	0.612	−0.547	0.980^**	0.258	0.582	0.966^*	0.951^*
F(Hc)	−0.826	0.508	0.978^*	0.403	−0.807	0.319	−0.535
F(Aa)	−0.200	−0.400	0.977^*	0.929^*	0.939^*	0.049	−0.866
F(Gl)	−0.362	0.996^**	0.965^*	−0.337	−0.458	0.612	0.034
F(Lc)	0.731	−0.266	0.761	0.978^*	0.338	0.747	−0.568
F(Lj)	0.266	−0.349	−0.652	−0.628	0.762	−0.686	0.707
F(Mc)	0.612	−0.547	0.980^**	0.258	0.582	0.966^*	0.951^*

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