C4植物狗尾草功能性状网络沿降水梯度带的区域分异规律

doi:10.17521/cjpe.2024.0388

植物生态学报 ›› 2025, Vol. 49 ›› Issue (11): 1817-1832.DOI: 10.17521/cjpe.2024.0388 cstr: 32100.14.cjpe.2024.0388

C₄植物狗尾草功能性状网络沿降水梯度带的区域分异规律

童金莲¹, 张博纳¹, 汤璐瑶¹, 叶琳峰¹, 李姝雯¹, 谢江波¹^,², 李彦¹^,², 王忠媛¹^,²^,^*()

¹浙江农林大学省部共建亚热带森林培育国家重点实验室, 浙江农林大学林业与生物技术学院, 杭州 311300
²中国科学院新疆生态与地理研究所荒漠与绿洲生态国家重点实验室, 乌鲁木齐 830011

收稿日期:2024-10-31 接受日期:2025-01-10 出版日期:2025-11-20 发布日期:2025-11-20
通讯作者: *王忠媛(wangzhongyuan2014@163.com)
基金资助:
国家自然科学基金(32371662);国家自然科学基金(42330503);浙江省科技厅重大专项(2022C02019)

Regional differentiation of functional trait network of C₄ plants Setaria viridis along precipitation gradient

TONG Jin-Lian¹, ZHANG Bo-Na¹, TANG Lu-Yao¹, YE Lin-Feng¹, LI Shu-Wen¹, XIE Jiang-Bo¹^,², LI Yan¹^,², WANG Zhong-Yuan¹^,²^,^*()

¹State Key Laboratory of Subtropical Silviculture, College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou 311300, China
²State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Ürümqi 830011, China

Received:2024-10-31 Accepted:2025-01-10 Online:2025-11-20 Published:2025-11-20
Supported by:
National Natural Science Foundation of China(32371662);National Natural Science Foundation of China(42330503);Major Special Project of Department of Science and Technology of Zhejiang Province(2022C02019)

摘要/Abstract

摘要： 揭示广布种功能性状及其适应策略的区域分异规律, 对预测植物在气候变化下的适应潜力具有重要意义。该研究以广布种狗尾草(Setaria viridis)为实验对象, 沿降水梯度带选取9个样点, 测量了狗尾草茎和叶器官水碳相关的18个功能性状, 采用性状网络与主成分分析等方法, 阐明其生境适应策略。结果表明: (1)狗尾草在湿润区具有最大的导管直径和比叶质量; 在半湿润/半干旱区具有最高的单位面积最大净光合速率、解剖学最大气孔导度和气孔面积分数; 在干旱区具有最大的导管厚度跨度比和单位质量最大净光合速率; 反映了狗尾草在不同区域的适应策略。(2)随着降水的减少, 性状之间的关联变少, 网络的连通性降低, 复杂性增加。性状间正相关关系占比在半湿润/半干旱区达到最大, 此时植物性状间表现出最佳的协作关系, 可能与此区域水、光资源配置达到平衡有关。(3) 9个样点性状网络的结果表明狗尾草沿降水梯度带的适应主要由气孔性状调控。该研究对预测气候变化背景下的植物/植被响应及其潜在适应机制具有重要意义。

关键词: 植物功能性状, 性状变异, 适应策略, 广布种, 狗尾草, 降水梯度带

Abstract:

Aims Revealing the regional differentiation of functional traits and their adaptative strategies of widely distributed species is of great ecological significance for predicting the adaptation of plants under climate change.

Methods Setaria viridiswas studied for its 18 water-carbon-related stem and leaf traits in 9 study sites along the precipitation gradient from southeast to northwest China. The trait network analysis and principal component analysis were used to quantify the regional differentiation of traits to clarify their habitat adaptative strategies.

Important findings (1) In humid regions, Setaria viridis exhibited the largest vessel diameter and specific leaf mass; in the semiarid/semihumid region, Setaria viridis exhibited the highest maximum net photosynthetic rate per unit leaf area, anatomical maximum stomatal conductance and stomatal area fraction; in arid regions, Setaria viridis exhibited the highest thickness-to-span ratio of vessel and maximum net photosynthetic rate per unit leaf mass. These trait variations revealed the adaptative strategies of Setaria viridis in different regions. (2) Both the correlations between traits and the connectivity of the network decreased with the decrease of precipitation, while the complexity of the network increased. The proportion of positive correlations among the trait network reached the maximum in the semiarid/semihumid regions, showing the best cooperative relationship between plant traits, which may be related to the balanced allocation of water and light resources in this region. (3) The trait network of nine sites indicated that the adaptation of Setaria viridis along the precipitation gradient was mainly regulated by stomatal traits. This study helps us to reveal the mechanisms of plant adaptation under the background of climate change.

Key words: plant functional trait, trait variation, adaptive strategy, widely distributed species, Setaria viridis, precipitation gradient

童金莲, 张博纳, 汤璐瑶, 叶琳峰, 李姝雯, 谢江波, 李彦, 王忠媛. C₄植物狗尾草功能性状网络沿降水梯度带的区域分异规律. 植物生态学报, 2025, 49(11): 1817-1832. DOI: 10.17521/cjpe.2024.0388

TONG Jin-Lian, ZHANG Bo-Na, TANG Lu-Yao, YE Lin-Feng, LI Shu-Wen, XIE Jiang-Bo, LI Yan, WANG Zhong-Yuan. Regional differentiation of functional trait network of C₄ plants Setaria viridis along precipitation gradient. Chinese Journal of Plant Ecology, 2025, 49(11): 1817-1832. DOI: 10.17521/cjpe.2024.0388

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2024.0388

https://www.plant-ecology.com/CN/Y2025/V49/I11/1817

图/表 9

表1 9个狗尾草研究样点地理概况及气候特征

Table 1 Environmental features and climatic characteristics of the nine study sites

区域 Region	样点 Site	缩写 Abbreviation	LON (° E)	LAT (° N)	MAP (mm)	GST (℃)	PAR (mol·m^-2·d^-1)	AI
湿润区 Humid zone	安徽宣城 Xuancheng, Anhui	AHXC	118.78	30.34	1 394.61	25.31	38.41	1.12
	安徽六安 Luan, Anhui	AHLA	115.44	31.53	1 134.24	25.22	40.03	1.19
	河南信阳 Xinyang, Henan	HNXY	113.85	32.07	1 082.29	24.74	40.16	1.92
半湿润/半干旱区 Semiarid/semihumid zone	河南三门峡 Sanmenxia, Henan	HNSMX	110.54	34.49	555.64	23.81	41.09	3.78
	陕西铜川 Tongchuan, Shaanxi	SXTC	109.14	35.40	584.43	20.29	44.17	2.69
	宁夏吴忠 Wuzhong, Ningxia	NXWZ	105.78	36.46	235.59	20.50	49.76	6.80
干旱区 Arid zone	甘肃张掖 Zhangye, Gansu	GSZY	100.18	39.23	131.72	19.55	50.26	13.88
	甘肃酒泉 Jiuquan, Gansu	GSJQ	98.64	39.67	81.85	19.18	51.96	21.57
	新疆哈密 Hami, Xinjiang	XJHM	93.45	42.62	44.17	23.37	54.47	40.88

表2 本研究中所测量的功能性状

Table 2 List for traits related to this study

性状 Trait	缩写 Abbreviation	单位 Unit
最大净光合速率(光饱和CO₂同化率) Maximum net photosynthetic rate	P_n	µmol·m^-2·s^-1
最大蒸腾速率 Maximum transpiration rate	T_r	mmol·m^-2·s^-1
最大可操作气孔导度 Maximized operational stomatal conductance	G_s	mol·m^-2·s^-1
水分利用效率 Water use efficiency	WUE	μmol·mmol⁻¹
比叶质量 Leaf mass per unit area	LMA	g·m^-2
单位质量最大净光合速率 Maximum net photosynthetic rate per unit leaf mass	A_mass	µmol·g^-1·s^-1
叶脉密度 Vein density	V_d	mm·mm^-2
气孔密度 Stomatal density	S_d	pore·mm^-2
气孔大小 Stomatal size	S_s	μm²
气孔面积分数 Stomatal area fraction	S_f	%
解剖学最大气孔导度 Anatomical maximum stomatal conductance	g_smax	mol·m^-2·s^-1
气孔打开比率 Stomatal opening ratio	g_ratio	%
叶导管直径 Leaf vessel diameter	D_leaf	μm
叶导管壁厚 Leaf thickness of vessel wall	TW_leaf	μm
叶导管厚度跨度比 Leaf thickness-to-span ratio	(t/b)_leaf	μm·μm^-1
茎导管直径 Stem vessel diameter	D_stem	μm
茎导管壁厚 Stem thickness of vessel wall	TW_stem	μm
茎导管厚度跨度比 Stem thickness-to-span ratio	(t/b)_stem	μm·μm^-1

图1 狗尾草功能性状在不同样点和干湿区间的差异。不同小写字母表示样点间差异显著(p < 0.05), 不同大写字母表示干湿区间差异显著(p < 0.05)。实线为平均值, 虚线为中值。样点和功能性状缩写见表1和表2。AR, 干旱区; HR, 湿润区; SASHR, 半湿润/半干旱区。

Fig. 1 Difference in Setaria viridis functional traits among different study sites and regions. Different lowercase letters indicate significance difference among study sites (p < 0.05), and different uppercase letters indicate significant difference among regions (p < 0.05). The solid line is the mean and the dotted line is the median. Site names the full functional trait names can be found in Table 1 and Table 2. AR, arid region; HR, humid region; SASHR, semiarid/semihumid region.

图2 狗尾草功能性状在9个样点间的平均变异系数(A)及嵌套方差分析(B)。功能性状缩写见表2。

Fig. 2 Coefficient of variation in Setaria viridis traits among the nine studied sites (A) and variance components of the studied traits based on nested ANOVAs (B). The full trait names can be found in Table 2.

图3 狗尾草18个功能性状在主成分分析(PCA)前两轴的空间中的分布(A)及各样点和干湿区在第一轴得分上的差异(B, 平均值±标准误)。不同小写字母表示样点间差异显著(p < 0.05), 不同大写字母表示干湿区间差异显著(p < 0.05)。样点缩写见表1。功能性状缩写见表2。AR, 干旱区; HR, 湿润区; SASHR, 半湿润/半干旱区。

Fig. 3 The first two principal components analysis (PCA) axes of the 18 functional traits in Setaria viridis (A), and the scores of the first principal components analysis (PCA) axis among different study sites and regions (B, mean ± SE). Different lowercase letters indicate significance difference among study sites (p < 0.05), and different uppercase letters indicate significant difference among regions (p < 0.05). Full site names can be found in Table 1, and full functional trait names can be found in Table 2. AR, arid region; HR, humid region; SASHR, semiarid/semihumid region.

图4 狗尾草功能性状网络图。红圈标记为中心性状, 蓝圈标记为中介性状。边的长度代表性状间的距离, 红色和灰色连接线分别代表正相关关系和负相关关系, 线越粗则相关性越强。相同颜色的性状代表在同一模块。样点缩写见表1。功能性状缩写见表2。

Fig. 4 Trait network of Setaria viridis at each study site. The hub trait is labeled as red circles, and the intermediate trait is labeled as blue circles. The length of the edge represents the distance between the traits. Red and gray lines represent positive and negative correlations, respectively. Thicker lines indicate stronger correlations. The traits from the same module is represented in same color. Site names are shown in Table 1. Functional trait names are shown in Table 2.

表3 9个样点狗尾草功能性状网络的差异

Table 3 Differences of functional trait networks of Setaria viridis in 9 study sites

样点 Site	平均路径长度 Average path length	边密度 Edge density	模块度 Modularity	边数量 Edge number	权衡边比例 Trade-off edge ratio (%)
安徽宣城 Xuancheng, Anhui	1.22	0.44	0.09	67	52
安徽六安 Luan, Anhui	1.84	0.40	0.22	61	39
河南信阳 Xinyang, Henan	1.76	0.41	0.35	62	45
河南三门峡 Sanmenxia, Henan	1.11	0.31	0.31	48	15
陕西铜川 Tongchuan, Shaanxi	2.88	0.20	0.46	31	35
宁夏吴忠 Wuzhong, Ningxia	2.23	0.30	0.23	46	30
甘肃张掖 Zhangye, Gansu	2.40	0.31	0.36	48	46
甘肃酒泉 Jiuquan, Gansu	2.85	0.22	0.46	33	39
新疆哈密 Hami, Xinjiang	1.71	0.18	0.53	27	52
整体 Whole	1.17	0.83	0.08	127	37

图5 年降水量与狗尾草功能性状网络平均路径长度(A)、边密度(B)、模块度(C)、边数量(D)和权衡边比例(E)的关系。ns, p > 0.05。样点名称见表1。

Fig. 5 Relationship of mean annual precipitation and average path length (A), edge density (B), modularity (C), edge number (D) and trade-off edge number (E) of trait coordination network of Setaria viridis. ns, p > 0.05.

图6 狗尾草功能性状变异系数与平均度(A)、平均介数(B)、平均紧密度(C)的关系以及平均度与平均紧密度的关系(D)。ns, p > 0.05。

Fig. 6 Relationship of coefficient of variation of traits and average degree (A), average betweenness (B), average closeness (C), and the relationship between average degree and average closeness (D). ns, p > 0.05.

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C₄植物狗尾草功能性状网络沿降水梯度带的区域分异规律

Regional differentiation of functional trait network of C₄ plants Setaria viridis along precipitation gradient

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