生境因子和系统发育协同驱动云南金沙江干热河谷植物叶片化学计量特征

doi:10.17521/cjpe.2025.0179

植物生态学报 ›› 2026, Vol. 50 ›› Issue (2): 352-361.DOI: 10.17521/cjpe.2025.0179 cstr: 32100.14.cjpe.2025.0179

生境因子和系统发育协同驱动云南金沙江干热河谷植物叶片化学计量特征

冯哲¹^,³, 许格希¹^,³, 刘顺¹^,³, 陈健¹^,³, 李非凡¹^,³, 巩闪闪¹^,³, 贾磊¹^,³, 孙镇¹^,³, 余美霓¹^,³, 史作民¹^,²^,³^,^*(), 周庆宏⁴, 蒋冬梅⁴

¹ 中国林业科学研究院森林生态环境与自然保护研究所, 森林生态系统保护修复国家林业和草原局重点实验室, 北京 100091
² 南京林业大学)江苏省南方现代林业协同创新中心, 南京 210037
³ 中国林业科学研究院森林生态环境与自然保护研究所四川米亚罗森林生态系统定位观测研究站, 四川理县 623100
⁴ 楚雄彝族自治州林业和草原科学研究所, 云南楚雄 675005

收稿日期:2025-05-16 接受日期:2025-08-25 出版日期:2026-02-28 发布日期:2026-04-01
通讯作者: *史作民(shizm@caf.ac.cn)
基金资助:
云南省科技人才与专家计划(202305AF150100);国家重点研发计划(2023YFD2200404-03);国家重点研发计划(2021YFD2200405)

Habitat factors and phylogeny jointly drive leaf stoichiometry in dry-hot valley region of Jinsha River, Yunnan, China

FENG Zhe¹^,³, XU Ge-Xi¹^,³, LIU Shun¹^,³, CHEN Jian¹^,³, LI Fei-Fan¹^,³, GONG Shan-Shan¹^,³, JIA Lei¹^,³, SUN Zhen¹^,³, YU Mei-Ni¹^,³, SHI Zuo-Min¹^,²^,³^,^*(), ZHOU Qing-Hong⁴, JIANG Dong-Mei⁴

¹ Key Laboratory of National Forestry and Grassland Administration on Forest Ecosystem Protection and Restoration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
² Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing 210037, China
³ Sichuan Miyaluo Forest Ecosystem Observation and Research Station, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Lixian, Sichuan 623100, China
⁴ Chuxiong Research Institute of Forestry and Grassland, Chuxiong, Yunnan 675005, China

Received:2025-05-16 Accepted:2025-08-25 Online:2026-02-28 Published:2026-04-01
Contact: *SHI Zuo-Min (shizm@caf.ac.cn)
Supported by:
Yunnan Provincial Science and Technology Talent and Expert Program(202305AF150100);National Key R&D Program of China(2023YFD2200404-03);National Key R&D Program of China(2021YFD2200405)

摘要/Abstract

摘要：

植物元素组成及其化学计量特征对于理解植物养分策略与生态系统生物地球化学循环至关重要。尽管“生物地球化学生态位假说”和“化学计量可塑性假说”已在宏观尺度得到验证, 但在极端胁迫环境中, 特别是在考虑系统发育保守性时, 其适用性仍不确定。该研究采集了金沙江干热河谷区5个地点13种共240个灌木和草本植物叶片样本, 测定了其碳(C)、氮(N)、磷(P)化学计量特征及对应土壤理化性质。通过贝叶斯系统发育线性混合模型等方法, 定量评估了生境因子与系统发育对叶片化学计量特征变异的相对贡献, 并探讨了主要生境因子对叶片养分利用策略的调控机制。结果表明, 生境因子对叶片化学计量特征变异的解释度较低, 其中海拔是叶片C、P含量及C:P、N:P的主要驱动因子, 土壤pH则主导叶片N含量和C:N的变化。系统发育分析显示, 叶片N、P含量及C:N、C:P表现出显著的系统发育信号, 贝叶斯模型结果进一步支持系统发育对叶片化学计量特征的主要影响。除系统发育保守性外, 叶片C含量的差异与植物生活型有关, 而N:P则表现出较高的种内可塑性。总之, 该区域叶片化学计量格局主要受系统发育保守性控制, 并由表型可塑性加以补充。该研究有助于深化对环境胁迫条件下植物多样性维持机制的理解, 同时拓展了区域尺度上植物养分利用策略的相关认识。

关键词: 叶片化学计量, 系统发育, 表型可塑性, 生境过滤, 干热河谷

Abstract:

Aims The objective of this study was to determine whether leaf stoichiometry is predominantly shaped by habitat filtering or phylogenetic conservatism in the extreme dry-hot valley of the Jinsha River. We further evaluated the applicability of the biogeochemical niche and stoichiometric plasticity hypotheses at a regional scale.

Methods We collected 240 leaf samples from 13 shrub and herbaceous species at 5 sampling sites along the Jinsha River. Leaf carbon (C), nitrogen (N), and phosphorus (P) stoichiometric traits were measured. Corresponding soil physicochemical properties were also analyzed. Bayesian phylogenetic linear mixed models were used to quantify the relative contributions of habitat factors and phylogeny to variation in leaf stoichiometry, and to explore how major habitat gradients regulate plant nutrient use strategies.

Important findings Habitat factors collectively explained 1.9% to 13.7% of the variability in leaf elements and their stoichiometric ratios. Elevation was the primary driver of leaf C and P concentrations and of C:P and N:P, whereas soil pH was the main regulator of leaf N concentration and C:N. Importantly, significant phylogenetic signals were observed in leaf N and P concentrations, as well as in C:N and C:P, indicating the conservatism of these traits. In addition to phylogenetic constraints, we found that leaf C concentration was primarily associated with plant life form and N:P showed greater intraspecific plasticity. In conclusion, regional leaf stoichiometric patterns were governed mainly by phylogenetic conservatism and refined by phenotypic plasticity. These findings enhance our understanding of how plant diversity is maintained under habitat stress and broaden knowledge of plant nutrient-use strategies at regional scales.

Key words: leaf stoichiometry, phylogeny, phenotypic plasticity, habitat filtering, dry-hot river valley

冯哲, 许格希, 刘顺, 陈健, 李非凡, 巩闪闪, 贾磊, 孙镇, 余美霓, 史作民, 周庆宏, 蒋冬梅. 生境因子和系统发育协同驱动云南金沙江干热河谷植物叶片化学计量特征. 植物生态学报, 2026, 50(2): 352-361. DOI: 10.17521/cjpe.2025.0179

FENG Zhe, XU Ge-Xi, LIU Shun, CHEN Jian, LI Fei-Fan, GONG Shan-Shan, JIA Lei, SUN Zhen, YU Mei-Ni, SHI Zuo-Min, ZHOU Qing-Hong, JIANG Dong-Mei. Habitat factors and phylogeny jointly drive leaf stoichiometry in dry-hot valley region of Jinsha River, Yunnan, China. Chinese Journal of Plant Ecology, 2026, 50(2): 352-361. DOI: 10.17521/cjpe.2025.0179

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2025.0179

https://www.plant-ecology.com/CN/Y2026/V50/I2/352

图/表 6

图1 金沙江干热河谷采样点。HP, 华坪; LQ, 禄劝; YM, 元谋; YR, 永仁; YS, 永胜。

Fig. 1 Study sites in dry-hot valley of Jinsha River. HP, Huaping; LQ, Luquan; YM, Yuanmou; YR, Yongren; YS, Yongsheng.

表1 金沙江干热河谷采样点基本信息

Table 1 Basic information on the study sites in dry-hot valley of Jinsha River

采样地点 Study site	纬度 Latitude (° N)	经度 Longitude (° E)	海拔 Altitude (m)	年平均气温 Mean annual temperature (℃)	年降水量 Mean annual precipitation (mm)	胸高断面积 Basal area (cm²·m^-2)	草本盖度 Herb cover (%)
永胜 Yongsheng	26.20	100.62	1 297	18.3	825.0	5.85	90
华坪 Huaping	26.37	101.23	1 307	20.5	857.8	20.42	88
永仁 Yongren	26.40	101.46	1 496	18.5	925.6	34.51	93
元谋 Yuanmou	25.72	101.78	1 217	20.2	827.9	2.70	92
禄劝 Luquan	26.30	102.64	1 023	21.3	879.6	3.42	95

图2 用基于随机森林模型和五折交叉验证的递归特征消除法筛选与植物叶片化学计量特征相关的生境变量。变量的最终选择情况由浅色条目表示。深色条目表示其他次重要的预测变量, 但未用于后续分析。C, 碳; N, 氮; P, 磷。AP, 土壤有效磷含量; ELE, 海拔; MAP, 年降水量; MAT, 年平均气温; NH+ 4-N, 土壤铵态氮含量; NO- 3-N, 土壤硝态氮含量; pH, 土壤pH; SBD, 土壤容重; STC, 土壤总碳含量; STN, 土壤总氮含量; STP, 土壤总磷含量; TK, 土壤总钾含量; WC, 土壤含水量; MSE, 均方误差。

Fig. 2 Recursive Feature Elimination based on random forest and 5-fold cross-validation was used to select habitat variables associated with plant leaf stoichiometry. The final selection of variables is indicated by the light bars. Dark bars indicate additional, next most important predictors, but not used for subsequent analyses. C, carbon; N, nitrogen; P, phosphorus. AP, soil effective phosphorus content; ELE, elevation above sea level; MAP, mean annual precipitation; MAT, mean annual air temperature; NH+ 4-N, soil ammonium nitrogen content; NO- 3-N, soil nitrate nitrogen content; pH, soil pH; SBD, soil bulk density; STC, soil total carbon content; STN, soil total nitrogen content; STP, soil total phosphorus content; TK, soil total potassium content; WC, soil water content; MSE, mean squared error.

图3 使用线性混合效应模型分析叶片化学计量特征与入选变量的关系。效应强度以标准化固定效应系数表示。C, 碳; N, 氮; P, 磷。ELE, 海拔; MAP, 年降水量; MAT, 年平均气温; pH, 土壤pH; STN, 土壤总氮含量; STP, 土壤总磷含量; TK, 土壤总钾含量; WC, 土壤含水量; LMM, 线性混合效应模型。

Fig. 3 Relationships between leaf stoichiometric and the selected variables were analyzed using linear mixed effect models. Effect magnitudes are expressed as normalized fixed effect coefficients. See Fig. 2 for variable abbreviations. C, carbon; N, nitrogen; P, phosphorus. ELE, elevation above sea level; MAP, mean annual precipitation; MAT, mean annual air temperature; pH, soil pH; STN, soil total nitrogen content; STP, soil total phosphorus content; TK, soil total potassium content; WC, soil water content; LMM, linear mixed-effect model.

图4 贝叶斯系统发育线性混合模型(A)和物种变异分解结果(B)。A中“生境因子”代表固定效应(通过递归特征消除法从生境因素中选取的一部分子集)。C, 碳; N, 氮; P, 磷。

Fig. 4 Results of the Bayesian phylogenetic mixture model (A) and variance partitioning of species-level variation (B). In panel A, “Environments” represents the fixed effects (a subset of habitat factors selected through recursive feature elimination). C, carbon; N, nitrogen; P, phosphorus.

表2 植物叶片化学计量特征的系统发育信号

Table 2 Phylogenetic signals of plant leaf stoichiometric traits

	Blomberg’s K	p	Pagel’s λ	p
C	0.155	0.135	0.507	0.297
N	0.479^**	0.003	0.915^*	0.017
P	0.385^*	0.016	0.736^*	0.014
C:N	0.583^**	0.004	0.951^*	0.011
C:P	0.354^*	0.025	0.746^*	0.021
N:P	0.290	0.526	0.868	0.190

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生境因子和系统发育协同驱动云南金沙江干热河谷植物叶片化学计量特征

Habitat factors and phylogeny jointly drive leaf stoichiometry in dry-hot valley region of Jinsha River, Yunnan, China

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