岷江上游干旱河谷−山地森林交错带土壤碳氮含量及同位素的空间异质性

陈健; 陈淼; 邢红爽; 李非凡; 刘顺; 许格希; 史作民

doi:10.12356/j.2096-8884.2024-0011

岷江上游干旱河谷−山地森林交错带土壤碳氮含量及同位素的空间异质性

doi: 10.12356/j.2096-8884.2024-0011

陈健^{1, 2,},
陈淼^{1, 2},
邢红爽^{1, 2},
李非凡^{1, 2},
刘顺^{1, 2},
许格希^{1, 2},
史作民^{1, 2, 3, ,}

1.
中国林业科学研究院森林生态环境与自然保护研究所，国家林业和草原局森林生态环境重点实验室，北京 100091
2.
四川米亚罗森林生态系统国家定位观测研究站，理县 623100
3.
南京林业大学南方现代林业协同创新中心，南京 210037

基金项目: 基金项目： “十四五”国家重点研发计划课题（2023YFD2200404-03）；中央级公益性科研院所基本科研业务费专项资金项目（CAFYBB2021ZA002-2，CAFYBB2022QC002，CAFYBB2022SY021）

详细信息

作者简介:
陈健：E-mail：cafchenjian@163.com

通讯作者:
E-mail：shizm@caf.ac.cn

中图分类号: S714
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- 文章访问数: 91
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- 被引次数: 0
出版历程
- 收稿日期: 2024-01-18
- 网络出版日期: 2024-04-18
- 刊出日期: 2024-02-01

Spatial Heterogeneity of Soil Carbon and Nitrogen Contents and Isotopes in the Arid Valley-Mountain Forest Ecotone in the Upper Reaches of Minjiang River, China

Jian Chen^{1, 2
,},
Miao Chen^{1, 2},
Hongshuang Xing^{1, 2},
Feifan Li^{1, 2},
Shun Liu^{1, 2},
Gexi Xu^{1, 2},
Zuomin Shi^{1, 2, 3
, ,}

1.
Key Laboratory of Forest Ecology and Environment of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
2.
Sichuan Miyaluo Forest Ecosystem National Observation and Research Station, Lixian County 623100, China
3.
Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China

摘要

摘要: 目的探究岷江上游干旱河谷−山地森林交错带土壤碳氮循环的空间异质性及其影响机制，为该地区科学管理提供理论依据。方法于岷江上游干旱河谷与山地森林的过渡区选取具有典型代表性的橿子栎（Quercus baronii）灌木林为研究对象，基于拉丁超立方体抽样设计对样地土壤进行取样，采用经典统计学和地统计学相结合的方法分析了样地土壤碳氮含量和碳氮同位素的描述性统计特征、空间异质性、空间相似性及其相关关系。结果岷江上游干旱河谷−山地森林交错带橿子栎灌木林土壤δ¹³C和土壤δ¹⁵N分别呈现弱变异和中等程度的空间变异。土壤δ¹³C和土壤δ¹⁵N均呈现正的空间自相关关系，并且土壤δ¹³C的空间聚集性高于土壤δ¹⁵N。土壤δ¹³C的空间异质性由结构性因素主导，土壤δ¹⁵N的空间异质性受结构性因素和随机性因素共同影响。土壤δ¹³C与土壤δ¹⁵N的空间分布具有很强的相似性，并且都与土壤碳氮含量具有较强的空间关联。土壤δ¹³C与土壤δ¹⁵N具有很强的相关关系，并都受到土壤水分、碳氮含量及其比值的直接或间接影响。结论岷江上游干旱河谷−山地森林交错带橿子栎灌木林具有不同的土壤碳氮同位素空间变异程度和耦合的碳氮同位素关系。
- 干旱河谷 /
- 橿子栎 /
- 交错带 /
- 空间异质性 /
- 同位素
Abstract: Objective This study was aimed to explore the spatial heterogeneity of soil carbon (C) and nitrogen (N) cycling and its impact mechanisms of arid valley-mountain forest ecotone in the upper reaches of Minjiang River, and to provide a theoretical basis for scientific management in this region. Method A typical shrub forest of Quercus baronii was selected in the transition area between the arid valley and the mountain forest in the upper reaches of Minjiang River. Soil samples were sampled through a Latin hypercube sampling design, descriptive statistical characteristics, spatial heterogeneity, spatial similarity and correlation of soil C and N contents and their isotopes (δ¹³C and δ¹⁵N) were analyzed using a combination of classical statistics and geostatistical methods. Result The soil δ¹³C and soil δ¹⁵N of Quercus baronii shrub forest in the arid valley-mountain forest ecotone in the upper reaches of Minjiang River showed a weak and moderate spatial variability, respectively. Both soil δ¹³C and soil δ¹⁵N showed positive spatial autocorrelation, and the spatial aggregation of soil δ¹³C was higher than that of soil δ¹⁵N. The spatial heterogeneity of soil δ¹³C was dominated by structural factors, and the spatial heterogeneity of soil δ¹⁵N was jointly influenced by structural and stochastic factors. The spatial distributions of soil δ¹³C and soil δ¹⁵N were strongly similar, and were both strongly spatially correlated with soil C and N contents. Soil δ¹³C and soil δ¹⁵N were strongly correlated and were both directly or indirectly affected by soil moisture, C and N contents and C/N ratio. Conclusion The soil δ¹³C and δ¹⁵N showed different spatial variability but coupled relationship in the Q. baronii shrub forest in the arid valley-mountain forest ecotone in the upper reaches of Minjiang River.
- dry valley /
- Quercus baronii /
- ecotone /
- spatial heterogeneity /
- isotopes

HTML全文

图 1 采样点位置

注：X为样地东西方向轴，Y为样地南北方向轴。下同。X is the east-west axis of the sample plot and Y is the north-south axis of the sample plot. Same as below.

Figure 1. Distribution of soil sampling points

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图 2 土壤碳氮含量及其同位素的空间自相关关系

Figure 2. Spatial autocorrelation analysis of soil carbon and nitrogen contents and their stable isotopes

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图 3 土壤碳氮含量及其同位素的空间分布图

Figure 3. Spatial distribution of soil carbon and nitrogen contents and their stable isotopes

下载: 全尺寸图片幻灯片

图 4 土壤碳氮同位素的偏相关分析

注：Zero-order代表零阶相关分析的结果。图中星号和ns (no significance)代表显著性水平。ns，P＞0.05；*，0.01＜P＜0.05；**，0.001＜P＜0.01；***，P＜0.001。STC，土壤全碳；STN，土壤全氮；SCN，土壤碳氮比；Soil δ¹³C，土壤δ¹³C；Soil δ¹⁵N，土壤δ¹⁵N。Zero-order represents the result of zero-order correlation analysis. Asterisks and ns in the figure represent the level of significance. ns, P＞0.05; *, 0.01＜P＜0.05; **, 0.001＜P＜0.01; ***, P＜0.001. STC, soil total carbon; STN, soil total nitrogen; SCN, soil carbon to nitrogen ratio; Soil δ¹³C, the natural abundance of soil stable carbon isotopes; Soil δ¹⁵N, the natural abundance of soil stable nitrogen isotopes.

Figure 4. Partial correlation analysis of soil carbon and nitrogen stable isotopes

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图 5 土壤因子的相关分析

注：图中星号代表显著性水平，颜色与数字代表Pearson相关系数的大小。***，P＜0.001。Asterisks represent the level of significance, the color and numbers shown by Pearson's r ranging from -1 to 1 indicate the strength of the correlation. ***, P＜0.001.

Figure 5. Correlation analysis of soil factors

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表 1 土壤碳氮含量及其同位素的描述统计分析与K-S检验

Table 1. Descriptive statistical analysis and K-S test of soil carbon and nitrogen contents and their stable isotopes

指标 Parameter	平均值 Mean	标准差 Standard deviation	变异系数 CV/%	P值 P-value
土壤全碳 STC/(g·kg⁻¹)	44.162	12.526	28.365	0.540
土壤全氮 STN/(g·kg⁻¹)	3.745	1.072	28.638	0.685
土壤碳氮比 SCN	11.811	0.510	4.318	0.787
土壤δ¹³C Soil δ¹³C/‰	−25.333	0.957	3.778	0.425
土壤δ¹⁵N Soil δ¹⁵N/‰	4.957	1.082	21.833	0.575

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表 2 土壤碳氮含量及其同位素的半变异函数模型及其参数

Table 2. Parameters of semivariogram models for soil carbon and nitrogen contents and their stable isotopes

指标 Parameter	最优模型 Best model	块金值 Nugget	基台值 Sill	块金值/基台值 Nugget /Sill	变程 Range/m	决定系数 R²	残差平方和 RSS
土壤全碳 STC	高斯模型 Gaussian model	82.200	222.400	0.370	38.954	0.886	746
土壤全氮 STN	球状模型 Spherical model	0.380	1.641	0.232	43.970	0.913	0.033
土壤碳氮比 SCN	球状模型 Spherical model	0.001	0.248	0.005	9.570	0.695	0.001
土壤δ¹³C Soil δ¹³C	指数模型 Exponential model	0.130	0.999	0.130	17.490	0.952	0.003
土壤δ¹⁵N Soil δ¹⁵N	指数模型 Exponential model	0.601	1.354	0.444	27.600	0.640	0.040

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表 3 土壤碳氮含量及其同位素的分形维数

Table 3. Fractal dimensions of soil carbon and nitrogen content and their stable isotopes

指标 Parameter	各向同性 Isotropy	各向异性 Anisotropy
指标 Parameter	各向同性 Isotropy	0°	45°	90°	135°
土壤全碳 STC	1.752 (0.886)	1.742 (0.994)	1.732 (0.874)	1.700 (0.847)	1.862 (0.469)
土壤全氮 STN	1.740 (0.919)	1.731 (0.993)	1.709 (0.901)	1.695 (0.877)	1.852 (0.542)
土壤碳氮比 SCN	1.952 (0.309)	1.972 (0.029)	1.962 (0.049)	1.969 (0.700)	1.830 (0.982)
土壤δ¹³C Soil δ¹³C	1.881 (0.940)	1.895 (0.437)	1.914 (0.546)	1.863 (0.760)	1.828 (0.984)
土壤δ¹⁵N Soil δ¹⁵N	1.898 (0.670)	1.851 (0.745)	1.866 (0.260)	1.836 (0.698)	1.951 (0.097)
注：括号中的数据为模型的决定系数（R²）。Data in parentheses are model coefficients of determination (R²).

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表 4 土壤碳氮含量及其同位素的交叉变异函数模型及其参数

Table 4. Parameters of cross-variogram models for soil carbon and nitrogen contents and their stable isotopes

指标 Parameter	最优模型 Model	结构方差比 C/(C₀+C)	变程 Range/m	决定系数 R²	残差平方和 RSS
Soil δ¹³C ～ STC	高斯模型 Gaussian model	0.671	34.884	0.983	0.201
Soil δ¹³C ～ STN	球状模型 Spherical model	0.748	35.030	0.973	0.002
Soil δ¹³C ～ SCN	球状模型 Spherical model	0.999	8.400	0.078	0.003
Soil δ¹³C ～ Soil δ¹⁵N	指数模型 Exponential model	0.590	43.860	0.971	0.002
Soil δ¹⁵N ～ STC	球状模型 Spherical model	0.642	38.980	0.811	4.950
Soil δ¹⁵N ～ STN	球状模型 Spherical model	0.635	37.110	0.816	0.037
Soil δ¹⁵N ～ SCN	高斯模型 Gaussian model	0.999	9.682	0.599	0.001
注：STC，土壤全碳；STN，土壤全氮；SCN，土壤碳氮比；Soil δ¹³C，土壤δ¹³C；Soil δ¹⁵N，土壤δ¹⁵N。STC, soil total carbon; STN, soil total nitrogen; SCN, soil carbon to nitrogen ratio; Soil δ¹³C, the natural abundance of soil stable carbon isotopes; Soil δ¹⁵N, the natural abundance of soil stable nitrogen isotopes.

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参考文献(106)

[1]	艾喆, 徐婷婷, 李媛媛, 等, 2021. 鬼箭锦鸡儿叶片和土壤碳稳定同位素特征及其影响因素[J]. 应用生态学报, 32(5): 1744-1752. doi: 10.13287/j.1001-9332.202105.004
[2]	柏松, 黄成敏, 唐亚, 2008. 岷江上游干旱河谷海拔梯度上的土壤发生特征[J]. 土壤, 40(6): 980-985. doi: 10.13758/j.cnki.tr.2008.06.005
[3]	包维楷, 庞学勇, 李芳兰, 等, 2012. 干旱河谷生态恢复与持续管理的科学基础[M]. 北京: 科学出版社.
[4]	蔡海霞, 吴福忠, 杨万勤, 2010. 模拟干旱胁迫对岷江干旱河谷-山地森林交错带 4 种乡土植物抗氧化酶系统的影响[J]. 应用与环境生物学报, 16(4): 478-482. doi: 10.3724/SP.J.1145.2010.00478
[5]	蔡海霞, 吴福忠, 杨万勤, 2011. 干旱胁迫对高山柳和沙棘幼苗光合生理特征的影响[J]. 生态学报, 31(9): 2430-2436.
[6]	曹瑞, 吴福忠, 杨万勤, 等, 2016. 海拔对高山峡谷区土壤微生物生物量和酶活性的影响[J]. 应用生态学报, 27(4): 1257-1264. doi: 10.13287/j.1001-9332.201604.018
[7]	曹祥会, 龙怀玉, 周脚根, 等, 2016. 河北省表层土壤有机碳和全氮空间变异特征性及影响因子分析[J]. 植物营养与肥料学报, 22(4): 937-948. doi: 10.11674/zwyf.15135
[8]	陈淼, 刘顺, 许格希, 等, 2021. 土壤剖面碳氮稳定同位素自然丰度的垂直分布模式及其影响机制[J]. 应用生态学报, 32(6): 1919-1927. doi: 10.13287/j.1001-9332.202106.028
[9]	程良爽, 宫渊波, 关灵, 等, 2009. 山地森林-干旱河谷交错带不同植被枯落物水文效益研究[J]. 中国水土保持, (12): 36-39. doi: 10.14123/j.cnki.swcc.2009.12.036
[10]	范亚宁, 党蕊娟, 李世清, 等, 2007. 云雾山草地土壤氮素及有机碳空间变异特征[J]. 水土保持研究, 14(4): 82-86.
[11]	方炫, 安韶山, 薛志婧, 等, 2014. 基于最大似然法与矩法的黄土高原小流域土壤碳氮空间变异分析[J]. 水土保持通报, 34(4): 141-146. doi: 10.13961/j.cnki.stbctb.2014.04.041
[12]	关文彬, 冶民生, 马克明, 等, 2004a. 岷江干旱河谷植被分类及其主要类型[J]. 山地学报, 1(6): 679-686. doi: 10.3969/j.issn.1008-2786.2004.06.007
[13]	关文彬, 冶民生, 马克明, 等, 2004b. 岷江干旱河谷植物群落物种周转速率与环境因子的关系[J]. 生态学报, 24(11): 2367-2373.
[14]	何淑勤, 宫渊波, 郑子成, 2020. 岷江上游不同植被恢复模式枯落物层水源涵养能力[J]. 长江流域资源与环境, 29(9): 1986-1994. doi: 10.11870/cjlyzyyhj202009009
[15]	何淑勤, 宫渊波, 郑子成, 等, 2013. 山地森林-干旱河谷交错带表层土壤侵蚀率与土壤物理性质的关系[J]. 资源科学, 35(4): 824-830.
[16]	姜霓雯, 童根平, 叶正钱, 等, 2022. 浙江清凉峰自然保护区土壤肥力指标空间变异及其影响因素[J]. 生态学报, 42(6): 2430-2441. doi: 10.5846/stxb202103310832
[17]	景莎, 田静, 王晶苑, 等, 2016. 长白山原始阔叶红松林土壤有机质组分小尺度空间异质性[J]. 生态学报, 36(20): 6445-6456. doi: 10.5846/stxb201503310626
[18]	孔红梅, 刘天星, 段靖, 等, 2012. 岷江干旱河谷灌木幼苗的土壤养分适应性研究[J]. 生态环境学报, 21(6): 1016-1023. doi: 10.16258/j.cnki.1674-5906.2012.06.002
[19]	李海东, 林杰, 张金池, 等, 2008. 小流域尺度下土壤有机碳和全氮空间变异特征[J]. 南京林业大学学报(自然科学版), 51(4): 38-42. doi: 10.3969/j.jssn.1000-2006.2008.04.008
[20]	李元寿, 张人禾, 王根绪, 等, 2009. 青藏高原典型高寒草甸区土壤有机碳氮的变异特性[J]. 环境科学, 30(6): 1826-1831. doi: 10.13227/j.hjkx.2009.06.051
[21]	连玉珍, 曹丽花, 刘合满, 等, 2020. 色季拉山西坡表层土壤有机碳的小尺度空间分布特征[J]. 北京林业大学学报, 42(9): 70-79. doi: 10.12171/j.1000-1522.20190481
[22]	廖宇琴, 龙娟, 木志坚, 等, 2022. 重庆农田土壤有机碳稳定性同位素空间分布特征[J]. 环境科学, 43(6): 3348-3356. doi: 10.13227/j.hjkx.202109090
[23]	刘彬, 鞠佳伶, 罗承德, 等, 2012. 岷江干旱河谷-山地森林交错带根层土壤碳活性与储量特征[J]. 水土保持学报, 26(2): 121-126. doi: 10.13870/j.cnki.stbcxb.2012.02.033
[24]	刘彬, 罗承德, 张健, 等, 2011. 干旱河谷-山地森林交错带土壤水分与养分特征[J]. 生态学报, 31(1): 58-66.
[25]	刘彬, 吴福忠, 张健, 等, 2008. 岷江干旱河谷-山地森林交错带震后生态恢复的关键科学技术问题[J]. 生态学报, 28(12): 5892-5898.
[26]	刘国华, 张洁瑜, 张育新, 等, 2003. 岷江干旱河谷三种主要灌丛地上生物量的分布规律[J]. 山地学报, 21(1): 24-32.
[27]	刘金鑫, 宫渊波, 郑江坤, 等, 2013. 岷江上游山地牧道与锥花小檗种群特征的关系[J]. 应用生态学报, 24(1): 63-70. doi: 10.13287/j.1001-9332.2013.0127
[28]	刘丽丹, 谢应忠, 邱开阳, 等, 2013. 宁夏盐池沙地 3 种植物群落土壤表层养分的空间异质性[J]. 中国沙漠, 33(3): 782-787. doi: 10.7522/j.issn.1000-694X.2013.00090
[29]	刘珊珊, 王芬, 张兴华, 等, 2014. 放牧干扰对岷江上游山地森林-干旱河谷交错带土壤微生物量及呼吸熵的影响[J]. 水土保持通报, 34(2): 63-68. doi: 10.13961/j.cnki.stbctb.2014.02.014
[30]	刘世荣, 缪宁, 张远东, 等, 2022. 岷江上游退化森林的保护、修复与展望[J]. 陆地生态系统与保护学报, 2(5): 95-101. doi: 10.12356/j.2096-8884.2022-0038
[31]	刘正刚, 裴柏洋, 王宪帅, 2011. 岷江上游干旱河谷不同土地利用类型的土壤有机碳和易氧化态碳特征[J]. 水土保持研究, 18(3): 24-27.
[32]	孟国才, 马东涛, 王士革, 等, 2007. 岷江上游地区环境问题及其驱动力[J]. 干旱区地理, 30(5): 759-765. doi: 10.13826/j.cnki.cn65-1103/x.2007.05.017
[33]	庞学勇, 包维楷, 吴宁, 2008. 岷江上游干旱河谷气候特征及成因[J]. 长江流域资源与环境, 17(S1): 46-53.
[34]	彭潇贤, 薛冬梅, 王义东, 等, 2021. 天津农田土壤碳氮含量及其同位素组成的空间分布[J]. 天津师范大学学报 (自然科学版), 41(5): 52-59. doi: 10.19638/j.issn1671-1114.20210507
[35]	秦雯怡, 陈果, 李小臻, 等, 2021. 基于机器语言的岷江上游流域表层土壤氢氧稳定同位素空间分布模拟[J]. 应用生态学报, 32(12): 4327-4338. doi: 10.13287/j.1001-9332.202112.002
[36]	任加国, 王彬, 师华定, 等, 2020. 沱江上源支流土壤重金属污染空间相关性及变异解析[J]. 农业环境科学学报, 39(3): 530-541. doi: 10.11654/jaes.2019-1049
[37]	苏松锦, 刘金福, 何中声, 等, 2012. 格氏栲天然林土壤养分空间异质性[J]. 生态学报, 32(18): 5673-5682. doi: 10.5846/stxb201108041146
[38]	童珊, 曹广超, 张卓, 等, 2022. 土壤全碳全氮空间异质性及影响因素分析——以祁连山南坡黑河上游为例[J]. 土壤, 54(5): 1064-1072. doi: 10.13758/j.cnki.tr.2022.05.025
[39]	王家强, 彭杰, 柳维扬, 等, 2014. 干旱区荒漠河岸林土壤全氮空间变异特征研究[J]. 西北林学院学报, 29(2): 12-19. doi: 10.3969/j.jssn.1001-7461.2014.02.03
[40]	王晶, 包维楷, 2011. 岷江干旱河谷中心地段植被微尺度空间格局特征[J]. 山地学报, 29(6): 668-676. doi: 10.16089/j.cnki.1008-2786.2011.06.015
[41]	王天高, 何淑勤, 尹忠, 等, 2014. 山地森林/干旱河谷交错带不同植被条件下土壤团聚体及其腐殖质分布特征[J]. 水土保持学报, 28(6): 222-227. doi: 10.13870/j.cnki.stbcxb.2014.06.041
[42]	王晓君, 王宪帅, 黄从德, 等, 2011. 岷江上游森林/干旱河谷交错带不同土地利用类型土壤有机碳和活性有机碳特征[J]. 水土保持学报, 25(2): 167-172. doi: 10.13870/j.cnki.stbcxb.2011.02.038
[43]	文春玉, 徐明, 聂坤, 等, 2023. 亚热带山地马尾松–甜槠针阔混交林土壤养分空间分布特征与合理取样[J]. 土壤, 55(6): 1244-1250. doi: 10.13758/j.cnki.tr.2023.06.011
[44]	吴海勇, 曾馥平, 宋同清, 等, 2009. 喀斯特峰丛洼地土壤有机碳和氮素空间变异特征[J]. 植物营养与肥料学报(5): 1029-1036.
[45]	武小钢, 郭晋平, 田旭平, 等, 2013. 芦芽山亚高山草甸, 云杉林土壤有机碳, 全氮含量的小尺度空间异质性[J]. 生态学报, 33(24): 7756-7764. doi: 10.5846/stxb201210231466
[46]	夏红霞, 宫渊波, 朱启红, 2012. 岷江上游干旱河谷-山地森林交错带植被α多样性分析[J]. 安徽农业科学, 40(29): 14288-14289. doi: 10.13989/j.cnki.0517-6611.2012.29.159
[47]	严代碧, 岳永杰, 郑绍伟, 等, 2006. 岷江上游干旱河谷区土壤水分含量及其动态[J]. 南京林业大学学报: 自然科学版, 30(4): 64-68.
[48]	杨丹, 项文化, 方晰, 等, 2014. 石栎-青冈常绿阔叶林土壤有机碳和全氮空间变异特征[J]. 生态学报, 34(12): 3452-3462. doi: 10.5846/stxb201401230170
[49]	杨钦周, 2007. 岷江上游干旱河谷灌丛研究[J]. 山地学报, 25(1): 1-32.
[50]	杨秀清, 韩有志, 2011. 关帝山森林土壤有机碳和氮素的空间变异特征[J]. 林业科学研究, 24(2): 223-229. doi: 10.13275/j.cnki.lykxyj.2011.02.001
[51]	杨兆平, 常禹, 布仁仓, 等, 2007. 岷江上游干旱河谷区域空间变化的定量判定[J]. 生态学报, 27(8): 3250-3256.
[52]	冶民生, 关文彬, 谭辉, 等, 2004. 岷江干旱河谷灌丛 α 多样性分析[J]. 生态学报, 24(6): 1123-1130.
[53]	冶民生, 关文彬, 吴斌, 等, 2006. 岷江干旱河谷主要灌木种群生态位研究[J]. 北京林业大学学报, 28(1): 7-13. doi: 10.13332/j.1000-1522.2006.01.002
[54]	叶延琼, 陈国阶, 樊宏, 2002. 岷江上游脆弱生态环境刍论[J]. 长江流域资源与环境, 11(4): 383-387.
[55]	易海燕, 宫渊波, 伍维翰, 等, 2010. 岷江上游山地森林/干旱河谷交错带植被恢复对土壤微生物量及酶活性的影响[J]. 水土保持学报, 24(3): 145-149. doi: 10.13870/j.cnki.stbcxb.2010.03.029
[56]	昝麒麟, 赖晓明, 朱青, 等, 2022. 全球尺度上土壤¹⁵N 自然丰度空间变化的影响因素[J]. 土壤, 54(5): 920-927. doi: 10.13758/j.cnki.tr.2022.05.007
[57]	张法升, 刘作新, 2011. 分形理论及其在土壤空间变异研究中的应用[J]. 应用生态学报, 22(5): 1351-1358. doi: 10.13287/j.1001-9332.2011.0180
[58]	张凤杰, 乌云娜, 杨宝灵, 等, 2009. 呼伦贝尔草原土壤养分与植物群落数量特征的空间异质性[J]. 西北农业学报, 18(2): 173-177.
[59]	张伟, 张宏, 王亁蕴, 2016. 青藏高原东缘高寒草地土壤碳空间异质性[J]. 四川师范大学学报:自然科学版, 39(4): 602-607.
[60]	张文辉, 卢涛, 马克明, 等, 2004. 岷江上游干旱河谷植物群落分布的环境与空间因素分析[J]. 生态学报, 24(3): 552-559.
[61]	张亚茹, 欧阳旭, 褚国伟, 等, 2014. 鼎湖山季风常绿阔叶林土壤有机碳和全氮的空间分布[J]. 应用生态学报, 25(1): 19-23. doi: 10.13287/j.1001-9332.2014.01.003
[62]	张远东, 刘世荣, 马姜明, 2006. 川西高山和亚高山灌丛的地被物及土壤持水性能[J]. 生态学报, 26(9): 2775-2782.
[63]	赵钦, 2009. 岷江上游山地森林–干旱河谷交错带土壤理化性质研究[D]. 雅安: 四川农业大学.
[64]	郑杰, 冯文兰, 王凤杰, 等, 2017. 岷江上游干旱河谷范围的界定及其变化分析[J]. 干旱区地理, 40(3): 541-548. doi: 10.13826/j.cnki.cn65-1103/x.2017.03.007
[65]	钟熙敏, 宫渊波, 陈林武, 等, 2011. 岷江上游山地森林/干旱河谷交错带不同植被恢复模式对根际土壤微生物量碳氮及固氮菌群落结构的影响[J]. 水土保持学报, 25(1): 208-213. doi: 10.13870/j.cnki.stbcxb.2011.01.022
[66]	祖元刚, 马克明, 张喜军, 1997. 植被空间异质性的分形分析方法[J]. 生态学报, 17(3): 333-337.
[67]	Amundson R, Austin A T, Schuur E A G, et al, 2003. Global patterns of the isotopic composition of soil and plant nitrogen[J]. Global Biogeochemical Cycles, 17(1): 1031. doi: 10.1029/2002GB001903
[68]	Andriollo D D, Redin C G, Reichert J M, et al, 2017. Soil carbon isotope ratios in forest-grassland toposequences to identify vegetation changes in southern Brazilian grasslands[J]. Catena, 159: 126-135. doi: 10.1016/j.catena.2017.08.012
[69]	Aranibar J N, Otter L, Macko S A, et al, 2004. Nitrogen cycling in the soil–plant system along a precipitation gradient in the Kalahari sands[J]. Global Change Biology, 10(3): 359-373. doi: 10.1111/j.1365-2486.2003.00698.x
[70]	Bai E, Boutton T W, Liu F, et al, 2012. Spatial variation of soil δ¹³C and its relation to carbon input and soil texture in a subtropical lowland woodland[J]. Soil Biology and Biochemistry, 44(1): 102-112. doi: 10.1016/j.soilbio.2011.09.013
[71]	Batjes N H, 1996. Total carbon and nitrogen in the soils of the world[J]. European Journal of Soil Science, 47(2): 151-163. doi: 10.1111/ejss.12114_2
[72]	Bekele A, Kellman L, Beltrami H, 2013. Plot level spatial variability of soil organic carbon, nitrogen, and their stable isotopic compositions in temperate managed forest soils of Atlantic Canada[J]. Soil Science, 178(8): 400-416. doi: 10.1097/SS.0000000000000003
[73]	Biggs T H, Quade J, Webb R H, 2002. δ¹³C values of soil organic matter in semiarid grassland with mesquite (Prosopis) encroachment in southeastern Arizona[J]. Geoderma, 110(1/2): 109-130. doi: 10.1016/S0016-7061(02)00227-6
[74]	Brüggemann N, Gessler A, Kayler Z, et al, 2011. Carbon allocation and carbon isotope fluxes in the plant-soil-atmosphere continuum: a review[J]. Biogeosciences, 8(11): 3457-3489. doi: 10.5194/bg-8-3457-2011
[75]	Brunello A T, Nardoto G B, Santos F L S, et al, 2024. Soil δ¹⁵N spatial distribution is primarily shaped by climatic patterns in the semiarid Caatinga, Northeast Brazil[J]. Science of The Total Environment, 908: 168405. doi: 10.1016/j.scitotenv.2023.168405
[76]	Collins A L, Burak E, Harris P, et al, 2019. Field scale temporal and spatial variability of δ¹³C, δ¹⁵N, TC and TN soil properties: implications for sediment source tracing[J]. Geoderma, 333: 108-122. doi: 10.1016/j.geoderma.2018.07.019
[77]	Condit R, 1998. Tropical forest census plots: methods and results from Barro Colorado Island, Panama and a comparison with other plots [M]. Heidelberg: Springer.
[78]	Craine J M, Brookshire E N J, Cramer M D, et al, 2015. Ecological interpretations of nitrogen isotope ratios of terrestrial plants and soils[J]. Plant and Soil, 396: 1-26. doi: 10.1007/s11104-015-2542-1
[79]	das Neves G, Sena-Souza J P, de Souza Santos F L, et al, 2021. Spatial distribution of soil δ¹³C in the central Brazilian savanna[J]. Journal of Environmental Management, 300: 113758. doi: 10.1016/j.jenvman.2021.113758
[80]	Ehleringer J R, Buchmann N, Flanagan L B, 2000. Carbon isotope ratios in belowground carbon cycle processes[J]. Ecological Applications, 10(2): 412-422. doi: 10.2307/2641103
[81]	Golubtsov V A, Vanteeva Y V, Voropay N N, et al, 2022. The effect of local environmental factors on the stable carbon isotopic composition of soils in the Olkhonregion[J]. Moscow University Soil Science Bulletin, 77(4): 284-294. doi: 10.3103/S0147687422040056
[82]	John B, Yamashita T, Ludwig B, et al, 2005. Storage of organic carbon in aggregate and density fractions of silty soils under different types of land use[J]. Geoderma, 128(1/2): 63-79. doi: 10.1016/j.geoderma.2004.12.013
[83]	Li H Z, Yan F, Tuo D, et al, 2020. The effect of climatic and edaphic factors on soil organic carbon turnover in hummocks based on δ¹³C on the Qinghai-Tibet Plateau[J]. Science of The Total Environment, 741: 140141. doi: 10.1016/j.scitotenv.2020.140141
[84]	Marty C, Houle D, Courchesne F, et al, 2019. Soil C: N ratio is the main driver of soil δ¹⁵N in cold and N-limited eastern Canadian forests[J]. Catena, 172: 285-294. doi: 10.1016/j.catena.2018.08.029
[85]	Nel J A, Craine J M, Cramer M D, 2018. Correspondence between δ¹³C and δ¹⁵N in soils suggests coordinated fractionation processes for soil C and N[J]. Plant and soil, 423: 257-271. doi: 10.1007/s11104-017-3500-x
[86]	Nitzsche K N, Verch G, Premke K, et al, 2016. Visualizing land-use and management complexity within biogeochemical cycles of an agricultural landscape[J]. Ecosphere, 7(5): e01282. doi: 10.1002/ecs2.1282
[87]	Peri P L, Ladd B, Pepper D A, et al, 2012. Carbon (δ¹³C) and nitrogen (δ¹⁵N) stable isotope composition in plant and soil in Southern Patagonia's native forests[J]. Global Change Biology, 18(1): 311-321. doi: 10.1111/j.1365-2486.2011.02494.x
[88]	Peukert S, Bol R, Roberts W, et al, 2012. Understanding spatial variability of soil properties: a key step in establishing field- to farm-scale agro-ecosystem experiments[J]. Rapid Communications in Mass Spectrometry, 26(20): 2413-2421. doi: 10.1002/rcm.6336
[89]	Powers J S, 2006. Spatial variation of soil organic carbon concentrations and stable isotopic composition in 1-ha plots of forest and pasture in Costa Rica: implications for the natural abundance technique[J]. Biology and Fertility of Soils, 42: 580-584. doi: 10.1007/s00374-005-0054-5
[90]	Robinson D, 2001. δ¹⁵N as an integrator of the nitrogen cycle[J]. Trends in Ecology & Evolution, 16(3): 153-162. doi: 10.1016/S0169-5347(00)02098-X
[91]	Shan Y, Huang M B, Suo L Z, et al, 2019. Composition and variation of soil δ¹⁵N stable isotope in natural ecosystems[J]. Catena, 183: 104236. doi: 10.1016/j.catena.2019.104236
[92]	Tian J, McCormack L, Wang J Y, et al, 2015. Linkages between the soil organic matter fractions and the microbial metabolic functional diversity within a broad-leaved Korean pine forest[J]. European Journal of Soil Biology, 66: 57-64. doi: 10.1016/j.ejsobi.2014.12.001
[93]	Wang C, Wang X B, Liu D W, et al, 2014. Aridity threshold in controlling ecosystem nitrogen cycling in arid and semi-arid grasslands[J]. Nature Communications, 5(1): 4799. doi: 10.1038/ncomms5799
[94]	Wang G A, Jia Y F, Li W, 2015. Effects of environmental and biotic factors on carbon isotopic fractionation during decomposition of soil organic matter[J]. Scientific Reports, 5(1): 11043. doi: 10.1038/srep11043
[95]	Wang L X, Okin G S, Caylor K K, et al, 2009. Spatial heterogeneity and sources of soil carbon in southern African savannas[J]. Geoderma, 149(3/4): 402-408. doi: 10.1016/j.geoderma.2008.12.014
[96]	Wang T, Kang F F, Cheng X Q, et al, 2017. Spatial variability of organic carbon and total nitrogen in the soils of a subalpine forested catchment at Mt. Taiyue, China[J]. Catena, 155: 41-52. doi: 10.1016/j.catena.2017.03.004
[97]	Western A W, Blöschl G, Grayson R B, 1998. Geostatistical characterisation of soil moisture patterns in the Tarrawarra catchment[J]. Journal of Hydrology, 205(1/2): 20-37. doi: 10.1016/S0022-1694(97)00142-X
[98]	Xia S P, Song Z L, Singh B P, et al, 2023. Contrasting patterns and controls of soil carbon and nitrogen isotope compositions in coastal wetlands of China[J]. Plant and Soil, 489: 483-505. doi: 10.1007/s11104-023-06034-2
[99]	Xu C G, He H S, Hu Y M, et al, 2005. Latin hypercube sampling and geostatistical modeling of spatial uncertainty in a spatially explicit forest landscape model simulation[J]. Ecological Modelling, 185(2/4): 255-269. doi: 10.1016/j.ecolmodel.2004.12.009
[100]	Yang F, Tian J, Fang H J, et al, 2018. Spatial heterogeneity of microbial community and enzyme activities in a broad-leaved Korean pine mixed forest[J]. European Journal of Soil Biology, 88: 65-72. doi: 10.1016/j.ejsobi.2018.07.001
[101]	Yang J, El-Kassaby Y A, Guan W, 2020. Multiple ecological drivers determining vegetation attributes across scales in a mountainous dry valley, southwest China[J]. Forests, 11(11): 1140. doi: 10.3390/f11111140
[102]	Yang Y H, Ji C J, Chen L Y, et al, 2015. Edaphic rather than climatic controls over ¹³C enrichment between soil and vegetation in alpine grasslands on the Tibetan Plateau[J]. Functional Ecology, 29(6): 839-848. doi: 10.1111/1365-2435.12393
[103]	You M Y, Zhu-Barker X, Hao X X, et al, 2021. Profile distribution of soil organic carbon and its isotopic value following long term land-use changes[J]. Catena, 207: 105623. doi: 10.1016/j.catena.2021.105623
[104]	Zhao Y F, Wang X, Ou Y S, et al, 2019. Variations in soil δ¹³C with alpine meadow degradation on the eastern Qinghai–Tibet Plateau[J]. Geoderma, 338: 178-186. doi: 10.1016/j.geoderma.2018.12.005
[105]	Zhou S W, Wu J J, Bi X L, 2020. Spatial characteristics of soil δ¹³C and δ¹⁵N reveal shrub-induced successional process in a coastal wetland[J]. Estuarine, Coastal and Shelf Science, 236: 106621. doi: 10.1016/j.ecss.2020.106621
[106]	Zhu Q, Castellano M J, Yang G S, 2018. Coupling soil water processes and the nitrogen cycle across spatial scales: potentials, bottlenecks and solutions[J]. Earth-Science Reviews, 187: 248-258. doi: 10.1016/j.earscirev.2018.10.005