1.甘肃祁连山国家级自然保护区夏玛自然保护站, 甘肃 天祝 733000
2.甘肃祁连山国家级自然保护区管护中心, 甘肃 张掖 734000
3.甘肃祁连山国家级;自然保护区祁连自然保护站, 甘肃 武威 733000
4.甘肃省祁连山水源涵养林研究院,甘肃 张掖 734000
5.甘肃祁连山国家级自然保护区乌鞘岭自然保护站, 甘肃 武威 733000
冯金元(1985—),男(汉族),甘肃省武威市人,本科,高级工程师,主要从事林业生态环境保护方面的研究。Email:275414761@qq.com。
蒋志成(1979—),男(土族),甘肃省武威市人,本科,正高级工程师,主要从事林业生态环境保护方面的研究。Email:403666957@qq.com。
收稿:2024-04-22,
修回:2024-07-25,
纸质出版:2025-06-10
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冯金元, 蒋志成, 蒋志仁, 等.祁连山中段青海云杉林土壤有机碳分布特征及影响因素[J].水土保持通报,2025,45(3):261-267.
Feng Jinyuan, Jiang Zhicheng, Jiang Zhiren, et al. Characteristics and influencing factors of soil organic carbon at Picea crassifolia forests in middle part of Qilian Mountains[J]. Bulletin of Soil and Water Conservation,2025,45(3):261-267.
冯金元, 蒋志成, 蒋志仁, 等.祁连山中段青海云杉林土壤有机碳分布特征及影响因素[J].水土保持通报,2025,45(3):261-267. DOI: 10.13961/j.cnki.stbctb.2025.03.001. CSTR: 32312.14.stbctb.2025.03.001..
Feng Jinyuan, Jiang Zhicheng, Jiang Zhiren, et al. Characteristics and influencing factors of soil organic carbon at Picea crassifolia forests in middle part of Qilian Mountains[J]. Bulletin of Soil and Water Conservation,2025,45(3):261-267. DOI: 10.13961/j.cnki.stbctb.2025.03.001. CSTR: 32312.14.stbctb.2025.03.001..
目的
2
研究土壤因子和林分因子对祁连山青海云杉林土壤有机碳分布的影响,以深入理解祁连山区土壤碳循环机制,并为该地区碳平衡的维持提供科学依据。
方法
2
于2021年7月沿2 700,2 900,3 100和3 300 m海拔梯度设置样地,采集样地内土壤和林分数据,通过非参数检验分析不同土层土壤有机碳在海拔间的差异,使用Pearson相关性和线性拟合分析土壤有机碳与土壤pH值、容重、质量含水率、温度、郁闭度和林分密度之间的关系,采用置换多因素方差分析影响土壤有机碳变异的因素。
结果
2
①海拔高度2 700 m土壤有机碳含量平均最高,为90.12~127.63 g/kg,海拔3 100 m土壤有机碳含量平均最低,为62.17~70.50 g/kg。10 cm土层土壤有机碳含量最高,为70.50~127.63 g/kg,40 cm土层土壤有机碳含量最低,为62.17~90.12 g/kg。 ②所有土层土壤有机碳与pH值和容重呈显著负相关(
p
<
0.05),与温度、郁闭度和林分密度呈显著正相关(
p
<
0.05),与质量含水率呈不显著负相关(
p
>
0.05)。线性拟合关系表现为容重最好,决定系数为0.81(
p
<
0.01),pH值和温度决定系数分别为0.57(
p
<
0.01)和0.32(
p
<
0.01)。 ③随着土层深度增加,在各因子对土壤有机碳差异的影响中pH值的比例在逐渐增加,容重的影响在逐渐减小,林分密度影响逐渐增加。
结论
2
各土层土壤有机碳随海拔呈现为先降后升的趋势,表层土壤有机碳变化幅度最大,深度土壤有机碳变化幅度最小。土壤有机碳与土壤及林分因子相关关系表现为:容重>pH值>温度>林分密度>郁闭度>质量含水率。pH值是形成不同海拔高度间土壤有机碳差异的主要影响因子。
Objective
2
The effects of soil and stand factors on the distribution of soil organic carbon (SOC) were investigated at
Picea crassifolia
forests in the Qilian Mountains, aiming to deepen the understanding of soil carbon cycling mechanisms in the region and provide a scientific basis for maintaining regional carbon balance.
Methods
2
In July 2021, sample plots were set up at 2 700 m, 2 900 m, 3 100 m, and 3 300 m along the elevation gradients, and soil and stand data were collected. The differences in soil organic carbon in different soil layers were analyzed using non-parametric tests. Pearson correlation and linear fitting were used to examine the relationship between soil organic carbon and soil pH value, bulk density, mass moisture content, soil temperature, canopy closure, and stand density. Permutational multivariate analysis of variance (PERMANOVA) was used to identify factors influencing SOC variability.
Results
2
① The highest average SOC content was found at 2 700 m elevation, ranging from 90.12 to 127.63 g/kg. Meanwhile, the lowest average SOC content was observed at 3 100 m elevation, ranging from 62.17 to 70.50 g/kg. The 10 cm soil layer had the highest SOC content, ranging from 70.50 to 127.63 g/kg. Meanwhile, the 40 cm soil layer had the lowest SOC content, ranging from 62.17 to 90.12 g/kg. ② SOC in all soil layers showed a significant negative correlation with pH value and bulk density (
p
<
0.05), a significant positive correlation with temperature, canopy closure, and stand density (
p
<
0.05), and a non-significant negative correlation with mass water content (
p
>
0.05). Linear regression indicated that bulk density had the strongest relationship with SOC, with a coefficient of determination (
R
²) of 0.81 (
p
<
0.01), followed by pH value (
R
²=0.57,
p
<
0.01) and temperature (
R
²=0.32,
p
<
0.01). ③ As soil depth increased, the influence of pH value on SOC variability gradually increased. Meanwhile, the influence of bulk density decreased, and the impact of stand density gradually increased.
Conclusion
2
The SOC content in different soil layers showed a trend of first decreasing and then increasing with elevation. The surface soil layer showed the largest variation in SOC content, whereas the deeper soil layers showed the least variation. Correlations between SOC and soil and stand factors were ranked as follows: bulk density > pH value> temperature > stand density > canopy closure > mass moisture content. pH value was the primary factor contributing to differences in SOC across elevations.
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