Distribution patterns and evaluation of soil nutrients in Picea schrenkiana var. tianschanica forests across different regions and altitudes

XU Dong, CHEN Hao, Yeerjiang BAIKETUERHAN, WANG Qiang
(College of Forestry and Landscape Architecture, Xinjiang Agricultural University/Key Laboratory of Forestry Ecology and Industrial Technology in Arid Areas of Xinjiang, Urumqi 830052, Xinjiang, China)

Abstract

To investigate the spatial variability of soil nutrients under Picea schrenkiana var. tianschanica forests and provide a scientific basis for forest health evaluation, an experiment was conducted across four study areas located along different longitude ranges from east to west on the northern slope of the Tianshan Mountains. Sample lines and plots were established along elevation gradients, and soil samples were collected to analyze nutrient distribution patterns and differences across regions and elevations. The results indicated the following: (1) Elevation had a certain influence on the distribution of soil organic matter, total nitrogen, and total phosphorus content. (2) Soil organic matter, total nitrogen, and total phosphorus contents were significantly positively correlated. (3) Based on a comprehensive evaluation, the ranking of soil nutrient content across different elevations, from highest to lowest, was as follows: Mid-high elevation (96.3 points), high elevation (95.5 points), mid elevation (95.0 points), mid-low elevation (88.5 points), and low elevation (79.4 points); across different regions, the soil nutrient rankings were: Western Tianshan (93.4 points), mid-eastern Tianshan (91.4 points), mid-western Tianshan (91.0 points), and central Tianshan (88.0 points). (4) Total potassium content exhibited more stable distribution across elevations, with minimal influence from elevation factors. (5) Overall, soil nutrient levels under Picea schrenkiana var. tianschanica forests on the northern slope of the Tianshan Mountains were generally abundant, although certain differences still existed across elevations and regions. The highest nutrient content was observed in western Tianshan and the mid-high elevation zone.

Keywords: northern slope of the Tianshan Mountains; Picea schrenkiana var. tianschanica forests; soil nutrients; altitude; nutrient rating

Introduction

The importance of soil in forest ecosystems has long been widely recognized. As a core component of forest ecological processes, soil serves as a critical source of nutrients required for tree growth and provides the foundation for supporting and anchoring forest vegetation. All essential ecological elements for tree development—including water, nutrients, air, and heat—are supplied through soil, which plays a pivotal role in the natural succession of entire forest ecosystems. Soil organic matter content not only influences soil physical, chemical, and ecological properties but also affects soil fertility and ecosystem stability. Nitrogen is the element most demanded by plants, and soil total nitrogen content represents an important indicator for measuring soil fertility. Phosphorus in soil not only participates in essential life processes such as photosynthesis and respiration but also directly affects ecosystem nutrient cycling. Potassium ranks seventh among mineral nutrients in the earth's crust and constitutes an indispensable element for plant growth and development. Consequently, investigating soil nutrients beneath Picea schrenkiana var. tianschanica forests is crucial.

Picea schrenkiana var. tianschanica forests occupy an important ecological position in the Tianshan Mountains, yet research on the distribution characteristics of soil nutrients beneath these forests remains insufficient. Studying the spatial distribution of soil nutrients not only helps reveal how soils support spruce forest growth but also provides scientific foundations for health evaluation, soil management, and conservation measures across different regional forest ecosystems. The Tianshan Mountains' primary forest component consists of natural Picea schrenkiana var. tianschanica stands, which represent precious forest ecosystems with high biodiversity and unique ecological functions. Soil surveys can help understand the soil fertility status of these natural forests, providing a basis for protection and management strategies to promote forest ecosystem health and sustainability.

Previous studies on Picea schrenkiana var. tianschanica forest soils have been scarce, particularly concerning soil nutrient variation patterns along elevation gradients. Therefore, this study selected four typical regions along the northern slope of the Tianshan Mountains, following the principle of combining multiple regions with elevation gradients. According to the longitudinal distribution of the Tianshan Mountains from east to west, soil data from four different regions and five elevation gradients were collected to investigate distribution patterns and conduct evaluations. This research is essential for soil nutrient management and health protection of Picea schrenkiana var. tianschanica forests.

1 Materials and Methods

1.1 Data Acquisition

In 2023, four typical study regions were selected sequentially from east to west along the northern slope of the Tianshan Mountains (Table 1). All stands were pure Picea schrenkiana var. tianschanica forests. The soil type was mountainous gray-cinnamon soil and mountainous chernozem, with deep soil layers rich in humus and moisture. The climate belongs to the temperate continental arid and semi-arid type. Understory herbaceous vegetation was abundant, with dominant species including Tianshan meadow grass (Poa tianschanica), Tianshan lady's mantle (Alchemilla tianschanica), and garden balsam (Impatiens balsamina).

According to the natural growth limits of Picea schrenkiana var. tianschanica forests (1700–2700 m), sample lines were established in each of the four study regions (Figure 1). The study comprehensively considered natural conditions, vegetation distribution, and topographic characteristics to ensure sampling point representativeness. Within the spruce distribution range, one 30 m × 30 m plot was established every 50 m elevation interval, totaling 60 plots across all regions. These plots were categorized into five elevation bands: low elevation (1700–1850 m, 12 plots), mid-low elevation (1900–2050 m, 12 plots), mid elevation (2100–2300 m, 12 plots), mid-high elevation (2350–2500 m, 12 plots), and high elevation (2550–2700 m, 12 plots).

Within each plot, soil samples were collected from 0–20 cm and 20–40 cm depths using a five-point sampling method, with three replicates per depth. Samples were naturally air-dried, passed through a 2 mm sieve, uniformly mixed, and transported to the laboratory for processing and analysis. Soil organic matter, total nitrogen, total phosphorus, and total potassium contents were determined using the Walkley-Black dichromate titration method, Kjeldahl method, nitric acid-perchloric acid digestion method, and flame photometry, respectively.

1.2 Data Processing and Analysis

Based on the nutrient content grading standards from the Second National Soil Survey, soil nutrient contents were graded (Table 2) and assigned normalized scores of 5, 4, 3, 2, and 1 for each grade. The coefficient of variation (CV) measures the degree of dispersion, with CV < 10%, 10–100%, and >100% corresponding to weak, moderate, and strong variation, respectively. The weight of each soil nutrient indicator was calculated based on its coefficient of variation using the following formula:

$$W_i = \frac{U_i}{\sum_{k=1}^{n} U_k}$$

where $W_i$ is the weight coefficient of indicator $i$, $U_i$ is the coefficient of variation for indicator $i$, $U_k$ is the coefficient of variation for indicator $k$, and $k$ is the summation index variable. The calculated weights for organic matter, total nitrogen, total phosphorus, and total potassium were 0.28, 0.26, 0.24, and 0.22, respectively.

The soil nutrient content index (SNCI) for each plot was obtained through weighted summation of normalized scores:

$$\text{SNCI} = \sum_{i=1}^{n} W_i X_i$$

where SNCI is the soil nutrient content index and $X_i$ is the standardized score of indicator $i$.

Microsoft Excel 2023 was used to calculate means, standard deviations, and coefficients of variation for soil organic matter, total nitrogen, total phosphorus, and total potassium. Origin 2024 was used to create figures, and SPSS 26 was used for significance testing and analysis of variance.

2 Results

2.1 Basic Characteristics of Soil Nutrients in Different Regions

The basic soil nutrient information for the four regions is presented in Table 3. Organic matter content was highest in the mid-eastern Tianshan (111.40 g·kg⁻¹) and lowest in the central Tianshan (90.02 g·kg⁻¹). Total nitrogen content was highest in the mid-eastern Tianshan (6.14 g·kg⁻¹) and lowest in the mid-western Tianshan (4.75 g·kg⁻¹). Total phosphorus content was highest in the western Tianshan (0.97 g·kg⁻¹) and lowest in the mid-western Tianshan (0.71 g·kg⁻¹). Total potassium content was highest in the mid-western Tianshan (28.50 g·kg⁻¹) and lowest in the mid-eastern Tianshan (22.81 g·kg⁻¹).

2.2 Distribution Patterns of Soil Nutrient Content Along Elevation Gradients

Soil nutrient content variation with elevation in the four regions is shown in Figure 2. Soil organic matter content exhibited obvious fluctuating trends with elevation (Figure 2a), showing a significant increase within the 1700–2300 m range, reaching maximum values around 2300 m, followed by a clear decreasing trend. The highest content occurred in the 2200–2400 m range (185.00 g·kg⁻¹ in the western Tianshan at 2300 m), while the lowest occurred at 1700 m (27.20 g·kg⁻¹ in the western Tianshan). Soil total nitrogen content showed very similar trends to organic matter (Figure 2b), suggesting strong coupling between these parameters. The highest total nitrogen content occurred at 2400 m (12.30 g·kg⁻¹ in the mid-eastern Tianshan), while the lowest occurred at 1700 m (1.14 g·kg⁻¹ in the mid-eastern Tianshan).

Total phosphorus content showed distinct fluctuation patterns (Figure 2c). In the mid-eastern and central Tianshan, it showed a slow increasing trend with relatively gentle fluctuations. In the mid-western and western Tianshan, it exhibited an overall trend of first increasing then decreasing, also with gentle fluctuations, peaking at 2350 m (1.41 g·kg⁻¹ in the western Tianshan) and reaching its minimum at 1700 m (0.28 g·kg⁻¹ in the mid-western Tianshan). Total potassium content showed relatively stable fluctuations overall (Figure 2d). The mid-eastern and central Tianshan displayed initial increases followed by decreases, while the mid-western and western Tianshan showed slight increasing trends with relatively stable patterns. The highest value was 31.60 g·kg⁻¹ (mid-western Tianshan at 2400 m), and the lowest was 12.80 g·kg⁻¹ (mid-eastern Tianshan at 1700 m).

2.3 Correlation Between Soil Nutrient Content and Elevation

Correlation analysis results between soil nutrient content and elevation are presented in Figure 3. Organic matter and total nitrogen contents showed extremely significant correlations across all four regions (P < 0.001), indicating strong commonality in their formation and fertility processes. In the mid-eastern Tianshan, elevation was extremely significantly correlated with organic matter and total phosphorus, and significantly correlated with total nitrogen and total potassium. In the central Tianshan, elevation was extremely significantly correlated with organic matter, total nitrogen, and total phosphorus, but not correlated with total potassium. In the mid-western Tianshan, elevation was weakly positively correlated with organic matter and total nitrogen, moderately correlated with total phosphorus, and extremely significantly correlated with total potassium. In the western Tianshan, elevation was extremely significantly correlated with total nitrogen, significantly correlated with organic matter and total phosphorus, and weakly positively correlated with total potassium. Overall, elevation showed positive correlations with organic matter, total nitrogen, and total phosphorus contents, particularly pronounced in the mid-eastern, central, and western Tianshan.

2.4 Variability and Differences in Soil Nutrient Content

Analysis of soil nutrient content variability is shown in Figure 4. Organic matter variability in the mid-eastern Tianshan stabilized with increasing elevation, while it was relatively high in the mid and high elevation zones of the central Tianshan, and high in the mid and mid-high elevation zones of the mid-western Tianshan. In the western Tianshan, variability was high across all elevations except the mid-low zone (Figure 4a). Total nitrogen variability was minimal in the mid-low, mid, and high elevation zones of the mid-eastern Tianshan; minimal in the mid elevation zone of the central Tianshan; and high in the mid-high elevation zone of the mid-western Tianshan. Variability was generally moderate across all elevation zones in the western Tianshan (Figure 4b).

Total phosphorus variability in the mid-eastern Tianshan increased with elevation but remained small overall. In the central Tianshan, variability became moderate with increasing elevation. In the mid-western Tianshan, variability increased from low to mid-high elevations, decreasing at high elevations with increased variability. The western Tianshan showed similar patterns but with greater overall variability (Figure 4c). Total potassium variability in the mid-eastern and central Tianshan showed a decreasing-then-increasing-then-decreasing trend with elevation, while in the mid-western and western Tianshan it showed a decreasing-then-increasing pattern, reaching minimum values in the mid elevation zone across all regions (Figure 4d).

Analysis of variance results for soil nutrient content across elevations are presented in Table 4. Organic matter content was highest in the mid elevation zone, not significantly different from the mid-high and high elevation zones, but significantly higher than in low and mid-low elevation zones (P < 0.05). Total nitrogen content was highest in the mid-high elevation zone, significantly higher than in other zones (P < 0.05). Total phosphorus content was highest in the mid-high elevation zone, not significantly different from mid and high elevation zones, but significantly higher than low and mid-low elevation zones (P < 0.05). Total potassium content was highest in the mid-high elevation zone, not significantly different from the mid elevation zone, but significantly higher than other zones (P < 0.05).

2.5 Evaluation of Soil Nutrient Content in Spruce Forests

Soil nutrient evaluation scores for plot units are shown in Table 5. In the mid-eastern and central Tianshan, soil nutrient evaluation scores increased with elevation. In the mid-western and western Tianshan, scores increased from low to mid-high elevations, then decreased from mid-high to high elevations. Based on average scores, within the same region, soil nutrient content rankings from highest to lowest were: mid-high elevation (96.3 points), high elevation (95.5 points), mid elevation (95.0 points), mid-low elevation (88.5 points), and low elevation (79.4 points). Across different regions at the same elevation, soil nutrient scores ranked from highest to lowest as: western Tianshan (93.4 points), mid-eastern Tianshan (91.4 points), mid-western Tianshan (91.0 points), and central Tianshan (88.0 points).

3 Discussion

In mountain ecosystems, elevation is an important factor influencing soil nutrient content differences. Xi et al. found that soil nutrient distribution in Picea schrenkiana var. tianschanica forests showed significant differences across elevation belts, consistent with our results. Soil organic matter, total nitrogen, and total phosphorus contents in all four regions accumulated most substantially at mid-high elevations, particularly in the 2200–2400 m range, indicating that elevation significantly influences soil nutrient distribution. With increasing elevation, soil organic matter and total nitrogen showed clear trends of initial increase followed by decrease, likely related to temperature and moisture changes associated with altitude. Increased soil moisture reduces mineralization rates of organic matter and total nitrogen, while low-temperature environments at certain elevations affect water infiltration and microbial activity, leading to decreased organic matter and total nitrogen contents.

Different regional climates, soil types, vegetation cover, and biogeochemical processes play key roles in soil nutrient formation and distribution. Under the combined influence of topography, climate, and vegetation, soil nutrients in Picea schrenkiana var. tianschanica forests show complex variability. Particularly in the mid-eastern and western Tianshan, soil organic matter content was relatively high, with this trend being more pronounced at mid-high elevations. In contrast, the central and mid-western Tianshan had relatively lower soil nutrient contents, especially in low and mid-low elevation zones where soil nutrient variation showed greater fluctuation. These differences may be related to regional precipitation, temperature, disturbances, and forest management practices. Our findings align with Li et al.'s research on soil organic matter and total nitrogen variation with elevation in the Taibai Mountains.

This study confirms that elevation has extremely significant correlations with soil organic matter, total nitrogen, and total phosphorus contents, with these nutrients gradually increasing with elevation until reaching peak values followed by decline. This phenomenon indicates a non-linear relationship between soil nutrient accumulation and elevation, likely influenced by multiple factors. Qin et al. found that although elevation affects soil nutrients, it is not the sole determinant of soil nutrient distribution. In the mid-western Tianshan, despite high elevations, soil nutrient variation remained relatively stable, particularly for total potassium content, which showed minimal significant impact from elevation changes. This suggests that environmental factors other than elevation also largely determine soil nutrient distribution. Soil nutrient variability may be influenced by multiple environmental factors such as seasonal precipitation fluctuations, soil pH, and moisture content differences.

The significant positive correlations among soil nutrients indicate strong coupling relationships among organic matter, total nitrogen, and total phosphorus across different elevations and regions. In the mid-eastern and central Tianshan, extremely significant correlations between organic matter and total nitrogen/total phosphorus suggest that nutrient accumulation processes may be interdependent. Soil organic matter, as an important indicator of soil fertility, has decomposition processes closely related to nitrogen and phosphorus release, which in turn affect plant growth and soil microbial activity. Although total potassium content showed small fluctuations across elevation zones, significant correlations between total potassium and other nutrients in the mid-eastern and mid-western Tianshan may be related to soil potassium exchangeability and mineral composition, reflecting regional potassium stability.

Our results show that the western Tianshan had the highest overall soil nutrient levels, particularly evident at mid-high elevations. The mid-eastern and mid-western Tianshan had intermediate levels, while the central Tianshan was relatively poor. These differences reflect variations in natural conditions and ecological environments across regions. Higher nutrient accumulation may be associated with superior climatic conditions, while relative nutrient deficiency in the central region may result from climate, terrain, and human disturbances.

4 Conclusions

1) Elevation significantly influences soil organic matter, total nitrogen, and total phosphorus contents beneath Picea schrenkiana var. tianschanica forests.

2) Soil organic matter, total nitrogen, and total phosphorus contents show significant positive correlations with elevation. Total potassium content shows the most stable distribution across elevations, being least affected by elevation. Overall, soil nutrient content beneath Picea schrenkiana var. tianschanica forests is relatively abundant, but shows certain differences and patterns across different regions and elevation gradients.

3) Regional soil nutrient content rankings from highest to lowest are: western Tianshan, mid-eastern Tianshan, mid-western Tianshan, and central Tianshan.

4) Elevational soil nutrient content rankings from highest to lowest are: mid-high elevation, high elevation, mid elevation, mid-low elevation, and low elevation.

References

[1] Zhao Huiying, Wang Haiyan. Soil multifunctionality and its driving factors: A review[J]. Chinese Journal of Applied and Environmental Biology, 2024, 30(3): 615-622.

[2] Zhang Zhihua, Zhang Jinhao, Sang Yuqiang, et al. Spatial variations and its influencing factors of soil carbon and nitrogen on the southern foot of Taihang Mountains, China[J]. Chinese Journal of Applied Ecology, 2021, 32(8): 2829-2838.

[3] Li Yuxin, Zhao Xiaomin, Guo Xi, et al. Spatial pattern of soil organic matter in the suburbs of Nanchang City and its influencing factors[J]. Acta Agriculturae Universitatis Jiangxiensis, 2023, 45(3): 749-758.

[4] Jia Lujing, Yang Lian'an, Ji Yongfan, et al. Review on inversion of soil organic matter using satellite remote sensing[J]. Remote Sensing Information, 2023, 38(2): 1-9.

[5] Quan Simao, Wang Xukui, Hu Feng. Changes of soil total nitrogen content in farmland of Jiangsu Province and its influencing factors[J]. Journal of Nanjing Agricultural University, 2018, 41(6): 1078-1084.

[6] Cha Meiqin, Xu Haidong, Cheng Xiangrong, et al. Variations of soil phosphorus form and microbial functional diversity in Cunninghumia lanceolata-Phoebe bournei multi-layered mixed plantations of different ages[J]. Acta Ecologica Sinica, 2020, 40(19): 6938-6947.

[7] Wang M, Chen H, Zhang W, et al. Soil nutrients and stoichiometric ratios as affected by land use and lithology at county scale in a karst area, southwest China[J]. Science of the Total Environment, 2018, 619: 1299-1307.

[8] Yan Dongfeng, Geng Jianwei, Yang Xitian, et al. Health evaluation of forest system in Baotianman Nature Reserve[J]. Journal of Northwest Forestry University, 2011, 26(2): 69-74.

[9] Zhang Huiru. Discussion on the important guarantee for sustainable forest management: Integrated monitoring of forest resource[J]. Forest Research, 2008, 21(Suppl. 1): 95-99.

[10] Hu Fang, Lin Qizhong, Wang Qinjun, et al. Quantitative inversion of soil potassium content by using hyperspectral reflectance[J]. Remote Sensing for Natural Resources, 2012(4): 157-162.

[11] Cong Rihuan, Li Xiaokun, Lu Jianwei. Advances in research on influence factors of soil potassium transformation[J]. Journal of Huazhong Agricultural University, 2007, 26(6): 907-913.

[12] Lü Shili, Li Xinping, Li Wenbin, et al. Forest soil nutrient characteristics at different altitudes in Niubeiliang National Natural Reserve[J]. Journal of Northwest A&F University (Natural Science Edition), 2013, 41(4): 161-168, 177.

[13] Zhang Zhonghua, Hu Gang, Zhu Jiedong, et al. Spatial heterogeneity of soil nutrients and its impact on tree species distribution in a karst forest of southwest China[J]. Chinese Journal of Plant Ecology, 2011, 35(10): 1038-1049.

[14] Su Songjin, Liu Jinfu, He Zhongsheng, et al. The spatial heterogeneity of soil nutrients in a mid-subtropical Castanopsis kawakamii natural forest[J]. Acta Ecologica Sinica, 2012, 32(18): 5673-5682.

[15] Zhang Fuli, Yin Quan, Mao Jianfei, et al. Effects of Bacillus thuringiensis transgenic cotton straw returning to field on soil[J]. Chinese Journal of Eco-Agriculture, 2020, 28(5): 734-744.

[16] Tsui C C, Tsai C C, Chen Z. Soil organic carbon stocks in relation to elevation gradients in volcanic ash soils of Taiwan[J]. Geoderma, 2013, 209: 119-127.

[17] Chen L F, He Z B, Du J, et al. Patterns and environmental controls of soil organic carbon and total nitrogen in alpine ecosystems of northwestern China[J]. Catena, 2016, 137: 37-43.

[18] Xi Li, Li Siyao, Xia Xiaoying, et al. Spatial heterogeneity of soil nutrients and environmental interpretation in Picea schrenkiana var. tianschanica forest[J]. Journal of Central South University of Forestry & Technology, 2022, 42(10): 93-101, 167.

[19] Lou Yanmin, Liu Juanhong, Zhou Xiaoping, et al. Temperature on the viscosity and diffusion coefficient of water[J]. Artificial Intelligence Science and Engineering, 2009, 34(6): 34-39.

[20] Li Dan, Zhang Changlu, Chen Haibin, et al. Carbon, nitrogen and phosphorus contents in soils on Taibai Mountain and their ecological stoichiometry relative to elevation[J]. Acta Pedologica Sinica, 2017, 54(1): 160-170.

[21] Dang Kunliang, Zhang Changlu, Chen Haibin, et al. Spatial distribution and variation pattern of soil fertility at different altitude on south slope in Qinling Mountains[J]. Scientia Silvae Sinicae, 2006, 42(1): 16-21.

[22] Zhang Zhonghua. Ecological research on population and community stability in karst forest vegetation[D]. Shanghai: East China Normal University, 2011.

[23] Li Honglin, Gong Lu, Zhu Meiling, et al. Stoichiometric characteristics of soil in an oasis on northern edge of Tarim Basin, China[J]. Acta Pedologica Sinica, 2015, 52(6): 1345-1355.

[24] Xu Xiaoyan, Ma Yijie. K release from potassium containing minerals in soil and its significance for plant nutrition[J]. Chinese Journal of Soil Science, 2001, 32(4): 173-176.

[25] Zhang Lei, Zhang Yujuan, Sun Shixian, et al. Effects of different grazing intensity on soil organic carbon content in desert steppe[J/OL]. Acta Agrestia Sinica. [2025-04-14]. http://kns.cnki.net/kcms/detail/11.3362.s.20250410.1506.009.html.

[26] Zhao Xinmiao, Wang Yongming, Zhang Rongfeng, et al. The study of soil nutrients of Larix principis-rupprechtii plantations at different altitudes in the northern mountainous of Hebei[J]. Journal of Hebei Agricultural University, 2013, 36(4): 56-61, 81.

[27] Zhang Xibiao, Shangguan Zhouping. Effect of human-induced disturbance on physical properties of soil in artificial Pinus tabulaeformis Carr. forests of the Loess Plateau[J]. Acta Ecologica Sinica, 2006, 26(11): 3685-3695.