Spatial Partitioning and Driving Factors of Soil Carbon and Nitrogen Contents in Subtropical Urban Forests—A Case of Shenzhen, China
Abstract
1. Introduction
2. Materials and Methods
2.1. Overview of the Study Area
2.2. Soil Sampling and Determination of Indicators
2.3. Driver Data Acquisition
2.4. Data Processing
3. Results
3.1. Descriptive Analysis of SOC, TN, and C/N
3.2. Characterization of the Spatial Distribution of SOC, TN, and C/N
3.3. Spatial Autocorrelation Analysis of Soil Nutrients
3.4. Patterns of Spatial Distribution of SOC, TN, and C/N
3.5. Correlation Analysis of SOC, TN, and C/N with Impact Factors
3.6. Differences in SOC, TN, and C/N Across Vegetation Types
3.7. Regression Analysis of SOC, TN, and C/N with Environmental Factors
3.8. Structural Equation Analysis of SOC, TN, and C/N Using the Partial Least Squares Method
4. Discussion
4.1. Characterization of SOC, TN, and C/N and Spatial Distribution
4.2. Analysis of Spatial Distribution Characteristics and Anomaly Formation Mechanism
4.3. Analysis of Factors Affecting SOC, TN, and C/N
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Don, A.; Schumacher, J.; Freibauer, A. Impact of tropical land-use change on soil organic carbon stocks—A meta-analysis. Glob. Change Biol. 2011, 17, 1658–1670. [Google Scholar] [CrossRef]
- Bae, J.; Ryu, Y. Land use and land cover changes explain spatial and temporal variations of the soil organic carbon stocks in a constructed urban park. Landsc. Urban Plan. 2015, 136, 57–67. [Google Scholar] [CrossRef]
- Chen, F.-S.; Yavitt, J.; Hu, X.-F. Phosphorus enrichment helps increase soil carbon mineralization in vegetation along an urban-to-rural gradient, Nanchang, China. Appl. Soil Ecol. 2014, 75, 181–188. [Google Scholar] [CrossRef]
- Li, T.; Zheng, W.; Zhang, S.; Jia, Y.; Li, Y.; Xu, X. Spatial variations in soil phosphorus along a gradient of central city-suburb-exurban satellite. Catena 2018, 170, 150–158. [Google Scholar] [CrossRef]
- O’Brien, L.E.; Urbanek, R.E.; Gregory, J.D. Ecological functions and human benefits of urban forests. Urban For. Urban Green. 2022, 75, 127707. [Google Scholar] [CrossRef]
- Fang, X.; An, S.S.; Xue, Z.L.; Li, B.C. Small watersheds of the Loess Plateau based on maximum likelihood and moment methods Spatial variation analysis of soil carbon and nitrogen. Bull. Soil Water Conserv. 2014, 34, 141–146. [Google Scholar] [CrossRef]
- Setälä, H.M.; Francini, G.; Allen, J.A.; Hui, N.; Jumpponen, A.; Kotze, D.J. Vegetation type and age drive changes in soil properties, nitrogen and carbon sequestration in urban parks under cold climate. Front. Ecol. Evol. 2016, 4, 93. [Google Scholar] [CrossRef]
- Gregorich, E.G.; McLaughlin, N.B.; Lapen, D.R.; Ma, B.L.; Rochette, P. Soil Compaction, Both an Environmental and Agronomic Culprit: Increased Nitrous Oxide Emissions and Reduced Plant Nitrogen Uptake. Soil Sci. Soc. Am. J. 2014, 78, 1913–1923. [Google Scholar] [CrossRef]
- Guo, B.X.; Zhou, J.; Zhan, L.Q.; Wang, Z.Y.; Wu, W.; Liu, H.B. Spatial and Temporal Variability of Soil pH, Organic Matter and Available Nutrients (N, P and K) in Southwestern China. Agronomy 2024, 14, 1796. [Google Scholar] [CrossRef]
- Hadole, S.S.; Sarap, P.A.; Sarode, M.D.; Reddy, Y.A.; Padekar, P.D.; Dhule, D.T.; Dangore, S.T. Assessment of Spatial Variability of Major and Micro Nutrients in Soils of Satara District, Maharashtra, India. Int. J. Plant Soil Sci. 2024, 36, 541–552. [Google Scholar] [CrossRef]
- Lal, R. Soil Carbon Sequestration Impacts on Global Climate Change and Food Security. Science 2004, 304, 1623–1627. [Google Scholar] [CrossRef]
- Lili, Y.; Ning, M. Empirical Study on the Influence of Urban Environmental Industrial Structure Optimization on Ecological Landscape Greening Construction. Int. J. Environ. Res. Public Health 2022, 19, 16842. [Google Scholar] [CrossRef]
- Liu, D.; Wang, Z.; Zhang, B.; Song, K.; Li, X.; Li, J.; Li, F.; Duan, H. Spatial distribution of soil organic carbon and analysis of related factors in croplands of the black soil region, Northeast China. Agric. Ecosyst. Environ. 2005, 113, 73–81. [Google Scholar] [CrossRef]
- Liu, Q.Q.; Li, W.S.; Liu, X.; Dong, L.N.; Zhao, C.; Leng, H.M.; Liu, X.; Zhang, J.C. Effects of stampede on the species composition and diversity of vegetation in the herbaceous layer of urban forests and the physical and chemical properties of soil. J. Northeast. For. Univ. 2024, 52, 117–124. [Google Scholar] [CrossRef]
- Liu, W.L.; Zhang, L.B.; Ye, Y.H.; Zou, J.F.; Wang, Y.Z.; Qi, Y. The content and density of soil organic carbon under different land use types in Shenzhen. Ecol. Sci. 2011, 30, 486–492. [Google Scholar]
- Lu, Y.; Zhuang, J.; Yang, C.; Li, L.; Kong, M. How the digital economy promotes urban–rural integration through optimizing factor allocation: Theoretical mechanisms and evidence from China. Front. Sustain. Food Syst. 2025, 9, 1494247. [Google Scholar] [CrossRef]
- Santos-Andrade, M.; Hatje, V.; AriasOrtiz, A.; Patire, V.F.; da Silva, L.A. Human disturbance drives loss of soil organic matter and changes its stability and sources in mangroves. Environ. Res. 2021, 202, 111663. [Google Scholar] [CrossRef] [PubMed]
- Zhang, S.; Zhou, X.; Chen, Y.; Du, F.; Zhu, B. Soil organic carbon fractions in China: Spatial distribution, drivers, and future changes. Sci. Total Environ. 2024, 919, 170890. [Google Scholar] [CrossRef]
- Jiwen, C.; Ruili, Z.; Xiya, W.; Xinpeng, X.; Chao, A.; Ping, H.; Guoqing, L.; Wei, Z.; Ping, Z. Effect of high soil C/N ratio and nitrogen limitation caused by the long-term combined organic-inorganic fertilization on the soil microbial community structure and its dominated SOC decomposition. J. Environ. Manag. 2022, 303, 114155. [Google Scholar] [CrossRef]
- Niemelä, J.; Saarela, S.-R.; Söderman, T.; Kopperoinen, L.; Yli-Pelkonen, V.; Väre, S.; Kotze, D.J. Using the ecosystem services approach for better planning and conservation of urban green spaces: A Finland case study. Biodivers. Conserv. 2010, 19, 3225–3243. [Google Scholar] [CrossRef]
- Nowak, D.J.; Greenfield, E.J.; Hoehn, R.E.; Lapoint, E. Carbon storage and sequestration by trees in urban and community areas of the United States. Environ. Pollut. 2013, 178, 229–236. [Google Scholar] [CrossRef]
- Nyamadzawo, G.; Shukla, M.K.; Lal, R. Spatial variability of total soil carbon and nitrogen stocks for some reclaimed minesoils of southeastern Ohio. Land Degrad. Dev. 2008, 19, 275–288. [Google Scholar] [CrossRef]
- Qian, F.; Yu, Y.; Dong, X.; Gu, H. Soil Quality Evaluation Based on a Minimum Data Set (MDS)—A Case Study of Tieling County, Northeast China. Land 2023, 12, 1263. [Google Scholar] [CrossRef]
- Jing, Z.; Miao, Z.; Shaoyan, H.; Xuan, Z. Assessing spatial variability of soil organic carbon and total nitrogen in eroded hilly region of subtropical China. PLoS ONE 2020, 15, e0244322. [Google Scholar] [CrossRef]
- Ginestet, C. ggplot2: Elegant Graphics for Data Analysis. J. Stat. Softw. 2011, 174, 245–246. [Google Scholar] [CrossRef]
- Gromping, U. Relative Importance for Linear Regression in R: The Package relaimpo. J. Stat. Softw. 2006, 17, 1–27. [Google Scholar] [CrossRef]
- Min-Suk, K.; Sang-Hwan, L.; Jeong-Gyu, K. Evaluation of factors affecting arsenic uptake by Brassica juncea in alkali soil after biochar application using partial least squares path modeling (PLS-PM). Chemosphere 2021, 275, 130095. [Google Scholar] [CrossRef]
- Ramon, M.; Lafortezza, R.; Ribeiro, A.P.; Camargo, P.B.d.; Domingos, M.; Gomes, E.P.C.; Tavares, A.d.R.; Dias, A.G.; Kniess, C.T.; Ferreira, M.L. Carbon and nitrogen stock in soils of subtropical urban forests: Isotopic δ13C and δ15N indicators for nature-based solutions in a megacity. Ecol. Indic. 2024, 160, 111743. [Google Scholar] [CrossRef]
- Kiran, G.S.; Kinnary, S. Carbon Sequestration by Urban Trees on Roadsides of Vadodara City. Int. J. Eng. Sci. Technol. 2011, 3, 3066. [Google Scholar]
- Semenov, M.Y.; Silaev, A.V.; Semenov, Y.M.; Begunova, L.A.; Semenov, Y.M. Identifying and Characterizing Critical Source Areas of Organic and Inorganic Pollutants in Urban Agglomeration in Lake Baikal Watershed. Sustainability 2022, 14, 14827. [Google Scholar] [CrossRef]
- Shaopan, X.; Zhaoliang, S.; Lukas, V.Z.; Laodong, G.; Changxun, Y.; Weiqi, W.; Qiang, L.; Hartley, P.I.; Yuanhe, Y.; Hongyan, L.; et al. Storage, patterns and influencing factors for soil organic carbon in coastal wetlands of China. Glob. Change Biol. 2022, 28, 6065–6085. [Google Scholar] [CrossRef]
- Song, P.; Kim, G.; Mayer, A.; He, R.; Tian, G. Assessing the Ecosystem Services of Various Types of Urban Green Spaces Based on i-Tree Eco. Sustainability 2020, 12, 1630. [Google Scholar] [CrossRef]
- Sun, Q.; Wang, P.; Zhou, H.M.; Wang, X.J.; Xie, W.Y.; Yang, Z.X. Spatial variability of soil carbon, nitrogen and phosphorus ecological stoichiometric characteristics in small watersheds in loess hilly area. Chin. J. Ecol. 2020, 39, 766–774. [Google Scholar] [CrossRef]
- Wang, J.; Yang, R.; Bai, Z. Spatial variability and sampling optimization of soil organic carbon and total nitrogen for Minesoils of the Loess Plateau using geostatistics. Ecol. Eng. 2015, 82, 159–164. [Google Scholar] [CrossRef]
- Wang, X.; Wang, C.; Zhang, Y.; Yan, Y. Pathway to identify and assess regional potential soil pollution risk from industrial activities: Case of Pearl River Delta region, China. Int. J. Sustain. Dev. World Ecol. 2025, 32, 511–524. [Google Scholar] [CrossRef]
- Wu, L.; Li, L.; Yao, Y.; Qin, F.; Guo, Y.; Gao, Y.; Zhang, M. Spatial distribution of soil organic carbon and its influencing factors at different soil depths in a semiarid region of China. Environ. Earth Sci. 2017, 76, 654. [Google Scholar] [CrossRef]
- Xin, Z.; Qin, Y.; Yu, X. Spatial variability in soil organic carbon and its influencing factors in a hilly watershed of the Loess Plateau, China. Environ. Earth Sci. 2016, 137, 660–669. [Google Scholar] [CrossRef]
- Xing, H.; Yang, L. Retention of fragmented fine woody debris enhances soil health, microbial activity, and ecosystem functions in urban forests of Northeast China. Plant Soil 2025, 1–19. [Google Scholar] [CrossRef]
- Xiong, X.; Xiong, H.Q.; Guo, X.; Han, Y.; Qing, Z.; Chen, L.; Yu, H.M. Spatial variation characteristics of total nitrogen, organic carbon and carbon-to-nitrogen ratio of cultivated land in typical hilly areas in southern China and their influencing factors. J. Plant Nutr. Fertil. 2020, 26, 1656–1668. [Google Scholar]
- Xiong, Z.; Li, S.; Yao, L.; Liu, G.; Zhang, Q.; Liu, W. Topography and land use effects on spatial variability of soil denitrification and related soil properties in riparian wetlands. Ecol. Eng. 2015, 83, 437–443. [Google Scholar] [CrossRef]
- Chao, Y.; Huizeng, L.; Qingquan, L.; Aihong, C.; Rongling, X.; Tiezhu, S.; Jie, Z.; Wenxiu, G.; Xiang, Z.; Guofeng, W. Rapid Urbanization Induced Extensive Forest Loss to Urban Land in the Guangdong-Hong Kong-Macao Greater Bay Area, China. Chin. Geogr. Sci. 2021, 31, 93–108. [Google Scholar] [CrossRef]
- Zhang, D.; Feng, Y.; Zhang, B.; Fan, X.; Han, Z.; Zhang, J. Unveiling the Spatial Variability of Soil Nutrients in Typical Karst Rocky Desertification Areas. Water 2024, 16, 334. [Google Scholar] [CrossRef]
- Zhou, X.Y.; Wang, S.Q. The spatio-temporal response of ecosystem service value of the Yangtze River Economic Belt to urban expansion based on the GTWR model. Res. Soil Water Conserv. 2021, 28, 300–307. [Google Scholar] [CrossRef]
- Zhu, Y.; Jia, P.; Liu, Y. Spatiotemporal evolution effects of habitat quality with the conservation policies in the Upper Yangtze River, China. Sci. Rep. 2025, 15, 5972. [Google Scholar] [CrossRef] [PubMed]
Driving Factor | Type | Units | Resolution | Data Sources |
---|---|---|---|---|
Climatic | Average annual temperature | °C | 1 km | National Earth System Science Data Center |
Average annual rainfall | mm | 1 km | National Earth System Science Data Center | |
Geomorphologic | Elevation | m | / | Real time data |
Slope | ° | / | Real time data | |
Human | Nighttime Lighting Index | / | / | Resource and Environmental Sciences Data Center |
GDP | CNY·km−2 | 1 km | National Tibetan Plateau Data Center | |
Population density | persons·km−2 | / | Oak Ridge National Laboratory, USA | |
Distance to City Hall | m | / | National Center for Basic Geographic Information | |
Plant | Normalized Difference Vegetation Index | / | 1 km | Resource and Environmental Sciences Data Center |
Fractional Vegetation Cover | % | 250 m | Resource and Environmental Sciences Data Center | |
Net Primary Productivity | g/(m2·a) | 1 km | Resource and Environmental Sciences Data Center | |
Crown density | / | / | Real time data | |
Average tree height | m | / | Real time data | |
Soil | pH | / | / | Real time data |
Conductivity | dS/cm | / | Real time data | |
Bulk density | g/cm3 | / | Real time data | |
Mechanical stable aggregate | mm | / | Real time data | |
Mean weight diameter | mm | / | Real time data | |
Geometric mean diameter | mm | / | Real time data |
Index | Depth (cm) | Min/(g·kg−1) | Max/(g·kg−1) | Average Value/(g·kg−1) | Standard Deviation | Coefficient of Variation (%) | Skewness | Kurtosis | p(K–S) |
---|---|---|---|---|---|---|---|---|---|
SOC | 0–10 | 3.18 | 33.81 | 18.32 | 7.00 | 38.21 | 0.07 | −0.36 | 0.20 |
10–30 | 1.30 | 23.68 | 9.24 | 4.18 | 45.24 | 0.87 | 1.33 | 0.20 | |
TN | 0–10 | 0.26 | 2.41 | 1.29 | 0.49 | 37.98 | 0.02 | −0.32 | 0.20 |
10–30 | 0.18 | 1.33 | 0.67 | 0.28 | 41.79 | 0.35 | −0.52 | 0.20 | |
C/N | 0–10 | 7.70 | 19.29 | 14.43 | 2.27 | 15.73 | 0.01 | 0.01 | 0.20 |
10–30 | 5.29 | 20.44 | 13.75 | 2.68 | 19.49 | −0.07 | 1.41 | 0.05 |
Index | Depth | Theoretical Model | Nugget Value | Abutment Value | Block base Ratio/% | Range/m | R2 | IN | Z | Cross Validation | |
---|---|---|---|---|---|---|---|---|---|---|---|
(cm) | MAPE | RMSE | |||||||||
SOC | 0–10 | Spherical | 6.6 | 74.8 | 8.82 | 2443 | 0.39 | 0.62 | 13.35 | 0.24 | 4.96 |
10–30 | Gaussian | 0.22 | 3.45 | 6.38 | 6948.99 | 0.49 | 0.25 | 5.48 | 0.36 | 4.07 | |
TN | 0–10 | Gaussian | 0 | 0.33 | 0.3 | 864.29 | 0.54 | 0.47 | 10.58 | 0.28 | 0.54 |
10–30 | Exponential | 0.03 | 0.37 | 7.22 | 21,330 | 0.31 | 0.22 | 4.92 | 0.31 | 0.33 | |
C/N | 0–10 | Linear | 4.05 | 4.05 | 100 | 11,031.57 | 0.78 | 0.42 | 8.99 | 0.14 | 2.14 |
10–30 | Linear | 7.23 | 7.23 | 100 | 12,380.85 | 0.63 | 0.29 | 6.38 | 0.31 | 3.14 |
Vegetation Type | Soil Depth/(cm) | SOC/(g·kg−1) | TN (g·kg−1) | C/N |
---|---|---|---|---|
Secondary broadleaf forest | 0–10 | 18.40 ± 7.39 a | 1.28 ± 0.48 a | 14.39 ± 2.00 a |
10–30 | 9.56 ± 3.82 ab | 0.71 ± 0.26 a | 13.38 ± 2.69 a | |
Broad-leaved plantation | 0–10 | 18.62 ± 6.29 a | 1.29 ± 0.46 a | 14.69 ± 2.11 a |
10–30 | 8.00 ± 3.11 b | 0.58 ± 0.23 a | 13.94 ± 2.18 a | |
Coniferous forests | 0–10 | 17.25 ± 8.01 a | 1.31 ± 0.63 a | 13.86 ± 3.46 a |
10–30 | 11.28 ± 6.69 a | 0.78 ± 0.39 a | 14.55 ± 3.78 a |
Depth Soil/cm | Impact Factor | Non-Standardized Coefficient | Standardized Coefficient | t | p | VIF | R2 | Adj. R2 | AIC | BIC | F | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
B | Standard Error | Beta | |||||||||||
SOC | 0–10 | / | 31.16 | 9.27 | 0.00 | 3.36 | 0.001 *** | - | 0.46 | 0.43 | 397.6 | 408.31 | F = 16.346, p = 0.000 *** |
BD | −25.70 | 5.86 | −0.45 | −4.39 | 0.000 *** | 1.10 | |||||||
EC | 119.19 | 29.59 | 0.48 | 4.03 | 0.000 *** | 1.48 | |||||||
AP | 0.00 | 0.00 | 0.32 | 2.81 | 0.007 *** | 1.37 | |||||||
TN | / | 1.42 | 0.61 | 0.00 | 2.32 | 0.024 ** | - | 0.52 | 0.48 | 53.65 | 66.51 | F = 14.982, p = 0.000 *** | |
EC | 5.99 | 1.85 | 0.35 | 3.24 | 0.002 *** | 1.32 | |||||||
BD | −1.00 | 0.41 | −0.25 | −2.43 | 0.018 ** | 1.23 | |||||||
ELE | 0.00 | 0.00 | 0.23 | 2.49 | 0.016 ** | 1.02 | |||||||
CD | 0.69 | 0.29 | 0.26 | 2.35 | 0.023 ** | 1.42 | |||||||
C/N | / | 26.75 | 5.10 | 0.00 | 5.25 | 0.000 *** | - | 0.88 | 0.87 | 160.72 | 173.58 | F = 83.078, p = 0.000 *** | |
GWD | −3.31 | 1.57 | −0.10 | −2.11 | 0.040 ** | 1.09 | |||||||
BD | −1.37 | 1.03 | −0.07 | −1.33 | 0.190 | 1.44 | |||||||
TN | −8.67 | 0.46 | −1.86 | −19.01 | 0.000 *** | 4.49 | |||||||
SOC | 0.60 | 0.03 | 1.86 | 17.91 | 0.000 *** | 5.06 | |||||||
SP | −0.02 | 0.01 | −0.12 | −2.44 | 0.018 ** | 1.08 | |||||||
SOC | 10–30 | / | 80.36 | 16.48 | 0.00 | 4.88 | 0.000 *** | - | 0.42 | 0.39 | 334.44 | 345.16 | F = 13.629, p = 0.000 *** |
BD | −18.21 | 3.93 | −0.47 | −4.63 | 0.000 *** | 1.00 | |||||||
ELE | 0.01 | 0.00 | 0.36 | 3.54 | 0.001 *** | 1.01 | |||||||
GWD | −16.24 | 5.16 | −0.32 | −3.15 | 0.003 *** | 1.02 | |||||||
TN | / | 1.58 | 0.43 | 0.00 | 3.70 | 0.000 *** | - | 0.28 | 0.24 | 6.55 | 17.26 | F = 7.414, p = 0.000 *** | |
BD | −0.93 | 0.29 | −0.37 | −3.22 | 0.002 *** | 1.02 | |||||||
ELE | 0.00 | 0.00 | 0.25 | 2.23 | 0.030 ** | 1.00 | |||||||
EC | 4.43 | 2.06 | 0.24 | 2.15 | 0.036 ** | 1.02 | |||||||
C/N | / | 14.46 | 1.02 | 0.00 | 14.18 | 0.000 *** | - | 0.82 | 0.81 | 208.93 | 221.79 | F = 65.42, p = 0.000 *** | |
SOC | 1.29 | 0.08 | 1.99 | 15.30 | 0.000 *** | 5.39 | |||||||
TN | −18.51 | 1.27 | −1.87 | −14.56 | 0.000 *** | 5.25 | |||||||
EC | 29.32 | 10.65 | 0.16 | 2.75 | 0.008 *** | 1.12 | |||||||
NDVI | −2.40 | 1.10 | −0.12 | −2.17 | 0.034 ** | 1.03 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Dong, Z.; Du, S.; Mao, X.; Xie, H.; Shi, Z.; Zeng, W. Spatial Partitioning and Driving Factors of Soil Carbon and Nitrogen Contents in Subtropical Urban Forests—A Case of Shenzhen, China. Forests 2025, 16, 1492. https://doi.org/10.3390/f16091492
Dong Z, Du S, Mao X, Xie H, Shi Z, Zeng W. Spatial Partitioning and Driving Factors of Soil Carbon and Nitrogen Contents in Subtropical Urban Forests—A Case of Shenzhen, China. Forests. 2025; 16(9):1492. https://doi.org/10.3390/f16091492
Chicago/Turabian StyleDong, Zhiqiang, Shaobo Du, Xufeng Mao, Huichun Xie, Zhengjun Shi, and Wei Zeng. 2025. "Spatial Partitioning and Driving Factors of Soil Carbon and Nitrogen Contents in Subtropical Urban Forests—A Case of Shenzhen, China" Forests 16, no. 9: 1492. https://doi.org/10.3390/f16091492
APA StyleDong, Z., Du, S., Mao, X., Xie, H., Shi, Z., & Zeng, W. (2025). Spatial Partitioning and Driving Factors of Soil Carbon and Nitrogen Contents in Subtropical Urban Forests—A Case of Shenzhen, China. Forests, 16(9), 1492. https://doi.org/10.3390/f16091492