Biogeochemical Responses of Soil Organic Carbon and Enzymatic Activity to Elevation and Depth: Comparing Fixed Depth and Equivalent Soil Mass Approaches

Document Type : Research Paper

Authors

Department of Soil Science, Faculty of Agriculture, University of Zanjan, Zanjan, Iran

10.22059/ijswr.2025.399910.669990

Abstract

Soil organic carbon stocks (SOCs) and enzyme activities are key indicators for assessing ecosystem dynamics in mountainous regions. This study examined variations in SOCs and the activity of major enzymes along an altitudinal gradient (0–2400 m) and a depth gradient (0–100 cm) in mountain forests. Two approaches, fixed depth (FD) and equivalent soil mass (ESM), were applied to estimate SOCs. The results showed that SOCs were significantly influenced by altitude, depth, and their interaction (P ≤ 0.001). SOCs increased with altitude but decreased with depth; the highest and lowest values up to one meter depth were recorded at altitudes of 1800–2400 m and 0–600 m, respectively, representing a 1.14-fold increase in SOCs at higher elevations. Moreover, mean SOCs in deep layers (80–100 cm) showed about a 70% reduction compared with the surface layer (0–20 cm). The ESM method provided greater accuracy than the fixed-depth method (CV = 2.61% vs. 3.65%). The activities of β-glucosidase, urease, and arylsulfatase increased with altitude but decreased with depth, whereas cellulase, acid phosphatase, and alkaline phosphatase decreased with both factors. In contrast, dehydrogenase (DHA) activity increased with depth and exhibited a negative correlation with SOCs (r = –0.92). Additionally, SOCs were strongly correlated with microbial biomass carbon (r = 0.99) and enzyme activities (r ≥ 0.82), while its depth distribution remained consistent across the entire altitudinal gradient. These findings underscore the importance of jointly considering soil depth and altitude in SOC modeling and the sustainable management of mountain ecosystems.

Keywords

Main Subjects

Introduction

Soil Organic Carbon (SOC) is a critical component of terrestrial carbon pools and plays a key role in soil health, productivity, and climate change mitigation. In mountainous forest ecosystems, SOC stocks and related microbial processes are shaped by topographic variations, particularly elevation and soil depth. These factors jointly influence microclimatic conditions, vegetation dynamics, and organic matter decomposition. Enzyme-mediated biogeochemical processes serve as sensitive indicators of soil microbial activity and are tightly linked to carbon cycling. However, the combined effects of elevation and depth on SOC and enzyme activity have not been comprehensively studied, especially using both fixed-depth and equivalent soil mass (ESM) approaches. This study aimed to evaluate SOC stocks and key enzyme activities along an elevation gradient and across soil profiles in a mountainous forest ecosystem.

Methods

The study was conducted in a mountainous forest region covering an elevation range from 0 to 2400 meters above sea level. Soil samples were collected along this gradient using two methods: the conventional fixed-depth method and the Equivalent Soil Mass (ESM) approach, which accounts for differences in soil bulk density to provide more accurate carbon stock estimations. Samples were taken from five soil depth intervals: 0–20 cm, 20–40 cm, 40–60 cm, 60–80 cm, and 80–100 cm. SOC was measured using standard dry combustion methods. Microbial activity was assessed by analyzing the activity of key soil enzymes: β-glucosidase, urease, arylsulfatase, cellulase, acid phosphatase, alkaline phosphatase, and dehydrogenase. Statistical analyses including ANOVA and Pearson correlation were applied to evaluate the effects of elevation and soil depth on SOC stocks and enzyme activities.

Results

SOC stocks were significantly affected by elevation, soil depth, and their interaction (P ≤ 0.001). Soil depth had the strongest influence, with SOC stocks decreasing by approximately 70% from the surface layer (0–20 cm) to the deepest layer (80–100 cm). In contrast, SOC stocks increased by 1.14 times from the lowest to the highest elevation. The ESM method provided higher sensitivity and accuracy than the fixed-depth method, with a lower coefficient of variation (CV = 2.61% vs. 3.65%). It was more effective in detecting significant SOC differences across elevation and precipitation gradients. Enzyme activities responded differently to changes in elevation and depth. Activities of β-glucosidase, urease, and arylsulfatase increased significantly with elevation but declined with increasing soil depth. Conversely, cellulase, acid phosphatase, and alkaline phosphatase activities showed a decreasing trend along both elevation and depth gradients. Dehydrogenase activity exhibited an opposite pattern, increasing up to 49 times with depth and showing a strong negative correlation with SOC (R² = 0.83), suggesting microbial adaptation to carbon-limited conditions in deeper layers. SOC also showed a strong positive correlation with microbial biomass carbon (r = 0.99) and enzyme activity (r ≥ 0.82). Despite the increase in total SOC stocks with elevation, the relative distribution of carbon with soil depth remained consistent. This suggests structural stability in vegetation cover and root distribution across the elevation gradient.

Conclusions

This study highlights the importance of accounting for both elevation and soil depth when assessing SOC dynamics in mountainous forest ecosystems. The Equivalent Soil Mass (ESM) method proved to be a more accurate and sensitive tool for estimating SOC stocks under varying topographic and climatic conditions. The contrasting enzyme activity patterns underscore the complexity of microbial responses to environmental gradients. While SOC stocks increased with elevation, the vertical distribution of carbon remained stable, likely due to consistent vegetation structure. These findings emphasize the need to integrate both vertical and elevational dimensions in carbon modeling and land management strategies, particularly in topographically complex and climate-sensitive regions.

Author Contributions

Elham Jozedaemi: Writing – original draft, Methodology, Formal analysis, Investigation, Resources.

Ahmad Golchin: Writing – review and editing, Supervision, Methodology, Conceptualization, Resources.

Mehran Misaghi: Writing – review and editing, Investigation, Resources, Software, Formal analysis.

Data Availability Statement

Data available on request from the authors.

 

Acknowledgements

The authors express their gratitude to the University of Zanjan, Zanjan, Iran, for its financial and technical support, which facilitated the completion of this study.

Conflict of interest

The author declares no conflict of interest.

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Iranian Journal of Soil and Water Research
Volume 56, Issue 10
January 2026
Pages 2767-2790

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