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Aims <p>Nitrogen is a key indicator of soil fertility and strongly regulates forest productivity. Although China’s forests span broad environmental gradients, national-scale assessments of soil total nitrogen (STN) across forest distribution areas remain limited. From 2021 to 2023, we collected 3,029 soil sample points from depths of 0–100&#xa0;cm across China's forest regions.</p> Methods <p>We applied an integrated framework combining SCORPAN-based digital soil mapping (DSM) as a tool, interpretable machine learning, and structural equation modeling to generate forest-domain STN predictions and to diagnose classification-based patterns of topsoil STN.</p> Results <p>The quantile regression forest model reliably predicted STN and revealed pronounced spatial heterogeneity across China’s forests. STN exhibited strong vertical stratification, decreasing significantly with depth (<i>p</i> &lt; 0.05). Plateau climate zones stored the highest STN (3.84&#xa0;g&#xa0;kg⁻<sup>1</sup>), followed by temperate zones, while subtropical and tropical zones showed lower values. Natural forests contained 53.20% higher STN than plantations, and mixed forests exceeded pure forests by 5.88%. Loamy soils retained more nitrogen than clayey or sandy soils. Soil depth interval (SD) was treated as a stratification control variable capturing the expected vertical gradient; after accounting for SD, macro-geographical factors (e.g., elevation and latitude) primarily influenced STN through indirect, climate-mediated pathways.</p> Conclusions <p>Forest STN in China follows a hierarchical organization characterized by strong vertical stratification and broad horizontal gradients driven mainly by climate-mediated geographic controls and forest attributes. Promoting mixed-species forests in temperate regions and conserving natural forests in plateau areas may enhance soil nitrogen retention. This study provides a coherent forest-domain perspective on national STN patterns, supporting spatially explicit forest management under environmental change.</p>

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Multi-dimensional heterogeneity and drivers of soil total nitrogen across China's forests

  • 期刊论文

  • 发表日期：

    2026年4月29日

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  • Xin Zhang,
  • Jizhen Chen,
  • Zihao Fan,
  • Zhilin Huang,
  • Jifa Qin

摘要

Aims

Nitrogen is a key indicator of soil fertility and strongly regulates forest productivity. Although China’s forests span broad environmental gradients, national-scale assessments of soil total nitrogen (STN) across forest distribution areas remain limited. From 2021 to 2023, we collected 3,029 soil sample points from depths of 0–100 cm across China's forest regions.

Methods

We applied an integrated framework combining SCORPAN-based digital soil mapping (DSM) as a tool, interpretable machine learning, and structural equation modeling to generate forest-domain STN predictions and to diagnose classification-based patterns of topsoil STN.

Results

The quantile regression forest model reliably predicted STN and revealed pronounced spatial heterogeneity across China’s forests. STN exhibited strong vertical stratification, decreasing significantly with depth (p < 0.05). Plateau climate zones stored the highest STN (3.84 g kg⁻1), followed by temperate zones, while subtropical and tropical zones showed lower values. Natural forests contained 53.20% higher STN than plantations, and mixed forests exceeded pure forests by 5.88%. Loamy soils retained more nitrogen than clayey or sandy soils. Soil depth interval (SD) was treated as a stratification control variable capturing the expected vertical gradient; after accounting for SD, macro-geographical factors (e.g., elevation and latitude) primarily influenced STN through indirect, climate-mediated pathways.

Conclusions

Forest STN in China follows a hierarchical organization characterized by strong vertical stratification and broad horizontal gradients driven mainly by climate-mediated geographic controls and forest attributes. Promoting mixed-species forests in temperate regions and conserving natural forests in plateau areas may enhance soil nitrogen retention. This study provides a coherent forest-domain perspective on national STN patterns, supporting spatially explicit forest management under environmental change.