← Back to articles
Scientific article 1 min read

Vertical stratification of soil stoichiometric drivers across urban forest parks in Shenzhen, China

The vertical distribution of soil nutrients and their stoichiometry is shaped by landscape-scale processes and soil-forming factors, but how these controls vary by depth remains unclear in urban forest parks. We examined this in six urban parks in Shenzhen, China, all below 300 m elevation and on similar parent material, by analyzing soil carbon (C), nitrogen (N), and phosphorus (P) stoichiometry across four depths (0–10, 10–20, 20–40, 40–60 cm). Higher N/P and C/P ratios in surface soils indicate potential P deficiency. Soil pH mainly regulates stoichiometry, likely by affecting P availabilit...

YR
Yukun Ren, Rongshu Zhu, Zhiqiang Dong, Wei Zeng, Fengjun Yuan, Zhengjun Shi
Scientific Reports · 2026

The vertical distribution of soil nutrients and their stoichiometry is shaped by landscape-scale processes and soil-forming factors, but how these controls vary by depth remains unclear in urban forest parks. We examined this in six urban parks in Shenzhen, China, all below 300 m elevation and on similar parent material, by analyzing soil carbon (C), nitrogen (N), and phosphorus (P) stoichiometry across four depths (0–10, 10–20, 20–40, 40–60 cm). Higher N/P and C/P ratios in surface soils indicate potential P deficiency. Soil pH mainly regulates stoichiometry, likely by affecting P availability. Precipitation and elevation shaped nutrient patterns through leaching control and organic matter buildup. Notably, dominant factors shifted with depth: climate, topography, and human management drove patterns in surface layers (0–20 cm), while plant diversity and inherent soil properties were more important at 20–60 cm. This shift suggests greater biological and legacy effects in deeper, less disturbed soil. Our findings show that soil stoichiometry marks biogeochemical separation with depth and underscores the need to include deep-soil processes in nutrient cycling models to better predict ecosystem stability under environmental change.

This article is peer-reviewed and appeared in Scientific Reports (2026). Feel free to use the content for educational purposes with attribution.

Imported from OpenAlex · View original

We use cookies to make the site work and — with your consent — to improve it. Read more in our privacy policy.