Preprints
https://doi.org/10.5194/bg-2017-536
https://doi.org/10.5194/bg-2017-536

  16 Jan 2018

16 Jan 2018

Review status: this discussion paper is a preprint. It has been under review for the journal Biogeosciences (BG). The manuscript was not accepted for further review after discussion.

Spatial estimation of soil carbon, nitrogen and phosphorus stoichiometry in complex terrains: a case study of Schrenk's spruce forest in the Tianshan Mountains

Zhonglin Xu1,2, Yapeng Chang1, Lu Li1, Qinghui Luo1, Zeyuan Xu1, Xiaofei Li1, Xuewei Qiao1, Xinyi Xu1, Xinni Song1, and Yao Wang3 Zhonglin Xu et al.
  • 1College of Resource and Environmental Science, Xinjiang University, Urumqi 830002, China
  • 2Key Laboratory of Oasis Ecology of the Ministry of Education, Xinjiang University, Urumqi 830002, China
  • 3Institute of Desert Meteorology, CMA, Urumqi, Urumqi 830002, China

Abstract. Spatial patterns of soil carbon (C), nitrogen (N) and phosphorus (P) and their stoichiometric characteristics (C : N : P) play an important role in nutrient limitations, community dynamics, nutrient use efficiency and biogeochemical cycles, etc. To date, the spatial distributions of soil organic C at various spatial scales have been extensively studied, whereas little is known about the spatial patterns of N and P and C : N : P ratios in various landscapes, especially across complex terrains. To fill this gap, we estimated the spatial patterns of concentrations of C, N and P and C : N : P ratios in Schrenk's spruce (Picea schrenkiana) forest in the Tianshan Mountains using multiple linear regression (MLR) model based on data from soil profiles collected from 2012 to 2017. We found that (1) elevation and climatic variables jointly contributed to concentrations of C, N and P and C : N : P ratios, (2) soil concentrations and stoichiometric ratios demonstrated different but continual spatial patterns in Schrenk's spruce forest, and (3) MLR models could be reliably used to estimate the spatial patterns of soil elemental concentrations and stoichiometric ratios in mountainous terrain. We suggest that more independent variables (including biotic, abiotic and anthropogenic factors) should be considered in future works. Additionally, adjustment of MLR and other models should be used for a better delineation of spatial patterns in the concentrations of soil elements and stoichiometric ratios.

Zhonglin Xu et al.

 
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Zhonglin Xu et al.

Zhonglin Xu et al.

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Short summary
Spatial distribution of ecological stochiometry is useful for studies corresponding to nutrient limitations, community dynamics, nutrient use efficiency and biogeochemical cycles. We syctematically sampled the soils in Schrenk's spruce forest and modeled the spatial distribution of C : N : P ratios in the forest. we found that multipel linear regression models could be reliably used to model the spatial patterns of soil elemental concentrations and stoichiometric ratios in mountainous terrain.
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