Preprints
https://doi.org/10.5194/essd-2020-398
https://doi.org/10.5194/essd-2020-398

  08 Mar 2021

08 Mar 2021

Review status: a revised version of this preprint is currently under review for the journal ESSD.

Patterns of nitrogen and phosphorus pools in terrestrial ecosystems in China

Yi-Wei Zhang1,, Yanpei Guo1,, Zhiyao Tang1, Yuhao Feng1, Xinrong Zhu1, Wenting Xu2, Yongfei Bai2, Guoyi Zhou3, Zongqiang Xie2, and Jingyun Fang1 Yi-Wei Zhang et al.
  • 1Institute of Ecology, College of Urban and Environmental Sciences and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871
  • 2State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093
  • 3Institute of Ecology, Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
  • Equal contribution

Abstract. Recent increases in atmospheric carbon dioxide (CO2) and temperature relieve the limitation of these two on terrestrial ecosystem productivity, while nutrient availability constrains the increasing plant photosynthesis more intensively. Nitrogen (N) and phosphorus (P) are critical for plant physiological activities and consequently regulates ecosystem productivity. Here, for the first time, we mapped N and P densities of leaves, woody stems, roots, litter and soil in forest, shrubland and grassland ecosystems across China, based on an intensive investigation in 4175 sites, covering species composition, biomass, and nutrient concentrations of different tissues of living plants, litter and soil. Forest, shrubland and grassland ecosystems in China stored 7665.62 × 106 Mg N, with 7434.53 × 106 Mg (96.99 %) fixed in soil (to a depth of one metre), and 32.39 × 106 Mg (0.42 %), 59.57 × 106 Mg (0.78 %), 124.21 × 106 Mg (1.62 %) and 14.92 × 106 Mg (0.19 %) in leaves, stems, roots and litter, respectively. The forest, shrubland and grassland ecosystems in China stored 3852.66 × 106 Mg P, with 3821.64 × 106 Mg (99.19 %) fixed in soil (to a depth of one metre), and 3.36 × 106 Mg (0.09 %), 14.06 × 106 Mg (0.36 %), 11.47 × 106 Mg (0.30 %) and 2.14 × 106 Mg (0.06 %) in leaves, stems, roots and litter, respectively. Our estimation showed that N pools were low in northern China except Changbai Mountains, Mount Tianshan and Mount Alta, while relatively higher values existed in eastern Qinghai-Tibetan Plateau and Yunnan. P densities in plant organs were higher towards the south and east part of China, while soil P density was higher towards the north and west part of China. The estimated N and P density datasets, Patterns of nitrogen and phosphorus pools in terrestrial ecosystems in China (the pre-publication sharing link: https://datadryad.org/stash/share/78EBjhBqNoam2jOSoO1AXvbZtgIpCTi9eT-eGE7wyOk, are available from the Dryad Digital Repository (Zhang et al., 2020). These patterns of N and P densities could potentially improve existing earth system models and large-scale researches on ecosystem nutrients.

Yi-Wei Zhang et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2020-398', Anonymous Referee #1, 27 Mar 2021
    • AC1: 'Reply on RC1', Yiwei Zhang, 15 Jun 2021
  • RC2: 'Comment on essd-2020-398', Enqing Hou, 31 Mar 2021
    • AC2: 'Reply on RC2', Yiwei Zhang, 15 Jun 2021
  • EC1: 'Final reviewer report for essd-2020-398', David Carlson, 28 Jul 2021
    • AC3: 'Reply on EC1', Yiwei Zhang, 30 Jul 2021

Yi-Wei Zhang et al.

Data sets

Patterns of nitrogen and phosphorus pools in terrestrial ecosystems in China Zhang, Y. W., Guo, Y. P., Tang, Z. Y., Feng, Y. H., Zhu, X. R., Xu, W. T., Bai, Y. F., Zhou, G. Y., Xie, Z. Q., and Fang, J. Y. https://doi.org/10.5061/dryad.6hdr7sqzx

Yi-Wei Zhang et al.

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Short summary
Nitrogen (N) and phosphorus (P) are limiting nutrients for ecosystem productivity. For the first time, we mapped N and P densities of living plants, litter and soil in forest, shrubland and grassland ecosystems across China using artificial neural network models based on a dataset of 4,175 field sites. Our results depicted the spatial distribution pattern, the total pool, and the allocation among ecosystem components of N and P, which could benefit a more precise prediction of carbon cycle.