J Plant Ecol ›› 2021, Vol. 14 ›› Issue (1): 10-21 .DOI: 10.1093/jpe/rtaa072

• Research Articles • Previous Articles     Next Articles

Improvement of predicting ecosystem productivity by modifying carbon–water–nitrogen coupling processes in a temperate grassland

Kaili Cheng1,2 , Zhongmin Hu3,4, *, Shenggong Li1,2, *, Qun Guo1,2 , Yanbin Hao5 and Wenping Yuan4,6   

  1. 1 Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China, 2 College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China, 3 School of Geography, South China Normal University, Shipai Campus, Guangzhou 510631, China, 4 Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, 519082, China, 5 College of Life Sciences, University of Chinese Academy Sciences, Beijing 100049, China, 6 School of Atmospheric Sciences, Sun Yat-Sen University, Guangzhou 519082, China

    *Corresponding author. E-mail: huzm@m.scnu.edu.cn (Z.H.); lisg@igsnrr.ac.cn (S.L.)
  • Received:2020-05-07 Revised:2020-07-25 Accepted:2020-11-02 Online:2020-11-09 Published:2021-02-01



Prediction of changes in ecosystem gross primary productivity (GPP) in response to climatic variability is a core mission in the field of global change ecology. However, it remains a big challenge for the model community to reproduce the interannual variation (IAV) of GPP in arid ecosystems. Accurate estimates of soil water content (SWC) and GPP sensitivity to SWC are the two most critical aspects for predicting the IAV of GPP in arid ecosystems.


We took a widely used model Biome-BGC as an example, to improve the model performances in a temperate grassland ecosystem. Firstly, we updated the estimation of SWC by modifying modules of evapotranspiration, SWC vertical profile and field capacity. Secondly, we modified the function of controlling water–nitrogen relation, which regulates the GPP–SWC sensitivity.

Important Findings

The original Biome-BGC overestimated the SWC and underestimated the IAV of GPP sensitivity, resulting in lower IAV of GPP than the observations, e.g. it largely underestimated the reduction of GPP in drought years. In comparison, the modified model accurately reproduced the observed seasonal and IAVs in SWC, especially in the surface layer. Simulated GPP–SWC sensitivity was also enhanced and became closer to the observations by optimizing parameter controlling nitrogen mineralization. Consequently, the model’s capability of reproducing IAV of GPP has been largely improved by the modifications. Our results demonstrate that SWC in the surface layer and the consequent effects on nitrogen availability should be among the first considerations for accurate modeling IAV of GPP in arid ecosystems.

Key words: gross primary productivity, ecosystem model, soil water content, nitrogen constraint, sensitivity, grassland ecosystem




关键词: 总初级生产力, 生态系统模型, 土壤含水量, 氮限制, 敏感性, 草地生态系统