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

Abstract:

Aims

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.

Methods

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

摘要:

基于碳-水-氮耦合过程改进模型的温带草地生态系统生产力模拟研究

预测气候变化背景下生态系统总初级生产力的响应是全球变化生态学研究领域的一项核心任务。然而,对模型研究领域来说,准确模拟干旱生态系统总初级生产力的年际变异仍然是一个巨大的挑战。土壤含水量和总初级生产力对土壤水敏感性的精确模拟,是预测干旱生态系统中总初级生产力年际变异的两个关键方面。为此,本研究以一个广泛应用的生态系统模型(Biome-BGC模型)为例,旨在改进温带草地生态系统的模型模拟效果。一方面,通过对蒸散模块、土壤水沿剖面的垂直分布和田间持水量计算的改进和调整,模型实现了对土壤水模拟的更新。另一方面,我们改进了影响水-氮关系的函数,从而调节了总初级生产力对土壤水的敏感性。研究结果表明,原有模型高估了土壤含水量,低估了总初级生产力敏感性的年际变异,从而导致模拟总初级生产力的年际变异低于观测值。例如,原模型严重低估了总初级生产力在干旱年份的减少。相比之下,改进后的模型准确地模拟了观测土壤水的季节和年际变化,特别是表层土壤水。通过优化影响氮矿化的参数,改进后的模型改善了总初级生产力对土壤水敏感性的模拟,使其更接近观测值。因此,改进后模型对总初级生产力年际变异的模拟得到了很大程度的提高。我们的结果表明,在对干旱生态系统总初级生产力年际变异进行模拟时,应优先考虑表层土壤水及其对氮有效性的影响。

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