Joint structural and physiological control on the interannual variation in productivity in a temperate grassland: A data-model comparison

Zhongmin Hu, Hao Shi, Kaili Cheng, Ying Ping Wang, Shilong Piao, Yue Li, Li Zhang, Jianyang Xia, Lei Zhou, Wenping Yuan, Steve Running, Longhui Li, Yanbin Hao, Nianpeng He, Qiang Yu, Guirui Yu

Research output: Contribution to journalArticlepeer-review

61 Scopus citations

Abstract

Given the important contributions of semiarid region to global land carbon cycle, accurate modeling of the interannual variability (IAV) of terrestrial gross primary productivity (GPP) is important but remains challenging. By decomposing GPP into leaf area index (LAI) and photosynthesis per leaf area (i.e., GPP_leaf), we investigated the IAV of GPP and the mechanisms responsible in a temperate grassland of northwestern China. We further assessed six ecosystem models for their capabilities in reproducing the observed IAV of GPP in a temperate grassland from 2004 to 2011 in China. We observed that the responses to LAI and GPP_leaf to soil water significantly contributed to IAV of GPP at the grassland ecosystem. Two of six models with prescribed LAI simulated of the observed IAV of GPP quite well, but still underestimated the variance of GPP_leaf, therefore the variance of GPP. In comparison, simulated pattern by the other four models with prognostic LAI differed significantly from the observed IAV of GPP. Only some models with prognostic LAI can capture the observed sharp decline of GPP in drought years. Further analysis indicated that accurately representing the responses of GPP_leaf and leaf stomatal conductance to soil moisture are critical for the models to reproduce the observed IAV of GPP_leaf. Our framework also identified that the contributions of LAI and GPP_leaf to the observed IAV of GPP were relatively independent. We conclude that our framework of decomposing GPP into LAI and GPP_leaf has a significant potential for facilitating future model intercomparison, benchmarking and optimization should be adopted for future data-model comparisons.

Original languageEnglish
Pages (from-to)2965-2979
Number of pages15
JournalGlobal Change Biology
Volume24
Issue number7
DOIs
StatePublished - Jul 2018

Keywords

  • data-model comparison
  • ecosystem models
  • grassland
  • gross primary productivity
  • interannual variability

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