Chin J Plant Ecol ›› 2026, Vol. 50 ›› Issue (6): 1343-1356.DOI: 10.17521/cjpe.2025.0328  cstr: 32100.14.cjpe.2025.0328

• Research Articles • Previous Articles     Next Articles

Applicability assessment of global gross primary productivity products in alpine meadows of the Qingzang Plateau

LI Yu-Kun1,2, ZHENG Zhou-Tao1,*()(), CONG Nan1, ZHAO Guang1, ZHU Yi-Xuan1, ZHANG Yang-Jian1,2, SUN Xiao-Lin3, YAN Jun4   

  1. 1 Lhasa Plateau Ecosystem Research Station, 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 100049, China
    3 School of Life Sciences, Hebei University, Baoding, Hebei 071002, China
    4 Nagqu Agriculture, Animal Husbandry, and Prataculture Science and Technology Research and Extension Center, Nagqu, Xizang 852000, China
  • Received:2025-09-05 Accepted:2025-10-17 Online:2026-06-28 Published:2026-08-29
  • Contact: ZHENG Zhou-Tao
  • Supported by:
    National Natural Science Foundation of China(32061143037);The Science and Technology Projects of Xizang Autonomous Region, China(XZ202202YD0010C);The Science and Technology Projects of Xizang Autonomous Region, China(XZ202501ZY0118);The Science and Technology Projects of Xizang Autonomous Region, China(XZ202401ZY0103);The Science and Technology Projects of Xizang Autonomous Region, China(XZ202401JD0015)

Abstract:

Aims Gross Primary Productivity (GPP) is a key component of carbon cycle in terrestrial ecosystems, and improving its simulation accuracy is crucial for understanding the variations of carbon dioxide concentration in the atmosphere. Currently, there are numerous global GPP products developed based on different data sources and models, but systematic assessments of their performance in the Qingzang Plateau are lacking.

Methods In this study, we collected GPP data from 17 eddy covariance flux towers on the Qingzang Plateau and comprehensively evaluated the accuracy of 8 global GPP products (GPPGOSIF, GPPNIRv, GPPMODIS, GPPVPM, GPPGLASS, GPPTL-LUE, GPPPML, and GPPBESS) in alpine meadows of the Qingzang Plateau using three indicators: coefficient of determination, relative root mean square error, and relative bias.

Important findings The results showed that GPPVPM and GPPGOSIF generally exhibited relatively higher accuracy and were more suitable for the alpine meadows of the Qingzang Plateau. Moreover, the accuracy of GPP products varied significantly in space and time. Seasonally, the accuracy was higher in summer and autumn than in spring; in terms of ecosystem types, typical alpine meadow showed better accuracy than other meadow ecosystems; regarding permafrost types, the accuracy was higher in permafrost zone than in seasonal frost zone; in climate zones, semi-humid region demonstrated higher accuracy than semi-arid region; in terms of drought conditions, the accuracy was greater in non-drought months compared to drought months; and with respect to fractional vegetation cover conditions, medium and high vegetation cover stages achieved higher accuracy than low vegetation cover stages. This study reveals the uncertainties of global GPP products in the alpine meadows of the Qingzang Plateau and provides important insights for selecting GPP data and improving GPP simulations in this region.

Key words: Qingzang Plateau, gross primary productivity, statistical model, light use efficiency model, process model, accuracy