Large-scale estimates of gross primary production on the Qinghai-Tibet plateau based on remote sensing data. Issue 11 (2nd November 2018)

• Record Type: Journal Article
• Authors: Ma, Minna; Yuan, Wenping; Dong, Jie; Zhang, Fawei; Cai, Wenwen; Li, Hongqin
• Is Part Of: International journal of digital earth. Volume 11:Issue 11(2018)
• Page Start: 1166
• Page End: 1183
• Publication Date: 2018-11-02
• Subjects: Qinghai-Tibetan Plateau -- gross primary production -- EC-LUE model -- eddy covariance -- light use efficiency; Geographic information systems -- Periodicals; Sustainable development -- Information technology -- Periodicals; Social planning -- Information technology -- Periodicals; 910.285
• DOI: 10.1080/17538947.2017.1381192
• Languages: English
• ISSNs: 1753-8947

Abstract

ABSTRACT: Vegetation gross primary production (GPP) is an important variable for the carbon cycle on the Qinghai-Tibetan Plateau (QTP). Based on the measurements from 12 eddy covariance flux sites, we validated a light use efficiency model (i.e. EC-LUE) to evaluate the spatial-temporal patterns of GPP and the effect of environmental variables on QTP. In general, EC-LUE model performed well in predicting GPP at different time scale over QTP. Annual GPP over the entire QTP ranged from 575 to 703 Tg C, and showed a significantly increasing trend from 1982 to 2013. However, there were large spatial heterogeneities in long-term trends of GPP. Throughout the entire QTP, air temperature increase had a greater influence than solar radiation and precipitation (PREC) changes on productivity. Moreover, our results highlight the large uncertainties of previous GPP estimates due to insufficient parameterization and validations. When compared with GPP estimates of the EC-LUE model, most Coupled Model Intercomparison Project (CMIP5) GPP products overestimate the magnitude and increasing trends of regional GPP, which potentially impact the feedback of ecosystems to regional climate changes.