Large-scale estimates of gross primary production on the Qinghai-Tibet plateau based on remote sensing data

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.

[1]  Yanhong Tang,et al.  Application of the ORCHIDEE global vegetation model to evaluate biomass and soil carbon stocks of Qinghai‐Tibetan grasslands , 2010 .

[2]  Mingyuan Du,et al.  Mutual influence between human activities and climate change in the Tibetan Plateau during recent years , 2004 .

[3]  C. Long,et al.  Global distribution of cloud cover derived from NOAA/AVHRR operational satellite data , 1991 .

[4]  K. Mccree.  Photosynthetically Active Radiation , 1981 .

[5]  A-Xing Zhu,et al.  Developing a continental-scale measure of gross primary production by combining MODIS and AmeriFlux data through Support Vector Machine approach , 2007 .

[6]  Zhongbo Yu,et al.  Assessing future climate changes and extreme indicators in east and south Asia using the RegCM4 regional climate model , 2012, Climatic Change.

[7]  Min Liu,et al.  Large‐scale estimation and uncertainty analysis of gross primary production in Tibetan alpine grasslands , 2014 .

[8]  B. Holben.  Characteristics of maximum-value composite images from temporal AVHRR data , 1986 .

[9]  Huazhong Zhu,et al.  ESTIMATED BIOMASS AND PRODUCTIVITY OF NATURAL VEGETATION ON THE TIBETAN PLATEAU , 2002 .

[10]  N. Gobron,et al.  Diagnostic assessment of European gross primary production , 2008 .

[11]  S. Schubert,et al.  MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications , 2011 .

[12]  J. Tao,et al.  The impact of climate change and anthropogenic activities on alpine grassland over the Qinghai-Tibet Plateau , 2014 .

[13]  Dan Liu,et al.  Large Differences in Terrestrial Vegetation Production Derived from Satellite-Based Light Use Efficiency Models , 2014, Remote. Sens..

[14]  Ü. Rannik,et al.  Gap filling strategies for defensible annual sums of net ecosystem exchange , 2001 .

[15]  Liangfu Chen,et al.  Vegetation net primary productivity and its response to climate change during 2001-2008 in the Tibetan Plateau. , 2013, The Science of the total environment.

[16]  Karl E. Taylor,et al.  An overview of CMIP5 and the experiment design , 2012 .

[17]  F. Woodward,et al.  Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate , 2010, Science.

[18]  Yuan Jiang,et al.  Trends in the thermal growing season throughout the Tibetan Plateau during 1960–2009 , 2012 .

[19]  T. Vesala,et al.  Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes , 2007 .

[20]  Bruce K. Wylie,et al.  Adaptive data-driven models for estimating carbon fluxes in the Northern Great Plains , 2007 .

[21]  J. Lloyd,et al.  On the temperature dependence of soil respiration , 1994 .

[22]  K. Davis,et al.  Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data , 2010 .

[23]  S. Piao,et al.  Variations in Vegetation Net Primary Production in the Qinghai-Xizang Plateau, China, from 1982 to 1999 , 2006 .

[24]  Frank Veroustraete,et al.  Vegetation primary production estimation at maize and alpine meadow over the Heihe River Basin, China , 2012, Int. J. Appl. Earth Obs. Geoinformation.

[25]  Mingguo Ma,et al.  Estimation of gross primary production over the terrestrial ecosystems in China , 2013 .

[26]  Inez Y. Fung,et al.  The changing carbon cycle at Mauna Loa Observatory , 2007, Proceedings of the National Academy of Sciences.

[27]  John L. Innes,et al.  Spatial and temporal variations in the end date of the vegetation growing season throughout the Qinghai-Tibetan Plateau from 1982 to 2011 , 2014 .

[28]  S. Running,et al.  Global Terrestrial Gross and Net Primary Productivity from the Earth Observing System , 2000 .

[29]  Josep G. Canadell,et al.  Anthropogenic and biophysical contributions to increasing atmospheric CO 2 growth rate and airborne fraction , 2008 .

[30]  Yanhong Tang,et al.  Altitude and temperature dependence of change in the spring vegetation green-up date from 1982 to 2006 in the Qinghai-Xizang Plateau , 2011 .

[31]  Edwin W. Pak,et al.  An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data , 2005 .

[32]  Zhou Caiping,et al.  Estimation of Net Primary Productivity in Tibetan Plateau , 2004 .

[33]  Liqiang Ji,et al.  Carbon dynamics of terrestrial ecosystems on the Tibetan Plateau during the 20th century: an analysis with a process-based biogeochemical model , 2010 .

[34]  Steffen Fritz,et al.  Improved light and temperature responses for light-use-efficiency-based GPP models , 2013 .

[35]  Hu Dan,et al.  Simulation of terrestrial carbon cycle balance model in Tibet , 2003 .

[36]  Lin Zhao,et al.  Seasonal variations in carbon dioxide exchange in an alpine wetland meadow on the Qinghai-Tibetan Plateau. , 2009 .

[37]  Chunhua Zhang,et al.  Variations in net primary productivity and its relationships with warming climate in the permafrost zone of the Tibetan Plateau , 2015, Journal of Geographical Sciences.