A growing season climatic index to simulate gross primary productivity and carbon budget in a Tibetan alpine meadow

摘要: Accurate estimation of gross primary production (GPP) ecosystem is needed to evaluate terrestrial carbon cycle at various spatial and temporal scales. Eddy covariance (EC) technique provides continuous measurements net CO2 exchange (NEE) can be used separate GPP from NEE in real time series. However, seasonal inter-annual variation consequently budget still very difficult simulate climatic environment. To address this limitation, we develop a growing season indicator (GSI) based on low temperature soil water stress model predict intra dynamic productivity (GPP). Validation new index was conducted using six-year consective EC measurement 2004 2009 Tibetan alpine meadow. Simulated agreed well with the observed terms variation. The correlation coefficients scale between GSI scalar derived reached more than 0.85 no matter dry years or wet years. In addition, quite similar those values by measurement. Moreover, accumulated annual variability (NEP). Higher yearly corresponded NEP. When cumulative arrived up 92, target sink. This probably threshold which meadow changes source It indicated that simple, alternative approach estimating has potential larger scale. performance other vegetation types regions needs further verification.