Close relationship between spectral vegetation indices and V_cmax in deciduous and mixed forests

Abstract

Seasonal variations of photosynthetic capacity parameters, notably the maximum carboxylation rate, V_cmax, play an important role in accurate estimation of CO₂ assimilation in gas-exchange models. Satellite-derived normalised difference vegetation index (NDVI), enhanced vegetation index (EVI) and model-data fusion can provide means to predict seasonal variation in V_cmax. In this study, V_cmax was obtained from a process-based model inversion, based on an ensemble Kalman filter (EnKF), and gross primary productivity, and sensible and latent heat fluxes measured using eddy covariance technique at two deciduous broadleaf forest sites and a mixed forest site. Optimised V_cmax showed considerable seasonal and inter-annual variations in both mixed and deciduous forest ecosystems. There was noticeable seasonal hysteresis in V_cmax in relation to EVI and NDVI from 8 d composites of satellite data during the growing period. When the growing period was phenologically divided into two phases (increasing VIs and decreasing VIs phases), significant seasonal correlations were found between V_cmax and VIs, mostly showing R²>0.95. V_cmax varied exponentially with increasing VIs during the first phase (increasing VIs), but second and third-order polynomials provided the best fits of V_cmax to VIs in the second phase (decreasing VIs). The relationships between NDVI and EVI with V_cmax were different. Further efforts are needed to investigate V_cmax–VIs relationships at more ecosystem sites to the use of satellite-based VIs for estimating V_cmax.

• V_cmax
• spectral vegetation indices
• ensemble Kalman filter
• BEPS model

6. Acknowledgements

This research was supported by National Basic Research Program of China (2010CB950702) and National Natural Science Foundation of China (41371070). The authors greatly thank researchers of Changbai Mountain experiment station, Saskatchewan BERMS Old Aspen site and University of Michigan Biological Station for providing fluxes and meteorological data, and Professor Scott Munro, University of Toronto, for editing this manuscript.