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

Seasonal variations of photosynthetic capacity parameters, notably the maximum carboxylation rate, Vcmax, 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 Vcmax. In this study, Vcmax 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 Vcmax showed considerable seasonal and inter-annual variations in both mixed and deciduous forest ecosystems. There was noticeable seasonal hysteresis in Vcmax 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 Vcmax and VIs, mostly showing R2>0.95. Vcmax varied exponentially with increasing VIs during the first phase (increasing VIs), but second and third-order polynomials provided the best fits of Vcmax to VIs in the second phase (decreasing VIs). The relationships between NDVI and EVI with Vcmax were different. Further efforts are needed to investigate Vcmax–VIs relationships at more ecosystem sites to the use of satellite-based VIs for estimating Vcmax.

[1]  Yanlian Zhou,et al.  Modeling the impact of drought on canopy carbon and water fluxes for a subtropical evergreen coniferous plantation in southern China through parameter optimization using an ensemble Kalman filter , 2010 .

[2]  Markus Reichstein,et al.  Statistical properties of random CO2 flux measurement uncertainty inferred from model residuals , 2008 .

[3]  Xiangming Xiao,et al.  Satellite-based estimation of evapotranspiration of an old-growth temperate mixed forest , 2009 .

[4]  G. Carter.  Reflectance Wavebands and Indices for Remote Estimation of Photosynthesis and Stomatal Conductance in Pine Canopies , 1998 .

[5]  T. Vesala,et al.  Correlated change in normalized difference vegetation index and the seasonal trajectory of photosynthetic capacity in a conifer stand , 2009 .

[6]  K. Schulz,et al.  Identification of a general light use efficiency model for gross primary production , 2010 .

[7]  J. William Munger,et al.  Measurements of carbon sequestration by long‐term eddy covariance: methods and a critical evaluation of accuracy , 1996 .

[8]  Federico Magnani,et al.  Seasonal and interannual variability of photosynthetic capacity in relation to leaf nitrogen in a deciduous forest plantation in northern Italy. , 2005, Tree physiology.

[9]  J. S. Kimball,et al.  Regional assessment of boreal forest productivity using an ecological process model and remote sensing parameter maps. , 2000, Tree physiology.

[10]  J. Dash,et al.  The MERIS terrestrial chlorophyll index , 2004 .

[11]  I. E. Woodrow,et al.  A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions , 1987 .

[12]  A. Goldstein,et al.  Seasonality of photosynthetic parameters in a multi-specific and vertically complex forest ecosystem in the Sierra Nevada of California. , 2006, Tree physiology.

[13]  B. Choudhury.  Estimating Gross Photosynthesis Using Satellite and Ancillary Data: Approach and Preliminary Results , 2001 .

[14]  M. Wesely,et al.  Variability of Short Term Eddy-Correlation Estimates of Mass Exchange , 1985 .

[15]  T. A. Black,et al.  Intercomparison of techniques to model water stress effects on CO2 and energy exchange in temperate and boreal deciduous forests , 2006 .

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

[17]  John M. Norman,et al.  Carbon distribution and aboveground net primary production in aspen, jack pine, and black spruce stands in Saskatchewan and Manitoba, Canada , 1997 .

[18]  Xiaomin Sun,et al.  Environmental controls over carbon exchange of three forest ecosystems in eastern China , 2008 .

[19]  J. Tenhunen,et al.  Annual and seasonal variations in photosynthetic capacity of Fagus crenata along an elevation gradient in the Naeba Mountains, Japan. , 2008, Tree physiology.

[20]  Dennis D. Baldocchi,et al.  Leaf age affects the seasonal pattern of photosynthetic capacity and net ecosystem exchange of carbon in a deciduous forest , 2001 .

[21]  D. Baldocchi,et al.  Seasonal trends in photosynthetic parameters and stomatal conductance of blue oak (Quercus douglasii) under prolonged summer drought and high temperature. , 2003, Tree physiology.

[22]  T. Andrew Black,et al.  Impact of changing soil moisture distribution on net ecosystem productivity of a boreal aspen forest during and following drought , 2006 .

[23]  F. Hoffmann.  FAGUS, A MODEL FOR GROWTH AND DEVELOPMENT OF BEECH , 1995 .

[24]  Markus Reichstein,et al.  Similarities in ground- and satellite-based NDVI time series and their relationship to physiological activity of a Scots pine forest in Finland , 2004 .

[25]  Susanne von Stamm.  Linked stomata and photosynthesis model for Corylus avellana (hazel) , 1994 .

[26]  H. Schmid,et al.  Multi-year convergence of biometric and meteorological estimates of forest carbon storage , 2008 .

[27]  Xiaomin Sun,et al.  CO2 fluxes over an old, temperate mixed forest in northeastern China , 2006 .

[28]  Y. Kosugi,et al.  Seasonal fluctuations and temperature dependence of leaf gas exchange parameters of co-occurring evergreen and deciduous trees in a temperate broad-leaved forest. , 2006, Tree physiology.

[29]  J. Pisek,et al.  Effects of foliage clumping on the estimation of global terrestrial gross primary productivity , 2012 .

[30]  Yoshiko Kosugi,et al.  Parameterization of the CO2 and H2O gas exchange of several temperate deciduous broad‐leaved trees at the leaf scale considering seasonal changes , 2003 .

[31]  S. Running,et al.  A general model of forest ecosystem processes for regional applications I. Hydrologic balance, canopy gas exchange and primary production processes , 1988 .

[32]  Atul K. Jain,et al.  A model-data comparison of gross primary productivity: Results from the North American Carbon Program site synthesis , 2012 .

[33]  T. Vesala,et al.  Simulation and scaling of temporal variation in gross primary production for coniferous and deciduous temperate forests , 2004 .

[34]  T. A. Black,et al.  Modelling multi-year coupled carbon and water fluxes in a boreal aspen forest , 2006 .

[35]  Jing M. Chen,et al.  Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications , 1999 .

[36]  John A. Gamon,et al.  Assessing leaf pigment content and activity with a reflectometer , 1999 .

[37]  K. Tu,et al.  Modeling plant-soil-atmosphere carbon dioxide exchange using optimality principles , 2000 .

[38]  Guirui Yu,et al.  A preliminary study for spatial representiveness of flux observation at ChinaFLUX sites , 2006 .

[39]  Xiaoliang Lu,et al.  A contemporary carbon balance for the Northeast region of the United States. , 2013, Environmental science & technology.

[40]  Atsuhiro Iio,et al.  Broadband simple ratio closely traced seasonal trajectory of canopy photosynthetic capacity , 2008 .

[41]  P. Sellers.  Canopy reflectance, photosynthesis and transpiration , 1985 .

[42]  H. Mooney,et al.  Modeling the Exchanges of Energy, Water, and Carbon Between Continents and the Atmosphere , 1997, Science.

[43]  Markus Reichstein,et al.  Cross-site evaluation of eddy covariance GPP and RE decomposition techniques , 2008 .

[44]  Markus Reichstein,et al.  Influences of observation errors in eddy flux data on inverse model parameter estimation , 2008 .

[45]  J. Randerson,et al.  Global net primary production: Combining ecology and remote sensing , 1995 .

[46]  Dennis D. Baldocchi,et al.  Estimating parameters in a land‐surface model by applying nonlinear inversion to eddy covariance flux measurements from eight FLUXNET sites , 2007 .

[47]  C. Field,et al.  Relationships Between NDVI, Canopy Structure, and Photosynthesis in Three Californian Vegetation Types , 1995 .

[48]  T. A. Black,et al.  Optimization of ecosystem model parameters through assimilating eddy covariance flux data with an ensemble Kalman filter , 2008 .

[49]  A. Gitelson,et al.  A bio-optical algorithm for the remote estimation of the chlorophyll-a concentration in case 2 waters , 2009 .

[50]  Jadunandan Dash,et al.  The potential of the MERIS Terrestrial Chlorophyll Index for carbon flux estimation , 2010 .

[51]  Soroosh Sorooshian,et al.  Dual state-parameter estimation of hydrological models using ensemble Kalman filter , 2005 .

[52]  Determination of photosynthetic parameters Vcmax and Jmax for a C3 plant (spring hulless barley) at two altitudes on the Tibetan Plateau , 2011 .

[53]  J. Tenhunen,et al.  Inverse modeling of seasonal drought effects on canopy CO2/H2O exchange in three Mediterranean ecosystems , 2003 .

[54]  J. Berry,et al.  A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species , 1980, Planta.

[55]  S. Zaehle,et al.  Improved understanding of drought controls on seasonal variation in Mediterranean forest canopy CO2 and water fluxes through combined in situ measurements and ecosystem modelling. , 2009 .

[56]  Pablo J. Zarco-Tejada,et al.  Simple reflectance indices track heat and water stress-induced changes in steady-state chlorophyll fluorescence at the canopy scale , 2005 .

[57]  Yanhong Tang,et al.  Can EVI-derived land-surface phenology be used as a surrogate for phenology of canopy photosynthesis? , 2014 .

[58]  H. Schmid,et al.  Respiratory carbon losses and the carbon-use efficiency of a northern hardwood forest, 1999-2003. , 2005, The New phytologist.

[59]  Jing M. Chen,et al.  Locally adjusted cubic-spline capping for reconstructing seasonal trajectories of a satellite-derived surface parameter , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[60]  Gordon B. Bonan,et al.  Land-atmosphere CO2 exchange simulated by a land surface process model coupled to an atmospheric general circulation model , 1995 .

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

[62]  W. Stickan,et al.  Modelling the influence of climatic variability on carbon and water budgets of beech saplings (Fagus sylvatica L.) based on field data , 1994 .

[63]  Philippe Ciais,et al.  Optimizing a process‐based ecosystem model with eddy‐covariance flux measurements: A pine forest in southern France , 2007 .

[64]  N. Saigusa,et al.  Spectral vegetation indices as the indicator of canopy photosynthetic productivity in a deciduous broadleaf forest , 2013 .

[65]  Quan Wang,et al.  Retrieval of seasonal variation in photosynthetic capacity from multi-source vegetation indices , 2012, Ecol. Informatics.

[66]  B. Kruijt,et al.  Assessing the uncertainty of estimated annual totals of net ecosystem productivity: A practical approach applied to a mid latitude temperate pine forest , 2011 .

[67]  W. Kustas,et al.  Satellite retrievals of leaf chlorophyll and photosynthetic capacity for improved modeling of GPP , 2013 .

[68]  Andrew E. Suyker,et al.  Gap filling strategies for long term energy flux data sets , 2001 .

[69]  C. Field,et al.  A reanalysis using improved leaf models and a new canopy integration scheme , 1992 .

[70]  Philippe Ciais,et al.  Optimal determination of the parameters controlling biospheric CO2 fluxes over Europe using eddy covariance fluxes and satellite NDVI measurements , 2004 .

[71]  Dennis D. Baldocchi,et al.  Spatial and seasonal variability of photosynthetic parameters and their relationship to leaf nitrogen in a deciduous forest. , 2000, Tree physiology.

[72]  Gil Bohrer,et al.  Sustained carbon uptake and storage following moderate disturbance in a Great Lakes forest. , 2013, Ecological applications : a publication of the Ecological Society of America.