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

Abstract

A B S T R A C T Seasonal variations of photosynthetic capacity parameters, notably the maximum carboxylation rate, V cmax , play an important role in accurate estimation of CO 2 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 R 2 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 ÁVIs relationships at more ecosystem sites to the use of satellitebased VIs for estimating V cmax .

SCOPE model applied for rapeseed in Spain

“…In this kind of approach, the mean value for the whole growing season or, the maximum crop-specific value, is used as the said fixed value. However, this approach might induce a major deviation in carbon flux values Zhou et al, 2014), a fact also confirmed by a sensitivity analysis performed in this paper (not shown). Therefore, indicating a range of values to introduce the seasonal variation of V cmax and J max , as done in this paper, would be desirable.…”

Remotely estimating photosynthetic capacity, and its response to temperature, in vegetation canopies using imaging spectroscopy

“…Indeed, ours is one of several emerging strategies that use remotely sensed data to address current difficulties in accurately characterizing V cmax variation at broad spatiotemporal scales (e.g., Zhang et al, 2014;Zhou et al, 2014). The work presented here was conducted in agricultural landscapes, and we can readily envision the potential of our method to improve yield forecasting and facilitate real-time monitoring of crop physiological status.…”

“…In response to the compromises that generalization by PFTs incurs, there is increasing interest in the development of novel approaches to use optical remote sensing to map variability in physiological function and biochemistry of terrestrial vegetation at broad spatial and temporal scales (e.g., Frankenberg et al, 2014;Guanter et al, 2014;Singh, Serbin, McNeil, Kingdon, & Townsend, in press;Zhang et al, 2014;Zhou et al, 2014). Of critical importance is the ability to accurately estimate the spatial and temporal variability in the photosynthetic capacity of vegetation canopies, which is governed in large part by V cmax , the maximum rate at which the enzyme rubisco catalyzes the carboxylation of RuBP in leaf chloroplasts (Bernacchi et al, 2013;Farquhar, von Caemmerer, & Berry, 1980).…”

Assessing the Impact of Urban Sprawl on Net Primary Productivity of Terrestrial Ecosystems Using a Process-Based Model—A Case Study in Nanjing, China

“…Although initially developed to simulate NPP in boreal ecosystems in Canada, BEPS has been improved in many ways and has been used to simulate NPP at county and national scales in China [33], [36]- [38] and regional and global terrestrial carbon and water fluxes widely [39], [40]. BEPS details have been fully described elsewhere [39], [41]- [43]. Only some of the major methods related to NPP calculation are summarized here.…”