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Adiku, SGK, Reichstein, M, Lohila, A, Dinh, NQ, Aurela, M, Laurila, T, Lueers, J, Tenhunen, JD (2006). PIXGRO: A model for simulating the ecosystem CO2 exchange and growth of spring barley. ECOLOGICAL MODELLING, 190(4-Mar), 260-276.

Abstract
A model, PIXGRO, developed by coupling a canopy flux sub-model (PROXELNEE; PROcess-based piXEL Net Ecosystem CO2 Exchange) to a vegetation structure submodel (CGRO), for simulating both net ecosystem CO2 exchange (NEE) and growth of spring barley is described. PIXGRO is an extension of the stand-level CO, and H2O-flux model PROXELNEE, that simulates the NEE on a process basis, but goes further to include the dry matter production, partitioning, and crop development for spring barley. Dry matter partitioned to the leaf was converted to leaf area index (LAI) using relationships for the specific leaf area (SLA). The canopy flux component, PROXELNEE was calibrated using information from the literature on C3 plants and was tested using CO2 flux data from an eddy-covariance (EC) method in Finland with long-term observations. The growth component (CGRO) was calibrated using data from the literature on spring barley as well as data from the Finland site. It was then validated against field data from two sites in Germany and partly via the use of MODIS remotely sensed LAI from the Finland site. Both the diurnal and the seasonal patterns of gross CO2 uptake were very well simulated (R-2= 0.92). A slight seasonal bias may be attributed to leaf ageing. Crop growth was also well simulated; simulated dry matter agreed with field observed data from Germany (R-2 = 0.90). For LAI, the agreement between the simulated and observed was good (R-2 = 0.80), giving an indication that functions describing the conversion of fixed C02 to dry matter and the subsequent partitioning leaf dry matter and LAI simulation were robust and provided reliable estimates. The MODIS LAI at a resolution of 1000 m agreed poorly (R-2 = 0.45) with the PIXGRO simulated LAI and the observed LAI at the Finland site in 2001. We attributed this to the coarse resolution of the image and/or the small size of the barley field (about 17 ha or 0.25 kM(2)) at the Finland site. By deriving a regression relation between the observed LAI and NDVI from a higher resolution MODIS (500 m resolution), the MODIS-recalculated LAI agreed better with the PIXGRO-simulated LAI (R-2 = 0.86). PIXGRO provides a prototype model bridging the disciplines of plant physiology, crop modeling and remote sensing, for use in a spatial context in evaluating carbon balances and plant growth at stand level, landscape, regional, and with some care, continental scales. Since almost 50% of the European land surface is covered by crops, such a model is needed for the dynamic estimation of LAI and NEE of croplands. (c) 2005 Elsevier B.V. All rights reserved.

DOI:
10.1016/j.ecolmodel.2005.04.024

ISSN:
0304-3800

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