A process-based model to estimate gas exchange and monoterpene emission rates in the mediterranean maquis – comparisons between modelled and measured fluxes at different scales

Abstract. This paper concerns the application of a process-based model (MOCA, Modelling of Carbon Assessment) as an useful tool for estimating gas exchange, and integrating the empirical algorithms for calculation of monoterpene fluxes, in a Mediterranean maquis of central Italy (Castelporziano, Rome). Simulations were carried out for a range of hypothetical but realistic canopies of the evergreen Quercus ilex (holm oak), Arbutus unedo (strawberry tree) and Phillyrea latifolia. More, the dependence on total leaf area and leaf distribution of monoterpene fluxes at the canopy scale has been considered in the algorithms. Simulation of the gas exchange rates showed higher values for P. latifolia and A. unedo (2.39±0.30 and 3.12±0.27 gC m⁻² d⁻¹, respectively) with respect to Q. ilex (1.67±0.08 gC m⁻² d⁻¹) in the measuring campaign (May–June). Comparisons of the average Gross Primary Production (GPP) values with those measured by eddy covariance were well in accordance (7.98±0.20 and 6.00±1.46 gC m⁻² d⁻¹, respectively, in May–June), although some differences (of about 30%) were evident in a point-to-point comparison. These differences could be explained by considering the non uniformity of the measuring site where diurnal winds blown S-SW direction affecting thus calculations of CO₂ and water fluxes. The introduction of some structural parameters in the algorithms for monoterpene calculation allowed to simulate monoterpene emission rates and fluxes which were in accord to those measured (6.50±2.25 vs. 9.39±4.5μg g⁻¹_DW h⁻¹ for Q. ilex, and 0.63±0.207μg g⁻¹_DW h⁻¹ vs. 0.98±0.30μg g⁻¹_DW h⁻¹ for P. latifolia). Some constraints of the MOCA model are discussed, but it is demonstrated to be an useful tool to simulate physiological processes and BVOC fluxes in a very complicated plant distributions and environmental conditions, and necessitating also of a low number of input data.