###### Abstract  
Quantification of forest Gross Primary Productivity (GPP) is important for understanding ecosystem function and designing appropriate carbon mitigation strategies. Coupling forest biometric data with canopy photosynthesis models can provide a means to simulate GPP across different stand ages. In this study we developed a simple framework to integrate biometric and leaf gas-exchange measurements, and to estimate GPP across four Mediterranean pine forests of different post-fire age. We used three different methods to estimate the Leaf Area Index (LAI) of the stands, and monthly gas exchange data to calibrate the photosynthetic light response of the leaves. Upscaling of carbon sequestration at the canopy level was made by implementing a Big Leaf and a Sun/Shade model, using both average and variant (monthly) photosynthetic capacity values. The Big Leaf model simulations systematically underestimated GPP compared to the Sun/Shade model simulations. Our simulations suggest an increasing GPP with age up to a stand maturity stage. The shape of the GPP trend with stand age was not affected by the method used to parameterise the model. At the scale of our study, variability in stand and canopy structure among the study sites seems to be the key determinant of GPP. P 2021 2021 2021 12 September 202  
directly affects the Leaf Area Index (LAI), the amount of foliage area per unit ground area [15; 16]. LAI is determined from the stand morphology and characteristics [17], and it is a major biotic factor controlling within-stand light availability [13; 18], microclimate [19] and water balance [20], and thus the overall GPP of a stand [21]. At sites with infrequent disturbances, as stands mature and LAI reaches a local maximum [22], nutrient and water limitation may occur due to competition among trees, leading to reductions of stand-level GPP. However, disturbances such as wildfires and their regimes (frequency, interval and severity) play a crucial role in GPP dynamics, by resetting various ecosystem features [14]. Thus, a sound understanding of how abiotic factors, such as solar radiation, temperature and precipitation, and biotic factors, such as stand and canopy structure, control GPP is important to understand how forest ecosystems function on seasonal and interannual timescales. Climate change is expected to affect the dynamics of Mediterranean forests [23]. Projected temperature increases [24; 25], the uncertain distribution of water availability [26; 27] and the interplay between drought and wildfire [28; 29] are some of the most important agents that could shift the rate of C assimilation in Mediterranean forests. In areas surrounding the Mediterranean basin, mean annual temperature is expected to increase by up to 3-4 \({}^{\circ}\)C and precipitation to decrease by 20%, leading to shifts in the forest fires regime [30]. As a result, fires could disturb the consistency of forest ecosystems, creating areas with different stages of succession and species synthesis [31]. Typically, in the post-fire period, the trajectory of ecosystem productivity follows a single peak curve with the maximum of productivity achieved at middle age stands [7; 32]. Following such scenarios, it is important to accurately simulate C fluxes to elucidate the role of Mediterranean forests in the global C cycle and to develop effective reforestation strategies for C sequestration. Estimation of the C exchange from forest ecosystems is challenging due to the complex relationships between biotic and abiotic factors [33]. Currently, two methodologies are implemented to infer forest productivity, the \"top-down\" and the \"bottom-up\" approaches [33; 34]. The \"top-down\" or meteorological approach attains the estimation using eddy-covariance flux towers [35].