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International audience; Evapotranspiration and energy partitioning are complex to estimate because they result from the interaction of many different processes, especially in multi-species and multi-strata ecosystems. We used MAESPA model, a mechanistic, 3D model of coupled radiative transfer, photosynthesis, and balances of energy and water, to simulate the partitioning of energy and evapotranspiration in homogeneous tree plantations, as well as in heterogeneous multi-species, multi-strata agroforests with diverse spatial scales and management schemes. The MAESPA model was modified to add (1) calculation of foliage surface water evaporation at the voxel scale; (2) computation of an average within-canopy air temperature and vapour pressure; and (3) use of (1) and (2) in iterative calculations of soil and leaf temperatures to close ecosystem-level energy balances. We tested MAESPA model simulations on a simple monospecific Eucalyptus stand in Brazil, and also in two complex, heterogeneous Coffea agroforests in Costa Rica. MAESPA satisfactorily simulated the daily and seasonal dynamics of net radiation (RMSE = 29.6 and 28.4 W m−2; R2 = 0.99 and 0.99 for Eucalyptus and Coffea sites respectively) and its partitioning between latent-(RMSE = 68.1 and 37.2 W m−2; R2 = 0.87 and 0.85) and sensible-energy (RMSE = 54.6 and 45.8 W m−2; R2 = 0.57 and 0.88) over a one-year simulation at half-hourly time-step. After validation, we use the modified MAESPA to calculate partitioning of evapotranspiration and energy between plants and soil in the above-mentioned agro-ecosystems. In the Eucalyptus plantation, 95% of the outgoing energy was emitted as latent-heat, while the Coffea agroforestry system’s partitioning between sensible and latent-heat fluxes was roughly equal. We conclude that MAESPA process-based model has an appropriate balance of detail, accuracy, and computational speed to be applicable to simple or complex forest ecosystems and at different scales for energy and evapotranspiration partitioning.

International audience; Biomass as a resource, and as a vulnerable carbon pool, is a key variable to diagnose the impacts of global changes on the terrestrial biosphere, and therefore its proper description in models is crucial. Model-Data Fusion (MDF) or data assimilation methods are useful tools in improving ecosystem models that describe interactions between vegetation and atmosphere. We use a MDF method based on a Bayesian approach, in which data are combined with a process model in order to provide optimized estimates of model parameters and to better quantify model uncertainties, whilst taking into account prior information on the parameters. With this method we are able to use multiple data streams, which allows us to simultaneously constrain modeled variables at site level across different temporal scales. In this study both high frequency eddy covariance flux measurements of net CO2 and evapotranspiration (ET), and low frequency biometric measurements of total aboveground biomass and the annual increment (which includes all compartments), are assimilated with the ORCHIDEE model version "AR5" at a beech (Hesse) and a maritime pine (Le Bray) forest site using four to five years of flux data and nine years of biomass data. When assimilating the observed aboveground annual biomass increment (AGB_inc) together with net CO2 and ET flux, the RMSE of modelled AGBinc was reduced from the a priori estimates by 37% at Hesse and 69% at Le Bray, without reducing the fit to the net CO2 and ET that can be achieved when assimilating flux data alone. Assimilating biomass increment data also provides insight in the performance of the allocation scheme of the model. Comparison with detailed site-based measurements at Hesse showed that the optimization reduced positive biases in the model, for example in fine root and leaf production. We also investigated how to use stand-scale total aboveground biomass in optimization (AGB_tot). However, this study demonstrated that assimilating AGB_tot measurements in the ORCHIDEE-AR5 model lead to some inconsistencies, particularly for the annual dynamics of the AGB_inc, partly because this version of the model lacked a realistic representation of forest stand processes including management and disturbances.

We investigated changes in the pattern of stand water use in a chronosequence of four even-aged maritime pine stands, differing in age (10-, 32-, 54- and 91-year old) and growing under similar environmental conditions. Extensive sap flow measurements were carried out during a period of 2 years (2001‐2002), using thermal dissipation sensors located 1 m below the live crown and corrected for the radial profile of sap flow. We found significant differences in transpiration among stands. Overstorey transpiration, ET, declined with stand age from 508 mm per year for the 10-year-old stand to 144 mm per year for the 54-year-old stand in 2001. This age-related decline was driven by (i) a decrease in transpiration per unit leaf area (55%), due to a decrease in stomatal conductance in taller trees and (ii) a significant reduction in leaf area index (38%). There was a strong effect of soil moisture deficit on transpiration and an interaction with age. A strong decrease in overstorey transpiration resulted from the prolonged drought in 2002 due to both a lower transpiration rate per unit leaf area and lower leaf area evidenced both by optical and litterfall measurements. The drought effect was greater in the younger stands compared to older stands. In the 32year-old stand, simultaneous measurements of sap flow and eddy covariance showed that the overstorey transpiration contributed to half of the total ecosystem water loss, E. Moreover, the total ecosystem evaporation estimated for each stand by a water balance approach was not different between stand ages. We suggest, therefore, that the decline in overstorey transpiration with stand age mainly affects partitioning of the components of evaporation between trees, understorey and soil but not the magnitude of total evaporation. # 2005 Elsevier B.V. All rights reserved.

Modelling biomass repartition in a tree is either done using theories regarding carbon transfer and allocation or through empirical repartition coefficients. The latter can be derived from the study of the allometric relationships inside a tree, which reflect the equilibrium between tree structure and biomass. In order to quantify the biomasses of the main aerial compartments (needles, stem wood, stem bark, branch wood and buds) of a Maritime pine tree (Pinus pinaster Ait.) and to assess their relationships with tree structure, we undertook some destructive measurements of architecture and biomass. The study of leaf area was presented in a specific paper [Porte et al., Ann. For. Sci. 57 (1) (2000) 73], and the present paper is dealing with the woody compartments (branch wood, stem bark and wood). We collected biomass samples on thirty 5-year-old, sixteen 26-year-old and ten 32-year-old Maritime pines. Allometric equations were developed per site to estimate branch wood biomass. It depended only on the branch basal diameter and the models were very satisfying. Using these equations, we estimated the total branch wood biomass of each sampled tree. A single relationship for all sites was found to model crown or trunk biomass. A power function of tree diameter at breast height (DBH) and the inverse of tree age was fitted to the branch wood data. A power function of DBH and tree age was used for the stem wood and bark models, which takes into account the differences in vitality with different ages. All models performed quite well. Input variables were easy to measure so that the models could be applied to estimate the aerial biomass of a whole stand, per compartment, over a 20-year-long period. The allometric relationships presented here can be derived to be used as biomass repartition laws, for a 5–30-year-old Maritime pine stand in humid Lande.

Interception, throughfall and stemflow were determined in an 18-year-old maritime pine stand for a period of 30 months. This involved 71 rainfall events, each corresponding either to a single storm or to several storms. Gash's analytical model of interception was used to estimate the sensitivity of interception to canopy structure and climatic parameters. The seasonal cumulative interception loss corresponded to 12.6–21.0% of the amount of rainfall, whereas throughfall and stemflow accounted for 77–83% and 1–6%, respectively. On a seasonal basis, simulated data fitted the measured data satisfactorily (r2 = 0.75). The rainfall partitioning between interception, throughfall and stemflow was shown to be sensitive to (1) the rainfall regime, i.e. the relative importance of light storms to total rainfall, (2) the climatic parameters, rainfall rate and average evaporation rate during storms, and (3) the canopy structure parameters of the model. The low interception rate of the canopy was attributed primarily to the low leaf area index of the stand.