Abstract: Micrometeorological measurements of night time ecosystem respiration can be systematically biased when stable atmospheric conditions lead to drainage flows associated with decoupling of air flow above and within plant canopies. The associated horizontal and vertical advective fluxes cannot be measured using instrumentation on the single towers typically used at micrometeorological sites. A common approach to minimize bias is to use a threshold in friction velocity, u*, to exclude periods when advection is assumed to be important, but this is problematic in situations when in-canopy flows are decoupled from the flow above. Using data from 25 flux stations in a wide variety of forest ecosystems globally, we examine the generality of a novel approach to estimating nocturnal respiration developed by van Gorsel et al. (van Gorsel, E., Leuning, R., Cleugh, H.A., Keith, H., Suni, T., 2007. Nocturnal carbon efflux: reconciliation of eddy covariance and chamber measurements using an alternative to the u*-threshold filtering technique. Tellus 59B, 397-403, Tellus, 59B, 307-403). The approach is based on the assumption that advection is small relative to the vertical turbulent flux (F-C) and change in storage (F-S) of CO2 in the few hours after sundown. The sum of F-C and F-S reach a maximum during this period which is used to derive a temperature response function for ecosystem respiration. Measured hourly soil temperatures are then used with this function to estimate respiration R-Rmax. The new approach yielded excellent agreement with (1) independent measurements using respiration chambers, (2) with estimates using ecosystem light-response curves of F-c + F-s extrapolated to zero light, R-LRC, and (3) with a detailed process-based forest ecosystem model, R-cast. At most sites respiration rates estimated using the u*-filter, R-ust, were smaller than R-Rmax, and R-LRC. Agreement of our approach with independent measurements indicates that R-Rmax, provides an excellent estimate of nighttime ecosystem respiration. (C) 2009 Elsevier B.V. All rights reserved.

Abstract: A thorough understanding of how tropical forests respond to climate is important to improve ecosystem process models and to reduce uncertainties in current and future global carbon balance calculations. The Amazon rainforest, a major contributor to the global carbon cycle, is subject to strong intra- and interannual variations in climate conditions. Understanding their effect on carbon fluxes between the ecosystem and the atmosphere and on the resulting carbon balance is still incomplete. We examined the long-term (over a 12-year period; 2004–2015) variations in gross primary productivity (GPP), ecosystem respiration (RE) and net ecosystem exchange (NEE) in a tropical rainforest in French Guiana and identified key climatic drivers influencing the changes. The study period was characterized by strong differences in climatic conditions among years, particularly differences in the intensity of the dry and wet seasons, as well as differences in annual carbon fluxes and balance. Annual average GPP varied from 3384.9?g?C?m-2?yr?1 (95% CI [3320.7, 3445.9]) to 4061.2?g?C?m-2?yr?1 (95% CI [3980.1, 4145.0]). RE varied even more than GPP, with a difference of 933.1?C?m-2?yr?1 between the minimum (3020.6?g?C?m-2?yr?1; 95% CI [2889.4, 3051.3]) and maximum (3953.7?g?C?m-2?yr?1; 95% CI [3887.6, 4019.6]) values. Although NEE showed large interannual variability (nine-fold), from ?65.6?g?C?m-2?yr?1 (95% CI [?4.4, ?126.0]) to ?590.5?g?C?m-2 yr?1 (95% CI [?532.3, ?651.6]), the forest remained a carbon sink over the 12-year period. A combination of global radiation (Rg), relative extractable water (REW) and soil temperature (Ts) explained 51% of the daily variations for GPP, 30% for RE and 39% for NEE. Global radiation was always the best predictor of these variations, but soil water content and temperature did also influence carbon fluxes and balance. Seasonally, Rg was the major controlling factor for GPP, RE and NEE during the wet season. During the dry season, variations in carbon fluxes and balance were poorly explained by climate factors. Yet, REW was the key driver of variations in NEE during the dry season. This study highlights that, over the long-term, carbon fluxes and balance in such tropical rainforest ecosystems are largely controlled by both radiation and water limitation. Even though variations in Rg have a greater impact on these fluxes, water limitation during seasonal droughts is enough to reduce ecosystem productivity, respiration and carbon uptake. The reduced precipitation expected in tropical rainforest areas under future climatic conditions will therefore strongly influence carbon fluxes and carbon uptake. This study also highlights the importance for land surface or dynamic global vegetation models to consider the main drivers of carbon fluxes and balance separately for dry and wet seasons.

Abstract: In agroforestry systems, the distribution of light transmitted under tree canopies can be a limiting factor for the development of intercrops. The light available for intercrops depends on the quantity of light intercepted by tree canopies and, consequently, on the architecture of the tree species present. The influence of tree architecture on light transmission was analysed using dynamic 3D architectural models. The architectural analysis of Acacia mangium and Tectona grandis was performed in Indonesian agroforestry systems with trees aged from 1 to 3 years. 3D virtual trees were then generated with the AmapSim simulation software and 3D virtual experiments in which tree age, planting density, planting pattern and pruning intensity varied were reconstructed in order to simulate light available for the crop. Canopy closure of trees was more rapid in A. mangium than in T. grandis agroforestry systems; after 3 years the quantity of light available for A. mangium intercrops was three times lower than under T. grandis. Simulations with A. mangium showed that practices such as pruning and widening tree spacing enable to increase the total transmitted light within the stand. On T. grandis, modification of the tree row azimuth resulted in changes in the spatial and seasonal distribution of light available for the intercrops. These results are discussed in terms of agroforestry system management.

Abstract: Research on antifungal compounds from the durable wood from French Guiana Amazonian forest trees highlights the correlation between the activity of their extracts against wood-rotting fungi and human pathogens. The fractionation of an ethyl acetate extract of Sextonia rubra wood led to the isolation of rubrenolide (1) and rubrynolide (2). The potential of compounds 1 and 2 is described through the evaluation of their activity against 16 pathogenic fungi and their cytotoxicity toward NIH-3T3 mammalian fibroblast cells.

Abstract: [1] In some regions of the Amazon, global biogeophysical models have difficulties in reproducing measured seasonal patterns of net ecosystem exchange (NEE) of carbon dioxide. The global process-based biosphere model Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) used in this study showed that a standard model parameterization produces seasonal NEE patterns that are opposite in phase to the eddy flux data of the tropical evergreen forest at the Tapajos km 67 site (Brazil), like many other global models. However, we optimized several key parameters of ORCHIDEE using eddy covariance data of the Tapajos km 67 site in order to identify the driving factors of the seasonal variations in CO2 flux in this tropical forest ecosystem. The validity of the retrieved parameter values was evaluated for two other flux tower sites in the Amazon. The different tested optimization scenarios showed that only a few parameters substantially improve the fit to NEE and latent heat data. Our results confirm that these forests have the ability to maintain high transpiration and photosynthesis during the dry season in association with a large soil depth (D-soil = 10 m) and a rooting system density that decreases almost linearly with depth (H-root = 0.1). Previous analyses of seasonal variations in eddy covariance fluxes indicated that higher GPP levels were reached in the dry season compared to the wet season. Our optimization analysis suggests that this pattern could be caused by a leaf flush at the start of the dry season increasing the photosynthetic capacity of the canopy. Nevertheless, the current model structure is not yet able to simulate such a leaf flush, and we therefore suggest improving the ORCHIDEE model by including a specific phenology module that is driven by light availability for the tropical evergreen plant functional types. In addition, our results highlight both the potential and the limitations of flux data to improve global terrestrial models. Several parameters were not identifiable, and the risk of overfitting of the model was illustrated. Nevertheless, we conclude that these models can be improved substantially by assimilating site level flux data over the tropics.