Abstract: The influence of seasonal phenology on canopy photosynthesis in tropical evergreen forests remains poorly understood, and its representation in global ecosystem models is highly simplified, typically with no seasonal variation of canopy leaf properties taken into account. Including seasonal variation in leaf age and photosynthetic capacity could improve the correspondence of global vegetation model outputs with the wet-dry season CO2 patterns measured at flux tower sites in these forests. We introduced a leaf litterfall dynamics scheme in the global terrestrial ecosystem model ORCHIDEE based on seasonal variations in net primary production (NPP), resulting in higher leaf turnover in periods of high productivity. The modifications in the leaf litterfall scheme induce seasonal variation in leaf age distribution and photosynthetic capacity. We evaluated the results of the modification against seasonal patterns of three long-term in-situ leaf litterfall datasets of evergreen tropical forests in Panama, French Guiana and Brazil. In addition, we evaluated the impact of the model improvements on simulated latent heat (LE) and gross primary productivity (GPP) fluxes for the flux tower sites Guyaflux (French Guiana) and TapajÃ3s (km 67, Brazil). The results show that the introduced seasonal leaf litterfall corresponds well with field inventory leaf litter data and times with its seasonality. Although the simulated litterfall improved substantially by the model modifications, the impact on the modelled fluxes remained limited. The seasonal pattern of GPP improved clearly for the Guyaflux site, but no significant improvement was obtained for the TapajÃ3s site. The seasonal pattern of the modelled latent heat fluxes was hardly changed and remained consistent with the observed fluxes. We conclude that we introduced a realistic and generic litterfall dynamics scheme, but that other processes need to be improved in the model to achieve better simulations of GPP seasonal patterns for tropical evergreen forests. © Author(s) 2012. CC Attribution 3.0 License.

Abstract: Tree vigor is often used as a covariate when tree mortality is predicted from tree growth in tropical forest dynamic models, but it is rarely explicitly accounted for in a coherent modeling framework. We quantify tree vigor at the individual tree level, based on the difference between expected and observed growth. The available methods to join nonlinear tree growth and mortality processes are not commonly used by forest ecologists so that we develop an inference methodology based on an MCMC approach, allowing us to sample the parameters of the growth and mortality model according to their posterior distribution using the joint model likelihood. We apply our framework to a set of data on the 20-year dynamics of a forest in Paracou, French Guiana, taking advantage of functional trait-based growth and mortality models already developed independently. Our results showed that growth and mortality are intimately linked and that the vigor estimator is an essential predictor of mortality, highlighting that trees growing more than expected have a far lower probability of dying. Our joint model methodology is sufficiently generic to be used to join two longitudinal and punctual linked processes and thus may be applied to a wide range of growth and mortality models. In the context of global changes, such joint models are urgently needed in tropical forests to analyze, and then predict, the effects of the ongoing changes on the tree dynamics in hyperdiverse tropical forests. © 2015 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

Abstract: Background: Natural disturbance is a fundamental component of the functioning of tropical rainforests let to natural dynamics, with tree mortality the driving force of forest renewal. With ongoing global (i.e. land-use and climate) changes, tropical forests are currently facing deep and rapid modifications in disturbance regimes that may hamper their recovering capacity so that developing robust predictive model able to predict ecosystem resilience and recovery becomes of primary importance for decision-making: (i) Do regenerating forests recover faster than mature forests given the same level of disturbance? (ii) Is the local topography an important predictor of the post-disturbance forest trajectories? (iii) Is the community functional composition, assessed with community weighted-mean functional traits, a good predictor of carbon stock recovery? (iv) How important is the climate stress (seasonal drought and/or soil water saturation) in shaping the recovery trajectory? Methods: Paracou is a large scale forest disturbance experiment set up in 1984 with nine 6.25 ha plots spanning on a large disturbance gradient where 15 to 60% of the initial forest ecosystem biomass were removed. More than 70,000 trees belonging to ca. 700 tree species have then been censused every 2 years up today. Using this unique dataset, we aim at deciphering the endogenous (forest structure and composition) and exogenous (local environment and climate stress) drivers of ecosystem recovery in time. To do so, we disentangle carbon recovery into demographic processes (recruitment, growth, mortality fluxes) and cohorts (recruited trees, survivors). Results: Variations in the pre-disturbance forest structure or in local environment do not shape significantly the ecosystem recovery rates. Variations in the pre-disturbance forest composition and in the post-disturbance climate significantly change the forest recovery trajectory. Pioneer-rich forests have slower recovery rates than assemblages of late-successional species. Soil water saturation during the wet season strongly impedes ecosystem recovery but not seasonal drought. From a sensitivity analysis, we highlight the pre-disturbance forest composition and the post-disturbance climate conditions as the primary factors controlling the recovery trajectory. Conclusions: Highly-disturbed forests and secondary forests because they are composed of a lot of pioneer species will be less able to cope with new disturbance. In the context of increasing tree mortality due to both (i) severe droughts imputable to climate change and (ii) human-induced perturbations, tropical forest management should focus on reducing disturbances by developing Reduced Impact Logging techniques.

Abstract: We analysed 1040 individual trees, located in 62 plots across the Amazon Basin for leaf mass per unit area (M-A), foliar carbon isotopic composition (delta C-13) and leaf level concentrations of C, N, P, Ca, Mg, K and Al. All trees were identified to the species level with the dataset containing 58 families, 236 genera and 508 species, distributed across a wide range of soil types and precipitation regimes. Some foliar characteristics such as M-A, [C], [N] and [Mg] emerge as highly constrained by the taxonomic affiliation of tree species, but with others such as [P], [K], [Ca] and delta C-13 also strongly influenced by site growing conditions. By removing the environmental contribution to trait variation, we find that intrinsic values of most trait pairs coordinate, although different species ( characterised by different trait suites) are found at discrete locations along a common axis of coordination. Species that tend to occupy higher fertility soils are characterised by a lower M-A and have a higher intrinsic [N], [P], [K], [Mg] and delta C-13 than their lower fertility counterparts. Despite this consistency, different scaling patterns were observed between low and high fertility sites. Inter-relationships are thus substantially modified by growth environment. Analysing the environmental component of trait variation, we found soil fertility to be the most important predictor, influencing all leaf nutrient concentrations and delta C-13 and reducing M-A. Mean annual temperature was negatively associated with leaf level [N], [P] and [K] concentrations. Total annual precipitation positively influences M-A, [C] and delta C-13, but with a negative impact on [Mg]. These results provide a first basis for understanding the relationship between the physiological functioning and distribution of tree species across Amazonia.

Abstract: Corrosion inhibition effect of alkaloids extract from Palicourea guianensis plant (AEPG) on C38 tell in 1 M HCl medium has been investigated by potentiodynamic polarization and electrochemical impedance spectroscopy. The polarization studies that AEPG acts as mixed-type inhibitor. The electrochemical impedance spectroscopy showed that the charge transfer resistance increases and the double layer capacitance decreases on increasing plant extract concentration. The inhibition efficiency of the extract obtained from impedance and polarization measurements was in a good agreement and was found to increase with increasing concentration of the extract. Inhibition efficiency of 89% was achieved with 100 mg L-1 of AEPG at 25 degrees C. The obtained results showed that, the Palicourea guianensis extract could serve as an effective inhibitor for the corrosion of steel in acid media. The adsorption of AEPG obeys the Langmuir adsorption isotherm.