Abstract: Corrosion inhibition by alkaloids extract (AE) from Geissospermum laeve on C38 steel in 1. M HCl is investigated with electrochemical studies. Inhibition efficiency of 92% is reached with 100. mg/L of AE at 25. °C. Potentiodynamic polarization showed that the extract behaves as mixed-type inhibitors. The Nyquist plots showed that increasing AE concentration, charge-transfer resistance increased and double-layer capacitance decreased, involving increased inhibition efficiency. Adsorption of the inhibitor molecules corresponds to Langmuir adsorption isotherm. Immersion time and temperature effects were investigated using EIS and potentiodynamic polarization. SEM and EDX supported the adsorption conclusions. The active compound responsible for the corrosion inhibition is geissospermine.

Abstract: Mapping forest aboveground biomass (AGB) has become an important task, particularly for the reporting of carbon stocks and changes. AGB can be mapped using synthetic aperture radar data (SAR) or passive optical data. However, these data are insensitive to high AGB levels (>150 Mg/ha, and >300 Mg/ha for P-band), which are commonly found in tropical forests. Studies have mapped the rough variations in AGB by combining optical and environmental data at regional and global scales. Nevertheless, these maps cannot represent local variations in AGB in tropical forests. In this paper, we hypothesize that the problem of misrepresenting local variations in AGB and AGB estimation with good precision occurs because of both methodological limits (signal saturation or dilution bias) and a lack of adequate calibration data in this range of AGB values. We test this hypothesis by developing a calibrated regression model to predict variations in high AGB values (mean >300 Mg/ha) in French Guiana by a methodological approach for spatial extrapolation with data from the optical geoscience laser altimeter system (GLAS), forest inventories, radar, optics, and environmental variables for spatial inter- and extrapolation. Given their higher point count, GLAS data allow a wider coverage of AGB values. We find that the metrics from GLAS footprints are correlated with field AGB estimations (R2 = 0.54, RMSE = 48.3 Mg/ha) with no bias for high values. First, predictive models, including remote-sensing, environmental variables and spatial correlation functions, allow us to obtain “wall-to-wall” AGB maps over French Guiana with an RMSE for the in situ AGB estimates of ∼50 Mg/ha and R2 = 0.66 at a 1-km grid size. We conclude that a calibrated regression model based on GLAS with dependent environmental data can produce good AGB predictions even for high AGB values if the calibration data fit the AGB range. We also demonstrate that small temporal and spatial mismatches between field data and GLAS footprints are not a problem for regional and global calibrated regression models because field data aim to predict large and deep tendencies in AGB variations from environmental gradients and do not aim to represent high but stochastic and temporally limited variations from forest dynamics. Thus, we advocate including a greater variety of data, even if less precise and shifted, to better represent high AGB values in global models and to improve the fitting of these models for high values. © 2016 Elsevier B.V.

Abstract: 2. This hypothesis was tested by comparing a generalist and a specialist ladybird species belonging to the same genus. 3. A resorption index was calculated for females of both species subjected to several starvation regimes. This index indicated that over a period of fasting of 3 days, the intensity of resorption was greater in the generalist than the specialist. When food was again supplied, oogenesis resumed and within 1 day was faster in the generalist than in the specialist. 4. As predicted, the resorption of oocytes and replenishment occurred faster in the generalist than in the specialist species. This is the first time, to our knowledge, that the speed and intensity of the ovarian dynamics of a predatory insect have been linked to its way of life.

Abstract: P>1. Relationships between tropical rain forest biomass and environmental factors have been determined at regional scales, e.g. the Amazon Basin, but the reasons for the high variability in forest biomass at local scales are poorly understood. Interactions between topography, soil properties, tree growth and mortality rates, and treefalls are a likely reason for this variability. 2. We used repeated measurements of permanent plots in lowland rain forest in French Guiana to evaluate these relationships. The plots sampled topographic gradients from hilltops to slopes to bottomlands, with accompanying variation in soil waterlogging along these gradients. Biomass was calculated for > 175 tree species in the plots, along with biomass productivity and recruitment rates. Mortality was determined as standing dead and treefalls. 3. Treefall rates were twice as high in bottomlands as on hilltops, and tree recruitment rates, radial growth rates and the abundance of light-demanding tree species were also higher. 4. In the bottomlands, the mean wood density was 10% lower than on hilltops, the basal area 29% lower and the height:diameter ratio of trees was lower, collectively resulting in a total woody biomass that was 43% lower in bottomlands than on hilltops. 5. Biomass productivity was 9% lower in bottomlands than on hilltops, even though soil Olsen P concentrations were higher in bottomlands. 6. Synthesis. Along a topographic gradient from hilltops to bottomlands there were higher rates of treefall, which decreased the stand basal area and favoured lower allocation to height growth and recruitment of light-demanding species with low wood density. The resultant large variation in tree biomass along the gradient shows the importance of determining site characteristics and including these characteristics when scaling up biomass estimates from stand to local or regional scales.

Abstract: White-sand forests represent natural laboratories of evolution over their long history throughout Amazonia and the Guiana Shield and pose significant physiological challenges to the plants and animals they host. The study of diversification in plant lineages comprising species endemic to white-sand forest can therefore give insights into processes of evolution and community assembly in tropical forests. In this article, we synthesize recent studies of white-sand forests to integrate patterns of plant species distribution with processes of lineage diversification and community assembly in the white-sand flora. We contrast lineages that have radiated uniquely in these habitats (e.g., Pagamea, Rubiaceae), with cosmopolitan lineages comprising specialists to white-sand forests and other habitats that may have arisen via ecological speciation across habitat gradients (e.g., Protium, Burseraceae). In both cases, similar suites of functional traits have evolved, including investment in dense, long-lived tissues that are well-defended structurally and chemically. White-sand endemics, therefore, play an important role in biodiversity conservation because they represent unique combinations of functional and phylogenetic diversity. Furthermore, white-sand endemics may respond differently than other tropical forest plant species to contemporary global changes because they comprise resilient functional types that may better withstand increased drought, temperature, and invasions of exotic pests in these regions. © 2016 The Association for Tropical Biology and Conservation.