Abstract: We studied the foraging and predatory behaviors of the invasive African myrmicine ant, Pheidole megacephala (F.) in its native range. Workers can singly capture a wide range of insects, including relatively large prey items. For still larger prey, they recruit at short range those nestmates situated within reach of an alarm pheromone and together spread-eagle the insect. These behaviors are complimented by a long-range recruitment (of nestmates remaining in the nest) based on prey size. P. megacephala scouts also use long-range recruitment when they detect the landmarks of termites and competing ant species, thus permitting them to avoid confronting these termites and ants solitarily.

Abstract: Characterisation of forest structure is a major stake for forestry, species conservation, carbon stock estimates and many forest ecology and management issues. At large scale natural forest structure tends to vary according to climate and geomorphomology (Paget, 1999; Steege et al., 2006) while soil characteristics (and notably water regime) and syMgenetic stage add some finer scale variation (Oldeman, 1989; Sabatier et al., 1997). Forest structure characterisation traditionally relies on field-based collection of individual tree dimensions such as stem diameter and stem height sampled across tracks of forest (Hall et al., 1998). However, such field intensive methods are costly, and of low accuracy regarding measures of tree heights. Airborne light detection and ranging (LiDAR) technology provides horizontal and vertical Information at high spatial resolutions and vertical accuracies (Lim et al., 2003; Hyyppä et al., 2004). It has the potential for gathering vegetation structure data over large areas rapidly at moderate cost and hence is of particular relevance for poorly sampled, difficult to access and largely unexplored tropical rainforests. In this study we examined the ability of airborne LiDAR to detect spatial changes in the structure of dense tropical rain forest and we probed this remote sensing approach against local statistics derived from stem diameters (i.e. classical field data information) mapped across a large track of forest at a long term experimental site in French Guyana. The large variability in forest structure occurring at the experimental site is du to natural variation of the soil cover (and notably drainage properties) combined with various logging intensities applied 15 years before the LiDAR data were acquired. On this basis ten different forest types were identified at the site (figure 1 and 3). Various stem based statistics were computed for a series of meshes with cells ranging from 30 by 30 m plots to 250 by 250 m plots. These statistics included basal area, stem density, quadratic mean diameter, and diameter distribution percentiles. Similarly local statistics were extracted either from the Canopy Height Model (e.g. median height, mean height, standard height deviation, height coefficient of variation, height percentiles, frequency of hits below 5 m above ground level). Additionally a wetness index (Böhner et al., 2002) was computed at each node of a 5 by 5 m grid from the Digital Terrain Model also extracted from the LiDAR data set. We used both types of cell statistics to discriminate the various forest types. Comparison between the two approaches for a range of spatial resolution is available from in table 1. Results indicate that LiDAR based statistics are essentially as powerful as field based statistics to discriminate forest types at coarse scale. This reflects the very strong correlation between the CHM and the field based stem diameter data. For example (figure 5) the Pearson correlation coefficient between median height and quadratic mean diameter for cells of 125 by 125 m is 0.945 (n=0.72). When a finer resolution is required however as for the detection of seasonally flooded bottomland forest along thalwegs, then LiDAR technology proves more efficient than field based inventories as it combines information from the DTM and the CHM. The wetness index alone correctly retrieves about 2 thirds of the seasonally flooded areas. All in all, discriminant analysis performance of the LiDAR derived information approaches 80% when classifying forests cover at the finest scale of 5 by 5m into 10 different types and reaches 87% when a coarser classification Into 6 forest types is considered (figure 4).

Abstract: The components of ecosystem evapotranspiration of a Norway spruce forest (Picea abies L.) as well as the vertical structure of canopy evapotranspiration were analyzed with a combination of measurements and models for a case study of 5 days in September 2007. Eddy-covariance and sap flux measurements were performed at several heights within the canopy at the FLUXNET site Waldstein-Weidenbrunnen (DE-Bay) in the Fichtelgebirge mountains in Germany. Within and above canopy fluxes were simulated with two stand-scale models, the 1D multilayer model ACASA that includes a third-order turbulence closure and the 3D model STANDFLUX. The soil and understory evapotranspiration captured with the eddy-covariance system in the trunk space constituted 10% of ecosystem evapotranspiration measured with the eddy-covariance system above the canopy. A comparison of transpiration measured with the sap flux technique and inferred from below and above canopy eddy-covariance systems revealed higher estimates from eddy-covariance measurements than for sap flux measurements. The relative influences of possible sources of this mismatch, such as the assumption of negligible contribution of evaporation from intercepted water, and differences between the eddy-covariance flux footprint and the area used for scaling sap flux measurements, were discussed. Ecosystem evapotranspiration as well as canopy transpiration simulated with the two models captured the dynamics of the measurements well, but slightly underestimated eddy-covariance values. Profile measurements and models also gave us the chance to assess in-canopy profiles of canopy evapotranspiration and the contributions of in-canopy layers. For daytime and a coupled or partly coupled canopy, mean simulated profiles of both models agreed well with eddy-covariance measurements, with a similar performance of the ACASA and the STANDFLUX model. Both models underestimated profiles for nighttime and decoupled conditions. During daytime, the upper half of the canopy contributed approximately 80% to canopy evapotranspiration, whereas during nighttime the contribution shifted to lower parts of the canopy. © 2010 Elsevier B.V.

Abstract: The inhibitive action of 9H-pyrido[3,4-b]indole (norharmane) and 1-Methyl-9H-pyrido[3,4-b]indole (harmane) on corrosion of C38 steel in 0.5 M H2SO4 solution was investigated through electrochemical techniques. The experimental results obtained revealed that these compounds inhibited the steel corrosion in acid solution for all concentrations studied. Polarization measurements indicate that the examined compounds act as a mixed inhibitor and its inhibition efficiency increases with inhibitor concentration. Data obtained from ac impedance technique show a frequency distribution and therefore a modelling element with frequency dispersion behaviour, a constant phase element (CPE), has been used. The adsorption of used compounds on the steel surface obeys Langmuir's isotherm. The ΔG°ads values were calculated and discussed for both inhibitors. Significant correlations are obtained between inhibition efficiency and quantum chemical parameters using quantitative structure-activity relationship (QSAR) method. © 2011 by ESG.

Abstract: We explored the relationship between soil processes, estimated through soil respiration (Rsoil), and the spatial variation in forest structure, assessed through the distribution of tree size, in order to understand the determinism of spatial variations in Rsoil in a tropical forest. The influence of tree size was examined using an index (Ic) calculated for each tree as a function of (1) the trunk cross section area and (2) the distance from the measurement point. We investigated the relationships between Ic and litterfall, root mass and Rsoil, respectively. Strong significant relationships were found between Ic and both litterfall and root mass. Rsoil showed a large range of variations over the 1-ha experimental plot, from 1. 5 to 12. 6 gC m-2 d-1. The best relationship between Ic and Rsoil only explained 17% of the spatial variation in Rsoil. These results support the assumption that local spatial patterns in litter production and root mass depend on tree distribution in tropical forests. Our study also emphasizes the modest contribution of tree size distribution-which is mainly influenced by the presence of the biggest trees (among the large range size of the inventoried trees greater than 10 cm diameter at 1. 30 m above ground level or at 0. 5 m above the buttresses)-in explaining spatial variations in Rsoil. © 2011 Springer Science+Business Media B.V.