Abstract: The clear multi-scale structure of composite textile reinforcements leads to develop continuous and discrete approaches for their forming simulations. In this paper two continuous modelling respectively based on a hypoelastic and hyperelastic constitutive model are presented. A discrete approach is also considered in which each yarn is modelled by shell finite elements and where the contact with friction and possible sliding between the yarns are taken into account. Finally the semi-discrete approach is presented in which the shell finite element interpolation involves continuity of the displacement field but where the internal virtual work is obtained as the sum of tension, in-plane shear and bending ones of all the woven unit cells within the element. The advantages and drawbacks of the different approaches are discussed.

Abstract: We describe five new species in the aurita group of the genus Azteca: Azteca andreae sp. n. (French Guiana), Azteca diabolica sp. n. (Panama), Azteca laurae sp. n. (Brazil), Azteca linamariae sp. n. (Brazil and Colombia) and Azteca snellingi sp. n. (Panama). Four of these new species are based on gynes, while the last is based only on the worker caste. All of them bear the aurita group characteristics. The second taxon is remarkable, as it differs from all of the other members of the group in the exaggerated, horn-like extensions of the posterolateral vertex margins. Azteca snellingi sp. n. is named in honor of our colleague, Roy Snelling, in tribute to his life-long contribution to knowledge of the world of Hymenoptera. A key to all known species of the aurita group, based on gynes, is provided. We report also for the first time an intercast case for the genus Azteca, based on an Azteca schimperi specimen.

Abstract: MILLET J, PASCAL JP & MET LC. 2010. Effects of disturbance over 60 years on a lowland forest in southern Vietnam. Tropical lowland forests are some of the most threatened in the world and this is particularly the case in Vietnam. This study aimed to identify changes in species composition and forest structure in the Tan Phu lowland forest resulting from disturbance over a 60 year period. Analysis of forest composition and structure rely on data from 25 plots of 0.5-ha size established in a lowland secondary forest. The five forest stands described differed greatly from the three forest stand types described in 1943. Some long-lived shade-tolerant species had been replaced by pioneer species, such as Cratoxylon formosum and Shorea roxburghii. In addition to altering composition, forest disturbances had resulted in large changes in forest structure. While in the past, forest stands had a large number of exploitable trees, current forest stands have few trees in the diameter class > 50 cm and sometimes no trees in the diameter class > 80 cm. This paper provides notable results on forest tree ecology, forest dynamics and on the state of secondary forests in Vietnam. This is particularly important as future goods and services will increasingly have to come from such forests.

Abstract: The presence of the frontal gland is well established in termite soldiers of Rhinotermitidae, Serritermitidae, and Termitidae. It is one of their main defensive adaptations or even an exclusive weapon. The gland was also occasionally reported in alate imagoes, but never in the worker caste. Here, we report the first observation of a frontal gland in workers of several Neotropical and one African species of Apicotermitinae. The ultrastructure of Aparatermes cingulatus and Anoplotermes nr. subterraneus is described in detail. In these two species, the gland is well-developed, functional and consists of class 1 secretory cells. The presence of envelope cells, wrapping the gland, is an unusual feature, as well as the presence of several zonulae adherens, connecting neighbouring glandular cells. The frontal gland of workers is homologous to this organ in soldiers and imagoes, as evidenced by the same position in the head and its connection to the same muscle. However, the defensive role of the frontal gland in workers remains to be confirmed.

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).