Abstract: Wood has a hierarchical structure involving several levels of organisation. The stiffness of wood relies on its capacity to transfer mechanical stress to its stiffest element at the lowest scale, namely crystalline cellulose. This study aims at quantifying to what extend crystalline cellulose contributes to wood stiffness depending on its moisture content. The crystal strains of cellulose were measured using X-ray diffraction on wet and dry specimens of spruce, based on a previously published methodology. The comparison between crystal strain and macroscopic strain shows that, during elastic loading, cellulose strain is lower than macroscopic strain. The means ratio of crystal/macroscopic strain amounts 0.85 for dry specimens and 0.64 for wet specimens. This strain ratio cannot be explained just by the projection effect due to the difference in orientation between cellulose microfibrils and cell wall, but results from deformation mechanisms in series with cellulose. Analysis shows that this series contribution represents a non-negligible contribution to wood compliance and is strongly moisture-dependent. This contribution amounts 9% for dry specimens and 33% for wet specimens, corresponding to a 4-fold increase in compliance for the series contribution. The origin of these strains is ascribed to mechanisms involving bending or shear strain at different scales, due to the fact that reinforcing element are neither perfectly straight nor infinitely long. © 2016

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: Many recent studies have searched to integrate species’ functions and phylogenies in the measurement of biodiversity. To obtain easily interpretable measures, some researchers recommended diversity indices expressed in terms of equivalent numbers of species: the number of equally likely and maximally dissimilar species needed to produce the given value of diversity. Then, biodiversity is often calculated at three scales: within communities (α diversity), among communities (β diversity) and in a region (γ diversity). These three scales are, however, insufficient to tackle the organization of biodiversity in space because, for most organisms, there is a nested hierarchy of multiple scales characterized by different patterns and processes, from the small neighbourhood to the biosphere. We developed methodologies for analysing species, functional, taxonomic or phylogenetic diversity in a hierarchy of multiple scales using equivalent numbers of species. As an example, we analysed the taxonomic and functional diversity of macroinvertebrate assemblages in the Loire River, France, at four levels: within sites (α diversity), among sites within geological regions (β1 diversity), among geological regions (β2 diversity) and at the river scale (γ diversity). The new hierarchical approaches of biodiversity revealed very low differences among sites within regions and among regions in terms of taxonomy and functional traits (size and diet), despite moderate, significant species turnover among geological regions. We compare our framework with those other authors have developed. We argue that different definitions of α, β, γ diversities are used in the literature reflecting different points of view on biodiversity. We make recommendations on how to normalize functional (or phylogenetic) dissimilarities among species to render sites and regions comparable, and discuss the pros and cons of our approach. The hierarchical approaches of biodiversity in terms of ‘equivalent numbers’ respond to current demands to obtain intuitive, easily interpretable components of biodiversity. The approaches we propose go beyond current developments by considering a hierarchy of spatial scales and unbalanced sampling design. They will provide powerful tools to detect the ecological and evolutionary processes that act differently at different scales. © 2016 The Authors. Methods in Ecology and Evolution © 2016 British Ecological Society

Abstract: Animal venom peptides are currently being developed as novel drugs and bioinsecticides. Because ants use venoms for defense and predation, venomous ants represent an untapped source of potential bioactive toxins. This study compared the protein and peptide components of the poneroid ants Neoponera commutata, Neoponera apicalis, and Odontomachus hastatus and the formicoid ants Ectatomma tuberculatum, Ectatomma brunneum, and Myrmecia gulosa. 1D and 2D PAGE revealed venom proteins in the mass range <10 to >250 kDa. NanoLC-ESI-QTOF MS/MS analysis of tryptic peptides revealed the presence of common venom proteins and also many undescribed proteins. RP-HPLC separation followed by MALDI-TOF MS of the venom peptides also revealed considerable heterogeneity. It was found that the venoms contained between 144 and 1032 peptides with 5-95% of peptides in the ranges 1-4 and 1-8 kDa for poneroid and formicoid ants, respectively. By employing the reducing MALDI matrix 1,5-diaminonapthalene, up to 28 disulfide-bonded peptides were also identified in each of the venoms. In particular, the mass range of peptides from poneroid ants is lower than peptides from other venoms, indicating possible novel structures and pharmacologies. These results indicate that ant venoms represent an enormous, untapped source of novel therapeutic and bioinsecticide leads. © 2016 American Chemical Society.

Abstract: The tropical rainforest of Amazonia is one of the most species-rich ecosystems on earth, with an estimated 16000 tree species. Due to this high diversity, botanical identification of trees in the Amazon is difficult, even to genus, often requiring the assistance of parataxonomists or taxonomic specialists. Advances in informatics tools offer a promising opportunity to develop user-friendly electronic keys to improve Amazonian tree identification. Here, we introduce an original multi-access electronic key for the identification of 389 tree genera occurring in French Guiana terra-firme forests, based on a set of 79 morphological characters related to vegetative, floral and fruit characters. Its purpose is to help Amazonian tree identification and to support the dissemination of botanical knowledge to non-specialists, including forest workers, students and researchers from other scientific disciplines. The electronic key is accessible with the free access software Xper2, and the database is publicly available on figshare: https://figshare.com/s/75d890b7d707e0ffc9bf (doi: 10.6084/m9.figshare.2682550). © Julien Engel et al.