Abstract: Ants, the most abundant taxa among canopy-dwelling animals in tropical rainforests, are mostly represented by territorially dominant arboreal ants (TDAs) whose territories are distributed in a mosaic pattern (arboreal ant mosaics). Large TDA colonies regulate insect herbivores, with implications for forestry and agronomy. What generates these mosaics in vegetal formations, which are dynamic, still needs to be better understood. So, from empirical research based on 3 Cameroonian tree species (Lophira alata, Ochnaceae; Anthocleista vogelii, Gentianaceae; and Barteria fistulosa, Passifloraceae), we used the Self-Organizing Map (SOM, neural network) to illustrate the succession of TDAs as their host trees grow and age. The SOM separated the trees by species and by size for L. alata, which can reach 60 m in height and live several centuries. An ontogenic succession of TDAs from sapling to mature trees is shown, and some ecological traits are highlighted for certain TDAs. Also, because the SOM permits the analysis of data with many zeroes with no effect of outliers on the overall scatterplot distributions, we obtained ecological information on rare species. Finally, the SOM permitted us to show that functional groups cannot be selected at the genus level as congeneric species can have very different ecological niches, something particularly true for Crematogaster spp., which include a species specifically associated with B. fistulosa, nondominant species and TDAs. Therefore, the SOM permitted the complex relationships between TDAs and their growing host trees to be analyzed, while also providing new information on the ecological traits of the ant species involved. © 2015 Institute of Zoology, Chinese Academy of Sciences

Abstract: Devil's gardens are one of the most remarkable mutualistic associations between ants and plants. Myrmelachista ants eliminate all vegetation from around their host plants, resulting in wide forest clearings which have intrigued scientists from the start. Despite their noticeability, here we report the discovery of devil's gardens in remote highland cloud forests of the Eastern Amazon, more than 2000 km away from their nearest known analogues in Western Amazonia. We describe the ecological characteristics of these gardens and consider what factors could have produced the geographic isolation of Eastern Amazonian devil's gardens. Three hypotheses are investigated: (1) the host plant distribution restricts the distribution of the mutualism, (2) the ecological tolerances of Myrmelachista explain the isolation, and (3) the devil's gardens of the Eastern Amazon constitute relicts from ancient forest refugia. The distribution of the possible associated myrmecophytes and previously described ecological ranges of devil's gardens cannot explain their ecological restriction to cloud forests in Eastern Amazonia, but our discovery is consistent with the biogeographic refuge hypothesis (i.e. highlands along the Amazon Basin constitute refugia for humid forests that spread during the Cenozoic). Our finding opens exciting perspectives for comparative studies of the origin, ecology and evolutionary history of this ant-plant mutualism. Copyright © Cambridge University Press 2016.

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.

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: 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