Abstract: The natural durability of wood species, defined as their inherent resistance to wood-destroying agents, is a complex phenomenon depending on many biotic and abiotic factors. Besides the presence of recalcitrant polymers, the presence of compounds with antimicrobial properties is known to be important to explain wood durability. Based on the advancement in our understanding of fungal detoxification systems, a reverse chemical ecology approach was proposed to explore wood natural durability using fungal glutathione transferases. A set of six glutathione transferases from the white-rot Trametes versicolor were used as targets to test wood extracts from seventeen French Guiana neotropical species. Fluorescent thermal shift assays quantified interactions between fungal glutathione transferases and these extracts. From these data, a model combining this approach and wood density significantly predicts the wood natural durability of the species tested previously using long-term soil bed tests. Overall, our findings confirm that detoxification systems could be used to explore the chemical environment encountered by wood-decaying fungi and also wood natural durability. © 2020 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Abstract: Research on antifungal compounds from the durable wood from French Guiana Amazonian forest trees highlights the correlation between the activity of their extracts against wood-rotting fungi and human pathogens. The fractionation of an ethyl acetate extract of Sextonia rubra wood led to the isolation of rubrenolide (1) and rubrynolide (2). The potential of compounds 1 and 2 is described through the evaluation of their activity against 16 pathogenic fungi and their cytotoxicity toward NIH-3T3 mammalian fibroblast cells.

Abstract: Urban expansion and associated habitat transformation drives shifts in biodiversity, with declines in taxonomic and functional diversity. Forests fragments within urban landscapes offer a number of ecosystem services, and help to maintain biodiversity and ecosystem functions. Here, we focus on a tropical forest environment, and on the soil biota. Using eDNA metabarcoding, we compare forest fragments within the city of Cayenne, French Guiana, with a neighbouring continuous undisturbed forest. We wished to determine if urban forest fragments conserve high levels of alpha and beta diversity as well as similar functional composition for plants, soil animals, fungi and bacteria. We found that alpha diversity is similar across habitats for plants and fungi, lower in urban forests for metazoans and higher for bacteria. We also found that urban forests communities differ from undisturbed forests in their taxonomic composition, with urban forests exhibiting greater turnover between fragments potentially caused by ecological drift and limited dispersal. However, their functional composition exhibited limited differences, with an enrichment of palms, arbuscular mycorrhizal fungi and bacteria and a depletion of climber plants and termites. Thus, although urban forest fragments do shelter soil biodiversity that differs from native forests, the losses of soil functions may be relatively limited. This study demonstrates the strong potential of a multi-taxa eDNA approach for rapid inventories across taxonomic kingdoms, in particular for cryptic soil diversity. It also demonstrates the key role of urban forest fragments in conserving biodiversity and ecosystem function, and points to a need for more systematic monitoring of these areas in urban management plans.

Abstract: Herbivores are often implicated in the generation of the extraordinarily diverse tropical flora. One hypothesis linking enemies to plant diversification posits that the evolution of novel defenses allows plants to escape their enemies and expand their ranges. When range expansion involves entering a new habitat type, this could accelerate defense evolution if habitats contain different assemblages of herbivores and/or divergent resource availabilities that affect plant defense allocation. We evaluated this hypothesis by investigating two sister habitat specialist ecotypes of Protium subserratum (Burseraceae), a common Amazonian tree that occurs in white-sand and terra firme forests. We collected insect herbivores feeding on the plants, assessed whether growth differences between habitats were genetically based using a reciprocal transplant experiment, and sampled multiple populations of both lineages for defense chemistry. Protium subserratum plants were attacked mainly by chrysomelid beetles and cicadellid hemipterans. Assemblages of insect herbivores were dissimilar between populations of ecotypes from different habitats, as well as from the same habitat 100 km distant. Populations from terra firme habitats grew significantly faster than white-sand populations; they were taller, produced more leaf area, and had more chlorophyll. White-sand populations expressed more dry mass of secondary compounds and accumulated more flavone glycosides and oxidized terpenes, whereas terra firme populations produced a coumaroylquinic acid that was absent from white-sand populations. We interpret these results as strong evidence that herbivores and resource availability select for divergent types and amounts of defense investment in white-sand and terra firme lineages of Protium subserratum, which may contribute to habitat-mediated speciation in these trees. © 2013 by the Ecological Society of America.

Abstract: Modelling the local density of tropical saplings can provide insights into the ecological processes that drive species regeneration and thereby help predict population recovery after disturbance. Yet, few studies have addressed the challenging issues in autocorrelation and zero-inflation of local density. This paper presents Hierarchical Bayesian Modelling (HBM) of sapling density that includes these two features. Special attention is devoted to variable selection, model estimation and comparison. We developed a Zero-Inflated Poisson (ZIP) model with a latent correlated spatial structure and compared it with non-spatial ZIP and Poisson models that were either autocorrelated (Spatial Generalized Linear Mixed, SGLM) or not (generalized linear models, GLM). In our spatial models, local density autocorrelation was modeled by a Conditional Auto-Regressive (CAR) process. 13 explicative variables described ecological conditions with respect to topography, disturbance, stand structure and intraspecific processes. Models were applied to six tropical tree species with differing biological attributes: Oxandra asbeckii, Eperua falcata, Eperua grandiflora, Dicorynia guianensis, Qualea rosea, and Tachigali melinonii. We built species-specific models using a simple method of variable selection based on a latent binary indicator. Our spatial models showed a close correlation between observed and estimated densities with site spatial structure being correctly reproduced. By contrast, the non-spatial models showed poor fits. Variable selection highlighted species-specific requirements and susceptibility to local conditions. Model comparison overall showed that the SGLM was the most accurate explanatory and predictive model. Surprisingly, zero-inflated models performed less well. Although the SZIP model was relevant with respect to data distribution, and more flexible with respect to response curves, its model complexity caused marked variability in parameter estimates. In the SUM, the spatial process alone accounted for zero-inflation in the data. A refinement of the hypotheses employed at the process level could compensate for distribution flaws at the data level. This study emphasized the importance of the HBM framework in improving the modelling of density-environment relationships. (C) 2008 Elsevier B.V. All rights reserved.