Abstract: A major challenge remains to understand the relative contributions of history, dispersal, and environmental filtering to the assembly of hyperdiverse communities across spatial scales. Here, we examine the extent to which biogeographical history and habitat specialization have generated turnover among and within lineages of Amazonian trees across broad geographic and environmental gradients. We replicated standardized tree inventories in 102 0.1-ha plots located in two distant regions—the western Amazon and the eastern Guiana shield. Within each region, we used a nested design to replicate plots on contrasted habitats: white-sand, terra firme, and seasonally flooded forests. Our plot network encompassed 26,386 trees that together represented 2,745 distinct taxa, which we standardized across all plots and regions. We combined taxonomic and phylogenetic data with detailed soil measurements and climatic data to: (1) test whether patterns of taxonomic and phylogenetic composition are consistent with recent or historical processes, (2) disentangle the relative effects of habitat, environment, and geographic distance on taxonomic and phylogenetic turnover among plots, and (3) contrast the proportion of habitat specialists among species from each region. We found substantial species turnover between Peru and French Guiana, with only 8.8% of species shared across regions; genus composition remained differentiated across habitats and regions, whereas turnover at higher taxonomic levels (family, order) was much lower. Species turnover across plots was explained primarily by regions, but also substantially by habitat differences and to a lesser extent by spatial distance within regions. Conversely, the composition of higher taxonomic levels was better explained by habitats (especially comparing white-sand forests to other habitats) than spatial distance. White-sand forests harbored most of the habitat specialists in both regions, with stronger habitat specialization in Peru than in French Guiana. Our results suggest that recent diversification events have resulted in extremely high turnover in species and genus composition with relatively little change in the composition of higher lineages. Our results also emphasize the contributions of rare habitats, such as white-sand forests, to the extraordinary diversity of the Amazon and underline their importance as conservation priorities.

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.

Abstract: A model to simulate the ecological processes of tree growth, mortality and recruitment, and the processes of forest management, in the terra firme forests of the eastern Amazon is described. It is implemented within the SYMFOR (http://www.symfor.org) framework. It is based on measurements of all trees that have a diameter greater than 5 cm from experimental plots in the Jari Cellulose and Tapajos National Forest areas over a 16-year period. Ten species groups are used to describe the natural processes affecting tree behaviour. Growth rates are calculated for each species group using the tree diameter and a competition index. Mortality and recruitment are simulated as stochastic processes. Recruitment probability is based on the predicted growth rate of a hypothetical tree. Options exist to vary the human interaction with the forest reflecting forest management decisions, as for other SYMFOR models. Model evaluation compares the performance of the model with data describing forest recovery for 16 years following logging. The model was applied to simulate current forest management practice in the Brazilian Amazon, with 40 m(3) ha(-1) of timber extracted with a cutting cycle of 30 years. Results show that yields are sustained for three harvests following the first logging of primary forest, but that the composition of timber moves towards lightwooded species rather than hardwooded. The predicted size of extracted trees decreases and the number of trees extracted increases with successive harvests, leading to a prediction of increased costs and lower profits for the logging company despite constant yields. The standing volume of all trees just before harvest is reduced by 15% over 150 years, with pioneer species becoming increasingly prevalent in the stand. The model, in the SYMFOR framework, can be used to help understand the differences between alternative forest management strategies in the Brazilian Amazon. Such knowledge is required to improve forest management, regulation and certification, and help to conserve the worlds largest remaining tropical forest. (C) 2003 Elsevier B.V. All rights reserved.

Abstract: In the context of an ongoing monitoring study on the impacts of gold-mining activities on critical ecosystem processes, we explored the use of soil Denitrifying Enzyme Activity (DEA) and Substrate Induced Respiration (SIR) as ecosystem indicators in tropical rainforests of French Guiana. We also propose DEA/SIR ratio as ecosystem attribute able to describe the state of an ecosystem and to reflect changes in ecological processes. With this purpose, we measured SIR, DEA and DEA/SIR ratio in five gold-mining areas and five surrounding natural reference rainforests. We also measured indicators in two conditions of spontaneous regeneration of vegetation (stratified or not) and two conditions of soil rehabilitation (prior preparation of soils or not). We showed a high variability of DEA, SIR and DEA/SIR ratio in the natural reference forests. This pointed out the necessity to identify relevant reference systems – i.e. proving a close match in all relevant ecological dimensions – to compare with closed perturbed systems in order to assess the levels of alterations after disturbances. Results showed a high impact of gold mine on microbial processes with a strong decrease of DEA (10-fold lower), SIR (2-fold lower) and DEA/SIR ratio (8-fold lower) in perturbed areas in comparison with natural reference forests. The type of spontaneous vegetation (stratified or not) influenced the values of indicators as well as prior rehabilitation of soils, demonstrating the capacity of DEA, SIR and DEA/SIR ratio to respond in proportion to the perturbation (robustness) and to the different levels of restoration (sensitivity). The systematic decrease of the ratio DEA/SIR observed in the studied perturbed situations demonstrates clearly that the structure of microbial communities has been also modified. The ratio DEA/SIR proved to be robust and sensitive, and able to describe in fairly fine way changes of soil microbial communities in terms of structure and function in gold mine areas and during processes of restoration. We propose to use DEA, SIR and DEA/SIR ratio as bioindicators of both structural and functional aspects of C and N cycling in soils. Together with others bioindicators based on key supporting functions in soils, these indicators should accurately evaluate the ecological potential of natural ecosystems and the levels of degradation in case of land-use changes. © 2012 Elsevier Ltd.

Abstract: I investigated whether the morphological traits of Neotropical ants can be used to infer food resource use by individual species and by entire communities, and whether these relationships are related to habitat type and/or by morphological differences between ant subfamilies. I attracted ants using food baits that represented different ecological processes (e.g. predation, granivory, detritivory, nectarivory) in five habitat types along a land-use gradient (from forests to gardens). I assessed ant activity at the baits and characterized 64 species from six subfamilies according to their food use and community-level resource exploitation intensity in the different habitats. Next, I performed a Mantel test to reveal the relationships between 13 morphological measures and resource use at the species level. I then used ant clades (i.e. subfamily) and habitat to rank the ants along three axes of variation in relation to their morphology and food resource use. Finally, I tested whether associations existed between the community-level exploitation intensity for such resources and the distribution of morphological trait values using the “4th-corner” analysis. Morphological traits were closely linked to the species’ ability to exploit different resources. These relationships were affected by subfamily and, to a lesser extent, by habitat type. The characterization of trait sets for entire communities was not useful, however, in predicting the intensity of the exploitation of different types of resources in varying environmental conditions. I conclude that morphological traits are accurate predictors of the ecology of species, but they should be used with caution when trying to understand community-level patterns. © 2017 Elsevier Ltd