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: This article reviews an experimental system set up in French Guiana to test different selective thinning methods that started ten to fifteen years after logging in order to reconstitute commercially viable stands within the shortest time. The thinning methods tested involve a combination of selective intervention within a radius of 10 metres around crop trees and systematic intervention applied uniformly to the entire forest parcel. The resulting thinning intensity produces an 8% to 45% reduction in basal area. While the growth of the residual stand is strongly boosted in all species and for all diameters, there is little change in basal area because of high mortality and lower recruitment of commercial species. Standing commercial capital, however, is strongly affected by the thinning operations as defined. In effect, these thinning methods that benefit crop stems do not meet the objective of shorter rotations in Guiana's tropical logging forests. On the other hand, the measurements made in under-treatment stands agree with those obtained at the Paracou experimental station and confirm the need to adopt long cutting cycles of more than fifty years to ensure that the extraction of valuable species is sustainable in the current logging context in French Guiana.

Abstract: Geomorphic landscape features have been suggested as indicators of forest diversity. However, their explanatory power has not yet been explicitly tested at a regional scale in tropical rainforest. We used forest inventories conducted according to a stratified sampling design (3,132 plots in 111 transects at 33 sites) and holistic multi-scale geomorphological mapping derived from a Shuttle Radar Topography Mission digital elevation model to describe and explain spatial patterns in floristic composition across French Guiana (80,000 km2). We measured and identified 123,906 trees with DBH ≥20 cm and used constrained and unconstrained ordinations to analyze variations in the abundance of 221 taxa and 51 families. Variance partitioning and variograms were used to detect spatial patterns in species composition, compare the explanatory power of spatial and environmental factors, and select the variables that best explain forest composition. Strong floristic patterns corresponded to a major latitudinal gradient and significant sub-regional floristic structure. Geomorphological landscapes shaped by historic climate fluctuations and major geological events successfully captured these patterns and explained the variation in abundance of 80 taxa, corresponding to 65 % of the inventoried trees. Our findings suggest that long-term forest dynamics are under substantial “geomorphographic control”. A geomorphological perspective on landscapes that incorporates current and past environmental filters and historical biogeographical processes could thus be used more systematically in tropical regions for regional planning and forest conservation. © 2014, Springer Science+Business Media Dordrecht.

Abstract: Analyses of tree diversity and community composition in tropical rain forests are usually based either on general herbarium data or on a restricted number of botanical plots. Despite their high taxonomic accuracy, both types of data are difficult to extrapolate to landscape scales. Meanwhile, forestry surveys provide quantitative occurrence data on large areas, and are thus increasingly used for landscape-scale analyses of tree diversity. However, the reliability of these approaches has been challenged because of the ambiguity of the common (vernacular) names used by foresters and the complexity of tree taxonomy in those hyper-diverse communities.We developed and tested a novel approach to evaluate taxonomic reliability of forestry surveys and to propagate the resulting uncertainty in the estimates of several diversity indicators (alpha and beta entropy, Fisher-alpha and Sørensen similarity). Our approach is based on Monte-Carlo processes that simulate communities by taking into account the expected accuracy and reliability of common names. We tested this method in French Guiana, on 9 one-hectare plots (4279 trees – DBH. ≥. 10. cm) for which both common names and standardized taxonomic determinations were available. We then applied our method of community simulation on large forestry inventories (560. ha) at the landscape scale and compared the diversity indices obtained for 10 sites with those computed from precise botanical determination situated at the same localities.We found that taxonomic reliability of forestry inventories varied from 22% (species level) to 83% (family level) in this Amazonian region. Indices computed directly with raw forestry data resulted in incorrect values, except for Gini-Simpson beta-diversity. On the contrary, our correction method provides more accurate diversity estimates, highly correlated with botanical measurements, for almost all diversity indices at both regional and local scales. We obtained a robust ranking of sites consistent with those shown by botanical inventories.These results show that (i) forestry inventories represent a significant part of taxonomic information, (ii) the relative diversity of regional sites can be successfully ranked using forestry inventory data using our method and (iii) forestry inventories can valuably contribute to the detection of large-scale diversity patterns when biases are well-controlled and corrected.The tools we developed as R-functions are available in supplementary material and can be adapted with local parameters to be used for forest management and conservation issues in other regional contexts. © 2014 Elsevier B.V.

Abstract: Proper estimates of decomposition are essential for tropical forests, given their key role in the global carbon (C) cycle. However, the current paradigm for litter decomposition is insufficient to account for recent observations and may limit model predictions for highly diverse tropical ecosystems. In light of recent findings from a nutrient-poor Amazonian rainforest, we revisit the commonly held views that: litter traits are a mere legacy of live leaf traits; nitrogen (N) and lignin are the key litter traits controlling decomposition; and favourable climatic conditions result in rapid decomposition in tropical forests. Substantial interspecific variation in litter phosphorus (P) was found to be unrelated to variation in green leaves. Litter nutrients explained no variation in decomposition, which instead was controlled primarily by nonlignin litter C compounds at low concentrations with important soil fauna effects. Despite near-optimal climatic conditions, tropical litter decomposition proceeded more slowly than in a climatically less favourable temperate forest. We suggest that slow decomposition in the studied rainforest results from a syndrome of poor litter C quality beyond a simple lignin control, enforcing energy starvation of decomposers. We hypothesize that the litter trait syndrome in nutrient-poor tropical rainforests may have evolved to increase plant access to limiting nutrients via mycorrhizal associations.