Abstract: The recent development of REDD+ mechanisms requires reliable estimation of carbon stocks, especially in tropical forests that are particularly threatened by global changes. Even though tree height is a crucial variable for computing aboveground forest biomass (AGB), it is rarely measured in large-scale forest censuses because it requires extra effort. Therefore, tree height has to be predicted with height models. The height and diameter of all trees over 10 cm in diameter were measured in 33 half-hectare plots and 9 one-hectare plots throughout northern French Guiana, an area with substantial climate and environmental gradients. We compared four different model shapes and found that the Michaelis-Menten shape was most appropriate for the tree biomass prediction. Model parameter values were significantly different from one forest plot to another, and this leads to large errors in biomass estimates. Variables from the forest stand structure explained a sufficient part of plot-to-plot variations of the height model parameters to improve the quality of the AGB predictions. In the forest stands dominated by small trees, the trees were found to have rapid height growth for small diameters. In forest stands dominated by larger trees, the trees were found to have the greatest heights for large diameters. The aboveground biomass estimation uncertainty of the forest plots was reduced by the use of the forest structure-based height model. It demonstrated the feasibility and the importance of height modeling in tropical forests for carbon mapping. When the tree heights are not measured in an inventory, they can be predicted with a height-diameter model and incorporating forest structure descriptors may improve the predictions. © Author(s) 2014. CC Attribution 3.0 License.

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: This study is an assessment of the chemical quality and evaluation of antibacterial and antifungal activity of rosemary’s essential oils from three regions of Morocco (Rchida and Berkine/Eastern Morocco and Aknoul/North East of Morocco. The essential oils obtained by hydrodistillation of the leaves and young twigs of rosemary, were analyzed by GC / FID and GC/ MS. These essential oils are characterized by the presence of α and β-pinene, camphene, 1,8-cineole and camphor compounds. The quality of these essential oils met the AFNOR NF ISO 4730 rosemary Morocco kind (1,8-cineole). The evaluation of the antimicrobial activity of essential oils of Rosmarinus officinalis showed low efficacy against microorganisms tested which were all inhibited from 1/100 v/v except for Penicillium expansum whose growth was stopped at the concentration 1/250 v/v.

Abstract: Climate models predict significant rainfall reduction in Amazonia, reducing water availability for trees. We present how functional traits modulate the tree growth response to climate. We used data from 3 years of bimestrial growth measurements for 204 trees of 53 species in the forest of Paracou, French Guiana. We integrated climate variables from an eddy covariance tower and functional trait values describing life history, leaf, and stem economics. Our results indicated that the measured functional traits are to some extent linked to the response of trees to climate but they are poor predictors of the tree climate-induced growth variation. Tree growth was affected by water availability for most of the species with different species growth strategies in drought conditions. These strategies were linked to some functional traits, especially maximum height and wood density. These results suggest that (i) trees seem adapted to the dry season at Paracou but they show different growth responses to drought, (ii) drought response is linked to growth strategy and is partly explained by functional traits, and (iii) the limited part of the variation of tree growth explained by functional traits may be a strong limiting factor for the prediction of tree growth response to climate. © 2014 Fabien Wagner et al.

Abstract: Herbivory is viewed as a major driver of plant evolution and the most important energy pathway from plants to higher trophic levels. Therefore, understanding patterns of herbivory on plants remains a key focus in evolution and ecology. The evolutionary impacts of leaf herbivory include altering plant fitness, local adaptation, the evolution of defenses, and the diversification of plants as well as natural enemies. Leaf herbivory also impacts ecological processes such as plant productivity, community composition, and ecosystem nutrient cycling. Understanding the impact of herbivory on these ecological and evolutionary processes requires species-specific, as opposed to community-level, measures of herbivory. In addition, species-specific data enables the use of modern comparative methods to account for phylogenetic non-independence. Although hundreds of studies have measured natural rates of leaf consumption, we are unaware of any accessible compilation of these data. We created such a data set to provide the raw data needed to test general hypotheses relating to plant?herbivore interactions and to test the influence of biotic and abiotic factors on herbivory rates across large spatial scales. A large repository will make this endeavor more efficient and robust. In total, we compiled 2641 population-level measures for either annual or daily rates of leaf herbivory across 1145 species of vascular plants collected from 189 studies. All damage measures represent natural occurrences of herbivory that span numerous angiosperm, gymnosperm, and fern species. To enable researchers to explore the causes of variation in herbivory and how these might interact, we added information about the study sites including: geolocation, climate classification, habitat descriptions (e.g., seashore, grassland, forest, agricultural fields), and plant trait information concerning growth form and duration (e.g., annual vs. perennial). We also included extensive details of the methodology used to measure leaf damage, including seasons and months of sampling, age of leaves, and the method used to estimate percentage area missing. We anticipate that these data will make it possible to test important hypotheses in the plant?herbivore literature, including the plant apparency hypothesis, the latitudinal-herbivory defense hypothesis, the resource availability hypothesis, and the macroevolutionary escalation of defense hypothesis.