Abstract: Most eukaryotic organisms are arthropods. Yet, their diversity in rich terrestrial ecosystems is still unknown. Here we produce tangible estimates of the total species richness of arthropods in a tropical rainforest. Using a comprehensive range of structured protocols, we sampled the phylogenetic breadth of arthropod taxa from the soil to the forest canopy in the San Lorenzo forest, Panama. We collected 6144 arthropod species from 0.48 hectare and extrapolated total species richness to larger areas on the basis of competing models. The whole 6000-hectare forest reserve most likely sustains 25,000 arthropod species. Notably, just 1 hectare of rainforest yields >60% of the arthropod biodiversity held in the wider landscape. Models based on plant diversity fitted the accumulated species richness of both herbivore and nonherbivore taxa exceptionally well. This lends credence to global estimates of arthropod biodiversity developed from plant models.

Abstract: Cecropia (Cecropiaceae) is a Neotropical genus of pioneer plants. A review of bat/plant dispersal interactions revealed that 15 species of Cecropia are consumed by 32 species of bats. In French Guiana, bats were captured in primary and secondary forests, yielding 936 fecal samples with diaspores, among which 162 contained fruits of C. obtusa, C. palmata, and C. sciadophylla. A comparative morphological and anatomical study of fruits and seeds taken directly from herbarium specimens, bat feces, and an experimental soil seed bank was made. Contrary to previous reports, the dispersal unit of Cecropia is the fruit not the seed. Bats consume the infructescence, digest pulp derived from the enlarged, fleshy perianth, and defecate the fruits. The mucilaginous pericarp of Cecropia is described. The external mucilage production of Cecropia may facilitate endozoochory. The exocarp and part of the mesocarp may be lost after passage through the digestive tract of bats, but fruits buried for a year in the soil seed bank remain structurally unchanged. Fruit characters were found to be useful for identifying species of bat-dispersed Cecropia. Bat dispersal is not necessary for seed germination but it increases seed survival and subsequent germination. Fruit structure plays a significant role in seed longevity.

Abstract: Mapping forest aboveground biomass (AGB) has become an important task, particularly for the reporting of carbon stocks and changes. AGB can be mapped using synthetic aperture radar data (SAR) or passive optical data. However, these data are insensitive to high AGB levels (>150 Mg/ha, and >300 Mg/ha for P-band), which are commonly found in tropical forests. Studies have mapped the rough variations in AGB by combining optical and environmental data at regional and global scales. Nevertheless, these maps cannot represent local variations in AGB in tropical forests. In this paper, we hypothesize that the problem of misrepresenting local variations in AGB and AGB estimation with good precision occurs because of both methodological limits (signal saturation or dilution bias) and a lack of adequate calibration data in this range of AGB values. We test this hypothesis by developing a calibrated regression model to predict variations in high AGB values (mean >300 Mg/ha) in French Guiana by a methodological approach for spatial extrapolation with data from the optical geoscience laser altimeter system (GLAS), forest inventories, radar, optics, and environmental variables for spatial inter- and extrapolation. Given their higher point count, GLAS data allow a wider coverage of AGB values. We find that the metrics from GLAS footprints are correlated with field AGB estimations (R2 = 0.54, RMSE = 48.3 Mg/ha) with no bias for high values. First, predictive models, including remote-sensing, environmental variables and spatial correlation functions, allow us to obtain “wall-to-wall” AGB maps over French Guiana with an RMSE for the in situ AGB estimates of ∼50 Mg/ha and R2 = 0.66 at a 1-km grid size. We conclude that a calibrated regression model based on GLAS with dependent environmental data can produce good AGB predictions even for high AGB values if the calibration data fit the AGB range. We also demonstrate that small temporal and spatial mismatches between field data and GLAS footprints are not a problem for regional and global calibrated regression models because field data aim to predict large and deep tendencies in AGB variations from environmental gradients and do not aim to represent high but stochastic and temporally limited variations from forest dynamics. Thus, we advocate including a greater variety of data, even if less precise and shifted, to better represent high AGB values in global models and to improve the fitting of these models for high values. © 2016 Elsevier B.V.

Abstract: Essential oil from the Amazonian rosewood tree (Aniba rosaeodora Ducke) is valued as an important aromatic ingredient in luxury perfumes. Due to over-harvesting in recent decades, rosewood is now listed as an endangered species. Rosewood tree planting is now considered a viable alternative to logging as it can support both reforestation and sustainable agriculture thanks to sales of the essential oil extracted. We planted 605 rosewood trees in French Guiana from two seeds of local provenance, in a 5 445 m2 plot surrounded by primary forest. Nine years after planting, we assessed the effect of the position of the tree relative to the surrounding forest and of the seed provenance on dendrometric traits (height, circumference, above ground woody biomass) and hence on the yield of essential oil. Measurements were made on 99 trees. Average growth rates for the young trees were 0.7 m/year in height, 2.5 cm/year in stem circumference and 990.5 kg dry mass/ha/year in aboveground biomass, while essential oil yields ranged from 0.6% to 3.6% with a mean of 2.1%. The position of the tree relative to the surrounding forest was the main factor affecting tree growth and essential oil production: trees located close to the surrounding forest were significantly smaller and accumulated less essential oil due to the reduced availability of light. Seed provenance had less effect on dendrometric traits and essential oil yields. In conclusion, although planting practices will need to be adapted to avoid the edge effects of proximity to the forest, short-rotation cultivation of rosewood trees could be the optimum and most economically attractive system for the production of essential oil.

Abstract: We predict stand basal area (BA) from small footprint LiDAR data in 129 one-ha tropical forest plots across four sites in French Guiana and encompassing a great diversity of forest structures resulting from natural (soil and geological substrate) and anthropogenic effects (unlogged and logged forests). We use predictors extracted from the Canopy Height Model to compare models of varying complexity: single or multiple regressions and nested models that predict BA by independent estimates of stem density and quadratic mean diameter. Direct multiple regression was the most accurate, giving a 9.6% Root Mean Squared Error of Prediction (RMSEP). The magnitude of the various errors introduced during the data collection stage is evaluated and their contribution to MSEP is analyzed. It was found that these errors accounted for less than 10% of model MSEP, suggesting that there is considerable scope for model improvement. Although site-specific models showed lower MSEP than global models, stratification by site may not be the optimal solution. The key to future improvement would appear to lie in a stratification that captures variations in relations between LiDAR and forest structure. © 2012 Elsevier Inc.