Search

Key message: We used lightweight terrestrial laser scanning (TLS) to detect over 3000 stems per hectare across a 12-ha permanent forest plot in French Guiana, 81% of them < 10 cm in trunk diameter. This method retrieved 85% of the trees of a classic inventory. Finally, TLS revealed that stem positions of the classic inventory had geolocation errors of up to 6 m. Context: Accurate position mapping of tropical rainforest trees is crucial for baseline studies of tropical forest ecology but is labor-intensive. Terrestrial lidar scanning (TLS) is broadly used in temperate forest inventories, but its use in rainforests is restricted to the determination of individual tree volumes within small survey areas. Aims: Mapping tree stems across one large (12-ha) rainforest plot, including trees less than 10 cm DBH, and evaluating the precision of traditional mapping approaches. Methods: We used lightweight TLS, co-registered the acquisitions, and developed a new efficient algorithm to process the TLS data. Results: We detected 36,422 stems of which 29,665 (81%) were < 10 cm in diameter at breast height (DBH). Of the trees ≥ 10 cm DBH previously censused in the plot, 85% were identified by TLS. Automatic DBH estimation from TLS data had an RMSE of 6 cm. RMSE was improved to 3 cm by a manual verification of the shape and quality of the stem points. The initial census map had substantial bias in tree geolocation with a maximum value around 6 m. Conclusion: Lightweight TLS technology is a promising tool for the estimation of stem tapering and volume. Here, we show that it also facilitates the establishment of large tropical forest inventories, by improving the positioning of trees, thus increasing the accuracy of forest inventories and their cost-effectiveness. [ABSTRACT FROM AUTHOR]

Developing and improving methods to monitor forest carbon in space and time is a timely challenge, especially for tropical forests. The next European Space Agency Earth Explorer Core Mission BIOMASS will collect synthetic aperture radar (SAR) data globally from employing a multiple baseline orbit during the initial phase of its lifetime. These data will be used for tomographic SAR (TomoSAR) processing, with a vertical resolution of about 20 m, a resolution sufficient to decompose the backscatter signal into two to three layers for most closed-canopy tropical forests. A recent study, conducted in the Paracou site, French Guiana, has already shown that TomoSAR significantly improves the retrieval of forest aboveground biomass (AGB) in a high biomass forest, with an error of only 10% at 1.5-ha resolution. However, the degree to which this TomoSAR approach can be transferred from one site to another has not been assessed. We test this approach at the Nouragues site in central French Guiana (ca 100 km away from Paracou), and develop a method to retrieve the top-of-canopy height from TomoSAR. We found a high correlation between the backscatter signal and AGB in the upper canopy layer (i.e. 20–40 m), while lower layers only showed poor correlations. The relationship between AGB and TomoSAR data was found to be highly similar for forests at Nouragues and Paracou. Cross validation using training plots from Nouragues and validation plots from Paracou, and vice versa, gave an error of 16–18% of AGB using 1-ha plots. Finally, using a high-resolution LiDAR canopy model as a reference, we showed that TomoSAR has the potential to retrieve the top-of-canopy height with an error to within 2.5 m. Our analyses show that the TomoSAR-AGB retrieval method is accurate even in hilly and high-biomass forest areas and suggest that our approach may be generalizable to other study sites, having a canopy taller than 30 m. These results have strong implications for the tomographic phase of the BIOMASS spaceborne mission. [ABSTRACT FROM AUTHOR]

Dung beetles have widely been accepted as cost-effective indicator taxa for biodiversity assessment; thus, standard protocols have been created to examine their species richness and diversity in many habitats. However, the vast majority of studies adopt short-term sampling protocols; few studies have quantified sampling efficiency at longer time scales or tested the efficacy of species richness estimates. Here we present long- and short-term sampling data from two regions of French Guiana: the Nouragues Tropical Forest Research Station and Kaw Mountain. We examine species richness and diversity, and use these data to make suggestions for future biodiversity assessments of dung beetles using dung baited pitfall transects. Species richness estimates based on short-term samples strongly underestimate the actual species richness by approximately 40 %. Duration of trapping was found to be more important than the number of traps and length of transects; by setting a second transect (4-day sample period) in the same habitat of Nouragues, thereby increasing the sample duration, the number of species increased by 14 %. [ABSTRACT FROM AUTHOR]

Abstract: Lianas hold an important, but understudied, role in forest dynamics, however they are difficult to measure and detailed liana measurements are time consuming. Many researchers have therefore used an ordinal scale index, the crown occupancy index (COI), to describe the liana load carried by trees. Here we assess the overall effectiveness, in terms of accuracy, precision, repeatability and efficiency, of the COI in tropical forests. We relate the COI to more detailed liana measurements at the individual tree-level and site-level, comparing sites with different levels of liana infestation. Our results show (1) that the COI accurately measures individual tree and plot level liana loads, indicated by the strong correlations between the COI and the number and basal area of lianas. However, (2) as expected, the COI is only weakly related to the basal area of lianas rooted close to the tree, which is a proxy for competition for below-ground resources. The COI is also (3) an efficient measure of liana loads, as the input time needed for a COI survey is considerably less than that of a detailed liana survey. We also (4) found a high degree of repeatability in COI classification between observers. Additionally (5), the COI can be used to differentiate between sites in terms of their overall liana canopy competition (precision), but (6) may not be a precise indicator of the site-level mean basal area of lianas in tree crowns. [Copyright &y& Elsevier]

1. Leaf-litter ants represent a major component of biodiversity and are excellent bioindicators reflecting the health of terrestrial ecosystems. This study, conducted in an unspoiled forest near the Nouragues Research Station, represents the first inventory of leaf-litter ant diversity conducted in French Guiana, and so can be considered as the baseline dataset for ants in this country. 2. Ants were extracted from the leaf-litter using the Ants of the Leaf Litter Protocol, along an altitudinal gradient at four forest sites, including an inselberg. 3. A total of 196 ant species representing 46 genera distributed over eight subfamilies were collected. Four distinct communities spread over a gradient of diversity were thus identified: the liana forest was the most species-rich (140 species) followed by the forested plateau (102 species), the transition forest (87 species) and the forest at the top of the inselberg (71 species). 4. The discovery of species new to science plus several species recorded for the first time in French Guiana, coupled with the particular context of this area, suggests that the Nouragues Research Station might represent a centre of endemism. Once completed, this leaf-litter ant dataset will contribute greatly to the knowledge of ant biodiversity in French Guiana, and has the potential to progressively become an indispensable tool for country-wide conservation planning programmes. [ABSTRACT FROM AUTHOR]

Abstract: Tank-bromeliads are discrete habitats which contain distinct aquatic communities, and which commonly occur in the neotropics. Because they span a broad range of ecological gradients in terms of habitat structure and amount of resources, researchers study the associations between the biodiversity of communities and these gradients in rainforests, where the very high species richness and densities within other continuous habitats makes it difficult to quantify animal communities. We analysed the diversity of aquatic insect communities in relation to different tank-bromeliad species in a primary rainforest (French Guiana) using artificial intelligence and complex optimization techniques to classify communities and model their determinants. First, the self-organizing map (neural network) was used to classify 158 bromeliads according to the quantitative structure of the insect communities. Catopsis berteroniana and Guzmania lingulata formed separate clusters of plants on the virtual map, while Vriesea splendens, Vriesea pleiosticha and Aechmea melinonii were grouped together in the remaining clusters. Some insect taxa occurred in all bromeliads, while other taxa were specific to a given species. Second, general linear modelling allowed us to specify the influence of the bromeliad species; water volume and volume of fine particulate organic matter inside of the tank; elevation above the ground; and sampling site on taxonomic richness and insect abundance. The number of taxa and individuals per plant increased with greater water volume, but the slope of the relationships depended on the bromeliad species. The significant influence of bromeliad species suggested that at similar water volumes different plant species had different taxon richness and insect abundance. Greater amounts of fine particulate organic matter were detrimental to community diversity in the tanks, probably because they decreased available space by clogging it and/or affected oxygen concentrations. The influence of tank-bromeliad species on the aquatic insect community was primarily related to their physical (and probably chemical) features rather than to species-specific associations sensu stricto. The classification of bromeliads with respect to animal species is likely to provide referential schemes for those biodiversity patterns to be expected under certain conditions, and may help to target model communities for subsequent experimental research. [Copyright &y& Elsevier]

Spatial and temporal variation in seedling dynamics was assessed using records of community-wide seedling demography collected with identical monitoring methods at four tropical lowland forests in Panama, Malaysia, Ecuador and French Guiana for periods of between 3 and 10 y. At each site, the fates of between 8617 and 391 777 seedlings were followed through annual censuses of the 370–1008 1-m2 seedling plots. Within-site spatial and inter-annual variation in density, recruitment, growth and mortality was compared with among-site variability using Bayesian hierarchical modelling to determine the generality of each site's patterns and potential for meaningful comparisons among sites. The Malaysian forest, which experiences community-wide masting, was the most variable in both seedling density and recruitment. However, density varied year-to-year at all sites (CVamong years at site = 8–43%), driven largely by high variability in recruitment rates (CV = 40–117%). At all sites, recruitment was more variable than mortality (CV = 5–64%) or growth (CV = 12–51%). Increases in mortality rates lagged 1 y behind large recruitment events. Within-site spatial variation and inter-annual differences were greater than differences among site averages in all rates, emphasizing the value of long-term comparative studies when generalizing how spatial and temporal variation drive patterns of recruitment in tropical forests. [ABSTRACT FROM PUBLISHER]

Copyright of Biotropica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Biotropica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)