Abstract: Characterisation of forest structure is a major stake for forestry, species conservation, carbon stock estimates and many forest ecology and management issues. At large scale natural forest structure tends to vary according to climate and geomorphomology (Paget, 1999; Steege et al., 2006) while soil characteristics (and notably water regime) and syMgenetic stage add some finer scale variation (Oldeman, 1989; Sabatier et al., 1997). Forest structure characterisation traditionally relies on field-based collection of individual tree dimensions such as stem diameter and stem height sampled across tracks of forest (Hall et al., 1998). However, such field intensive methods are costly, and of low accuracy regarding measures of tree heights. Airborne light detection and ranging (LiDAR) technology provides horizontal and vertical Information at high spatial resolutions and vertical accuracies (Lim et al., 2003; Hyyppä et al., 2004). It has the potential for gathering vegetation structure data over large areas rapidly at moderate cost and hence is of particular relevance for poorly sampled, difficult to access and largely unexplored tropical rainforests. In this study we examined the ability of airborne LiDAR to detect spatial changes in the structure of dense tropical rain forest and we probed this remote sensing approach against local statistics derived from stem diameters (i.e. classical field data information) mapped across a large track of forest at a long term experimental site in French Guyana. The large variability in forest structure occurring at the experimental site is du to natural variation of the soil cover (and notably drainage properties) combined with various logging intensities applied 15 years before the LiDAR data were acquired. On this basis ten different forest types were identified at the site (figure 1 and 3). Various stem based statistics were computed for a series of meshes with cells ranging from 30 by 30 m plots to 250 by 250 m plots. These statistics included basal area, stem density, quadratic mean diameter, and diameter distribution percentiles. Similarly local statistics were extracted either from the Canopy Height Model (e.g. median height, mean height, standard height deviation, height coefficient of variation, height percentiles, frequency of hits below 5 m above ground level). Additionally a wetness index (Böhner et al., 2002) was computed at each node of a 5 by 5 m grid from the Digital Terrain Model also extracted from the LiDAR data set. We used both types of cell statistics to discriminate the various forest types. Comparison between the two approaches for a range of spatial resolution is available from in table 1. Results indicate that LiDAR based statistics are essentially as powerful as field based statistics to discriminate forest types at coarse scale. This reflects the very strong correlation between the CHM and the field based stem diameter data. For example (figure 5) the Pearson correlation coefficient between median height and quadratic mean diameter for cells of 125 by 125 m is 0.945 (n=0.72). When a finer resolution is required however as for the detection of seasonally flooded bottomland forest along thalwegs, then LiDAR technology proves more efficient than field based inventories as it combines information from the DTM and the CHM. The wetness index alone correctly retrieves about 2 thirds of the seasonally flooded areas. All in all, discriminant analysis performance of the LiDAR derived information approaches 80% when classifying forests cover at the finest scale of 5 by 5m into 10 different types and reaches 87% when a coarser classification Into 6 forest types is considered (figure 4).

Abstract: Most strains of the widespread endosymbiotic bacterium Wolbachia pipientis are benign or behave as reproductive parasites. The pathogenic strain wMelPop is a striking exception, however: it overreplicates in its insect hosts and causes severe life shortening. The mechanism of this pathogenesis is currently unknown. We have sequenced the genomes of three variants of wMelPop and of the closely related nonpathogenic strain wMelCS. We show that the genomes of wMelCS and wMelPop appear to be identical in the nonrepeat regions of the genome and differ detectably only by the triplication of a 19-kb region that is unlikely to be associated with life shortening, demonstrating that dramatic differences in the host phenotype caused by this endosymbiont may be the result of only minor genetic changes. We also compare the genomes of the original wMelPop strain from Drosophila melanogaster and two sequentialderivatives, wMelPop-CLA and wMelPop-PGYP. To develop wMelPop as a novel biocontrol agent, it was first transinfected into and passaged in mosquito cell lines for approximately 3.5 years, generating wMelPop-CLA. This cell line-passaged strain was then transinfected into Aedesaegypti mosquitoes, creating wMelPop-PGYP,which wassequenced after 4yearsin the insecthost. We observe a rapid burst of genomic changes during cell line passaging, but no further mutations were detected after transinfection into mosquitoes, indicating either that host preadaptation had occurred in cell lines, that cell lines are a more selectively permissive environment than animal hosts, or both. Our results provide valuable data on the rates of genomic and phenotypic change in Wolbachia associated with host shifts over short time scales. © The Author(s) 2013. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Abstract: Tropical canopies are complex, with multiple canopy layers and pronounced gap dynamics contributing to their high species diversity and productivity. An important reason for this complexity is the large variation in shade tolerance among different tree species. At present, we lack a clear understanding of which plant traits control this variation, e.g., regarding the relative contributions of whole-plant versus leaf traits or structural versus physiological traits. We investigated a broad range of traits in six tropical montane rainforest tree species with different degrees of shade tolerance, grown under three different radiation regimes (under the open sky or beneath sparse or dense canopies). The two distinct shade-tolerant species had higher fractional biomass in leaves and branches while shade-intolerant species invested more into stems, and these differences were greater under low radiation. Leaf respiration and photosynthetic light compensation point did not vary with species shade tolerance, regardless of radiation regime. Leaf temperatures in open plots were markedly higher in shade-tolerant species due to their low transpiration rates and large leaf sizes. Our results suggest that interspecific variation in shade tolerance of tropical montane trees is controlled by species differences in whole-plant biomass allocation strategy rather than by difference in physiological leaf traits determining leaf carbon balance at low radiation. © The Author(s) 2019. Published by Oxford University Press.

Abstract: Whole genome sequencing is helping generate robust phylogenetic hypotheses for a range of taxonomic groups that were previously recalcitrant to classical molecular phylogenetic approaches. As a case study, we performed a shallow shotgun sequencing of eight species in the tropical tree family Chrysobalanaceae to retrieve large fragments of high-copy number DNA regions and test the potential of these regions for phylogeny reconstruction. We were able to assemble the nuclear ribosomal cluster (nrDNA), the complete plastid genome (ptDNA) and a large fraction of the mitochondrial genome (mtDNA) with approximately 1000×, 450× and 120× sequencing depth respectively. The phylogenetic tree obtained with ptDNA resolved five of the seven internal nodes. In contrast, the tree obtained with mtDNA and nrDNA data were largely unresolved. This study demonstrates that genome skimming is a cost-effective approach and shows potential in plant molecular systematics within Chrysobalanaceae and other under-studied groups. © 2014 John Wiley & Sons Ltd.

Abstract: High-throughput sequencing of amplicons from environmental DNA samples permits rapid, standardized and comprehensive biodiversity assessments. However, retrieving and interpreting the structure of such data sets requires efficient methods for dimensionality reduction. Latent Dirichlet Allocation (LDA) can be used to decompose environmental DNA samples into overlapping assemblages of co-occurring taxa. It is a flexible model-based method adapted to uneven sample sizes and to large and sparse data sets. Here, we compare LDA performance on abundance and occurrence data, and we quantify the robustness of the LDA decomposition by measuring its stability with respect to the algorithm's initialization. We then apply LDA to a survey of 1,131 soil DNA samples that were collected in a 12-ha plot of primary tropical forest and amplified using standard primers for bacteria, protists, fungi and metazoans. The analysis reveals that bacteria, protists and fungi exhibit a strong spatial structure, which matches the topographical features of the plot, while metazoans do not, confirming that microbial diversity is primarily controlled by environmental variation at the studied scale. We conclude that LDA is a sensitive, robust and computationally efficient method to detect and interpret the structure of large DNA-based biodiversity data sets. We finally discuss the possible future applications of this approach for the study of biodiversity. © 2019 John Wiley & Sons Ltd