Abstract: The tank bromeliads Aechmea aquilega (Salisb.) and Catopsis berteroniana (Schultes f.) coexist on a sun-exposed Neotropical inselberg in French Guiana, where they permit conspicuous freshwater pools to form that differ in size, complexity and detritus content. We sampled the algal communities (both eukaryotic and cyanobacterial taxa, including colourless forms) inhabiting either A. aquilega (n = 31) or C. berteroniana (n = 30) and examined differences in community composition and biomass patterns in relation to several biotic and abiotic variables. Chlorella sp. and Bumilleriopsis sp. were the most common taxa and dominated the algal biomass in A. aquilega and C. berteroniana, respectively. Using a redundancy analysis, we found that water volume, habitat complexity and the density of phagotrophic protozoa and collector-gatherer invertebrates were the main factors explaining the distribution of the algal taxa among the samples. Hierarchical clustering procedures based on abundance and presence/absence data clearly segregated the samples according to bromeliad species, revealing that the algal communities in the smaller bromeliad species were not a subset of the communities found in the larger bromeliad species. We conclude that, even though two coexisting tank bromeliad populations create adjacent aquatic habitats, each population hosts a distinct algal community. Hence, bromeliad diversity is thought to promote the local diversity of freshwater algae in the Neotropics. © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands.

Abstract: The duration of the dry seasons in south-eastern Amazonia is expected to increase. Little is known of how freshwater assemblages respond to drought in the humid rainforests and of the extent to which they resist the absence of rainfall before the collapse of the system. We manipulated rainshelters over tank-forming bromeliads (i.e. the interlocking leaf axils of these plants form wells that collect rainwater) to simulate an exceptionally long dry period (49 days, compared with a 10-year mean ± SD annual maximum number of 17 ± 5.3 days without rainfall at the study site) and then a rewetting period. By sampling weekly over 3 months, we followed the dynamics of the representation of abundance-weighted traits in invertebrate assemblages in these treatment plants and in a control group. The functional structure of assemblages was drought resistant until the water volume in the bromeliad pools dropped by 90%, when there was a sudden shift in the functional trait structure due to the loss of most populations except the drought-resistant culicids. Traits related to life history, body size and preferred food showed significant responses to drought. There was a convergence in the functional traits of species surviving in dry plants, strengthening the idea that environmental filtering, rather than stochasticity, determines the functional trajectory of aquatic assemblages during drought. At the end of the dry period, samples of the detritus potentially containing drought-resistant eggs/cysts (and eventually live larvae) were taken from the dry plants and rewetted in the laboratory, allowing us to distinguish resistant species from those requiring recolonisation via subsequent oviposition by adults from elsewhere. Patches of water-filled bromeliads persisting in the area provided the most important pool of colonists, and communities returned to the pre-disturbance state within 1-2 weeks of rewetting. Our results suggest that the functional trait structure of invertebrate assemblages in bromeliads could remain stable under scenarios of precipitation change that would triple the duration of current dry periods at a local scale. Future experiments should evaluate how environmental factors might alter the tipping point between resistance to drought and a collapse in ecosystem processes. © 2015 John Wiley & Sons Ltd.

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: Differential growth response to light level is widely accepted as a potential mechanism for maintaining tree species richness in tropical forests. The position of tree species in the hierarchy of the canopy is considered an important indicator of species light capture and growth strategy. Paradoxically, the relative importance of species identity and competition for light in determining individual tree growth is poorly documented at the adult stage. In this study, we used a hierarchical Bayesian model to quantify the overall importance of species identity, light and belowground competition as determinants of tree growth in French Guiana tropical forest. Light competitive status is assessed by a crown exposure score and below ground competition is estimated from local crowding. We examined species sensitivity to both types of competition in relation to adult stature. Our results are based on annual diameter increments of more than 13,510 stems from 282 species monitored over 10years. Mean annual growth rate was 0.11cmy-1 with species identity explaining 35% of the individual variation in growth rate. Crown exposure and local crowding explained 3.5% and 2.4% of the variation in growth rate, respectively. Predicted changes in growth rate as crown exposure (resp. local crowding) index changed from lower to upper interquartile level was 0.03cmy-1 (resp. 0.02cmy-1). Species sensitivity to crown exposure and to local crowding were positively correlated (i) with predicted growth rate at high-light standardized conditions and (ii) with adult stature.This vertical niche partitioning is invoked to explain the limited contribution made by level of light competition for predicting individual tropical tree growth as the community-level response is dominated by the abundance of small-statured species with low sensitivity to light level.Light appears to drive the stem growth rate of tropical trees through species differentiation more than through individual tree growth limitation. This vertical stratification complements the previously reported regeneration niche and together these provide evidence for light niche partitioning in the three-dimensional space of tropical forests. © 2014 Elsevier B.V.

Abstract: In the study, we developed new markers for phylogenetic relationships and intraspecies differentiation in Coffea. Nana and Divo, two novel Ty1-copia LTR-retrotransposon families, were isolated through C. canephora BAC clone sequencing. Nana- and Divo-based markers were used to test their: (1) ability to resolve recent phylogenetic relationships; (2) efficiency in detecting intra-species differentiation. Sequence-specific amplification polymorphism (SSAP), retrotransposon-microsatellite amplified polymorphism (REMAP) and retrotransposon-based insertion polymorphism (RBIP) approaches were applied to 182 accessions (31 Coffea species and one Psilanthus accession). Nana- and Divo-based markers revealed contrasted transpositional histories. At the BAC clone locus, RBIP results on C. canephora demonstrated that Nana insertion took place prior to C. canephora differentiation, while Divo insertion occurred after differentiation. Combined SSAP and REMAP data showed that Nana could resolve Coffea lineages, while Divo was efficient at a lower taxonomic level. The combined results indicated that the retrotransposon-based markers were useful in highlighting Coffea genetic diversity and the chronological pattern of speciation/differentiation events. Ongoing complete sequencing of the C. canephora genome will soon enable exhaustive identification of LTR-RTN families, as well as more precise in-depth analyses on contributions to genome size variation and Coffea evolution. © 2011 Springer-Verlag.