Abstract: Irradiance elicits a large plasticity in leaf traits, but little is known about the modulation of this plasticity by ontogeny. Interactive effects of relative irradiance and ontogeny were assessed on leaf traits for two tropical rainforest tree species: Dicorynia guianensis Amshoff and Tachigali melinonii (Harms) Barneby (Fabaceae, Caesalpinioideae). Eleven morphological and physiological leaf traits, relative to photosynthetic performance, were measured on saplings at three different architectural development stages (ASD 1, 2 and 3) and used to derive composite traits like photosynthetic N-use efficiency. Measurements were made along a natural irradiance gradient. The effect of ASD was very visible and differed between the two species. For Dicorynia guianensis, only leaf mass-per-area (LMA) significantly increased with ASDs whereas for Tachigali melinonii, almost all traits were affected by ASD: LMA, leaf N content and photosynthetic capacity increased from ASD 1 to ASD 3. Photosynthetic N-use-efficiency was not affected by ASD in any species. Leaf traits were severely modulated by irradiance, whereas the degree of plasticity was very similar among ASDs. Only few interactions were detected between irradiance and ASD, for leaf thickness, carbon content, and the ratio Chl/N in T. melinonii and for photosynthetic capacity in D. guianensis. We conclude that ontogenic development and irradiance-elicited plasticity modulated leaf traits, with almost no interaction, i.e., the degree of irradiance-elicited plasticity was stable across development stages and independent of ontogeny in these two species, at least in the early stages of development assessed here.

Abstract: Theory suggests that spatial structuring should select for intermediate levels of virulence in parasites, but empirical tests are rare and have never been conducted with castration (sterilizing) parasites. To test this theory in a natural landscape, we construct a spatially explicit model of the symbiosis between the ant-plant Cordia nodosa and its two, protecting ant symbionts, Allomerus and Azteca. Allomerus is also a castration parasite, preventing fruiting to increase colony fecundity. Limiting the dispersal of Allomerus and host plant selects for intermediate castration virulence. Increasing the frequency of the mutualist, Azteca, selects for higher castration virulence in Allomerus, because seeds from Azteca-inhabited plants are a public good that Allomerus exploits. These results are consistent with field observations and, to our knowledge, provide the first empirical evidence supporting the hypothesis that spatial structure can reduce castration virulence and the first such evidence in a natural landscape for either mortality or castration virulence.

Abstract: Tree species-rich tropical rainforests are characterized by a highly variable quality of leaf litter input to the soil at small spatial scales. This diverse plant litter is a major source of energy and nutrients for soil microorganisms, particularly in rainforests developed on old and nutrient-impoverished soils. Here we tested the hypothesis that the variability in leaf litter quality produced by a highly diverse tree community determines the spatial variability of the microbial respiration process in the underlying soil. We analyzed a total of 225 litter-soil pairs from an undisturbed Amazonian rainforest in French Guiana using a hierarchical sampling design. The microbial respiration process was assessed using substrate-induced respiration (SIR) and compared to a wide range of quality parameters of the associated litter layer (litter nutrients, carbon forms, stoichiometry, litter mass and pH). The results show that the variability of both litter quality and SIR rates was more important at large than at small scales. SIR rates varied between 1.1 and 4.0 μg h(-1) and were significantly correlated with litter layer quality (up to 50% of the variability explained by the best mixed linear model). Total litter P content was the individual most important factor explaining the observed spatial variation in soil SIR, with higher rates associated to high litter P. SIR rates also correlated positively with total litter N content and with increasing proportions of labile C compounds. However, contrary to our expectation, SIR rates were not related to litter stoichiometry. These data suggest that in the studied Amazonian rainforest, tree canopy composition is an important driver of the microbial respiration process via leaf litter fall, resulting in potentially strong plant-soil feedbacks. (C) 2011 Elsevier Ltd. All rights reserved.

Abstract: P>1. Relationships between tropical rain forest biomass and environmental factors have been determined at regional scales, e.g. the Amazon Basin, but the reasons for the high variability in forest biomass at local scales are poorly understood. Interactions between topography, soil properties, tree growth and mortality rates, and treefalls are a likely reason for this variability. 2. We used repeated measurements of permanent plots in lowland rain forest in French Guiana to evaluate these relationships. The plots sampled topographic gradients from hilltops to slopes to bottomlands, with accompanying variation in soil waterlogging along these gradients. Biomass was calculated for > 175 tree species in the plots, along with biomass productivity and recruitment rates. Mortality was determined as standing dead and treefalls. 3. Treefall rates were twice as high in bottomlands as on hilltops, and tree recruitment rates, radial growth rates and the abundance of light-demanding tree species were also higher. 4. In the bottomlands, the mean wood density was 10% lower than on hilltops, the basal area 29% lower and the height:diameter ratio of trees was lower, collectively resulting in a total woody biomass that was 43% lower in bottomlands than on hilltops. 5. Biomass productivity was 9% lower in bottomlands than on hilltops, even though soil Olsen P concentrations were higher in bottomlands. 6. Synthesis. Along a topographic gradient from hilltops to bottomlands there were higher rates of treefall, which decreased the stand basal area and favoured lower allocation to height growth and recruitment of light-demanding species with low wood density. The resultant large variation in tree biomass along the gradient shows the importance of determining site characteristics and including these characteristics when scaling up biomass estimates from stand to local or regional scales.

Abstract: Modelling the local density of tropical saplings can provide insights into the ecological processes that drive species regeneration and thereby help predict population recovery after disturbance. Yet, few studies have addressed the challenging issues in autocorrelation and zero-inflation of local density. This paper presents Hierarchical Bayesian Modelling (HBM) of sapling density that includes these two features. Special attention is devoted to variable selection, model estimation and comparison. We developed a Zero-Inflated Poisson (ZIP) model with a latent correlated spatial structure and compared it with non-spatial ZIP and Poisson models that were either autocorrelated (Spatial Generalized Linear Mixed, SGLM) or not (generalized linear models, GLM). In our spatial models, local density autocorrelation was modeled by a Conditional Auto-Regressive (CAR) process. 13 explicative variables described ecological conditions with respect to topography, disturbance, stand structure and intraspecific processes. Models were applied to six tropical tree species with differing biological attributes: Oxandra asbeckii, Eperua falcata, Eperua grandiflora, Dicorynia guianensis, Qualea rosea, and Tachigali melinonii. We built species-specific models using a simple method of variable selection based on a latent binary indicator. Our spatial models showed a close correlation between observed and estimated densities with site spatial structure being correctly reproduced. By contrast, the non-spatial models showed poor fits. Variable selection highlighted species-specific requirements and susceptibility to local conditions. Model comparison overall showed that the SGLM was the most accurate explanatory and predictive model. Surprisingly, zero-inflated models performed less well. Although the SZIP model was relevant with respect to data distribution, and more flexible with respect to response curves, its model complexity caused marked variability in parameter estimates. In the SUM, the spatial process alone accounted for zero-inflation in the data. A refinement of the hypotheses employed at the process level could compensate for distribution flaws at the data level. This study emphasized the importance of the HBM framework in improving the modelling of density-environment relationships. (C) 2008 Elsevier B.V. All rights reserved.