Abstract: Seasonal variations in environmental conditions influence the functioning of the whole ecosystem of tropical rain forests, but as yet little is known about how such variations directly influence the leaf gas exchange and transpiration of individual canopy tree species. We examined the influence of seasonal variations in relative extractable water in the upper soil layers on predawn leaf water potential, saturated net photosynthesis, leaf dark respiration, stomatal conductance, and tree transpiration of 13 tropical rain forest canopy trees (eight species) over 2 yr in French Guiana. The canopies were accessed by climbing ropes attached to the trees and to a tower. Our results indicate that a small proportion of the studied trees were unaffected by soil water depletion during seasonal dry periods, probably thanks to efficient deep root systems. The trees showing decreased tree water status (i.e., predawn leaf water potential) displayed a wide range of leaf gas exchange responses. Some trees strongly regulated photosynthesis and transpiration when relative extractable water decreased drastically. In contrast, other trees showed little variation, thus indicating good adaptation to soil drought conditions. These results have important applications to modeling approaches: indeed, precise evaluation and grouping of these response patterns are required before any tree-based functional models can efficiently describe the response of tropical rain forest ecosystems to future changes in environmental conditions. © 2012 by The Association for Tropical Biology and Conservation.

Abstract: Unveiling the genetic basis of local adaptation to environmental variation is a major goal in molecular ecology. In rugged landscapes characterized by environmental mosaics, living populations and communities can experience steep ecological gradients over very short geographical distances. In lowland tropical forests, interspecific divergence in edaphic specialization (for seasonally flooded bottomlands and seasonally dry terra firme soils) has been proven by ecological studies on adaptive traits. Some species are nevertheless capable of covering the entire span of the gradient; intraspecific variation for adaptation to contrasting conditions may explain the distribution of such ecological generalists. We investigated whether local divergence happens at small spatial scales in two stands of Eperua falcata (Fabaceae), a widespread tree species of the Guiana Shield. We investigated Single Nucleotide Polymorphisms (SNP) and sequence divergence as well as spatial genetic structure (SGS) at four genes putatively involved in stress response and three genes with unknown function. Significant genetic differentiation was observed among sub-populations within stands, and eight SNP loci showed patterns compatible with disruptive selection. SGS analysis showed genetic turnover along the gradients at three loci, and at least one haplotype was found to be in repulsion with one habitat. Taken together, these results suggest genetic differentiation at small spatial scale in spite of gene flow. We hypothesize that heterogeneous environments may cause molecular divergence, possibly associated to local adaptation in E. falcata. © 2012 European Society For Evolutionary Biology.

Abstract: Reliable above-ground biomass (AGB) estimates are required for studies of carbon fluxes and stocks. However, there is a huge lack of knowledge concerning the precision of AGB estimates and the sources of this uncertainty. At the tree level, the tree height is predicted using the tree diameter at breast height (DBH) and a height sub-model. The wood-specific gravity (WSG) is predicted with taxonomic information and a WSG sub-model. The tree mass is predicted using the predicted height, the predicted WSG and the biomass sub-model. Our models were inferred with Bayesian methods and the uncertainty propagated with a Monte Carlo scheme. The uncertainties in the predictions of tree height, tree WSG and tree mass were neglected sequentially to quantify their contributions to the uncertainty in AGB. The study was conducted in French Guiana where long-term research on forest ecosystems provided an outstanding data collection on tree height, tree dynamics, tree mass and species WSG. We found that the uncertainty in the AGB estimates was found to derive primarily from the biomass sub-model. The models used to predict the tree heights and WSG contributed negligible uncertainty to the final estimate. Considering our results, a poor knowledge of WSG and the height-diameter relationship does not increase the uncertainty in AGB estimates. However, it could lead to bias. Therefore, models and databases should be used with care. This study provides a methodological framework that can be broadly used by foresters and plant ecologist. It provides the accurate confidence intervals associated with forest AGB estimates made from inventory data. When estimating region-scale AGB values (through spatial interpolation, spatial modelling or satellite signal treatment), the uncertainty of the forest AGB value in the reference forest plots has to be taken in account. We believe that in the light of the Reducing Emissions from Deforestation and Degradation debate, our method is a crucial step in monitoring carbon stocks and their spatio-temporal evolution. © 2012 The Authors. Methods in Ecology and Evolution © 2012 British Ecological Society.

Abstract: Vegetation phenology is the study of the timing of seasonal events that are considered to be the result of adaptive responses to climate variations on short and long time scales. In the field of remote sensing of vegetation phenology, phenological metrics are derived from time series of optical data. For that purpose, considerable effort has been specifically focused on developing noise reduction and cloud-contaminated data removal techniques to improve the quality of remotely-sensed time series. Comparative studies between time series composed of satellite data acquired under clear and cloudy conditions and from radiometric data obtained with high accuracy from ground-based measurements constitute a direct and effective way to assess the operational use and limitations of remote sensing for predicting the main plant phenological events. In the present paper, we sought to explicitly evaluate the potential use of MODerate resolution Imaging Spectroradiometer (MODIS) remote sensing data for monitoring the seasonal dynamics of different types of vegetation cover that are representative of the major terrestrial biomes, including temperate deciduous forests, evergreen forests, African savannah, and crops. After cloud screening and filtering, we compared the temporal patterns and phenological metrics derived from in situ NDVI time series and from MODIS daily and 16-composite products. We also evaluated the effects of residual noise and the influence of data gaps in MODIS NDVI time series on the identification of the most relevant metrics for vegetation phenology monitoring. The results show that the inflexion points of a model fitted to a MODIS NDVI time series allow accurate estimates of the onset of greenness in the spring and the onset of yellowing in the autumn in deciduous forests (RMSE ≤ one week). Phenological metrics identical to those provided with the MODIS Global Vegetation Phenology product (MDC12Q2) are less robust to data gaps, and they can be subject to large biases of approximately two weeks or more during the autumn phenological transitions. In the evergreen forests, in situ NDVI time series describe the phenology with high fidelity despite small temporal changes in the canopy foliage. However, MODIS is unable to provide consistent phenological patterns. In crops and savannah, MODIS NDVI time series reproduce the general temporal patterns of phenology, but significant discrepancies appear between MODIS and ground-based NDVI time series during very localized periods of time depending on the weather conditions and spatial heterogeneity within the MODIS pixel. In the rainforest, the temporal pattern exhibited by a MODIS 16-day composite NDVI time series is more likely due to a pattern of noise in the NDVI data structure according to both rainy and dry seasons rather than to phenological changes. More investigations are needed, but in all cases, this result leads us to conclude that MODIS time series in tropical rainforests should be interpreted with great caution. © 2013 Elsevier Inc.