Abstract: Though the root biomass of tropical rainforest trees is concentrated in the upper soil layers, soil water uptake by deep roots has been shown to contribute to tree transpiration. A precise evaluation of the relationship between tree dimensions and depth of water uptake would be useful in tree-based modelling approaches designed to anticipate the response of tropical rainforest ecosystems to future changes in environmental conditions. We used an innovative dual-isotope labelling approach (deuterium in surface soil and oxygen at 120-cm depth) coupled with a modelling approach to investigate the role of tree dimensions in soil water uptake in a tropical rainforest exposed to seasonal drought. We studied 65 trees of varying diameter and height and with a wide range of predawn leaf water potential (Ψpd) values. We confirmed that about half of the studied trees relied on soil water below 100-cm depth during dry periods. Ψpd was negatively correlated with depth of water extraction and can be taken as a rough proxy of this depth. Some trees showed considerable plasticity in their depth of water uptake, exhibiting an efficient adaptive strategy for water and nutrient resource acquisition. We did not find a strong relationship between tree dimensions and depth of water uptake. While tall trees preferentially extract water from layers below 100-cm depth, shorter trees show broad variations in mean depth of water uptake. This precludes the use of tree dimensions to parameterize functional models. © 2013 Springer-Verlag Berlin Heidelberg.

Abstract: Although niche-based and stochastic processes, including dispersal limitation and demographic stochasticity, can each contribute to community assembly, it is difficult to quantify the relative importance of each process in natural vegetation. Here, we extend Shipley's maxent model (Community Assembly by Trait Selection, CATS) for the prediction of relative abundances to incorporate both trait-based filtering and dispersal limitation from the larger landscape and develop a statistical decomposition of the proportions of the total information content of relative abundances in local communities that are attributable to traitbased filtering, dispersal limitation, and demographic stochasticity. We apply the method to tree communities in a mature, species-rich, tropical forest in French Guiana at 1-, 0.25-and 0.04-ha scales. Trait data consisted of species' means of 17 functional traits measured over both the entire meta-community and separately in each of nine 1-ha plots. Trait means calculated separately for each site always gave better predictions. There was clear evidence of trait-based filtering at all spatial scales. Trait-based filtering was the most important process at the 1-ha scale (34%), whereas demographic stochasticity was the most important at smaller scales (37-53%). Dispersal limitation from the meta-community was less important and approximately constant across scales (∼9%), and there was also an unresolved association between site-specific traits and meta-community relative abundances. Our method allows one to quantify the relative importance of local niche-based and meta-community processes and demographic stochasticity during community assembly across spatial and temporal scales. © 2012 by the Ecological Society of America.

Abstract: Devil's gardens are one of the most remarkable mutualistic associations between ants and plants. Myrmelachista ants eliminate all vegetation from around their host plants, resulting in wide forest clearings which have intrigued scientists from the start. Despite their noticeability, here we report the discovery of devil's gardens in remote highland cloud forests of the Eastern Amazon, more than 2000 km away from their nearest known analogues in Western Amazonia. We describe the ecological characteristics of these gardens and consider what factors could have produced the geographic isolation of Eastern Amazonian devil's gardens. Three hypotheses are investigated: (1) the host plant distribution restricts the distribution of the mutualism, (2) the ecological tolerances of Myrmelachista explain the isolation, and (3) the devil's gardens of the Eastern Amazon constitute relicts from ancient forest refugia. The distribution of the possible associated myrmecophytes and previously described ecological ranges of devil's gardens cannot explain their ecological restriction to cloud forests in Eastern Amazonia, but our discovery is consistent with the biogeographic refuge hypothesis (i.e. highlands along the Amazon Basin constitute refugia for humid forests that spread during the Cenozoic). Our finding opens exciting perspectives for comparative studies of the origin, ecology and evolutionary history of this ant-plant mutualism. Copyright © Cambridge University Press 2016.

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.