Abstract: P>Cross-species analyses of plant functional traits have shed light on factors contributing to differences in performance and distribution, but to date most studies have focused on either leaves or stems. We extend these tissue-specific analyses of functional strategy towards a whole-plant approach by integrating data on functional traits for 13 448 leaves and wood tissues from 4672 trees representing 668 species of Neotropical trees. Strong correlations amongst traits previously defined as the leaf economics spectrum reflect a tradeoff between investments in productive leaves with rapid turnover vs. costly physical leaf structure with a long revenue stream. A second axis of variation, the 'stem economics spectrum', defines a similar tradeoff at the stem level: dense wood vs. high wood water content and thick bark. Most importantly, these two axes are orthogonal, suggesting that tradeoffs operate independently at the leaf and at the stem levels. By simplifying the multivariate ecological strategies of tropical trees into positions along these two spectra, our results provide a basis to improve global vegetation models predicting responses of tropical forests to global change.

Abstract: This article documents the addition of 205 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Bagassa guianensis, Bulweria bulwerii, Camelus bactrianus, Chaenogobius annularis, Creontiades dilutus, Diachasmimorpha tryoni, Dioscorea alata, Euhrychiopsis lecontei, Gmelina arborea, Haliotis discus hannai, Hirtella physophora, Melanaphis sacchari, Munida isos, Thaumastocoris peregrinus and Tuberolachnus salignus. These loci were cross-tested on the following species: Halobaena caerulea, Procellaria aequinoctialis, Oceanodroma monteiroi, Camelus ferus, Creontiades pacificus, Dioscorea rotundata, Dioscorea praehensilis, Dioscorea abyssinica, Dioscorea nummularia, Dioscorea transversa, Dioscorea esculenta, Dioscorea pentaphylla, Dioscorea trifida, Hirtella bicornis, Hirtella glandulosa, Licania alba, Licania canescens, Licania membranaceae, Couepia guianensis and 7 undescribed Thaumastocoris species.

Abstract: In order to explain the durability of the Moraceae plant family, phytochemistry of Bagassa guianensis was performed. Ethyl acetate extract was obtained from the heartwood and 18 secondary metabolites were isolated, including 6 moracins [6-O-methyl-moracin M, 6-O-methyl-moracin N and moracin Z; previously identified: moracin M, moracin N and moracin P], 8 stilbenoids [presently identified: (-)-epialboctalol and arachidin 4; previously identified: alboctalol, trans-resveratrol, arachidin 2, trans-oxyresveratrol and artogomezianol], 3 previously identified flavonoids, steppogenin, katuranin and dihydromorin, beta-sitosterol and resorcinol. Previous studies suggest that stilbenoids are responsible for the natural durability of wood. Our study has determined that B. guianensis is closely related to Morus sp. in phylogeny and should be included in the Moreae sensu stricto tribe of the Moraceae family. (C) 2010 Elsevier Ltd. All rights reserved.

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.