Abstract: Rosewood (Aniba rosaeodora) essential oil is a valuable ingredient that has long been used in the perfume and cosmetic industries. The main rosewood timber quality parameters are its essential oil yield and quality. A hydrodistillation method has been developed for yield determination, but it is time consuming. Here we tested the applicability of near infrared (NIR) spectroscopy for determining essential oil yield directly from wood powder. Essential oil from 139 wood powders was extracted via hydrodistillation. The measurements were based on the ratio between the extracted essential oil mass and the oven-dried wood mass and were correlated with the wood powder NIR spectra. The calibration model statistical findings demonstrated that NIR could be a fast and feasible alternative method for selecting trees with a high essential oil yield potential. NIR-based predictions obtained in an independent validation set indicated a high correlation (r2e = 0.92) with laboratory essential oil yield measurements. This NIR model could help wood managers in selecting trees with a high essential oil yield potential and in developing sustainable rosewood management strategies. © IM Publications LLP 2016. All rights reserved.

Abstract: Two methods of N transfer between plants-by litter decomposition and root-to-root exchange-were examined in mixed plantations of N-fixing and non-fixing trees. Nitrogen transfers from decaying litters were measured by placing N-15-labelled litters from four actinorhizal tree species around shoots of containerized Prunus avium. Nitrogen transfers by root-to-root exchanges were measured after foliar NO3-N-15 fertilization of Alnus subcordata and Elaeagnus angustifolia growing in containers in association with P. avium. During the first 2 years of litter decomposition, from 5-20% of the N, depending on the litter identity, was released and taken up by P. avium. N availability in the different litters was strongly correlated with the amount of water-soluble N, which was highest in leaves of E. angustifolia. In the association between fixing and non-fixing plants, 7.5% of the A. subcordata N and 25% of E. angustifolia N was transferred to P. avium by root exchange. These results showed that the magnitude of N transfers by root exchange depended on the associated N-2-fixing species. Among the species investigated, E. angustifolia displayed the highest capacity for exudating N from roots as well as for releasing N from litters. These qualities make this tree a promising species for enhancing wood yields in mixed stands.

Abstract: Estimates of extinction risk for Amazonian plant and animal species are rare and not often incorporated into land-use policy and conservation planning. We overlay spatial distribution models with historical and projected deforestation to show that at least 36% and up to 57% of all Amazonian tree species are likely to qualify as globally threatened under International Union for Conservation of Nature (IUCN) Red List criteria. If confirmed, these results would increase the number of threatened plant species on Earth by 22%. We show that the trends observed in Amazonia apply to trees throughout the tropics, and we predict that most of the world’s >40,000 tropical tree species now qualify as globally threatened. A gap analysis suggests that existing Amazonian protected areas and indigenous territories will protect viable populations of most threatened species if these areas suffer no further degradation, highlighting the key roles that protected areas, indigenous peoples, and improved governance can play in preventing large-scale extinctions in the tropics in this century.

Abstract: We propose new methods for evaluating the spatial distribution of firms. To assess whether firms are concentrated or dispersed, economists have traditionally used indices that analyse the heterogeneity of a spatial structure at a single geographic level. We introduce distance-based methods, Besag's L function (derived from Ripley's K function) and Diggle and Chetwynd's D function to describe simultaneously spatial distribution at different geographical scales. Our empirical applications consider the distribution of French manufacturing firms in the Paris area and in France generally. For some geographic levels, results show significant concentration or dispersion of firms according to their sector of activity.

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.