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Amusant, N., Beauchene, J., Digeon, A., & Chaix, G. (2016). Essential oil yield in rosewood (Aniba rosaeodora Ducke): Initial application of rapid prediction by near infrared spectroscopy based on wood spectra. Journal of Near Infrared Spectroscopy, 24(6), 507–515.
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.
Keywords: Aniba rosaeodora; Calibration; Essential oil yield; Nir; Pls; Rosewood
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Petit, M., Denis, T., Rux, O., Richard-Hansen, C., & Berzins, R. (2018). Estimating jaguar (Panthera onca) density in a preserved coastal area of French Guiana. Mammalia, 82(2), 188–192.
Abstract: Knowledge of the jaguar population is needed in French Guiana that faces an increase of human-jaguar conflicts. We carried out a camera trap survey to assess jaguar local density and home range size in a preserved coastal area of French Guiana. We ran spatially explicit capture recapture (SECR) models. In our model, the scale parameter σ, that is linked to the home range size, was larger for males (σ=3.87±0.59 SE km) than for females (σ=2.33±0.30 SE km). The assessed jaguar density was 3.22±0.87 SE ind. 100 km â '2, which should be considered as an optimal density in a French Guiana coastal area.
Keywords: camera trapping; density; French Guiana; home range; Panthera onca; spatially explicit capture recapture
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Roggy, J. C., Moiroud, A., Lensi, R., & Domenach, A. M. (2004). Estimating N transfers between N-2-fixing actinorhizal species and the non-N-2-fixing Prunus avium under partially controlled conditions. Biol. Fertil. Soils, 39(5), 312–319.
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.
Keywords: actinorhizal trees; mixed culture; litter; N transfer by roots; N-15
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van Gorsel, E., Delpierre, N., Leuning, R., Black, A., Munger, J. W., Wofsy, S., et al. (2009). Estimating nocturnal ecosystem respiration from the vertical turbulent flux and change in storage of CO2. Agric. For. Meteorol., 149(11), 1919–1930.
Abstract: Micrometeorological measurements of night time ecosystem respiration can be systematically biased when stable atmospheric conditions lead to drainage flows associated with decoupling of air flow above and within plant canopies. The associated horizontal and vertical advective fluxes cannot be measured using instrumentation on the single towers typically used at micrometeorological sites. A common approach to minimize bias is to use a threshold in friction velocity, u*, to exclude periods when advection is assumed to be important, but this is problematic in situations when in-canopy flows are decoupled from the flow above. Using data from 25 flux stations in a wide variety of forest ecosystems globally, we examine the generality of a novel approach to estimating nocturnal respiration developed by van Gorsel et al. (van Gorsel, E., Leuning, R., Cleugh, H.A., Keith, H., Suni, T., 2007. Nocturnal carbon efflux: reconciliation of eddy covariance and chamber measurements using an alternative to the u*-threshold filtering technique. Tellus 59B, 397-403, Tellus, 59B, 307-403). The approach is based on the assumption that advection is small relative to the vertical turbulent flux (F-C) and change in storage (F-S) of CO2 in the few hours after sundown. The sum of F-C and F-S reach a maximum during this period which is used to derive a temperature response function for ecosystem respiration. Measured hourly soil temperatures are then used with this function to estimate respiration R-Rmax. The new approach yielded excellent agreement with (1) independent measurements using respiration chambers, (2) with estimates using ecosystem light-response curves of F-c + F-s extrapolated to zero light, R-LRC, and (3) with a detailed process-based forest ecosystem model, R-cast. At most sites respiration rates estimated using the u*-filter, R-ust, were smaller than R-Rmax, and R-LRC. Agreement of our approach with independent measurements indicates that R-Rmax, provides an excellent estimate of nighttime ecosystem respiration. (C) 2009 Elsevier B.V. All rights reserved.
Keywords: Ecosystem respiration; Micrometeorology; Advection; u-star correction; Eddy covariance; Chamber; Process-based modelling
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ter Steege, H., Pitman, N. C. A., Killeen, T. J., Laurance, W. F., Peres, C. A., Guevara, J. E., et al. (2015). Estimating the global conservation status of more than 15,000 Amazonian tree species. Science Advances, 1(10).
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.
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Guitet, S., Sabatier, D., Brunaux, O., Herault, B., Aubry-Kientz, M., Molino, J. - F., et al. (2014). Estimating tropical tree diversity indices from forestry surveys: A method to integrate taxonomic uncertainty. For. Ecol. Manage., 328, 270–281.
Abstract: Analyses of tree diversity and community composition in tropical rain forests are usually based either on general herbarium data or on a restricted number of botanical plots. Despite their high taxonomic accuracy, both types of data are difficult to extrapolate to landscape scales. Meanwhile, forestry surveys provide quantitative occurrence data on large areas, and are thus increasingly used for landscape-scale analyses of tree diversity. However, the reliability of these approaches has been challenged because of the ambiguity of the common (vernacular) names used by foresters and the complexity of tree taxonomy in those hyper-diverse communities.We developed and tested a novel approach to evaluate taxonomic reliability of forestry surveys and to propagate the resulting uncertainty in the estimates of several diversity indicators (alpha and beta entropy, Fisher-alpha and Sørensen similarity). Our approach is based on Monte-Carlo processes that simulate communities by taking into account the expected accuracy and reliability of common names. We tested this method in French Guiana, on 9 one-hectare plots (4279 trees – DBH. ≥. 10. cm) for which both common names and standardized taxonomic determinations were available. We then applied our method of community simulation on large forestry inventories (560. ha) at the landscape scale and compared the diversity indices obtained for 10 sites with those computed from precise botanical determination situated at the same localities.We found that taxonomic reliability of forestry inventories varied from 22% (species level) to 83% (family level) in this Amazonian region. Indices computed directly with raw forestry data resulted in incorrect values, except for Gini-Simpson beta-diversity. On the contrary, our correction method provides more accurate diversity estimates, highly correlated with botanical measurements, for almost all diversity indices at both regional and local scales. We obtained a robust ranking of sites consistent with those shown by botanical inventories.These results show that (i) forestry inventories represent a significant part of taxonomic information, (ii) the relative diversity of regional sites can be successfully ranked using forestry inventory data using our method and (iii) forestry inventories can valuably contribute to the detection of large-scale diversity patterns when biases are well-controlled and corrected.The tools we developed as R-functions are available in supplementary material and can be adapted with local parameters to be used for forest management and conservation issues in other regional contexts. © 2014 Elsevier B.V.
Keywords: Diversity; French guiana; Landscape scale; Monte-Carlo process; Rainforest; Tree community; Reliability; Surveys; Timber; Uncertainty analysis; Diversity; French Guiana; Landscape scale; Rainforest; Tree community; Forestry; estimation method; forest inventory; herbarium; landscape; numerical model; species diversity; taxonomy; uncertainty analysis; Forestry; Forests; Reliability; Surveys; French Guiana
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Marcon, E., & Puech, F. (2003). Evaluating the geographic concentration of industries using distance-based methods. J. Econ. Geogr., 3(4), 409–428.
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.
Keywords: agglomeration; clustering; geographic concentration; location of firms
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Maron, P. A., Schimann, H., Ranjard, L., Brothier, E., Domenach, A. M., Lensi, R., et al. (2006). Evaluation of quantitative and qualitative recovery of bacterial communities from different soil types by density gradient centrifugation. Eur. J. Soil Biol., 42(2), 65–73.
Abstract: Extracting and purifying a representative fraction of bacteria from soil is necessary for the application of many techniques of microbial ecology. Here the influence of different soil types on the quantitative and qualitative recovery of bacteria by soil grinding and Nycodenz density gradient centrifugation was investigated. Three soils presenting contrasted physicochemical characteristics were used for this study. For each soil, the total (AODC: acridine orange direct count) and culturable (cfa: colony-forming units) bacterial densities were measured in three distinct fractions: (i) the primary soil, (ii) the soil pellet (soil remaining after centrifugation), and (iii) the extracted cells. The automated-ribosomal intergenic spacer analysis (A-RISA) was used to characterize the community structure directly from the DNA extracted from each fraction. The physicochemical characteristics of soils were found to influence both the efficiency of bacterial cell recovery and the representativeness of the extracted cells in term of community structures between the different fractions. Surprisingly, the most representative extracted cells were obtained from the soil exhibiting the lowest efficiency of cell recovery. Our results demonstrated that quantitative and qualitative cell recovery using Nycodenz density gradient centrifugation are not necessarily related and could be differentially biased according to soil type. (c) 2006 Elsevier SAS. All rights reserved.
Keywords: bacterial community; soil; density gradient; DNA fingerprint
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Hmimina, G., Dufrêne, E., Pontailler, J. - Y., Delpierre, N., Aubinet, M., Caquet, B., et al. (2013). Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: An investigation using ground-based NDVI measurements. Remote Sensing of Environment, 132, 145–158.
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.
Keywords: Crops; Deciduous forests; Evergreen forests; Ground-based NDVI; Modis; Phenology
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Schimann, H., Joffre, R., Roggy, J. C., Lensi, R., & Domenach, A. M. (2007). Evaluation of the recovery of microbial functions during soil restoration using near-infrared spectroscopy. Appl. Soil Ecol., 37(3), 223–232.
Abstract: Microbial-based indicators, such as C and N contents or microbial functions involved in C and N cycles, are currently used to describe the status of soils in disturbed areas. Microbial functions are more accurate indicators but their measurement for studies at the ecosystem level remains problematical because of the huge spatial variability of these processes and, consequently, of the large number of soil samples which must be analyzed. Our goal was to test the capacity of near-infrared reflectance spectroscopy (NIRS) to predict respiration and denitrification but also carbon and nitrogen contents of soils submitted to various procedures of restoration. To achieve this objective, we took advantage of an experiment conducted on a reforestation system established after open-cast gold mining in French Guiana. In this experimental station, plantations of various ages and various soil textures were at our disposal. Our results showed that both plantations and soil texture had a strong impact on the recovery of soil functioning: carbon and nitrogen contents, respiration and denitrification increased with age of plantation and clay content. Calibrations were performed between spectral data and microbial-based indicators using partial least squares regression (PLS). The results showed that C and N contents were accurately predicted. Microbial functions were less precisely predicted with results more accurate on clayey soils than on sandy soils. In clayey soils, perturbed or restored soils and the year of plantation were discriminated very efficiently through principal component analyses of spectral signatures (over 80% of variance explained on the first two axes). Near-infrared spectroscopy may thus be extended to the prediction of functional soil parameters, but the capacity of this method must be strengthened by expending the databases with other soils in other contexts. The possibility of using NIRS provides many opportunities for understanding both the temporal dynamics and the spatial variability of the recovery of key microbial functions during soil restoration. (c) 2007 Elsevier B.V. All rights reserved.
Keywords: NIRS; microbial activities; respiration; denitrification; carbon; nitrogen; soil functioning; restoration
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