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Aix-en-Provence, France

Lebourgeois F.,Agro ParisTech | Rathgeber C.B.K.,French National Institute for Agricultural Research | Ulrich E.,Office National des Forets
Journal of Vegetation Science | Year: 2010

Questions: (1) How do extreme climatic events and climate variability influence radial growth of conifers (silver fir, Norway spruce, Scots pine)? (2) How do elevation and soil water capacity (SWC) modulate sensitivity to climate? Location: The sampled conifer stands are in France, in western lowland and mountain forests, at elevations from 400 to 1700 m, and an SWC from 50 to 190 mm. Methods: We established stand chronologies for total ring width, earlywood and latewood width for the 33 studied stands (985 trees in total). Responses to climate were analysed using pointer years and bootstrapped response functions. Principal component analysis was applied to pointer years and response function coefficients in order to elucidate the ecological structure of the studied stands. Results: Extreme winter frosts are responsible for greater growth reductions in silver fir than in Norway spruce, especially at the upper elevation, while Scots pine was the least sensitive species. Exceptional spring droughts caused a notable growth decrease, especially when local conditions were dry (altitude<1000 m and SWC<100 mm for silver fir, western lowlands for Scots pine). Earlywood of silver fir depended on previous September and November and current-year February temperature, after which current June and July water supply influenced latewood. Earlywood of Norway spruce was influenced by previous September temperature, after which current spring and summer droughts influenced both ring components. In Scots pine, earlywood and latewood depended on the current summer water balance. Local conditions mainly modulated latewood formation. Conclusions: If the climate becomes drier, low-elevation dry stands or trees growing in western lowlands may face problems, as their growth is highly dependent on soil moisture availability. © 2009 International Association for Vegetation Science. Source

Lebourgeois F.,Agro ParisTech | Lebourgeois F.,French National Institute for Agricultural Research | Gomez N.,Office National des Forets | Pinto P.,French National Institute for Agricultural Research | And 3 more authors.
Forest Ecology and Management | Year: 2013

In most dendroecological studies, climate-tree growth relationships are established for trees growing on pure stands. However, response to climate may be affected by inter-species interactions and local constraints, which beg the question of the effect of mixture on tree growth response under various ecological conditions. To assess these effects, climate-tree growth relationships of pure Abies alba stands were compared to those of three different mixtures: A. alba with Fagus sylvatica, with Picea abies and with both species. 151 stands (456 A. alba trees) were sampled in the Vosges mountains in north-eastern France under three contrasted climates, from low altitude and dry conditions (mean precipitation in July <85. mm and altitude <600. m) to high altitude and humid conditions (P July >115. mm and alt. <900. m). We sampled adult trees and homogeneous stand conditions to clearly assess differences in sensitivity to climate. Climate-tree growth relationships were evaluated from 12 A. alba chronologies (four mixtures. ×. three climatic conditions) through pointer years and response function analyses. Late previous summer conditions and current summer soil water deficit and temperature played a major role on A. alba growth. Results showed greater sensitivity to temperature at high elevation, and to summer drought at low altitude and under dry conditions. Mixture allowed maintaining a higher level of A. alba growth during extreme climatic events and reduced A. alba response to summer drought especially under the driest contexts. Different facilitation processes may explain mixture effects such as changes in rooting depth, water input by stemflow and rainfall interception. This differentiated functioning of mixed forests highlights their importance for adapting forest management to climate change. © 2013 Elsevier B.V. Source

Lebourgeois F.,Agro ParisTech | Lebourgeois F.,French National Institute for Agricultural Research | Merian P.,Agro ParisTech | Merian P.,French National Institute for Agricultural Research | And 3 more authors.
Trees - Structure and Function | Year: 2012

Temporal instability of climate signal in tree-ring width of the five dominant species (Pinus nigra, P. sylvestris, P. uncinata, Abies alba, Fagus sylvatica) growing under Mediterranean mountainous climate was studied over the last century (1910-2004). To disentangle the tree-climate-site complex, the effects of both soil water availability (SWA) (dry, mesic and humid sites) and altitude (from 430 to 1,690 m) were investigated on the response patterns. Responses to climate were analysed using bootstrapped correlation coefficients from 17 ring-width chronologies built from 293 trees sampled in 64 stands in South-Eastern France. Temporal analyses were performed considering forty-six 50-years intervals (from 1910-1959 to 1955-2004). May-June drought was the primary limiting factor. For P. sylvestris, summer precipitation also played a key role. F. sylvatica was the less responding species with no clear common pattern. Low SWA led to an increasing correlation with precipitation in May for P. nigra and A. alba. Precipitation from May to August prevailed on the driest conditions for P. sylvestris. Correlation analyses suggested that warm autumn or winter enhanced growth, except for F. sylvatica. For P. nigra, the importance of April temperature increased with increasing altitude. Temporal analyses revealed a stability of sensitivity for the highest contexts (P. uncinata and F. sylvatica). At lower altitudes, the correlation with minimum temperature in April increased while temperature more often exceeded the threshold of 0°C over the last decades. For precipitation, a decrease in the strength of correlation was observed without close relationships with local xericity. © 2011 Springer-Verlag. Source

Othmani A.,French National Center for Scientific Research | Lew Yan Voon L.F.C.,French National Center for Scientific Research | Stolz C.,French National Center for Scientific Research | Piboule A.,Office National des Forets
Pattern Recognition Letters | Year: 2013

Due to the increasing use of Terrestrial Laser Scanning (TLS) systems in the forestry domain for forest inventory, the development of software tools for the automatic measurement of forest inventory attributes from TLS data has become a major research field. Numerous research work on the measurement of attributes such as the localization of the trees, the Diameter at Breast Height (DBH), the height of the trees, and the volume of wood has been reported in the literature. However, to the best of our knowledge the problem of tree species recognition from TLS data has received very little attention from the scientific community. Most of the research work uses Airborne Laser Scanning (ALS) data and measures tree species attributes on large scales. In this paper we propose a method for individual tree species classification of five different species based on the analysis of the 3D geometric texture of the bark. The texture features are computed using a combination of the Complex Wavelet Transforms (CWT) and the Contourlet Transform (CT), and classification is done using the Random Forest (RF) classifier. The method has been tested using a dataset composed of 230 samples. The results obtained are very encouraging and promising. © 2013 Elsevier B.V. All rights reserved. Source

Vega C.,Institute National Of Linformation Geographique Et Forestiere | Renaud J.-P.,Office National des Forets | Durrieu S.,IRSTEA | Bouvier M.,IRSTEA
Remote Sensing of Environment | Year: 2016

We proposed a new area-based approach to process Lidar point clouds and develop new sets of metrics to improve models dedicated to predict forest parameters. First, we introduced point normalization based on penetration depth below the outer canopy layer to avoid biases introduced by ground normalization and canopy surface heterogeneity during metric computation. Second, we proposed computation of area and volume metrics from canopy surface models computed from both first and last returns to better characterize the 3D plot heterogeneity. The set of proposed metrics were combined with traditional ones, based on point height above ground level, to measure their contribution to models of basal area (BA) and aboveground volume (AGV). The modeling framework included a wide range of forest types, canopy structures and Lidar characteristics. Models were developed for all sites grouped together or separately. In each case, the set of metrics was submitted to a hierarchical clustering process to select the best variables to be included in the models that were further established using a best-subset method. Overall, the introduction of the proposed metrics allowed a reduction in models root mean squared error from - 0.06% to 19.58% according to forest types and target forest parameters. Best improvements were achieved for broadleaved forests, showing the potential of the proposed metrics to efficiently characterize the structure of such porous forest canopies. © 2015 Elsevier Inc. Source

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