Studies on wood basic density (BD) vertical variations become essential to predict more accurately the within-stem distributions of biomass and wood quality in the forest resource. The vertical variation of wood BD in the stem has been little studied until now, most BD studies being based on measurements taken at breast height. The main objective of this work was to observe and to understand the patterns of vertical BD variation within stems in relation to classical dendrometric variables and to propose relevant equation forms for future modelling. Two softwood species were studied: Abies alba and Pseudotsuga menziesii. Contrasted thinning intensities were studied including strongly thinned plots versus control plots without thinning. BD was most of the time highest at the base of the tree for both species. Then, after a strong decrease from the base of the tree, an increase in BD was often observed towards the top of the tree especially for A. alba. The variation in BD with height was stronger for the unthinned plots than for the heavily thinned ones of A. alba. The opposite was observed for Ps. menziesii. The modulation of growth rate and tree size through thinning intensities modifies the observed vertical variations in BD. Two types of biexponential models were proposed to describe BD variations. The first model used the height in the stem and classical easily-measurable tree variables as inputs, the other one additionally used BD at breast height (BD130). The relative RMSE of BD for A. alba and Ps. menziesii were 9.9% and 8.1%, respectively, with the model without BD130 and 7.6% and 5.9%, respectively, with the model including BD130.

Strong density differences were observed between stem wood at 1.30 m and other tree components (stem wood, stem bark, knots, branch stumps and branches). The difference, up to 40% depending on the component, should be taken into account when estimating the biomass available for industrial uses, mainly fuelwood and wood for chemistry. Basic density is a major variable in the calculation of tree biomass. However, it is usually measured on stem wood only and at breast height. The objectives of this study were to compare basic density of stem wood at 1.30 m with other tree components and assess the impact of differences on biomass. Three softwood species were studied: Abies alba Mill., Picea abies (L.) H. Karst., Pseudotsuga menziesii (Mirb.) Franco. X-Ray computed tomography was used to measure density. Large differences were observed between components. Basic density of components was little influenced by tree size and stand density. Overall, bark, knot and branch biomasses were highly underestimated by using basic density measured at 1.30 m. Using available wood density databases mainly based on breast height measurements would lead to important biases (up to more than 40%) on biomass estimates for some tree components. Further work is necessary to complete available databases.

A set of models of bark thickness at breast height and bark volume are now available for six species in France. A common model suitable for predicting bark volume was proposed for all species. A small but significant altitude effect on bark thickness at breast height was detected for three species. The growing demand for wood energy and bio-molecules requires a thorough evaluation of forest biomass, particularly bark. The objective of this study is to have statistical models of bark volumes for the six main forest species present in North-Eastern France and to be able to estimate regional bark biomasses and quantities of chemical extractives at regional scale. A large databank gathering bark thickness measured at different heights in France was used for selecting literature or new alternative models of tree bark volume. These models were applied to the available forest inventory data from North-Eastern France to estimate the regional bark volume. Secondly, by multiplying these volumes by basic density data and extractive content recently obtained, bark biomasses and extractives quantities were deduced. The first results consist in a set of species-specific models of bark thickness at breast height with R2 around 0.70 and a relative RMSE around 30% which is an improvement of 0.1 for R2 and of 1–2% for relative RMSE depending on the species compared to the best models from the literature. The second results consist in a set of species-specific models of tree bark volumes with R2 of 0.90 and a relative RMSE which varies between 22% when bark thickness at breast height is included and 40% when it is predicted. A significant relationship between bark thickness at breast height and altitude was also observed. The bark resources of Grand Est and Bourgogne-Franche-Comté regions were estimated at 558 000 m3/year and 611 000 m3/year respectively representing between 5.5% and 15% of the stem volume depending on the species. The propagation of the measurement error of bark gauge was estimated at 5% for model of bark thickness at breast height and 24% for bark volume model. These results constitute an important contribution for a better knowledge of the bark resource at a regional scale and may help to optimise bark valuation by the forest-wood sector.

We present a methodological framework that both scientists and supply chain actors can mobilise to organise information at different scales of observation, and further make informed decisions regarding the supply and extraction of bio-molecules from forest biomass. We demonstrate its usefulness for extracting bio-molecules contained in silver fir growing in France. Numerous bio-active molecules can be extracted from trees at an industrial scale. Supply chain actors play a central role in this emerging bio-economy. However, they do not have enough information and tools to make informed decisions with respect to species, growing locations, or identities of potential suppliers of relevant wood biomass. We explore and demonstrate an information chain and methodological framework that can help make three critical decisions regarding the selection of (1) the species containing the desired bio-molecules, (2) the locations where the resource is collected, and (3) the supply chain partners and types of industrial wood by-products necessary to obtain sufficient biomass for industrial extraction. The methodological framework provides detailed guidelines and references to select the right combination of sampling protocol, allometric models, chemical analyses, GIS tools, and forest growth and supply chain models in order to produce information for the three decision steps within various regional contexts. We apply the framework within the context of supply chain actors who are interested in estimating the quantity and diversity of bio-molecules contained in silver fir (Abies alba Mill.) growing in the Grand Est region of France. We show how conflicting environmental, legal and economic constraints can affect the results. We discuss future challenges that need to be tackled to improve the methodological framework. This study represents a highly detailed overview of the potential bio-molecules contained in a tree species, from its natural habitat or plantation to the end of the regional supply chain. It also represents a step towards the development of a generic knowledge infrastructure and methodology that is necessary to solve various decision-making problems regarding the industrial supply and extraction of high-value bio-molecules.

Today, climate change, scarcity of fossil fuels and new regulations (as the European REACH regulation) lead chemical industry to find new resources in order to make its conversion toward green chemistry. Use of forest resources makes this conversion possible. Indeed, in addition to the ligno-cellulosic material, wood contains molecules, called extractives. These molecules, of little size compared to the wood polymers, lignin and cellulose, are easy to recover and can be used as a feedstock for the fine chemistry, for example pharmaceutics or cosmetics. In order to assess the feasibility of installing regional extraction plants, the quantity of available extractives must be first estimated. This study, aims to estimate the volume of bark in Pseudotsuga menziesii, Picea abies et Abies alba, and combine it subsequently with density and concentration in extractives. Several French bark databases have been merged including a total of 12 000 trees measured. Both stem diameter were measured regularly all along the stem. A modelling approach is presented to predict bark volume from tree measurements, like DBH or tree height. This model is applied to the forests of NorthEastern France measured by the National Forest Inventory service (IGN). A first estimation of the resource of bark extractives is delivered from our bark volume estimates, density values and extractives concentrations.

Although biomass depends as much on volume as on density, in the case of trees, only the volume of the stem and the density at breast height have been studied quite extensively. The rare existing works and our preliminary analyses showed that, according to the species, the density could vary strongly between and within tree components. There is a need to better know the forest resource in terms of wood density and biomass of the different tree components (clear wood, knots, bark, branches). Such work will contribute to refine biomass estimates to evaluate carbon sequestration in forests and to optimize the use of wood resource (lumber, pulp, panel, fuelwood, new utilisations such as extractives for chemistry), with a particular attention paid to the recovering of waste woods. Wood samples of stem, knots and branches were X-rayed in oven-dried state with a medical CT scanner. For each type of sample, a specific image analysis procedure was developed under ImageJ software to measure wood density. We present here our results for the stem and knot components for three major softwood species in France. This was done within the frame of a project about the developement of a chemical industry. Knots are particulary rich in lignans, used in the cosmetics, medicine and nutrition industries. Knots have a much greater wood density than stem wood, whereas most wood density measurements, on which wood density databases are based, were performed at breast height. Depending on the species, it would be necessary to take into account theses variations to estimate correctly the biomass of tree components.