Human pressure on forest resources increased significantly during the past decades through land use and land use change, especially in the tropics where forest clearing is a major source of CO2 release in the atmosphere. Consequently, forests are the focus of international environmental policies and discussions aiming to reduce emissions from deforestation and forest degradation (i.e. REDD+). The capacity of participating countries to regularly provide accurate forests C stocks measurements at a national scale thus represents an important challenge to address. In dense forests, generally only the above ground biomass (AGB) is measured as it accounts for more than 50% of total C stocks. However, important gaps remain at each scale of measurement, i.e. from felled tree to regional mapping, with the resulting errors propagation through these different scales being probably the most concerning issue.<p><p>In the present work, we propose to address these issues by using a multi-scale approach in order to improve our global understanding of AGB variations in dense tropical forests of Central Africa. In particular, we studied (i) forest AGB prediction from remote-sensing textural analysis, (ii) the potential role of largest trees as predictor of the entire forest-stand AGB and (iii) intra- and inter-individual radial variation of wood specific gravity (WSG, i.e. oven-dry mass divided by its green volume) and its potential consequences on the estimation of the AGB of the tree. <p>First, we analyzed the potential use of textural analysis to predict AGB distribution based on very high spatial resolution satellite scenes. In particular, we used the Fast Fourier Transform Ordination (FOTO) method to predict AGB from heterogeneous forest stands of the Democratic Republic of the Congo (DRC). Here, based on 26 ground plots of 1-ha gathered from the field, plus a successful combination of Geoeye and Quickbird contrasted scenes, we were able to predict and to map AGB with a robust model (R² = 0.85; RMSE = 15%) based on textural gradients. <p>Secondly, the research of AGB indicators was focused on the dissection of the role played by largest trees. Here we found largest trees not only hold large share of forest carbon stock but they contain the print of most of forest-stand structure and diversity. Using a large dataset from western Cameroon to eastern DRC, we developed a non-linear model to predict forest carbon stock from the measurement of only a few large trees. We found the AGB of the 5 % largest stems allow to predict the AGB of the entire forest-stand yielding an R² of 0.87 at a regional scale. Focusing on largest trees species composition, we also showed only 5 % of species account for 50 % of total AGB.<p>In the end, we investigated inter- and intra-individual WSG variations. Despite recognized inter- and intra-specific variations along the radial axis, their ecological determinants and their consequences on trees aboveground biomass assessments remain understudied in tropical regions. To our knowledge, it has never been investigated in Africa. Using a 3-D X-Ray scanner, we studied the radial WSG variation of 14 canopy species of DRC tropical forests. Wood specific gravity variance along the radial profile was dominated by differences between species intercepts (~76%), followed by the differences between their slope (~11%) and between individual cores intercept (~10%). Residual variance was minimal (~3%). Interestingly, no differences were found in the comparison of mean WSG observed on the entire core and the mean WSG at 1-cm under the bark (intercept ~0; coefficient = 1.03). In addition, local values of WSG are strongly correlated with mean value in the global data base at species level. <p><p>I deeply believe these results favor the development of promising tools to map and to estimate accurately the AGB of tropical forest-stands. The information provided by largest trees on the entire forest-stand is particularly interesting both for developing new sampling strategies for carbon stocks monitoring and to characterize tropical forest-stand structure. In particular, our results should provide the opportunity to decrease current sampling cost while decreasing its main related uncertainties, and might also favor an increase of the current sampling coverage. <p> / Doctorat en Sciences agronomiques et ingénierie biologique / info:eu-repo/semantics/nonPublished

Le secteur canadien des pâtes et papiers (P&P) a joué un rôle socioéconomique majeur durant les deux derniers siècles. Ces compagnies, en plus de l’avantage de leur positionnement géographique, ont accumulé une expérience confirmée en matière d’industrie forestière, dont notamment le traitement de la biomasse ligneuse. Au cours des trois dernières décennies, ces entités ont encouru des contraintes environnementales difficiles, auxquelles vient s’ajouter une crise chronique du marché. Cette dernière crise a eu des retombées sans précédent sur le côté social, ce qui a amené à qualifier le contexte difficile du secteur comme une crise de soutenabilité. Au cours de la dernière décennie, l’industrie de l’énergie verte est devenue une composante basique des stratégies de transition énergétique pour les pays développés. La biomasse a toujours été au coeur de cette stratégie pour le Canada. Pour les P&P, cette orientation constitue une opportunité pour résoudre la crise environnementale et économique accrue du secteur. Les preneurs de décision ont besoin d’une feuille de route pour transformer les usines de P&P en Bioraffinerie Forestière Intégrée (BRFI). Le choix des technologies, le dimensionnement de la capacité de production et le choix des voies d’investissement bioénergétique constituent des préoccupations majeures pour les preneurs de décision. Toutefois l’évaluation de la soutenabilité de cette transformation demeure un défi de taille. Notre contribution vise à développer des approches et des outils d’aide à la décision pour supporter une transformation efficace, robuste et durable de l’industrie des P&P au Canada. L'objectif est d’évaluer la soutenabilité de l’intégration des BRFI et de communiquer un nouveau modèle d’affaires aux preneurs de décision, tout en renforçant leur capacité de négocier une politique incitative propice en matière des investissements bioénergétiques dans le cadre du partenariat public-privé. La méthodologie utilisée pour atteindre cet objectif se place à l'intersection de l'aide à la décision, de l'optimisation mathématique et de l'analyse financière et économique. Notre première contribution propose la conception et l’application d’une méthode d’évaluation de la soutenabilité intégrant l’approche cycle de vie à l'optimisation du réseau de création de valeur dans le cadre d’un modèle mathématique multiobjectif. Ce dernier modèle fournira une feuille de route pour les investissements soutenables en bioénergie, minimisant les émissions de Gaz à Effet de Serre (GES) et maximisant la valeur financière de la bioraffinerie sur un horizon de planification à long terme tout en assurant une gestion optimale de l’activité incubatrice. Au niveau de la deuxième contribution, nous présentons une analyse de sensibilité du modèle mathématique proposé selon des scénarios plausibles, et ce, avec l’élaboration d’un canevas pour bien communiquer le modèle aux preneurs de décision. Le but de cette partie est d'évaluer la robustesse du modèle, de bien communiquer aux parties prenantes les implications des choix d'investissement dans la production de bioénergie dans un environnement incertain et d’identifier les perspectives pour améliorer l'efficacité du modèle proposé. Dans la troisième contribution, nous proposons une analyse fiscale approfondie des modes de dépréciations dérogatoires appliqués aux investissements en bioénergie. Cette analyse traite l’impact des types d’amortissements dérogatoires sur le choix d’investissement bioénergétique et sur la soutenabilité. Notre objectif est de fournir aux preneurs de décision un ensemble d’outils d’aide à la décision tout en renforçant leur pouvoir de négocier une politique fiscale favorable à l’investissement bioénergétique. Dans cette partie, on a mis en évidence le fait que le choix de l’investissement couplé avec le choix de sa façon de dépréciation offre à l’investisseur une visibilité plus complète sur les conséquences pratiques de l’investissement dans le domaine bioénergétique en connivence avec la législation fiscale en vigueur. Ce qui conforte le partenariat public-privé et détermine le niveau d’interventionnisme public dans la réussite des transformations escomptées du secteur de P&P. L’analyse d’impacts sociaux et les approches de programmation stochastique pour l’étude de robustesse n’ont pas été abordées par ce travail, elles ont été présentées comme perspectives de recherche. / The Canadian pulp and paper sector has played a major socio-economic role in the last two centuries. In addition to the advantage of their geographical position, P&P companies have accumulated proven experience in the forest industry, including the treatment of wood biomass. Over the last three decades, these entities have faced difficult environmental constraints, compounded by a chronic market crisis. This latest crisis has had unprecedented social consequences leading to a crisis of sustainability. Over the last decade, the green energy industry has become a basic component of the energy transition strategies for developed countries. Biomass has always been at the heart of such a strategy for Canada. For the P&P, this orientation is an opportunity to solve the growing environmental and economic crisis of the sector. Decision-makers need a road map to transform P&P's factories into an Integrated Forest Biorefinery (IFBR). The choice of technologies, the sizing of production capacity and the choice of bioenergy investment are major concerns for decision-makers. However, assessing the sustainability of this transformation remains a major challenge. Our contribution is focused on developing decision support approaches and tools to support an effective, robust and sustainable transformation of Canada's P&P industry. The objective is to assess the sustainability of the IFBR integration and to present a new business model to decision-makers, which can strengthen their ability to negotiate a favorable incentive policy for bioenergy investments within the framework of the public-private partnership. To achieve this goal, our methodology combines decision support tools, mathematical optimization models, along with financial and economic analysis. Our first contribution proposes the design and application of a sustainability evaluation method integrating the life cycle approach and the optimization of the value creation network as part of a multi-objective mathematical model. The proposed model provides a roadmap for sustainable bioenergy investments, minimizing GHG emissions and maximizing the financial value of the biorefinery over a long-term planning horizon while ensuring optimal management of the incubator activity. In the second contribution, we present a sensitivity analysis of the proposed mathematical model according to well selected scenarios, with the development of a framework for communicating the model to the decision-makers. The purpose of this analysis is to assess the robustness of the model, to communicate to stakeholders the implications of investment choices in bioenergy production in an uncertain environment, and to identify opportunities for improving the effectiveness of the proposed model. In the third contribution, we propose an in-depth tax analysis using accelerated depreciation methods applied to investments in bioenergy. This analysis deals with the impact of the types of depreciations on the choice of bioenergy investment and on sustainability. Our goal is to provide decision makers with a set of decision support tools while strengthening their power to negotiate a tax policy favorable to bioenergy investment. In this part, it was highlighted that the choice of the investment coupled with the choice of its depreciation way offers the investor a more complete visibility on the practical consequences of the investment in the bioenergetics field with respect to prevalent tax legislation. This reinforces the public-private partnership and determines the level of public interventionism needed for the success of the expected transformation of the P&P sector. The social impact analysis and stochastic programming approaches for the robust study were not addressed by this work, they were presented as research perspectives.