An innovative modelling framework and metrics are developed to assess the economic and environmental performances of regional incentives in the wood energy sector. Our approach is based on the coupling between a partial equilibrium economic model of the forest sector with Life Cycle Assessment (LCA). Its originality relies on the computation of regional eco-efficiency ratios while taking account of diverse direct and indirect spatial and market interactions. Several adaptations were implemented to ensure consistency between the two modelling approaches in terms of process yields and flow balances. These adaptations make it possible to produce both economic and environmental indicators with a consistent perimeter. Finally, we used two kinds of eco-efficiency indicators to compare bioenergy policies. On the one hand, Partial Eco-Efficiency (PEE) combines the economic surplus induced by an incentive on the energy wood sector with its potential environmental impacts. On the other hand, Full Eco-Efficiency (FEE) adds the environmental impacts avoided by substitution between wood-energy and fossil fuels, compared to a business-as-usual (BAU) scenario. The proposed adaptations were applied to a case study in the French Grand Est region that compared the eco-efficiency of scenarios with or without a subsidy to wood energy consumption. Results show that subsidy increases the eco-efficiency of the forest-based sector using both PEE and FEE while keeping competition with the other regions to a minimum. However, most benefits come from the consideration of avoided impacts, with FEE far exceeding PEE. Using FEE, the scenario with the subsidy is 5% to 50% more eco-efficient than the BAU despite an increased consumption of wood products, due to economic gains and avoided impacts. These outcomes show the importance of considering potential trade-offs when assessing the economic and environmental performance of regional policies in favour of the bioeconomy.

Under the influence of climate change, wildfire regimes are expected to intensify and expand to new areas, increasing threats to natural and socioeconomic assets. We explore the environmental and economic implications for the forest sector of climate-induced changes in wildfire regimes. To retain genericity while considering local determinants, we focus on the regional level and take Mediterranean France as an example. Coupling a bioeconomic forest sector model and a model of wildfire activity, we perform spatially explicit simulations under various levels of radiative forcing. By using a probabilistic framework, we also assess the propagation of several sources of uncertainty to the forest sector, considering both climate-induced uncertainty and the intrinsic stochasticity of the fire process. By the end of the century, summer burned areas increase by up to 55%, causing moderate losses of merchantable timber and forest carbon stocks, with cascading impacts for industrial activities and climate mitigation in the forest sector. Implications for industries remain limited, but we observe price increases, especially for softwoods, as well as spatially differentiated changes in producer welfare. Inter-annual fluctuations explain most of uncertainty in wildfire activity, but their impacts on the forest sector are quickly dampened. Over time, owing to the cumulative nature of wildfire impacts on forest resources, uncertainty related to climate warming, climate models' response and stochasticity intrinsic to the wildfire phenomenon strongly increase in relative importance. Results reassert the need to consider multiple futures in prospective assessments, including uncertainty inherent to natural processes, often omitted in large-scale economic assessments.

Objectives: Evaluate the capacity of temperate forest resources to both provide climate change mitigation and to sustain the downstream timber sector explicitly considering the cascade of biophysical and economic drivers (in particular, climate change impacts and subsequent adaptation actions) and their uncertainty. Methodology: A recursive bio-economic model of French forest resources, management, and timber markets has been coupled for this study with spatial statistical models of forest response to climate change long-term scenarios and land-use change. Main Results: (a) Climate change impacts on tree mortality are greater than those on tree growth variations; (b) Due to increasing competition with agriculture, climate change may reverse current trends in forest area expansion; (c) Due to rising average tree sizes, volume growth strongly declines over time and may eventually cease within the next century; (d) Future climate change impacts already have strong consequences on today's forest investment profitability; (e) The relative importance of forest substitution over forest sequestration increases as the timeframe increases; (f) While the forest sector has the potential to counterbalance a significant share of the national carbon emissions, this potential is threatened by climate change and the need to adapt to it. Profit-driven forest management does increase mitigation; (g) Uncertainty derived from using different climatic models over the same IPCC storyline has the same order of magnitude as the uncertainty derived from using the same climatic model under different storylines.

La validation des modeles d’evaluation integree constitue un defi important de la recherche pluri- et interdisciplinaire. Nous montrons ici que les methodes de validation, souvent resumees a une comparaison entre resultats des modeles et donnees reelles passees, sont complexes et variees et que, dans le cas de modeles dont l’objectif est de porter un eclairage prospectif sur le long terme, la validation ne peut etre reduite aux methodes de comparaison. Pour illustrer nos propos, nous appliquons notre reflexion aux modeles de simulation bioeconomiques de la filiere foret-bois.

Objectives: Evaluate the capacity of temperate forest resources to both provide climate change mitigation and to sustain the downstream timber sector explicitly considering the cascade of biophysical and economic drivers (in particular, climate change impacts and subsequent adaptation actions) and their uncertainty. Methodology: A recursive bio-economic model of French forest resources, management, and timber markets has been coupled for this study with spatial statistical models of forest response to climate change long-term scenarios and land-use change. Main Results: (a) Climate change impacts on tree mortality are greater than those on tree growth variations; (b) Due to increasing competition with agriculture, climate change may reverse current trends in forest area expansion; (c) Due to rising average tree sizes, volume growth strongly declines over time and may eventually cease within the next century; (d) Future climate change impacts already have strong consequences on today's forest investment profitability; (e) The relative importance of forest substitution over forest sequestration increases as the timeframe increases; (f) While the forest sector has the potential to counterbalance a significant share of the national carbon emissions, this potential is threatened by climate change and the need to adapt to it. Profit-driven forest management does increase mitigation; (g) Uncertainty derived from using different climatic models over the same IPCC storyline has the same order of magnitude as the uncertainty derived from using the same climatic model under different storylines.

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.

We explore the implications of managing forests for the dual purpose of sequestering carbon and producing timber, using a model of the forest sector that includes a Hartman-based representation of forest owners' behaviour as well as heterogeneity in environmental conditions. We focus on France, where recent policies aim at increasing the carbon sink and where the diversity of forests makes an analysis of spatial dynamics relevant, and we use recent estimates of the shadow price of carbon consistent with the country's climate commitments. Results suggest that forests may sequester up to 550 MtCO(2)eq by 2100, driven by changes in harvest levels and species choice, whilst rotation lengths increase overall. A spatial analysis reveals a high spatial variability for these trends, highlighting the importance of considering the local context. Changes in investment patterns affect the spatial distribution of forest cover types: by the end of the century, a majority of regions comprise a larger share of older, multiple-species and mixed-structure forests. Whilst such an evolution may present benefits in terms of biodiversity, ecosystem services provision and resilience, it raises questions regarding the adequacy of such developments with current forest policy, which also aims at increasing harvest levels. An overall mitigation strategy for the forest sector would likely include incentives to energy and material substitution in downstream industries, which we did not consider and may interact with sequestration incentives.

This article explores the links between relocation and greening processes within the French forest-wood chain. We show that the parallel emergence of both processes led to the legitimization of the territory as a relevant scale for the implementation of ecological alternatives. The induced changes of the practices now make it clear that both processes should be considered as concomitant, operating at a key moment in the reorganization of the productive systems feeding on each other rather than being actually the cause or the consequence one of the other. While existing tools for the evaluation of practices are largely under development, a particularly fertile front is arising at the intersection of environmental and human sciences.

Forest sector models encompass a set of models used for forest-related policy analysis. As representations of a complex human-environment system, they incorporate multiple facts from their target, the forest sector, which is usually understood as comprising forests, forestry and forest industries. Even though they pursue similar goals and display similarities, forest sector models show divergences in their representation of the forest sector. In this paper, we question and discuss the determinants behind the representation of facts in forest sector models, and try to highlight the reasons behind modelling practices. The forest sector's boundaries are often unclear, and it comprises facts of different natures for which dynamics take place on different time and spatial scales. As a result, modelling practices vary, and both empirical data and theory play varying roles in representing facts. Early models were developed in the 1970s and find their roots in traditional forest economics, the economics of natural resources, econometrics, but also transportation problems and system dynamics. Because they developed within a small but well-connected field, early efforts were influential in shaping current practices. Numerical simulation and scenario analysis are used as means of enquiry into model worlds: in that, forest sector models are a classical example of model use in economics, and they constitute a good example of how simulation models have been developed for decision-support purposes. Forest sector modelling is heavily influenced by its applied uses, and policy contexts shape both questions asked and how facts are introduced in scenario storylines. Understanding the determinants of modelling choices is necessary to ensure sound modelling practices. Forest sector models are now used to address issues wider than timber production. Practices turn to integration into multi-model frameworks to expand the boundaries of the system studied, but also towards the use of qualitative methods as new ways of representing facts, in particular deep changes that quantitative models may not be able to capture.

Schedules of declining discount rates have been advocated, and adopted by several European governments. They undermine classical solutions to forest economics problems, especially optimal rotation. Adapting classical first-order conditions created problems of local optimisation. A global search algorithm allowed inclusion of initial costs and thinning revenues. It produced results according with expectations – lengthening rotations as time progressed – and results paralleling those for constant discount rates – shorter rotations for high productivity and unthinned crops, and with zero crop formation costs. Apparent anomalies in the pattern of rotations are the due result of opportunity costs from later rotations, which increase as discount rate declines. Sometimes the solution oscillates, usually owing to steps in the discount schedule or irregular profile of felling revenues. Inspection allows the most profitable result to be identified.

Integrated simulation models are commonly used to provide insight on the complex functioning of social-ecological systems, often drawing on earlier tools with a narrower focus. Forest sector models (FSM) encompass a set of simulation models originally developed to forecast economic developments in timber markets but now commonly used to analyse climate and environmental policy. In this paper, we document and investigate this evolution through the prism of the inclusion of several non-timber objectives into FSM. We perform a systematic, quantitative survey of the literature followed by a more in-depth narrative review. Results show that a majority of papers in FSM research today focuses on non-timber objectives related to climate change mitigation, namely carbon sequestration and bioenergy production. Habitat conservation, deforestation and the mitigation of disturbances are secondary foci, while aspects such as forest recreation and many regulation services are absent. Non-timber objectives closest to the original targets of FSM, as well as those for which economic values are easier to estimate, have been more deeply integrated to the models, entering the objective function as decision variables. Others objectives are usually modelled as constraints and only considered through their negative economic impacts on the forest sector. Current limits to a deeper inclusion of non-timber objectives include the models’ ability to represent local environmental conditions as well as the formulation of the optimisation problem as a maximisation of economic welfare. Recent research has turned towards the use of model couplings and the development of models at the local scale to overcome these limitations. Challenges for future research comprise extensions to other non-timber objectives, especially cultural services, as well as model calibration at lower spatial scales.

Forest sector models encompass a set of models used for forest-related policy analysis. As representations of a complex human-environment system, they incorporate multiple facts from their target, the forest sector, which is usually understood as comprising forests, forestry and forest industries. Even though they pursue similar goals and display similarities, forest sector models show divergences in their representation of the forest sector. In this paper, we question and discuss the determinants behind the representation of facts in forest sector models, and try to highlight the reasons behind modelling practices. The forest sector’s boundaries are often unclear, and it comprises facts of different natures for which dynamics take place on different time and spatial scales. As a result, modelling practices vary, and both empirical data and theory play varying roles in representing facts. Early models were developed in the 1970s and find their roots in traditional forest economics, the economics of natural resources, econometrics, but also transportation problems and system dynamics. Because they developed within a small but well-connected field, early efforts were influential in shaping current practices. Numerical simulation and scenario analysis are used as means of enquiry into model worlds: in that, forest sector models are a classical example of model use in economics, and they constitute a good example of how simulation models have been developed for decision-support purposes. Forest sector modelling is heavily influenced by its applied uses, and policy contexts shape both questions asked and how facts are introduced in scenario storylines. Understanding the determinants of modelling choices is necessary to ensure sound modelling practices. Forest sector models are now used to address issues wider than timber production. Practices turn to integration into multi-model frameworks to expand the boundaries of the system studied, but also towards the use of qualitative methods as new ways of representing facts, in particular deep changes that quantitative models may not be able to capture.

This review analyses and compares the most promising methods to perform ex ante economic and environmental assessment of policies at the meso scale, i.e. from local communities to subnational regions. These methods called Economic-Environment Integrated Models (EEIM) are based on the coupling of formalised economic modelling tools with environmental assessment methods. The economic modelling tools considered are Input Output (IO) models, Computable General Equilibrium (CGE) and Partial Equilibrium (PE) models, Agent-Based models (ABM), and System Dynamics (SD) models, which we pair with environmental assessment methods such as Footprints (FP), Life Cycle Assessment (LCA), or Material Flow Analysis (MFA). A grid of criteria is developed to perform a qualitative rating of the EEIMs according to existing literature. The grid encompasses the detail level of the economic modelling, the level of coupling between environmental and economic tools, the quality and diversity of indicators, the ability to account for diverse indirect effects, spatial differentiation, time aspects, and the coupled model usability. First, the results show that the couplings do not perform on the same criteria, which shows complementarity to deal with diverse issues. Second, overall, for most criteria, PE/CGE models coupled with FP/LCA ranked highest. Third, a few case studies showed that couplings involving a third tool can be beneficial— for instance AB modelling or MFA with PE/CGE-LCA/FP may allow to overcome some shortcomings such as agent behaviour modelling or data availability for biophysical flows.

Forest ecosystems are typical examples of socio-ecological systems. However, in terms of modelling, the social aspect has been given far less attention than the ecological aspect. In this study, we modelled the impact of economic and social factors on the occurrence of harvesting. This harvest model was then integrated into an individual-based model of forest growth designed for large-area forecasts. The resulting socio-ecological model was then used to produce volume predictions for two regions of France. Among the economic factors, the annual stumpage prices in interaction with the species proved to be a significant predictor of harvest occurrence. Simulating different stumpage price evolutions made it possible to predict supply curves for the two regions. Projections until 2060 showed that increases in stumpage prices will be detrimental to standing volumes in both regions. Integrating the demand for wood products into such socio-ecological models in forestry would be a major improvement.

The invasion of a forest by a pathogen is a complex dynamic and spatial problem. The induced disturbances do not only reduce the present availability of the affected tree species but alter its future availability, population structure and distribution as well. These disturbances also have an impact on the prices of wood products via supply shocks, which, in turn, influence forest management choices, thus introducing feedback effects between market and ecological dynamics. The main objective of this paper is to evaluate the economic impact of an invasive pathogen at a large scale by integrating the biophysical and economic aspects of the invasion into a dynamic and spatially explicit setting. The analysis is developed using a modified version of the French Forest Sector Model (FFSM), a recursive partial equilibrium model, to which a specifically designed pathogen spread and mortality model have been coupled. We calibrated the model to represent the ash dieback invasion in France. Results showed that impacts are not homogeneous across regions and generally depend on the resource distribution, pathogen spread and market structure. We observed that the behavioural adaptation of forest managers (i.e. regeneration and harvesting choices) is a non-negligible component of the total standing volume loss.

In Western Europe, future climate changes go hand-in-hand with increasing risks of droughts and heat waves during summer. For forest ecosystems, a drought may result in both an increase in tree mortality and a reduction in tree growth. These impacts are delayed over time, i.e., there is a time gap between the drought and its impacts on the forest stand, which makes it possible to adjust forest management practices and, in particular, to prematurely harvest the impacted stand and to replant a new one if it is economically profitable to do so. Consequently, we define Climate Services (CS) as the information that supports forest owners in their decision to prematurely harvest or not after a drought. Our paper aims at developing a method to estimate the economic value of these CS in the case of a maritime pine stand in Southwestern France. Using a comparison of Land Expected Values (LEV) over an infinite period of forest rotations, our analysis suggests that the Climate Service Value (CSV) is highly dependent on three characteristics: (1) the age of the forest exposed to the drought; (2) the intensity of the drought in terms of both mortality and growth impacts; and (3) the discount rate value used. Overall, for a 2% discount rate for a young stand (less than 15-20 years old), the CSV is rather low and ranges from 0 to (sic)50/ha depending on the intensity of the drought. However, for a mature stand, the CSV rapidly increases, up to a maximum the year before the optimal harvest date. In this latter case, the CSV may be as high as (sic)4900/ha for intense droughts.

We compute the optimal subsidy level for fuelwood consumption that makes it possible to achieve the French biomass energy consumption target. For this purpose, we model the competition and trade-offs between the consumption of fuelwood for heat (FW-H) and the consumption of fuelwood for electricity (FW-E). To do so, we couple a forest sector model with an electricity simulation model, and we test different scenarios combining FW-H and FW-E that account for contrasting potential increases in the carbon price and the potential reduction in the number of nuclear plants. We assess the implications of these scenarios on (1) the budgetary costs for the government, (2) industrial wood producers' profits, (3) cost savings in the power sector for the different scenarios tested, and (4) the carbon balance. We show that the scenario with the highest carbon price and the lowest number of nuclear plants is the least expensive from a budgetary perspective. Indeed, when associated with a high carbon price, co-firing may increase FW-E demand with a lower subsidy level, which makes it possible to reduce the cost of reaching the target. However, in this case, FW-E crowds out part of FW-H, which may cause political and economic issues. From a carbon balance perspective, an FW-H-only scenario performs better than any other scenario that combines FW-H and FW-E due to the relatively low emissions factors of alternative technologies for electricity generation and, in particular, nuclear energy. (C) 2018 Published by Elsevier B.V.