The bioeconomy is a nexus of interactions and trade-offs that are too complex for individual modelling tools to capture. In this setting, an integrated modelling approach within a multidisciplinary team is key to an improved understanding of the interactions between biophysical and economic processes, and the social and environmental implications of the system as a whole. Integrated modelling requires a dedicated multi-disciplinary team to understand those interactions. During these past years, our team has been working towards holistic modelling approaches by integrating our two core forest-based models, the Carbon Budget Model (CBM), and the Global Forest Trade Model (GFTM) within a spatially-explicit platform FUSION (Forestry Unified System for Input and Output geNeration), in order to assess the environmental implications of wood-based products demand and supply in the context of the EU Bioeconomy. .
The Carbon Budget Model (CBM-CFS3) is an inventory-based, yield-data driven model that simulates the stand- and landscape-level C dynamics of above- and belowground biomass, dead wood, litter and mineral soil (Kurz et al. 2009, Kull et al 2016). The model, developed by Natural Resources Canada’s Canadian Forest Service (CFS), and all the supporting technical documentation are available free-of-charge online (www.nrcan.gc.ca/forests/climate-change/carbon-accounting). The model has been adapted and used by JRC to simulate forest C dynamics at EU level (excluding Cyprus and Malta, see Pilli et al. 2016 and Pilli et al. 2018).
The model framework conceptually follows IPCC Reporting Method 1 in which spatial units (SPUs) are defined by their geographic boundaries in a non-spatially explicit manner. Within a SPU, each forest stand is characterized by age, area and 6 classifiers that provide administrative and ecological information, the link to the appropriate yield curves, and parameters defining the silvicultural system such as forest composition and management type (MT), and the main use of the harvest provided by each SPU, as fuelwood or industrial roundwood. For each country, these parameters were mainly derived by NFIs. According to country-specific information, MTs may include even-aged high forests, uneven-aged high forests, coppices and specific silvicultural systems such as clear-cuts (with different rotation lengths for each FT), thinnings, shelterwood systems, partial cuttings, etc..
Main assumptions and output (i.e., area, harvest, increment, volume, carbon sink) are regularly compared with other data sources (i.e., SoEF 2015, FAOSTAT, National Inventory Reports, most recent publications) in order to increase the consistency of the model with these data sources and within the larger modelling framework.
The CBM model, in the context of the LULUCF (Land Use, Land Use Change and Forest) sector, is used to estimate the current and future forest carbon dynamic, both as a verification tool (i.e. to compare the results with the estimates provided by other models) and as a support to EU legislation (e.g. the recent EU Regulation 2018/841). Results are also used to estimate the carbon flows in the harvested wood products.
In the BIOMASS project the CBM is a core component of the bio-economy modelling framework. Here CBM is used to estimate the maximum wood supply from forests and, after being coupled with the GFTM model (e.g., Jonsson et al. 2018), the future forest carbon dynamics under specific future harvest scenarios. In both contexts, CBM can simulate a business as usual scenario and other policy scenarios which may differ for the different disturbances. Integrated into FUSION, results from CBM are spatially allocated, so that they can be used, for example, to produce cost-supply curves of forest biomass (Mubareka et al. 2018).
Kull SJ, Rampley G, Morken S, Metsaranta J, Neilson ET, Kurz WA (2016) Operational-scale Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) version 1.2: user’s guide. Nat. Resour. Can., Can. For. Serv., North. For. Cent., Edmonton, AB. https://cfs.nrcan.gc.ca/publications?id=36556
Kurz WA, Dymond CC, White TM, Stinson G, Shaw CH, Rampley GJ, Smyth C, Simpson BN, Neilson ET, Trofymow JA, Metsaranta J, Apps MJ (2009) CBM-CFS3: A model of carbon-dynamics in forestry and land-use change implementing IPCC standards. Ecol. Model. 220(4): 480-504. https://cfs.nrcan.gc.ca/publications?id=29137
Pilli R, Grassi G, Kurz WA, Viñas RA, Guerrero N (2016) Modelling forest carbon stock changes as affected by harvest and natural disturbances. I. Comparison with countries’ estimates for forest management. Carbon Balance and Management, 11:5. http://link.springer.com/article/10.1186/s13021-016-0047-8
Pilli, R., Kull, S. J., Blujdea, V. N., Grassi, G. (2018). The Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3): customization of the Archive Index Database for European Union countries. Annals of Forest Science, 75(3), URL: https://link.springer.com/article/10.1007/s13595-018-0743-5
The EU Archive Index Database customised for the Carbon Budget Model (CBM-CFS3). URL: https://ec.europa.eu/jrc/en/scientific-tool/eu-archive-index-database-customised-carbon-budget-model-cbm-cfs3
The Global Forest Trade Model (GFTM) is a partial equilibrium model for the forest-based sector, aimed at deriving projections for consumption, production and international trade of wood-based products and pellets under different scenarios. As a global model GFTM covers 48 sub-regions of the world. While EU member states and major producers and/or consumers of wood-based products are modelled individually, some non-major producer and/or consumer countries are aggregated into global sub-regions.
In the model, primary products (coniferous and non-coniferous sawlogs and pulpwood) are harvested and then transformed into intermediate products (chemical pulp, coniferous and non-coniferous sawdust), or directly into final products. Intermediate products also contribute to final products production. Consumer welfare is derived by the consumption of final products, and all products (with the exception of coniferous and non-coniferous sawdust) are tradable. The specific levels of harvest, production, trade and consumption are derived through the maximization of the whole forest sector welfare, subject to feasibility, resources, productivity and equilibrium constraints. Equilibrium constraints act at regional and also global level. Specifically, at regional level production must equal the sum between domestic consumption and net trade, for each region and each product, while at global level net trade has to be zero for each product. Additional bounds can be set to establish trends, inertia constraints etc. for all/some variables.
GFTM supports policy formulation within the area of forest-based bioeconomy. More specifically it allows modelling the economic implications of policy changes on the market for wood-based products, as well as the impact of such implications on forest resources.
GFTM is a stand-alone model, but designed to be integrated into a forest-based bioeconomy modelling framework. In particular, the GFTM works in close cooperation with the forest resource model the Carbon Budget Model, both receiving inputs and providing outputs. GFTM provides scenarios of consumption, production, and international trade of wood-based products (sawlogs, pulpwood, sawnwood, wood-based panels, pulp, paper, and wood pellets) for 48 countries and global sub-regions.
The feedback from one model to the other works as follows: CBM provides as input to the GFTM the maximum sustainable supply of industrial roundwood (IRW) for a given European country, accounting for legal restrictions and other bounds. This information is in turn used in GFTM as a constraint on the equilibrium supply of raw materials. Then GFTM derives equilibrium quantities of produced wood- based products in the country in question, and sends back to CBM information concerning the amount of IRW needed to be harvested. Given this information, CBM provides potential timber supply for the following period.
Jonsson, R., Blujdea, V., Fiorese, G., Pilli, R., Rinaldi, F., Baranzelli, C., & Camia, A. (2018). Outlook of the European forest-based sector: forest growth, harvest demand, wood-product markets, and forest carbon dynamics implications. iForest - Biogeosciences and Forestry, 11(2), 315–328. doi:10.3832/ifor2636-011
Jonsson, R., & Rinaldi, F. (2017). The impact on global wood-product markets of increasing consumption of wood pellets within the European Union. Energy, 133, 864–878. doi:10.1016/j.energy.2017.05.178
Jonsson K; Rinaldi F; Räty M; Sallnaes P. Integrating forest-based industry and forest resource modeling. IFOREST-BIOGEOSCIENCES AND FORESTRY; 2016. p. e1-e8. JRC97245 http://dx.doi.org/10.3832/ifor1961-009
Rinaldi F, Jonsson K, San-Miguel-Ayanz J. Fact sheet: the Global Forest Trade Model (GFTM) in the Bioeconomy modelling framework. Luxembourg (Luxembourg): Publications Office of the European Union; 2015. JRC97272 http://dx.doi.org/10.2788/945912
Rinaldi F, Jonsson K, San-Miguel-Ayanz J. The Global Forest Trade Model - GFTM. EUR 27360. Luxembourg (Luxembourg): Publications Office of the European Union; 2015. JRC96814 http://dx.doi.org/10.2788/666206
FUSION (Forestry Unified System for Input & Output geNeration) is a modelling platform that was designed and built to support research related to the forest-based sector of the EU Bioeconomy. It’s main purpose is to facilitate the interchange of data between models but it also has built-in features that are used to spatially disaggregate data, compute costs related to accessibility, and resolve objective functions. Depending on the application and the time-step in the simulation, different modules in the FUSION model may be called.
FUSION is written in F/OSS GeoDMS, a C++-based scripting language. It's strength is in its processing speed, facilitated by memory array based processing; tiling of raster data; memory mapping (to avoid using virtual address spaces for standby data sets); and other tricks. FUSION's spatial coverage is of the European Union and has a spatial resolution of 100m x 100m and is typically run on an annual time step to either 2030 or 2050.
Although FUSION was originally designed for the forest-based sector of the bioeconomy, recent developments include the integration of agricultural crops. In this way, the total potential residues for different crops are computed based on their yields. This generates a link to land-use and land-functions changes.
This platform was developed within the context of the BIOMASS Mandate (https://biobs.jrc.ec.europa.eu/page/biomass-assessment-study-jrc) and is being configured to support the Updated EU Bioeconomy Strategy and Action Plan.
Mubareka et al. (2018) Integrated modelling approach to assess woody biomass supply demand and environmental impacts of forest management in the EU, iEMSs 9 th International Congress on Environmental Modelling and Tools.