FORMIT-M + EFDM workflow for forest state modelling across Europe
| dc.contributor.affiliation | University of Eastern Finland-Jari Vauhkonen | |
| dc.contributor.author | Jari Vauhkonen | |
| dc.date.accessioned | 2025-04-29T14:02:42Z | |
| dc.date.issued | 2023-07-28 | |
| dc.date.issued | 2023-07-28 | |
| dc.description | The European Forestry Dynamics Model (EFDM) is a transition matrix model that simulates the evolution of forest area distribution according to probabilities of receiving forest management activities and transition probabilities conditional on these activities. Observations or models based on permanent National Forest Inventory (NFI) plots are typically used to model transition probabilities. The scarcity of the permanent NFI plot network becomes an issue at more detailed scales. We propose that process-based growth modeling of EFDM transition probabilities could overcome this challenge, while accounting for changes in growth due to evolving weather and climate factors in a regular grid over Europe. We demonstrate the derivation of transition probabilities for natural processes using the process- and data-based hybrid ecosystem model FORMIT-M with assumed forest structure maps and weather data as inputs. We present a generic dataset to demonstrate the inputs and outputs (e.g. variables and data structures) obtainable by this approach in the assumed use case of modeling future forest structure and living biomass carbon at a resolution of 1 km2 over Europe, based on forest resource data aggregated to this resolution. The use of generic data is expected to make the steps involved transparent, allow testing and communication of the underlying assumptions and principles even in the absence of actual data, and thus promote the adoption of this approach in later applications. Specifically, input data are generated according to the FORMIT-M simulation logic and used as input data to simulate no-management (hereafter noman) scenario that can used as a basis for creating any other forest management scenario. The forecasts account for climate effects via maximum annual gross primary productivity (GPP) parameter and alternative noman scenarios with the maximum annual GPP parameter corresponding to two alternating Representative Concentration Pathways of 2.6 and 4.5. Variation in forest structure and growth patterns across European continent is accounted for by using seven tree species groups and three sub-regions (i.e. North, Central, and South Europe) and a time-period from 2020 to 2100. To visualize changes in areas occupied by different tree species groups with predefined size-classes, areal changes in tree size-classes will be converted to changes in biomass and litter components, and deadwood. The generic data and code producing it are published in this repository. | |
| dc.identifier | https://doi.org/10.5281/zenodo.8187428 | |
| dc.identifier.uri | https://datakatalogi.helsinki.fi/handle/123456789/5315 | |
| dc.rights.license | cc-by-4.0 | |
| dc.subject | European Forest Dynamics Model | |
| dc.subject | Forest resource projection | |
| dc.subject | National Forest Inventory (NFI) data | |
| dc.subject | Forest State modelling | |
| dc.subject | Matrix model | |
| dc.subject | Scenario analysis | |
| dc.title | FORMIT-M + EFDM workflow for forest state modelling across Europe | |
| dc.type | software |