Periodic Reporting for period 1 - MoniFun (Co-creating a blueprint of a harmonised European Forest Multifunctionality Monitoring System - MoniFun)
Okres sprawozdawczy: 2024-01-01 do 2025-06-30
MoniFun is a project that brings together different experts and stakeholders to design a shared system for monitoring how forests in Europe are used and managed for multiple purposes. This new system, called the European Forest Multifunctionality Monitoring System (EFMMS), will combine scattered data from various sources into one clear and useful platform. It will help meet the needs of policymakers, researchers, and society.
Here’s how MoniFun works:
First, it identifies what kind of forest-related information different groups need. Then, experts work together to turn these needs into common indicators and design the technical details of the system. They also suggest how the system should be managed and funded in the long term.
MoniFun also develops and tests practical methods, such as:
* Combining field data (like national forest inventories) with remote sensing data, while keeping sensitive location data private.
* Using artificial intelligence to detect fast changes in forests in real time.
* Creating reliable and detailed statistics that match users’ needs.
* Predicting how forests will provide services like climate regulation and biodiversity support over time, to help assess the impact of forest policies.
The project also utilizes other researchers via grants to test these methods and exploring whether technologies like blockchain could help keep the system’s data up to date.
To make sure MoniFun builds on existing knowledge, it works closely with other forest-related projects (like DIABOLO, PathFinder, FORWARDS, and ForestPaths), whose leaders are also involved in MoniFun.
In the end, MoniFun will deliver a clear sketch for a European forest monitoring system. Once in place, it will help improve decision-making, support climate and biodiversity goals, and guide forest policies across Europe.
Here’s how MoniFun works:
First, it identifies what kind of forest-related information different groups need. Then, experts work together to turn these needs into common indicators and design the technical details of the system. They also suggest how the system should be managed and funded in the long term.
MoniFun also develops and tests practical methods, such as:
* Combining field data (like national forest inventories) with remote sensing data, while keeping sensitive location data private.
* Using artificial intelligence to detect fast changes in forests in real time.
* Creating reliable and detailed statistics that match users’ needs.
* Predicting how forests will provide services like climate regulation and biodiversity support over time, to help assess the impact of forest policies.
The project also utilizes other researchers via grants to test these methods and exploring whether technologies like blockchain could help keep the system’s data up to date.
To make sure MoniFun builds on existing knowledge, it works closely with other forest-related projects (like DIABOLO, PathFinder, FORWARDS, and ForestPaths), whose leaders are also involved in MoniFun.
In the end, MoniFun will deliver a clear sketch for a European forest monitoring system. Once in place, it will help improve decision-making, support climate and biodiversity goals, and guide forest policies across Europe.
MoniFun is a compact project where the Work Packages (WPs) progress towards one common aim, the blueprint of EFMMS. The scientific and technical work is organized into four WPs:
1. Co-create EFMMS blueprint based on stakeholder needs
2. Expert indicator definitions & methods
3. Next generation mapping of forest multifunctionality
4. Harmonised estimation of multifunctionality indicators
The work done in these WPs is supported by two work packages which take care of project coordination, administration, dissemination, exploitation and communication.
The work started in WP1, where the first tasks were to map from stakeholders what kind of information should be monitored in EFMMS, and what kind of indicators have been suggested for such monitoring. The output of these analyses has been reported in Deliverables 2.1 (Set of factsheets describing indicators that address information needs), 2.2 (Report on forest-related information needs, uses & data sources), and the first batch of practice abstracts (D5.5).
These outputs from WP1 have been utilized in WP2, where experts on different fields are working to map relevant information sources and define operational indicators to be monitored in the EFMMS. This work is currently on-going, but the WP2 has already submitted D2.1 entitled "Detailed metadata on available data & information on the selected variables across target countries" in June, 2025.
The WPs 3 and 4 develop technical solutions for identified critical bottlenecks related to the monitoring of forest multifunctionality. WP3 works on developing maps and remote sensing material, whereas WP4 works on solutions based on domains, defined by forest properties, spatial location and time.
To enable starting of the work in WPs 3 and 4. WP2 has provided a short list of indicators to be monitored, and WPs 3 and 4 will work on these. We assume that once technical solutions for monitoring these indicators for a set of European countries has been developed, extension to the full list for the whole Europe is straightforward.
To support this work, a national forest inventory (NFI) data collection has been completed in WP4 and they will be combined with harmonized European level maps developed in WP3.
A new growth curve and an approach to fit domain-based curves using the measured past growth from NFI data was developed and published in 2025 using NFI data from Finland. It has been used for analysing the long-term trends in harvest removals and growth in Finland by using a recently developed Age Class Simulator. The same curve has been successfully fitted to the data of Norway and Germany, as well. Since M9 planning for a joint scenario modelling has been done by Luke and WR. E.g. modelling of future forest resources and related variables was done in draft form by WR with EFISCEN-space for 20 EU countries, testing also on the seven MoniFun demo countries.
1. Co-create EFMMS blueprint based on stakeholder needs
2. Expert indicator definitions & methods
3. Next generation mapping of forest multifunctionality
4. Harmonised estimation of multifunctionality indicators
The work done in these WPs is supported by two work packages which take care of project coordination, administration, dissemination, exploitation and communication.
The work started in WP1, where the first tasks were to map from stakeholders what kind of information should be monitored in EFMMS, and what kind of indicators have been suggested for such monitoring. The output of these analyses has been reported in Deliverables 2.1 (Set of factsheets describing indicators that address information needs), 2.2 (Report on forest-related information needs, uses & data sources), and the first batch of practice abstracts (D5.5).
These outputs from WP1 have been utilized in WP2, where experts on different fields are working to map relevant information sources and define operational indicators to be monitored in the EFMMS. This work is currently on-going, but the WP2 has already submitted D2.1 entitled "Detailed metadata on available data & information on the selected variables across target countries" in June, 2025.
The WPs 3 and 4 develop technical solutions for identified critical bottlenecks related to the monitoring of forest multifunctionality. WP3 works on developing maps and remote sensing material, whereas WP4 works on solutions based on domains, defined by forest properties, spatial location and time.
To enable starting of the work in WPs 3 and 4. WP2 has provided a short list of indicators to be monitored, and WPs 3 and 4 will work on these. We assume that once technical solutions for monitoring these indicators for a set of European countries has been developed, extension to the full list for the whole Europe is straightforward.
To support this work, a national forest inventory (NFI) data collection has been completed in WP4 and they will be combined with harmonized European level maps developed in WP3.
A new growth curve and an approach to fit domain-based curves using the measured past growth from NFI data was developed and published in 2025 using NFI data from Finland. It has been used for analysing the long-term trends in harvest removals and growth in Finland by using a recently developed Age Class Simulator. The same curve has been successfully fitted to the data of Norway and Germany, as well. Since M9 planning for a joint scenario modelling has been done by Luke and WR. E.g. modelling of future forest resources and related variables was done in draft form by WR with EFISCEN-space for 20 EU countries, testing also on the seven MoniFun demo countries.
Some project results have high potential to make important steps forward in monitoring of forest multi-functionality in Europe.
The EFDM, which has been available already before for some European countries, and the Age Class simulator, which was recently developed for Finland are simple tools for constructing scenarios about the development of forests based on the most recent national forest inventory (NFI) data sets. The project has done a data collection campaign, which allows calibration of the growth models of the scenario modelling tools by using the most recent NFI data. The recently published new growth curve and approach to fit it using NFI data opens possibilities to develop simple tools for simulating the development of European forests using most recent NFI data sets.
The EFDM, which has been available already before for some European countries, and the Age Class simulator, which was recently developed for Finland are simple tools for constructing scenarios about the development of forests based on the most recent national forest inventory (NFI) data sets. The project has done a data collection campaign, which allows calibration of the growth models of the scenario modelling tools by using the most recent NFI data. The recently published new growth curve and approach to fit it using NFI data opens possibilities to develop simple tools for simulating the development of European forests using most recent NFI data sets.