Combining prescribed fire and retention forestry promotes natural tree regeneration
University of Eastern Finland
Prescribed burning, when combined with tree retention, can effectively support natural regeneration in managed boreal forests, new research shows. The study demonstrates that post-fire seedling establishment remains strong across key commercial species, Scots pine and birch, suggesting that integrating these practices may help reconcile biodiversity goals with sustainable forest management.
In a landscape-scale experiment, the researchers found that natural tree regeneration (i.e. not artificially seeded or planted) met or exceeded commercial standards after prescribed burning and clear-cutting with moderate levels of green tree retention. Pioneer species that establish after disturbance, including Scots pine and silver birch, flourished after burning, while Norway spruce, a species that grows later in forest development, did better on unburned areas where it remained after harvesting. Compared to these harvested areas, natural regeneration was smaller and sparser in protected areas that were burned for restoration with no harvesting. In protected areas, a new generation of young trees may regenerate more slowly and lead to a more diverse age structure of trees after fires.
The researchers examined the quality and amount of natural tree regeneration 11 years after prescribed burning and tree retention treatments in a replicated large-scale experiment. A total of 24 sites ranging in size from three to five hectares were distributed across the landscape in the Ilomantsi and Lieksa regions of Eastern Finland. Half of these were burned in the summer of 2001, while the other half remained unburned. Each site was either clear-cut, harvested with retention (10 m³/ha or 50 m³/ha), or left uncut. On each site, a systematic grid of plots was established where the density, height, diameter, health, and species of each tree was recorded, to investigate how trees regenerate after harvesting and burning.
The study suggests that current forest management practices on dry upland Scots pine sites could be updated to better meet biodiversity objectives, while still achieving commercially acceptable regeneration. New practices include retaining higher amounts of mature trees during harvesting, prescribed burning after harvesting, and reducing site preparation that disturbs the soil. The higher costs of burning and decreased harvesting volume due to retention trees can be partially offset by relying on natural regeneration and eliminating the need to scarify the soil to improve regeneration. The overarching aim of these practices is to counteract the negative effects of clear-cutting and to increase biodiversity and improve habitats for threatened species in the intensively managed Fennoscandian boreal forest.
Journal
Forest Ecology and Management
Article Title
Natural tree regeneration 11 years after prescribed burning with tree retention in the Fennoscandian boreal forest
Article Publication Date
17-Apr-2026
Horizon Europe’s SWIFTT project concludes with Copernicus-based forest management tool to map, mitigate, and prevent the main threats to EU forests
The SWIFTT platform supports timely, data-driven decision-making in the field against spruce bark beetle outbreaks, wildfires, and windthrow.
Da Vinci Labs
image:
SWIFTT is a forest management platform that combines the rich Copernicus Sentinel satellite data and powerful machine learning models. It helps foresters identify changes in tree health, map dieback in their forests and coordinate sanitary cuts, map windthrow damage, and identify areas at high risk of and damaged by wildfires.
view moreCredit: SWIFTT Project
SWIFTT is a forest management platform that combines the rich Copernicus Sentinel satellite data and powerful machine learning models. It helps foresters identify changes in tree health, map dieback in their forests and coordinate sanitary cuts, map windthrow damage, and identify areas at high risk of and damaged by wildfires.
Upon joining the SWIFTT Platform, foresters can register each forest parcel under their management and request an analysis for one or multiple threats. Machine learning models regularly analyse multispectral satellite imagery for anomalies that could indicate different risks or damage, such as spruce bark beetle, windthrow, and wildfires. After detection, foresters receive alerts containing the threat type, severity, as well as indicators for threatened tree volume and hectarage that allow them to prioritise where to inspect or intervene first.
SWIFTT is built to meet the needs of foresters also in the field through its mapping system and geolocation of threats. SWIFTT's mobile app guides foresters directly to the affected location, making inspection efficient and targeted. There, foresters can collect and upload field information, confirming or updating the status of the alert, which contributes to the refinement of models, making future predictions even more reliable. After confirmation, foresters can efficiently coordinate the clearing of dead wood or sanitary cuts of infected trees, preventing further damage and allowing for the protection and restoration of existing forests.
The SWIFTT platform will be commercialized by project partner Timbtrack. ‘SWIFTT is designed for scalability and collaboration, supporting foresters, managers, and authorities in different European countries. SWIFTT allows us to fight back against threats, protect ecosystem diversity, and help maintain resilient forests for future generations’, says Quentin d'Huart, CEO at Timbtrack.
Learn more about SWIFTT at: https://swiftt.eu/
The SWIFTT Project
SWIFTT is a teamwork effort from the consortium composed by AXA Climate (FR), Da Vinci Labs (FR), Equitable Earth (FR), Leibniz University Hannover (DE), Rigas Mezi (LV), Space Research Institute of Ukraine (UA), University of Bari Aldo Moro (IT), and Timbtrack (BE). They were responsible for developing the SWIFTT platform, alongside its web and mobile apps, for the analysis of satellite imagery and the creation and improvement of the AI models, as well as the collection of precise, time-stamped and geo-referenced forest data sets used as input.
‘Coordinating the SWIFTT project with such a committed European consortium has been an exceptional undertaking. Together, we have delivered a state-of-the-art platform leveraging Copernicus satellite data and advanced AI to equip forestry professionals with timely, actionable and robust tools. The results achieved reflect the strength of our collaboration, and I am confident this initiative will drive meaningful advancements in forest protection across Europe.’, highlights Ariane Kaploun, Head of Nature-based Solutions at AXA Climate and Horizon Europe SWIFTT’s project coordinator.
The consortium was awarded a highly competitive grant in the Horizon Europe funding programme, under the topic 'EGNSS & Copernicus applications fostering the European Green Deal' managed by EUSPA. The partners received a cumulative €2.8M grant from the EUSPA/European Commission between 2022 and 2026.
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