Boreal forests &
climate resilience.

Abstract

This thesis explored how remote sensing and GIS can contribute to understanding the role of ectomycorrhizal fungi (EMF) in Scandinavian boreal forests and their relevance to climate change mitigation. The research focused on three connected studies: long-term forest and tree-species change in Trysil, Norway; soil moisture resilience during extreme weather years in Trysil; and post-fire landscape recovery in Enskogen, Sweden. The project combined Landsat, Sentinel-1, Sentinel-2, LiDAR-supported data, ArcGIS Pro, SNAP, and classification and change detection methods to examine forest dynamics over time.

Across the case studies, the work showed that geospatial methods can support analysis of forest composition, resilience, and disturbance. The findings suggested that forest areas associated with EMF-linked systems may contribute to resilience under drought conditions, with 15.6% of the forest area showing significant soil moisture increase between 2006 and 2018. In the Enskogen fire study, the burn area reduced by 18.33% between 2018 and 2022 while non-burn area increased by 34.27%, indicating measurable recovery over time. The study also highlighted limitations related to spatial resolution and limited ground-truthing, and pointed to the value of future work using higher resolution data and more extensive validation.

1. Introduction

Boreal forests play a major role in climate regulation, biodiversity support, and carbon sequestration. As one of the largest forest biomes on Earth, the Scandinavian boreal region is especially important for understanding how forest ecosystems respond to climate change, disturbance, and long-term environmental stress. These forests also support a wide range of ecological interactions that are essential to forest health and stability.

A central focus of this study is ectomycorrhizal fungi. EMF form symbiotic relationships with the roots of woody plants, helping trees acquire water, nutrients, and minerals from the soil while receiving plant-derived carbon in return. Because of these relationships, EMF are closely linked to nutrient cycling, growth, resilience, and forest ecosystem function. Their possible role in strengthening forest response to drought, disturbance, and recovery makes them relevant to both conservation and climate mitigation research.

The study is positioned within a broader concern that current climate mitigation strategies in Scandinavian forestry often emphasise timber, species diversity, and carbon storage, but do not adequately account for the contribution of EMF and associated below-ground ecological systems. Remote sensing and GIS offer a way to investigate these relationships at landscape scale, even though direct mapping of fungal networks remains challenging. This thesis therefore explores how geospatial proxies and linked forest variables can be used to support understanding of EMF-related forest resilience.

2. Aim of the Study

The aim of this thesis was to investigate the potential role of mapping EMF-related forest dynamics in Scandinavian boreal forests for climate change mitigation. This was approached through three linked strands of analysis:

• mapping tree species distribution and associated EMF-linked forest patterns in Trysil over 26 years
• assessing soil moisture resilience during extreme weather years in Trysil
• examining the effects of wildfire disturbance and landscape recovery in Enskogen, Sweden

Together, these studies were designed to explore whether geospatial methods could reveal useful patterns related to forest resilience, ecological disturbance, and the wider management value of EMF-linked systems.

3. Theoretical Background

The thesis drew on several interconnected theoretical ideas. The first was symbiosis, which frames the mutual relationship between trees and ectomycorrhizal fungi. The second was biogeography, used to think about species distribution over space and time, including how forest composition changes across the study areas. The third was disturbance theory, which helps explain how forest systems respond to drought, fire, and other pressures. These were brought together within the broader framework of climate change mitigation and ecological resilience.

4. Methodology

The research was structured into three separate but connected studies. Each used remote sensing and GIS methods to investigate a different aspect of forest condition or response. The work relied on a combination of Landsat, Sentinel-1 SAR, Sentinel-2 multispectral imagery, LiDAR-supported data, national forest data, ArcGIS Pro, and SNAP. Classification, index generation, and change detection formed the core analytical methods throughout the project.

4.1 Study 1: Mapping EMF-Linked Forest Change in Trysil

The first study focused on Trysil, Norway, an extensive forested area in south-eastern Norway near the Swedish border. The region includes productive boreal forest, varied terrain, and protected old-growth areas, making it suitable for investigating long-term forest composition and potential EMF-linked patterns.

Landsat imagery from 1992, 2007, and 2016 was used alongside 2018 SatSkog and LiDAR-supported reference data. NDVI was calculated to identify vegetated and forested areas, then a thresholded dataset was classified using a Support Vector Machine approach. Training samples were prepared by visually interpreting Landsat and higher resolution reference data. The resulting classes included mixed forest, coniferous mixed forest, pine-dominated, spruce-dominated, and deciduous-dominated forest. These classes were then linked to an EMF association table to examine changes over time, both across the wider landscape and within protected areas.

4.2 Study 2: Soil Moisture Resilience During Extreme Weather Years

The second study also focused on Trysil, but shifted attention toward soil moisture dynamics and forest resilience during extreme weather years. The Normalized Difference Moisture Index (NDMI) was used as the principal indicator because it is a well-established remote sensing method for estimating moisture content in forested areas. Landsat imagery from 2006, 2010, and 2018 was combined with forest data from the National Forest Inventory and related Norwegian sources.

NDMI maps were generated for the selected years, followed by difference raster calculations to identify temporal change. These were reclassified into significant decrease, little to no change, and significant increase. The analysis then extracted resilient forest areas where moisture levels remained stable or increased over time. Zonal statistics were used to calculate the percentage of forest showing each change category.

4.3 Study 3: Forest Fire Impacts and Recovery in Enskogen

The third study examined the Enskogen wildfire in Sweden, a major 2018 forest fire event that affected approximately 25,000 hectares. This case study aimed to investigate post-fire change and recovery using both synthetic aperture radar and optical imagery. Sentinel-1 SAR was used to assess structural and surface change, while Sentinel-2 imagery supported vegetation analysis.

Sentinel-1 data was pre-processed in SNAP through standard steps including thermal noise reduction, calibration, terrain correction, and speckle filtering. Sentinel-2 imagery was processed in ArcGIS Pro. NDVI and MSAVI were calculated for pre-fire, post-fire, and later recovery periods, and change detection was used to compare vegetation conditions over time. This made it possible to examine both immediate disturbance and longer-term recovery patterns.

5. Results and Discussion

5.1 Study 1: Forest Composition and EMF-Associated Change

The first study showed substantial shifts in tree species distribution and associated EMF-linked patterns across the Trysil landscape over the 26-year period. Classification outputs suggested that forest composition did not remain static, and that changes in species distribution were reflected in corresponding changes to mapped fungi-association categories. Protected areas also showed notable variation between classes over time.

Within protected areas, some classes increased steadily while others rose sharply and then declined. For example, spruce-exclusive classes increased by 12.64% between 1992 and 2007 and by a further 31.22% between 2007 and 2016. Deciduous-exclusive classes showed a dramatic increase of 387.16% between 1992 and 2007 followed by a large decrease of 85.08% between 2007 and 2016. Ubiquitous classes declined strongly at first, then showed a modest increase in the later period. These patterns indicate changing forest composition and shifting ecological associations across the reserve landscape.

The broader value of this study lies in showing that geospatial techniques can support monitoring of long-term forest dynamics and provide a structured way of linking forest classes with ecological associations relevant to resilience and management. At the same time, the thesis acknowledged that Landsat resolution limits fine-scale accuracy and that future work would benefit from more extensive ground-truthing and higher-resolution data such as Sentinel-2 and LiDAR.

5.2 Study 2: Soil Moisture Resilience in Trysil

The second study identified important spatial differences in soil moisture response during the chosen extreme weather years. NDMI-based mapping showed that moisture conditions varied across the study area, with the highest values occurring in 2010 and the lowest in 2018. Difference maps and classified outputs highlighted where moisture decreased, remained stable, or increased over time.

The final classification showed that 54.0% of forest area experienced little to no change in soil moisture, 30.4% experienced a significant decrease, and 15.6% showed a significant increase between 2006 and 2018. These results were interpreted as evidence that some forest areas displayed resilience under drought-related stress, and that these areas may be especially relevant for future management and conservation planning.

The study proposed that understanding these resilient areas could support forest health planning and contribute to future work on how EMF-linked systems may influence resistance to climatic stress. However, it also recognised that NDMI is only an indirect indicator and cannot directly measure EMF resilience on its own. The relatively short time range also limits strong conclusions about long-term ecological change.

5.3 Study 3: Wildfire Disturbance and Recovery in Enskogen

The Enskogen study showed clear signs of disturbance and partial recovery across the post-fire period. SAR backscatter differences highlighted widespread immediate change after the fire and further change in subsequent years. Optical analysis using NDVI and MSAVI showed a decline in vegetation health after the 2018 event and partial, but incomplete, recovery by 2022.

NDVI values suggested healthier vegetation before the fire, lower vegetation condition directly after the event, and intermediate values during the recovery phase. MSAVI similarly showed that vegetation remained below pre-fire condition in the burn area several years later. Change detection outputs reinforced that the landscape had undergone major alteration and that recovery was spatially uneven.

The percentage comparison between 2018 and 2022 showed that burn area decreased from 43.403 km² to 35.4479 km², a reduction of 18.33%, while non-burn area increased from 93.2096 km² to 125.1647 km², an increase of 34.27%. This points to substantial recovery, while also indicating that recovery was incomplete and that some areas may require longer-term observation and restoration attention.

6. Interpretation

Taken together, the three studies suggest that GIS and remote sensing can contribute meaningfully to understanding forest resilience and ecological change in Scandinavian boreal systems. Although the project did not directly map underground fungal networks, it used forest composition, soil moisture, and post-disturbance recovery as linked geospatial pathways for exploring where EMF-related resilience may matter most.

The thesis therefore supports the idea that spatial analysis can help identify conservation-relevant patterns and strengthen future climate mitigation planning. It also shows that below-ground ecological processes deserve more attention in forestry and landscape research, particularly where resilience, carbon storage, and recovery are central concerns.

7. Limitations

The thesis identified several limitations. First, some of the imagery used, especially Landsat, may not provide enough spatial detail for precise fine-scale ecological interpretation. Second, limited access to extensive ground-truth data restricted the ability to validate classification outputs and ecological assumptions. Third, soil moisture and vegetation indices do not directly measure EMF presence or function, so the findings are necessarily interpretive rather than definitive. Finally, the time windows used in parts of the study, especially the disturbance analysis, were relatively short for understanding long-term ecological processes.

8. Conclusion

This thesis investigated how remote sensing and GIS can be used to explore forest change, ecological resilience, and climate-related disturbance in Scandinavian boreal forests through the lens of ectomycorrhizal fungi and associated forest systems. The research showed that geospatial methods can support analysis of long-term tree-species change, identify moisture-resilient forest areas, and track post-fire recovery.

The work contributes to understanding how forest composition, water dynamics, and disturbance response may relate to resilience in boreal systems. It also suggests that future climate mitigation and forest management strategies could benefit from paying greater attention to EMF-linked ecological processes. Further research using higher-resolution data, broader spatial coverage, and stronger ground validation would help develop this approach and improve confidence in the results.

9. Methods, Data, and Tools Summary

• ArcGIS Pro
• SNAP (Sentinel Application Platform)
• Landsat 5 and 8 imagery
• Sentinel-1 SAR
• Sentinel-2 multispectral imagery
• LiDAR-supported reference data
• National Forest Inventory and related Norwegian forest datasets
• NDVI, NDMI, and MSAVI indices
• Supervised classification and Support Vector Machine classification
• Raster differencing, zonal statistics, and change detection

These tools formed the analytical backbone of the three case studies in Trysil and Enskogen.

10. Selected References

A full academic reference list appears in the original thesis document. Selected references cited in the thesis include work on drought and tree mortality, forest-climate feedbacks, soil respiration, mycorrhizal ecology, forest disturbance, and remote sensing approaches to ecological monitoring. The uploaded PDF contains the full bibliography section.

11. Original Thesis PDF

The original uploaded thesis document can still be kept available as a PDF alongside this webpage version for readers who want the original academic formatting.

Open Original Thesis PDF