Biology subjects

Heikkinen, J.

Publications and source records attributed to Heikkinen, J..

3 recordsLinked to original sources

bioRxiv2025

Rot or not? Uncovering the spatial patterns and drivers of Norway spruce root rot with harvester data

Root rot is a major problem for forestry, leading to reduced timber quality, growth losses, and increased disturbance risks. Harvester data provides a promising source of information for improving the knowledge on the root rot distribution. Here, we used harvester data (1) to map the risk of spruce root rot in southern and central Finland, and (2) to understand the drivers of the spatial patterns in rot occurrence. First, we built a statistical model predicting the percentage of stems affected by root rot on stand-level. To train the model, we used an extensive set of harvester data, containing 10,402 clear-cut forest stands, where the presence of root rot was recorded for each cut tree using an algorithm based on bucking patterns (i.e., cutting of the stem into different log assortments) recorded by the harvester. The model consisted of two parts, a fixed component describing the effects of different drivers of root rot, and a spatial random component describing the spatial patterns not explained by the fixed part of the model. The fixed part included forest and site attributes, landscape characteristics and proxies of forest-use legacies. The model was then used to map root rot risk, by predicting the probability of root rot occurrence using spatial data sets of the variables in the fixed part of the model, and the known rot status of locations in the data set for the random part of the model. Finally, the map was tested with an independent validation data, verifying its ability to identify the high-risk areas. Proxies of forest-use legacies, tree size and site fertility were found to drive the percentage of rot-affected stems in stands. The results quantify the root rot risk in Finland in higher detail than before and demonstrate the large potential of harvester data in informing about the risk of root rot in boreal forests.

ecology↗

bioRxiv2023

Harmonized decay classification for dead wood in Nordic national forest inventories

Dead wood quality is recorded as a biodiversity indicator and in estimating forest ecosystem carbon storage, using decay classification systems. In large-scale national forest inventories (NFIs), these systems are typically slightly different among countries, but harmonizing them would allows analyses over much broader scales and the use of larger data sets. Here, we developed a harmonized decay classification for the NFIs of Finland, Norway, and Sweden, using wood density as the harmonizing criterion. We sampled 441 pine, spruce, birch and aspen in different conditions and decay classes, measured their density and developed the harmonized classification for each species and dead wood type (standing and fallen dead wood). The assignments relied on minimizing within-class variance in wood density in the harmonized classes. Assigned into three (standing dead wood) and four (fallen dead wood) classes, the harmonization led to some losses of information, especially in the advanced decay stages in Finnish and Norwegian classifications. Importantly, the harmonized classes included slightly different decay classes from the national classifications, depending on the tree species and type. This is an advantage over the expert assessment that typically treat all species and types of dead wood the same way despite clear differences in decomposition pathways.

ecology↗

bioRxiv2022

Spatial patterns of biomass change across Finland in 2009 - 2015

Forest characteristics vary largely at the regional level and in smaller geographic areas in Finland. The amount of greenhouse gas emissions is related to changes in biomass and the soil type (e.g. upland soils vs. peatlands). Spatially accurate map data of forests and biomass changes could improve the ability to suggest optimal management alternatives for any patch of land, e.g. in terms of climate change mitigation. In our study, estimating and explaining spatial patterns of biomass change across Finland was the main interest. We analysed biomass changes on different soil and site types on forested land using the Finnish Multi-Source National Forest Inventory (MS-NFI) map layers of the 2009 and 2015 datasets. Silvicultural management and treatment units larger than individual pixels were created by automatic segmentation of the thematic maps. The segmented MS-NFI biomass maps of growing stocks, including above and below ground biomass resulted an average estimate of 77.7 tons ha-1 compared to the national forest inventory estimate of 76.5 tons ha-1 in 2015 for Finland. Forest soil type had a similar effect on average biomass in segmented MS-NFI and NFI data. Despite good regional and country-level results, at the segment level the biomass distributions were narrowed and averaging of biomass estimates was observed. Hence, biomass changes on segments can be considered only approximate values; also, those small differences in average biomass may accumulate when map layers from more than one time point are compared. MS-NFI classification results depend on the satellite images and field data used, causing variation in successive inventories. In addition, to avoid false biomass change observations due to the low growth rate of boreal forests, a six-year study period was set. A kappa of 0.44 was achieved for precision when comparing undisturbed and disturbed forest stands in the Global Forest Cover layer and MS-NFI segmented map, indicating the low ability of the global forest map to identify land cover changes for Finland. The segmented biomass maps provide a useful tool for forest owners to analyse carbon stock changes in their forests and how to affect the amount of carbon by forest management.

ecology↗