Climate change induces multiple risks to boreal forests and forestry in Finland: A literature review.

Climate change induces multiple abiotic and biotic risks to forests and forestry. Risks in different spatial and temporal scales must be considered to ensure preconditions for sustainable multifunctional management of forests for different ecosystem services. For this purpose, the present review article summarizes the most recent findings on major abiotic and biotic risks to boreal forests in Finland under the current and changing climate, with the focus on windstorms, heavy snow loading, drought and forest fires and major insect pests and pathogens of trees. In general, the forest growth is projected to increase mainly in northern Finland. In the south, the growing conditions may become suboptimal, particularly for Norway spruce. Although the wind climate does not change remarkably, wind damage risk will increase especially in the south, because of the shortening of the soil frost period. The risk of snow damage is anticipated to increase in the north and decrease in the south. Increasing drought in summer will boost the risk of large-scale forest fires. Also, the warmer climate increases the risk of bark beetle outbreaks and the wood decay by Heterobasidion root rot in coniferous forests. The probability of detrimental cascading events, such as those caused by a large-scale wind damage followed by a widespread bark beetle outbreak, will increase remarkably in the future. Therefore, the simultaneous consideration of the biotic and abiotic risks is essential.

Bioclimate change across the protected area network of Finland.

Protected areas (PAs) are crucial in conserving biodiversity under climate change. In boreal regions, trends of biologically relevant climate variables (i.e., bioclimate) in PAs have remained unquantified. We investigated the changes and variability of 11 key bioclimatic variables across Finland during the period 1961-2020 based on gridded climatology. Our results suggest significant changes in annual mean and growing season temperatures over the entire study area, whereas, e.g., annual precipitation sum and April-September water balance have increased especially in the central and northern parts of Finland. We found substantial variation in bioclimatic changes over the 631 studied PAs; in the northern boreal zone (NB) the number of snow-covered days has decreased on average by 5.9 days between 1961-1990 and 1991-2020, while in the southern boreal zone (SB) the corresponding decrease has been 16.1 days. The number of frost days in spring with absent snow cover has decreased in the NB (on average -0.9 days) while increasing in the SB (0.5 days), reflecting the changing exposure of biota to frost. The observed increases in accumulation of heat in the SB and more frequent rain-on-snow events in the NB can affect drought tolerance and winter survival of species, respectively. Principal component analysis suggested that the main dimensions of bioclimate change in PAs vary across vegetation zones; for example, in the SB the changes are related to annual and growing season temperatures, whereas in the middle boreal zone the changes are linked to altered moisture and snow conditions. Our results highlight the substantial spatial variation in bioclimatic trends and climate vulnerability across the PAs and vegetation zones. These findings provide a basis for the understanding of the multifaceted changes the boreal PA network is facing and help to develop and direct conservation and management.

Correction: Mapping the probability of forest snow disturbances in Finland.

[This corrects the article DOI: 10.1371/journal.pone.0254876.].

Mapping the probability of forest snow disturbances in Finland.

The changing forest disturbance regimes emphasize the need for improved damage risk information. Here, our aim was to (1) improve the current understanding of snow damage risks by assessing the importance of abiotic factors, particularly the modelled snow load on trees, versus forest properties in predicting the probability of snow damage, (2) produce a snow damage probability map for Finland. We also compared the results for winters with typical snow load conditions and a winter with exceptionally heavy snow loads. To do this, we used damage observations from the Finnish national forest inventory (NFI) to create a statistical snow damage occurrence model, spatial data layers from different sources to use the model to predict the damage probability for the whole country in 16 x 16 m resolution. Snow damage reports from forest owners were used for testing the final map. Our results showed that best results were obtained when both abiotic and forest variables were included in the model. However, in the case of the high snow load winter, the model with only abiotic predictors performed nearly as well as the full model and the ability of the models to identify the snow damaged stands was higher than in other years. The results showed patterns of forest adaptation to high snow loads, as spruce stands in the north were less susceptible to damage than in southern areas and long-term snow load reduced the damage probability. The model and the derived wall-to-wall map were able to discriminate damage from no-damage cases on a good level (AUC > 0.7). The damage probability mapping approach identifies the drivers of snow disturbances across forest landscapes and can be used to spatially estimate the current and future disturbance probabilities in forests, informing practical forestry and decision-making and supporting the adaptation to the changing disturbance regimes.