Biology subjects

Suvanto, S.

Publications and source records attributed to Suvanto, S..

5 recordsLinked to original sources

bioRxiv2026

Contrasting trends in forest growth and mortality of major European tree species under increasing climatic stress

Forests play a crucial role in mitigating climate change as primary terrestrial carbon sinks. While some studies suggest that global warming enhances forest productivity, a growing body of evidence highlights detrimental impact primarily driven by increased water stress. Yet the extent to which positive effects of climate change offset its negative impacts on tree species productivity remains unclear at large spatial extents. We assessed forest growth and mortality for the 21 most abundant tree species in Europe using National Forest Inventory data from more than 50,000 plots and 700,000 trees to disentangle the relative importance of climate and forest structure. Specifically, we examined how vapor pressure deficit (VPD) anomalies across species climatic edges and stand developmental stages affect forest growth and mortality occurrence and intensity (i.e. whether mortality occurred and the amount of basal area lost). Then, we aggregated the responses across species and separately for broad-leaved and needle-leaved species to assess whether forest growth and mortality differed between major functional groups. Although the importance of forest growth and mortality drivers varied markedly among species, climate had a stronger influence on mortality than on growth, particularly in needle-leaved species. Forest growth declined and mortality increased along VPD anomaly in most species and forests studied. Responses were most pronounced at arid species edges in early-stage broad-leaved forests and at wet edges in late-stage needle-leaved forests, where differences between functional groups were also highest. We evidence the need to parametrise species-specific models of forest growth and mortality across large spatial extents to better understand and predict effects of climate change on forest productivity. In addition, our results emphasize the importance of improving the understanding of forest mortality processes given the strong influence of climate on mortality, while also further studying vulnerable populations to climate change in arid edges of species distributions.

ecology↗

bioRxiv2025

Harvesting effects on forest condition indicators across Iberian forests: Implications for the EU Nature Restoration Regulation

O_LIForest degradation is posing a growing threat to biodiversity conservation, climate regulation and nature contributions to people worldwide. The EU Nature Restoration Regulation (NRR) recognise the need of healthy forests and has established indicators to assess the condition of forest ecosystems. Forest management practices, especially harvesting may contribute to improve these indicators by, for example, reducing tree density and promoting tree species diversification. C_LIO_LIHere, we assessed temporal trends in forest condition indicators (hereafter, indicators) across Iberian forests since the 80s and evaluated how harvesting occurrence and intensity modulated these trends. Using 46,354 plots from the Spanish Forest Inventory (1986-2022), we analysed trends in indicators depending on stand diversity (monospecific or mixed), protection status (protected or unprotected), origin of the stand (natural or planted), and biogeographical region (Mediterranean or temperate). C_LIO_LIOverall, indicators increased over time. Harvesting occurrence reduced the increases in aboveground carbon stocks, structural diversity, tree species diversity, and standing deadwood; however, it contributed to increase the proportion of native species in specific forest types. Medium to high harvesting intensity negatively impacted aboveground carbon stocks, while medium intensities increased tree species diversity but reduced the structural diversity. C_LIO_LISynthesis and applications. Our results suggest that indicators are increasing as stand develops in absence of disturbances such as harvesting. Tree harvesting cannot be considered as a silver bullet to achieve the objectives of the NRR, but it can contribute under certain conditions - specifically at low intensities for carbon stocks and at medium intensities for species diversity. The naturally positive trend of indicators underlines the need to establish thresholds values and minimum rates of changes that distinguish restoration outcomes from natural dynamics. Finally, our study also highlights the key role of forest inventories in monitoring forest condition over time and across diverse landscapes. C_LI

ecology↗

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↗

bioRxiv2020

Mapping the probability of forest snowdisturbances 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. 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 risks in forests, informing practical forestry and decision-making and supporting the adaptation to the changing disturbance regimes.

ecology↗

bioRxiv2019

High-resolution mapping of forest vulnerability to wind for disturbance-aware forestry and climate change adaptation

Windstorms cause major disturbances in European forests and forest management can play a key role in making forests more persistent to disturbances. However, better information is needed to support decision making that effectively accounts for wind disturbances. Here we show how empirical probability models of wind damage, combined with existing spatial datasets, can be used to provide fine-scale spatial information about disturbance probability over large areas. First, we created stand-level damage probability models with predictors describing forest characteristics, recent forest management history and local wind, soil, site and climate conditions. We tested three different methods for creating the damage probability models - generalized linear models (GLM), generalized additive models (GAM) and boosted regression trees (BRT). Then, the damage probability maps were calculated by combining the models (GLM, GAM and BRT) with GIS data sets representing the model predictors. Finally, we demonstrated the predictive performance of the maps with a large, independent test data, which shows that the damage probability maps are able to identify vulnerable forests also in new wind damage events (AUC > 0.7). Use of the more complex methods (GAM and BRT) was not found to improve the predictive performance of the map compared to GLM, and therefore we would suggest using the more simple GLM method that can be more easily interpreted. The map allows identification of vulnerable forest areas in high spatial resolution (16 x 16 m2 raster resolution), making it useful in assessing the vulnerability of individual forest stands when making management decisions. The map is also a powerful tool for communicating disturbance risks to forest owners and managers and it has the potential to steer forest management practices to a more disturbance aware direction. Our study showed that in spite of the inherent stochasticity of the wind and damage phenomena at all spatial scales, it can be modelled with good accuracy across large spatial scales when existing ground and earth observation data sources are combined smartly. With improving data quality and availability, map-based risk assessments can be extended to other regions and other disturbance types.

ecology↗