• Energy Research

Process-based models and empirical modelling techniques are frequently used to (i) explore the sensitivity of tree growth to environmental variables, and (ii) predict the future growth of trees and forest stands under climate change scenarios. However, modelling approaches substantially influence predictions of the sensitivity of trees to environmental factors. Here, we used tree-ring width (TRW) data from 1630 beech trees from a network of 70 plots established across European mountains to build empirical predictive growth models using various modelling approaches. In addition, we used 3-PG and Biome-BGCMuSo process-based models to compare growth predictions with derived empirical models. Results revealed similar prediction errors (RMSE) across models ranging between 3.71 and 7.54 cm2 of basal area increment (BAI). The models explained most of the variability in BAI ranging from 54 % to 87 %. Selected explanatory variables (despite being statistically highly significant) and the pattern of the growth sensitivity differed between models substantially. We identified only five factors with the same effect and the same sensitivity pattern in all empirical models: tree DBH, competition index, elevation, Gini index of DBH, and soil silt content. However, the sensitivity to most of the climate variables was low and inconsistent among the empirical models. Both empirical and process-based models suggest that beech in European mountains will, on average, likely experience better growth conditions under both 4.5 and 8.5 RCP scenarios. The process-based models indicated that beech may grow better across European mountains by 1.05 to 1.4 times in warmer conditions. The empirical models identified several drivers of tree growth that are not included in the current process-based models (e.g., different nutrients) but may have a substantial effect on final results, particularly if they are limiting factors. Hence, future development of process-based models may build upon our findings to increase their ability to correctly capture ecosystem dynamics.

Global warming is most pronounced at high latitudes where temperatures increase twice as fast as the global average. Boreal forest growth is generally limited by low temperatures, so elevated temperature is supposed to enhance biomass production and carbon sequestration. A large amount of evidence has recently shown inconsistent responses of tree growth derived from annual tree rings to increasing temperature. We studied Siberian spruce growth in the remote and isolated Putorana Mts, Western Siberia in populations at its natural distribution limit. Tree ring cores were sampled along vertical transect in 100, 200 and 350 m a.s.l. as the aim was to identify the tree growth rate at different altitudes. Detailed sampling site descriptions served to identify possible factors controlling the growth rate in extremely heterogeneous environments. Monthly climate data for the period 1900–2020 were extracted from the gridded CRU database. Tree ring chronologies confirmed long-lasting limited growth, and despite high year-to-year ring width variability, synchronous growth at vertical study sites dominantly controlled by climate. The positive tree ring growth response to summer temperature was significant for most of the 20th century but dramatically changed in recent decades, when unusually warm summers were reported. There was no, or even a negative growth rate correlation with precipitation, which indicates a sufficient water supply at the study sites. Elevated temperature in this region with a continental climate might turn the study localities to water-limited areas with many negative consequences on tree growth and related ecosystem services.

This study focused on the responses of soil microorganisms to different management regimes on disturbed windthrow areas. Microbial parameters potentially serving as indicators of environmental changes within a long-term monitoring of forest development after large-scale disturbance events were assessed. Basal and substrate-induced respiration, N mineralisation, catalase activity, microbial biomass as well as functional diversity based on Biolog assay were determined in soil samples from three disturbed plots and an undisturbed reference plot in the Tatra National Park (Slovakia) since 2006. A relative congruence of inter-annual trends of microbial activity indicators at all plots results from a common response of microbiota to changes of climate at the landscape level after forest stands were destroyed. While catalase activity and functional diversity proved to be useful indicators of temporal trends, microbial biomass seems to reflect different management regimes at the disturbed plots.

The global forest carbon (C) stock is estimated at 662 Gt of which 45% is in soil organic matter. Thus, comprehensive understanding of the effects of forest management practices on forest soil C stock and greenhouse gas (GHG) fluxes is needed for the development of effective forest-based climate change mitigation strategies. To improve this understanding, we synthesized peer-reviewed literature on forest management practices that can mitigate climate change by increasing soil C stocks and reducing GHG emissions. We further identified soil processes that affect soil GHG balance and discussed how models represent forest management effects on soil in GHG inventories and scenario analyses to address forest climate change mitigation potential. Forest management effects depend strongly on the specific practice and land type. Intensive timber harvesting with removal of harvest residues/stumps results in a reduction in soil C stock, while high stocking density and enhanced productivity by fertilization or dominance of coniferous species increase soil C stock. Nitrogen fertilization increases the soil C stock and N2O emissions while decreasing the CH4 sink. Peatland hydrology management is a major driver of the GHG emissions of the peatland forests, with lower water level corresponding to higher CO2 emissions. Furthermore, the global warming potential of all GHG emissions (CO2, CH4 and N2O) together can be ten-fold higher after clear-cutting than in peatlands with standing trees. The climate change mitigation potential of forest soils, as estimated by modelling approaches, accounts for stand biomass driven effects and climate factors that affect the decomposition rate. A future challenge is to account for the effects of soil preparation and other management that affects soil processes by changing soil temperature, soil moisture, soil nutrient balance, microbial community structure and processes, hydrology and soil oxygen concentration in the models. We recommend that soil monitoring and modelling focus on linking processes of soil C stabilization with the functioning of soil microbiota. This review has been supported by the grant Holistic management practices, modelling and monitoring for European forest soils – HoliSoils (EU Horizon 2020 Grant Agreement No 101000289) and the Academy of Finland Fellow project (330136, B. Adamczyk). In addition to the HoliSoils consortium partners, Dr. Abramoff contributed on this study and her work was supported by the United States Department of Energy, Office of Science, Office of Biological and Environmental Research. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the United States Department of Energy under contract DE-AC05-00OR22725.