According to the forecast, in future the number of storms in Latvia is going to increase. The wind and the snow are risk factors influencing damages of forests; the least tolerant species against wind damages is Picea abies (L.) Karst. It is impossible to avoid the damages caused by weather conditions – windbreaks, windthrows, snowbreaks, snow crushes and snowthrows in forests, since they reoccur in certain periods of time. The aim of the research was to analyze the impact of abiotic risk factors on the management of young Picea abies (L.) Karst. stands. Young stands of Norway spruce were researched in all regions of Latvia in 2011 and 2012. These stands were up to 40 years old. In total, 75 stands were measured and surveyed, and 257 sample plots were arranged, where the following damages were identified: frost damages, snow crushes, snowbreaks, snowthrows, windfall and windthrows. The sample plot method was used. The intensity of damages is higher on drained soils. The linear correlation between occurrence and intensity of impact damages caused by abiotic factors was significant (r = 0.988 is greater than r0.05 = 0.253). There is no significant (p = 0.686 is greater than α = 0.05) difference between the intensity of impact damages caused by abiotic risk factors in the stands with regular and irregular shapes of forest compartments. Irregular form forest plots have formed naturally, occurrence of abiotic factors there is 7.5% but the factor intensity – 6.7% and that is higher than in regular forest plots where abovementioned parameters reach 4.7% and 2.9%.

Yasso07 soil carbon model was used to estimate soil carbon balance in dry forest site types (6 site types in total) in Latvia and the results were compared with data from Biosoil2012 soil surveys. Litter input, chemical quality and climatic data are required to run the model. Three different scenarios were used for climate data input – steady climate, climate change + 0.025 °C annually and climate change + 0.05 °C annually. Forest mineral soil is a carbon sink for the whole modelled period - the years of 1990 – 2030. Under steady climate, the average carbon removal is 0.6 t CO2 haE-1 yrE-1, under climate change (+ 0.025 °C) scenario 0.4 t CO2 haE-1 yrE-1, but under climate change (+ 0.05 °C) scenario 0.3 t CO2 haE-1 yrE-1. CO2 removal at the beginning of the period (1990) was 0.35 – 0.38 t CO2 haE-1 yrE-1. Carbon stock modelled with Yasso07 is lower than estimated in Biosoil2012 soil surveys. Differences between modelled and Biosoil2012 results vary from 2 t C haE-1 in the poorest and 41 t CO2 haE-1 in the third poorest site type. Carbon stock modelled with Yasso07 increases from the poorest to the most fertile site type while Biosoil2012 shows an increase from the poorest to the third poorest, and a decrease from the third poorest to the most fertile site type. Underestimation and different trends between Yasso07 and measured carbon stock may be explained by inappropriate equations and models used to estimate non-woody biomass. It is necessary to improve accuracy of input data for non-woody biomass by elaborating national equations and models in order to include Yasso07 in the national GHG inventory.