Browsing by Subject "Dead wood"

Trees play an important ecological role also after their death. Earlier studies have introduced various methods of modelling coarse woody debris (CWD). However, CWD models that would consider different types of CWD, and their decay class dynamics are lacking from the Finnish commercial forests. The aim of this study was to predict the development of CWD for UPM-Kymmene owned FSC-certified forests in Finland. For that purpose, models for simulating CWD dynamics in Finnish commercial forests were developed for Pinus sylvestris, Picea abies and hardwoods. Trees were classified to different decay classes based on their visual appearance and softness of the wood. The mean residence time of each decay class was used to develop transition matrix model for predicting the possibilities of transitions between different decay classes. In the generated model a tree can stay in the class m or move to classes m+1 or m+2 in a time frame of five years. In addition snags had a possibility to fall i.e. move to down woody debris pool. The results showed that within all the studied tree species, the half-life of snags was 15–20 years. Hardwood logs decomposed faster than softwoods: the half-life of softwood logs was 35–40 years and the half-life of hardwoods was about 25 years. In a hypothetical equilibrium state reached by a continuous CWD input, most snags were in early decay class, whereas most logs were in the advanced decay class. Volume and quality of future CWD in UPM-Kymmene owned FSC-certified forests was predicted, using their current CWD pool and future tree mortality predicted by the forest simulation system MELA. In these simulations, the volume of CWD increased in the future. At the end of the 50-year simulation period, the predicted volume of CWD was 5,9 m3 ha-1. Pinus sylvesris was the dominant CWD species and advanced decayed wood was dominant decay class. The simulation approach demonstrated here has much potential as a useful decision-making tool for CWD management in commercial forests. Incorporating these models into forest management planning could provide valuable information about the effects of management practices on CWD dynamics in commercial forests.