Abstract
AbstractLocal-level, bioclimatic regression models that relate stand characteristics (forest composition, height, site quality class and wood stocking) to site climate (temperature sums, base 5°C, and dryness index) were developed to predict the stand structure of dark-needled forest (Pinus sibirica and Abies sibirica) climax successions and their transformations in a changing climate over the Sayan mountain range in southern Siberia, Russia. The models explained up to 80% of the variation in forest growth and productivity characteristics. Productivity varied widely and depended on heat supply rather than moisture. Stand tree species composition depended on moisture: dark-needled species and light-needled tree species (P. sylvestris) were separated by a dryness index value of 1.0. Living phytomass was calculated from a wood stocking model. Tree heights and living phytomass were mapped over the mountain range under current climate conditions and a regional climate change scenario. The model predicts that total dark-needled forest phytomass will decrease by 17% in a warmed climate.
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