Cherednikova Yu. S., Krasnoshchekov Yu. N. Forest Ecosystems of South-Western Pribaikalie: Contemporary Status and Mapping
How to cite: Cherednikova Yu. S., Krasnoshchekov Yu. N. Forest ecosystems of South-Western Pribaikalie: contemporary status and mapping // Sibirskij Lesnoj Zurnal (Siberian Journal of Forest Science). 2016. N. 3: 10–23 (in Russian with English abstract).
© Cherednikova Yu. S., Krasnoshchekov Yu. N., 2016
The spatial structure of the natural ecosystems in the South-Western Pribaikalie is considered. In mountain-belt arrangement ecosystems are divided into mountain taiga, dark- and light coniferous, sub-taiga-forest steppe and steppe. A special group assigned the ecosystems of the river valleys. Within Goloustnensky landfill 53 kinds of ecosystems are allocated. Depending on geomorphological and lithological structures within the mountain taiga dark coniferous belt – 12, in mountain taiga light coniferous – 18, subtaiga-forest-steppe – 8, steppe ecosystems are represented by 4 and 11 – are formed in the river valleys. The main factor destabilizing the normal functioning of forest ecosystems in South-Western Pribaikalie is fire. In the region, almost all the forests were subjected to varying degrees of fire. Forest Fund is presented along with a conditional not impacted by fire areas, large burned areas of different age and with different trends in their recovery. It was found that the litter grassroots-humus fires of low and moderate intensity without damaging the forest stand, allow it to maintain basic edificator role, but destroy the undergrowth and thereby violate the normal course of forest renewing process. Evaluation of anthropogenic disturbance of forest ecosystems by fires and final felling have been designed. Fragments of the maps of natural and anthropogenically disturbed ecosystems at a scale of 1:200 000 within the Goloustnensky forestry district of Irkutsk region are presented. Assessment and mapping of ecosystems serves as a base for the organization of monitoring of the state of ecosystems, as well as to predict possible changes in its economic activities.