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Simulation and Analyses of Landscape Scenario in Xiaokelan Forest Region of Altai Mountains in Xinjiang

新疆阿尔泰小克兰林区景观情景模拟分析


利用从北美引进的景观情景分析探索技术(TELSA), 对小克兰林区景观变化进行无干扰和5种经营管理情景模拟,并分析影响景观变化的因子。结果表明:在无干扰情况下,牧草地和未利用地在80年内仍是该区域的主要景观类型,新疆落叶松林仍是主要的乔木景观类型; 对5种经营管理情景的模拟分析可以清楚地表示出景观类型、面积、林龄组成、更新方式等的变化,结果展示的可视化程度较高; 对影响景观变化的不利因子按重要性排序为放牧打草(36.50%)>火干扰(28.76%)>病虫害(23.68%)>风干扰(6.48%)>游憩践踏(4.58%); 有利因子按重要性排序为封山育林(28.92%)>人工促进天然更新(23.94%)>退牧还林或人工造林(17.81%)>防火(14.04%)>病虫害防治(11.00%)>枯倒木清理(4.29%)。

Based on data from forest relief maps and field investigations, landscape scenarios in Xiaokelan forest region of Altai Mountains in Xinjiang were analyzed by using the TELSA (tool for exploratory landscape scenario analyses) and VDDT (vegetation dynamics development tool), which were introduced from North America. Five different simulation scenarios representing 5 different management approaches were established and analyzed by integrating disturbances from nature and human, and management treatments. In scenarios without disturbance, the pastures and unused lands were the main landscape types in this area, and Larix sibirica forests predominated in the tree landscape type during the simulated period of 80 years. The TELSA can successfully and clearly simulate the changes in landscape type, area, age composition, regeneration manner, and the simulated result has relatively higher visibility. The relative importance of adverse interference factors on landscape dynamics changes was sorted as following: grazing (36.50%) > fire (28.76%) > diseases and insect pests (23.68%) > wind (6.48%) > trampling and recreation (4.58%). The importance of positive interference factors on landscape dynamics changes was sorted as following: closing the land for reforestation (28.91%) > natural regeneration with artificial promotion (23.94%) > returning grazing land to forest and reforestation (17.81%) > fire prevention (14.04%) > disease and insect pest controlling (11.00%) > cleaning of fallen wood (4.29%). We believe that TELSA can be used in the forest regions which are similar to the Xiaokelan forest region in China, and our simulating results would provide a guide for developing management plans and practice in this area.


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