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Spatial patterns of dominant tree species in sub-alpine Betula-Abies forest in West Sichuan of China.

MIAO Ning1;LIU Shi-rong1;SHI Zuo-min1;YU Hong2;LIU Xing-liang3   

  1. 1State Forestry Administration Key Laboratory of Forest Ecology and Environment, Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China;2Research Institute of Forestry, Chinese Academy of Forestry, China;3Sichuan Academy of Forestry, Chengdu 610081, China
  • Received:2009-03-05 Revised:1900-01-01 Online:2009-06-20 Published:2009-06-20

Abstract: Based on the investigation in a 4 hm2 Betula-Abies forest plot in sub-alpine area in West Sichuan of China, and by using point pattern analysi s method in terms of O-ring statistics, the spatial patterns of dominant specie s Betula albo-sinensis and Abies faxoniana in different age classes in study ar ea were analyzed, and the intra- and inter-species associations between these age classes were studied. B. albo-sinensis had a unimodal distribution of i ts DBH frequency, indicating a declining population, while A. faxoniana had a reverse J-shaped pattern, showing an increasing population. All the big trees of B. albo-sinensis and A. faxoniana were spatially in random at all s cales, while the medium age and small trees were spatially clumped at small scal es and tended to be randomly or evenly distributed with increasing spatial scale . The maximum aggregation degree decreased with increasing age class. Spatial as sociation mainly occurred at small scales. A. faxoniana generally showed pos itive intra-specific association, while B. albo-sinensis generally showed negative intra-specific association. For the two populations, big and small tre es had no significant spatial association, but middle age trees had negative spa tial association. Negative inter-specific associations of the two populations w ere commonly found in different age classes. The larger the difference of age cl ass, the stronger the negative inter-specific association.

Key words: Contingent Valuation Method, temporal stability, time interval, willingness to pay, urban river.