Welcome to Chinese Journal of Applied Ecology! Today is Share:

Chinese Journal of Applied Ecology ›› 2011, Vol. 22 ›› Issue (07): 1668-1674.

• Articles • Previous Articles     Next Articles

Community structure and distribution pattern of a natural secondary forest in Beigou forest farm.

WANG Peng, CHEN Li-hua, BIAN Xi-chen, WU Qiao-ying   

  1. College of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
  • Online:2011-07-18 Published:2011-07-18

Abstract: Taking the 4 hm2 fixed sampling plot in the Beigou forest farm of Weichang County in Hebei Province as test object, and by adopting the parameters (point pattern distribution, mingling, and size differentiation), this paper analyzed the community structure and distribution pattern of a natural secondary forest in the farm. There were eleven populations in the arbor layer of the forest, among which, Populus davidiana and Betula platyphylla had the obvious advantage in population density and basal area, being the dominant and constructive species of the arbor layer. Spatially, these two species all presented cluster modes remarkably, and competed each other greatly. The main accompanying species Larix principis-rupprechti and Acer truncatum also presented cluster modes, but the density and volume were significantly lower than the two dominant species’, not able to compete with the dominate species. Affected by the low mingling of dominant species, the average mingling of the whole stand was only 0.40, while the mingling of accompanying species generally presented moderate or high. The mean size differentiation of the whole stand was 0.49, and P. davidiana, B. platyphylla, L. principis-rupprechti, and Quercus mongolica were of dominance or sub-dominance in the spatial structural units, while the other accompanying species had no obvious dominance.

Key words: natural secondary forest, point pattern distribution, mingling, size differentiation, remote sensing., fractional vegetation cover (FVC), normalized difference vegetation index (NDVI), regression analysis, seasonal variation correction