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Threedimension structure model of the costal Metasequoia glyptostroboides shelterbelts.

ZHANG Lei1, ZHANG Peng1, WANG Hua2, ZHOU Xin-hua3, YU Mu-kui1, WU Tong-gui1*#br#   

  1. (1 East China Coastal Forest Ecosystem Longterm Research Station, State Forestry Administration of China; Costal Forest Research Center, Research Institute of Subtropical Forestry, CAF, Hangzhou 311400, China; 2 Dongtai City Forestry Center, Dongtai 224200, Jiangsu, China; 3 Campbell Scientific, Inc., Logan, USA UT 84321).
  • Online:2017-04-10 Published:2017-04-10

Abstract: In order to clarify the structure features of Metasequoia glyptostroboides shelterbelts and improve the prediction accuracy of windbreak effect, we measured the vegetative surface area and volume of the trunks, branches and leaves and established the threedimensional structure model of M. glyptostroboides stands. The results showed that the vegetative surface area density ranged from 0.0012 to 3.4857 m2·m-3, and the cubic density ranged from 0.000002 to 0.012397 m3·m-3. Moreover, the crown shape and growth status were closely related with the shelterbelt structure. And the structure was heterogeneous in space: the surface and volume of branches and leaves reached a maximum value at the middle of the crown, but for the trunk, they gathered at the lower part. Meanwhile, the vegetative surface area density changed with the shapes of trunks, braches and leaves. The trunk had big volume (accounting for 75.28% of the total volume) but less vegetative surface area (accounting for 5.57% of the total surface area), the leaves had big surface area (accounting for 78.39% of the total surface area) but less volume (accounting for 3.87% of the total volume). The ratio of surface to volume was ranked in the order of leaves (20.23) > branches (0.77) > trunks (0.07). Compared with previous studies, our model could describe the structure much more comprehensively, which was much closer to the real structure of the shelterbelts. Additionally, owing to the different influences of wind, each component had different aerodynamic effects. Thus, using both vegetative surface area density and cubic density to parameterize the shelterbelts structure could reflect the different effects of each component on wind and better exhibit the aerodynamic effect of the shelterbelts.

Key words: sequential indicator simulation method, soil heavy metals, zoning, farmland, risk identification