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Eco-anatomical characteristics of Sophora davidii leaves along an elevation gradient in upper Minjiang River dry valley

LI Fanglan1,2;BAO Weikai1;LIU Junhua1,2;WU Ning1   

  1. 1Chengdu Institute of Biology,Chinese Academy of Sciences,Chengdu 610041,China;2Graduate School of Chinese Academy of Sciences,Beijing 100039,China

  • Received:2005-01-11 Revised:2005-05-23 Online:2006-01-18 Published:2006-01-18

Abstract: This paper studied the ecoanatomical characteristics of Sorphora davidiileaves at the elevations of 1 650,1 750,1 850 and 1 950 m in the upper reaches of Minjiang River dry valley.The indices investigated were leaf length (LL),leaf width (LW),LL/ LW,leaf area,leaf thickness,leaf epidermal thickness,leaf palisade mesophyll thickness (P),leaf spongy mesophyll thickness (S),P/S,leaf cutin membrane thickness,leaf stomatal density and area,leaf epidermis cell density and area,and leaf pubescence length and density.The results showed that the leaves of S.davidii were elliptic,with an area 0.144~0.208 cm2 and a thickness 171.58~195.83 μm.The mesophyll was significantly differentiated into palisade and spongy.The thickness of palisade mesophyll was 69.83~ 82.42 μm,that of spongy mesophyll was 62.00~80.67 μm,and P/S was 1.14~1.01.Upper epidermal thickness was 14.03~15.33 μm,while lower epidermal thickness was 13.88~16.17 μm.The stomatal density,stomatal area,epidermis cell density,epidermis cell area,pubescence length,and pubescence density were 13.71~15.02 mm-2,249.86~280.43 μm2,160.54~178.43 mm-2,557.43~626.85 μm2,186.51~260.99 μm,and 18.29~32.27 mm-2,respectively.With increasing elevation,the leaf area,leaf thickness,palisade mesophyll thickness,spongy mesophyll thickness,stomatal area,epidermis cell area and pubescence density were increased,while cutin membrane thickness,epidermis cell density,pubescence length,and stomatal density were decreased.There was no significant difference in LL/LW,P/S,epidermal thickness and stomatal density along the elevation gradient.

Key words: vegetation type, regression model., soil nutrient, spatial prediction, Kriging