摘要
以崇明岛为研究区域,采用野外样方调查和实验室模拟相结合方法,研究崇明岛主要植被类型碳储量.结果表明:(1)崇明岛不同森林植被类型其碳储量是不同,从大到小的排序为水杉、柳杉,黑松等针叶树为主的植被,其次是阔叶树林,最后香樟林;(2)崇明岛的植被碳储量的分布有很大的空间差异性,主要分布在河流两岸、道路两侧以及居民区等;(3)崇明岛主要植被类型的碳储量为491 212.16 Mg,平均碳密度为18.70 Mg/hm2,低于中国和世界的平均水平;(4)根据本研究结果和存在的问题,就未来的发展方向进行讨论.
Abstract
In the context of global change, research on the terrestrial ecosystem carbon cycle has become a big trend. Due to human activities and the impact of urbanization, such native terrestrial ecosystem as Amazon is becoming less and less. On the contrary, such region as Chongming Island which has been seriously affected by human activities is getting more and more. In this study, the carbon storage of vegetation types in Chongming Island was studied based on an method combining field sampling survey and laboratory simulation. Firstly, stratified sampling method was used and randomly picked 234 sample plots with vegetation in Chongming Island; Secondly, biotic parameters (e. g. diameter at breast height DBH, tree height, etc. ) were investigated; Thirdly, the improved volume-derived biomass method was used to calculate the carbon storage of main vegetation types. The results showed that: 1 ) In Chongming island, the carbon storage among different forest type was different, coniferous forests ( e. g. , M. glyptostroboides, C. fortunei, and P. thunbergii ) had the higher carbon storage compared with the broadleaved forests ( e. g. , C. camphora). 2) The disparity of carbon storage in spatial distribution existed in Chongming Island, and vegetation carbon storage is mainly distributed in the river banks, both sides of roads, and residential areas. 3) The carbon storage of the main vegetation in Chongming Island is 491 212.16 mg, and mean vegetation carbon density is 18.70 mg/ha. And 4) the future work in this study area was explored based on this study results. Not only does this study provide a scientific method in studing peri-urban forest vegetation carbon issues, but also scientific data for building Chongming eco-island and managing "zero carbon emission" city.
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维普
万方数据