Aboveground biomass estimation and carbon stock assessment along a topographical gradient in the forests of Manipur, Northeast India

被引:6
|
作者
Sharma, Kiran [1 ]
Saikia, Anup [1 ]
Goswami, Santonu [2 ]
Borthakur, Monjit [3 ]
机构
[1] Gauhati Univ, Dept Geog, Gauhati, India
[2] Govt India, Dept Space, Natl Remote Sensing Ctr, Hyderabad, India
[3] Omeo Kumar Das Inst Sci Change & Dev, Gauhati, India
关键词
Aboveground biomass; Carbon stock; Stand density; Topographical gradient; Sub-tropical forest; Remote sensing; NET PRIMARY PRODUCTIVITY; TROPICAL-FOREST; LAND-USE; TREE DIVERSITY; WOODY BIOMASS; PLANTATION FORESTS; WILDLIFE SANCTUARY; SPECIES-DIVERSITY; DECIDUOUS FORESTS; KASHMIR HIMALAYA;
D O I
10.1007/s12517-020-05398-4
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Forests act as a source and sink of carbon. Forest biomass has been extensively used for environmental modelling and carbon stock estimation. In recent decades, significant land use changes occurred in the Manipur valley, India, impacting biomass production and carbon sequestration potentials. To assess the trajectories of these changes and their impact on biomass, this study examined the effect of land use changes and altitude on aboveground biomass (AGB). Satellite data along with tree sampling were used to assess AGB and carbon stock. Between 1989 and 2016, forest area decreased by 68,245 ha and dense forest (DF) proportion declined from 19.3 to 5.2% with a total loss of 111,387 ha. Stand density declined from 498 to 178 trees ha(1). The maximum AGB stock (27.6 Mt) which lay in DF in 1989 declined by 74% in 2016. Lowland forests fared more poorly with an average AGB of 144.2 Mg ha(-1) DF and 46.5 Mg ha(-1) in open forests (OF). In highland forests, these varied from 212.6 Mg ha(-1) in DF to 52.5 Mg ha(-1) in OF. The maximum carbon stored occurred in 40-60 cm diameter at breast height (dbh) in highland DF and > 80 cm dbh in lowland DF. A positive correlation (R-2 = 0.544) existed between AGB and elevation. A non-linear relationship between AGB and elevation using the quadratic regression model, AGB = 11.5-0.03 x elevation + 0.0002 x elevation(2) was found to be best fit. Higher elevation inhibited the exploitation of forest resources and enhanced carbon sequestration potentials in Manipur's forests.
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页数:16
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