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Volume 2018 (2018), Article ID 1383482, 8 pages
Research Article

Linear Regression Model to Identify the Factors Associated with Carbon Stock in Chure Forest of Nepal

1Prince of Songkla University, Pattani Campus, Pattani, Thailand
2Nepal Institute of Health Sciences, Jorpati, Kathmandu, Nepal

Correspondence should be addressed to Ira Sharma; moc.liamg@321gsari

Received 11 November 2017; Accepted 26 February 2018; Published 3 April 2018

Academic Editor: Ravi K. Chaturvedi

Copyright © 2018 Ira Sharma and Sampurna Kakchapati. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Use of woody plants for greenhouse gas mitigation has led to the demand for rapid cost-effective estimation of forest carbon stock and related factors. This study aims to assess the factors associated with carbon stock in Chure forest of Nepal. The data were obtained from Department of Forest Research and Survey (DFRS) of Nepal. A multiple linear regression model and then sum contrasts were used to observe the association between variables such as stem volume, diameter at breast height, altitude, districts, number of trees per plot, and ownership of the forest. 95% confidence interval (CI) plots were drawn for comparing the adjusted carbon stocks with each of the factors and with the overall carbon stock. The linear regression showed a good fit of the model (adjusted = 83.75%) with the results that the stem volume (sv), diameter at breast height (dbh), and the number of trees per plot showed statistically significant ( value ≤ 0.05) positive association with carbon stock. The highest carbon stock was associated with sv more than 199 m3/ha, average dbh more than 43.3 cm/plot, and number of trees more than 20/plot, whereas the altitude, geographical location, and ownership had no statistical associations at all. The results can be of use to the government for enhancing carbon stock in Chure that supports both natural resource conservation and United Nations-Reducing Emission from Deforestation and Forest Degradation program to mitigate carbon emission issues.