Carbon Stock Estimation of Selected Subtropical Broad-Leaved Evergreen Scrub Forest

Aisha Sajjad, Shaheen Begum (), Muhammad Adnan, Gul-e-Saba Chaudhry (), Muhammad Ibrahim, Mehwish Jamil Noor, Asma Jabeen, Sofia Khalid, Shazia Iram, Yeong Yik Sung and Tengku Sifzizul Tengku Muhammad
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Aisha Sajjad: Department of Environmental Sciences, Fatima Jinnah Women University, Rawalpindi 46000, Pakistan
Shaheen Begum: Department of Environmental Sciences, Fatima Jinnah Women University, Rawalpindi 46000, Pakistan
Muhammad Adnan: Department of Botany, Kohat University of Science and Technology, Kohat 26000, Pakistan
Gul-e-Saba Chaudhry: Institute of Marine Biotechnology, Universiti Malaysia Terengganu, Kuala Tereangganu 21030, Malaysia
Muhammad Ibrahim: WWF-P, Islamabad 44000, Pakistan
Mehwish Jamil Noor: Department of Environmental Sciences, Fatima Jinnah Women University, Rawalpindi 46000, Pakistan
Asma Jabeen: Department of Environmental Sciences, Fatima Jinnah Women University, Rawalpindi 46000, Pakistan
Sofia Khalid: Department of Environmental Sciences, Allama Iqbal Open University, Islamabad 44000, Pakistan
Shazia Iram: Department of Environmental Sciences, Fatima Jinnah Women University, Rawalpindi 46000, Pakistan
Yeong Yik Sung: Institute of Marine Biotechnology, Universiti Malaysia Terengganu, Kuala Tereangganu 21030, Malaysia
Tengku Sifzizul Tengku Muhammad: Institute of Marine Biotechnology, Universiti Malaysia Terengganu, Kuala Tereangganu 21030, Malaysia

Sustainability, 2022, vol. 14, issue 18, 1-11

Abstract: This research estimates the carbon stock of the subtropical broad-leaved evergreen scrub forest of Lehtrar, a revenue estate of Kotli Sattian, Rawalpindi, Punjab, Pakistan. A total of six nested co-centric plots of 17.84 m 2 each were laid out in the forest, having two sub-plots of 5.64 m 2 and 1 m 2 each, for shrubs and litter, respectively. Stem density, tree height, diameter at breast height (DBH), total tree biomass, and total carbon stock were calculated. In each plot, parameters like latitude, longitude, aspect, slope, elevation, tree count, etc., were catalogued. The carbon value was calculated in pools such as aboveground biomass (AGB), belowground biomass (BGB), litter, shrubs, etc. The tree height was measured using Abney’s level and the diameter at breast height (DBH) with diameter tape, while factors such as volume, shrub mass, litter mass, total tree biomass, and total carbon stock were calculated by using standard formulas. Results showed Olea ferrugineae to be the most abundant tree species in the study area, followed by Acacia modesta . The total average DBH and height were calculated as 17.03 and 16.79, respectively, with the species Dalbergia sissoo having the greatest DBH value. The mean carbon stock came out to be 47.75 tons/ha, with plot number 3 having the highest value of carbon stock, owing to the greatest stem count. The results of the study were significant and reflected a rich stem density, rich biomass, and an adequate carbon stocking capacity. The scrub forests of the study area, being important carbon sinks, are prone to deforestation and forest degradation activities that need to be controlled by using proper forest management practices to keep their carbon sequestration ability intact, as suggested under various reducing emissions from deforestation and forest degradation (REDD initiatives of UNFCCC.

Keywords: carbon stock; scrub forest; Lehtrar; deforestation; biomass; REDD+ (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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