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Tree Distribution Pattern, Growing Stock Characteristics and Carbon Mitigation Potential of Different Forests Ecosystems in Kumrat, Hindukush Region of Northern Pakistan.
Author(s):
1. ADNAN AHMAD: Laboratory of Integrated Forest Management, School of Forestry, Beijing Forestry University, Beijing, 100083, ChinaShaheed Benazir Bhutto, University, Sheringal Dir Upper, KPK, Pakistan
2. QI-JING LIU: Laboratory of Integrated Forest Management, School of Forestry, Beijing Forestry University, Beijing, 100083, China
3. KHAN BAHADAR MARWAT: Shaheed Benazir Bhutto, University, Sheringal Dir Upper, KPK, Pakistan
4. SHER SHAH: Laboratory of Integrated Forest Management, School of Forestry, Beijing Forestry University, Beijing, 100083, China
5. MUHAMMAD AMIR: Laboratory of Integrated Forest Management, School of Forestry, Beijing Forestry University, Beijing, 100083, China
6. ABDUL MANNAN: Beijing Key Laboratory of Precision Forestry, Beijing Forestry, University Beijing, 100083, China
Abstract:
Using ground inventory and remotely sensed data, this study explored the tree distribution pattern, growing stock characteristics and carbon mitigation potential of different forests of the Hindukush region in Kumrat valley, of northern Pakistan. The results showed that forestland covered an area of 51.13% of the valley. Stem density varied between 243±55 to 585±221 ha-1. Tree height was found in the range of 3 m and 49.85 m among the different forests. The regression analysis between stem density and diameter showed a week correlation in Cedrus deodara (CD) and Abies pindrow forest (AP), but showed positive correlation in Pinus wallichiana (PW), mixed coniferous (MC), and open forest (OF). Tree basal area and stem volume ranged from 343.45±210.68 to 159.64±58.41 m2 ha-1 and 343.45±210.68 to 2160.4±974.91 m3 ha-1 respectively. The range of calculated tree biomass was between 244.06±153.25 and 1499.5±627.74 Mg C ha-1. The carbon values varied between 122.03±76.62 and 749.69±313.85 Mg C ha-1. The results showed that among the different forests, CD had the highest carbon mitigation potential and OF had the lowest carbon mitigation potential. Furthermore, our results showed that the values of stem volume, total tree biomass and carbon in each forest were highly correlated with the basal area. Additionally, our findings provide evidence that basal area is the best predictor of biomass carbon estimation in each forest that suggests the use of the basal area for biomass carbon estimation. This approach could considerably reduce both, financial and physical efforts in carbon inventory regarding the field data collection particularly over the extensive tract of underrepresented carbon forests in Pakistan.
Page(s): 2185-2194
Published: Journal: Pakistan Journal of Botany, Volume: 51, Issue: 6, Year: 2019
Keywords:
Kumrat forests , Remote Sensing , Carbon stock , Inventory
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