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How do leaf functional traits influence above-ground tree carbon in tropical hill forests of Bangladesh?
被引:0
|作者:
Khan, Ariful
[1
,2
]
Karim, Md Rezaul
[1
,3
]
Arfin-Khan, Mohammed A. S.
[1
]
Saimun, Md. Shamim Reza
[1
]
Sultana, Fahmida
[1
,4
]
Mukul, Sharif A.
[5
,6
,7
]
机构:
[1] Shahjalal Univ Sci & Technol, Dept Forestry & Environm Sci, Sylhet 3114, Bangladesh
[2] North South Univ, Dept Environm Sci & Management, Dhaka 1229, Bangladesh
[3] Univ Toronto, Inst Forestry & Conservat, John H Daniels Fac Architecture Landscape & Design, 33 Willcocks St, Toronto, ON M5S 3B3, Canada
[4] Swansea Univ, Fac Sci & Engn, Dept Biosci, Singleton Pk Campus, Swansea SA2 8PP, Wales
[5] United Int Univ, Dept Environm & Dev Studies, Dhaka 1212, Bangladesh
[6] Univ Sunshine Coast, Trop Forests & People Res Ctr, Maroochydore, Qld 4556, Australia
[7] Florida Int Univ, Dept Earth & Environm, Miami, FL 33199 USA
关键词:
Carbon dynamics;
Forest management;
Functional traits;
Tree carbon;
Aboveground biomass;
Tropical forest;
Ecological adaptation;
GOOD PREDICTORS;
GROWTH-RATES;
ECOSYSTEM;
BIOMASS;
SENSITIVITY;
ALLOCATION;
HANDBOOK;
CLIMATE;
SOIL;
D O I:
10.1016/j.ecolind.2025.113131
中图分类号:
X176 [生物多样性保护];
学科分类号:
090705 ;
摘要:
Plant leaf functional traits significantly influence carbon cycling in tropical forests, though the relationships between these traits and carbon stocks are complex. The present study investigates the role of leaf functional traits, i.e., specific leaf area (SLA), leaf dry matter content (LDMC), leaf width, and leaf thickness-on aboveground tree carbon (AGTC) stocks in two forest protected areas (PA) in northeast Bangladesh: Khadimnagar National Park (KNP) and Rema Kalenga Wildlife Sanctuary (RKWS). Data were collected from 110 plots, comprising 60 in RKWS and 50 in KNP. We observed that the community-weighted mean (CWM) leaf trait values were predominantly higher in the southwestern regions of KNP, while in RKWS, they were primarily distributed in the northern or southern regions. The results revealed that, at the landscape level, CWM-leaf width (R-2 = 0.10, P < 0.01) had a significant effect on AGTC. In site-specific analyses, CWM-leaf thickness (R-2 = 0.25), CWM-leaf width (R-2 = 0.10), and CWM-SLA (R-2 = 0.17) had significant (p < 0.05) negative effects on AGTC in KNP. However, in RKWS, only CWM-leaf width (R-2= 0.015, P < 0.01) significantly affected AGTC, while other CWMleaf traits showed no significant impact. Additionally, the effects of two common environmental variables-solar radiation and mean annual temperature (MAT)-were significant (p < 0.05) predictors of AGTC at the landscape level but not at the site level. The total carbon stock in RKWS was 1.98 % higher than in KNP per hectare, with species-specific carbon content varying across the landscape. Notably, Chukrasia tabularis showed the highest carbon content (31.57 t ha(- 1)). These findings highlight significant spatial variability in leaf functional traits and AGTC distribution across the two forests. This study enhances our understanding of how leaf functional traits influence AGTC stocks, underscoring the importance of localized investigations for global climate change mitigation efforts and supporting sustainable forest management in Bangladesh.
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