How do leaf functional traits influence above-ground tree carbon in tropical hill forests of Bangladesh?
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), lea...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X25000603 |
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| Summary: | 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 above-ground 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 (R2 = 0.10, P < 0.01) had a significant effect on AGTC. In site-specific analyses, CWM-leaf thickness (R2 = 0.25), CWM-leaf width (R2 = 0.10), and CWM-SLA (R2 = 0.17) had significant (p < 0.05) negative effects on AGTC in KNP. However, in RKWS, only CWM-leaf width (R2 = 0.015, P < 0.01) significantly affected AGTC, while other CWM-leaf 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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| ISSN: | 1470-160X |