Allometric models for liana aboveground biomass in old-growth and secondary tropical forests of Tanzania

Lianas are common in tropical forests, where they influence forest dynamics, thus impacting the global carbon sink, with implications for climate change mitigation. Despite their increasing competitiveness with trees at the global scale, robust measurements of liana aboveground biomass (AGB) have been limited. Here we use data from destructive sampling to develop two separate allometric equations for estimating liana AGB from stem diameter in old-growth (n =15 lianas) and secondary forests (n =22 lianas). We compared estimates of AGB using our equations for 3141 lianas (≥1 cm diameter) in Tanzania’s Kilombero Valley against estimates from previously published equations in other tropical regions. Our equations demonstrated stronger correlations be tween diameter and destructively measured AGB, than those from previously published equations (R2 = 0.86–0.89, versus R2 =0.82–0.88). Across all stems, the average stem-level liana AGB estimated using the equation for old-growth forests was 52 % higher than that estimated by the equation for secondary forests, showing that lianas have lower biomass per unit diameter in forests impacted by disturbance. In such forests, liana stems are damaged, deformed, or cannot reach maximum height due to reduced structural support. At the scale of the forest stand, our equations estimated a mean liana AGB of 3.25 Mg ha 1 (95 % Confidence Interval: 1.52–6.96) in old-growth forests and 10.19 Mg ha 1 (5.91–17.64) in secondary forests. These estimates roughly
aligned with estimates from other equations, although there was considerable variation. Depending on the equation used, mean stand-level estimates of liana AGB ranged from 2.49–9.76 Mg ha 1 in old-growth forests and 10.19–20.74 Mg ha 1 in secondary forests. Our findings show the variability in liana allometry and AGB with disturbance and successional stage, further underscoring a need for caution when comparing estimates of liana biomass across studies and regions.

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