Bamboo plantations are increasingly recognized as significant terrestrial carbon sinks, yet accurate estimation of biomass and carbon stocks requires species-specific, regionally validated allometric models.
Bambusa emeiensis L.C.Chia & H.L.Fung (ci bamboo) is among the most ecologically and economically important clump-forming bamboo species in
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Bamboo plantations are increasingly recognized as significant terrestrial carbon sinks, yet accurate estimation of biomass and carbon stocks requires species-specific, regionally validated allometric models.
Bambusa emeiensis L.C.Chia & H.L.Fung (ci bamboo) is among the most ecologically and economically important clump-forming bamboo species in southwestern China, but robust multi-regional allometric models are lacking. Using destructive sampling data from 127 culms across two major production areas—Sichuan Province (
n = 82) and Guizhou Province (
n = 45)—we developed additive biomass and carbon storage model systems enforcing mathematical additivity via nonlinear seemingly unrelated regression (NSUR). Allometric equations used diameter at breast height (
D), culm height (
H), and compound variables (
DH,
D2H) as predictors. Regional models achieved
Ra2 of 0.0879–0.8320 total relative error (
TRE): −0.99% to 0.04% for biomass and
Ra2 of 0.0923–0.8282 (
TRE: −1.01% to 0.03%) for carbon storage; culm and total aboveground models attained
Ra2 ≥ 0.52. Organ-level carbon content (40.79%–44.46%) was significantly lower than the intergovernmental panel on climate change (IPCC) default of 50% (one-sample
t-test, p < 0.01 for all organs), with Sichuan values exceeding Guizhou values (independent-samples
t-test, p < 0.01), indicating that use of the default would overestimate carbon stocks by 12%–22%. Cross-regional validation revealed prediction biases of up to ±19.24% when applying single-region models outside their training area, whereas the combined model held errors within ±11.36% for biomass and ±8.49% for carbon storage. External validation using 32 independent culms from Hunan, Yunnan, and Chongqing confirmed the robustness of the combined model (
TRE: −6.30% to 4.27%). A key limitation is that belowground biomass was not measured. The established models provide scientifically rigorous and practically applicable tools for regional carbon accounting of
B. emeiensis plantations under China’s national greenhouse gas inventory framework and for informing sustainable bamboo management planning, and demonstrate that species- and region-specific carbon fractions are essential for accurate carbon stock assessments.
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