Allometric Equations for Aboveground Biomass Estimation in Natural Forest Trees: Generalized or Species-Specific?

Accurate estimation of aboveground biomass (AGB) in tree–shrub communities is critical for quantifying forest ecosystem productivity and carbon sequestration potential. Although generalized allometric equations offer expediency in natural forest AGB estimation, their neglect of interspecific variability introduces methodological pitfalls. Precise AGB prediction necessitates resolving two biological constraints: phylogenetic conservation of allometric coefficients and ontogenetic regulation of scaling relationships. This study establishes an integrated framework combining the following: (1) phylogenetic signal detection (Blomberg’s K/Pagel’s λ) across 157 species’ allometric equations, revealing weak but significant evolutionary constraints (λ = 0.1249, p = 0.0027; K ≈ 0, p = 0.621); (2) hierarchical error decomposition of 9105 stems in a Mt. Wuyishan forest dynamics plot (15 species), identifying family-level error stratification (e.g., Theaceae vs. Myrtaceae, Δerror > 25%); (3) ontogenetic trajectory analysis of Castanopsis eyrei between Mt. Wuyishan and Mt. Huangshan, demonstrating significant biomass deviations in small trees (5–15 cm DBH, p < 0.05). Key findings resolve the following hypotheses: (1) absence of strong phylogenetic signals validates generalized models for phylogenetically diverse communities; (2) ontogenetic regulation dominates error magnitude, particularly in early developmental stages; (3) differential modeling is recommended: species-specific equations for pure forests/seedlings vs. generalized equations for mixed mature forests. This work establishes an error hierarchy: ontogeny > taxonomy > phylogeny, providing a mechanistic basis for optimizing forest carbon stock assessments.