Shifts in tree allometry in a tropical dry forest: implications for above-ground biomass estimation

Gustavo Ramírez-Ramírez, Luis Ramírez y Avilés, Francisco Javier Solorio-Sánchez, Jorge Augusto Navarro-Alberto, Juan Manuel Dupuy-Rada

Abstract


Background: Accurate estimations of aboveground biomass (AGB) based on allometric models are needed to implement climate-change mitigation strategies. However, allometry can change with tree size.

Questions: Does allometry in a tropical dry forest change with tree size? Does combining different allometric equations provide better AGB estimates than using a single equation?

Study site and dates: San Agustín Ejido, Yucatán, México, 2016.

Methods: Forty-seven trees of 18 species with 2.5 to 41.5 cm in diameter at breast height (DBH) were sampled. Stems and branches were sectioned, and samples were dried and weighed to estimate tree AGB. Segmented linear regression was used to evaluate changes in allometry between DBH, height and AGB. Different equations were tested for each size category identified, and the best models and model-combinations selected.

Results: A shift in the AGB-height relationship was found, defining two tree-size categories (2.5-9.9 cm and ≥ 10 cm in DBH), with the inflection point corresponding to the average canopy height (12.2 m). The best models were AGB = exp(-2.769+0.937ln(D2HPw)) for trees < 10 cm DBH and AGB = exp(-9.171+1.591lnD+3.902lnH+0.496lnPw) for trees ≥ 10 cm DBH (R2 = 0.85 and R2 = 0.92, respectively). The combination of these models produced more accurate AGB estimates than a single model or combinations involving regional models with larger sample sizes.

Conclusions: These results highlight the importance of locally-developed models and suggest changes in allometry and resource allocation: towards height growth for small trees, thereby reducing the risk of suppression, versus towards AGB growth for larger trees, thereby maximizing stability and resource acquisition.


Keywords


Allometric equations; growth; resource allocation; segmented regression; tree-size categories

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References


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