Local vs global allometric equations for mangrove biomass estimation: Evaluating multiple variables in mixed effects models using a global data compilation

Accurate estimation of mangrove biomass is a key component of the blue carbon economy and allometric equations are a cornerstone of methodological approaches to quantify carbon from plot to landscape scales. A perennial question facing investigators is whether global allometric equations can be applied to their region of interest, or whether trees need to be harvested to provide accurate local estimates. Further, it is not always clear which combinations of tree dimensions provide the most accurate estimates. We examined 16 different allometric equations for four tree measurements within a global data set for three common trans-Atlantic mangroves species. We used mixed effects models with site location and tree species modeled as random effects, and tree height, diameter at breast height (DBH), canopy diameter, and wood density as fixed effects. While the mixed effects model with the greatest number of parameters was the best performing model based on five different statistical measures with a mean error of 1.392 kg, the improvement over simpler models was marginal. Using just the DBH of each tree would only add an additional 380 grams of error per tree compared to the best performing model. These results provide qualified support for the use of global equations and can help subsequent investigators to prioritize data collection efforts.