Background: Dry tropical forests in arid lands cover large areas in Brazil, but few studies report the total biomass stock showing the importance of height measurements, in addition to applying and comparing local and pan-tropical models of biomass prediction for the domain of trees and shrubs found in that environment. Here, we use a biomass data set of 500 trees and shrubs, covering 15 species harvested in a management plan in the state of Pernambuco, in Brazil. We seek to develop local models and compare them with the equations traditionally applied to dry forests - showing the importance of tree height measurements. Due to the non-linear relationships with the independent variables of the tree, we used a nonlinear least squares modeling technique when adjusting models, we adopted the cross-validation procedure. The selection of the models was based on the likelihood measures (AIC), total explained variation (R2) and forecast error (RSE, RMSE and Bias).
Results: In summary, our above-ground biomass data set is best represented by the Schumacher-Hall equation: exp [3.5336 + 1.9126 × log (D) + 1.2438 × log (Ht)], which shows that height measurements are essential to estimate accurately biomass. The biggest prediction errors observed when testing pan-tropical models in our data demonstrated the importance of developing new local models and indicated that careful considerations should be made if generic “pantropical” models without height measurements are planned for application in dry forests in Brazil.
Conclusions: Thus, local equations can be used for carbon accounting in REDD + and sustainable incentive projects that initiate the development of dry forests and assess ecosystem services.