Structure and allometry in tropical forests of Chocó, Colombia

- The use of harvested trees to assess the H:DBH relation is recommended.
- New AGB allometries for trees and palms are developed.
- Stem wood density can be estimated from branch wood density.
- At the plot scale, the increase of palms AGB means a decrease in total AGB.
- Local allometries help to quantify the likely bias of the pantropical ones.

The very wet forests of Chocó on the Pacific region of Colombia are unique in their plant diversity and function but are poorly known in aboveground structure and biomass (AGB). Conservation of these forests from widespread degradation in recent years has resulted in numerous REDD+ projects that require rapid assessment of the carbon stocks and changes. Here, we use a combination of inventory plots and harvested trees to develop allometric models and to quantify the variations of forest structure and carbon density across the Chocó region. We used 45 ha of inventory plots sampled in 15 1-ha permanent and 120 temporary 0.25-ha plots set under a stratified design. Likewise, we used 296 and 96 harvested trees and palms, respectively, with diameter ranging between 5 and 158.6 cm to develop the tree and palm allometry for AGB estimation. A model to estimate stem wood density from branch wood density was applied. Coarse woody debris (CWD) was also tallied and the dry mass stored quantified. We evaluated an alternative method to rapidly estimate wood density in tropical forests from sampling small branches. The total mean AGB in the 15 plot clusters was 239.8 ± 73.2 Mg ha−1. The mean percentage of AGB represented by trees, palms, and CWD was 88.6 ± 3.2, 3.1 ± 2.0, and 8.3 ± 3.0, respectively. Overall, our total AGB estimates are similar to those reported for wet lowland tropical forests but lower than those reported in tropical dry-seasonal forests. Our results emphasize on the advantage of employing height-diameter models developed from harvested trees to increase the accuracy of the AGB estimation in tropical forests. The wood density estimation was in good agreement with mean plot estimates made to reliable floristic inventories available for four 1-ha plots. This methodology can be further improved by including a sampling design based on tree diameter classes, which can help overcome the use of “static” databases built on species names. Finally, our findings support the use of the existing regional and pantropical allometries to estimate both tree height and the aboveground biomass in tropical wet forests, but emphasize the need of having more local and regional models to quantify the bias and improve the estimation of forest carbon density across different forest types.